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2016 Dynamics of Natural Hydrocarbon Seeps in the Northern Gulf of Mexico Caroline Van Limbeek Johansen

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COLLEGE OF ARTS AND SCIENCES

DYNAMICS OF NATURAL HYDROCARBON SEEPS IN THE NORTHERN GULF OF MEXICO

By

CAROLINE VAN LIMBEEK JOHANSEN

A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy

2016 Caroline Johansen defended this dissertation on June 3, 2016. The members of the supervisory committee were:

Ian R. MacDonald Professor Directing Dissertation

Tarek Abichou University Representative

Bill Dewar Committee Member

Jeff Chanton Committee Member

Michael Abrams Committee Member

The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements.

ii I dedicate this thesis to Mother Earth. Thank you for the nature and nurture you provide. My hope is that one day the human species will collectively recognize that we need you. In the meantime, I’ll do my best to learn from you and advocate for you.

iii ACKNOWLEDGMENTS

First and foremost, I thank my advisor, Dr. Ian MacDonald. Thank you for the all the opportunities, thank you for your patience, thank you for believing in me, and thank you for your friendship. My PhD has been a fruitful and meaningful experience that I am honored and proud to have completed under your guidance.

I would also like to acknowledge my lab mates Samira Daneshgar Asl and Mauricio Silva Aguilera; for their support and becoming my lab family. Additionally I would like to thank my committee members for insightful discussion and guidance. Particularly Dr. Dewar, a mentor and listening ear both in my academic and personal life.

Finally, thank you to all colleagues at FSU and other Universities and Institutions that have been supporters, collaborators, and become friends throughout my PhD.

This research was made possible in part by a grant from The Gulf of Mexico Research Initiative, and in part by National Science Foundation Award (EF-0801741). Data are publicly available through the Gulf of Mexico Research Initiative Information & Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org (R1.x132.137:0011, R1.x132.137:0009, R1.x132.137:0028, R1.x132.137:0033, R1.x132.137:0010, R1.x132.137:0037, doi: 10.7266/N7M906N3).

iv TABLE OF CONTENTS

List of Tables ...... viii List of Figures...... ix Abstract...... xiv

1. INTRODUCTION...... 1

1.1 Introduction...... 1

1.2 Geological features in the Gulf of Mexico ...... 3 1.2.1 Formation of the Gulf of Mexico...... 3 1.2.2 Salt deposition and movement...... 4

1.3 Oil production in the Gulf of Mexico basin...... 6 1.3.1 Source rocks...... 7 1.3.2 Migration and pathways to seeps...... 9

1.4 Natural seeps ...... 10 1.4.1 Mud volcanoes...... 11 1.4.2 Brine pools...... 11 1.4.3 Gas hydrates...... 11 1.4.4 Carbonates...... 12 1.4.5 Chronic natural and anthropogenic oil discharges...... 12

1.5 Study location ...... 12

1.6 Thesis objectives...... 13

2. EQUIPMENT AND METHODS...... 15

2.1 Video Time Lapse Camera ...... 15 2.1.1 High Definition VTLC for deep sea time-lapse imaging...... 16 2.1.2 Autonomous and triggered event settings...... 18 2.1.3 Deployment and retrieval...... 18

2.2 Semi-automatic bubble counting method ...... 19 2.2.1 Pre-program run...... 22 2.2.2 Automatic bubble counting program ...... 23 2.2.3 Bubble algorithm ...... 24

v 3. BUBBLE RELEASE PROCESSES AT NATURAL HYDROCARBON SEEPS IN THE GULF OF MEXICO ...... 25

3.1 Introduction...... 25

3.2 Study Site...... 28

3.3 Methods ...... 29 3.3.1 Camera properties ...... 29 3.3.2 Camera deployments...... 30 3.3.3 Measuring bubble size ...... 31 3.3.4 Overview of image processing...... 33 3.3.5 Bubble counting algorithm ...... 35 3.3.6 Extrapolation...... 36

3.4 Results...... 36 3.4.1 Vent characteristics...... 36 3.4.2 Bubble measurements and rates...... 39 3.4.3 Pressure differential and bubble release ...... 40

3.5 Discussion...... 40 3.5.1 Considerations for long-term deployment ...... 40 3.5.2 Temporal variation of bubble release ...... 43 3.5.3 Bubble flow rate comparisons ...... 45

3.6 Conclusion ...... 46

4. A HYDROCARBON BUDGET FOR A GULF OF MEXICO NATURAL SEEP SITE: GC600...... 47

4.1 Introduction...... 47 4.1.1 Indications of fluid flow...... 49

4.2 Site Description ...... 50

4.3 Methods ...... 51 4.3.1 Faults and salt distribution...... 52 4.3.2 Subbottom blanking zones...... 52 4.3.3 Multibeam bathymetry and backscatter...... 53 4.3.4 Seafloor geomorphology...... 53 4.3.5 Bubble flares in water column ...... 54 4.3.6 Chemical analysis ...... 54

4.4 Results...... 56 4.4.1 Acoustic anomalies in seep zones...... 56 4.4.1.1 Seep domains ...... 56

vi 4.4.1.2 Seismic interpretation ...... 56 4.4.1.3 Backscatter and subbottom interpretation...... 57 4.4.1.4 Flares in water column...... 57 4.4.2 Seafloor fluxes ...... 57 4.4.2.1 In-flow: Hydrocarbons migrating from depth...... 61 4.4.2.2 Out-flow: focused bubble release ...... 62 4.4.2.3 Out-flow: diffusive hydrocarbon seepage...... 62 4.4.2.4 Out-flow: dissociative flux from exposed hydrates ...... 62 4.4.2.5 Additional flow ...... 63 4.4.3 Chemical analysis ...... 63

4.5 Discussion...... 65 4.5.1 Assumptions and uncertainties ...... 65 4.5.2 Migration from source rock ...... 67 4.5.3 Hydrate growth ...... 68 4.5.4 Provisional hydrocarbon budget ...... 68

4.6 Conclusion ...... 70

5. DESCRIPTIVE OVERVIEW OF METAZOANS IN TWO GULF OF MEXICO SEEP ZONES ...... 71

5.1 Introduction...... 71

5.2 Methods and importance...... 72

5.3 Results and discussion ...... 72

5.4 Conclusion ...... 79

6. CONCLUSIONS ...... 80

APPENDICES...... 83

A. VTLC DEPLOYMENT METADATA...... 83

B. MATLAB CODE FOR BUBBLE COUNTING ALGORITHM ...... 84

C. SUPPLEMENTAL FIGURES FROM CH. 4 ...... 90

References...... 96

Biographical Sketch...... 107

vii LIST OF TABLES

Table 3.1: VTLC deployment location, date, and autonomous settings. Date from Birthday Candles were still frame; all other data were HD video ...... 28

Table 3.2: Averages of bubble release rates for each site. Annual release in m3 yr-1 is at depth. Gas amount for Birthday Candles is not applicable...... 33

Table 4.1: List of objectives, instruments, and methods used to collect data. DOI for data are listed in acknowledgments...... 52

Table 4.2: Putative in-flow, out-flow, and relative sizes of each hydrocarbon pool ...... 60

Table 5.1: List of animals observed at visited seep sites ...... 73

Table A.1: Meta data for analyzed VTLC deployments ...... 83

Table C.1: Biomarker ratios (Ts/Tm, H29/H30, H31S/H31R, H32S/H32R, H30/Σ (H31-H35), C27α β β /C29α β β steranes, and C27β α /C29β α diasteranes) for Megaplume oil seep, Megaplume oil slick, Birthday Candles oil slick, Holstein crude oil, and Macondo crude oil (NIST2779). The results are expressed as average values from triplicate analysis ± the standard deviation...... 90

viii LIST OF FIGURES

Fig. 1.1: Formation of the Gulf ov Mexico in the Late Jurassic (Fig. source: http://media- 2.web.britannica.com/eb-media/45/136145-004-4E7735F7.jpg)...... 2

Fig. 1.2: Study location: Sigsbee escarpment in the Northern Gulf of Mexico, with detailed view of the mini basins and salt pillows visible in the bathymetry in the Sigsbee escarpment. The two stars indicate our two study sites: GC600 and MC118. Bathymetry courtesy of Bureau of Ocean Energy Management (BOEM)...... 3

Fig. 1.3: Present day water shed from the North American continent into the Gulf of Mexico. (Fig. source: http://flowergarden.noaa.gov/image_library/maps/gomwatershed.jpg)...... 5

Fig. 1.4: Deformation of salt with increased sediment deposition (Fig. source: https://en.wikipedia.org/w/index.php?curid=14244862)...... 5

Fig. 1.5: Succession of salt movement from the Late Jurassic to the present day. Present day Sigsbee escarpment is identifiable by black salt diapirs to the south (left). (Fig. source: Galloway, 2008)...... 6

Fig. 1.6: Major oil families in the Northern Gulf of Mexico. Yellow box represents the GC600 study site, blue box represents the MC118 study site (Fig. source: Hood et al. 2002)...... 7

Fig. 1.7: Biomarker analysis from oil samples of two separate seep sites stemming from the same Tithonian source rock (Fig. source: Cole et al. 2001) ...... 8

Fig. 1.8: Natural seep zone locations detected using satellite images. Approximately 914 seep zones detected (Fig. source: MacDonald et al. 2015)...... 9

Fig. 1.9: Schematic diagram showing the study focus from subbottom migration of hydrocarbons to the different processes at the seafloor (Fig. source: http://dynatog.whoi.edu/research/gas_hydrates/hyd_gas_ov.png)...... 10

Fig. 2.1: The VTLC system on deck of the R/V Atlantis after a 26 day recovery...... 15

Fig. 2.2. XD 1080 mini video camera (http://www.replayxd.com/product/1080-mini/) ...... 16

Fig. 2.3: The head and body of the VTLC built by Aquapix ...... 17

Fig. 2.4: VTLC attached to acoustic release lander camera at sea floor (MC118) ...... 17

Fig. 2.5: a MC118, Ruddyville deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background...... 20

ix Fig. 2.6: a GC600, Mega Plume 2012 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background...... 20

Fig. 2.7: a GC600, Mega Plume 2014 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background...... 21

Fig. 2.8: a GC600, Cigar Mound 2014 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background...... 21

Fig. 2.9: Example of default variables text file ...... 22

Fig. 2.10: Box entitled original is the difference image as seen in Fig. 2.4, 2.5, 2.6, and 2.7 and contour shows the contours applied with high/strict (Yellow), medium (cyan), and low/loose (magenta) thresholds...... 23

Fig. 3.1: Study sites MC118 (850 m deep) and GC600 (1200 m deep) off the coast of Louisiana are separated by 260 km. Rudyville vent is located at MC118. Birthday Candles and Mega Plume are located at GC600. Inset shows 3D rendering of sea floor and hydroacoustic signature of bubble plumes in the water column at GC600. The hydroacoustic data was collected on the R/V Falkor (cruise F006B), and processed in Fledermaus. Mega Plume is located to the NW and Birthday Candles approximately 1 km to the SE...... 26

Fig. 3.2. Camera positioned in front of vents. A Birthday Candles at GC600. B Rudyville at MC118. C 2 d deployment, Mega Plume at GC600. D 26 d deployment, Mega Plume at GC600...... 30

Fig. 3.3: Schematic depicting the image processing method. A This is the original image from which a counting region is determined and converted to gray scale. The cropped counting region is then subtracted from the consecutive image (B – C) to negate constant background and identify bubbles (shown here as bright spots D). To account for bubble size, motion blurring, and oil content, three thresholds (high, medium, and low) are assigned to the bubbles (E – F). The bubbles are counted and sub-sampled along 60 pixels in the counting region. The bubble count for each pixel (1-60) is summed across every frame in a clip, and then averaged to generate three values of bubble release at each threshold (high, medium, low) for one clip. This is repeated for each clip to create a time series of bubble release for the entire deployment time…...... 34

Fig. 3.4: Frame grabs of individual vents investigated in this study. A Birthday Candles at GC600. Frame grab from the camera where dark oily bubbles escape from ~ 38 individual tubes via a gas hydrate out crop. B Rudyville at MC118. Frame grab from this deployment shows bubbles are clear and gaseous escaping from ~ 17 small tubes of gas hydrate. Fish in the foreground was observed grazing on the bacteria mats that surround the vent. C and D Mega Plume at GC600. Oil stained gas hydrate is visible around the vent, and white mats on surrounding sediments expanded and retracted during deployment. C Mixed oily and gaseous bubbles escaped from the gas hydrate out crop with an area of ~ 4 X 11 cm. D White oval

x indicates an area where acute, episodic gas explosions would occur, lasting ~ 2 h. The bubble stream in the foreground was used for analysis...... 37

Fig. 3.5: Close up of bubbles depicting the difference between gaseous, mixed, and oily vent type...... 38

Fig. 3.6: Individual bubble size distribution of the three different classes of vents (oily, mixed, and gaseous). A smooth kernel distribution is used to fit the histogram, where n is the number of bubbles measured. Inset depicts a visual of the bubble size distribution in line with the measuring stick. Measuring stick shows ticks every 1 cm ...... 39

Fig. 3.7: Observed pressure and bubble release rates. All values have been de-trended by subtracting the mean and dividing with the maximum value to show the variance about zero. Additionally a low pass filter was administered to reduce noise for visualization in the graph. The dashed red line represents the low and high threshold values of bubble release, and the solid red line is the results for the medium threshold. A Mega Plume, short deployment of 48 h. B Mega Plume 26 d deployment. C Rudyville, 5 d deployment...... 41

Fig. 3.8: The power spectral density for Rudyville at cph. The peak for both Bubble Release and Pressure (dbar) occurs at 0.04 cph (0.98 cpd)...... 42

Fig. 4.1: a Study location, Gulf of Mexico, GC600. b shows the two seep domains Mega Plume (MP) and Birthday Candles (BC). The entire seep zone extends over 2 km. c 3D rendition of the flares detected at both seep domains MP and BC. Additionally there is an example of how the flares show up during multibeam mapping in the triangular swath beam. This is used to determine the geolocation of the flares...... 50

Fig. 4.2: Spatial clustering of bubble flare detected by EM302 and EM122 swathmapper. a Raw data of all detected flares from R/V Falkor (expedition F006b) and R/V Atlantis (expedition AT26-13). b Pair-wise distances between each detected plume. c Resulting clusters shown as separate colors (21 total). d Geographic centroids of each cluster (colored points) overlain on detected plumes (grey points). a, c, and d axes are in UTM meters, zone 15N...... 55

Fig. 4.3: a Bathymetry of GC600 seep domain, Mega Plume is the mound to the NW and Birthday Candles is the mound to the SE. Black contour outlines blanking zone in subottom data. Green points show cluster centroids. Stars are positions of individual vents ground-truthed with VTLC records and AUV and submersible surveys. b Backscatter data with blanking contour outlined to show match. Red points show flares detected in acoustic mapping for each survey line; green points are flare cluster centroids ...... 58

Fig. 4.4: Geophysical structures in the GC600 region. a Seafloor amplitude map. Red line shows seismic traverse for seismic section shown in b. Red polygons delineate interpreted faults on the seafloor amplitude map. b Seismic section of the traverse in a. b shows inferred migration pathway of oil and gas from the source rock (Cretaceous (~11 kmbsf) or Smackover (14 kmbsf). c Overview (in the time domain) of the traverse in d. Blue show interpreted faults. Discontinuous Bottom Simulating Reflector (BSR) identified at approximately 305 m. d seafloor amplitude map, polygons depicting acoustic amplitude anomalies caused by the fault scarps. e Grid of the base of the salt coverage. The salt void is the same as the ones seen in a and b ...... 58

xi Fig. 4.5: a Grid showing base of the blanking zone determined with a closed contour of 1 m intervals. b chirp line of corresponding line in a (A-A’). Red arrows show depth from seafloor to blanking area...... 59

Fig. 4.6: Schematic of all the different methane fluxes for each identified “pool” at both Birthday Candles and Mega Plume. Values given in Table 4.2 ...... 61

Fig. 4.7: Seafloor observations at Mega Plume and Birthday Candles. Yellow star is the same vent in each image a, b, c, and d. a 60 x 60 m Mola Mola AUV track at Mega Plume. Bacterial mats outlined in yellow. b Individual image from the Mola Mola mosaic (a). c Frame grab from VTLC. d Slice from Mola Mola survey. e Frame grab from ALVIN dive at Birthday Candles. f Close up image of a mound at Birthday Candles. g Mound showing gas hydrate dissociation leaving a hole of approximately 75 x 30 cm...... 64

Fig. 4.8: GC/APCI-MS/MS of an oil sample from the Mega Plume vent, compared to a sample from the Holstein reservoir sample...... 66

Fig. 5.1: Progression of bacterial mat coverage and how it changes over time. a bacterial mat coverage at the Mega Plume site 1 day after initial deployment, b 5 days after initial deployment, c 16 days after initial deployment, and finally d is bacterial mat coverage 25 days after initial deployment...... 75

Fig. 5.2: Example of the movement of live clams and the tracks (lebensporen) they leave behind...... 77

Fig. 5.3: Images of some of the different mobile animals observed. a is a fish eating a bacteria mat, b is an eel that comes into contact with the bubble stream, , c are three gastropods that were viewed, and d is a crab that were commonly seen entering the VTLC’s field of view………….77

Fig. 5.4: Close up of a gas hydrate outcrop that is infested with Hesiocaeca methanicola (ice worms). Little burrows and depressions in the gas hydrate made by the ice worms are quite evident...... 78

Fig. C.1: Mega Plume (MP) and Birthday Candles (BC) location in relation to the larger GoM bathymetry. Inset shows other seep locations that fall along the trend of the curving salt ridge ...... …91

Fig. C.2: Rugosity figure of Mega Plume (MP) and Birthday Candles (BC) showing the pockmarks in more detail...... 92

Fig. C.3: Correlation coefficients for quantitative comparison of four samples with Megaplume oil seep. The correlation of Megaplume oil seep with itself is equal to 1, as shown by the purple bar...... 93

xii Fig. C.4: Overlaid spider diagrams for Mega Plume oil seep, Mega Plume oil slick, Birthday Candles oil slick, Holstein crude oil, and Macondo crude oil (NIST2779) constructed from seven diagnostic biomarker ratios (Ts/Tm, H29/H30, H32S/H32R, H30(H31+H32+H33+H34+H35), H33S/H33R, C27α β β /C29α β β steranes, and C27β α /C29β α diasteranes). Macondo crude oil (NIST2779) analyzed to demonstrate the fidelity of the visualization method for the differentiation of samples of the same origin to those originating from other sources...... 94

Fig. C.5: Details from AUV Mola Mola survey. a Mosaic of the 60 x 60 m survey at the Mega Plume seep domain. b Close up section of the red rectangle in a. This section was processed with higher detail using close range photogrammetry. c Individual image from Mola Mola mosaic including the same bubble stream analyzed with the VTLC ...... 95

xiii ABSTRACT

Since the discovery of the Gulf of Mexico, it has become an area of extensive exploration. The Gulf of Mexico harbors specific commodities that are essential in our modern economy. Oil companies provided money and technology to find and study locations for oil exploitation. With the onset of seismic data acquisition, it was possible to gain a more comprehensive understanding of the formation and structure of this unique basin that is in constant dynamic disequilibrium, and facilitates hydrocarbon leakage. The natural seepage of oil and gas to the sea floor is of interest because these “leaks” expel methane which is potentially a significant factor in the global Carbon cycle. Determining the migration pathways through the sedimentary strata to the various primary conduits at the sea floor provides a comprehensive understanding of the large scale dynamic “plumbing system” in the Gulf of Mexico.

One of the objectives in this research was to quantify the rate and volume of oil and gas released from two natural seeps in lease blocks GC600 (1200 m depth) and MC118 (850 m depth). Our purpose was to determine variability in bubble size and release rates at three individual vents and to estimate how changes in pressure affect bubble release rates. Observations with autonomous video cameras (VTLC) captured the formation of individual bubbles as they were released through gas hydrate outcrops. Image processing techniques determined bubble type (oily, gaseous, and mixed: oily and gaseous), size distribution, release rate, and temporal variations (observation intervals from 3 h to 26 d). One vent at GC600 (Birthday Candles) released oily bubbles with an average diameter of 5.0 mm (std. 1.30) at a rate of 4.37 bubbles s-1. A second vent at GC600 (Mega Plume) released mixed oil and gas bubbles with an average diameter of 3.9 mm (std. 1.19) at a rate of 103 bubbles s-1 (std. 24.6). A third vent at MC118 (Rudyville) released gaseous bubbles with an average diameter of 3.0 mm (std. 1.99) at a rate of 127 bubbles s-1 (std. 34.1). To quantify bubble release, a robust image processing technique was developed that is adaptable to the various environments found in deep-sea oil and gas vents.

xiv Our second objective was to constrain the migration of hydrocarbons from the source rock to the sea floor. A compilation of data sets from the macro to micro scale were used to describe the overall sequence of hydrocarbon migration and discharge from ~15 kmbsf to the water column. Geochemical similarities were found by fingerprinting oil samples from reservoir, active vents and sea-surface to show migration connectivity from source to seafloor. To support the geochemical data, measurements of fluxes and the magnitude of fluid flow indicators (e.g. bacteria mats, hydrate mounds, etc.) were compiled, and we have attempted to categorize and quantify the various processes that sequester hydrocarbons. Different stages of upward hydrocarbon flow were characterized by visual and morphological tracers. Varying reflectivity values in seismic and subbottom profile data delineate salt distribution, fault position, and acoustic blanking zones. Local geomorphological features such as hydrate mounds, carbonate hardground cover, and chemosynthetic communities, suggest passive/focused fluid flow. VTLC records and acoustic targets detected by swath mapping were used to determine the number of vents in the seep zone. We used a systems approach to combine the various data sets at different scales and resolutions to quantify values for the hydrocarbon budget at GC600.

Finally, our third objective was to describe the type of benthic communities that frequented the vents in our study and to determine the evolutionary stage of the seep zone. Natural seeps provide a source of energy to chemosynthetic communities in seep areas. We used the autonomous VTLC that was deployed for extended periods of time for an “uninterrupted” view of the behavior of animals within this particular seep zone. We observed a number of metazoans including ice worms burrowing in hydrate outcrops, fish feeding on thick bacteria mats, swarms of annelids, and curious eels and crabs visiting bubble streams. By analyzing the type of organisms within the seep zone, we could determine that these seeps were immature based on the community composition. More matured seeps would include more authigenic carbonate hard grounds, less focused fluid flow (bubbling) and increased abundance of mussels and possibly tube worms. Of particular interest was the sheer abundance of ice worms (~2.8 x 104 in GC600) that inhabit the gas hydrate outcrops and don’t seem to have any predators. Where they go once the gas hydrate dissociates is still an open question.

xv CHAPTER 1

INTRODUCTION

1.1 Introduction

The initial interest in the Gulf of Mexico (GoM) for European explorers was the belief that it was a passageway to the treasures of the Orient. In modern times interest in the GoM lies mostly in another type of treasure; namely the organic matter that seeps out of the sea floor. The GoM is a world class oil producing region with lucrative hydrocarbon reserves. According to the Bureau of Ocean Energy Management (BOEM), as of May 2016, there are approximately 2366 active oil rigs in the Northern GoM, and 17% of the oil produced by the USA comes from off shore drilling. Due to the essential role of oil in the modern global economy, the petroleum industry has made the largest contribution to technological advances that expand our understanding of the geological and geophysical framework of the basin (Duncan and Youngquist, 2005; Mancini et al., 2001; Salvador, 1991). These continuous advances have expanded our knowledge of the tectonic activity and sources of hydrocarbons that help us understand natural seeps within the context of this oily basin.

