Spatial Dynamics of Quaternary Igneous Intrusion in Raton Basin

Spatial Dynamics of Tertiary Igneous Intrusion in Raton Basin, Southern Colorado

Charles Lee Cavness III

Submitted in partial fulfillment of the requirements for the degree of Bachelor of Arts Department of Geology Middlebury College Middlebury, Vermont

May 2009

Spatial Dynamics of Tertiary Igneous Intrusion in Raton Basin, Southern Colorado

Charles Cavness, Department of Geology Middlebury College, Middlebury, Vermont 05753

Between 33Ma and 20Ma, over 500 dikes intruded the Raton Basin in Southern Colorado. Dikes extend radially from the Spanish Peaks double volcano located on the northwest margin of the basin. In addition to dikes, sills permeate the basin, often intruding bituminous rank coal beds used by oil and gas companies to extract Coal Bed Methane (CBM). Previous research focusing on the geothermal and intrusive history of the basin suggests that the pervasive sill complexes are directly related to “feeder dikes.” This report combines 89 CBM well logs and an aeromagnetic survey to test this feeder dike hypothesis. Sills are identified in well logs by dual induction resistivity (DIR) log spikes exceeding 200 ohm(m). Dikes are identified by rotated to poll (RTP) vertical magnetic gradients exceeding 65 nT/m and dikes are mapped by tracing anomalous gradient ridges on aeromagnetic maps. Sill abundance is quantified for five stratigraphic categories in each well. Abundance is compared to (a) the proximity of the nearest dike to a given well and (b) the number of dikes within ten proximity ranges (500 meter intervals from 500 meters to 5 kilometers). Results show that sill abundance is significantly controlled by the number of dikes within 500 meters from a well, but that dikes outside of the 500 meter range have an insignificant effect on sill abundance in a well. Furthermore, the proximity of the single closest dike has a negligible effect on sill abundance. Results are presented in a series of scatter and bar graphs with accompanying regression analysis. Isopach mapping of sills supports statistical results by showing sill “hotspots” coinciding with areas of dike convergence. Given the quantitative and qualitative evidence that dike frequency within close proximity to a well affects sill abundance, the feeder dike hypothesis can be confirmed. These results may be useful to geothermal energy companies and CMB companies. Previous research suggests that sills control the movement of hydrothermal fluids, so drilling in areas where dikes converge on the surface will increase the probability of intercepting sills and the connected hydrothermal resources. Furthermore, CBM producers may avoid areas where sills have intruded and destroyed coals by drilling in areas removed from dikes.

ii Acknowledgements

I owe many thanks to those who made this project possible. Certainly the place to start will be my family. I owe you the most. Without you I would never have the opportunities that I enjoy so cavalierly today. Thank you mom and dad especially for all the support, love, encouragement, and advice. I can never repay you for all that you’ve given; I only hope that I’ve made you proud. Dad, you have been a guide and a motivator through my entire life – you always show me the way and push me to improve and excel. Mom, you have been my emotional support and nurturer – I don’t know how I could have survived without you. Frazier, you’ve been a great brother and friend, and I’m so proud of everything that you’ve accomplished. Thanks for keeping me in check. Thank you to the Middlebury Geology department. The department’s culture fueled me academically and socially during the long nights and challenging problem sets. That special culture would be impossible without the amazing faculty. Thank you Ray Coish, Pat Manley, Tom Manley, Jeff Munroe, Pete Ryan (thanks for a great senior seminar), and Eileen Fahey for making the fourth floor so lively. I also want to thank the other geology seniors for making our seminar one of the most enjoyable class I’ve taken at Middlebury. The closeness of our major made my thesis feel more like a group project than a solo mission. I’d like to give special thanks to Dave West for his tremendous advising on this project and throughout my career at Middlebury. Dave, you introduced me to geology and sparked my excitement in the subject. It was a privilege and honor to speak at your reception of the Perkins Award, which could not have been awarded to a more deserving professor. I sincerely appreciate all the opportunities afforded to me by Middlebury College. You surrounded me with great people and great ideas. Thank you for the Senior Research Fellowship, Palen ’40 Travel Conference Grant, Sustainable Study Abroad Grant, Old Stone Mill office and creative space, ACE grant, and countless other opportunities. Thank you Midd for helping me become the person that I am proud to be. Thanks to Pioneer Natural Resources and all its employees. Hal Macartney deserves special accolades; he was instrumental in facilitating this project, delivering the required data, and securing a license of PETRA software for Middlebury. Furthermore, Hal was a tremendous mentor and advisor during my summer working at Pioneer. Thank you Hadi Soetrisno, Karyn Powell, Neal Dannemiller, Paul Wilson, Sarah Hawkins, and Paul Clarke for answering so many of my questions and providing important information for this project. Thank you Bill Hegman and Chris Rodgers for your assistance in the stunningly complicated PETRA installation and data upload process. I may not have made it past square one without you. Last but certainly not least I must thank all my friends who always kept my work in check with my life. Some would say you’ve been a horrible influence, but I wouldn’t have it any other way. Thank you for so many memories – you are the greatest piece of my college experience, and you are who I will remember most fondly. You are fascinating, caring, genuine, and so much fun, and I am lucky to have each one of you in my life.

