Thermal Maturity Modeling of Organic-Rich Mudrocks in The

THERMAL MATURITY MODELING OF ORGANIC-RICH MUDROCKS IN THE

DELAWARE BASIN USING RAMAN SPECTROSCOPY OF CARBONACEOUS

MATERIAL

A Thesis

TELEMACHOS ANDREW MANOS

Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Chair of Committee, Nicholas Perez Committee Members, Franco Marcantonio Brent Miller Head of Department, Michael Pope

August 2018

Major Subject: Geology

ABSTRACT

Raman spectroscopy of carbonaceous material (RSCM) is an emerging tool to investigate the peak temperature organic-rich sediments experience during burial and exhumation. Previously, peak temperature and maturity have been commonly determined using vitrinite reflectance (%Ro), but results may be affected by user bias, organic material composition, hydrogen-index, and pressure suppression. Thermal maturity of organic material is an important factor in determining source rock viability, and RSCM presents an alternative technique to constrain peak temperatures that is not affected by issues that may alter %Ro results. This study investigated the viability of

RSCM thermometry against %Ro and pyrolysis on well cuttings retrieved from Permian through Ordovician intervals of the Delaware Basin in West Texas, assessing peak temperatures and paleogeothermal gradients. New RSCM results from this study demonstrate that the western portion of the basin experienced higher peak temperatures than equivalent depths in the eastern portion of the basin by up to 100oC, which is consistent with existing vitrinite reflectance measurements. This study also reconstructs the paleogeothermal gradient profile of the basin center by incorporating

11 wells in Reeves and Loving County, including wells which have intersected igneous intrusions. Geothermal gradients at times of peak temperature are 40-45oC/km in the east and up to 72.5oC/km in the west. Higher geothermal gradients in the west correspond to areas with poor agreement between RSCM and vitrinite reflectance.

Reconciling the differences between methods requires elevated heat flow, which may

have been supplied by mid-Cenozoic intrusions and regional heat flow associated with the Rio Grande Rift.

iii

ACKNOWLEDGEMENTS

I would like to thank my committee chair Dr. Nicholas Perez, for his continued guidance and mentorship throughout my graduate work at Texas A&M University. His high standards and ambitious drive modeled my expectations of a young professional at

Texas A&M University, helping me consistently push my limits as a researcher and critical thinker.

I would also like to thank the faculty at Texas A&M who contributed discussion to the topic, Dr. Jim Markello, Dr. Mike Pope, and Dr. Brent Miller; the staff at the Texas

Oil and Gas Institute, Dr. Brian Casey and Dr. David DeFelice; and the basin modelers at the Chevron Center of Research Excellence, Dr. Mauro Becker, Dr. Irene Arango, Dr.

Tess Minotti, Dr. Barry Katz, Dr. Andrea Romero, and Dr. Norellis Rodriguez.

Finally, thanks to the fellow graduate students in Dr. Perez’s research group who helped spearhead a new research team, specifically Vicky Gao, Clyde Findlay, and

Maria Pesek. Their encouragement and assistance greatly aided in overcoming the many obstacles that comes with venturing into new territory.

CONTRIBUTORS AND FUNDING SOURCES

Contributors

This work was supported by a defense committee consisting of Dr.Nicholas

Perez, Dr. Brent Miller of the Department of Geology & Geophysics and Professor

Franco Marcantonio of the Department of Oceanography and Department of Geology.

The Raman Spectrometer, training, and decomposition software used for peak- temperature analysis was constructed and written by Professor Emmanuel Soignard at the Arizona State University Leeroy Eyring Center for Solid State Science. Thin sections were generated at National Petrographic Laboratory. %Ro and Pyrolysis Rock-Eval was contracted through Geomark Research Ltd. Maps of gas-oil ratios were constructed with assistance from a fellow graduate student Vicky Gao, and well correlations were completed with assistance from Dr. Brian Casey at the Texas Oil and Gas Institute and

Nate Naylor at Texas A&M University. All other work conducted for this thesis was completed by the student independently.

Funding Sources

This work was supported by a Graduate Student Research Grant from the

Geological Society of America, Grands-in-Aid funding from the American Association of

Petroleum Geologists, a scholarship from the Permian Basin Area Foundation, a scholarship from the West Texas Geological Society, a scholarship from the US Army

Reserves, startup funding from Dr. Nicholas Perez, and a fellowship from the Berg-

Hughes center for Petroleum and Sedimentary Systems.

v TABLE OF CONTENTS

Page

ABSTRACT…………………………………………………………………………… ii

ACKNOWLEDGEMENTS…………………………………………………………… iv

CONTRIBUTORS AND FUNDING SOURCES…………………………………… v

TABLE OF CONTENTS……………………………………………………………… vi

LIST OF FIGURES…………………………………………………………………… viii

LIST OF TABLES…………………………………………………………………….. x

1. INTRODUCTION…………………………………………………………………. 1

1.1 Current Thermal Maturity Indicators…………………………………… 4 1.2 Raman Spectroscopy of Carbonaceous Material as an Emerging Method...... 5 1.3 Limitations of RSCM……………………………………………………. 9

2. BACKGROUND GEOLOGY…………………………………………………… 12

2.1 Delaware Basin………………………………………………………….. 12 2.2 Stratigraphy………………………………………………………………. 12 2.3 Exhumation History……………………………………………………… 15 2.4 Thermal Characteristics………………………………………...... 15 2.5 Igneous Intrusions in the Delaware Basin…………………………….. 17

3. METHODS………………………………………………………………………… 22

3.1 Raman Spectroscopy of Carbonaceous Material (RSCM)………… 22 3.2 Collection Regime……………………………………………………… 24 3.3 Peak Fitting and Data Decomposition……………………………….. 25 3.4 Sampling Regime……………………………………………………… 27 3.5 Data Plotting……………………………………………………………. 29 3.6 Vitrinite Reflectance……………………………………………………. 31 3.7 Rock-Eval Pyrolysis……………………………………………………. 31

4. RESULTS……….………………………………………………………………… 33

4.1 Calibration Wells………………………………………………………… 33 4.2 RSCM and Vitrinite Reflectance Compatibility……………...………. 33 4.3 Vitrinite Reflectance Interpolation…………………………………….. 36

4.4 Rock-Eval Pyrolysis…………………………………………………….. 37 4.5 RSCM Data Points……………………………………………………… 38 4.6 RSCM Uncertainty……………………………………………………… 41 4.7 RSCM Surfaces…………………………………………………………. 42

5. DISCUSSION……………………………………………………………………… 44

5.1 RSCM Peak Temperatures Contrasted with %Ro Temperature Estimates………………………………………………………………… 44 5.2 Comparison with Pyrolysis Rock-Eval………………………………… 45 5.3 Trends in Peak Temperature…………………………………………… 46 5.4 Comparison of Trends between RSCM and %Ro…………………… 48

6. BASIN MODELING……………………………………………………………….. 52

6.1 Introduction to Basin Modeling…………………………………………. 52 6.2 Model Inputs……………………………………………………………… 53 6.3 Cold Case – Lineberry Evelyn #1……………………………………… 54 6.4 Hot Case – Texaco #1-29………………………………………………. 53 6.5 Rifting Style………………………………………………………………. 59 6.6 Igneous Intrusions………………………………………………………. 61 6.7 Additional Sources of Heat…………………………………………….. 65 6.8 Cretaceous Overburden Removal…………………………………….. 66 6.9 Peak Temperatures over Time………………………………………… 68

7. CONCLUSIONS………………………………………………………………….. 72

REFERENCES……………………………………………………………………….. 75

APPENDIX…………………..………………………………………………………... 98

vii

LIST OF FIGURES

FIGURE Page

1. Gas oil ratios from lateral production of the Wolfcamp formation in the Delaware Basin of West Texas…………………………………………………… 3

2. Cartoon illustrating virtual energy states of molecules when elevated by photon absorption………………………………………………………………….. 6

3. Illustration detailing the transformation of amorphous carbon to ordered graphene sheets with increasing temperature………………………………….. 7

4. Map showing the Delaware basin location and stratigraphy, with well location and study area indicated………………………………………………… 14

5. Events illustrating the link between change in magmatic composition and regional tectonics…………………………………………………………………... 19

6. Map showing the location of known igneous intrusions in the Delaware Basin region………………………………………………………………………… 20

7. Thin section plain polarized light view showing opaque macerals illuminated in a carbonate matrix, with the laser focus position in red…………………….. 24

8. The raw Raman spectra are initially corrected for background fluorescence by subtracting a linear function connecting the lowest points at 1100cm-1 and 1800cm-1……………………………………………………………………….. 26

9. Peak-fitted Raman spectra showing evolving peak parameters with increasing depth and temperature……………………………………………….. 28

10. Worksheet showing individual peak-temperature measurements from Woodford sediments in Tenney Gerald E. #1 well at 1840m TVDSS………... 30

11. Depth/temperature profiles and 1σ errors for each well analyzed with RSCM……………………………………………………………………………….. 34

12. RSCM temperatures as determined from eq. 1 and eq. 2 diverge for measured samples of less than 150oC…………………………………………... 35

13. Maps of interpolated vitrinite reflectance values, showing depth to 0.8% maturity (left) and the vitrinite gradient from 0.8-2.8% (right)…………………. 37

14. Maps showing the depth to RSCM values of 120oC (left) and the peak temperature paleogeothermal gradient (right)…………………………………... 42

viii

15. Plot of %Ro measured vs. RSCM %Ro equivalence…………………………… 45

16. %Ro, Pyrolysis, and RSCM results (converted to %Ro) plotted against depth from the Tenney, Gerald E. #1 well……………………………………………… 47

17. Negative isochore values (hot) show areas where the vitrinite surface is shallower than it’s equivalent RSCM surface, suggesting heating duration is high…………………………………………………………………………………... 50

18. Burial history curve for the Lineberry Evelyn #1 well, showing deposition of major units and total subsidence over time……………………………………… 55

19. RSCM, measured %Ro, and Easy%Ro results plotted against depth for the Lineberry Evelyn #1 well…………………………………………………………... 56

20. Easy%Ro modeling for the Texaco #1-29 well showing inconsistent results with observed %Ro data, suggesting input parameters such as basal heat flow and eroded overburden are not constant throughout the basin…………. 58

21. Depth/maturity profile for Texaco #1-29 well iterated using McKenzie-style rift modeling with 90mW/m2 peak heat flow for 20 million years from 30 Ma to 10 Ma……………………………………………………………………………... 60

22. Basal heat flow values extracted from the 1D model of Texaco #1-29 as a function of extension (increased ß value)……………………………………….. 62

23. Plot of temperature, maturity, and depth…………………………………………. 64

24. Mapped igneous intrusions of the west Delaware basin align well with positive magnetic anomalies published in Adams and Keller (1996)………… 65

25. Charts modeling peak temperature over time for each interval analyzed by RSCM……………………………………………………………………………….. 70

LIST OF TABLES

TABLE Page

1. Wells selected for RSCM analysis ………………………..………………………… 21

2. Rock Eval Pyrolysis results for Tenney, Gerald, E. #1………………………..….. 38

3. RSCM results for 11 wells sampled in the Delaware Basin …………………….. 39

4. Input parameters used for 1D basin models of Texaco #1-29 and Lineberry Evelyn #1……………..……………………………………………………………….. 53

1. INTRODUCTION

Understanding the peak temperature sediments reach during burial is critical for determining the generative potential of petroleum source rocks. The amount of kerogen maturation into hydrocarbon and the phase of produced hydrocarbons are in part controlled by the peak temperature (Espitalié et al., 1977; Campbell et al., 1978; Tissot et al., 1987; Ungerer & Pelet, 1987). Because source rock intervals in conventional hydrocarbon production are rarely encountered by drilling, the degree of organic matter maturation is commonly deduced from basin models. However, maturity is also a function of time that sediments experience elevated temperature, and this duration is influenced by burial rate, thermal conductivity, and basement heat flux (Ungerer et al.,

1991; Carr, 1999; Amir et al., 2005). Typically, these values are iteratively adjusted in basin models to match observed sediment maturity values and extrapolated to unexplored portions of a basin to predict the generative potential of source rocks.

Improved constraints on peak temperature and thermal maturity may also refine the tectonic reconstructions of basins, as paleo- and modern temperature comparisons could indicate previous subsidence or exhumation. While the magnitude and timing of burial can be quantified using backstripping techniques, and the timing of exhumation constrained using thermochronologic techniques, constraining the peak temperature remains difficult because existing paleothermometry methods may be subject to multiple sources of uncertainty.