To understand why the Northern GoM is such a prolific oil producing basin we must understand the geologic history of the basin formation (Fig. 1.1). The GoM started to form during the Jurassic when the super continent Pangea started to split (Brun and Fort, 2011). During this time, the GoM was a shallow water-way (Mancini et al., 2001). The climate was warm and the surrounding land masses of this shallow water way caused high amounts of sediment and organic matter deposition, and sea water evaporation precipitated forming km-thick salt deposits (Brun and Fort, 2011). The high sedimentation rates, and thick salt deposits are two factors that play an important role in the generation and migration of oil.

Understanding the structural and physiological processes of the basin can provide a basis to explain the migration pathways of oil and gas from subbottom reservoirs to the sea floor. The GoM is a passive margin with no tectonic activity, however, due to the thick layers of evaporites that were deposited early in continental rifting the basin became quite “active” (Brun and Fort, 2011). As sediment load increased over time, salt deposits moved and deformed serving as a cap rock or

1 trapping mechanism allowing for the entrapment or migration of petroleum (Planckaert, 2005; Wagner and Jackson, 2011). The deformation and movement of the salt sheets affect the bathymetry causing mini basins, and salt pillows. The Sigsbee escarpment is the area in the Northern GoM where the bathymetric deformation is particularly evident (Fig. 1.2) (Rowan and Ratliff, 2012).

Fig. 1.1: Formation of the Gulf of Mexico in the Late Jurassic (Fig. source: http://media-2.web.britannica.com/eb-media/45/136145-004-4E7735F7.jpg).

This study focuses on two natural seep sites in the Northern GoM, to understand the dynamics of natural seeps from the migration pathways to the different processes at the sediment-water column interface. The different characteristics indicating hydrocarbon seepage were analyzed to determine how hydrocarbons migrate from the subbottom reservoirs, through the sedimentary column and finally to the sea floor. It is important to quantify the magnitude and rate of methane released into the water column since it could potentially influence the climate if it reaches the atmosphere (Beauchamp, 2004; Solomon et al., 2009). Our research focuses on the release of bubbles at the sediment-water column interface, migration pathways from subsurface, and the benthic communities that hydrocarbon seepage supports. We have established replicable methods

2 to analyze the flow and volume of oil and gas bubble release that can be applied to other sites in the GoM. Additionally we have combined multiple data sets ranging over various disciplines to create a schematic model of the most likely migration pathway that oil and gas travel from source rock to seafloor, and identified hydrocarbon sequestration processes in order to create an energy budget for the site. Finally, we have described the benthic communities that profit from hydrocarbon leakage of and postulate their role in the consumption of hydrocarbons entering the system.

Fig. 1.2: Study location: Sigsbee escarpment in the Northern Gulf of Mexico, with detailed view of the mini basins and salt pillows visible in the bathymetry in the Sigsbee escarpment. The two stars indicate our two study sites: GC600 and MC118. Bathymetry courtesy of Bureau of Ocean Energy Management (BOEM).

1.2 Geological features of the Gulf of Mexico 1.2.1 Formation of the Gulf of Mexico

The GoM is a circular structural basin about 1500 km in diameter, and the thickest sedimentary fill is approximately 10-15 km, with rocks ranging from the late Triassic to Holocene (Salvador, 1991). The physiography of the GoM basin is controlled by a number of tectonic and sedimentary processes (Bryant et al., 1991), specifically the deformation of surrounding sediments due to salt structures (Rowan and Ratliff, 2012; Talukder, 2012).

3 After the breakup of Pangaea, during the end of the Jurassic, and into the Early Cretaceous, the GoM looked very much as it does today. A deep central subsiding area surrounded by shallow stable shelves and continuous subsidence of the ocean crust (Mancini et al., 2001; Salvador, 1991). Connection between the GoM and both the Pacific and Atlantic oceans, and continuous high sedimentation rates originating from the Appalachian and Ouachita Mountains were characteristics during this time (Pindell and Kennan, 2009).

Changes in sea level, sedimentation rates, and regression of the GoM basin formed various depositional centers (Galloway et al., 2011). During the Pleistocene sedimentary depocenter approximately 3800 m of sediments were deposited in less than 2MY. This rapid rate of sediment deposition was accompanied by growth faulting and triggered the mobilization of Middle Jurassic salt (Salvador, 1991). Fig. 1.3 shows the present day drainage into the GoM from the North American continent. All rivers east of the Rocky Mountains and west of the Appalachian Mountains drain into the Gulf, with a significant portion entering via the Mississippi river delta. Sediments enter the GoM via water shed either in suspension, solution or as bed rock.

1.2.2 Salt deposition and movement

High deposition of sediments affect the salt sheets by creating increased pressure causing the formation of ridges, diapirs, and mini withdrawal basins (Fig. 1.4) Salt deformation causes gravity slumping, submarine canyons, and creates numerous small basins (Salvador, 1991). Increased sediment deposition causes the salt to mobilize causing extensional and compressional faults to detach and mobilize into different stratigraphic layers (Peel et al., 1995b; Pyles et al., 2001). Fig. 1.5 shows the succession of salt movement and sediment deposition from the Jurassic to the Present day, and how the solid salt sheet deformed and resulted in the pronounced bathymetry seen in the Sigsbee escarpment. When a salt diapir forms, the surrounding strata are upturned against the salt flank, cracking the sediments, and creating ideal conduits for hydrocarbon migration (Rowan and Ratliff, 2012). High sedimentation rates strongly affected salt mobilization and diapiric salt flow is still active in the present day (Fig. 1.5) (Pyles et al., 2001; Salvador, 1991).

4 Fig. 1.3: Present day water shed from the North American continent into the Gulf of Mexico. (Fig. source: http://flowergarden.noaa.gov/image_library/maps/gomwatershed.jpg).

Fig. 1.4: Deformation of salt with increased sediment deposition. (Fig. source: https://en.wikipedia.org/w/index.php?curid=14244862)

5 Sigsbee escarpment

Fig. 1.5. Succession of salt movement from the Late Jurassic to the present day. Present day Sigsbee escarpment is identifyable by black salt diapirs to the south (left). (Fig. source Galloway, 2008).

1.3 Oil production in the Gulf of Mexico basin

To generate petroleum a complete system consisting of the following elements is required; a source rock, a seal, a trapping structure, and a reservoir rock (Abrams, 2005). During the Jurassic, organic-rich sediments were deposited in conditions of anoxic waters and low oceanic circulation. In addition to organic matter deposition, diagenesis and catagenesis is required for the degradation of organic matter, and tectonic deformation create the traps for reservoirs (Planckaert, 2005). Reservoir rocks have large capacities to store organic matter which has been degraded to oil; the storage capacity of a reservoir is largely dependent on the rocks porosity and permeability (Brown,

6 2000). The cap rock prohibits the migration of oil, effectively trapping petroleum in the reservoir. Finally the traps are created by tectonic movement, or sedimentary deformations (Planckaert, 2005). All these conditions, coupled with the right timing, are necessary for the generation and accumulation of oil and gas, before it can be exploited.

1.3.1 Source rocks

There are approximately five oil families in the GoM (Fig. 1.6). The chemical components of each oil family (e.g. fluorescence, sulfur, and salt content) differ based on the time at which they were deposited (Hood et al., 2002). Determining the original source rock of a leaking system is accomplished using a model that considers the generation time after source rock deposition, hydrocarbon migration, and traps in younger reservoirs (Curtis, 1989; Sassen, 1990). Oil and gas migrate in a continuous liquid phase or as a solute in the gaseous phase, from the older, deeper source rocks to the younger and shallower reservoirs via deep-seated faults (Nejring, 1991). Along with fault systems, the salt diapirs aid in forming hydrocarbon migration conduits from the deep source rock to shallower reservoirs. Fig. 1.7 illustrates similarities between biomarker analyses from two different sites (Green Canyon yellow box Fig. 1.6 and Atwater red box Fig. 1.6) that stem from the same Tithonian source rock.

Fig. 1.6: Major oil families in the Northern Gulf of Mexico. Yellow box represents the GC600 study site, blue box represents the MC118 study site. (Fig. source: Hood et al. 2002).

7 Fig. 1.7: Biomarker analysis from oil samples of two separate seep sites stemming from the same Tithonian source rock. (Fig. source: Cole et al. 2001). Several factors that control the oil found in particular reservoirs include: different kerogen types, (marine or terrestrial); migration of oil and gas solely in the immediate vicinity of salt diapirs; and salt deformation creating local barriers for oil migration (Liu and Bryant, 2000). In general, the GoM adheres to each of the necessary conditions required to form oil. Even though the reservoirs are often of poor quality with low primary porosity and permeability, the source is so rich it expels enough oil to fill these weak reservoirs (Nejring, 1991). The rapid sedimentation rates that produced the reservoirs during the Cenozoic also caused the movement of underlying salt and the creation of growth faults, both of which are both considered key structures for trapping the hydrocarbons (Nejring, 1991). The seals help to maintain hydrocarbons in the reservoirs, except in the deformed Sigsbee escarpment, where even today active natural seepage of hydrocarbons persists.

8 1.3.2 Migration and pathways to seeps

The migration of hydrocarbons from the deep reservoirs is dependent on the tectonic structure of the basin. High sedimentation rates (including organic material), and the deformation of salt bodies, creates a unique basin with active tectonic activity albeit a passive margin (Mancini et al., 2001). The delicate relationship between reservoirs, seals, trap formations, source rocks, salt deposits, and petroleum generation, contribute to the migration of the hydrocarbons to the seafloor surface (Pyles et al., 2001). The oil that makes it into the water column and finally the sea surface creates oil slicks that can be detected via Satellite images. Fig. 1.8 indicates the natural seeps detected using satellite images. Each point represents a seep zone which is approximately 2 km in diameter and there are approximately 914 seep zones in the GoM. The majority of these natural seeps are located within the Sigsbee escarpment region.

Fig. 1.8: Natural seep zone locations detected using satellite images. Approximately 914 seep zones detected. (Fig. source: MacDonald et al. 2015).

9 1.4 Natural seeps

Natural seepage can be identified by structures or processes at the seafloor, such as mud volcanoes, brine pools, hydrate mounds, and authigenic carbonates. These features and processes serve as indicators of gas, oil, and/or mud escaping into the water column from the sediments. They are a dynamic component of the carbon cycle and have a significant impact on surrounding benthic communities (MacDonald et al., 2003). Kvenvolden and Cooper (2003) suggest that apart from anthropogenic activities, natural oil seeps may be the single most important source of oil entering the ocean. The different structures on the seafloor dispel gasses, oils and/or muds at different rates and time scales. We attempt to understand the dynamics of natural seeps from the migration pathways to the different processes at the seafloor-water column interface (Fig. 1.9).

Fig. 1.9: Schematic diagram showing the study focus from subbottom migration of hydrocarbons to the different processes at the seafloor. (Fig. source: http://dynatog.whoi.edu/research/gas_hydrates/hyd_gas_ov.png)

10 1.4.1 Mud volcanoes

Mud volcanoes are high flux mud and gas releasing structures that are found on continental slopes. The two main features required for the formation of mud volcanoes are high sedimentation rates, and lateral tectonic pressure (Milkov, 2000). Mud volcanoes are a source of methane release into the water column and can be associated with gas hydrates and carbonate precipitation (Milkov, 2000). They are ecologically important features because they provide a source of nutrients to microbial communities (Joye et al., 2005) and can form large brine pools when left dormant (MacDonald and Peccini, 2009).

1.4.2 Brine pools

Brine pools form when mud volcanoes have become dormant, or at the edges of hydrate mounds. They are composed of hypersaline water or the dissolution of shallow salt that fill depressions (MacDonald and Peccini, 2009) or by the brine rejection in association with gas hydrate formation. Brine pools have an extremely high salinity and are slightly warmer than the surrounding water temperatures by about 20C (MacDonald et al., 1990). They are generally surrounded by live mussels which are able to keep their siphons above the brine to survive (MacDonald and Peccini, 2009).

1.4.3 Gas hydrates

Gas hydrates are considered to be a major reservoir for methane (1 volume of gas hydrate contains 164 volumes of methane at standard temperature and pressure), and can be formed at or near the seafloor (MacDonald et al., 2005a). Water and gas migrate through interstitial pore spaces forming a crystalline structure that is sensitive to temperature and pressure changes (Kvenvolden, 1993). These crystals are naturally formed and are comprised of water molecules encasing a gas molecule. Type I and type II lattice structures are commonly found in nature, depending on the size of the gas molecule that is encased in the crystal. In areas where oil is present, it will dissipate through the pores of the hydrate (Klapp et al., 2010) and cause the, usually white ice-like structure to become oily-brown in color. The stability of gas hydrates can be affected by geologic burial processes, or changes in sea level (Kvenvolden, 1993). Hydrates alter the physical, geophysical, and geochemical properties of sediments and affect the benthic communities around seep sites (MacDonald et al., 2010).

11 1.4.4 Carbonates

Carbonates are features that mark the areas where natural seeps such as gas hydrates and mud volcanoes were once active (Naehr et al., 2007). Natural seeps create ecosystems where chemosynthetic organisms can thrive and cause for chemical disequilibrium in the water column, which allows for the precipitation and formation of authigenic carbonates. The combination of a consistent flux of hydrocarbons from underlying sediments along with bacterial methanogenesis supporting sulfate reduction and hydrocarbon oxidation, which produces these hard carbonate structures (Stakes et al., 1999).

1.4.5 Chronic natural and anthropogenic oil discharges

There is a major difference between the chronic natural and anthropogenic oil discharges which affect the GoM. Natural seeps contribute approximately 47% of the crude oil into the marine environment, and 53% of oil release is contributed by anthropogenic driven leaks or spills (note: this value is prior to the Deep Water Horizon spill) (Kvenvolden, 1993). The estimated natural seepage rate for GoM ranges between 80 000 to 200 000 Metric Tons per year (Kvenvolden, 1993). Satellite images obtained using Synthetic Aperture Radar (SAR) is an effective way to determine the origin of natural seeps by picking up the presence of oil slicks on the sea surface (Garcia- Pineda et al., 2010; MacDonald et al., 2015). The oil is discharged from natural seeps in the form of oily bubbles that travel up through the water column and to the sea surface where it is detected by the satellite.

Understanding the differences between anthropogenic and natural oil discharges can help create a baseline to determine the threshold of oil which the benthic ecosystems can tolerate, and distinguish the difference between the amount of oil that is considered “normal” and that which is “abnormal;” such as oil spills or leaks.

1.5 Study location

The study locations for this research are two ~5 x 5 km lease blocks designated by the Bureau of Ocean Energy Management (BOEM) Green Canyon 600 (GC600), and Mississippi Canyon 118 (MC118).

12 GC600 is one of the most prolific oil producing areas in the Northern GoM that is about 1200 m deep. Prolific oil slicks are chronically visible on the ocean surface (Garcia-Pineda et al., 2010). This area has become an important test bed for research at natural seeps (D'souza et al., 2016; Garcia-Pineda et al., 2010; Roberts et al., 2010; Wang and Socolofsky, 2015; Wang et al., 2016). We focused on two seep domains referred to as Birthday Candles and Mega Plume, which are separated by approximately 1 km and situated on a salt-supported ridge trending in a NW-SE direction. Two faults that lead to the ridge likely serve as migration pathways for the oil and gas (Roberts et al., 2010).

The MC118 site is shallower than GC600, with a water depth of approximately 850 m. We focus on the Rudyville vent which is found in a small depression at MC118 and released predominantly gaseous bubbles at rapid rates. Oil slicks are infrequently visible at the surface; however, persistent gas seepage is confirmed by repeated mapping of vent activity combining bathymetric and seismic data (Lutken and Welch, 2013). This area is underlain by deposits of gas hydrate within fault zones (Dunbar, 2012; Macelloni et al., 2012) and there is active gas venting with thick bacterial mats and associated chemosynthetic fauna (Lapham et al., 2008; Wilson et al., 2014). Both sites (GC600 and MC118) host shallow gas hydrate deposits.

1.6 Thesis objectives

Understanding the dynamics of natural hydrocarbon seeps in the GoM is crucial to assess the impact on the local ecosystems at the sea floor and to quantify the amounts of natural oil and gas released into the water column. Additionally, a better understanding of the seep “plumbing system” as well as a detailed description of the benthic community provides insight into the differences among separate seep sites across the basin. In a context where anthropogenic oil extractions have caused disastrous quantities of hydrocarbons (i.e. Macondo Blow out and most recently Shell) into the ocean, such knowledge about the natural seepage is of particular importance.

Techniques for measuring and quantifying in situ bubble release are still in their infancy. To date, investigators have based the size distribution, behavior and fate of gaseous bubbles measured during short snapshots in time, i.e. seconds to minutes of video footage (Grant and Whiticar, 2002; Greinert et al., 2010; Leifer, 2010; Leifer and MacDonald, 2003b; Römer et al., 2012; Römer et al., 2014; Sahling et al., 2009; Sahling et al., 2014; Valentine et al., 2001). We introduce

13 quantification techniques that are suitable for in situ long-term deployments (several days to months) to analyze bubble release variability over time, and examine the different processes involved in the overall dynamic system of natural seeps.

In my work, we focus on direct observation and measurement on a small scale and use this to scale out to understand the system as a whole. Seepage produces dramatic effects on the otherwise homogeneous deep sea environment. Our basic premise is that seafloor features indicating seepage reveal processes and magnitudes which can be constrained by measurement. The goals of this research were to (1) develop and describe repeatable methods for quantifying oil and gas bubble release and study how release rates vary over time and between sites, (2) to constrain the hydrocarbon budget of GC600 by combining datasets from multiple disciplines in order to understand the source and fate of hydrocarbons, and (3) to describe and identify the seep associated benthic communities.

In Chapter 2 we introduce the technical aspects of the video time lapse camera (VTLC) system used for this research and a detailed list of the image processing steps. Chapter 3 is a manuscript submitted to Marine Petroleum Geology describing the bubble counting technique used to quantify the rate and volume of oil and gas released from two natural seeps where we determined the variability in bubble size and release rates to estimate changes due to pressure. Chapter 4 is a manuscript submitted to Earth and Planetary Science Letters (EPSL) in which we constrain the migration of hydrocarbons from the source rock to the sea floor. A compilation of data sets from the macro to micro scale were used to describe the overall sequence of oil and gas migration and discharge from ~15 kmbsf to the sediment/water column interface. Finally, Chapter 5 is a detailed description of the distribution and types of metazoan communities that benefit from natural seeps located on the mid slope of the Gulf of Mexico using in situ observations.

14 CHAPTER 2

EQUIPMENT AND METHODS

2.1 Video Time Lapse Camera

A video time lapse camera (VTLC) was developed by Aquapix©, and was the central piece of equipment for this research (Fig. 2.1). It provided long term video data that were processed to determine bubble release rates and counts. Additionally the video data allowed observation of the surrounding seafloor for insightful analysis of the benthic ecosystems. In the following sections the specifications and set up of the VTLC system are described. Metadata of all VTLC deployments are available in Table A.1.

Fig. 2.1: The VTLC system on deck of the R/V Atlantis after a 26 day recovery.

15 2.1.1 High Definition VTLC for deep sea time-lapse imaging.

The VTLC consists of a Replay XD 1080 Mini video camera housed in an anodized aluminum casing. The XD 1080 Mini video camera is 85 mm long; with a diameter of 24 mm and a field of view of 120˚ (Fig. 2.2). A VTLC terminal developed by Aquapix© is downloadable so that time-lapse can be controlled by programmable intervals or an external trigger. Micro SD cards of 4, 16, and 32 GB are compatible. With a 32GB micro SD card, up to 4 hours of continuous video can be recorded at a resolution of 1080 X 1920.

Fig. 2.2: XD 1080 mini video camera (http://www.replayxd.com/product/1080-mini/).

The anodized aluminum housing holds the video camera and 24 V battery-pack that provides power for the entire assemblage. The threaded rod (Fig. 2.3) is to secure the battery within the housing. The VTLC has a depth rating of 4000 m, and an anti-fouling copper face ring. The housing is 46 cm in length and 10 cm in diameter. There is one 8 plug connector on the head of the camera to which the wiring harness for light (SeaLite, Deep Sea Power and Light, 3700 lumens) and/or laser (line laser Deep Sea Power and Light) is attached. To download data, and set autonomous settings there is an 8 plug to USB connector.

For deployment, the housing is mounted on a 30.5 x 50.8 x 66 cm Delrin© plastic frame and positively buoyant syntactic foam blocks can be added to lessen the payload for the ROV or submersible. The dry weight of the entire system is 20 kg, and the weight in sea water is 8 kg. A

16 benthic release Lander was built to be able to acoustically release the camera for recovery (Fig. 2.4), which reduced costs of using a ROV.

Fig. 2.3: The head and body of the VTLC built by Aquapix.

Fig. 2.4: VTLC attached to acoustic release lander camera at sea floor (MC118).

17 2.1.2 Autonomous and triggered event settings

Time and date were altered in the XD 1080 text file, and only updated if the “edit” section was correctly selected. In this same text file, different settings of the camera could be adjusted such as saturation, contrast, HD, etc. The autonomous time-lapse program is set on the VTLC terminal before deployment. For our purposes, we generally programmed the time lapse to take 10-30 second video clips every 30-60 min. These settings differed depending on deployment and objective. Video data acquisition started once the settings were saved and the VTLC was plugged in.

The event trigger was also pre-programmed on the VTLC terminal prior to deployment. We often used the event trigger to decrease the interval time between video clips in order to use the light and laser for positioning. For example, we would set a triggered event schedule to last for 8 hours taking a 5 second video clip every 5 min. This aided in positioning of the camera at the sea floor and ensuring that the VTLC captured the vent of interest. To trigger the event, a shorted dummy must be inserted in place of the un-shorted dummy in the 8 plug on the VTLC head just prior to deployment. Once the triggered event is over, the camera returned to the time-lapse schedule.

2.1.3 Deployment and retrieval

Prior to deployment, the camera cover was removed and when the VTLC was on the ROV or submersibles payload, a shorted dummy was inserted to trigger the event schedule. The “clock check” was of utmost importance to ensure that the clock on the VTLC was synced up to the ship time. The “clock check” consisted of displaying a personal watch set to UTC time in front of the VTLC just before deployment. This ensured that when the camera was retrieved we could cross check the time on the images with the time on the watch. Then the VTLC would be carried to the sea floor with either the submersible or the ROV.

In cases when the Lander was used, we needed to make sure that there were sufficient weights on the Lander, which was tested in swimming pools. Prior to deployment, the same steps for the VTLC described above were followed. Additionally the burn-wire was attached to secure the weights and the magnet had to be removed from the benthic release sphere to “turn on” the

18 receiver. The Lander was deployed individually, and the ROV went in shortly after to search for the Lander in order to position it in the desired location.

During the deployment, the ROV or submersible maneuvered the VTLC to position it approximately 20-50 cm away from the vent. The laser was used as a guide to adjust the camera angle. Once the camera was sufficiently positioned, a measuring stick was placed in line with the bubble stream in the field of view of the camera.

For recovery, a ROV or submersible was required to pick up the VTLC, unless it was deployed on the Lander. In that case, an acoustic signal was sent to the benthic release sphere causing an electrical current that makes the burn-wire corrode and drop the weights. Once the Lander reached the surface, the ship crew retrieved the Lander. Unfortunately during my studies, we deployed two Landers, and in both cases there were failures with the Lander’s release systems and therefore each time we had to pick up the VTLC’s using and ROV.