iii TABLE OF CONTENTS

TEXT PAGE

Abstract ii

Acknowledgements iii

Table of Contents iv

List of Figures vi

Chapters:

I. Introduction 1

II. Background on Geothermal Energy 3

III. Geology of Raton Basin 9 Introduction 11 Basin History and Stratigraphy 13 Structure 13 Igneous and Intrusive Geology 14 Coal and Coal Bed Methane 16 Geothermal Gradients 18 Previous Research in Raton Basin 19

IV. Data and Sources 20 Data and Sources 20 Well Data 22 Magnetic Data 24 Coal Data 24

V. Methods 26 Sill Measurements 26 Complex Identification 27 Sill Measurement Error 29 Dike Proximity Measurements 29 Dike Measurement Error 30

VI. Results 32 Nearest Dike Proximity 32 Frequency of Dikes Within Varying Proximity Ranges 36 Sill Isopach Mapping 40 Coal Isopach Mapping 43

VII. Discussion 47 Nearest Dike Proximity 47 Frequency of Dikes Within Varying Proximity Ranges 50 Positive Correlation between Sill Thickness and 500 m Dikes 51 Sill Isopach Mapping 53 Coal Isopach Mapping 54 Additional Controls 55 Recommendations for Future Studies 56

VIII. Conclusions 58

IX. References Cited 60

X. Appendix A 63

XI. Appendix B 66

XII. Appendix C 68

v LIST OF FIGURES

FIGURE PAGE

1. Locator Map 2

2. Diagram of Geothermal Energy Facility 4

3. Diagram of Binary Cycle Turbine 4

4. Diagram of Heat Exchanger 5

5. Well Cost Curve 7

6. Structural Map of Raton Basin 10

7. Generalized Stratigraphic Column of Raton Basin 11

8. Photograph of the Stone Wall dike 15

9. Photograph of Vertical Dikes 16

10. Photograph of Intruded Coal Seam 18

11. Map of Well Points 21

12. Well Log Example 23

13. Aeromagnetic Map 25

14. Sill Induced DIR Log Spike 26

15. Sill Complex Identification and Highlighting 28

16. Scatter Plot: Total Sill Thickness vs. Nearest Dike Proximity 33

17. Scatter Plot: Raton Sill Thickness vs. Nearest Dike Proximity 33

18. Scatter Plot: Vermejo Sill Thickness vs. Nearest Dike Proximity 34

vi 19. Scatter Plot: Lower Raton Complex vs. Nearest Dike Proximity 34

20. Scatter Plot: Upper Raton Complex vs. Nearest Dike Proximity 35

21. Scatter Plot: Average Sill Thickness vs. 500m Dikes 37

22. Bar Graph: Average Sill Thickness vs. 1000m Dikes 37

23. Bar Graph: Average Sill Thickness vs. 2500m Dikes 38

24. Bar Graph: Average Sill Thickness vs. 5000m Dikes 38

25. Isopach Map of Sill Thickness in the Raton Formation 41

26. Isopach Map of Sill Thickness in the Vermejo Formation 42

27. Isopach Map of Coal Thickness in the Raton Formation 45

28. Isopach Map of Coal Thickness in the Vermejo Formation 46

29. Diagrammatic Cross Section of Intrusion Situation 49

vii I. Introduction

Geothermal energy presents an economical, low emission, renewable

alternative to hydrocarbon energy sources. The potential for geothermal energy

production in the United States, particularly Enhanced Geothermal Systems (EGS), is

on the scale of Terawatts (Tester et al., 2006). Furthermore, huge opportunities are

offered by partnerships between geothermal energy producers and the oil and gas

industry, and the coal bed methane field in the Raton Basin of Southern Colorado

(Fig. 1) represents one such partnership opportunity.

Geologically, the Raton Basin’s high geothermal gradients present a prime

target for geothermal energy production. The basin also offers economic incentives

beyond geology and heat potential - existing wells, proximal energy markets, and

accessible land leases would reduce the cost of exploration, production, transmission,

and land negotiation for geothermal energy companies partnered with gas producers.

Geothermal energy producers must understand the sources of heat and the

behavior of hydrothermal fluids within a prospect – this research addresses those

issues by studying potential heat sources and controls on hydrothermal fluid

movement. Previous studies of hydrothermal alteration in the Raton Basin have

shown that intrusive bodies within the basin have acted as both heat sources and

conduits of hydrothermal fluid in the past (Cooper et al., 2007).