The Delaware Basin of West Texas and New Mexico provides an ideal location to test how spatial variability of sediment maturity may be linked to burial depth, burial

rate, present-day structure, and basement heat flux. With over a century of active exploration and production, new unconventional drilling techniques have renewed exploration interest, specifically within the stacked organic-rich mudrock intervals. The basin exhibits anomalous overpressure and gas-oil ratios that generally increase east to west despite decreasing modern burial depth (figure 1) (Schwartz et al., 2015;

Centennial, 2016). While over pressurization is likely associated with rapid Permian sediment accumulation and gas decompaction during uplift (Sinclair, 2007), controls on the counterintuitive gas-oil ratios remain unresolved. Proposed explanations include greater burial depths and subsequent exhumation, or elevated geothermal gradients in the western portion relative to the eastern portion (Ruppel et al., 2005). Igneous bodies encountered by several wells along the western and northwestern margin of the basin also suggest that Cenozoic intrusion, potentially associated with the Rio Grande Rift, may play a role in elevated maturity (Barker and Pawlewicz, 1987). As a long-lived depocenter recording passive margin sedimentation, continent-continent collision, and orogenic uplift, understanding the thermal evolution of the Delaware Basin has important implications for Paleozoic through Cenozoic tectonics and continued hydrocarbon exploration. This study aims to assess the lateral and vertical variability in peak temperatures and geothermal gradients of several organic-rich stratigraphic intervals in the Delaware Basin spanning the Ordovician through Permian. Existing thermal maturity indicators such as vitrinite reflectance (Pawlewicz et al., 2005) and pyrolysis Rock-Eval will be tested with results from an emerging geothermometer,

Raman Spectroscopy of Carbonaceous Material (RSCM), to minimize uncertainties arising from variable maceral chemistry and user bias that may affect existing

Figure 1. Gas oil ratios from lateral production of the Wolfcamp formation in the Delaware Basin of West Texas. A. Map view, B. Cross-sectional view. Gas oil ratios increase from east to west, highlighting changes in thermal maturity depth and geothermal gradients.

techniques. Peak temperature constraints and maturity gradients will be coupled with

1D backstripping models toidentify trends in elevated heat flow or increased exhumation. We test whether rocks in the western Delaware Basin experienced relatively higher peak temperatures and geothermal gradients than eastern regions and assess whether these may be linked with Cenozoic igneous intrusion, greater burial, or proximity to the Rio Grande Rift flank. Ultimately, trends in peak temperatures will assist in characterizing our understanding of Delaware Basin heat flux and tectonics, greatly informing basin models that constrain the flow and composition of fluids in the subsurface.

1.1 Current Thermal Maturity Indicators

The peak temperatures and thermal maturity of sediment are commonly constrained with vitrinite reflectance data (%Ro) and Rock-Eval pyrolysis. Vitrinite reflectance measures the percent of light reflected from vitrinite macerals immersed in oil and increases with higher degrees of organic maturation (Middleton, 1982; Tissot &

Welte, 1984). Rock-Eval pyrolysis measures the volume of hydrocarbons and carbon dioxide released from a sample of organic-rich sediments during a constant heating rate. (Espitalié et al, 1977; Jarvie & Baker, 1984). Neither method constrains peak- temperature values directly, but instead yields an indirect indicator for peak-temperature based on empirical relationships between maturity, heating rate, duration of heating, and organic material (OM) composition.

Vitrinite reflectance has been the industry standard for determining the thermal maturity of buried sediments, but may yield anomalous values in over-pressurized units

(Freund et al., 1992; Dalla Torre et al., 1997; Carr, 1999), rocks with high hydrogen

content (Price & Barker, 1985; Fang & Jianyu, 1992; George et al., 1994; Huang, 1996;

Zhong et al., 2000), or when mistakenly applied to macerals other than vitrinite

(Dembicki, 1984; Wilkins et al., 2014). These factors, combined with potential bias introduced through reflectance measurement by visual inspection (Kilby, 1988; Kilby,

1991), may limit %Ro precision.

Rock-Eval pyrolysis has also been used as a maturity indicator, as the organic composition of macerals and pore fluids evolves predictably with increasing temperature

(Espitalié et al, 1977; Jarvie & Baker, 1984). Hydrogen index, production index, Tmax, and S1/TOC parameters are used to calculate the maturity of organic components and characterize the transformation ratio, or percentage of kerogen that has been converted to hydrocarbons at a given depth (Espitalié, 1982; Jarvie & Baker, 1984; Jones, 1984;

Espitalié et al., 1985; Jarvie & Lundell, 2001; Keym et al, 2006). Source rocks may have laterally variable organic matter composition, and associated kinetic parameters for kerogen conversion may also vary across the basin (Tegelaar & Noble, 1994; Keym et al., 2006). This suggests that pyrolysis can only be used as a relative index of thermal maturity for like-formations, and not a direct paleo-temperature indicator.

1.2 Raman Spectroscopy of Carbonaceous Material as an Emerging Method

Raman spectroscopy measures the inelastic scattering of photons emitted when incident light of a constant wavelength interacts with the vibrational levels of a material and are scattered at different energies. Emitted photons can have the same energy as the incident light (Rayleigh elastic scattering) or have energy added or deducted from the vibration modes within the sample (inelastic Stokes or anti-Stokes scattering) (figure

2). The vibrations occur at frequencies determined by the atomic weight, chemical

bonds, symmetry, and structure of the material. The intensities of backscattered photons are measured and plotted against their shift to determine a characteristic backscattering profile for a material.

Figure 2. Cartoon illustrating virtual energy states of molecules when elevated by photon absorption. Molecules can return to their original energy state, emitting a photon of equal energy, or they can return to a different energy state, releasing a photon of different energy than the incident light. This shift in photon energy is what is recorded and plotted by the spectrometer (modified from Ember et al, 2017).

With increasing temperature, hydrogen, oxygen, and nitrogen are expelled from amorphous organic material, causing the remaining carbon atoms to become progressively organized into stacked graphene sheets; from misoriented aromatic layers

to stacked triperiodic graphite structure (figure 3) (Yui et al. 1996; Beyssac et al, 2002;

Kouketsu et al., 2014). The Raman spectra are sensitive to specific aspects of the carbon structure, which change systematically with increasing temperature. Because

RSCM is sensitive to carbon structure and not maceral texture, it can be applied to a wide range of organic macerals other than vitrinite (Wilkins, 2014). The carbon structure does not experience retrograde effects during cooling, making it an effective tool for determining the peak temperature a sample has reached (Yui et al, 1996).

Figure 3. Illustration detailing the transformation of amorphous carbon to ordered graphene sheets with increasing temperature.

The Raman spectra of carbon have been documented in previous studies characterizing the degree of crystallinity of carbonaceous material (CM). Early attempts were completed on artificially matured synthetic CM samples (Chieu et al., 1982; Dillon et al., 1984; Beny-Bassez & Rouzaud, 1985) and later extended to natural samples

(Wang et al., 1990). While synthetic carbon metamorphism failed to establish a direct correlation between Raman spectra and specific carbon transformations, a clear pattern of spectral variation trends emerged suggesting the Raman spectra could be used as an indicator for metamorphic grade of the host rock (Pasteris & Wopenka, 1991;

Wopenka & Pasteris 1993). In zeolite, prehnite-pumpellyite, and greenschist metamorphic facies, spectra features such as peak intensity (height) ratios, peak area

(integrated intensity), peak width (full width at half maximum), and x-axis position

(wavenumber) of peak maxima are correlated with increased metamorphic grade (Yui et al., 1996).

An early empirical geothermometer using Raman spectra of metamorphic samples was proposed from a diverse range of collected metamorphic regions spanning

330-650oC (Beyssac et al, 2002; Rahl et al, 2005). It was applied to both metamorphic rocks from burial heating as well as contact metamorphism, demonstrating suitability for rocks with a range of heating rates (Aoya et al. 2010). Additional geothermometers have been developed using different reference standards and peak-fitting methods to constrain peak metamorphic temperature, showing that several spectral parameters evolve systematically with increasing temperature (Lahfid et al. 2010; Kouketsu et al.

2014). Further attempts were made by to relate Raman parameters directly to vitrinite

reflectance for application to the oil and gas industry (Wilkins et al. 2014; Liu et al.

2013).

1.3 Limitations of RSCM

A review of RSCM by Lünsdorf et al, (2014) identified several major shortfalls of using Raman spectroscopy as a geothermometer:

1. The method of peak-fitting significantly impacts the final temperature reading.

Decomposition using one method may yield different results than another.

The variation is highest in low-temperature samples. The software used for

peak-fitting has minimal impact.

2. Manual peak-fitting introduces user bias which increases the variation in

sample readings. A standardized fitting procedure is recommended.

3. Separation of CM in low-temperature samples by use of acids generates a

systematic shift in values compared to untreated samples.

4. Samples have high heterogeneity, requiring several measurements to be

taken per sample and plotted to show clustering of populations. Similar to

vitrinite reflection measurements, recycling of previously matured CM can

occur.

5. Spectra of the same sample show a large variation between labs. This is

attributed to the diversity of lab equipment used that affect the spectral

resolution, intensity, and peak positions.

6. In high-temperature samples with ordered crystalline graphite, temperature

readings may vary depending on angle of incidence and crystallographic

orientation.

Additionally, low-temperature samples with peak temperatures less than 200oC have higher molecular complexities and yield different spectra from systematic studies of reference standards (Lahfid et al. 2010; Kouketsu et al. 2014). This is likely because existing Raman geothermometer relationships are calibrated with higher temperature metamorphic grade samples that yield Raman spectra that can be more easily and consistently deconvolved during peak-fitting. More ordered samples are expected to have less variance in the carbon structure, so it is unclear whether geothermometers intended for higher-grade metamorphic rocks can be extended to low-temperature ranges relevant to kerogen maturation. Because several disordered peaks representing different phases of carbon transformation are active at different temperature ranges, one peak-fitting method concerned with a specific spectra parameter is not appropriate to extend to all phases of CM metamorphism. A single geothermometer using one spectral parameter is appropriate for one narrow temperature range where that parameter systematically evolves with increasing metamorphic grade.

High fluorescence in low-maturity samples decreases the signal to noise ratio, leading to variation in final peak-fitting results (Lünsdorf, 2016). This biasing can be alleviated using a smaller wavelength laser (405-488nm) that is less sensitive to fluorescence intensities at lower maturities. This introduces the problem that many geothermometers were originally calibrated to reference samples using a different wavelength laser. Raman parameters vary with inconsistent laser wavelength due to the resonance effect, specifically altering peak position and peak area values at key positions that overlap the carbon spectra relevant to RSCM (Lünsdorf, 2016). It is important to maintain consistent laser wavelength between the selected

geothermometer and the samples being analyzed, which disqualifies many geothermometer peak-fitting methods based on the available equipment at the time of analysis.

Empirical relationships between Raman spectral parameters and known paleotemperatures are supported by independent temperature estimates from a range of techniques, including vitrinite reflectance, illite crystallinity, metamorphic mineral composition, and chlorite geothermometers (Aoya et al., 2010; Kouketsu et al., 2014;

Wilkins et al., 2014). RSCM is not suppressed by hydrogen content, does not require identification of maceral components beforehand, and if spectra are decomposed digitally, has minimal user bias (Wilkins et al, 2014). RSCM can also be applied to samples that would otherwise be absent or deprived of vitrinite macerals, such as distal fine-grained mudrocks or pre-Devonian age strata.

2. BACKGROUND GEOLOGY

2.1 Delaware Basin

The Delaware Basin is a subbasin of the greater Permian Basin, located in the foreland of the Ouachita-Marathon thrust belt in northwest Texas and southeast New

Mexico. The Permian Basin began as part of the passive margin Tobosa Basin during the Cambrian, depositing laterally extensive carbonates and shales across much of the southern Laurentian margin (Galley, 1958; Adams, 1965). Uplift and folding of the

NW/SE trending Central Basin Platform in the Pennsylvanian during the Ouachita-

Marathon orogeny separated the Tobosa basin into the Delaware and Midland Basins in the west and east, respectively. Both basins continued to subside from flexural subsidence during Mississippian-Pennsylvanian collision between Laurentia and

Gondwana and resulting Ancestral Rocky Mountain deformation (Ye et al., 1996), potentially driven by Central Basin platform and Ouachita-Marathon orogenic loads

(Hills, 1984; Ross, 1986; Ewing, 1991). Yang & Dorobeck (1995) suggest additional subsidence mechanisms are required, including variable basement composition, thermal contraction, or wrench-style faulting along the Central Basin Platform margins

(Barker & Pawlewicz, 1987; Barker & Pawlewicz, 1993; Adams & Keller, 1996; Hoak et al, 1998).

2.2 Stratigraphy

The stratigraphy of the Delaware Basin includes Ordovician through Cretaceous carbonates, siliciclastics, evaporates, and organic-rich mudtsones. Their structure and thicknesses have been well documented in previous studies (Ewing, 1991; Ruppel et

al., 2009; Wright, 2011). In general, these units thicken from west to east (figure 1). The majority of sedimentation takes place in the Paleozoic, with the Wolfcampian and

Leonardian constituting the major of basin fill up to 3500m thick (figure 4). The basal

Ordovician through Mississippian carbonates including the Ellenburger, Simpson,

Devonian, and Mississippian limestones record passive margin sedimentation during initial Tobosa Basin formation and are up to 2000m thick in the eastern depocenters of the basin. The Devonian Woodford formation and Mississippian Barnett formation are organic-rich mudrocks up to 150m and 800m thick respectively. Basinal mudstone facies continued to deposit through the Pennsylvanian and Permian as subsidence rates increased leading to increased accommodation, with up to 1500m of the carbonate and organic-rich Wolfcamp formation preserved. The overlying Leonardian

Bone Spring is a 1300m thick series of three alternating siliciclastic and carbonate- dominated mudstones, followed by three Guadalupian deep marine sandstone formations of the Delaware Mountain Group up to 2000m thick. Late Permian stages of basin filling include Ochoan evaporates such as the Rustler, Salado, and Castile formations, up to 1300m thick. Minor siliciclastic sedimentation of the Dockum group less than 200m thick occurred primarily in northern portions of the basin. An additional period of carbonate sedimentation occurred in the Cretaceous during the formation of the interior seaway, however its thickness is not well constrained due to modern uplift and erosion.