2.2 Semi-automatic bubble counting method

Once the video data was acquired, a semi-automatic bubble counting method was developed. This method works for various in situ bubble measurements that are explained in further detail in Ch. 3. This method is adjustable to multiple settings, and set-ups. The main requirement is that bubble ebullition is the most active and continuous movement in order to determine the cropped bubble counting area for the bubble counting algorithm (Fig. 2.5 – 2.8).

Prior to running the full program the frame frequency must be adjusted, the video must be converted to still frame images and default variables for contouring must be assigned. In this section will delineate the step by step processes necessary to run the program. In Ch. 3, we will define the uses and purpose in more detail.

19 Fig. 2.5: a MC118, Rudyville deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background.

Fig. 2.6: a GC600, Mega Plume 2012 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background.

20 Fig. 2.7: a GC600, Mega Plume 2014 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background.

Fig. 2.8: GC600, Cigar Mound 2014 deployment. a frame from video footage. b Cropped bubble counting area. c Grey scale of cropped area. d Negated image (frame 1 – frame 2) to remove constants in background.

21 2.2.1 Pre-program run

Initially all video files (29 frames per second) are converted to individual frames (Fig. 2.5 – 2.8). This was done using the “video-to-pic” program available through file shares on MatLab©. Once all the video files are converted, ImageJ© software was used to determine a suitable cropped area for the bubble counting where all bubbles are visible, and background noise is minimal.

The first step of the pre-program set up is to determine the default variables in the text file (Fig. 2.9). ImageJ© software was used to determine the approximate bubble height in pixels (avg. BPH, Fig. 2.9), and the bubble speed in pixels per second. This was done by defining the counting region (40-60 pixels) and going through consecutive images to see the speed of the bubbles rising through the image. This step must be done for multiple images throughout the data set in order to decrease error and ensures that each frame has a completely new set of bubbles.

Fig. 2.9: Example of default variables text file

To determine the appropriate thresholds, small subsections (ideally, beginning, middle and end) of the program must be run and contours must be applied in MatLab© to determine the high, medium, and low thresholds. Just like the cropped section and counting region, these thresholds must be adjusted and cross checked for each separate deployment as the bubble composition (gas/oil) differs between different locations. The contours identify the “color” or “brightness” of a bubble, and inform the program that when it recognizes the color within this threshold, to consider

22 that it is a bubble. We define a high, medium, and low, to correct for any errors due to differences in bubble brightness caused by bubble motion and blurring (Fig. 2.10).

Fig. 2.10: Box entitled original is the difference image as seen in Fig. 2.4, 2.5, 2.6, and 2.7 and boxes entitled contour shows the contours applied with high/strict (Yellow), medium (cyan), and low/loose (magenta) thresholds.

2.2.2 Automatic bubble counting program

Once all the default variables are assigned in the text file, it must be saved within the same folder that contains the still frame images. In the next section I will outline key aspects of the algorithm that was developed to count bubbles. The full MatLab© code is available in Appendix B, and all data are publicly available through the Gulf of Mexico Research Initiative Information Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org (doi: 10.7266/N7M906N3).

23 2.2.3 Bubble algorithm

1. Specify the file directory 2. Output folders are prepared and created 3. The program loops through to find the folders containing the images 4. The text file is opened to read the default variables 5. The cropped images area created based on the defined values in the “default variables text file.” 6. Start main loop for the bubble counting by reading in image 1 7. Introduce image 2 and subtract image 1 from image 2 to negate background and only visualize the bubbles 8. Iterate over all pixel lines in the counting region setting sections without bubbles (outside of the threshold value) to zero and counting the number of bubbles on each line. This is done separately for each threshold value defined in the text file. 9. Once this image is done, image 2 replaces image 1 and the loop continues with this next image. The loop continues for each individual image. 10. A summary file is created for each image with all the bubble count numbers for each line, and these values are normalized to portray the values in bubbles per second. 11. Finally, a global summary file is created with the mean bubble per second for each video clip creating a time series of bubble release.

24 CHAPTER 3

BUBBLE RELEASE PROCESSES AT NATURAL HYDROCARBON SEEPS IN THE GULF OF MEXICO

i. Manuscript submitted to PLOS ONE journal, May 1st, 2016 ii. Co-authors and affiliations: C. Johansen1, A. C. Todd2, I. R. MacDonald1

1Florida State University, Tallahassee, FL, USA, 2Telekom Innovation Laboratories, Technische Universität Berlin, Service-centric Networking, Berlin, Germany

3.1 Introduction

The Gulf of Mexico (GoM) is a well-studied hydrocarbon province of economic significance and scientific importance. This region is a prolific oil producing basin characterized by natural seeps resulting from abundant source rock (Kvenvolden and Cooper, 2003). It occurs on a tectonically passive margin, however, active salt dynamics (Peel et al., 1995a) have modified the strata by extruding through the sedimentary layers creating ridges, knolls, and mini basins (Brun and Fort, 2011) that make up the complex bathymetry on the Sigsbee Escarpment (Rowan et al., 2012) (Fig. 3.1). Salt diapirs serve as trapping structures that hold oil and gas in a reservoir, and also fracture sediments to create conduits for the migration of oil and gas to the sea floor (Planckaert, 2005).

Natural seeps are characteristic features in the GoM (MacDonald et al., 2003) where oil and gas are released from subsurface reservoirs to the water column in discrete zones (Garcia- Pineda et al., 2010; MacDonald et al., 2015). Hydrocarbon seepage alters the physical, geophysical, and geochemical properties of sediments creating broad distributions of hard grounds (De Beukelaer et al., 2003; MacDonald et al., 2010). Gas hydrates and authigenic carbonate mounds cover kilometer-scale areas in seep zones (Roberts and Aharon, 1994) and are associated with a variety of chemosynthetic fauna such as tube worms and mussels (MacDonald, 1998, 2004; Sassen et al., 1994).

25 Fig. 3.1: Study sites MC118 (850 m deep) and GC600 (1200 m deep) off the coast of Louisiana are separated by 260 km. Rudyville vent is located at MC118. Birthday Candles and Mega Plume are located at GC600. Inset shows 3D rendering of sea floor and hydroacoustic signature of bubble plumes in the water column at GC600. The hydroacoustic data was collected on the R/V Falkor (cruise F006B), and processed in Fledermaus. Mega Plume is located to the NW and Birthday Candles approximately 1 km to the SE.

Natural seepage can be focused (active and visible bubble ebullition) or diffusive (passive diffusion into the sediments). Focused seepage consists of a small subset of features within a seep zone, that is detectable in satellite and hydroacoustic data (Garcia-Pineda et al., 2015). Synthetic Aperture Radar (SAR) images show persistent layers of oil (oil slicks) on the ocean surface (Garcia-Pineda et al., 2010; MacDonald et al., 2015), and oil and gas bubbles in the water column are detected by echo sounders that generate distinctive plume shaped features known as flares (De Beukelaer et al., 2003; Greinert et al., 2006; Klaucke et al., 2005; Merewether et al., 1985). Both oil slicks and flares can be linked to distinct origin points at the sea floor where oil and gas is venting.

26 Detecting and analyzing hydrocarbon release from natural seeps can help quantify the input of methane from the deep sea into the global carbon budget (Kvenvolden, 1993, 2002; MacDonald et al., 2015; Maslin and Thomas, 2003). To date, investigators have based the size distribution, behavior and fate of gaseous bubbles measured during short snapshots in time, i.e. seconds to minutes of video footage (Grant and Whiticar, 2002; Greinert et al., 2010; Leifer, 2010; Leifer and MacDonald, 2003b; Römer et al., 2012; Römer et al., 2014; Sahling et al., 2009; Sahling et al., 2014; Valentine et al., 2001). In addition, state of the art camera systems have been developed to capture high definition video for accurate bubble size and velocity quantification (Bian et al., 2013; Thomanek et al., 2010; Wang and Socolofsky, 2015). We argue, however, that longer term deployments (days to months) are necessary to capture important processes such as temporal and spatial variability, biological effects, and changes in oil and gas content of bubbles.

Detailed time series analysis of gas seepage has shown that there is evident temporal variability in bubble release (Bayrakci et al., 2014; Boles et al., 2001; Leifer and Boles, 2005; Schneider von Deimling et al., 2011). In these studies, seeps were acoustically monitored (Bayrakci et al., 2014; Schneider von Deimling et al., 2011), or experiments were conducted at relatively shallow areas (~20 m – 75 m) (Boles et al., 2001; Leifer and Boles, 2005). The camera system introduced in this study is the first of its kind to capture long term in-situ video data of gaseous and oily bubbles released in the deep sea environment (~ 850 m -1200 m).

We address the temporal and spatial variability of bubble release with video collection extending from 3 h to 26 days using an autonomous video time lapse camera (VTLC). The VTLC was deployed in the Northern GoM at three individual vents for varying periods of time (Table 3.1), and a robust image processing technique adaptable to diverse deep sea environments was created to quantify bubble release rates. The VTLC was deliberately positioned and left on the seafloor to capture bubble exit points and surrounding hydrate outcrops to extend our understanding of the fine scale processes of bubble formation/composition and benthic activity.

Our first objective was to determine how oil content affects bubble size and release rates. We hypothesized that size and flow rate are inversely related. Bubble size is affected by the diameter of the pore opening (Leifer and MacDonald, 2003b) and the pore opening can in turn be affected by the composition of the bubble, i.e. gaseous or oily bubbles may affect the crystalline

27 structure of the hydrate outcrop differently (Klapp et al., 2010). External factors, such as reservoir fill or hydrostatic pressure on the seafloor can also have an effect on bubble release rates (Hovland et al., 1993; Judd and Hovland, 2007; Torres et al., 2004). Therefore, our second objective is to test whether overall bubble release is related to changes in pressure due to tides. Our results address the dynamics controlling the complex, natural seep systems in the GoM by describing the fine- scale bubble points and quantifying bubble emission from distinct vent sites.

Table 3.1: VTLC deployment location, date, and autonomous settings. Data from Birthday Candles are still frame; all other data were HD video.

Site Vent Depth Latitude Longitude Deployment Sampling Time Distance (m) date frequency deployed VTLC from seep (cm) GC600 Birthday 1215 27˚ 21.858 90˚ 33.822 26. Nov. 1 frame/ 3.5 h 11 Candles 2010 4 s GC600 Mega 1222 27˚ 22.204 90˚ 34.256 14. Nov. 15 s video/ 2 d 40 Plume 2012 5 min MC118 Rudyville 850 28° 51.136 88° 29.531 24. Jun. 10 s video/ 5 d 45 2013 1 h GC600 Mega 1222 27˚ 22.206 90˚ 34.254 9. Mar. 2014 10 s video/ 26 d 50 Plume 30 min

3.2 Study Site

This study was conducted at two seep zones located in the ~5x5 km lease blocks designated by the U.S. Bureau of Ocean Energy Management as Green Canyon 600 (GC600) and Mississippi Canyon 118 (MC118) (Fig. 3.1). GC600 is an oil producing area that is about 1200 m deep, where prolific oil slicks are chronically visible on the ocean surface (Garcia-Pineda et al., 2010). This area has become an important test bed for research at natural seeps (D'souza et al., 2016; Garcia- Pineda et al., 2010; Roberts et al., 2010; Wang and Socolofsky, 2015; Wang et al., 2016). We focused on two individual vents at GC600 referred to as Birthday Candles and Mega Plume, which are separated by approximately 1 km and situated on a salt-supported ridge trending in a NW-SE direction (inset Fig. 3.1). Two faults that lead to the ridge likely serve as migration pathways for the oil and gas (Roberts et al., 2010). Mega Plume is a small cluster of two active vents positioned at the NW end of the ridge that expels a mixture of oily and gaseous bubbles. Birthday Candles is

28 a larger complex of vents (~8) located SE of Mega Plume and characterized by prominent gas hydrate mounds and oily bubble release. Both sites host gas hydrate accumulations that breach the seafloor at the vent sites.

The MC118 site is shallower than GC600, with a water depth of approximately 850 m. The Rudyville vent is found in a small depression at MC118 and released predominantly gaseous bubbles at rapid rates. Oil slicks are infrequently visible at the surface; however, persistent gas seepage is confirmed by repeated mapping of vent activity combining bathymetric and seismic data (Lutken and Welch, 2013). This area is underlain by deposits of gas hydrate within fault zones (Dunbar, 2012) and there is active gas venting with thick bacterial mats and associated chemosynthetic fauna (Lapham et al., 2008). Both sites (GC600 and MC118) host shallow gas hydrate deposits.

3.3 Methods 3.3.1 Camera properties

For the first deployment at Birthday Candles, a compact camera (pixel resolution: 640x480) was used to take pictures of the hydrate outcrop and the associated bubble release. The camera was encased in an aluminum housing mounted on a triangular aluminum frame and held a 12V battery that powered both the light and camera (Fig. 3.2A).

For subsequent deployments at Mega Plume and Rudyville, we utilized the newly designed VTLC mounted on a high density polyethylene (HDPE) frame (Fig. 3.2B-D). The Aquapix VTLC records HD video with a Replay Video XD 1080® mini camera in anodized aluminum pressure housing (pixel resolution: 1080x1920, field of view: 120˚ at 29 frames per second). The housing also contains a 24V lithium battery that can power the camera and a 2400 lumens lamp. The HDPE frame can be adjusted by submersible manipulators to aim the camera towards the bubble emission points. The autonomous VTLC was programmed before deployment to record video clips at fixed sampling frequencies (Table 3.1). A temperature and pressure logger (RbRDuo®) was also attached to the frame to measure background environmental conditions during deployments at Mega Plume and Rudyville (Fig. 3.2B-D).

29 Fig 3.2. Camera positioned in front of vents. A Birthday Candles at GC600. B Rudyville at MC118. C 2 d deployment, Mega Plume at GC600. D 26 d deployment, Mega Plume at GC600.

3.3.2 Camera deployments

The Birthday Candles site was visited with the R/V Atlantis (cruise AT18-2) in November 2010. At this site, oily bubbles were observed escaping from an exposed portion of gas hydrate that was approximately 8 cm x 15 cm. The autonomous camera was deployed on November 26, 2010 with DSV Alvin (dive 4655) and positioned approximately 11 cm from the vent for 3.5 h, capturing a still frame image every 4 s (Fig. 3.2A).

The Mega Plume site was visited in November 2012 with the R/V Falkor (cruise F006B). Approximately 1 km NW of Birthday Candles, a composite of flares in the water column was

30 located with the ships swath mapping system (Kongsberg EM 302 Multibeam Echosounder). We deployed the VTLC next to a hydrate outcrop at Mega Plume that measured 11 cm x 4 cm on November 14, 2012 with the ROV Global Explorer (dive 04) (Fig. 3.2C). The VTLC was positioned approximately 40 cm from the vent and was deployed for 48 h, during which 15 s video clips were taken every 5 min (Table 3.1). In March 2014 we re-visited this site with the R/V Pelican (cruise PE14-14) and ROV Global Explorer (dive 01) to deploy the VTLC for 26 days (March 9 to April 4, 2014). The VTLC recorded 10 s video clips every 30 min, and was positioned approximately 50 cm from the bubble release points (Fig. 3.2D). This VTLC was recovered with the DSV Alvin (dive 4690) aboard the R/V Atlantis (cruise AT26-13).

The Rudyville site was visited with the E/V Nautilus (NA028) in June 2013. The VTLC was positioned about 45 cm away from this vent site with the ROV Hercules (dive H1261) on June 24, 2013 (Fig. 3.2B). For this deployment, we mounted the VTLC on a lander equipped with a benthic acoustic release. The lander was retrieved with the ROV Global Explorer (dive 5) on the R/V Pelican (cruise PE14-14) on March 12, 2014. The VTLC was programmed to record 10 s video clips every h, however, we only recorded 5 days of data (June 26 to July 1, 2013) due to equipment failure.

3.3.3 Measuring bubble size

The images captured by each camera showed bubbles in a two-dimensional plane imaged at less than 50 cm from the camera’s lens. A significant level of accuracy was forfeited due to parallax, in-situ camera positioning, and timing (e.g. limited ROV bottom time). At Birthday Candles, the pixel-to-mm conversion was determined using video footage from DSV ALVIN, where the size of the camera frame was known and converted from pixels to mm. We used the size of the outcrop obtained from the DSV ALVIN video for scale calibration of bubble size measurements (Fig. 3.2A). At Mega Plume and Rudyville, we were able to determine the pixel- to-mm conversion more accurately by inserting a graduated measuring stick into the bubble stream (Fig. 3.2C) or placing the measuring stick in line with the bubble stream (Fig. 3.2B).

After converting pixels to mm, ImageJ® was used to estimate bubble dimensions by measuring their major and minor axes. Since the camera did not move during data acquisition, the pixel-to-mm conversion was adjusted once for each deployment. To decrease error, bubble sizes

31 were measured in multiple images (n= 971-1766) within a 5 x 5 cm box approximately 6 cm above the bubble emission points. By measuring bubble sizes in multiple images, we also account for changes in bubble size over time.

To obtain volume measurements, which are inherently three-dimensional quantities, we estimated the radius of a sphere by calculating the major and minor axes of a spheroidal bubble following Sam et al. (Sam et al., 1996):

( ) = (1) where a is the semi-major axis, b is the semi-minor axis, and r is the radius of a spheroid bubble. From each bubble we estimated r in equation 1, and calculated the volume of the sphere (bubble) (V=4/3π r3) (Table 3.2). Although natural gas can contain higher hydrocarbons, we assumed a gas

composition of 100% CH4 in our calculations. Concentrations of higher hydrocarbons typically account for less than 10% of gas, by volume, escaping in the northern GoM (Bernard et al., 1976; Brooks et al., 1974; Kvenvolden, 1995). Based on this assumption, we determined the amount, n, of gas within this volume V, using equation (2) that corrects for the compressibility factor of methane at the given depth and pressure:

= (2) where P is the absolute pressure in MPa, V is the volume of the bubble in cm3, R is the universal gas constant equal to 8.314 cm3*MPa*mol-1*K-1, T is the temperature of the water in K, and Z is the compressibility factor of CH4 which was calculated using van der Waals equation of state based on the given pressure and temperature. Water temperatures averaged at 4.5 C (S.D. 0.02) at GC600 and 5.6 C (S.D. 0.07) at MC118.

The rise rate of bubbles can be affected by various hydrodynamic properties. These include bubble size, natural bubble oscillation, currents, and rate of emission, upwelling effects, and the bubble interface mobility: “dirty vs. “clean” bubbles (Grant and Whiticar, 2002; Leifer and Judd, 2002; MacDonald, 2002). In addition, pressure change, bubble oscillation and gas exchange can cause bubble size to increase after leaving the origin point (Greene and Wilson, 2012).

32 Therefore, to minimize discrepancies, we measured bubble size within a 5 x 5 cm square ~ 6 cm above the release points. Furthermore to minimize additional error, the release rates were determined independent of bubble size within a cropped box of 60 pixels in the vertical direction and ranging from 81 to 601 pixels in the horizontal direction. The width of the cropped box varied between sites to best encompass the entire bubble stream from the video for our bubble counting algorithm (Fig. 3.3).

Table 3.2: Averages of bubble release rates for each site. Annual release in m3yr-1 is at depth. Gas amount for Birthday Candles is not applicable.

Bubble Gas Annual Bubble Rise Annual Annual Volume at Amount Release rate Release Vent Volume at speed Release Mass flow depth per bubble -1 (mol 3 (bubbles s ) -1 3 -1 -1 3 1atm (mm ) (cm s ) (m yr ) (T yr ) -1 (mm ) (mol) yr ) N/A 1.30 x 104 Birthday 78.4 1.08 x (std. 1.368 x 4.37 1.34 1.12 – 6.48 N/A Candles (std. 77.01) 101 104) 2.91 x 10-4 7.18 x 103 Mega 40.2 103.3 1.30 x 9.47 x (std. 3.584 x (std. 8.849 x 14.5 14.4 – 78.5 Plume (std. 49.49) (std. 24.59) 102 105 10-4) 103) 2.18 x 10-4 5.37 x 103 46.8 127.3 1.88 x 8.73 x Rudyville (std. 7.245 x (std. 1.789 x 15.9 13.4 – 113 (std. 155.7) (std. 34.14) 102 105 10-4) 104)

3.3.4 Overview of image processing

For each deployment, we sampled the bubble flow by recording a sequence of video clips at set intervals (e.g. 10 s every h) (Table 3.1). Each clip was digitized at 29 frames per second. The bubble flow was examined to determine the ascent rate of bubbles in pixels per second. Individual frames from each video clip were extracted and cropped to include only the bubble counting region. This area was then converted from color to grayscale (Fig. 3.3A). For each frame, we subtracted the corresponding pixel values of the previous frame in the video sequence (Fig. 3.3B- C) to remove the unchanging background (e.g. sediments, gas hydrate, bacterial mats, and water column). The resulting image delineates the change between frames (i.e. bubble movement) as bright spots (Fig. 3.3D).

33 Fig. 3.3: Schematic depicting the image processing method. A This is the original image from which a counting region is determined and converted to gray scale. The cropped counting region is then subtracted from the consecutive image (B–C) to negate constant background and identify bubbles (shown here as bright spots D). To account for bubble size, motion blurring, and oil content, three thresholds (high, medium, and low) are assigned to the bubbles (E–F). The bubbles are counted and sub-sampled along 60 pixels in the counting region. The bubble count for each pixel (1-60) is summed across every frame in a clip, and then averaged to generate three values of bubble release at each threshold (high, medium, low) for one clip. This is repeated for each clip to create a time series of bubble release for the entire deployment time.

34 The intensity of bubble spots in the processed image varied for multiple reasons: 1) bubble size, 2) motion blurring, and 3) oil content or shadows that caused contrast differences. Larger bubbles had less distinct edges than small bubbles and motion blurring occurred when the video was digitized to separate frames. These factors caused the brightness of bubbles to vary, i.e. bubbles of the same size could have different intensities (Fig. 3.3D). Therefore, to qualify the bubble counts and to correct for inconsistent brightness intensities of bubble spots, three thresholds were defined based on the pixel value of bright spots: high, medium, and low (Fig. 3.3E). The values for the thresholds were adjusted manually for each separate site based on the pixel value, and depending on the lighting in the videos once they had been converted to gray scale. This created a range of thresholds from strict (high) to less strict (low) to adjust for any brightness variations (Fig. 3.3F).

This process was applied to each video clip, to estimate the temporal variability of bubble release rates over the entire deployment time. To avoid double counting bubbles in consecutive images, the same bubble counting region was used for all images in a sequence, and based on the ascent rate of bubbles through the counting section we determined a frequency interval between each processed image. This ensured a completely new assemblage of bubbles to be counted in each image that was analyzed (e.g Fig. 3.3B-C).

To improve the accuracy of bubble count we subsampled bubble counts over 60 lines of pixels in each frame (Fig. 3.3E). The counts of each pixel line (1-60) was then averaged across all frames to give one value of bubble release per second for every video clip at each of the thresholds (high, medium, low). With these results, we created a time series of bubble release with one value for each video clip for the duration of the deployment.

3.3.5 Bubble counting algorithm

We multiplied the bubble count of each frame by the frame rate per second and divided by the number of frames in the video clip to quantify the average bubble release per second for each video clip during the deployment:

= ( / ) / , (3)

35 where B is the average bubbles per second for the given video clip, m is the number of processed

images in a video clip, p is the number of horizontal pixel lines in a frame, cx(p) is the bubble count on line p for threshold x, and f is the number of frames per second.