Intrusive bodies in the Raton Basin may account for both the heating and

movement of hydrothermal fluid within the basin. Both factors, heating and water movement, constitute fundamental yet poorly studied components of geothermal energy prospecting in the Raton Basin. Accordingly, it is the central purpose of this

1 research to analyze the spatial distributions of intrusions within the Raton Basin and

to determine relationships or correlations between the two types of intrusions (dikes

and sills). This study may also lay the groundwork for future studies to expand on the

details of water movement, geothermal gradients, and heat sources.

Figure 1. Locator Map showing the location of the Raton Basin and the study area within the basin. Adapted from: http://geosurvey.state.co.us/Default.aspx?tabid=1

2 II. Background on Geothermal Energy

Geothermal energy production is essentially “heat mining;” it is the process of extracting heat from hot rocks via water. Various techniques have been developed and implemented since geothermal energy production began in Italy in 1904. The most appropriate method for the Raton Basin would be Enhanced Geothermal System

(EGS) production. EGS generation involves drilling down to hot rocks, which exist ubiquitously throughout the Earth’s crust, and creating a new water reservoir. The required drilling depth for EGS production is reduced by higher geothermal gradients.

Previous studies have indicated abnormally high geothermal gradients exceeding

90ºC/Km in the Raton Basin (Berkman and Carroll, 2007).

Once hot rocks are encountered, the rocks are fractured using injected hydraulic pressure, then “propped” open by injecting manufactured proppant grains.

Water is injected into the new reservoir via an injection well, then the water is heated by the surrounding rocks. Ultimately, the hot water is extracted through an extraction or production well. In ideal situations, the hot water vaporizes as it rises from depth and the pressure is reduced, then the steam is passed through a steam turbine to create electricity at the surface (Fig. 2).

Geothermal energy producers also employ a host of technologies to extract energy from non-steam resources – the most notable of these is called a binary phase turbine. Binary phase turbines pass extracted hot water over a system of pipes containing low boiling point organic fluid like iso-pentane or iso-butane, which vaporizes to drive steam turbines. The water and secondary fluids are then cooled and recondensed. Water is pumped back into the ground to re-heat for later extraction while the organic fluid reenters the closed loop heat exchanger (Figs 3, 4).

3 Figure 2. Schematic diagram of a geothermal energy production facility. Hot water is extracted through a production well, used to generate electricity, then re- injected for re-heating. Source: http://hidden- technology.org/Common-Alternative-Energy-Sources.php

Figure 3. Schematic diagram of a Binary Cycle geothermal energy turbine – ideal technology for the case of non-steam hydrothermal fluid in Raton Basin Source: http://www.rasertech.com/geothermal_how.html

4 Figure 4. Diagram of a Binary Cycle heat exchanger. Secondary fluids with low boiling points will vaporize after extracting heat from hydrothermal fluids. Source: http://www.rasertech.com/geothermal_how.html

Enhanced Geothermal Systems are closed-loop, produce very low emissions

relative to coal or gas power plants, are sustainable unless the heat resource is

mismanaged, and are cost competitive with other renewable energy sources like wind

and solar. Furthermore, good (hot and shallow) geothermal power resources can

compete with coal and natural gas power plants on a cost per kilowatt-hour basis

(Mims, 2009).

Major costs for geothermal energy companies include exploration drilling,

drilling and casing of extraction and injection wells, construction of transmission

grids from the power plant location (often remote) to nearby municipalities or power

consumers, and the leasing or purchasing of mineral rights in the proposed geothermal field. Of these costs, drilling is often the most capital intensive

5 component, and it is common for the cost of well drilling to account for 60 percent or

more of the total capital investment in an EGS project (Tester et al., 2006).

Accordingly, any reduction of drilling costs can be a significant boon to the economics and viability of a geothermal energy project.

Dry holes, abandoned oil and gas wells, poorly producing wells, and water disposal wells all represent sunk costs to oil and gas producers. These wells also

represent a huge opportunity to geothermal energy producers, who may re-enter

abandoned or un-economical wells, and thereby bypass costs of hundreds or thousands of meters of drilling. The Raton Basin is peppered with plugged and

abandoned wells, many of which make prime candidates for geothermal re-entry.

Figure 5 shows an average pricing curve for well depths, and indicates the potential

savings to a geothermal energy producer pursuing the proposed well re-entry strategy

presented in this study.