The Ellenburger, Woodford, and Barnett formations maintain their pre- deformation thickness across most Permian Basin features, and the post-Pennsylvanian

Wolfcamp and Bone Spring terminate at the Central Basin Platform transitioning into

shelf carbonates. Deposition of the Permian Delaware Mountain group, late Permian

Ochoan evaporites, and Triassic Dockum Group led to a maximum burial of 7600m

(Galley, 1958). The post-Paleozoic record is poorly preserved due to subsequent

Cenozoic tilting and uplift, leading to the current asymmetric basin structure (Hills, 1984;

Horak, 1985; Hill, 1996).

Figure 4. Map showing the Delaware basin location and stratigraphy, with well location and study area indicated. Stratigraphy was modeled based on the Lineberry Evelyn #1 well, which is adjacent to the Central Basin Platform in the basin depocenter. Organic rich intervals are listed in the right column, with blue stars showing the sample locations for RSCM measurements.

2.3 Exhumation History

The exhumation history of the Delaware Basin remains poorly constrained, but may have been affected by phases of uplift and erosion since maximum burial in the late Cretaceous. The first is attributed to Laramide shortening at ~80-50 Ma which potentially caused ~1185 m of exhumation across the Permian Basin (Horak, 1985;

Gregory & Chase, 1992; Hill, 1996; Sinclair, 2007). The second includes a period of thermal doming and eastward basin tilting during Basin and Range extension and crustal thinning from 30-0 Ma, causing up to 1100 m of unroofing. (Elston, 1984;

Sahagian, 1987; Hill, 1996; Sinclair, 2007). Near-vertical en echelon dikes accompanied extension, primarily along the western and northern basin margins, and are inferred to exist at depth based on aeromagnetic survey data and intercepted boreholes (Elliot,

1976; Calzia & Hiss, 1976; Henry & Price, 1985; Powers et al., 1978). This study investigates the thermal maturity of Ordovician through Permian marine mudrocks in

Reeves, Loving, and Ward counties, specifically the Bone Spring, Wolfcamp, Woodford,

Barnett, and Ellenburger Formations (figure 4). These units are laterally extensive and record changing tectonic settings during Paleozoic transition from passive margin basin to collisional orogenic foreland basin. Additionally, they contain high TOC (2-12%) and are currently situated within the hydrocarbon generation window (0.5-3.0 %Ro) making them strong candidates for low temperature RSCM.

2.4 Thermal Characteristics

Current bottom hole temperatures in the Delaware Basin show that the western portions have approximately 30-35% higher geothermal gradients than eastern portions, at approximately 40–45oC/km in the west vs. 20–30 oC in the east (Barker & Pawlewicz,

1987; Ruppel et al., 2005). Maturity estimates from vitrinite reflectance results suggest that current bottom hole temperatures are likely lower than peak temperature sediments reached during maximum burial (Sinclair, 2007; Pawlewicz et al., 2005). Laramide and

Basin and Range events in the late Cretaceous and Oligocene may have altered the thermal regime by eroding overburden bringing hotter sediments to shallower depths, increasing the heat flux through crustal thinning, or intruding volcanics creating thermal anomalies. Schneider and Hinojosa (1991) suggest that higher heat flows in the west may be attributed to proximity to the Rio Grande Rift thermal anomaly, which provided both elevated basal heat flow and thermal uplift for an area much wider than the mapped rift (Seager and Morgan, 1979). This anomaly was also responsible for much of the volcanism in the basin.

Isoreflectance lines of maximum maturity suggest two maturity profiles resulting from two episodes of heating (Barker & Pawlewicz, 1987; Barker & Halley, 1986; Barker

1990). Peak temperatures in the east follow closely with formation boundaries, suggesting they are a function of maximum burial depth. In the west, isoreflectance lines cross formation boundaries with some units becoming more mature at shallower depths, suggesting additional heating variables other than overburden elevated the paleogeothermal gradient past the average gradient for the rest of the basin (Figure 1).

While igneous intrusions along the western margin have only been inferred to exist in west Reeves, west Culberson, and Jeff Davis counties, gas-rich trends extend into east

Culberson and Reeves County, suggesting the identified intrusions alone are not responsible for the heightened maturity gradient.

2.5 Igneous Intrusions in the Delaware Basin

Cenozoic magmatism in west Texas is dominantly located in the Trans-Pecos region west of the Delaware basin in the Lincoln County Porphyry Belt (LCPB) on the

Northwest Shelf. These igneous features are considered part of the greater Rocky

Mountain alkali province, which is related to the transition from Laramide orogeny ending in the Eocene to the onset of Basin and Range extension (Henry & Price, 1986;

Barker & Pawlewicz, 1987; Allen & McLemore, 1991; Allen et al, 1991; Stewart &

Faulds, 1998). Two phases of magmatism are recorded in this region: a series of ENE trending alkali syenite, granite plutons, and mafic intrusions from 37 to 30 Ma; and several WNW trending mafic dike swarms from 32-28 ma. The shift in composition between the older alkali granites and younger exclusively mafic dikes occurs around 28

Ma and is associated with a change in feature orientation from ENE to WNW, potentially linked with changing stress regime during the transition between Laramide compression and Rio Grande Rift extension (McMillian et al, 2000; Price & Henry, 1984). Earlier alkaline intrusions are interpreted as being subduction related melts, while later mafic intrusions may be linked with mantle upwelling accompanying Farallon plate detachment and lithosphere removal (figure 5) (McMillian et al 2000; Henry et al, 1991).

A second trend of high-angle, mafic dikes exposed at the surface trend WNW and are dominantly situated in the Trans Pecos volcanic trend west and southwest of the Delaware basin. While some younger alkaline bodies also exist in the Trans Pecos trend, the mafic body emplacement almost exclusively postdates the onset of extension, is concentrated in the south, and unlike mafic trends of the Rio Grande region, continues through half-graben sedimentation 24-18 Ma (Dasch et al., 1969;

McDowell,1979; Barker, 1987). Most of these features are exposed in outcrop at the surface west of the basin in Culberson and Jeff Davis Counties, and are also present in the subsurface further east in Reeves County.

These two igneous trends occur roughly within the same region but represent different tectonic drivers at different times. Mapping their distribution and investigating the potential impact on peak temperatures has implications for localized organic matter maturation. While most of these features have surface exposures outside the confines of the basin, their trends continue in the subsurface and have been encountered in several exploration wells, such as Texaco #1-29 (Reeves County), Magnolia Cowden

#1 (Culberson County), and 23 additional wells in Eddy and Lea county (figure 6)

(Calzia and Hiss, 1978).

An attempt was made to obtain an emplacement date in the mafic intrusion encountered in Texaco #1-29 through apatite U-Pb LA-ICP-MS. However, apatite grains from the intrusion lacked sufficient U and Th for geochronologic analyses. General compositional observations are noted, such as an abundance of plagioclase, biotite, hornblende, apatite, and chlorite, and lacking in silica-rich minerals such as quartz and zircon. Due to its proximity to the Trans-Pecos volcanic province, apparent low silica content and likely mafic character, and being situated near several NW-trending normal faults, we suggest this as a subsurface expression of WNW-trending, post-Laramide, post-rift mafic intrusions exposed at the surface to the west.

Figure 5. Events illustrating the link between change in magmatic composition and regional tectonics. The shift in intrusion trends may be genetically linked to subduction characteristics of the Farallon Plate, which steepened and eventually detached between 45-28Ma. This shift is accompanied by altered regional stress regimes, thinning lithosphere, and uplift in the western Delaware Basin (modified from McMillan et al., 2000)

Figure 6. Map showing the location of known igneous intrusions in the Delaware basin region. Blue colors represent rocks of older, generally alkaline, composition trending ENE, and red colors represent younger WNW trending mafic rocks. Darker colors are surface exposures, while pale colors are intrusions encountered in the subsurface.

Table 1. Wells selected for RSCM analysis

Lease Name API TD (m) KB (m) Lat Lon TEXACO #1-29 423891055200 3333.0 1095.1 31.1895525 -104.0686863 REEVES STATE #1 423890090500 3532.6 981.2 31.1344183 -103.8457549 TENNEY, GERALD E. #1 423891046400 3651.5 934.5 30.9304198 -103.5785616 WEINACHT #1 423893155700 3916.7 1053.4 30.8928944 -103.6778147 TODD, W.L. ET AL JR. #1 423890054600 4011.2 851.9 31.3429387 -103.7006546 LAGO UNIT #1 423013004500 4998.7 869.6 31.9161985 -103.8511079 HORRY, L. ET AL #3 423891023400 5228.5 791.9 31.355509 -103.2588172 POWERS #1 423891053000 5486.4 831.5 31.2106646 -103.4799153 RAPE, J.M. #1 423891049600 5638.8 794.3 31.2556722 -103.1377006 MOORE & HOOPER ET AL #1 423013002000 6644.6 830.9 31.7154487 -103.5727203 LINEBERRY, EVELYN #1 423011017000 6844.6 906.5 31.9186841 -103.3317174

3. METHODS

11 vertical wells from the Delaware basin were identified at the University of

Texas Bureau of Economic Geology Austin Core Research Center that had stored cuttings spanning Ordovician through Guadalupian intervals and adequate lateral spacing to cover eastern and western portions of the basin (Table 1). The cuttings had been stored in paper envelopes in open-air conditions. Organic rich intervals of equivalent formations were identified in each well based on wireline log signature.

Targeted intervals included the upper contact of the First Bone Spring Carbonate,

Wolfcamp A, Barnett, Woodford, and top Ellenburger. These formations are buried at modern depths greater than 1000 m, and generally span the oil and gas generation windows from 0.5%Ro to 3.0%Ro. In wells that did not penetrate the basal Ellenburger formation, an organic-rich interval from the overlying Simpson formation was taken at maximum drilling depth. One well contained incomplete sections, and were supplemented by wells less than 1km away. In total, 53 samples were taken. Each sampled interval was averaged over 30m of labeled cutting section since sediment mixing occurs in the wellbore and sampling depth can contain cuttings from outside the labeled interval. The cuttings were washed with ethanol to remove paper flakes and mold from the storage envelopes, impregnated with epoxy resin and polished to 30µm open-face thin sections at National Petrographic Service, Inc.

3.1 Raman Spectroscopy of Carbonaceous Material (RSCM)

RSCM measurements were conducted in accordance with procedures described in Kouketsu et. al. (2014). The Raman data were collected using a custom-built Raman

spectrometer in a 180° geometry. The sample was excited using a 1.3 mW Coherent

Sapphire SF laser with a 532 nm laser wavelength and 1µm focal diameter. The laser power was controlled using a neutral density filter wheel and an initial laser power of

100mW. The laser was focused onto the sample using a 50X super long working distance plan APO Mitutoyo objective with a numerical aperture of 0.42. The signal was discriminated from the laser excitation using an Ondax® SureBlock™ ultranarrow-band notch filter combined with two optigrate notch filters. The data were collected using an

Acton 300i spectrograph of 1200nm grading and a back thinned Princeton Instruments liquid nitrogen cooled CCD detector.

Each polished cutting was initially interrogated at random points by the Raman laser at a low-resolution exposure of 0.1 seconds per spot to identify carbonaceous areas designated by peaks in the Raman spectra at 1350cm-1 and 1600cm-1. Once the presence of organic carbon was confirmed, the laser was focused on the surface of the thin section directly over the point of maximum peak intensity and signal to noise.

Identification by optical microscope aided in maceral identification (figure 7). Attempts were made to focus on a position 10µm below the surface to reduce the effects of oxidation, however the opaqueness of most grains prevented light interaction beneath the surface. Three collections acquired at 10 seconds each on the same location are averaged for each maceral to maximize signal-to-noise ratio. The spectrometer was calibrated with a known sample of cyclohexane every 12 hours of use to correct for instrument drift.

800

700

600

500 Intensity(counts)

400 0 500 1000 1500 2000 -1 Waveshift (cm )

Figure 7. Thin section plain polarized light view showing opaque macerals illuminated in a carbonate matrix, with the laser focus position in red. The presence of carbon is confirmed by an initial Raman laser interrogation of 0.1s, which can quickly confirm the characteristic dual-peak spectra with peak positions at 1350cm-1 and 1600cm-1 (right).

3.2 Collection Regime

For each thin section representing a 30m depth range, six well cuttings were randomly selected for analysis. Within each cutting, three macerals were analyzed for a total of 18 Raman data points per depth. There is no consensus as to how many minimum Raman data points can adequately characterize a sample. Within this study,

18 data points were determined to be sufficient to observe clustering of data, which is more than Beyssac et al. (2002), Rahl et al. (2005), Yui et al. (1996), Lahfid et al.

(2010), and Wilkins et al. (2014) who used 10-15 data points, but less than Aoya et al.

(2010) which used 25, Lünsdorf et al. (2014), and Kouketsu et al. (2014) who used 30.

Due to the irreversibility of thermal maturity, already matured organic material can be recycled from older detrital sources and incorporated into the target sedimentary layer,

biasing the peak temperature readings higher. In vitrinite reflectance studies, it is common to either accept the lowest reflectance reading as the true value or establish a histogram to determine clustering. Due to internal caving and cutting mixing within the wellbore, we chose to identify the average temperature within each sample and exclude data points outside 2σ error.