3.3.6 Extrapolation

To calculate the annual release in mol yr-1 we used the release rates derived from equation 3 and the amount of gas per bubble (mol) (Table 3.2). These values are based solely on the gas constant at depth; therefore extrapolating annual amounts of CH4 is most reliable for the gaseous- type vent (Rudyville). At the mixed-type vent (Mega Plume) we must consider a 50% margin of error when extrapolating annual CH4 values because both oil and gas are released. Extrapolating annual CH4 amounts is not applicable at the oily-type vent (Birthday Candles). In terms of total carbon release, rendering methane flow in mol values is an underestimation since higher hydrocarbons are not considered.

Table 3.2 also includes a range for mass flow in T yr-1 from each vent, based on the density of pure CH4 as a function of temperature and pressure for the low end, and the density of oil (600 kg m-3 in accordance with Smith et al. (2014) Table B.2) for the high end of the range.

3.4 Results

We analyzed VTLC HD video datasets for three distinctive vents (Table 3.1 and 3.2). Each vent consisted of a small cluster of pore openings from which bubbles escaped (Fig. 3.4). Our video footage confirmed that the individual pore openings were persistent on a daily to monthly scale. However, the bubble release rates from the pore openings varied in activity (bubbling or not bubbling) on an hourly interval. We found that gaseous bubbles had smaller diameters and more rapid release rates. Conversely, oilier bubbles had larger diameters, and slower release rates.

3.4.1 Vent characteristics

At Birthday Candles, dark brown oily bubbles were slowly released from tubes in an 8cm x 15cm gas hydrate outcrop (Fig. 3.4A). We classified Birthday Candles as an oily-type vent (Fig. 3.5). The Mega Plume vent consisted of a mixture of oily bubbles and gaseous bubbles released from small tubes in a hydrate outcrop of approximately 4cm x 11cm (Fig. 3.4C-D). Over the

36 deployment time, the bubbles varied from oily (brown) to gaseous (clear). Therefore, we classified this vent as a mixed-type vent (mixture of oil and gas) (Fig. 3.5). Rudyville consisted of a row of approximately 17 release tubes that protruded from the hydrate outcrop (Fig. 3.4B). These bubbles were all gaseous (clear in color) (Fig. 3.5); and we classified it as a gaseous-type vent. No oil was visibly escaping from Rudyville during the 5 days of video observation.

Fig. 3.4: Frame grabs of individual vents investigated in this study. A Birthday Candles at GC600. Frame grab from the camera where dark oily bubbles escape from ~ 38 individual tubes via a gas hydrate out crop. B Rudyville at MC118. Frame grab from this deployment shows bubbles are clear and gaseous escaping from ~ 17 small tubes of gas hydrate. Fish in the foreground was observed grazing on the bacteria mats that surround the vent. C and D Mega Plume at GC600. Oil stained gas hydrate is visible around the vent, and white mats on surrounding sediments expanded and retracted during deployment. C Mixed oily and gaseous bubbles escaped from the gas hydrate out crop with an area of ~ 4 X 11 cm. D White oval indicates an area where acute, episodic gas explosions would occur, lasting ~ 2 h. The bubble stream in the foreground was used for analysis.

37 Fig. 3.5: Close up of bubbles depicting the difference between gaseous, mixed, and oily vent type.

In general, bubble release was constrained to the local areas where pore openings were visible in the gas hydrate outcrop. However, in the more active vents such as Mega Plume and Rudyville, acute bubble streams would “pop-up” in the surrounding sediments. Of particular interest was an intense burst of gas bubbles observed during the 26 day deployment at Mega Plume. This gas blowout occurred only once during the entire deployment and lasted approximately 2 h (white oval in Fig. 3.4D). Our bubble counting analysis was applied to the main gas hydrate outcrop where bubble release was persistent and not the surrounding sediments where “pop up” streams were inconsistent, yet worth noting.

Viable biological communities were observed at each vent. Changes in bacterial mat coverage of the surrounding sediments were apparent over the deployment times. At Birthday Candles and Mega Plume there was a large number of the polychaete Hesiocaeca methanicola (ice worms) burrowing within the gas hydrate and overlying sediments. Within a 100 cm2 area of hydrate outcropping, we observed approximately 5-10 ice worms in a given video. Considering the extensive gas hydrate occurrences in this area of the Northern GoM, we posit that the total number of ice-worms to be quite large. In addition, a variety of other organisms such as; Provanidae, demersal fish (Dicrolene kanazawai), deep-sea eels (Synaphobranchus spp.), red crabs (Chaceon spp.), shrimp (Alvinocaris spp.), gastropods (Pleurotomariidae), bivalves (Calyptogena spp.), and living mussels (Bathymodiolus spp.), were common within the seep area, but not observed on the actual gas hydrate.

38 3.4.2 Bubble measurements and rates

Average bubble size decreased and bubble release rates increased as the bubble composition became more gaseous (Fig. 3.6 and Table 3.2). This indicated that the addition of oil yields bubbles that have larger diameters and slower rise rates. The bubble volume was calculated based on the measured diameter and recorded at depth as well as 1 atm to facilitate comparisons among different depths. We must concede that the value given at 1 atm does not consider dissolution of the bubble as it rises to the surface. The volume and gas amount (mol) was calculated separately for each bubble size measurement and then averaged for more accurate results.

Fig. 3.6: Individual bubble size distribution of the three different classes of vents (oily, mixed, and gaseous). A smooth kernel distribution is used to fit the histogram, where n is the number of bubbles measured. Inset depicts a visual of the bubble size distribution in line with the measuring stick. Measuring stick shows ticks every 1 cm.

39 For the mass flow rate we used the density of methane gas based on temperature and pressure (Birthday Candles: 109 kg m-3, Mega Plume: 110 kg m-3, Rudyville: 71.3 kg m-3), and the density of oil (600 kg m-3, derived from Smith et al. (2014) Table B2 for consistency in later comparisons). By calculating the mass flow rate of CH4 and oil, we provide a range of hydrocarbon flow from gaseous to oily (Table 3.2).

3.4.3 Pressure differential and bubble release

Our second objective was to determine how overall bubble release is related to changes in pressure due to tides. To compare the coherence of bubble release and pressure, both data sets were de-trended to show the variation about zero (Fig. 3.7). To test the correlation between tidal pressure and bubble release rates, the data were divided into four groups: low slack tide, rising tide, high slack tide, and falling tide. The Pearson’s Correlation test was administered to each of these groups to determine a linear correlation. For the deployments at Mega Plume, Pearson’s Correlation test indicated no positive correlation between bubble release rates and pressure (Fig. 3.7A-B) except during the low slack tide of the short deployment (ρ =0.52) (Fig. 3.7A). However, at Rudyville there was a positive correlation with the rising and falling tide (ρ =0.48 and ρ =0.60, respectively) (Fig. 3.7C).

A clear peak is distinguishable in the power density spectrum of the tide at approximately 1 cycle per day (cpd) at both Mega Plume and Rudyville. This is consistent with the diurnal tidal cycle typical for this area in the GoM. Peaks in the power density spectrum for bubble release rates at Mega Plume did not match those in the tidal power density spectrum. Conversely, at Rudyville the bubble release matched the peaks in the tidal power density spectrum at approximately 1 cpd (0.98 cpd) (Fig. 3.8).

3.5 Discussion 3.5.1 Considerations for long-term deployment

This study is the first attempt of long term camera deployment at individual vents in the deep sea. To achieve in-situ, long-term deployments, the VTLC has reduced precision in measurements compared to lab set ups and ROV-dependent systems in order to increase battery endurance, data capacity, and camera autonomy. To better describe the fundamental processes of

40 oil and gas flow, we consider the effect of gas hydrate and biological activity on bubble release. The VTLCs were deployed close to gas hydrate outcrops to observe individual pore openings from which the bubbles are released, multi-day changes in the environment (e.g. bubble bursts and “pop up” streams), and behavior of various benthic organisms (e.g. bacterial mat coverage, and ice- worm activity).

Fig. 3.7: Observed pressure and bubble release rates. All values have been de-trended by subtracting the mean and dividing with the maximum value to show the variance about zero. Additionally a low pass filter was administered to reduce noise for visualization in the graph. The dashed red line represents the low and high threshold values of bubble release, and the solid red line is the results for the medium threshold. A Mega Plume, short deployment of 48 h. B Mega Plume 26 d deployment. C Rudyville, 5 d deployment.

41 Fig. 3.8: The power spectral density for Rudyville at cph. The peak for both Bubble Release and Pressure (dbar) occurs at 0.04 cph (0.98 cpd).

As Leifer et al. (2003) discuss, there is often a sacrifice when moving from a controlled set up in the lab to the field (i.e. power being a limiting factor at sea compared to camera set up in the lab). Additional challenges are met when moving from ROV-dependent camera and lighting systems to autonomous systems. Even though more elaborate ROV-dependent camera systems have been used to observe bubbles with higher frame rates, modelled illumination, and smaller

42 lens apertures than the VTLCs could achieve (Bian et al., 2013; Leifer et al., 2003; Thomanek et al., 2010; Wang and Socolofsky, 2015; Wang et al., 2016), our bubble size measurements are comparable (within 10%), to those of Wang et al. (2016) at the same sites.

Furthermore, the bubble counting algorithm counts bubbles independent of size and was developed to accommodate in-situ positioning of the camera for long term video acquisition. It is adaptable to a variety of settings and does not require a uniform background to facilitate edge detection (Thomanek et al., 2010). This makes our method more versatile for in-situ camera deployments where carefully staged set-ups and high-intensity lighting are difficult to achieve.

Long-term seepage observation provides a more exact determination of the variability of bubble release compared to short snapshots in time, which may miss transient events or disturbance effects resulting from presence of a submersible. For example, bubble rates were prone to short- lived increases when the ROV contacted the bottom. Indeed, during the entire 26 d deployment, there was only one incident of the intense gas blow out at Mega Plume that lasted approximately 2 h (white oval Fig. 3.4D). If this bubble stream was observed in a small snapshot in time and then extrapolated, we would have quite different estimate of bubble flow rates in the GoM. Observed in the context of the 26 days, we can confirm that this site consists of oily and gaseous bubble release (mixed-type vent). Additionally, the biological components of the seep zone react to the ROV when it sits on the sea floor. During the 26 day deployment, white bacterial mats were not visible until approximately 3 days after disturbance caused by the ROV, and they did not reach the thick coverage seen in Fig. 3.4D until approximately 5 days after initial deployment. Finally, long- term deployment allows us to analyze possible effects of tidal pressure changes. These factors combined can set the stage for continuous research regarding the processes that affect hydrocarbon migration.

3.5.2 Temporal variation of bubble release

Studies have shown that tidal fluctuations influence the flow rate of CH4 gas because of the hydrostatic pressures affecting the underlying geological structures (Krabbenhoeft et al., 2010; Netzeband et al., 2010). In general the trend shows decreased bubble flow at high tide, and increased bubble flow at low tide (Bayrakci et al., 2014; Boles et al., 2001; Leifer and Boles, 2005; Schneider von Deimling et al., 2010). In our study, Rudyville was the only vent where we were

43 able to detect a positive correlation of approximately 1 cpd between pressure and bubble release (Fig. 3.8). In contrast to previous findings, we observed increased flow at high tide, and decreased flow at low tide (Fig. 3.7C). Schneider von Deimling et al. (2010) studied the temporal variability at multiple individual vents in the North Sea (~65 m) and found that one of these vents demonstrated the same pattern that we observed at Rudyville, increased bubble flow at high tide. However, of all the vents studied by Schneider von Deimling et al. (2010) only 1% had an on-off pattern correlated to tidal changes.

In general, the correlation of tides and bubble release were inconsistent among the different vents studied. For example, we found no significant correlation at Mega Plume even after the 26 day deployment. This may be explained by the fact that Rudyville was the shallowest vent studied (850 m) and therefore more sensitive to pressure differences due to larger tidal fluctuations relative to the water depth. The bubble release at Rudyville increased with pressure, but developed a lag of ± 6 h as neap tide approached (Fig. 3.7C) indicating a response to lower pressure forces.

In addition to tidal pressure effects, the migration pathway and geological setting of the seep zone must also be considered to explain the variation in bubble release. On a larger scale, bubble release is affected by the presence of gas hydrate, pressurization of oil and gas in reservoirs, and differential loading of sedimentary layers (Clayton and Hay, 1994). Indeed the GoM has high sedimentation rates and is strongly influenced by salt tectonic activity (Roberts et al., 2010).

Our study sites are located in the gas hydrate stability zone, which results in large gas hydrate accretion near the seafloor due to continuous migration of hydrocarbons (Torres et al., 2004). As we have demonstrated in our video data, and confirmed with site reconnaissance, the individual pores in bubble vents generally pass through gas hydrate outcrops. This implies that gas hydrate is porous enough to allow bubble flow through the crystaline microstructures (Klapp et al., 2010). In fact, the presence of gas hydrate outcroppings must be considered when comparing the variability of bubble release due to pressure changes in areas that are not within the gas hydrate stability zone since they will affect the local compressibility of the seafloor.

Hydrate mounds are formed when contiuous flow of hydrocarbons thicken the gas hydrate, causing for it to push up and breach the sediments (Römer et al., 2014). As the gas hydrate thickens it become less permeable and the oil and gas find alternative pathways of less resistance, which

44 explains why bubbles tend to escape from the sides of mounds (Lapham et al., 2014) . This system has been described by Rӧ mer et al. (Römer et al., 2012) in the Black Sea and is observed at Birthday Candles and other seep sites in the GoM, such as Bush Hill (MacDonald et al., 1994).

3.5.3 Bubble flow rate comparisons

Our estimated annual flow rate of gas and oil (Table 3.2) are comparable to those of other studies that measured mass flow from individual vents in the GoM, but used different methods for bubble quantification. Wang et al. (2016) determined average bubble rates at MC118 to be 6.17 x 104 L yr-1 (compared to our 1.88 x 105 L yr-1, Table 3.2) and at GC600 an average bubble rate of 3.44 x 104 L yr-1 (compared to our 1.31 x 105 L yr-1, Table 3.2). However, as described below, our results appear to diverge markedly from studies that estimate subbottom flow (e.g. Smith et al. (2014)). Garcia-Pineda et al. (2010) classifies a seep zone as a cluster of individual vents within a 1-km radius. Therefore, we delineate the GC600 seep zone to comprise the Birthday Candles and Mega Plume vents. In the hydroacoustic data (inset Fig. 3.1) we count a total of ten individual vents; eight at Birthday Candles and two at Mega Plume.

Smith et al. (2014), analyzed temperature and Cl- in a multiphase one-dimensional advection-diffusion model to estimate hydrocarbon flow rate from two seep zones, GB425 (from 3200 mbsf) and MC852/853 (from 1500 mbsf), and reported rates of 4.0 – 13 x 105 m3 yr-1 and 3.4 – 9.4 x 105 m3 yr-1, respectively. These values are as much as three orders of magnitude higher than our measured rates (1.1 x 102 – 1.3 x 103 m3 yr-1). Although these seep zones are different from the ones in our study, a description of oil and gas venting at the sites can be taken from published results. The GB425 site includes an active mud volcano with episodic gas and oil discharges (MacDonald et al., 2000). The MC853 site is a prominent hydrate mound, however, bubbles were only observed escaping from gas hydrate outcrops following disturbance by the submersible on the ground (MacDonald et al., 2003). MC118 and GC600, although more active, is comparable to MC853 since bubbles were escaping from prominent hydrate outcrops.

The differences between hydrocarbon flow rates estimated from temperature and Cl-, and flow rate estimates based on bubble venting is best explained by mechanisms that sequester or block the release of hydrocarbons into the water column. We posit that the accumulation of gas hydrate is a major factor in the sequestration of hydrocarbons, as is consumption by

45 biogeochemical processes. Additionally, we cannot ignore the diffusive flow into the water column that cannot be captured with the VTLC. Finally, we caution against extrapolating information from release rates of individual vents to the entire GoM, especially based on short data sets. As we have demonstrated with our multi-day video data, there is large variability of bubble release and bubble characteristics at individual vents. In order to estimate total flow rates in the GoM, we would need to analyze multiple vents within different seep zones, and detailed hydroacoustic surveys over larger areas would be necessary to resolve the number of vents in a seep zone.

3.6 Conclusion

Our research provides the first benchmark for estimating the temporal variability of oil and gas bubble release rates using video data from individual vents in the GoM deep sea. We developed a reproducible and adaptable image processing method to quantify bubble release rates in various deep-sea environments and estimated bubble size and flow rates. By collecting high definition video footage over extended periods of time (3 h -26 d), we can account for temporal variability of bubble composition and release rates.

VTLC’s were deployed at three individual vents; two at GC600 and one at MC118. We can conclude that in areas where more oil is present, the bubble size is larger and bubble speed is slower (Table 3.2). This is attributed to various factors including pressure, migration pathways in the sediments, and gas hydrate mounds. There is high variability in the activity of seeps, and the vents studied have been classified into three types: oily, mixed, and gaseous. We consider these classifications to cover the range of typical vent types found in the GoM.

With prolonged video deployments, we defined a bubble size distribution and quantified a range of bubble release rates. This paper is the start of an intensive study focusing on the dynamics of natural hydrocarbon seeps and the geophysical processes that take place during the release of oil and gas bubbles from the sediments into the water column.

46 CHAPTER 4

A HYDROCARBON BUDGET FOR A GULF OF MEXICO NATURAL SEEP SITE: GC600

i. Manuscript to be submitted to the journal of Earth and Planetary Science Letters beginning June, 2016 ii. Co-authors and affiliations: C. Johansen1, E. Marty2, M. Natter3, M. Silva1, J. Hill4, R. Viso4, V.V. Lobodin5, A.R Diercks6, M. Woolsey6,7, A. Woolsey7, L. Macelloni7, E.V. Maskimova8,9, W. Shedd3, S. Joye2, M. Abrams10, I.R. MacDonald1

1Florida State University, Tallahassee, FL, USA, 2University of Georgia, Marine Sciences, Athens, GA, USA, 3 Bureau of Ocean Energy Management, New Orleans, LA, USA, 4Coastal Carolina University, Conway, SC, USA, 5National Magnetic High Field Laboratory, Tallahassee, FL, USA, 6The University of Southern Mississippi, Stennis Space Center, MS, USA, 7National Institute for Undersea Science and Technology, University of Mississippi Field Station, Abbeville, MS, USA, 8College of Marine Science, University of South Florida, St. Petersburg, FL, USA, 9Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA, 10Imperial College, London, UK

4.1 Introduction

The Gulf of Mexico (GoM) is characterized by prolific natural oil and gas seepage (MacDonald et al., 2015) which profoundly affects seafloor geology (Roberts et al., 2010), benthic ecology (Fisher et al., 2007), and may enhance primary productivity of surface waters (D'souza et al., 2016). Persistent seepage of hydrocarbons can be detected via acoustic signatures of bubble plumes in the water column (flares) and video data from bubble release at individual vents on the sea floor. Locating natural seeps reveal specific locations of large scale hydrocarbon migration to the seafloor. We combine diverse data sets, which range from km-scale 3D multichannel seismic data to cm-scale sea floor observations, to systematically describe the different processes involved in hydrocarbon migration and sequestration at a natural seep.

The GoM is one of the most dynamic and complex passive continental slopes in the world (Liu and Bryant, 2000). One of the processes responsible for the continuous generation of hydrocarbon fields in the GoM is the high sediment deposition rates that result from river inputs from the North American continent (Prather, 2000). Rapid subsidence increases pressure, compaction, slope instability and creates over pressured formations that cause the geological system to be in constant disequilibrium (Clayton and Hay, 1994; Thrasher et al., 1996). Additionally, structural

47 deformation of salt deposits create faults and fractures that act as natural conduits for oil and gas migration to the seafloor (Macelloni et al., 2012; Peel et al., 1995; Planckaert, 2005).

Hydrocarbon seepage results from a complex interplay between hydrocarbon reservoirs, pressure regimes, migration pathways, and near surface processes (Abrams, 2005). For a carbon- containing molecule in a deep petroleum reservoir to return to the modern-day carbon cycle, the following series of processes must occur: 1) build-up of overpressure, causing leakage by fracturing the reservoir cap (Clayton and Hay, 1994); 2) upward migration along faults (Leifer and Boles, 2005; Macelloni et al., 2012); and 3) discharge at the sediment-water interface (Johansen et al., Submitted; Lapham et al., 2014; Solomon et al., 2008; Wankel et al., 2010). These processes generate distinctive signatures that can be detected acoustically (e.g. seismic, blanking zones, gas flares), or via visual observation (e.g. bubble plumes at the sea floor or surface oil slicks).

Natural seeps occur across diverse settings worldwide, and are characterized by gas plumes, shallow gas hydrates, and chemosynthetic fauna (Leifer and MacDonald, 2003; Römer et al., 2014; Sahling et al., 2008; Wilson et al., 2014). The GoM is characterized by many leaky reservoirs with conduits leading hydrocarbons to the sea floor that affect the geomorphology, chemistry, and biology of these localities (MacDonald et al., 2003; Sassen et al., 2004). The fate of hydrocarbons seeping out of reservoirs comprises the following processes. 1) Sequestration of hydrocarbons in gas hydrate mound growth; 2) gas hydrate dissociation (e.g. exposed gas hydrate outcrops); 3) focused venting (e.g. bubble streams); 4) diffusive or biological consumption (e.g. bacterial mats, mussel beds).

The objective of this work was to examine each processes that link the different stages of vertical hydrocarbon migration from source rock to seafloor, and to constrain the fate of the hydrocarbons throughout this journey. We combine various data sets to semi quantitatively interpret observations and to consider the hydrocarbon budget at this particular site – introducing a systems approach that can be applied to seeps across the GoM.

The Outer Continental Shelf (OCS) lease block Green Canyon 600 (GC600) is an example of a well-studied mid-slope seep zone with ample satellite data documenting surface oil slicks, seismic/acoustic mapping, and seafloor observations (Diercks et al., Submitted; Garcia-Pineda et al., 2010; MacDonald et al., 2015). To investigate and describe the overall sequence of

48 hydrocarbon migration we used a compilation of separate data sets for each stage of the system, which became smaller in scale and higher in resolution and detail as we moved from source to sea floor.

The different datasets examined during this study include the following: 1) multichannel seismic data (survey area ~60 x 20 km) to delineate salt structures and fault positions; 2) chirp subbottom profiles (survey area 1.2 x 1.8 km ) to detect acoustic blanking zones generated by gas charged sediments; 3) bathymetry, and backscatter (survey area 1.2 x 1.8 km), as well as AUV photogrammetric images (survey area 60 x 60 m) of the sea floor, to map out geomorphology; 4) acoustic swath mapping to detect plumes in the water column (survey area ~ 5 km2); 5) video time lapse cameras (VTLC), ROV, and submersible video to observe features on the sea floor (at a cm- scale); and 6) gas chromatography/mass spectrometry (GC/MS) results of oil samples from a reservoir, sea floor vent, and surface oil slick, to demonstrate continuity of oil chemistry at each stage of seepage.

4.1.1 Indications of fluid flow

Indicators of fluid flow at the seafloor include physical structures such as mud volcanoes, gas hydrate mounds, authigenic carbonate outcrops, sea floor depressions, (e.g. pockmarks) (Diercks et al., Submitted; Leifer and Boles, 2005; MacDonald et al., 1994; Naehr et al., 2007; Römer et al., 2012; Sahling et al., 2008), and complex chemosynthetic communities (Lessard-Pilon et al., 2010; MacDonald et al., 2010; Orcutt et al., 2004). These seafloor physical and biological features are supported by diffuse or active hydrocarbon flow in the upper sediments. The various indicators reflect not only the presence, but also the intensity, of seepage with focused flow visualized by bubble streams (Leifer and Boles, 2005), and diffuse flow detected by chemosynthetic communities (e.g. bacterial mat coverage).

Seismic data depicts the distribution of salt mounds and sheets, that can be used to estimate possible flow paths along faults and the salt-sediment interface from the deep source rock to the seafloor (Macelloni et al., 2012; Simonetti et al., 2013). Below the sediment interface, zones of indistinct acoustic return (a.k.a. wipe-out zones) in subbottom data (75 mbsf) delineates gas charged sediments (Abrams, 1992). Depending on the geothermal gradient and sediment pore space, shallow gas hydrates form when sufficiently high fluid flow rates are coupled with high

49 concentrations of methane (Haacke et al., 2007). Rapid vertical flux causes gas hydrate caps to form, promoting lateral migration of hydrocarbons (Liu and Flemings, 2006). Despite gas hydrate cap formation, vertical fluid migration continues from below, creating mounds that breech the sediment interface (MacDonald et al., 1994). As a result, pathways allowing focused flow (bubble ebullition) are often present along the edges of gas hydrate mounds (Lapham et al., 2014; MacDonald et al., 1994; Römer et al., 2012).

4.2 Site description

This study was conducted on the northern slope of the GoM in the ~ 5 x 5 km lease block GC600 (Fig. 4.1a). This part of the GoM is notable for the recurrent oil slicks which are continuously detected at the sea surface in SAR images (Garcia-Pineda et al., 2010; MacDonald et al., 2015). The bathymetry of the Northern GoM, consists of depressions and ridges formed by salt deformation (Roberts et al., 2010). GC600 falls on the rising ridge of the salt-driven bathymetry, a feature associated with seepage elsewhere in the GoM (Macelloni et al., 2012; Simonetti et al., 2013; Wilson et al., 2014) (Fig. C.1).

Fig. 4.1: a Study location, Gulf of Mexico, GC600. b shows the two seep domains Mega Plume (MP) and Birthday Candles (BC). The entire seep zone extends over 2 km. c 3D rendition of the flares detected at both seep domains MP and BC. Additionally there is an example of how the flares show up during multibeam mapping in the triangular swath beam. This is used to determine the geolocation of the flares.

50 Following the definitions of Leifer and Boles (2005) and Garcia-Pineda et al. (2010), our study is focused in the 2 km diameter seep zone where there are multiple and persistent vents. Within this zone, we defined two seep domains: Mega Plume and Birthday Candles (Fig. 4.1b). Birthday Candles is located to the SE of the salt ridge at 1215 m. Mega Plume is located 1 km NW from Birthday Candles at a depth of 1222 m. These seep domains consist of multiple individual vents; each vent comprises clusters of small pores in gas hydrate outcrops through which oily and gaseous bubbles escape. The domains also include many well-developed examples of fluid flow indicators described previously.

4.3 Methods

We examined the geophysical and geochemical aspects of the system using a broad suite of approaches. In order to explain how each separate data set contributes to the understanding of the natural seepage system as a whole, we use the data to define different stages of seep evolution. We define components of the system by the following regimes: “deep plumbing,” shallow subbottom blanking zones, geomorphology of seafloor surface, sediment-water interface processes. Each of these stages is characterized by data sets of various spatial scales and resolution. Regional seismic data (“deep plumbing”) provides the most complete picture of the seep system, but without resolution of important processes at the sediment-water interface. Therefore, we proceed to observations of finer scale processes to infer the overall dynamics of the seep zone. Additionally, chemical analysis of oil samples from each section of the system verifies connectivity among the regimes. Linkage among the separate components supports a systematic understanding of the seep system – from source rock to seafloor. Table 4.1 lists the different data collections used to address each component.

Characterization of the system begins with a description of the “deep plumbing” examined via multichannel seismic data collected over 60 x 20 km (dimensions for seismic overview; horizontal and vertical distance respectively). We can identify the salt coverage and fault systems that govern the hydrocarbon migration pathway of the system. We describe the general migration pathway from source rock to seafloor, rather than details of individual reservoirs. The shallow subbottom blanking zones are derived from chirp data illustrating gas-charged sediments in the upper 75 mbsf (meters below seafloor), which matches with the next component: geomorphology of the seafloor. The geomorphology of the seafloor was revealed through bathymetric and backscatter data over a

51 1.2 x 1.8 km area, and on a smaller scale AUV photogrammetric survey that allowed matching the bathymetry and surface images in a 60 x 60 m area. Finally sediment-water column interface dynamics are linked with the geomorphology and photogrammetric surveys using acoustic swath mapping of flares in the water column, and video observations at the sea floor with VTLCs or submersible assessments. The following sections describe the methods in more detail.

Table 4.1: List of objectives, instruments, and methods used to collect data. DOI for data are listed in acknowledgments.

Objective Collection Type Instrument Program Seafloor VTLC*, DSV ALVIN, ECOGIG-1, Video data observations ROV’s ECOGIG-2 Bubble flares in Kongsberg EM 302, Multibeam Echosounder ECOGIG-1 the water column Konsberg EM 122 Seafloor Photo survey MolaMola AUV ECOGIG-1 Geomorphology Blanking zones Backscatter and subbottom and hydrate Eagle Ray AUV ECOGIG-1 survey coverage Faults and salt BOEM seismic Seismic survey Q-Marine point-receiver distribution archive *VTLC: Video Time Lapse Camera

4.3.1 Faults and salt distribution

Geophysical interpretation of the study area was performed with use of Schlumberger’s GeoFrame reservoir characterization software on three-dimensional multichannel seismic datasets archived by the Bureau of Ocean Energy Management (BOEM). The interpreted volumes included one pre-stack, time-migrated seismic volume at 4 ms and one wave equation pre-stack depth migrated volume. Source to seep travel distances were computed utilizing a software-embedded digital planimeter.

4.3.2 Subbottom blanking zones

The chirp subbottom profile data covers an area of 1.2 x 1.8 km and was acquired using the AUV Eagle Ray operating at a target altitude of 2 m above bottom (Diercks et al., 2009; Diercks et al., Submitted). The raw GeoAcoustics.gcf format data were converted to standard SEG-Y format. The data were then processed using SIOSEIS. Processing steps include the following:

52 optimum pulse matching filter, bandpass filter between 4.5 – 7 kHz, spherical divergence correction, time-varying and automatic gain control applied at 100 ms window length, static correction for the AUV navigation, and muted data to the seafloor. Processed chirp lines were imported into IHS Kingdom Suite to identify the reflectors and compute the thickness of the geological units. The depth to the top of the gas charged horizon was determined by manually selecting both horizons of the sea floor and gas charge zone and subtracting them from each other which provided the sediment thickness above the gas charged sediments. These values were interpolated and gridded with 2 m spacing to visualize gas-charged wipe out zones.

4.3.3 Multibeam bathymetry and backscatter

The multibeam bathymetry data were corrected for errors (navigation, altitude parameters, sound velocity profile, tide) and then underwent a phase of sound editing and spike removal to ensure the high data quality for the gridding procedure. The final displays of the bathymetry data (x,y,z) are shaded relief maps, or tridimensional surfaces, at 1m bin resolution. Maps are usually vertically exaggerated about 4 to 6 times to emphasize seafloor morphology and to identify individual features and anomalies.

Backscatter data underwent a series of corrections following Beaudoin et al. (2002) and Clarke et al. (1996); yielding calibrated backscatter intensity data consisting of values that reflect differences in seafloor sediment characteristics.

4.3.4 Seafloor geomorphology

To analyze the geomorphology of the GC600 seep, the AUV Mola Mola (Diercks et al., 2009; Diercks et al., Submitted; Woolsey et al., 2015) surveyed a 60 x 60 m area in the Mega Plume domain. Agisoft PhotoScan software was used to perform close-range photogrammetry on the acquired images to create a Digital Terrain Model (DTM). Images were obtained at 3 m altitude with a 15% overlap between survey lines. For sections of interest in the survey area, a height field mesh suitable for terrain modelling was built to visualize distinct topographical depressions, reliefs, biology, and detailed color features. Mola Mola did not survey the Birthday Candles domain; therefore, DSV ALVIN videos were examined for detailed observations and characteristics of the seafloor morphology and biology in this area.

53 4.3.5 Bubble flares in water column

Acoustic (Table 4.1) and mapping (Fig. 4.1c) surveys detected anomalies (flares) ascending in the water column over the GC600 seep zone. Due to pitch, roll, and heave of the ship, overlap of swath path, and multiple overlapping survey lines, individual flare sources (vents) were detected at slightly different locations among the survey passes. Therefore we used a clustering routine to estimate best-probably vent sources based upon all available swath data.

Data sets from both R/V Falkor (expedition F006b, Kongsberg EM 302) and R/V Atlantis (expedition AT26-13, Kongsberg EM122) cruises were analyzed (horizontal coverage of swath was 3.5 km with an angle of 120; cell resolution of each beam at 4.1 m). The FMMidWater Toolbox in Fledermaus was used to detect flares and export the 3D volume (Fig. 4.1c). We ran multiple survey lines over the seep zone, and the geolocation of the plumes were manually noted along each survey line, generating an array of points for each flare detected by the ships multibeam system.

We clustered each data point that represented a flare based on the method described by Garcia- Pineda et al. (2010). After combining the data sets from the R/V Falkor and R/V Atlantis expeditions (Fig. 4.2a), we used the hierarchical cluster tree based on the pair-wise distances between each point, using the inconsistency coefficient to determine the maximum distance for grouping points (Fig. 4.2b). This distance (35 m) was used as an input for a MatLab© clustering function to estimate the total number of flares at Birthday Candles and Mega Plume. The number of clusters was used to determine the number of vents (Fig. 4.2c), and the centroid of each cluster (Fig. 4.2d) was used to plot the vents. Following this method, we cannot determine the exact location of a vent, however, we can determine the approximate number of individual vents within the seep zone.

4.3.6 Chemical analysis

Oil samples were collected from surface slicks at Birthday Candles and Mega Plume using U.S. Coast Guard certified Teflon collection nets (UCGTN) attached to extractable poles. Oil samples from the individual vent at Mega Plume were collected using UCGTN’s attached to a T- handle and maneuvered above the vent with the Global Explorer ROV. Nets were stored in a sealed

54 box on the ROV tray during the ascent. After collection the UCGTN’s covered in oil were immediately placed into glass jars and frozen at -20C. Additionally, samples of crude reservoir oil were provided from the Holstein Spar oil platform operated by Anadarko, located approximately 5 km SE from GC600 seep zone.

The UCGTN oil samples were extracted with toluene (HPLC grade), evaporated under a gentle nitrogen flow for complete solvent removal, and diluted with dicholoromethane (HPLC grade) to a concentration of 20 mg/mL. Crude oil samples (Holstein and Macondo) were subjected to five- fold dilution with the dicholoromethane. A chemical analysis was performed with a gas chromatography/atmospheric pressure chemical ionization mass spectrometry (GC/APCI-MS) instrument as described by Lobodin et al. (2016)

Fig. 4.2: Spatial clustering of bubble flare detected by EM302 and EM122 swathmapper. a Raw data of all detected flares from R/V Falkor (expedition F006b) and R/V Atlantis (expedition AT26-

55 13). b Pair-wise distances between each detected plume. c Resulting clusters shown as separate colors (21 total). d Geographic centroids of each cluster (colored points) overlain on detected plumes (grey points). a, c, and d axes are in UTM meters, zone 15N.

4.4 Results 4.4.1 Acoustic anomalies in seep zones

We examined acoustically acquired data in the water column (flares), at (bathymetry and backscatter), and below (subbottom and seismic) the seafloor and connect the different data sets to identify hydrocarbon migration pathway(s) from source rock to water column. By overlying the bathymetry and backscatter over blanking zones and comparing these results to interpreted fault positions in high amplitude maps, we determined migration pathways at each scale that are consistent with observations at the sea floor.

4.4.1.1 Seep domains

Seep domains are areas where migrated hydrocarbons are concentrated, accumulates, and transforms local bathymetry (Fig. 4.3a). Each seep domain (Birthday Candles and Mega Plume) is forms an elevated mound that appear to be independent of the shallow faults visible in Fig. 4.3, C.1 and the amplitude maps (Fig. 4.4a). These two mounds, in particular, are covered in pock marks (depressions), which are visible in the high definition bathymetry, indicative of fluid flow via gas hydrate formation and dissociation (Diercks et al., Submitted) (Fig. 4.3a and C.2).

4.4.1.2 Seismic interpretation

Salt can act as either a cap or conduit forming structure (Peel et al., 1995). In the case of this particular seep system, we found a distinct void in the salt horizon (Fig. 4.4a, b, and e), approximately 10 km2 in extent. This salt void is also visible in Fig. 4.4b where we infer the most reasonable migration pathway for the oil and gas from the source rock to seep zone. The amplitude maps (Fig. 4.4a, d) delineate the position and trend of the surface faults in relation to the Mega Plume and Birthday Candle seep domains. Additionally, Fig. 4.4c shows a (bottom simulating reflector) BSR indicating that the seeps are within the gas hydrate stability zone (GHSZ).

56 4.4.1.3 Backscatter and subbottom interpretation

The backscatter acquired with the AUV Eagle Ray depicts high reflectivity over a subset of the survey area that corresponded well with the subbottom blanking zones and bathymetry for the Birthday Candles and Mega Plume seep domains. High reflectivity in backscatter data suggests the presence of authigenic carbonates, hydrate outcroppings, or free gas venting – each of which is an indicator of seepage. From the subbottom profile data, we can distinguish two separate blanking zones; the minimum sediment thickness above the blanking zones was 0.31 m (Fig. 4.5a- b).

4.4.1.4 Flares in water column

We identified 7 individual vents at Birthday Candles and 8 individual vents at Mega Plume (Fig. 4.3a-b). Prior to the clustering analysis, most flares were detected within the high amplitude backscatter (Fig. 4.3b). The high amplitude of the backscatter matched the mounds in the bathymetry (Fig. 4.3a). Analyzing the post-clustering centroids, it is clear that most flares were detected in areas indicating seepage in both the bathymetry and backscatter data.

4.4.2 Seafloor fluxes

AUV surveys, DSV ALVIN flyovers, and VTLC video footage provide visual observations that ground-truth the data sets acquired acoustically. Fig. 4.6 depicts the hydrocarbon flow rates through all possible pools that sequester hydrocarbons. Below, we address each hydrocarbon pool including the flow rates and fluxes to begin the process of constraining overall flow regimes and fates of hydrocarbons during the journey from source rock to water column (Table 4.2).

57 Fig. 4.3: a Bathymetry of GC600 seep domain, Mega Plume is the mound to the NW and Birthday Candles is the mound to the SE. Black contour outlines blanking zone in subottom data. Green points show cluster centroids. Stars are positions of individual vents ground-truthed with VTLC records and AUV and submersible surveys. b Backscatter data with blanking contour outlined to show match. Red points show flares detected in acoustic mapping for each survey line; green points are flare cluster centroids.

Fig. 4.4: Geophysical structures in the GC600 region. a Seafloor amplitude map. Red line shows seismic traverse for seismic section shown in b. Red polygons delineate interpreted faults on the

58 seafloor amplitude map. b Seismic section of the traverse in a. b shows inferred migration pathway of oil and gas from the source rock (Cretaceous (~11 kmbsf) or Smackover (14 kmbsf). c Overview (in the time domain) of the traverse in d. Blue show interpreted faults. Discontinuous Bottom Simulating Reflector (BSR) identified at approximately 305 m. d seafloor amplitude map, polygons depicting acoustic amplitude anomalies caused by the fault scarps. e Grid of the base of the salt coverage. The salt void is the same as the ones seen in a and b.

Fig. 4.5: a Grid showing base of the blanking zone determined with a closed contour of 1 m intervals. b chirp line of corresponding line in a (A-A’). Red arrows show depth from seafloor to blanking area.

59 Table 4.2: Putative in-flow, out-flow, and relative sizes of each hydrocarbon pool.

BC MP BD+MP IN-FLOW Flux (mol/m2/yr)* 4.30E+03 4.30E+03 4.30E+03 Blanking zone cross-sectional area (m2) 2.39E+05 2.42E+05 4.81E+05 Mass flow rate (mol/yr) 1.03E+09 1.04E+09 2.07E+09 OUT-FLOW Focused (bubble streams) Flux (mol/m2/yr) 5.80E+06 7.50E+07 5.01E+07 Pool cross-sectional area (m2) 5.39E-02 9.60E-02 1.50E-01 Mass flow rate (mol/yr) 3.13E+05 7.20E+06 7.51E+06 Diffusive (bacterial mats) Flux (mol/m2/yr) 2.90E+01 2.90E+01 2.90E+01 Pool cross-sectional area (m2) 7.28E+02 8.32E+02 1.56E+03 Mass flow rate (mol/yr) 2.11E+04 2.41E+04 4.52E+04 Dissociative (gas hydrate outcrop) Flux (mol/m2/yr) 7.85E-02 7.85E-02 7.85E-02 Pool cross-sectional area (m2) 5.25E+00 6.00E+00 1.13E+01 Mass flow rate (mol/yr) 4.12E-01 4.71E-01 8.83E-01 Brine pools Flux (mol/m2/yr) 1.10E+00 1.10E+00 1.10E+00 Pool cross-sectional area (Qt. 1) (m2) 3.55E+00 3.55E+00 7.09E+00 Mass flow rate (mol/yr) 3.90E+00 3.90E+00 7.80E+00 Mussel beds Flux (mol/m2/yr) 8.90E-01 8.90E-01 8.90E-01 Pool cross-sectional area (Qt. 1) (m2) 1.64E-01 1.64E-01 3.29E-01 Mass flow rate (mol/yr) 1.46E-01 1.46E-01 2.92E-01 TOTAL OUTFLOW Flux (mol/m2/yr) 4.53E+02 8.58E+03 4.79E+03 Total pool cross-sectional area (m2) 7.37E+02 8.42E+02 1.58E+03 Total mass flow rate (mol/yr) 3.34E+05 7.22E+06 7.56E+06 MISSING HYDROCARBON (in flow out flow) Net flux (mol/m2/yr) 4.30E+03 4.27E+03 4.28E+03 Blanking zone cross-sectional area (m2) 2.39E+05 2.42E+05 4.81E+05 Net mass flow rate (mol/yr) 1.03E+09 1.03E+09 2.06E+09 Maximum possible gas hydrate growth rate Gas hydrate growth rate (m3/yr) 1.37E+05 1.38E+05 2.75E+05 Gas hydrate growth rate (m3/day) 3.76E+02 3.78E+02 7.54E+02 *Smith et al. 2014, Johansen et al. (submi ed), Solomon et al. 2008, Lapham et al. 2014, Wankel et al. 2010

60 Fig. 4.6: Schematic of all the different methane fluxes for each identified “pool” at both Birthday Candles and Mega Plume. Values given in Table 4.2.

4.4.2.1 In-flow: Hydrocarbons migrating from depth

The in-flow represent the hydrocarbons coming into the system from the top of the salt ridge ~ 2 kmbsf (Fig. 4.4b). We consider the in-flow from the top of the salt ridge because between this point and the seafloor there is enough fracturing in the sediments to assume hydrostatic pressure (Mann and Mackenzie, 1990). Based on the temperature and chloride concentrations near the seafloor in a similar seep zone (GC852), Smith et al. (2014) estimated a deeply sourced hydrocarbon flux of 4.3 x 103 mol/m2/yr. We applied this rate to the area of the blanking zones at Birthday Candles and Mega Plume (Table 4.2). Although we cannot confirm that blanking zones in the chirp are 100% free gas, we assume that blanking zones indicate active fluid flow, and therefore, contour intervals of 1 m were used to determine the base of the closed contour of each blanking zone. The blanking zone area for Birthday Candles was 2.39 x 105 m2 and the area for Mega Plume was 2.42 x 105 m2 (Fig. 4.5a).

61 4.4.2.2 Out-flow: focused bubble release

The release of hydrocarbons in the form of bubbles from individual vents was quantified using the bubble counting methods presented by Johansen et al. (Submitted). An individual vent is composed of a cluster of pore openings extruding from gas hydrate outcrops. The area of individual vents was determined from VTLC observations (Table 4.2). The number of vents (clustered) was based on the number of flares within the closed contour of the blanking zone for each domain (see above; Fig. 4.3a-b).

4.4.2.3 Out-flow: diffuse hydrocarbon seepage

We used bacterial mats as an indicator for diffuse flow of hydrocarbons out of the system. Hydrocarbon fluxes were based on the measurements of methane flux across the seafloor at bacterial mats using the MOSQUITO system (Solomon et al. 2008), an osmotic pump that uses a tracer injection device to measure fluid flow rates and solute fluxes at approximately 20-26 cmbsf. Solomon et al. (2008) estimated the methane flux to be 29 mol/m2/yr. We applied this rate to the area of bacterial mats measured at GC600 (Table 4.2). The area of the bacterial mats was determined from the 60 x 60 m photo survey and then scaled up for each seep domain. The bacterial mats were most concentrated close to focused venting, and became more scattered with distance from the vent (Fig. 4.7a-c). We estimate the total area of bacterial mat coverage to be about 100 m2 around each individual vent (Table 4.2).

4.4.2.4 Out-flow: dissociative flux from exposed hydrates

Passive dissociation of gas hydrate occurs when gas hydrate is exposed (not covered in sediments) (Lapham et al. 2014), and leads to benthic exchange of hydrocarbons. The flux was estimated based on the gas hydrate dissociation rates reported by Lapham et al. (2014). Following Eq. 10 in Lapahm et al. (2014) (assuming 80% methane saturation for solid gas hydrate) and their observed rate of dissolution (15 cm/yr); we calculated a flux of 0.079 mol/m2/yr (Table 4.2).

At Mega Plume gas hydrate outcroppings were visible beneath cracks in the sediment, and at Birthday Candles large mounds with exposed hydrate were visible. In the 60 x 60 m photo survey at Mega Plume a crack of gas hydrate outcropping approximately 7.5 m long and 0.1 m wide was measured; an area of active bubble release was associated with the feature (Fig. 4.7d).

62 At Birthday Candles we observed several mounds where bubbles escaped from patches of gas hydrate (Fig. 4.7e-f). We had limited reference scales for estimating the size of many of the hydrate outcroppings at Birthday Candles. Based on the measureable outcrops, we set the average area of hydrate outcrops to be 0.75 m2 around each vent. We determine the total area of gas hydrate outcrops to be 5.25 m2 at Birthday Candles, and 6.0 m2 at Mega Plume based on the number of vents in each seep domain.

4.4.2.5 Additional flow

Benthic hydrocarbon exchange at brine pools and mussel beds are additional and potentially significant fluxes, but we do not have sufficient data to fully constrain their distribution and fluxes within each seep domain.

Estimates of methane flux across the seafloor at mussel beds were based on measurements using the MOSQUITO (Solomon et al. 2008). At brine pools, methane flux from the brine was determined using in situ mass spectrometry (Wankel et al. 2010). Wankel et al. (2010) calculated the in situ methane concentrations at different depths within the brine fluid (5, 20, and 80 cm) and estimated the diffusive flux to be 1.8 mol/m2/yr; concluding that a very large component of the methane flux escaped both aerobic and anaerobic oxidation. We uploaded images to ImageJ© software to measure the areas of two brine pools and one mussel bed. The laser pointers on the submersible (a known distance of 10 cm) and multiple measurements for each brine pool (3 separate measurements at each brine pool) and mussel bed (7 separate measurements) were averaged to minimize error.