3.3 Peak Fitting and Data Decomposition

The spectrometer measures Raman shift noted in wavenumber (cm-1) and intensity. The collector focused on the first order region of carbon (1100-1800 cm-1). For peak temperatures less than 240oC, the disordered carbon structure displays up to 4 subpeaks at approximately 1245 (D4), 1350 (D1), 1510 (D3), and 1600 cm-1 (D2). In temperatures greater than 240-280oC, an additional subpeak at 1580-1593 cm-1 (G) appears, associated with the transition to ordered crystallographic graphite (Rahl et al.,

2005; Kouketsu et al., 2014).

The combined Raman spectra of each sample depth were decomposed using the peak-fitting functions in Matlab, which was compiled into a Raman-specific user interface platform by Emmanuel Soignard at Arizona State University LeRoy Eyring

Center for Solid State Science. The GUI iterates the parameters of each subpeak until achieving an optimal overlap between modeled and observed spectra. The initial collected spectra were corrected for background fluorescence by subtracting a linear function determined by connecting the lowest reading at 1100cm-1 and 1800cm-1 (figure

8). The amount of background fluorescence generally decreases with maturity, requiring almost no correction for samples greater than 1.7% Ro.

In previous studies, subpeak position, height, full width at half maximum, and other attributes have been empirically correlated with reference parameters from samples with well-constrained temperature histories. For this study, the

Figure 8. The raw Raman spectra are initially corrected for background fluorescence by subtracting a linear function connecting the lowest points at 1100cm-1 and 1800cm-1. The slope of the linear function is proportional to the background fluorescence of the sample, which decreases with thermal maturity.

Kouketsu et al. (2014) method was selected based on its potential sensitivity and precision in low-temperatures of 165-300oC. These temperatures approximately represent the onset of oil generation to the maximum predicted temperatures expected for the Ellenberger formation in the Delaware Basin. In this study, we applied this 26

method to samples with temperatures as low as 60oC to determine if the lower limit could be extended with reasonable results.

The Kouketsu et al. (2014) method determines a temperature value by deconvolving the spectra into 4 peaks at D4 (fixed at 1245 cm-1), D1 (approx. 1350 ± 20 cm-1), D3 (fixed at 1510 cm-1), and D2 (1600 ± 10 cm-1). Because graphite is not expected at temperatures less that 240o, this method matches parameters by excluding the G peak from the spectrum. The equations for obtaining temperature from the subpeak parameters are:

(eq 1.) T (oC) = -2.15(FWHM D1) + 478

(eq. 2) T (oC) = -6.78(FWHM D2) + 535 where FWHM D1 and FWHM D2 are the full width at half maximum of the D1 and D2 bands (figure 5). Both equations can be applied independently to the same samples and averaged, but Eq. 2 has higher precision for samples lower than 200oC, where eq. 1 generally plots higher and eq. 2. plots lower. Because some samples in this study are taken from intervals estimated as low as 60oC, reported temperatures are averaged from results of both equations for each sample.

3.4 Sampling Regime

In each sample, three macerals were analyzed in each of 6 cuttings. Each maceral was analyzed by three 10 second laser shots, and all of these shots of the sample are averaged automatically within the acquisition software. Thus, single-point variation and instrument-contributed error were not explicitly recorded as part of this study. Instrument drift was corrected by calibrating the laser and collector to a known spectra of cyclohexane every 12 hours. Additionally, peak-fitting error was minimized

through digital matching, using the same constraints for each sample. Error for each sample may be attributed to variation in maceral composition, detrital maceral recycling, high sample fluorescence which decreases signal quality, or cave-ins from shallower units within the wellbore. No effort was made to identify each maceral independently, so

Raman spectra differences between maceral type remain unconstrained. However, existing results suggest that RSCM is not sensitive to maceral type (Wilkins et al.,

2014).

Figure 9. Peak-fitted Raman spectra showing evolving peak parameters with increasing depth and temperature. Peak full width at half maximum (FWHM) and peak distance were found to have the strongest correlation with temperature, where D1 and D2 FWHM decreases and the separation distance decreases with increasing peak temperature.

3.5 Data Plotting

Final temperatures were averaged from individual results of eq. 1 and 2, and determined for each sample point independently prior to being averaged for the entire sample depth. The 18 data points for each sample are plotted, where an average was determined for each cutting, and finally the sample as a whole (figure 8). Error is determined as a 1σ deviation from the sample average. Data points which fall outside of

2σ error were excluded from the final temperature value and are interpreted as either recycled detrital organic material, non-kerogen organic material such as bitumen, or a poor exposure to the Raman laser. Cutting temperatures 2σ or greater different from other cuttings in the same sample were discarded.

Figure 10. Worksheet showing individual peak-temperature measurements from Woodford sediments in Tenney Gerald E. #1 well at 1840m TVDSS. Each sample depth has 18 total measurements from 6 cuttings, where a sample average and outliers can be determined. In this sample, cutting #2 has lower paleotemperature than the other cuttings, suggesting that this cutting may be a cave-in from a shallower depth in the well.

3.6 Vitrinite Reflectance

Mean random vitrinite reflectance (%Ro) data exist for 43 wells within the

Delaware basin, each with n=3-24 %Ro analyses spanning depths from 100–6800m

(Pawlewicz et al., 2005). The %Ro data points were modeled in Petrel as a logarithmic function of their depth and contoured at 0.2% intervals to generate surfaces indicating depths of equal vitrinite reflectance. The surfaces were compiled into a 3D model, providing a standard against which the RSCM will be compared. Four of the wells used in Pawlewicz et al. (2005) were also selected for this study: Horry, L. et al. #3, Tenney,

Gerald E. #1, Lineberry Evelyn #1, and Lago Unit #1. This allowed a direct comparison of %Ro and RSCM for the same sample depth. These wells were also used to calibrate the Kouketsu et al. (2014) method to ensure the peak fitting results measured temperatures from Raman spectra were geologically reasonable prior to expanding to additional wells within the study.

3.7 Rock-Eval Pyrolysis

Rock-Eval pyrolysis was conducted on the same depths as RSCM samples for the Horry, L. et al. #3 and Tenney, Gerald E. #1 wells, providing an additional constraint for thermal maturity as a function of depth. Two grams of cuttings were powdered to at least 60 mesh using a pestle and mortar and submitted to Geomark for HAWK©

Pyrolysis Rock-Eval. Samples were held at 300oC initial temperature for 5 minutes, then elevated at 25oC per minute to a final temperature of 600oC, where they were held for 1 minute. Released hydrocarbons were measured as a function of temperature using a flame ionization detector. Parameters such as the S1 and S2 peak, Tmax, Production

Index, and Hydrogen Index were determined according to specifications in Espitalié et al, (1977), Espitalié (1982), and Espitalié et al (1985).

4. RESULTS

4.1 Calibration Wells

4 wells were selected to be calibration wells to confirm the peak-fitting procedure provided reasonable values: Horry, L. et al. #3, Tenney, Gerald E. #1, Lineberry Evelyn

#1, and Lago Unit #1. These wells have available vitrinite reflectance data for wellbore cuttings (Pawlewicz et al., 2005) that allow direct comparison between the two methods.

Temperature readings from RSCM were compared against %Ro values using the conversion from Barker & Pawlewicz (1986)

eq. 3 T (oC) = (ln(%Ro) + 1.4) / 0.0096 where T is peak temperature (oC) and %Ro is the mean random vitrinite reflectance.

This conversion assumes that %Ro is a function of peak temperature alone, and not a function of both temperature and burial time. Kinetic models suggest that vitrinite also matures as a function of burial time (Sweeny and Burnham, 1980). However, the heating rate, the time spent at a particular temperature, and cooling rate can be difficult to constrain without additional data.

4.2 RSCM and Vitrinite Reflectance Compatibility

Measured RSCM temperatures predictably increase with depth, except within a

200m zone adjacent to an igneous intrusion, where an inverse peak temperature gradient exists below the intrusion in well Texaco #1-29 (figure 11). Temperature values determined here range between 60oC ± 30oC, equivalent to ~0.4-0.5 %Ro, and up to

260oC ± 15oC, equivalent to ~3.0%Ro. These temperatures and 1σ errors are consistent with those predicted by vitrinite reflectance, suggesting the method could be

o o o 43.5 C/km 71.8 C/km 59.1 C/km

o o o 51.4 C/km 41.1 C/km 67.4 C/km

o o o 56.9 C/km 51.9 C/km 81.8 C/km

o o 70.8 C/km 43.3 C/km

Figure 11. Depth/temperature profiles and 1σ errors for each well analyzed with RSCM. A linear best fit trend line connecting the data points is used to determine the paleogeothermal gradient at the time of maximum temperature. Texaco #1-29 encounters an igneous intrusion at 1700m, where an RSCM data point was taken 30m above and 30m below to test the effects of localized heating.

satisfactorily extended to other wells which did not have a direct %Ro comparison

(figure 12). Errors on individual sample measurements generally decrease with increasing temperature, from ± 20-35oC for samples of 60-100oC to 5-25oC for samples of 100 to 300oC.

RSCM individual vs. %Ro Temperature 300

250 eq. 1 C) o eq. 2 200 y = 0.0021x2 - 0.1641x + 122.87 R² = 0.73 150 100

50 y = 150.98ln(x) - 628.55 R² = 0.81

RSCM RSCM Temperature( 0 0 50 100 150 200 250 300 -50 Vitrinite Equivalence Temperature (oC) A.

1:1 match

y = -0.0617x + 26.767 R² = 0.209

Y = 0.913x + 11.164 R2 = 0.8549

B. C.

Figure 12. A. RSCM temperatures as determined from eq. 1 and eq. 2 diverge for measured samples of less than 150oC. B. An arithmetic average between Eq1 and Eq2 provides a good approximation with temperatures suggested by vitrinite reflectance. Error is represented as ±1σ. %Ro was converted to oC using eq. 3 from Barker & Pawlewicz (1986). The black line represents a perfect 1:1 match between RSCM and %Ro. C. 1σ error for individual measurements generally decreases with increasing temperature, which is potentially a function of reduced disorder and variability in the carbon structure. 35

Final RSCM temperatures for the 150-260oC range are lower than the %Ro- suggested values by 30-60oC. Samples in the 60-150o RSCM range are more similar to their expected average based on the measured %Ro, with divergence of less than

30oC. Overall, the divergence between the RSCM temperature and the %Ro temperature increases with greater maturity.

RSCM temperatures from individual decompositions of the D1 and D2 FWHM are in agreement with both each other and the Vitrinite Equivalence Temperature between 150oC and 260oC, but diverge in the 60-150oC range where the temperature derived from D1 peak predicts higher temperatures, and temperature derived from the

D2 predicts temperatures lower than the expected Vitrinite Equivalence Temperature

(figure 12).

4.3 Vitrinite Reflectance Interpolation

%Ro data from Pawlewicz et al (2005) was input into Petrel as value/depth pairs where surfaces representing depths to equivalent %Ro could be generated using spline interpolation. This allows specific %Ro value depths to be extended to regions with few wells, or where an RSCM datapoint falls between wells with %Ro. The interpolated surfaces show depth to a specific maturity generally decreasing to the west, with the deepest maturity windows adjacent to the Central Basin Platform (figure 13).

An isochore between 0.8% and 2.8% provides a close approximation of the %Ro gradient for the entire stratigraphic column. Gradient values generally increase from

0.5%/km in the east to 1.1%/km in the west. Isolated hotspots up to 1.3%/km exist in

Eddy and Leah County on the northwest and northern margin of the Delaware Basin and are generally restricted by one or two wells. A broader region of elevated gradient

of 1.0-1.1 %/km is constrained by 6 wells and is centered on the intersection of

Culberson, Reeves, and Jeff Davis Counties along the southwest margin of the basin.

Figure 13. Maps of interpolated vitrinite reflectance values, showing depth to 0.8% maturity (left) and the vitrinite gradient from 0.8-2.8% (right).

4.4 Rock-Eval Pyrolysis

Rock-Eval data for the Tenney, Gerald E #1 well are listed in table 2. Tmax,

Production Index, and Hydrogen Index values are of interest at each sample depth, since these parameters are most sensitive to thermal maturity. TOC values range from

0.58% in the Ellenburger to 3.95 in the Woodford. Tmax values range from 430oC to

457oC. Hydrogen Index values range from 376 to 35. Production index values range 37

from 0.13 to 0.32. The Tmax and Production Index values generally increase with depth, and the Hydrogen index values decrease with depth, showing the increasing thermal maturity. Using the classifications of Peters (1986) and Espitalié (1982), the

Hydrogen index of 376 mgHC/gTOC and Tmax of 376oC in the Bone Spring suggest the shallowest unit is marginally within the oil window, and Tmax of 457oC in the

Ellenburger suggest the deepest unit is in the gas window.

Table 2. Rock Eval Pyrolysis results for Tenney, Gerald, E. #1

Sample Fm. Depth S1 S2 Tmax HI OI PI TOC (m) (mgHC/g (mgHC/g (oC) (TVDSS) rock) rock) GRLD Bone 983 1.82 12.44 437 376 10 0.13 3.15% 1 Springs GRLD Wolfcamp 1589 0.86 4.36 439 151 16 0.16 2.80% 2 A GRLD Barnett 1687 1.49 6.31 430 166 10 0.19 3.66% 3 GRLD Woodford 1839 1.71 5.67 445 138 10 0.23 3.95% 4 GRLD Ellenburger 2613 0.09 0.2 457 35 36 0.32 0.57% 5

4.5 RSCM Data Points

Once the RSCM method of Kouketsu et al. (2014) could be successfully reproduced on the calibration wells and provide geologically reasonable values as compared with the vitrinite reflectance and Rock-Eval pyrolysis, identical peak-fitting procedures were carried out on the remaining 8 wells in the study that lack

complementary vitrinite reflectance data points, prohibiting direct comparison for these wells and intervals.