4.4.3 Chemical analysis

The diagnostic biomarker ratios were calculated from chromatographic peak areas for the corresponding compounds observed in the oil samples (Fig. 4.8). Reproducibility of the analytical procedure was confirmed by the triplicate analysis of all samples and 10% accuracy. Of the diagnostic ratios Ts/Tm, H29/H30, H31S/H31R, H32S/H32R, H30/(H31+H32+H33+H34+H35), C27α β β /C29α β β steranes, C27β α /C29β α diasteranes are commonly used for identification, correlation, and differentiation of petroleum samples (Hood et al., 2002; Wang and Stout, 2007) (Table C.1).

63 As recommended by the Nordtest (Faksness et al., 2002), we calculated a correlation coefficient –a quantitative statistical parameter that is used to “fingerprint” the oil to evaluate matches between the samples. We found that the correlation coefficient based on the biomarker ratios for all samples were statistically significant at the 95% confidence level, except the Macondo crude oil (NIST2779) (Fig C.4). We established that the oil seeping out at the seafloor and reaching the sea surface as slicks is geochemically similar to that of the Holstein crude oil (Fig. 4.8 and C.5). These match with published results of biomarker analysis of samples from the upper Jurassic (Tithonian) source (Cole et al., 2001; Hood et al., 2002).

Fig. 4.7: Seafloor observations at Mega Plume and Birthday Candles. Yellow star is the same vent in each image a, b, c, and d. a 60 x 60 m Mola Mola AUV track at Mega Plume. Bacterial mats outlined in yellow. b Individual image from the Mola Mola mosaic (a). c Frame grab from VTLC. d Slice from Mola Mola survey. e Frame grab from ALVIN dive at Birthday Candles. f Close up image of a mound at Birthday Candles. g Mound showing gas hydrate dissociation leaving a hole of approximately 75 x 30 cm.

64 4.5 Discussion

The results from this study advance the understanding of fluid seepage systems in the GoM and elsewhere. Across the Northern GoM we see similar patterns in seismic data: salt structures, hints of BSR’s indicating a GHSZ, and chimneys (blanking zones) leading to the sediment interface (Macelloni et al., 2012; Roberts et al., 2010; Simonetti et al., 2013; Smith et al., 2014). The complex bathymetry of mounds, ridges, and mini-basins typical of the Northern GoM is generated by salt deformations, which are also responsible for trapping or creating migration conduits for oil and gas. Hydrocarbon migration to the seafloor affects the geomorphology, chemistry, and biological communities within seep zones (MacDonald et al., 2003; Sassen et al., 2004).

4.5.1 Assumptions and uncertainties

Our purpose was to incorporate all the available data in a systems approach that outlines the current knowledge, and data gaps. This approach creates a basis for further research by holistically incorporating aspects of the seep system, and delineating areas where more in-depth studies are necessary. We have compiled the data, and assigned values to different processes to begin constraining the hydrocarbon budget of GC600. In doing so, assumptions were made where data were lacking. In this section we address those assumptions.

To estimate the overall diffuse hydrocarbon seepage, we considered the area of bacterial mats measured within the 60 x 60 m Mola Mola survey (Fig. 4.7a and C.6). The value we assign to represent bacterial mat coverage (104 m2) is a minimum estimate, because diffusive flow indicated by bacterial mats can often be found tens of meters from focused vents (Vardaro et al., 2006) so may have existed outside the survey area and been missed. We assume that the entire 104 m2 area around a focused vent was fully covered by bacterial mats. Larger scale AUV photo surveys would be necessary to constrain this value more accurately.

Hydrocarbon flux estimates at brine pools and mussel beds are associated with large uncertainties. We incorporated them to address and identify that they are part of a biological filter and to underscore the need for more information on their distribution patterns at seeps. Our estimates (Fig. 4.6 and Table 4.2) are based on two brine pools and one mussel bed, which is not representative of the total number density of these habitats at GC600 or other seeps. Thus, while

65 the available information suggests that their effect is small (total of 7.8 mol/yr for brine pools and 0.3 mol/yr for mussel beds compared to total out flow of 7.6 x 106), further research would be required to determine more precise flux regimes in these habitats.

Fig. 4.8: GC/APCI-MS/MS of an oil sample from the Mega Plume vent, compared to a sample from the Holstein reservoir sample.

66 The subbottom data confirms that sediments in this area are gas-charged (Fig. 4.5b). Since we do not have heat or salinity profiles available for GC600, we can neither constrain the proportion of free gas nor quantify the amount of solid gas hydrate within the blanking zone (Ruppel et al., 2005). We can confirm however, that there is or has been gas hydrate accumulation and growth using the backscatter data (Fig. 4.3b) (indicating carbonate hardgrounds, gas charged sediments, and hydrate outcrops), in conjunction with the inflated mounds in the bathymetry (Fig. 4.3a) that are ground-truthed by video and photo surveys at the sea floor (Fig. 4.7a-g).

The bathymetry and high amplitude maps (Fig. 4.4a and c) show that seep domains are inflated mounds within the fault system (Fig. C.1). We suggest that the reasons the mounds inflate in these specific positions must be related to hydrate buildup and the local GHSZ. In this area the GHSZ extends to the BSR at approximately 305 mbsf. Additionally, since the mounds do not follow the general fault trend, it is possible that the positioning of the mounds could be caused by the intersection of deep and shallow faults.

4.5.2 Migration from source rock

The GC600 hydrocarbon system is derived from the Upper Jurassic (Tithonian) source rock (Hood et al., 2002). The geochemical signatures of the oil samples collected were diagnostically similar which agrees with the published data of GoM oil families (Cole et al., 2001; Hood et al., 2002). Although we cannot determine the exact reservoir that is feeding the GC600 seep zone, we could infer a relationship between biomarkers from oil collected at a vent and a reservoir sample (Fig. 4.8) that match Tithonian oil family biomarker distributions and not the other oil families in the GoM (i.e. Macondo which belongs to another oil family Fig C.4, C.5). With this information in addition to the geophysical seismic data we interpreted the most plausible migration path of hydrocarbons from source rock to seafloor (Fig. 4.4b).

Areas of vertical or collapsed salt structures create more effective migration conduits than faults (Hood et al., 2002). Therefore, the interpreted hole in the salt canopy creates an opening and effective migration conduit for the fluids from the reservoir to reach the sea floor. For the migration of hydrocarbons above the salt body, we interpret separate surficial faults feeding into the two separate seep domains: one large fault with a branching arm around Mega Plume and a smaller fault leading to Birthday Candles (Fig. 4.4a, d). Wilson et al. (2014) conclude that hydrates are

67 likely constrained to sediments directly influenced by major faults. Based on the geomorphology (presence of gas hydrates Fig. 4.6 and 4.7), and geophysics (fault lines visible in seismic data Fig. 4.4a, c) we can confirm that there are two major faults that lead to the Birthday Candles and Mega Plume domain. However, based on the position of the mounds, it remains uncertain whether or not the surficial faults or deeper intersecting faults that are the main conduit for hydrocarbons to these seep specific seep domains.

4.5.3 Hydrate growth

Gas hydrates alter the physical, geophysical, and geochemical properties of sediments and affect the benthic communities around seep sites (MacDonald et al., 2010). As gas hydrate mounds grow, layers of gas hydrate push the mounds up causing the fluid to escape along the edges, where there is less clogging (Leifer and Boles, 2005; MacDonald et al., 1994; Römer et al., 2012).

We specifically observed how seepage affected chemical and biological processes at the seafloor through hydrate formation and dissociation in Fig. 4.7f-g. Lapham et al. (2010) described the “push-up-pop” model which implied that shallow gas hydrates remain stable by dissolving at exposed surfaces at the same rate as they formed within subsurface sediments. Assuming there is a sufficient in-flow of methane and the out-flow does not exceed the source, then the mounds that we see in Fig. 4.7f are quite stable. But if the dissolution of the exposed gas hydrate continues without a constant in-flow, the gas hydrate will dissociate and leave a hole with carbonate edges as seen in Fig. 4.7g. This process may explain the numerous pockmarks seen in the bathymetry (Fig. 4.4a and C.2).

4.5.4 Provisional hydrocarbon budget

We constrained the fate of hydrocarbons by identifying each of the following processes. 1) Sequestration of hydrocarbons in gas hydrate mound growth; 2) gas hydrate dissociation (e.g. exposed gas hydrate outcrops); 3) focused venting (e.g. bubble streams); 4) diffusive or biological consumption (e.g. bacterial mats, mussel beds). Based on our results, the overall total mass out- flow of hydrocarbons from the system were 3 orders of magnitude smaller than the total mass in- flow (Fig. 4.6, Table 4.2). The excess influx into the surface sediment is consistent with the gas saturated sediments within the blanking zones. If all the gas flowing into the system was converted

68 to gas hydrate, we calculate a rate of gas hydrate volume increase of 376 m3/day at Birthday Candles and 378 m3/day at Mega Plume. This upper limit corresponds to an expansion of 57.4 cm/yr at Birthday Candles and 57.0 cm/yr at Mega Plume if distributed over the area of the respective blanking zones.

There is a fundamental mismatch between the hydrocarbons flowing into the system, and the hydrocarbons that leave the system through each measurable seafloor process. Below, we list the possible reasons to explain this mismatch. First, it is probable that we are significantly underestimating the contribution of biological consumption. We only account for biology observed in the available video data and use the methane flux rates from the literature. Second, we are underestimating the growth and decay of gas hydrate mounds. It is difficult to directly measure gas hydrate dissociation in situ (Lapham et al., 2014) and most values found in the literature are based on measurements made in the lab. Pockmarks in the mounded bathymetry (Fig. 4.3a, C.2), and observations at the sea floor (Fig. 4.7g) indicate the growth and dissociation of shallow gas hydrate mounds; however, with these data we cannot constrain the time scale of this process. Third, we could not account for exactly how much sub-surface gas hydrate build-up there is. If all the “missing hydrocarbon” (hydrocarbons we could not account for) (Fig. 4.6) entering the system were converted to gas hydrate, we would see seep domain growth of approximately 0.57 m/yr, which is unlikely based on long term in situ observations at this site (in depth studies at this site range from 2010 to 2016). Additionally, the BSR is at approximately 305 mbsf (Fig. 4.4c), and gas hydrate accumulation can be intermittent within the hydrate stability zone from the BSR to sea floor (Andreassen et al., 1997; Ruppel et al., 2005). Finally, the large influx of hydrocarbons into the system from below may be grossly overestimated. Gravity core collections to determine the geothermal and salinity gradient in these specific areas may improve modeled values of hydrocarbon in-flow in this specific area.

There are emerging studies on the chemosynthetic communities in the deep sea. Levin et al. (2016) explain that seeps are no longer viewed as isolated areas, but important aspects to the overarching deep sea ecosystem. The interaction of the chemosynthetic communities at seep zones affect the evolution of the ecosystems on the sea floor, water column, and global geochemical cycles. The connection between chemosynthetic fauna and surrounding background ecosystems is largely unknown (Levin et al., 2016). With the many uncertainties still in place, we use our systems

69 approach to attempt to address some of the key aspects within this energy budget. We posit that the biological communities play a much larger role in the sequestration of hydrocarbons entering the system then we are able to constrain (Fig. 4.6).

4.6 Conclusion

The in-flow of hydrocarbons at the sediment-water column interface manipulates the geomorphology and biology of the system creating unique ecosystems of checks and balances. By combining the different data sets available at the GC600 seep site, we attempted to identify each hydrocarbon pool and developed a budget that accounts for the incoming hydrocarbon flow. We found that there was a disconnect between the total mass in-flow (2.07 x 109 mol/yr) and total mass out-flow (7.56 x 106 mol/yr). This leaves a “missing hydrocarbon” value of 2.06 x 109 mol/yr. We posit that some of this is used for gas hydrate accumulation, and that we are likely significantly underestimating the biological consumption component of this seep hydrocarbon budget.

Even with the stated assumptions and uncertainties, we have none the less created a base-line including quantitative measurements for which further studies can use as a base line to fill data gaps. Additionally, models can be designed to address some of the uncertainties faced when constraining the biological filter and gas hydrate dynamics, which can be difficult to address experimentally.

This is the first work of its kind in the GoM where we have had such a unique opportunity to combine a variety of data sets of different scales and resolutions ranging across multiple disciplines. With these data we have presented a semi quantitative interpolation of observations and described the connections between each dataset. These connections permit a holistic systems approach for describing natural dynamics within a specific seep system, and can be used as an exemplary springboard for further research.

70 CHAPTER 5

DESCRIPTIVE OVERVIEW OF METAZOANS IN TWO GULF OF MEXICO SEEP ZONES

i. In beginning stages to be submitted as a “LETTER” (Journal to be decided) ii. Authors: C. Johansen, I.R. MacDonald

5.1 Introduction

The Gulf of Mexico (GoM) is a leaky basin where oil and gas escape from subbottom reservoirs and are released into the water column; these characteristic features are known as natural [hydrocarbon] seeps (Johansen et al., Submitted). Natural seeps provide a source of energy for chemosynthetic communities, resulting in an abundance of life in seep zones compared to the otherwise barren desserts of the deep sea (Cordes et al., 2010; Fisher et al., 2007; MacDonald, 1998; Orcutt et al., 2004). Natural seeps are an important feature for deep sea organisms, since it provides energy that is crucial for life to persist. In the upper sediments hydrocarbons are affected by various biological processes such as anaerobic oxidation of methane (AOM), and sulfate reduction (Boetius et al., 2005; Joye et al., 2004). Additionally, within the gas hydrate stability zone, solid gas hydrate is formed which affects the temperature and salinity gradients in the sediment column (Macelloni et al., 2015; Ruppel et al., 2005). These processes are unique to active seep zones and are what set apart the biological communities in this study from other biologically active sites in the GoM. Here we identify and describe the different mega fauna that were observed at each natural seep visited and use this information to determine the evolutionary stage of the seep. In particular, we discuss Hesiocaeca methanicola (ice worm) which, to the present day, has only been discovered in the GoM (Desbruyères and Toulmond, 1998; Fisher et al., 2000). Using autonomous video time lapse camera (VTLC) observations, we were able to monitor natural seeps for extended periods of time (days to months). We observed ice worms burrowing in gas hydrate outcrops, fish feeding on thick bacterial mats that have not been disturbed by submersibles, abundant swarms of annelids, and curious crabs and eels visiting bubble streams. These results provide an in situ, “uninterrupted” (not affected by the presence of an underwater vehicle) view into the behavior of seep communities.

71 5.2 Methods and importance

We used the VTLC to observe the behavior of metazoans at natural seep sites on the mid-slope at two specific seep zones in the northern Gulf of Mexico (GC600, depth: ~1200 m and MC118, depth: ~850 m). Multiple deployments of the VTLC for extended periods of time give us video data ranging from 3 hours to 26 days to observe and describe the temporal and spatial variability of biological activity. In addition to VTLC data, we analyzed DSV ALVIN dive videos to complete the overview of biological distribution and activity covering larger spatial scales. The migration pathways and escape zones of hydrocarbons at the sea floor control the biological distribution (Cordes et al., 2010; Johansen et al., in prep; Wilson et al., 2014). In turn, the biological communities affect and alter the sediment properties such as carbonate precipitation forming hard grounds (Boetius et al., 2000; Feng and Roberts, 2010; Joye et al., 2004; Lessard-Pilon et al., 2010; Roberts and Carney, 1997), that create anchoring points for mussel beds and later tube worms (Bergquist et al., 2003; MacDonald et al., 2003). In fact, carbonate precipitation due to active seepage may well be the starting point for seep maturation and can tell us something about the evolution of natural seeps (Bergquist et al., 2003; Cordes et al., 2005; Lessard-Pilon et al., 2010). With a basic understanding of the general land scape of seep zones, we can determine the procession of seep zone development and relative age of seep sites based on the biological communities.

5.3 Results and discussion

The most common metazoans that we observed at the mid-slope (850 – 1220 m) natural hydrocarbon seeps visited are listed in Table 5.1. Carney (2010) states that the fauna found below (lower slope) and above (upper slope) 1000 m are very different. Within this definition, the sites we visited give an example of the upper slope (MC118 ~850 m) and lower slope (GC600 ~1200 m). We found some differences between the fauna at both sites. Namely, on the upper slope site (MC118) we saw a higher abundance of fish around the vent, and also saw gastropods that were not observed at the lower slope site (GC600) at all. Additionally, we did not observe any ice worms at MC118, however, this may be due to camera placing, and therefore we cannot rule out their presence.

72 Table 5.1: List of animals observed at visited seep sites Besides the obvious venting of bubbles

73 Unique interactions between sediment microoganisms and the animals found at seep sites, in addition to high methane concentrations found in oily and microbial-mat-inhabited sediments, suggests a connection between seep and subsurface fluid flow (Joye et al., 2010; Wilson et al., 2014). The sulfate reducing Beggiatoa are effective mat-forming organisms that grow at oxic- anoxic interfaces (Møller et al., 1985). The mat thickness can range from less than a mm thin to several cm’s thick depending on the dynamics and stability of the sulfide-oxidant interface (Teske and Nelson, 2006). Beggiatoa mats are sensitive to fluctuations in oxygen concentration and contract into the diffusive boundary layer when there is high oxygen concentration, and expand after the “oxygen stress” has passed (Møller et al., 1985). This behavior supports our observations of bacterial mat “disappearance” when approaching the seafloor with underwater vehicles. The movement of the vehicle, in addition to the impact when it touches down on the seafloor, likely increases oxygen flow causing the Beggiatoa to contract. We were able to prove this with our video data from a 26-day VTLC deployment at a vent named Mega Plume in GC600 (Johansen et al., Submitted). This data demonstrated that after agitation by the ROV or submersible used for placement of VTLC, it took approximately 3 days for bacteria mat coverage to thicken, and approximately 5 days to reach the thickness that persists until the end of the video footage. When the submersible returned to pick up the VTLC, the bacteria mats had all contracted again (Fig. 5.1).

The contraction and expansion of Beggiatoa mats due to vehicular interference is important to consider, because bacterial mat distributions have been described as being patchy and sparsely distributed by some (Lloyd et al., 2010). Increased bacterial mat patchiness, with increased depth, can be attributed to lower sulfate reduction and AOM rates (10 – 1000 times) in deeper areas (Joye et al., 2010). However, what hasn’t been considered in these studies is the persistence of bacteria mats and how they develop or change over time when there are no anthropogenic interruptions. With the VTLC, we were able to capture the natural progression.

Many small annelids of less than 1 cm in length were observed actively jumping around like lice. From the available data sets, the annelids cannot be identified in more detail than the phylum level. These organisms were observed on and around hydrated out crops, yet were more commonly found on the sediments. We did not observe any predation on the annelids in the VTLC videos.

74 Fig. 5.1: Progression of bacterial mat coverage and how it changes over time. a bacterial mat coverage at the Mega Plume site 1 day after initial deployment, b 5 days after initial deployment, c 16 days after initial deployment, and finally d bacterial mat coverage 25 days after initial deployment.

Mussels were found in areas with larger carbonate hard grounds compared to the areas of gas hydrate outcroppings with active bubbling a couple of meters away. These are possibly areas where active bubbling had ceased and gas hydrate outcrops had already dissociated leaving behind carbonates. Mussels with their methantrophic symbionts are typically considered primary colonists of seep communities (Bergquist et al., 2003; Cordes et al., 2010). The general succession of seep communities is thought to start with the formation of carbonate hardgrounds when bubbling ceases and gas hydrate dissociates, followed by mussel colonies that continue to influence the growth of authigenic carbonates, and finally when sulfide seepage declines, tubeworms colonies dominate (Bergquist et al., 2003; Cordes et al., 2010; Feng and Roberts, 2010; Lessard-Pilon et al., 2010).

Following this seep succession pattern, our VTLC’s were deployed at the initial stages of seep community formation, where active bubbling is still occurring and carbonate hard grounds were starting to form with the dissociation of gas hydrate outcrops and bacteria activity. At each of our sites, we did not observe any tube worm colonies within a 2 km radius around the vent of interest. We could, however, see hints of this seep succession at one of the vents in GC600 (a.k.a. Birthday

75 Candles) where seepage had slowed, and mussel beds were present a couple of meters from where slow bubble release was still occurring. At another seep in GC00 (a.k.a. Mega Plume) we observed no mussel colonies forming within meters from the vent indicating a “younger” seep domain. Active bubble venting is ephemeral persisting on a decadal scale (Garcia-Pineda et al., 2010; MacDonald et al., 2005b) and as we have observed by long term monitoring of the Mega Plume vent in GC600 (from 2012 – 2016), it has recently ceased to release bubbles (M. Woolsey, personal comm.), which possibly sets up the area for the next stage of community succession.

Directly adjacent to the bubbling vents at gas hydrate outcrops, we saw mostly dead clam shells scattered on the ground. Live clams were commonly observed farther away from the active vent site. The live clams are mobile and were seen to move quite far distances (on average 50 cm) which was measured by their lebensporen (Fig. 5.2). However, we were not able to determine the rate at which the clams can move.

Mobile fauna such as fish, eels, and crabs, are harder to keep track of as they would move in and out of the VTLC’s field of view. However, we were able to identify the different types of metazoans that frequent cold seeps (Table 5.1). These animals are referred to as “vagrant” animals, suggesting that they are short-term residents, living and eating both within and outside of seep zones (Carney, 2010). Vagrant animals can consist of detritus feeders, predators, scavengers, and suspension feeders (Carney, 2010). We observed all organisms listed in Table 5.1. Of particular behavioral interest were, fish (Dicrolene kanazawai) feeding on bacteria mats (Fig. 5.3a), the reaction of an eel (Synaphobranchus spp.) when interacting with the bubble stream (Fig. 5.3b), gastropods slithering along (Fig. 5.3c), crabs approaching bubbles (Fig. 5.3d), and of course, the sheer abundance of ice worms.

The ice worm (Hesiocaeca methanicola) was first discovered during a research cruise in July 1997. They are a pink polychaete approximately 2-5 cm in length. Both male and female sexes are separate, however; it is difficult to distinguish with the naked eye. Both sexes undergo broadcast spawning, but the males spawn exclusively through the anus, which is a behavior that was previously unknown in polychaetes (Eckelbarger et al., 2001). As adults, they seem to go through a pattern of continuous reproduction producing planktotrophic larvae with a planktonic dispersal phase of a few weeks (Eckelbarger et al., 2001).

76 Fig. 5.2: Example of the movement of live clams and the tracks (lebensporen) they leave behind.

Fig. 5.3: Images of some of the different mobile animals observed. a is a fish eating a bacteria mat, b is an eel that comes into contact with the bubble stream, , c are three gastropods that were viewed, and d is a crab that were commonly seen entering the VTLC’s field of view.

77 H. methanicola are the first non-microbial life that has been found living directly on gas hydrate structures. They crawl around on the gas hydrate creating little burrows through which they travel, or little depressions in which they reside. Based on our VTLC data, they move at slow paces. Fisher et al. (2000) suggest that the movement of H. methanicola on the gas hydrate outcroppings may supply oxygen to hydrates and increase gas hydrate dissociation. They are thought to go down to at least 10 cm below the sea floor, possibly deeper, and have a tolerance to anoxic conditions for about 48-96 h (Eckelbarger et al., 2001). They do not have any known predators, which seems to allow them to keep growing in such abundance. (Fig. 5.4).

Fig. 5.4: Close up of a gas hydrate outcrop that is infested with Hesiocaeca methanicola (ice worms). Little burrows and depressions in the gas hydrate made by the ice worms are quite evident.

Prokaryotes are the only known organisms to utilize reduced gases as energy sources or metabolize crude oil. Since there is no evidence of chemoautotrophic symbionts in H. methanicola and they have a functioning digestive tract it is thought that they obtain their bulk nutrition by grazing on the free living bacteria that colonize on the surface of the gas hydrate. This was confirmed by testing the ice worms tissue stable isotope value and finding that it was consistent with the microbial food source (Eckelbarger et al., 2001).