Table 3. RSCM results for 11 wells sampled in the Delaware Basin. Depths are in true vertical depth subsea (TVDSS). Equivalent %Ro is either measured at that depth (bold) or interpolated from isoreflectance surfaces generated in Petrel.

Sample TVDSS RSCM Temp. 1σ error FWHM D1 FWHM D2 D1 Temp D2 Temp Equivalent Name Formation (m) (Co) (Co) (cm -1) (cm -1) (Co) (Co) %Ro

Lago1 First Bone Spring 1386 74 17.46 166.99 75.19 121.54 27.38 0.45 Lago2 Wolfcamp A 2697 111 14.96 167.21 64.36 118.50 98.63 0.79 Lago3 Barnett 3779 188 12.03 143.08 49.56 170.38 198.98 2.61 Lago4 Woodford 4068 258 11.34 107.64 39.30 246.58 268.55 3.01 M+H1 First Bone Spring 1677 81 18.18 169.65 72.91 113.25 46.04 0.45 M+H2 Wolfcamp A 2960 142 9.34 150.05 60.38 155.39 128.62 1.51 M+H3 Barnett 4570 221 20.10 122.56 45.28 214.51 228.02 2.70 M+H4 Woodford 4786 244 11.03 110.10 42.38 241.29 247.64 3.20 Pow 1 First Bone Spring 1698 90 36.18 152.82 74.29 149.43 31.32 0.55 Pow 2 Wolfcamp A 2430 157 28.95 141.16 58.31 174.52 139.65 0.84 Pow 3 Cisco 3823 177 12.38 136.91 58.91 183.65 169.56 2.20 Pow 4 Barnett 4551 200 19.12 127.93 51.09 202.96 188.58 2.87 Pow 5 Woodford 4655 229 6.00 114.16 45.72 232.57 225.00 3.00 Terril Ellenburger 5665 259 5.77 100.48 41.11 261.96 256.30 3.50 Rape1 First Bone Spring 1705 73 12.45 170.01 76.49 112.48 30.75 0.69 Rape2 Wolfcamp A 2391 112 13.86 161.52 68.70 130.74 69.21 0.95 Rape3 Barnett 3320 142 15.52 153.24 62.97 153.73 130.87 1.47 Rape4 Woodford 3561 171 18.02 144.06 53.39 168.28 172.99 1.64 Rape5 Simpson 4616 240 25.83 109.14 44.10 243.35 236.00 2.60 Hory1 First Bone Spring 1403 59 27.79 167.95 77.52 116.91 9.40 0.40 Hory2 Wolfcamp A 2409 105 21.41 162.52 69.62 128.58 62.96 0.85 Hory3 Barnett 3018 125 25.40 149.22 65.19 157.17 92.98 1.33 Hory4 Woodford 3277 162 15.89 144.39 55.74 167.55 157.09 1.61 Hory5 Ellenburger 4365 172 39.10 141.40 53.84 173.99 169.93 3.01 Grld1 First Bone Spring 983 64 22.32 157.51 79.03 139.36 -0.85 0.51 Grld2 Wolfcamp A 1589 97 24.40 155.69 72.94 143.26 40.44 0.72 Grld3 Barnett 1687 118 24.59 161.85 24.59 118.32 118.32 0.76 Grld4 Woodford 1839 129 8.26 157.29 63.43 139.82 104.96 0.84 Grld5 Simpson 2613 175 19.35 140.90 52.91 174.93 175.55 1.39 Todd1 First Bone Spring 1327 102 18.84 161.15 69.18 131.53 71.37 0.65 Todd2 Wolfcamp A 2361 153 12.70 147.74 57.41 160.36 145.75 1.49 39

Table 3. Continued

Sample TVDSS RSCM Temp. 1σ error FWHM D1 FWHM D2 D1 Temp D2 Temp Equivalent Name Formation (m) (Co) (Co) (cm -1) (cm -1) (Co) (Co) %Ro

Todd3 Barnett 2973 190 11.29 133.62 50.96 190.72 189.52 2.47 Todd4 Woodford 3120 227 9.28 116.15 45.66 228.28 225.46 2.81 Tex1 First Bone Spring 673 63 19.57 181.18 73.52 88.46 36.56 0.63 Tex2 Barnett 1237 86 23.48 167.78 70.82 117.28 76.48 0.94 Tex3 Woodford 1480 140 15.62 149.87 61.49 155.79 122.54 1.19 Tex4 Fusselman 1654 198 12.39 129.53 50.05 199.52 195.66 1.50 Tex5 Montoya 1779 195 9.95 128.80 51.15 201.08 188.20 1.52 Tex6 Ellenburger 2227 182 12.00 130.51 54.31 197.40 166.81 2.39 Reev1 First Bone Spring 939 108 18.99 157.08 67.86 140.28 74.94 0.56 Reev2 Wolfcamp A 1195 109 14.74 153.10 69.86 148.84 71.76 0.68 Reev3 Woodford 1396 141 15.94 145.58 63.19 164.23 119.43 0.74 Reev4 Ellenburger 2244 176 12.63 134.13 55.06 189.42 161.54 1.50 Lbry1 First Bone Spring 1811 83 29.88 167.48 71.82 117.92 48.05 0.73 Lbry2 Wolfcamp A 3063 138 19.94 153.06 61.87 148.92 124.13 1.14 Lbry3 Barnett 4542 187 12.04 137.03 52.97 185.16 188.59 2.08 Lbry4 Woodford 4889 206 11.00 127.78 47.98 203.27 209.67 2.23 Lbry5 Simpson 5828 263 10.11 103.67 41.07 257.47 268.09 2.61

The sample points show peak temperatures between 62oC and 262oC. Best-fit linear trend lines were determined for each well, where the slope was intepreted as peak paleogeothermal gradient. This approximates an otherwise logarithmic gradient to a single value which can be mapped spatially. Temperature/depth pairs were imported into Petrel where isotherm grid surfaces were generated at 20oC intervals between 60oC and 260oC (figure 14). Contours that were not explicitly defined by observed data were extrapolated using spline interpolation based on the peak temperatures of nearby wells and the linear depth/temperature trendline. Depths are plotted as true vertical depth subsea (TVDSS). RSCM temperature contour maps were clipped near the Texas/New

Mexico border and the western border of Reeves County because we were unable to obtain well cuttings for Culberson, Jeff Davis, Eddy, or Lea County.

4.6 RSCM Uncertainty

Overall uncertainty for individual samples decreases linearly as a function of increasing peak temperature. At higher temperatures, the D1 and D2 parameters the decomposition is sensitive to are better constrained, less affected by background fluorescence, and are more consistent between individual macerals. Less ordered carbon results in less precise peak fitting of individual Raman spectra, resulting in more variability within the same cuttings. Additionally, Lünsdorf et al. (2014) show that fluorescence disrupts signal quality more for low-temperature samples than for high- temperature samples, and can be mitigated by using a shorter wavelength laser. Their study utilized a 488nm laser, whereas this study used a 532nm wavelength, leading to increased error associated with greater influence from sample fluorescence. In samples with %Ro greater than 1.3%, the background fluorescence decreases, with almost no correction being required for samples above 1.7%.

The variation in temperature derivations from FWHM measurements due to peak- fitting methods have negligible impact, because the peak-fitting was done objectively in

Matlab by minimizing the chi-squared value between observed and fitted spectra. This minimizes any user bias that could result from manual peak-fitting, which may generate non-unique values for FWHM if one peak is overemphasized in the user workflow. Most variation between measured samples of equivalent peak temperature can potentially be attributed to differences in maceral type, oxidation, or disorder within the carbon structure.

Figure 14. Maps showing the depth to RSCM values of 120oC (left) and the peak temperature paleogeothermal gradient (right).

4.7 RSCM Surfaces

Surfaces representing isotherms between 60oC and 260oC have north-south trending depth contours. This is consistent with higher temperatures at shallower depths in the western regions of the basin compared to the east. The greatest depth that the lowest peak temperature of 60oC occurs at 1670m TVDSS in the Rape, J.M. #1 well in the southeast corner of the study area, while the same temperature is observed at a minimum depth of 60m TVDSS in the Texaco #1-29 well in the western region. For the

highest peak temperature of 260oC, the deepest occurrence is observed at 6000m in

Horry, L. et al #3 towards the east, and the shallowest occurrence is observed at 3090m in Texaco #1-29. Depths to any particular isotherm are generally greatest in the east with the deepest values trending in a N/S trough adjacent to the Central Basin Platform.

The geothermal gradient from peak temperature was calculated in each well by dividing the differences in temperatures by the differences in depths between the shallowest and deepest isotherms in each well. In map view, this was generated by creating an isochore between the 80oC and 240oC grid surfaces. The 60oC and 260oC surfaces were not used in this calculation because not all the wells contained RSCM datapoints constraining these surfaces.

The peak-temperature geothermal gradient map shows values between 40oC/km and 72.5oC/km with the gradient generally increasing from east to west. Lowest geothermal gradient values define a north-south trending feature situated west of the

Central Basin Platform flank with peak gradient values between 40-50oC. The highest geothermal gradient values are observed on the western side of the study area up to

72.5oC. Geothermal gradient contour lines are generally parallel with the temperature depth contours, suggesting that areas of heightened gradient and temperature are spatially overlapping.

5. DISCUSSION

5.1 RSCM Peak Temperatures Contrasted with %Ro Temperature Estimates

When %Ro values are converted to peak temperatures using the time- independent model of Barker and Pawlewicz (1986), the RSCM and %Ro peak temperatures diverge with increasing depth (figure 15). In general, RSCM values underestimates %Ro results, especially in the higher maturity samples. Because %Ro values may continue to increase if subjected to continued heating at a constant temperature, a time-cumulative model such as the Time-Temperature Index (TTI) of

Lopatin (1971) and Waples (1980) may explain why sediments of longer heating duration are showing higher temperatures than RSCM values suggest.

Higher maturity sediments measured here (greater than 1.2 %Ro) are taken from pre-Wolfcamp units, which experienced burial at the end of the Permian, and remained at depth for greater than 200 million years. The lowest maturity samples (less than

0.8%Ro) may have only experienced burial during Cretaceous sedimentation, and were exhumed 20-30 million years later during late Cretaceous uplift and basin tilting.

If temperatures as constrained by vitrinite reflectance are sensitive to the cumulative time at peak temperature, and RSCM values as defined by the Kouketsu et al. (2014) publication are not sensitive to cumulative time at peak temperature, we could expect systematic offset between peak temperature estimates from RSCM and %Ro as burial duration increases in samples that were deeply buried and experienced minor exhumation. Time-independent vitrinite temperatures as shown here using the

Pawlewicz (1986) conversion do not account for the discrepancy in heating times and

RSCM vs. %Ro all Wells 3.50

3.00

2.50 Eq 2.00

1.50 RSCM%Ro 1.00

0.50

0.00 0 0.5 1 1.5 2 2.5 3 3.5 %Ro Measured

Figure 15. Plot of %Ro measured vs. RSCM %Ro equivalence. When all RSCM sample points in the study are compared with their equivalent %Ro surface value, there is greater spread for higher maturity samples, with RSCM values generally underpredicting %Ro.

will over-estimate temperatures, especially for deeper sediments that have remained at elevated temperatures for longer. This is consistent with similar %Ro comparisons with

RSCM, such as Wilkins et al (2014) which also showed higher divergence between

%Ro and RSCM for higher maturity samples.

5.2 Comparison with Pyrolysis Rock-Eval

The RSCM maturity estimates generally agree with Rock-Pyrolysis maturity estimates obtained in the Tenney, Gerald E. #1 well (figure 16). While maturity estimates from Pyrolysis are generally less precise than vitrinite reflectance unless

tailored to an immature sample of each source rock, generalized maturity estimates of oil and gas maturity thresholds from each parameter are described in Espitalié et al.

(1982), Jones (1984), Espitalié et al. (1985), and Peters (1986) and can provide estimates for oil and gas thresholds. RSCM, pyrolysis, and %Ro maturity estimates can be compared within each sample and extrapolated over the depth of the well to model the depths at which each hydrocarbon product is predicted to occur. At relatively shallow depths, Rock-Eval predicts higher maturity than equivalent RSCM results. At depths associated with gas generation, Rock-Eval and RSCM results are generally in agreement. However, this is a tenuous interpretation because only one measurement each was acquired from the heavy oil window and the dry gas window.

5.3 Trends in Peak Temperature

While many workers interpret the higher vitrinite reflectance values in the western portions of the basin as evidence of greater previous burial and later exhumation, this interpretation fails to account for the increased gradient of vitrinite reflectance in the same region, at 1.0-1.3 %Ro/km in the west vs. 0.55-0.9 %Ro/km in the east. While overburden may have been greater during times of maximum burial in the late

Cretaceous, the geothermal gradient at times of peak temperature would also need to be elevated to account for the observed gradients. Both RSCM and vitrinite models reveal an increase in geothermal gradient towards the west, consistent with this region experiencing a higher heat flux at some point in the basin history, and also suggesting that elevated peak temperatures are not a function of burial depth alone. RSCM peak temperature geothermal gradients vary from 42.5oC/km in the east to 72.5oC/km in the west, which is significantly higher than modern geothermal gradients for the Delaware

1000m

TVDSS(m) 2000m

3000m

Figure 16. %Ro, Pyrolysis, and RSCM results (converted to %Ro) plotted against depth from the Tenney, Gerald E. #1 well. Onset of oil and gas windows were equated based on approximations from Espitalié et al. (1982), Jones (1984), Espitalié et al. (1985), and Peters (1986). The shaded regions represent the depths inclusive of product onset that encompasses all variables compared. RSCM generally provides consistent results with %Ro and Pyrolysis, suggesting the method provides geologically reasonable values. suggests that peak temperatures in the past developed during a time when there was

Basin of 21-28oC/km (Ruppel et al., 2005). Those modern geothermal gradient estimates were based on surface temperatures and corrected bottom hole temperatures, assuming the geothermal gradient increased linearly with depth. This an elevated geothermal gradient. Radiogenic heat production from basement does not vary significantly through 250 million years (Arevalo et al., 2009), suggesting that elevated temperatures were the result of higher basal heat flow potentially related to transient tectonic or igneous events. Modern high heat flow is reported to occur in the

Rio Grande Rift west of the Delaware Basin, where thermal anomalies affect an area several times broader than the mapped rift (Seager and Morgan, 1979).

A peak geothermal gradient of 72.5oC/km is high even in rift zones where elevated gradients are typically 35-60oC/km (Nathenson and Guffanti, 1988; Christie and

Nagihara, 2016). Vitrinite reflectance gradients of 0.5%/km in the east to 1.3%/km in the west support higher gradients during times of maximum heat flow, where tectonic events such as rifting could be significantly contributing to the overall heat budget. The paleo-geothermal gradient of 72.5oC/km determined from these new RSCM data is not geologically unreasonable considering the proximity to igneous intrusions, and may be additionally biased higher by recording the maximum temperature sediments reach at any time, rather than maximum temperatures at a specific time (Amir et al., 2005).

5.4 Comparison of Trends between RSCM and %Ro

While both RSCM and Vitrinite reflectance both show roughly parallel trends of increasing thermal gradients and hotter temperatures shallower in the west, certain wells have decreased agreement between the two methods. In general, wells in the west show the RSCM results are consistent with %Ro maturity values, or overestimate

temperatures, whereas wells in the east show RSCM results that consistently predict peak temperatures lower than equivalent %Ro maturity values (figure 17). These regions with lower RSCM temperatures are closely aligned with the sediment depocenters adjacent to the Central Basin Platform. I interpret this disagreement as the difference between sediment maturity, and sediment peak temperature. Vitrinite reflectance integrates time spent at burial temperature and preserves resultant maturity

(Lopatin, 1971). In contrast, RSCM records peak temperature, but does not integrate time spent at that temperature. As such, when converting relatively higher maturity estimates from %Ro to peak temperatures, vitrinite reflectance may predict anomalously higher temperatures than RSCM.

Because vitrinite is a time-dependent process, and RSCM is a time-independent process, the difference between them can be used as an index for heating duration, as longer-duration sediments will have higher %Ro value than peak temperatures alone could produce over a short geologic time span. This interpretation is illustrated spatially when an isochore map is taken between surfaces representing a maturity of 0.8% and

RSCM temperatures of 120oC, which are equivalent in a time-independent conversion.

The trends in vertical offset between time-dependent (%Ro) and time-independent

(RSCM) surfaces aligns well with the boundary separating regions dominated by long heating duration and regions separating short heating duration, demonstrating that vitrinite and peak temperature cannot be directly equated consistently across regions of variable heating duration.

Sediments in the east experienced up to 7800m of overburden at the end of the

Permian, where they sat at depths for 200 million years leading to greater overall

600 0 -800

o Depth between 120 C RSCM and 0.8%Ro

Short  Heating duration → Long

RSCM surface %Ro surface

Positive value

Depth Increasing Increasing west east Negative value

Figure 17. Negative isochore values (hot) show areas where the vitrinite surface is shallower than it’s equivalent RSCM surface, suggesting heating duration is high. Cold colors are areas are positive values, where RSCM surfaces are shallower than their equivalent %Ro value, suggesting short heating duration which prevents the vitrinite reflectance from achieving higher values.

maturity (Sinclair, 2007). Permian and older sediments in the west experienced lesser burial up to 4300m in the late Permian, but potentially had a relatively short duration of elevated heat flux associated with late stage rifting in the Oligocene, causing RSCM temperatures to read high, but not providing an extended period of time for vitrinite reflectance to mature. The difference between RSCM and %Ro highlights trends in the amount of time sediments remained at depth.

6. BASIN MODELING

6.1 Introduction to Basin Modeling

1D basin modeling uses depositional ages, thicknesses, and lithology data of formations encountered in a single well to account for the entire history of a basin at a single point. Sediment layers are iteratively removed, or “back-stripped”, as a function of their age and thickness to estimate depth, compaction, subsidence, and timing of overburden. This is useful in determining the temperature history of a formation, as once inputs are established based on observed and published data, vitrinite reflectance data can be modelled using algorithms such as Easy %Ro, which uses an Arrhenius first-order parallel-reaction approach with a distribution of activation energies to predict vitrinite reflectance of horizons as a function of temperature and time (Sweeney and

Burnham, 1990). Factors such as the amount of overburden, the amount of basal heat flow, and the time sediments spent within a temperature window are iteratively modeled until the Easy%Ro data fits the observed data, suggesting the input conditions of the model are consistent with resulting maturities.

For this study, the commercial 1D basin modeling software Novva by Sirrius

Geochemistry was used to model subsidence and heat flow over time. Two wells were modeled, Texaco #1-29 representing a “hot” case in the west, and Lineberry Evelyn #1 representing a “cold” case in the east. Because Texaco #1-29 encountered an igneous intrusion and consistently demonstrates the highest temperature RSCM and vitrinite reflectance results, it would be the best candidate to model the added heat flow from late stage basin events. The Lineberry Evelyn #1 well is centered in one of the coolest

parts of the basin, in a depocenter where formations are thickest adjacent to the

Central Basin Platform.

6.2 Model Inputs

Input and boundary conditions for the two wells are listed in table 4, with references listed where applicable. Unit thicknesses and ages were taken directly from the wireline logs and original mudlogs, where lithologic composition were noted as relative composition percent. In some cases, major biostratigraphic markers were indicated on the logs, however formation contacts were cross-checked with published literature citing known formation ages (Hass and Huddle, 1965; Silver and Todd, 1969;

Ross and Ross, 1995). Lithology densities, thermal conductivities, and surface temperature through time utilized proprietary default functions in the Novva Software and are not specified with citation.

Table 4. Input parameters used for 1D basin models of Texaco #1-29 and Lineberry Evelyn #1. Variables that differed between the wells are unit thickness/ lithologies/ ages, basal heat flow through time, and Cretaceous overburden removal.

Input Value Citation Unit thickness/ Lithologies/ Proprietary well logs, mudlogs, and Ages cutting observations Lithology density, thermal conductivity, compaction coefficients Novva default library Earthbyte Group, Gplates, Paleoaltitude (Matthews et al., 2017) Compaction Model Athy Athy (1930) Density of the Mantle 3.3 g/cc Anderson (1989)

Table 4. Continued

Input Value Citation Haq et al. (1987); Haq and Eustatic Sea-level Variations Schutter (2008) Surface temperature through time Proprietary Novva default Blackwell et al. (2011); Davies Basal Heat Flow 43 mW/m2 (2013) Radiogenic heat production 28.8 mW/m2 Rudnick (1995) Corrected bottom hole temperatures Ruppel et al. (2005) vitrinite reflectance (observed) Pawlewicz et al. (2005) vitrinite reflectance modeled Easy%Ro Sweeny and Burnham (1990) Temperature at asthenosphere/lithosphere boundary 1330 ºC An et al. (2015); An and Shi (2006) Rift Heat Flow Model McKenzie et al. (1978) Beta Factor 1.1 Henry (1998)

Roberts et al. (1991), Allenby and Depth to Moho 45km Schnetzler (1983)

6.3 Cold Case – Lineberry Evelyn #1

The Lineberry Evelyn #1 well is similar to previous 1D basin models completed by other authors, including Barker and Pawlewicz (1987), Hills (1994); Luo et al.

(1994), Hill (1996), Dutton (2005), and Sinclair (2007). In this model, 2500-3000m of sediment was deposited in the Ordovician through Carboniferous at rates of 20-

50m/Myr associated with the Tobosa Passive margin phase, with rapid sedimentation rates of 50-200m/Myr in the Permian during Leonardian and Guadalupian associated with final phase of Marathon-Ouachita orogeny. Post-orogeny, the basin experienced a period of tectonic quiescence from the late Permian though the Cretaceous, modeled as Paleozoic sediments remaining at constant depth for over 100 million years.

Additional subsidence and sedimentation was modeled during the late Cretaceous because of Cretaceous Interior Seaway transgression, however it’s thickness is not preserved in the modern stratigraphic record due to post-Laramide exhumation and erosion. The maximum thickness of the Cretaceous section was estimated by iteratively adjusting thickness to match modeled Easy%Ro maturities with observed

%Ro.

Water depth

Figure 18. Burial history curve for the Lineberry Evelyn #1 well, showing deposition of major units and total subsidence over time. Peak subsidence was modelled during the late Cretaceous, followed by uplift to modern elevation. Isotherms of modeled temperature are overlain showing temperature through time of a given depth.

Initial inputs of the well log data show good overlap between the observed %Ro, and modeled Easy%Ro, with little iteration and model adjustment required. (figure 19).

Although not preserved today, an additional 1500 m of Cretaceous section was added to the model and was sufficient to account for observed maturity at depth. This is within the 900-2100 m range of previous estimates of Cretaceous basin fill (Barker and

Pawlewicz, 1987; Sinclair, 2007). Other model input conditions, including modern preserved overburden, relatively constant heat flow over time, and time spent at depth, sufficiently reproduce the observed depth/maturity profile.

Equivalent %Ro Equivalent %Ro

Figure 19. RSCM, measured %Ro, and Easy%Ro results plotted against depth for the Lineberry Evelyn #1 well. The observed %Ro matches well with the Easy%Ro model, suggesting the conditions observed today and previously published Cretaceous overburden estimates are sufficient to account for the thermal history of this point.

6.4 Hot Case – Texaco #1-29

An initial Easy%Ro model for Texaco #1-29 had results that are inconsistent with observed vitrinite reflectance data (Figure 20). This model applied the same uniform heat flow history that was sufficient to reproduce results in the Lineberry

Evelyn #1. In this initial model, measured vitrinite reflectance values at greater depths are higher than the Easy%Ro model results, and measured vitrinite reflectance values from shallower depths were less mature than the modeled results. The slope of the maturity gradient requires a higher geothermal gradient in this area, suggesting additional heat input occurred at some point in the geologic past to account for the gap in overall heat budget.

To resolve the mismatch between the initial model and observed results, basal heat flow was first modified. Then, the overburden magnitude was adjusted to match measured %Ro values at all depths. After manual inspection, two changes are required to improve model results and more closely match observed data:

(1) Increase basal heat flow to 90mW/m2 from 30-10 Ma.

(2) From 10-0 Ma, heat flow modeled at 65mW/m2

(3) The amount of total Cretaceous overburden removed from erosion in the

west must be reduced to 200m. This is significantly less than the 1500 m

of eroded Cretaceous section modeled to the east in Lineberry Evelyn #1.

Measured vitrinite Easy%Ro model

Increased RSCM overburden model

Intrusion encountered at 2770m

Figure 20. Easy%Ro modeling for the Texaco #1-29 well showing inconsistent results with observed %Ro data, suggesting input parameters such as basal heat flow and eroded overburden are not constant throughout the basin. When overburden was increased to account for higher maturity, shallower samples have maturities over- predicted by the model, suggesting greater overburden is not responsible for elevated maturities in Texaco #1-29.

The 1D basin model in the west required additional basal heat flow to match model results with observed data. Two mechanisms for elevated heat flow are proposed to account for increased heat flow: elevated heat flow from Basin and Range extension situated to the west of the basin, and igneous intrusions associated with the

Trans-Pecos volcanic trend. Both events partially overlap temporally between 30–10

Ma and may be linked by post-Laramide tectonic events including modification of

Farrallon plate interaction with North America, Rio Grande Rift, and associated basaltic-andesitic upper crustal intrusion (James and Henry, 1991; Barker, 1987;

Morgan et al, 1986).

6.5 Rifting Style

When modeling the thermal effects of rifting on the overlying crust, McKenzie (1979) or

Waples (2001) models are applied based on pure sheer or simple sheer deformation modes, respectively. McKenzie (1979) models a significant increase in basal heat flow syn-rift associated with ductile lithospheric thinning and upwelling of the asthenosphere. This process is modeled as instantaneous, independent of radiogenic heat input, and shows decreasing heat flow over time post-rift. The Waples (2001) model is best applied to extensional terrain with a single detachment surface where simple sheer deformation style dominates. This model results in radiogenic heat production playing a larger role, associated with initially decreased heat flow attributed to thinning of the upper crust, followed by a smaller increase in heat flow contributed from the asthenosphere.