78 So far H. methanicola has only been found in the GoM. They have been seen in large abundances mostly in the Northern Gulf, but in 2015 research teams spotted some in the Southern GoM as well (I.R. MacDonald, personal comm.). Their closest co-gener is Hesiocaeca hessleri, which is found at the Mariana Back Arc hydrothermal vent system, which suggests that this genus has adapted to live in areas with increased fluid flow where chemosynthetic bacteria are abundant for the Hesiocaeca to feed on.

Using the measurements by Fisher et al. (2000) who calculated approximately 2500 ice worms per m2 of gas hydrate, and Johansen et al. (in prep) who calculated the total area of gas hydrate outcrops in GC600 to be 11.3 m2, we calculated that there are approximately 2.8 x 104 ice worms that can be seen in GC600. Note – this value is based on the outcrops of gas hydrate measured, and does not take into account the ice worms in the sediments and those that cannot be seen burrowing in the gas hydrate covered by sediments.

5.4 Conclusion

The locations where we deployed the VTLC were at active vent sites where oil and gas bubbles were escaping from gas hydrate outcrops. Based on the fauna in these areas, we were documenting the beginning stages of seep communities (Bergquist et al., 2003; Feng and Roberts, 2010; Lessard-Pilon et al., 2010). With high methane concentrations in the sediments that may be too toxic for some organisms (Joye et al., 2010), these immature seep sites are characterized by bacteria mat coverage and ice worm infested gas hydrate outcrops from which oily and gaseous bubbles escape. Carbonate hardgrounds start to form from sulfate reduction coupled to AOM (Boetius et al., 2000; Joye et al., 2004) and dissociation of gas hydrates (Feng et al., 2010).

Using the VTLC we were able to examine animal behavior without disturbances such as bacterial mat coverage directly adjacent to vents, including larger mobile species feeding on the bacterial mats, and interacting with bubble streams. Finally, we got a close-up view of ice worms burrowing in gas hydrate out crops and determined the approximate number of ice worms that could possibly be present in the GoM. Where the ice worms go once all the gas hydrate dissociates and the seep community evolves is still an open question.

79 CHAPTER 6

CONCLUSIONS

Since the discovery of the GoM, it has become an area of extensive exploration. Detailed study of the entire basin was expedited by oil companies to exploit the oil trapped in reservoirs at different stratigraphic layers. With the advent of seismic data acquisition, it was possible to gain a more comprehensive understanding of the formation and structure of the basin. Throughout time, altering sedimentation rates and salt deposition have affected the basin structure. Evaporite deposits created large salt structures that continue to deform the basin creating conduits for hydrocarbon migration.

For oil production, a source rock, reservoir, seal, and trapping mechanism are necessary. These conditions are all met in the GoM, therefore making it a unique basin in that it is in constant dynamic disequilibrium, which facilitates hydrocarbon leakage. In the northern slope of the GoM salt movement deforms sedimentary layering, causing a chaotic seal and trapping system, which allows for the natural seepage of oil and gas to the sea floor. This is an important area of interest, because the oil that “leaks” may eventually make it up to the sea surface and expel methane to the atmosphere; a source of carbon that should be considered in the global carbon cycle. It is essential to determine the flux and volume of oil and gas being released from natural seeps, to determine the extent to which it may affect the climate, act as clues of reservoirs for oil producing companies, and an important source of energy for benthic ecosystems.

The amount of natural oil being released from the seafloor can be quantified by determining the source of the oil, the conduits through which it travels, and flow rate and magnitude at individual seeps that act as exit points. Individual seeps represent the leading edge of large-scale natural hydrocarbon seepage. Better understanding of the seep “plumbing system” and detailed description of the benthic community provides insight into the differences among separate seep sites across the basin, and of the way seep systems develop over time.

Our research provides the first benchmark for estimating the temporal variability of oil and gas bubble release rates using video data from individual vents. We developed a reproducible and adaptable image processing method to quantify bubble release rates in various deep-sea

80 environments and estimated bubble size and flow rates. By collecting high definition video footage over extended periods of time (3 h -26 d), we accounted for temporal variability of bubble composition and release rates. With prolonged video deployments, we defined a bubble size distribution and quantified a range of bubble release rates. Oily bubbles were larger and released at slower rates than gaseous bubbles.

By combining the different data sets, we are able to stitch together an integrated schematic model to describe the processes involved in fluid migration. For this systematic approach, we examined various data sets for every stage of the migration process, and then interpreted how each process was interrelated and reliant on the other. The buoyant nature of oil and gas naturally force their upward migration, which is directed by the positions of salt structures and faults. The in-flow of hydrocarbons at the sediment-water column interface manipulates the geomorphology and biology creating unique ecosystems of checks and balances. We attempted to identify each hydrocarbon pool and developed a budget that accounts for the incoming hydrocarbon flow.

With these data we have presented a semi-quantitative interpolation of observations and described the connections between each dataset. We found a fundamental mismatch between the hydrocarbons flowing into the system, and the hydrocarbons that leave the system through each measurable seafloor process. There are multiple reasons for this. First, it is probable that we are significantly underestimating the contribution of biological consumption. We only accounted for biology observed in the available video data and used the methane flux rates from the literature. Second, the underestimation of gas hydrate dissociation. It is difficult to directly measure gas hydrate dissociation in situ (Lapham et al., 2014) and most values found in the literature are based on measurements made in the lab. Third, we could not account for exactly how much sub-surface gas hydrate build-up there is. Based on our measurements, if all the unaccounted for gas entering the system was converted to gas hydrate, we would see a growth of 0.57 m/yr, which is unlikely based on observations. Finally, the large influx of hydrocarbons into the system from below may be grossly overestimated. Gravity core collections to determine the geothermal and salinity gradient in these specific areas may improve modeled values of hydrocarbon in-flow.

The locations where we deployed the VTLC were at active vent sites where oil and gas bubbles were escaping from gas hydrate outcrops. Based on the fauna in these areas, we were documenting

81 the beginning stages of seep communities. With high methane concentrations in the sediments, these infant seep sites were characterized by bacteria mat coverage and ice worm infested gas hydrate outcrops from which oily and gaseous bubbles escaped. Carbonate precipitates start to form from sulfate reduction coupled to AOM and dissociation of gas hydrates.

Using the VTLC we were able to examine animal behavior without disturbances such as bacterial mat coverage directly adjacent to vents, including larger mobile species feeding on the bacterial mats and interacting with bubble streams. In addition, we got a close-up view of ice worms burrowing in gas hydrate outcrops and estimated the size of the ice worm population to be 2.8 x 104 in GC600. Where the ice worms go after all the gas hydrate dissociates and the seep community evolves is still an open question.

There are emerging studies on the chemosynthetic communities in the deep sea. Levin et al. (2016) explain that seeps are no longer viewed as isolated areas, but important aspects to the overarching deep sea ecosystem. The interaction of the chemosynthetic communities at seep zones affect the evolution of the ecosystems on the sea floor, water column, and global geochemical cycles. The connection between chemosynthetic fauna and surrounding background ecosystems is largely unknown (Levin et al., 2016). With the many uncertainties still in place, we use our systems approach to attempt to address some of the key aspects within this energy budget.

This research addressed multiple approaches to understand the dynamics of natural hydrocarbon seeps. We attempted to quantify and describe the different processes involved in the overall mechanisms of the large scale “plumbing system” at specific seep sites in the GoM that can hopefully be used as a model for further research on natural seeps elsewhere.

82 APPENDIX A

VTLC DEPLOYMENT METADATA

Table 1A: Meta data for analyzed VTLC deployments

83 APPENDIX B

MATLAB CODE FOR BUBBLE COUNTING ALGORITHM

%% DEFINE PATHS % THIS SECTION AND TXT. FILE IS THE ONLY PART THAT SHOULD BE MODIFIED BY USER % Specify video file directory % Directory_path='G:\MATLAB\Folder\Files\';

if ~strcmp(Directory_path(end),sep), Directory_path = [Directory_path sep]; end

% Add external libraries to the search path addpath('G:\MATLAB\CODES');

%% Get list of sub-directories dirData = dir(Directory_path); % Get the data for the current directory dirIndex = [dirData.isdir]; % Find the index for directories dirList = {dirData(dirIndex).name}; % Get a list of the sub-directories dirList = dirList(~ismember(dirList,{'.','..'})); % remove '.' and '..' directories

%% Get date/time stamp for the output files dt = clock; strdate = sprintf('%4i%02i%02i_%02i%02i%02i',dt(1),dt(2),dt(3),dt(4),dt(5),round(dt(6)) );

%% Prepare Output folder % Create output folder if it does not exists outpath = [ Directory_path 'OutputFiles' sep ]; if exist(outpath,'dir')~=7, mkdir(outpath); end

%% Create Global Summary File gsFile = [ outpath strdate '_GlobalSummary.txt' ]; fidGS = fopen(gsFile,'w'); str = ['Folder',char(9),'Frames',char(9),'DurationInSeconds',char(9),...

'LowEstimate',char(9),'LowBubblePerSec',char(9),'MediumEstimate',char(9),... 'MediumBubblePerSec',char(9),'HighEstimate',char(9),'HighBubblePerSec']; fprintf(fidGS,'%s\r\n',str);

%% Loop through the folders for subdir = dirList

clear('allLines','imFirst','imLast');

subdir_txt = [ Directory_path subdir{1} '.txt' ];

if exist(subdir_txt,'file')==2 % check if text file with variables exists for this subfolder

84 varfile = subdir_txt; else varfile = [ Directory_path 'DefaultVariables.txt' ]; end

fprintf(1,'\nReading sub-directory ''%s'' and creating image list...',subdir{1});

% Open text file and read variables fid = fopen(varfile); while ~feof(fid) tline = fgetl(fid); % read the next line from the text file eval(tline); % run the command written in the line end fclose(fid);

subdir_path = [ Directory_path subdir{1} sep ]; subdirData = dir(subdir_path); % Get the data for the current directory subdirIndex = [subdirData.isdir]; % Find the index for directories fileList = {subdirData(~subdirIndex).name}; % Get a list of the files fileList = sort(fileList); % sort list in alphabetical order imList = []; for imstr = fileList try imfinfo([subdir_path imstr{1}]); imList = [ imList imstr ]; end end fprintf(1,'DONE\n',imstr{1});

% Jump to next subfolder if the current folder does not contain images if isempty(imList) || strcmp(subdir{1},'OutputFiles')==1 continue; end

if exist('imFirst','var')~=1, imFirst = 1; end if exist('imLast','var')~=1, imLast = numel(imList); end nmax = numel(imFirst:imLast);

% Create cropped images if crop_images == 1

crop_path = [ subdir_path 'cropped_images\' ]; if exist(crop_path,'dir')==7, rmdir(crop_path,'s'); end mkdir(crop_path);

for k = imFirst:imLast fprintf(1,'cropping frame: %i / %i\n',k,nmax); inframe = [subdir_path imList{k}]; ind = strfind(imList{k},'.'); outframe = [crop_path imList{k}(1:ind(end)) 'tif']; croppedFrame = imcrop(max(imread(inframe),[],3),crop_window); croppedFrame(hl,:) = 0; imwrite(croppedFrame,outframe,'tiff');

85 end

end

%% Prepare folders for difference images if diff_images == 1 diff_path = [ subdir_path 'diff_images\' ]; if exist(diff_path,'dir')==7, rmdir(diff_path,'s'); end mkdir(diff_path);

selec_path = [ subdir_path 'cropped_images_selection\' ]; if exist(selec_path,'dir')==7, rmdir(selec_path,'s'); end mkdir(selec_path); end

------%% Main bubble counting loop cnt = 0; % counter % Determine frame sampling interval to avoid double counting bubbles % between two frames fsi = ceil(avg_BPH / rising_speed * frames_per_sec);

for k1 = imFirst:fsi:imLast

cnt = cnt + 1;

fprintf(1,'Counting bubbles in frame: %i / %i\n',k1,nmax);

%bring in image 2 inframe = [subdir_path imList{k1}]; img_2 = imcrop(max(imread(inframe),[],3),crop_window);

if cnt > 1

%subtract image 1 from image 2 to get only bubbles in screen img_diff = img_2 - img_1;

%% Create difference images if diff_images == 1 diff_file = sprintf('%sdiff_%06i.tif',diff_path,cnt); diff_im = img_diff; diff_im(diff_im < 0) = 0; diff_im(hl,:) = 255; imwrite(diff_im,diff_file,'tiff'); end

86 % Iterate over all lines between the lower and upper lines cnt2 = 0; for k2 = min(hl):max(hl) % from upper line to lower line cnt2 = cnt2 + 1;

bubbleCount = img_diff(k2,:); bubbleCount(bubbleCount

bubbleCount = img_diff(k2,:); bubbleCount(bubbleCount

bubbleCount = img_diff(k2,:); bubbleCount(bubbleCount

if diff_images == 1 ind = strfind(imList{k1},'.'); outframe = [selec_path imList{k1}(1:ind(end)) 'tif']; outim = img_2; outim(hl,:) = 0; imwrite(outim,outframe,'tiff'); end

%image one replaced by image 2 to continue loop with next pic. img_1 = img_2;

end

if exist('allLines','var')~=1, continue; end

87 %% Summary file sumLine = squeeze(sum(allLines,1))';

summaryFile = [ outpath strdate '_' subdir{1} '_Summary.txt' ]; fidout = fopen(summaryFile,'w');

fprintf(fidout,'SUMMARY OF THE BUBBLE COUNTING FOR DIRECTORY: %s\r\n',subdir{1});

fprintf(fidout,'\r\n**********************\r\n'); fprintf(fidout,'TOTAL BUBBLE COUNT:\r\n'); fprintf(fidout,'**********************\r\n');

fprintf(fidout,'\r\nBubble count estimates (mean values over all lines):\r\n'); fprintf(fidout,'- Low: %i\r\n',round(mean(sumLine(:,1)))); fprintf(fidout,'- Medium: %i\r\n',round(mean(sumLine(:,2)))); fprintf(fidout,'- High: %i\r\n',round(mean(sumLine(:,3))));

fid = fopen(varfile); fprintf(fidout,'\r\n'); fprintf(fidout,'\r\n*****************\r\n'); fprintf(fidout,'SETTINGS USED:\r\n'); fprintf(fidout,'*****************\r\n'); while ~feof(fid) tline = fgetl(fid); % read the next line from the text file if ~isempty(tline) && ~strcmp(tline(1),'%') fprintf(fidout,'%s\r\n',tline); end end fclose(fid);

fclose(fidout);

%% Normalise the values to have the countings in Bubble/Sec allLinesPerSec = allLines / fsi * frames_per_sec; sumLinePerSec = sumLine / fsi * frames_per_sec;

88 %% Data files

% Save the Matlab variables allLinesFile = [ outpath strdate '_' subdir{1} '_allLinesData.mat' ]; save(allLinesFile,'allLines','allLinesPerSec','sumLine','sumLinePerSec');

% Save the mean values into a text file (i.e. mean of all lines) lineFile = [ outpath strdate '_' subdir{1} '_lineData.txt' ]; fidout = fopen(lineFile,'w'); fprintf(fidout,'LineNo\tLow\tMedium\tHigh\tLowPerSec\tMediumPerSec\tHighPerSe c\r\n'); fclose(fidout); dlmwrite(lineFile, [(min(hl):max(hl))' sumLine sumLinePerSec], ... '-append', 'delimiter', '\t', 'newline','pc');

%% Write in Global Summary File secmax = nmax / frames_per_sec; % duration fprintf(fidGS,'%s\t%i\t%f\t%i\t%f\t%i\t%f\t%i\t%f\r\n',... subdir{1}, nmax, secmax, ... mean(sumLine(:,1)), mean(sumLine(:,1))/secmax,... mean(sumLine(:,2)), mean(sumLine(:,2))/secmax,... mean(sumLine(:,3)), mean(sumLine(:,3))/secmax);

end fclose(fidGS); fprintf(1,'\nFinished!\n');

89 APPENDIX C

SUPPLEMENTAL FIGURES FROM CH. 4

Table C1: Biomarker ratios (Ts/Tm, H29/H30, H31S/H31R, H32S/H32R, H30/Σ (H31-H35), C27α β β /C29αββ steranes, and C27β α /C29β α diasteranes) for Megaplume oil seep, Megaplume oil slick, Birthday Candles oil slick, Holstein crude oil, and Macondo crude oil (NIST2779). The results are expressed as average values from triplicate analysis ± the standard deviation.

Ts/T H29/H H31S/H3 H32S/H3 H30/Σ (H3 C27α β β /C29α C27β α /C29βα Sample m 30 1R 2R 1-H35) β β steranes diasteranes

0.83 1.16 1.22 1.49 0.45 0.73 1.03 Megaplume ±0.05 ±0.12 ±0.06 ±0.04 ±0.04 ±0.07 ±0.08 oil seep

0.89 1.04 1.21 1.58 0.50 0.62 0.89 Megaplume ±0.07 ±0.10 ±0.11 ±0.12 ±0.03 ±0.06 ±0.07 oil slick

Birthday 0.81 1.26 1.18 1.33 0.62 0.68 0.87 Candles ±0.07 ±0.10 ±0.08 ±0.12 ±0.03 ±0.05 ±0.03 slick

Holstein 0.83 1.22 1.27 1.29 0.5 0.66 1.02 ±0.08 ±0.11 ±0.05 ±0.1 ±0.03 ±0.04 ±0.10

1.42 0.52 1.17 1.48 0.65 0.68 0.94 NIST2779 ±0.05 ±0.04 ±0.09 ±0.06 ±0.03 ±0.06 ±0.02

90 Fig. C.1.: Mega Plume (MP) and Birthday Candles (BC) location in relation to the larger GoM bathymetry. Inset shows other areas of plume (flare) detection along the trend of the curving salt ridge.

91 Fig. C.2.: Rugosity figure of Mega Plume (MP) and Birthday Candles (BC) showing the pockmarks in more detail.

92 Fig. C.3.: Correlation coefficients for quantitative comparison of four samples with Megaplume oil seep. The correlation of Megaplume oil seep with itself is equal to 1, as shown by the purple bar.

93 Fig. C.4: Overlaid spider diagrams for Mega Plume oil seep, Mega Plume oil slick, Birthday Candles oil slick, Holstein crude oil, and Macondo crude oil (NIST2779) constructed from seven diagnostic biomarker ratios (Ts/Tm, H29/H30, H32S/H32R, H30(H31+H32+H33+H34+H35), H33S/H33R, C27α β β /C29α β β steranes, and C27β α /C29β α diasteranes). Macondo crude oil (NIST2779) analyzed to demonstrate the fidelity of the visualization method for the differentiation of samples of the same origin to those originating from other sources.

94 Fig. C.5: Details from AUV Mola Mola survey. a Mosaic of the 60 x 60 m survey at the Mega Plume seep domain. b Close up section of the red rectangle in a. This section was processed with higher detail using close range photogrammetry. c Individual image from Mola Mola mosaic including the same bubble stream analyzed with the VTLC.

.

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100 Lessard-Pilon, S., Porter, M.D., Cordes, E.E., MacDonald, I., Fisher, C.R., 2010. Community composition and temporal change at deep Gulf of Mexico cold seeps. Deep Sea Research Part II: Topical Studies in Oceanography 57, 1891-1903. Levin, L., Baco, A., Bowden, D., Colaco, A., Cordes, E., Cunha, M., Demopoulos, A., Gobin, J., Grupe, B., Le, J., 2016. Hydrothermal Vents and Methane Seeps: Rethinking the Sphere of Influence. Front. Mar. Sci 3, 72. Liu, J.Y., Bryant, W.R., 2000. Seafloor Morphology and Sediment Paths of the Northern Gulf of Mexico Deep Water. Transactions 45, 95-101. Liu, X., Flemings, P.B., 2006. Passing gas through the hydrate stability zone at southern Hydrate Ridge, offshore Oregon. Earth and Planetary Science Letters 241, 211-226. Lloyd, K.G., Albert, D.B., Biddle, J.F., Chanton, J.P., Pizarro, O., Teske, A., 2010. Spatial structure and activity of sedimentary microbial communities underlying a Beggiatoa spp. mat in a Gulf of Mexico hydrocarbon seep. PLoS One 5, e8738. Lobodin, V.V., Maksimova, E.V., Rodgers, R.P., Submitted. GAs Chromatography/Atmospheric Pressure Chemical Ionization Mass Spectrometry for Fingerprinting the Macondo Oil Spill. Anal. Chem. Lutken, C., Welch, D., 2013. Hydrate research activities that both support and derive from the monitoring station/sea-floor observatory, Mississippi Canyon 118, Northern Gulf of Mexico. Semiannual Progress Report University of Mississippi. MacDonald, I.R., 1998. Habitat formation at Gulf of Mexico hydrocarbon seeps. Cah. Biol. Mar. 39, 4. MacDonald, I.R., 2002. Transfer of hydrocarbons from natural seeps to the water column and atmosphere. Geofluids 2, 95-107. MacDonald, I.R., 2004. Asphalt volcanism and chemosynthetic life in the Campeche Knolls: Gulf of Mexico. Science 304, 999-1002. MacDonald, I.R., Bender, L.C., Vadaro, M., Bernard, B., 2005a. Thermal and visual time-series at a seafloor gas hydrate deposit on the Gulf of Mexico slope. Earth and Planetary Science Letters 233, 14. MacDonald, I.R., Buthman, D., Sager, W.W., Peccini, M.B., Guinasso Jr., N.L., 2000. Pulsed oil discharge from a mud volcano. Geology 28, 907-910.

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101 MacDonald, I.R., Kastner, M., Leifer, I., 2005b. Estimates of natural hydrocarbon flux in the Gulf of Mexico basin from remote sensing data. Geophysical Research Abstracts 7. MacDonald, I.R., Peccini, M.B., 2009. Distinct activity phases during the recent geologic history of a Gulf of Mexico mud volcano. Marine and Petroleum Geology 26, 1824-1830. MacDonald, I.R., Reilly, J.F., Guinasso, N.L., Brooks, J.M., Carney, R.S., Bryant, W.A., Bright, T.J., 1990. Chemosynthetic mussels at a brine-filled pockmark in the Northern Gulf of Mexico. Science 248, 3. MacDonald, I.R., Sager, W.W., Peccini, M.B., 2003. Gas hydrate and chemosynthetic biota in mounded bathymetry at mid-slope hydrocarbon seeps: Northern Gulf of Mexico. Marine Geology 198, 133-158. MacDonald, I.R., Smith, M., Huffer, F.W., 2010. Community structure comparisons of lower slope hydrocarbon seeps, northern Gulf of Mexico. Deep Sea Research Part II: Topical Studies in Oceanography 57, 1904-1915. Macelloni, L., Lutken, C., Garg, S., Simonetti, A., D'Emidio, M., Wilson, R., Sleeper, K., Lapham, L., Lewis, T., Pizzi, M., 2015. Heat-flow regimes and the hydrate stability zone of a transient, thermogenic, fault-controlled hydrate system (Woolsey Mound northern Gulf of Mexico). Marine and Petroleum Geology 59, 491-504. Macelloni, L., Simonetti, A., Knapp, J.H., Knapp, C.C., Lutken, C.B., Lapham, L.L., 2012. Multiple resolution seismic imaging of a shallow hydrocarbon plumbing system, Woolsey Mound, Northern Gulf of Mexico. Marine and Petroleum Geology 38, 128-142. Mancini, E.A., Marcello, B., Puckett, T.M., Llinas, J.C., Parcell, W.C., 2001. Mesozoic carbonate petroleum systems in the Northeasters Gulf of Mexico area, Petroleum Systems of Deep- Water Basins. GCSSEMP Foundation 21st Annual Research Conference. Mann, D.M., Mackenzie, A.S., 1990. Prediction of pore fluid pressures in sedimentary basins. Marine and Petroleum Geology 7, 55-65. Maslin, M.A., Thomas, E., 2003. Balancing the deglacial global carbon budget: the hydrate factor. Quaternary Science Reviews 22, 1729-1736. Merewether, R., Olsson, M.S., Lonsdale, P., 1985. Acoustically detected hydrocarbon plumes rising from 2km depths in Guaymas Basin, Gulf of California. Journal of Geophysical Research: Solid Earth (1978–2012) 90, 3075-3085. Milkov, A.V., 2000. Worldwide distribution of submarine mud volcanoes and associated gas hydrates. Marine Geology 167, 13. Møller, M.M., Nielsen, L.P., Jørgensen, B.B., 1985. Oxygen responses and mat formation by Beggiatoa spp. Applied and Environmental Microbiology 50, 373-382.

102 Naehr, T.H., Eichhubl, P., Orphan, V.J., Hovland, M., Paull, C.K., Ussler, W., Lorenson, T.D., Greene, H.G., 2007. Authigenic carbonate formation at hydrocarbon seeps in continental margin sediments: a comparative study. Deep Sea Research Part II: Topical Studies in Oceanography 54, 1268-1291. Nejring, R., 1991. Oil and gas resources. Geological Society of America. Netzeband, G.L., Krabbenhoeft, A., Zillmer, M., Petersen, C.J., Papenberg, C., Bialas, J., 2010. The structures beneath submarine methane seeps: Seismic evidence from Opouawe Bank, Hikurangi Margin, New Zealand. Marine Geology 272, 59-70. Orcutt, B.N., Boetius, A., Lugo, S.K., MacDonald, I.R., Samarkin, V.A., Joye, S.B., 2004. Life at the edge of methane ice: microbial cycling of carbon and sulfur in Gulf of Mexico gas hydrates. Chemical Geology 205, 239-251. Peel, F., Travis, C., Hossack, J., 1995a. Genetic structural provinces and salt tectonics of the Cenozoic offshore US Gulf of Mexico: a preliminary analysis. Peel, F., Travis, C., Hossack, J., 1995b. Genetic structural provinces and salt tectonics of the Cenozoic offshore US Gulf of Mexico: a preliminary analysis. AAPG Memoir 65, 22. Peters, K.E., Walters, C.C., Moldowan, J.M., 2007. The biomarker guide: Volume 1, Biomarkers and isotopes in the environment and human history. Cambridge University Press. Pindell, K., Kennan, L., 2009. Tectonic evolution of the Gulf of Mexico, Carribean and northern South America in the mantle reference frame: and update. Geological Society of London, 60. Planckaert, M., 2005. Oil reservoirs and oil production. Petroleum microbiology, 3-19. Prather, B., 2000. Calibration and visualization of depositional process models for above-grade slopes: a case study from the Gulf of Mexico. Marine and Petroleum Geology 17, 619-638. Pyles, D.R., Weimer, P., Bouroullec, R., 2001. Stratigraphic and tectonic framework of the DeSoto Canyon and Lloyd Ridge protraction areas, Northeastern deep Gulf of Mexico: Implications for the petroleum systems and potential play types. GCSSEMP Foundation 21st Annual Research Conference, 29. Roberts, H.H., Aharon, P., 1994. Hydrocarbon-derived carbonate buildups of the northern Gulf of Mexico continental slope: a review of submersible investigations. Geo-Marine Letters 14, 135-148. Roberts, H.H., Carney, R.S., 1997. Evidence of episodic fluid, gas, and sediment venting on the northern Gulf of Mexico continental slope. Economic Geology and the Bulletin of the Society of Economic Geologists 92, 863-879. Roberts, H.H., Shedd, W., Hunt, J., 2010. Dive site geology: DSV ALVIN (2006) and ROV JASON II (2007) dives to the middle-lower continental slope, northern Gulf of Mexico. Deep Sea Research Part II: Topical Studies in Oceanography 57, 1837-1858.

103 Rowan, M.G., Peel, F.J., Vendeville, B.C., Gaullier, V., 2012. Salt tectonics at passive margins: Geology versus models - Discussion. Marine and Petroleum Geology 37, 184-194. Rowan, M.G., Ratliff, R.A., 2012. Cross-section restoration of salt-related deformation: Best practices and potential pitfalls. Journal of Structural Geology 41, 24-37. Ruppel, C., Dickens, G., Castellini, D., Gilhooly, W., Lizarralde, D., 2005. Heat and salt inhibition of gas hydrate formation in the northern Gulf of Mexico. Geophysical Research Letters 32. Römer, M., Sahling, H., Pape, T., Bahr, A., Feseker, T., Wintersteller, P., Bohrmann, G., 2012. Geological control and magnitude of methane ebullition from a high-flux seep area in the Black Sea—the Kerch seep area. Marine Geology 319, 57-74. Römer, M., Sahling, H., Pape, T., dos Santos Ferreira, C., Wenzhöfer, F., Boetius, A., Bohrmann, G., 2014. Methane fluxes and carbonate deposits at a cold seep area of the Central Nile Deep Sea Fan, Eastern Mediterranean Sea. Marine Geology 347, 27-42. Sahling, H., Bohrmann, G., Artemov, Y.G., Bahr, A., Brüning, M., Klapp, S.A., Klaucke, I., Kozlova, E., Nikolovska, A., Pape, T., 2009. Vodyanitskii mud volcano, Sorokin trough, Black Sea: Geological characterization and quantification of gas bubble streams. Marine and Petroleum Geology 26, 1799-1811. Sahling, H., Bohrmann, G., Spiess, V., Bialas, J., Breitzke, M., Ivanov, M., Kasten, S., Krastel, S., Schneider, R., 2008. Pockmarks in the Northern Congo Fan area, SW Africa: Complex seafloor features shaped by fluid flow. Marine Geology 249, 206-225. Sahling, H., Römer, M., Pape, T., Bergès, B., dos Santos Fereirra, C., Boelmann, J., Geprägs, P., Tomczyk, M., Nowald, N., Dimmler, W., 2014. Gas emissions at the continental margin west of Svalbard: mapping, sampling, and quantification. Biogeosciences 11, 6029-6046. Salvador, A., 1991. Origin and development of the Gulf of Mexico basin Ch. 14. Geological Soceity of America. Sam, A., Gomez, C., Finch, J., 1996. Axial velocity profiles of single bubbles in water/frother solutions. International Journal of Mineral Processing 47, 177-196. Sassen, R., 1990. Lower Tertiary and Upper Cretaceous Source Rocks in Louisiana and Mississippi: Implications to Gulf of Mexico Crude Oil (1). AAPG Bulletin 74, 857-878. Sassen, R., Macdonald, I.R., Requejo, A.G., Guinasso, N.L., Kennicutt, M.C., Sweet, S.T., Brooks, J.M., 1994. Organic geochemistry of sediments from chemosynthetic communities, Gulf of Mexico slope. Geo-Marine Letters 14, 110-119. Sassen, R., Roberts, H.H., Carney, R., Milkov, A.V., DeFreitas, D.A., Lanoil, B., Zhang, C., 2004. Free hydrocarbon gas, gas hydrate, and authigenic minerals in chemosynthetic communities of the northern Gulf of Mexico continental slope: relation to microbial processes. Chemical Geology 205, 195-217.

104 Schneider von Deimling, J., Greinert, J., Chapman, N.R., Rabbel, W., Linke, P., 2010. Acoustic imaging of natural gas seepage in the North Sea: Sensing bubbles controlled by variable currents. Limnology and Oceanography-Methods 8, 155-171. Schneider von Deimling, J., Rehder, G., Greinert, J., McGinnnis, D.F., Boetius, A., Linke, P., 2011. Quantification of seep-related methane gas emissions at Tommeliten, North Sea. Continental Shelf Research 31, 867-878. Simonetti, A., Knapp, J.H., Sleeper, K., Lutken, C.B., Macelloni, L., Knapp, C.C., 2013. Spatial distribution of gas hydrates from high-resolution seismic and core data, Woolsey Mound, Northern Gulf of Mexico. Marine and Petroleum Geology 44, 21-33. Smith, A.J., Flemings, P.B., Fulton, P.M., 2014. Hydrocarbon flux from natural deepwater Gulf of Mexico vents. Earth and Planetary Science Letters 395, 241-253. Solomon, E.A., Kastner, M., Jannasch, H., Robertson, G., Weinstein, Y., 2008. Dynamic fluid flow and chemical fluxes associated with a seafloor gas hydrate deposit on the northern Gulf of Mexico slope. Earth and Planetary Science Letters 270, 95-105. Solomon, E.A., Kastner, M., Macdonald, I., Leifer, I., 2009. Considerable methane fluxes to the atmosphere from hydrocarbon seeps in the Gulf of Mexico. Nature Geoscience Letters, 5. Stakes, D.S., Orange, D., Paduan, J.B., Salamy, K.A., Maher, N., 1999. Cold-seeps and authigenic carbonate formation in Monterey Bay, California. Marine Geology 159, 93-109. Talukder, A.R., 2012. Review of submarine cold seep plumbing systems: leakage to seepage and venting. Terra Nova 24, 255-272. Teske, A., Nelson, D.C., 2006. The genera Beggiatoa and Thioploca, The prokaryotes. Springer, pp. 784-810. Thomanek, K., Zielinski, O., Sahling, H., Bohrmann, G., 2010. Automated gas bubble imaging at sea floor–a new method of in situ gas flux quantification. Ocean Science 6, 549-562. Thrasher, J., Fleet, A.J., Hay, S.J., Hovland, M., Düppenbecker, S., 1996. Understanding geology as the key to using seepage in exploration: the spectrum of seepage styles. AAPG Memoir 66, 18. Torres, M., Wallmann, K., Tréhu, A., Bohrmann, G., Borowski, W., Tomaru, H., 2004. Gas hydrate growth, methane transport, and chloride enrichment at the southern summit of Hydrate Ridge, Cascadia margin off Oregon. Earth and Planetary Science Letters 226, 225- 241. Valentine, D.L., Blanton, D.C., Reeburgh, W.S., Kastner, M., 2001. Water column methane oxidation adjacent to an area of active hydrate dissociation, Eel River Basin. Geochim. Cosmochim. Acta 65, 2633-2640. Vardaro, M.F., MacDonald, I.R., Bender, L.C., Guinasso Jr, N.L., 2006. Dynamic processes observed at a gas hydrate outcropping on the continental slope of the Gulf of Mexico. Geo- Marine Letters 26, 6-15.

105 Wagner, B.H., Jackson, M.P.A., 2011. Viscous flow during salt welding. Tectonophysics 510, 309-326. Wang, B., Socolofsky, S.A., 2015. A deep-sea, high-speed, stereoscopic imaging system for in situ measurement of natural seep bubble and droplet characteristics. Deep Sea Research Part I: Oceanographic Research Papers 104, 134-148. Wang, B., Socolofsky, S.A., Breier, J.A., Seewald, J., 2016. Observations of bubbles in natural seep flares at MC 118 and GC 600 using in situ quantitative imaging. Journal of Geophysical Research: Oceans. Wang, Z., Stout, S.A., 2007. Oil spill environmental forensics: Fingerprinting and source identification. Academic PRess 1st ed., 620. Wankel, S.D., Joye, S.B., Samarkin, V.A., Shah, S.R., Friederich, G., Melas-Kyriazi, J., Girguis, P.R., 2010. New constraints on methane fluxes and rates of anaerobic methane oxidation in a Gulf of Mexico brine pool via in situ mass spectrometry. Deep Sea Research Part II: Topical Studies in Oceanography 57, 2022-2029. Whelan, J.K., Farrington, J.W., 2013. Organic Matter: productivity, accumulation, and preservation in recent and ancient sediments. Columbia University Press. Wilson, R.M., Macelloni, L., Simonetti, A., Lapham, L., Lutken, C., Sleeper, K., D'Emidio, M., Pizzi, M., Knapp, J., Chanton, J., 2014. Subsurface methane sources and migration pathways within a gas hydrate mound system, Gulf of Mexico. Geochemistry, Geophysics, Geosystems 15, 89-107. Woolsey, M., Woolsey, A., Hulme, S., 2015. AUV-derived geographical photomosaics-using multibeam bathymetry to correct image placement, OCEANS'15 MTS/IEEE Washington. IEEE, pp. 1-7. Zakaria, M.P., Horinouchi, A., Tsutsumi, S., Takada, H., Tanabe, S., Ismail, A., 2000. Oil pollution in the Straits of Malacca, Malaysia: Application of molecular markers for source identification. Environmental science & technology 34, 1189-1196.

106 BIOGRAPHICAL SKETCH

. EDUCATION

The Florida State University, Tallahassee, FL, USA PhD, Biogeochemical Oceanography Department of Earth, Ocean, and Atmospheric Science Advisor: Ian R. MacDonald

University of Florida, Gainesville, FL, USA B.S., Animal Biology Pre-Veterinary Track, December 2010

. WORK EXPERIENCE

Florida State University Tallahassee, FL, January, 2012-Present Research Scientist Current research based in the Gulf of Mexico. Understanding the dynamics of hydrocarbon seeps. North Wood Oaks Veterinary Hospital Gainesville, FL, June, 2009- May, 2011 Animal Care Nurse Cross trained as a veterinarian technician and receptionist. Responsible for making appointments, assisting/prepping for surgery, general check-ups, bathing, running blood, fecal, urine tests and cytology’s in the lab, and communicating clients concerns about the pet with the Doctors. English Language Institute at UF Gainesville, FL, August, 2008- December, 2008 Language Assistant Taught English as a second language to international students, in a conversational manner. I was in charge of developing different activities to encourage the students to use what they learned during lecture to prepare for the TOEFL (Test of English as a Foreign Language).

. TEACHING EXPERIENCE

Habitable Planet, Spring Semester 2015, Appointed Lecturer, Florida State University . Elective Earth Science Class for Environmental Science Majors (BS). . Prepared and administered all lectures for class, created/graded exams, and assigned/reviewed research papers. Habitable Planet, Fall Semester 2013, Teaching Assistant, Florida State University . Professor: Ian R. MacDonald Habitable Planet, Fall Semester 2012, Teaching Assistant, Florida State University . Professor: Ian R. MacDonald

107 . FIELD WORK (Research Cruises)

Gas Hydrates in Mud Volcanoes of the Anaximander Mountains, November, 2014 RV Meteor, M112, Eastern Mediterranean Mapping sea floor for fluid flow. Gravity core samples. Collecting carbonates and biological samples. CTD and water sample collection . Chief Scientist: Gerhard Bohrmann, MARUM University of Bremen. NRDA Mesophotic Reef Cruise, July, 2014 RV Walton Smith, Gulf of Mexico Preparing and deploying rotary cameras with the ROV. General maintenance of camera systems, downloading data, working in ROV van during transects etc. . Chief Scientist: Michael Randall, USGS, Gainesville . Funded by NOAA Mud Collection and Millet Cruise, May-June, 2014 RV Weather Bird, WB1411, Gulf of Mexico Data manager. Organization of sampling location and schedule. MUC and Piston Cores. . Chief Scientist: Ian MacDonald, Florida State University, Department of Earth, Ocean, and Atmospheric Sciences . Funded by Deep-C Brine and Seep Cruise, April, 2014 RV Atlantis, AT26-13, Gulf of Mexico Retrieval and deployment of VTLC camera at GC600 with ALVIN. Mud samples collected for USGS and FSU. Camera mounted on multiple core, and CTD for in situ visualization of operation. . Chief Scientist: Samantha Joye, University of Georgia, Department of Marine Sciences . Funded by ECOGIG, and NSF Lander and Camera recovery and deployment cruise, March, 2014 RV Pelican, PE14-14, Gulf of Mexico Retrieval and deployment of VTLC camera at MC118 and GC600. Water samples. . Chief Scientist: Beth Orcutt, Senior Research Scientist, Bigelow Laboratory for Ocean Sciences . Funded by ECOGIG Lander and mooring cruise, October, 2013 RV Pelican, PE14-09, Gulf of Mexico Attempted retrieval and deployment of VTLC camera at MC118 and GC600. Water samples collected. . Chief Scientist: Beth Orcutt, Senior Research Scientist, Bigelow Laboratory for Ocean Sciences . Funded by ECOGIG Long Term Effects of the Deep Water Horizon Oil Spill, FK006b, November, 2012 R/V Falkor, Gulf of Mexico Deployment and retrieval of VTLC camera at a hydrocarbon seep in GC600. Mud samples (multicore and push core), and water samples collected. Mapping bathymetry. . Chief Scientist: Ian R. MacDonald, Florida State University . Funded by ECOGIG

108 . PEER REVIEWED PUBLICATIONS

Johansen, C., A.C Todd, I.R. MacDonald. Bubble release processes at natural hydrocarbon seeps in the Gulf of Mexico . Submitted to PLOS ONE, May 1, 2016.

Johansen, C., E. Marty, M. Natter, M. Silva, J. Hill, R. Viso, V.V. Lobodin, A.R Diercks, M. Woolsey, A. Woolsey, L. Macelloni, E.V. Maskimova, W. Shedd, S. Joye, M. Abrams, I.R. MacDonald. A hydrocarbon budget for a Gulf of Mexico natural seep site: GC600 . To be submitted June, 2016 in EPSL (Earth and Planetary Science Letters)

Johansen, C., MacDonald, I.R. Descriptive overview of metazoans in Gulf of Mexico seep zones . In prep.

Diercks, A.R., Asper, V.L., Woolsey, M., Woolsey, A., Jarnagin, R., Johansen, C., MacDonald, I.R., Macelloni, L., Conti, A. AUV based High Resolution Seafloor Morphology of a Hydrocarbon Seep in the Gulf of Mexcio. . Submitted to Deep Sea Research I, April 21, 2016

. OTHER PUBLICATIONS

Johansen, C., 2014: How Oil Feeds the Deep Sea, November 18, 2014, http://ocean.si.edu/blog/how-oil-feeds-deep-sea

Johansen, C., 2013: ECOGIG VTLC Deployment on Nautilus, June, 2013, https://ecogig.org/sites/default/files/Johansen_ECOGIG%20VTLC%20Deployment%20o n%20Nautilus.pdf

Johansen, C., 2013: Professional Perspectives Video CPALMS, Mathematic Standards (MACC912GGMD13), June, 2013 http://www.cpalms.org/CPALMS/perspectives_professional_MACC912GGMD13_CJ_1. aspx

Johansen, C., 2013: Expert Perspectives Video CPALMS, Science Standards (SC912E64), June, 2013, http://www.cpalms.org/CPALMS/perspectives_expert_SC912E64_CJ_2.aspx

Johansen, C., 2013: Sharing Science with Students, (Blog Post) March, 2013, http://deep- c.org/news-and-multimedia/in-the-news/sharing-science-s-cool-factor

109 . CONFERENCE PRESENTATIONS

Johansen, C., E. Marty, M. Natter, M. Silva, J. Hill, R. Viso, V.V. Lobodin, A.R Diercks, M. Woolsey, A. Woolsey, L. Macelloni, E.V. Maskimova, W. Shedd, S. Joye, M. Abrams, I.R. MacDonald, 2016: Constraining the fate of hydrocarbons (Poster Presentation). Ocean Science Meeting, New Orleans, LA, February 2016

Johansen, C., A.C Todd, M. Silva, W. Shedd, I.R. MacDonald, 2015: Variability and quantification of oil and gas bubble release from natural seeps in the Gulf of Mexico (Oral Presentation). Gulf of Mexico Oil Spill & Ecosystem Science Conference, Houston, TX, February 2015

Johansen, C., A.C Todd, I.R. MacDonald, 2014: Quantifying the volume and frequency of bubble release from hydrocarbon seeps in the Gulf of Mexico (Oral Presentation). 5th Early Career Scientists Conference for Marine and Climate Research, Bremen, Germany, September 2014

Johansen, C., A.C Todd, W. Shedd, M. Silva, I.R. MacDonald, 2014: Quantifying the volume and frequency of bubble release from hydrocarbon seeps in the Gulf of Mexico: GC600 (Poster Presentation). Deep-C Student Research Symposium, Tallahassee, FL, September 2014

Johansen, C., A.C Todd, W. Dewar, W. Shedd, I.R. MacDonald, 2014: Quantifying the volume and frequency of bubble release from hydrocarbon seeps in the Gulf of Mexico: GC600 (Poster Presentation). Gulf of Mexico Oil Spill & Ecosystem Science Conference, Mobile, AL, January 2014

Johansen, C. 2013: Outreach from a Scientist’s perspective: The importance of convincing the public that your research matters (Poster Presentation). Deep-C Hands On Meeting, Tallahassee, FL, September 2013

Johansen, C., W. Shedd , T. Abichou, O. Pineda-Garcia, M. Silva, I.R. MacDonald, 2013: Dynamics of Hydrocarbon Vents: Focus on Primary Porosity (Poster Presentation). Deep-C Hands On Meeting, Tallahassee, FL, February 2013

Johansen, C., W. Shedd , T. Abichou, O. Pineda-Garcia, M. Silva, I.R. MacDonald, 2013: Dynamics of Hydrocarbon Vents in GC600 (Oral Presentation). Gulf of Mexico Oil Spill & Ecosystem Science Conference, New Orleans, LA, January 2013

Johansen, C., W. Shedd , T. Abichou, O. Pineda-Garcia, M. Silva, I.R. MacDonald, 2012: Dynamics of Hydrocarbon Vents: Focus on Primary Porosity (Poster Presentation). AGU Fall Meeting, San Francisco, CA, December 2012

Johansen, C., W. Shedd , T. Abichou, O. Pineda-Garcia, M. Silva, I.R. MacDonald, 2012: Dynamics of Hydrocarbon Vents: Focus on Primary Porosity (Poster Presentation). Deep-C Hands On Meeting, Tallahassee, FL, August 2012

110 . OUT REACH

Deep-C Educational Outreach, “Scientists in the Schools” Program, Feburary, 2014 Guest Scientist discussing Gulf of Mexico geology. Leading a porosity activity with sand.

CPALMS Perspectives Videos, April, 2013 Educational video describing specific geological processes and features in Florida and elsewhere. Video is to be used in K-12 classes meeting the Florida Science standards.

CPALMS Perspectives Videos, April, 2013 Educational video using the volume formula for a sphere to describe how to solve problems. Video is to be used in K-12 classes meeting the Florida Mathematic standards.

MagLab Open House, February, 2013 Working at the Deep-C booth at the MagLab open house, demonstrating oil spill cleanup.

Capitol Regional Science and Engineering Science Fair Judge, February, 2013 Judging the Earth Sciences portion of the Science Fair, grades 6-8.

Deep-C Educational Outreach, “Scientists in the Schools” Program, January, 2013 Guest Scientist discussing Gulf of Mexico deep sea ecosystems. Focusing on how hydrocarbon vents provide habitats for deep sea organisms.

Deep-C Educational Outreach, “Scientists in the Schools” Program, January, 2013 Guest Scientist discussing human impacts on the Gulf of Mexico. Focusing on the BP oil spill, and discussing the natural seepage of oil in the Gulf of Mexico.

. COMPUTER SKILLS

MATLAB, ArcGIS, Microsoft Office Programs, Adobe Photoshop

. LANGUAGES

English –Fluent, Dutch–Fluent, Norwegian–Fluent, French –Conversational

. MISCALANEOUS LEADERSHIP POSITIONS

Thalassic Graduate Student Society, FSU, President Aug 2013-Aug 2014 Team Captain, Relay for Life at FSU Apr2013

111