Wilson et al. (2005) and Gao et al. (2004) suggest that the early regional extension of the Rio Grande Rift is characterized by pure-sheer deformation style, with simple-sheer deformation occurring locally on individual detachment surfaces or during late-stage extension, occurring 10-5 Ma (Morgan et al. 1986). This suggests McKenzie-

Water depth

Figure 21: Depth/maturity profile for Texaco #1-29 well iterated using McKenzie-style rift modeling with 90mW/m2 peak heat flow for 20 million years from 30 Ma to 10 Ma. 200m Cretaceous overburden was added to current observed thicknesses to account for missing section. %Ro readings were interpolated from nearby wells and do not reflect the localized heating effects of the intrusion. RSCM datapoints were intentionally sampled 30m above and below the igneous intrusion to demonstrate the localized heating effect on adjacent strata. 60

style heat flow modeling is more appropriate for the western regions of the Delaware basin.

Morgan et al. (1986) models a regional average of 30-50% extension at the rift center through palinspastic restoration, however 50-100% extension is possible locally in areas with closely spaced, low-angle faults. Keller and Cather (1994) also estimate up to 50% extension occurs in the southern Rio Grande rift on the border of New

Mexico, Texas, and New Mexico. The western region of the Delaware basin lies on the eastern flank of the rift and did not experience the same magnitude of extension as the

Rio Grande Rift zone. Along the eastern Rio Grande Rift flank, ~10% extension is proposed for the Trans-Pecos region adjacent to the Delaware Basin (Henry, 1998).

Modeling 10% extension following the McKenzie (1979) model results in an additional 5.5mW/m2 to the heat budget (figure 22). This is insufficient to account for the additional 45 mW/m2 heat flow needed to match modeling results. Alternatively, the thermal anomaly from the Rio Grande region may affect an area much wider than the mapped rift (Seagar and Morgan, 1979). However, modeling a maximum 50% extension results in additional 22.5 mW/m2. This modeling suggests that rift-induced heat flow alone is insufficient to account for the total 90mW/m2 heat budget required to produce RSCM and vitrinite reflectance measurements from the western Delaware

Basin.

6.6 Igneous Intrusions

Igneous intrusions often accompany continental rifts where decompression melting of asthenospheric mantle rises passively beneath zones of stretched and thinned lithosphere (White and McKenzie, 1989). Igneous intrusions could potentially

Peak basal heat flow as a function of

extension

) 2 80

70 60 50 ß = 2.0 40

20 Peak Basal Basal Peak flow heat(mW/m 10 ß = 1.1 0 0 0.5 1 1.5 2 2.5 3 B

Figure 22. Basal heat flow values extracted from the 1D model of Texaco #1-29 as a function of extension (increased ß value).

contribute additional heat to the overall budget, however their effects are expected to be highly localized, and not distributed throughout the entire rock column. In general, the effects on sediment maturity from a localized igneous intrusion are negligible beyond ~5 times the thickness of the intrusion and are typically manifested as a bell- shaped distortion of thermal maturity parameters in close proximity to the intrusion

(Holford et al. 2013; Schutter, 2003; Goulart & Jardim,1982). Aquifers connected to a zone of igneous intrusion can circulate hot fluids into shallower units, providing a locally elevated geothermal gradient in the overlying sediments. These fluids may affect sediments up to several kilometers away, leading to overestimations of basal heat flow

(Duddy et al., 1994). The thermal effect is compounded when multiple, thick intrusive sills are sequentially emplaced into organic-rich sediments (Gordoyeva et al., 2001;

Schutter, 2003; Aarnes et al., 2011). For example, in the Queen Charlotte Islands,

British Columbia, an area prone to mafic dike swarms experiencing 10% extension had temperatures elevated by up to 100oC in 2km grid-square surrounding intrusions

(Souther et al.1991).

The distribution and frequency of subsurface igneous dykes in the western

Delaware Basin is not well constrained. The Railroad Mountain and Diablo Dykes in

Eddy County are 20-50m thick and may be reasonable analogs for the 30m intrusion encountered in Texaco #1-29 well. An additional 10 m intrusion was encountered at

1450m TVDSS in the Woodford Formation section of the same well, suggesting several dykes could occur locally in close succession.

In an effort to visualize the effect igneous intrusions may have on elevated maturity and interpret if they represent a regional or local alteration to the thermal maturity gradient, published maps of intrusions were georeferenced with magnetic anomaly map of Adams and Keller (1996) and the vitrinite gradient map from data provided in Pawlewicz et al. (2005) to determine overlap between igneous features, positive magnetic anomalies, and localized hotspots of vitrinite gradient (Henry and

Price, 1985; Calzia and Hiss, 1978; Barker and Pawlewicz, 1987) (figure 24). Mapped igneous bodies in the sedimentary column are spatially collocated with positive magnetic anomalies (figure 24). These same igneous bodies also overlie regions of locally elevated maturity gradient in the vitrinite dataset, which is also

Figure 23 (previous page). Plot of temperature, maturity, and depth. The effects of igneous intrusions on geothermal gradients are typically localized adjacent to the intrusion, with sediments more than five times the thickness of the intrusion away showing negligible effects. Below the intrusion, a negative geothermal gradient exists as sediments return to the background gradient. Above the gradient, an elevated gradient may exist due to the circulation of pore fluids influenced by the intrusion. Reprinted from Holford et al. (2013)

consistent with RSCM results. While well spacing and poor data resolution might bias the contouring method used, the data as visualized here suggests the western

Delaware basin experienced elevated peak maturity and geothermal gradients in areas affected by localized igneous intrusions. While the highest elevated gradients observed here are proximal to igneous activity, the regional gradient outside of these intrusions is still elevated in the west, suggesting larger regional trends of elevated temperatures closer to the Rio Grande Rift. If background heat input from regional trends are approximated as 10% McKenzie-style extension, igneous intrusions need to account for an additional 40mW/m2 to account for the remaining heat flow budget.

Figure 24. Mapped igneous intrusions of the west Delaware basin align well with positive magnetic anomalies published in Adams and Keller (1996). The same intrusions correlate well with vitrinite reflectance gradient hotspots, suggesting their presence is locally responsible for the hotspots. Regionally, the background elevated trend of reflectance gradients in the west continues even away from the intrusions, suggesting there may be more intrusions unaccounted for, or an additional mechanism of heating that spatially coexists with the intrusions.

6.7 Additional Sources of Heat

Because McKenzie-rift heat flow is of low magnitude in West Texas, and igneous intrusions may only be expected to elevate peak temperatures locally, it may be necessary to consider additional heat sources during Cenozoic deformation.

Collapse or foundering of the Farallon plate and movement of hot asthenosphere into the position previously occupied by the subducted slab is proposed as a mechanism for thermal weakening and removal of the overlying lithosphere, leading to a greater portion of the crustal lithosphere removed than what is expected during passive rifting 65

(Humphreys et al., 2003). This is supported by a shift in basalt compositions from lithosphere-derived to mantle-derived in the southern Rio Grande Rift synchronous with

Farallon foundering at 28.5ma (Henry et al, 1991; McMillan et al. 2000), anomalously slow P and S wave velocities in the mantle extending to shallow depths of less than

45km (Gao et al, 2004), and isotopic depletion of xenoliths suggesting lithosphere/asthenosphere interaction at 45km depth (Byerly and Lassiter, 2012). While lower crust delamination is proposed as a potential process, it is typically associated with a mechanical boundary at which lithosphere decouples (Lee et al., 2001). Byerly and Lassiter (2012) suggest dripping, foundering, or thermal erosion as a means of removal, as they do not require a mechanical boundary and do not require complete removal lower crust or lithospheric mantle. Removal of the base of the lithosphere would lead to an increased basal heat flow and is expected to trigger magmatism in the overlying crust (Lin and Wang, 2006).

6.8 Cretaceous overburden removal

The amount of Cretaceous overburden at times of peak burial is not well constrained in previous studies and is heavily dependent on the individual basin models used to estimate it. It is important to constrain timing and thickness of the missing strata, as it has strong implications for the timing and magnitude of hydrocarbon generation in relation to the formation of traps and migration pathways.

Late-stage basin uplift and tilting has eroded most of the post-Permian sediment, especially in the western shallower margins, preventing direct measurement of the sedimentary thickness. Lower Cretaceous sections up to 380m are observed within the basin, however are not indicative of peak upper Cretaceous burial (Hills, 1984). Data

from Cross and Pilger (1978) and Mitrovica et al. (1989) suggest restored upper

Cretaceous isopachs between 600-1200m, Friedman et al (1986) suggest 600m, and

Luo et al (1994) suggest less than 400m. Sinclair (2007) published shale compaction curves and apatite fission track (AFTA) data constraining peak burial at 55ma with an additional 2100m of Cretaceous overburden.

The 1D basin models presented here use Easy%Ro to predict overburden at time of maximum burial. In the deeper eastern portion of the basin at Lineberry Evelyn

#1, the model predicts 1460m of maximum Cretaceous overburden removed to account for the observed maturities at the shallowest vitrinite datapoints. This value was calculated based on basal heat flow and geothermal gradient remaining constant through time. This simple geologic scenario is unlikely supported in the western

Texaco #1-29 well, as modeled peak gradients were likely altered during post-

Laramide events after peak burial.

Texaco #1-29 also lies in an area of data scarcity, so shallower reflectance values inferred from nearby wells of Grisham Hunter State #1, Tenney Gerald E. #1, and Marvin R. Weatherby #1 may be biased by the uplift and removal of units otherwise constraining those datapoints at the location of Texaco #1-29. If deeper datapoints at the nearby wells are an indication of the overburden removed, then the

Easy%Ro model suggests 300-600m of overburden is adequate to provide observed maturities in the west, which is significantly less than the east.

Our estimation is 440m less than that of Sinclair (2007), although those results are based on a constant geothermal gradient of 21.8oC/km. Our RSCM data disagree with this assumption, showing that gradients have reached at least 40oC/km at times of

peak maturity. With this adjustment, it would require less overburden to provide temperatures necessary to mature vitrinite to levels observed today. Our estimation of

1460m of removed Cretaceous section is still within limits of previously established estimates.

6.9 Peak Temperatures over Time

Once subsidence, overburden, and heat flow have been established on the burial history curve, isotherms can be modeled through time, constraining when certain formations are predicted to enter within a given temperature window. These isotherms model both the peak geothermal gradient and peak temperature predicted by RSCM, and internal to the model are constrained by the surface temperature, thermal conductivity, energy input at depths, and current bottom-hole temperatures. When plotted on a temperature vs. time chart, timing and magnitude of peak temperature for each formation becomes apparent, showing relative heating rates as constrained by timing and magnitude of basal heat flow and burial (Figure 25). Peak temperatures can also be compared against RSCM data to determine if one accurately matches the other.

According to the basin models and RSCM data, both eastern and western portions of the basin have reached similar peak temperatures between 100oC and

230oC. However, the models suggest contrast in the rate, timing, and duration of heating, illustrating spatial variations in the basin tectonic history. Sediments in the east had a longer heating duration, having reached peak temperatures shortly after burial in the late Permian, followed by a long period of relative tectonic stability. Sediments again reached elevated temperatures in the late Cretaceous, where up to 1460m of additional

overburden was added. In the west, sediments did not reach peak temperature at the end of the Permian, but instead remained at relatively cooler temperatures during stable phases in the Mesozoic. In the late Cretaceous, some overburden was added, but less than what was experienced in the east, leading to a negligible increase in maturity.

Peak temperatures accompany the imposed basal heat increase in the Oligocene, when post-Laramide lithospheric thinning led to increased heat flow and igneous intrusion, rapidly rising the geothermal gradient and peak temperatures to the observed maturity today. The increased heat flow is modeled as short lived, with peak temperatures lasting less than 10 million years decreasing to their modern values.

The RSCM peak temperatures only partially align with peak temperatures predicted by the 1D basin model. In the Texaco #1-29 well, Ellenburger and Woodford temperatures are accurately matched, however RSCM results are lower than the predicted temperatures of the shallower Bone Spring and Barnett units. This may be an artifact of how the Novva software models conductive heat flow from basal sources, rather than localized point sources from advection. If we interpret igneous intrusions accounting for the majority of added heat in the overall heat budget, it would be expected to have a significant localized effect on the intruded rocks, with only marginal effect on surface rocks. This would support the elevated Ellenburger formation temperatures reported by RSCM, and cooler temperatures in the Bone Spring

Formation.

Bone Spring Wolfcamp A

Barnett Woodford Ellenburger

Figure 25. Charts modeling peak temperature over time for each interval analyzed by RSCM. Texaco #1-29 (top) models the “hot” case, where peak temperatures were elevated for short duration during post-Laramide events. Lineberry Evelyn #1 (bottom) models the “cool” case, where sediments were buried at the end of the Permian and remained stable at depth for 200 Ma.

In the Lineberry Evelyn #1 well the opposite trend occurs, where the shallower

Bone Spring and Wolfcamp RSCM results match the modeled temperatures, and the deeper Barnett, Woodford, and Ellenburger samples have RSCM temperature values that overpredict %Ro values by up to 60oC. This is because deeper sediments in

Lineberry Evelyn #1 spent extended time at elevated temperatures, the values represented by vitrinite had more time to mature, producing higher values than temperature alone would otherwise suggest.

7. CONCLUSIONS

RSCM can be successfully employed on sedimentary amorphous organic material and multiple maceral types including vitrinite to model the peak temperature sediments reach spanning deposition, burial, and exhumation. The results presented here show that RSCM can be applied to lower temperature sediments covering a range of peak temperatures associated with oil and gas maturation, and are consistent with vitrinite reflectance and pyrolysis Rock-Eval readings from the same samples.

RSCM peak temperatures are shallower in the west than equivalent temperatures in the east, and wells in the west have higher paleogeothermal gradients than wells in the east, suggesting they previously experienced greater heat flow. While these trends are broadly consistent with preexisting vitrinite reflectance data which show greater reflectance gradients in the same regions, but in detail results from

RSCM and vitrinite reflectance (%Ro) diverge in the deepest and shallowest portions of the basin. Samples in the east that are buried the deepest show that %Ro record relatively greater maturity compared to temperatures from RSCM results, and samples in the west that are shallower show RSCM results predict temperature greater than maturity estimates from %Ro. This may be the result of variable heating duration.

Although precise burial and exhumation histories remain debated, samples in the east were potentially buried quickly to greater depths at the end of the Permian, and remained at depth for 200 Ma. Samples in the west were potentially buried to shallower depths, but experienced short pulses of heating associated with post-Permian events that may be linked to Laramide tectonism, Rio Grande Rift, and various Cenozoic

intrusions. The difference in depths to predicted peak temperatures between RSCM and %Ro can be used as a relative index for heating duration, since RSCM is temperature-dependent, and %Ro is both time and temperature dependent.

Two wells representative of east (cool) and west (warm) conditions were modeled in a 1D basin modeling program to match observed vitrinite reflectance against Easy%Ro models to quantify the basal heat flow through time. Current burial conditions were modeled for each well, showing that both the east and west were previously buried deeper at the end of the Cretaceous and uplifted to modern depths during post-Laramide events, but the east demonstrated 1500m of missing overburden in the Cretaceous as opposed to 200m in the west. The west also previously experienced a significantly higher peak basal heat flow of up to 90mW/m2 to produce the vitrinite gradient observed, which is 45mW/m2 higher than the regional background basal heat flow.

Additional heat flow could potentially be contributed from post-Laramide tectonic events such as lithospheric removal or McKenzie-style rift heating, which are both accompanied by igneous intrusion and potentially associated with steepening and eventual removal of the Farallon plate. While elevated maturity gradients are systemic to western portions of the basin closer to the Rio Grande Rift, McKenzie-stye rift heat flow modeling is insufficient to account for the entire heat flow budget by itself, suggesting an additional heating mechanism.

Igneous intrusions were emplaced coeval with post-Laramide events, and appear to further elevate the geothermal gradient locally where they are encountered in the subsurface. These thermal anomalies extend further away from identified features

than a single isolated intrusion would otherwise produce by itself, potentially from circulating pore fluids advecting heat, or that there are several intrusions emplaced in close proximity.

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APPENDIX (also attached as separate supplemental file)

Sample MD KB TVDSS TVDSS Kouketsu FWHM D1 FWHM D2 Eq1 Eq2 RSCM RSCM %Ro measured Vitrinite Name Well/top depth formation inclusive (ft.) (ft.) (ft.) (ft.) (m) Temp +/- (cm-1) (cm-1) (Co) (Co) %Ro Eq. Eq. σ %Ro Temperature Lago1 Lago 5400 First Bone Spring 7400-7440 7400 2853 4547 1386 74.08 17.46 166.99 75.19 121.54 27.38 0.50 0.09 0.45 62.66 Lago2 Lago 8700 Wolfcamp A 11700-11750 11700 2853 8847 2697 110.85 14.96 167.21 64.36 118.50 98.63 0.71 0.11 0.785 120.62 Lago3 Lago 15250 Barnett 15250-15270 15250 2853 12397 3779 187.76 12.03 143.08 49.56 170.38 198.98 1.50 0.18 2.605 245.57 Lago4 Lago 16200 Woodford 16200-16220 16200 2853 13347 4068 257.56 11.34 107.64 39.30 246.58 268.55 2.92 0.34 3.01 260.62 M+H1 M+H 8210 First Bone Spring 8210-8250 8210 2708 5502 1677 80.85 18.18 169.65 72.91 113.25 46.04 0.54 0.10 0.45 62.66 M+H2 M+H 12420 Wolfcamp A 12420-12470 12420 2708 9712 2960 142.08 9.34 150.05 60.38 155.39 128.62 0.96 0.09 1.51 188.76 M+H3 M+H 17700 Barnett 17700-17750 17700 2708 14992 4570 221.26 20.10 122.56 45.28 214.51 228.02 2.06 0.44 2.7 249.30 M+H4 M+H 18410 Woodford 18410-18430 18410 2708 15702 4786 244.46 11.03 110.10 42.38 241.29 247.64 2.58 0.29 3.2 266.99 Pow1 Powers 8300 First Bone Spring 8300-8310 8300 2728 5572 1698 90.38 36.18 152.82 74.29 149.43 31.32 0.59 0.24 0.55 83.56 Pow2 Powers 10700 Wolfcamp A 10700-10720 10700 2728 7972 2430 157.08 28.95 141.16 58.31 174.52 139.65 1.11 0.36 0.84 127.67 Pow3 Powers 15270 Cisco 15270-15320 15270 2728 12542 3823 177.40 12.38 136.91 58.91 183.65 169.56 1.35 0.17 2.2 227.96 Pow4 Powers 17660 Barnett 17660-17680 17660 2728 14932 4551 199.63 19.12 127.93 51.09 202.96 188.58 1.68 0.34 2.87 255.66 Pow5 Powers 18000 Woodford 18000-18050 18000 2728 15272 4655 228.78 6.00 114.16 45.72 232.57 225.00 2.22 0.13 3 260.27 Terril Terril State Ellenburger 21265 21265 2680 18585 5665 259.13 5.77 100.48 41.11 261.96 256.30 2.97 0.17 3.5 276.33 Rape1 Rape 8200 First Bone Spring 8200-8220 8200 2606 5594 1705 73.22 12.45 170.01 76.49 112.48 30.75 0.50 0.06 0.69 107.18 Rape2 Rape 10450 Wolfcamp A 10450-10470 10450 2606 7844 2391 112.36 13.86 161.52 68.70 130.74 69.21 0.73 0.10 0.95 140.49 Rape3 Rape 13500 Barnett 13500-13530 13500 2606 10894 3320 142.47 15.52 153.24 62.97 153.73 130.87 0.97 0.16 1.47 185.96 Rape4 Rape 14290 Woodford 14290-14320 14290 2606 11684 3561 170.63 18.02 144.06 53.39 168.28 172.99 1.27 0.24 1.64 197.36 Rape5 Rape 17750 Simpson 17750-17770 17750 2606 15144 4616 239.68 25.83 109.14 44.10 243.35 236.00 2.46 0.69 2.6 245.37 Hory1 Horry 7200 First Bone Spring 7200-7240 7200 2598 4602 1403 59.25 27.79 167.95 77.52 116.91 9.40 0.44 0.13 0.4 50.39 Hory2 Horry 10500 Wolfcamp A 10500-10540 10500 2598 7902 2409 104.70 21.41 162.52 69.62 128.58 62.96 0.67 0.15 0.845 128.29 Hory3 Horry 12500 Barnett 12500-12550 12500 2598 9902 3018 125.08 25.40 149.22 65.19 157.17 92.98 0.82 0.23 1.325 175.15 Hory4 Horry 13350 Woodford 13350-13400 13350 2598 10752 3277 162.32 15.89 144.39 55.74 167.55 157.09 1.17 0.19 1.605 195.12 Hory5 Horry 16920 Ellenburger 16920-16970 16920 2598 14322 4365 171.96 39.10 141.40 53.84 173.99 169.93 1.29 0.59 3.01 260.62 Grld1 Gerald 6290 First Bone Spring 6290-6310 6290 3066 3224 983 64.09 22.32 157.51 79.03 139.36 -0.85 0.46 0.11 0.51 75.69 Grld2 Gerald 8280 Wolfcamp A 8280-8300 8280 3066 5214 1589 97.20 24.40 155.69 72.94 143.26 40.44 0.63 0.17 0.715 110.89 Grld3 Gerald 8600 Barnett 8600-8650 8600 3066 5534 1687 118.32 24.59 161.85 24.59 118.32 118.32 0.77 0.20 0.76 117.25 Grld4 Gerald 9100 Woodford 9100-9150 9100 3066 6034 1839 129.26 8.26 157.29 63.43 139.82 104.96 0.85 0.07 0.835 127.05 Grld5 Gerald 11640 Simpson 11640-11660 11640 3066 8574 2613 175.24 19.35 140.90 52.91 174.93 175.55 1.33 0.27 1.39 180.14 Todd1 Todd 7150 First Bone Spring 7150-7160 7150 2795 4355 1327 102.18 18.84 161.15 69.18 131.53 71.37 0.66 0.13 0.65 100.96 Todd2 Todd 10540 Wolfcamp A 10540-10590 10540 2795 7745 2361 153.06 12.70 147.74 57.41 160.36 145.75 1.07 0.14 1.49 187.37 Todd3 Todd 12550 Barnett 12550-12570 12550 2795 9755 2973 190.12 11.29 133.62 50.96 190.72 189.52 1.53 0.18 2.47 240.02 Todd4 Todd 13030 Woodford 13030-13050 13030 2795 10235 3120 226.87 9.28 116.15 45.66 228.28 225.46 2.18 0.20 2.81 253.46 Tex1 Texaco 5800 First Bone Spring 5800-5830 5800 3593 2207 673 62.51 19.57 181.18 73.52 88.46 36.56 0.45 0.09 0.63 97.70 Tex2 Texaco 7650 Barnett 7650-7700 7650 3593 4057 1237 86.07 23.48 167.78 70.82 117.28 76.48 0.56 0.14 0.94 139.39 Tex3 Texaco 8450 Woodford 8450-8500 8450 3593 4857 1480 140.05 15.62 149.87 61.49 155.79 122.54 0.95 0.15 1.19 163.95 Tex4 Texaco 9020 Fusselman 9020-9050 9020 3593 5427 1654 197.59 12.39 129.53 50.05 199.52 195.66 1.64 0.21 1.5 188.07 Tex5 Texaco 9430 Montoya 9430-9490 9430 3593 5837 1779 194.64 9.95 128.80 51.15 201.08 188.20 1.60 0.16 1.52 189.45 Tex6 Texaco 10900 Ellenburger 10900-10920 10900 3593 7307 2227 182.10 12.00 130.51 54.31 197.40 166.81 1.42 0.17 2.39 236.59 Reev1 Reeves 6300 First Bone Spring 6300-6350 6300 3219 3081 939 107.61 18.99 157.08 67.86 140.28 74.94 0.69 0.14 0.56 85.44 Reev2 Reeves 7140 Wolfcamp A 7140-7170 7140 3219 3921 1195 109.25 14.74 153.10 69.86 148.84 71.76 0.70 0.11 0.68 105.66 Reev3 Reeves 7800 Woodford 7800-7840 7800 3219 4581 1396 140.67 15.94 145.58 63.19 164.23 119.43 0.95 0.16 0.74 114.47 Reev4 Reeves 10580 Ellenburger 10580-10600 10580 3219 7361 2244 176.10 12.63 134.13 55.06 189.42 161.54 1.34 0.17 1.5 188.07 Lbry1 Lineberry 8940 First Bone Spring 8940-8960 8940 3000 5940 1811 82.98 29.88 167.48 71.82 117.92 48.05 0.55 0.18 0.725 112.34 Lbry2 Lineberry 13050 Wolfcamp A 13050-13100 13050 3000 10050 3063 138.2198 19.94 153.06 61.87 148.92 124.13 0.93 0.20 1.14 159.48 Lbry3 Lineberry 17900 Barnett 17900-17920 17900 3000 14900 4542 187.39 12.04 137.03 52.97 185.16 188.59 1.49 0.18 2.08 222.12 Lbry4 Lineberry 19040 Woodford 19040-19090 19040 3000 16040 4889 206.47 11.00 127.78 47.98 203.27 209.67 1.79 0.20 2.23 229.38 Lbry5 Lineberry 22120 Simpson 22120-22140 22120 3000 19120 5828 262.78 10.11 103.67 41.07 257.47 268.09 3.07 0.31 2.61 245.77 Wein1 Weinacht 7000 First Bone Spring 7000-7050 7000 3456 3544 1080 108.83 13.06 167.13 69.44 118.66 82.55 0.70 0.09 0.57 87.28 Wein2 Weinacht 8800 Wolfcamp A 8800-8840 8800 3456 5344 1629 122.58 25.85 156.36 66.38 141.84 84.96 0.80 0.23 0.8 122.59 Wein3 Weinacht 9300 Barnett 9300-9350 9300 3456 5844 1781 129.28 32.17 153.11 62.72 148.81 109.74 0.85 0.31 0.91 136.01 Wein4 Weinacht 10200 Woodford 10200-10250 10200 3456 6744 2056 168.10 9.57 140.21 55.36 176.56 159.65 1.24 0.12 1.11 156.70 Wein5 Weinacht 12700 Ellenburger 12700-12750 12700 3456 9244 2818 180.72 15.30 132.64 54.04 192.81 168.62 1.40 0.22 1.85 209.92