Geothermal producers may also leverage the existing leases held by oil and

gas companies. In the state of Colorado, federal mineral leases provide for geothermal energy. Many privately negotiated leases also provide for access to any and all

mineral assets in the subsurface, which includes geothermal energy potential. Oil and

gas producers in the Raton Basin have secured thousands of acres of leases, many of

which entitle the gas producers to geothermal energy resources. Those leases may be

used by a partnering geothermal energy producer to expedite and lower the costs of

asset acquisition.

Figure 5. Oil, gas, and geothermal well cost data. Graph shows completed well costs as a function of depth. The red line provides an average cost curve, and indicates the costs that a geothermal energy company might avoid by utilizing previously drilled and abandoned wells. Adapted from: Tester et al., 2006.

7 A final strategic component to partnership with oil and gas producers is the

usage of electricity once produced. Oil and gas producers consume tremendous

quantities of electricity to run their field stations and power their oil pumps. Much of that electricity is produced by generators, which burn natural gas produced locally by the oil and gas producer. Accordingly, oil and gas producers represent an immediate and local market for electricity, and thereby greatly decrease the cost of building transmission lines to consumers.

Pioneer Natural Resources Incorporated, one of many major oil and gas operators in the Raton Basin, uses approximately 105,000-horsepower of air

compressors in the Raton Basin. The power required to run those compressors is

supplied by generators burning natural gas, which is produced locally by Pioneer at a

market value of approximately 50 million dollars per year (Macartney, 2008). If that

compression could be powered by geothermal energy, the savings could be annuitized

to tens of millions of dollars per year and tons of reduced CO2 emissions.

8 III. Geology of the Raton Basin

Introduction

The Raton Basin is an elongate, north-south trending structural and sedimentary basin in southern Colorado and northern New Mexico (Fig. 1). The asymmetric synclinal basin contains up to 8,000 – 9,000 meters of sedimentary rock and encompasses an area of more than 240 kilometers in length (N-S) and 190 kilometers in width (E-W). This study focuses on the northwestern quarter of the

Raton Basin. The basin is bounded to the west by the Sangre De Cristo Range, to the northeast by the Wet Mountains, and flanked to the southeast and east by the Las

Animas Arch (Fig. 6)

The Raton Basin is distinguished by three unique geological attributes: an expansive system of vertical (dikes) and horizontal (sills) igneous intrusions, an abundance of meter scale coal beds, and anomalously high geothermal gradients. One additional point of interest within the basin is a thin tonstein clay layer separating

Cretaceous and Tertiary rocks (Pillmore et al., 1999). The layer contains anomalously high concentrations of iridium, and is therefore thought to represent the K-T boundary and the associated extinction caused by a massive iridium-laden meteor that struck the Earth 65Ma. The following section will address the broad geologic history of the Raton Basin, and then focus on the basin’s intrusive history, coal beds, and geothermal anomalies.

Major Geologic Zones Geologic Province Geologic Setting I - San Luis Valley Part of the Rio Grande rift system II - Sangre de Cristo Part of the Rocky Mountains Mountains III - Raton Basin Tertiary sedimentary basin IV - Apishapa Uplift Broad arch in the High Plains Important Regional Features 1. Huerfano Butte 2. Walensburg vicinity 3. Goemmer Butte 4. Dakota hogback at Sulfur Springs 5. Spanish Peaks and dikes 6. Cucharas Pass 7. Culebra Range and 8. Monument and North Lakes vicinity Trinchera Peak 9. Dakota hogback at 10. La Veta Pass and Mount Maestas Stonewall 11. Zapata Falls 12. Great Sand Dunes National Monument Figure 6. Structural Map of Raton Basin and surrounding area with accompanying legend. Shows important structures and features in and around Raton Basin. Red box represents study area. Source: http://academic.emporia.edu/aberjame/field/rocky_mt/rocky.htm

10 Basin History and Stratigraphy

Upper Cretaceous and Lower Tertiary sedimentary sequences are the host rocks for the igneous intrusions and are the focus of this study. Specifically this study is most concerned with the Cretaceous Vermejo Formation and Tertiary Raton

Formation (Fig. 7). These formations have a combined thickness of 500 to 750 meters within the study area and the relevant depositional history will be described in the following section.

Figure 7. Generalized Stratigraphic Column for Raton Basin. The column illustrates the sedimentary units and their respective thicknesses throughout the basin. Adapted from Keighin et al. (1995)

11 Epirogenic arching associated with the Laramide Orogeny occurred during the

Late Cretaceous in the area directly west of Raton Basin, resulting in increased

erosion, which provided the clastic sediments of the Upper Pierre Shale and Trinidad

Sandstone (Fig. 7). Subsequently, Late Cretaceous orogenic activity resulted in uplift to the west of the Raton Basin, and provided the influx of sediments that were deposited as the Vermejo Formation, Raton Formation, and Lower Poison Canyon

Formation, all of which are dominated by coarse sandstones with occasional silty interbeds. These formations are devoid of carbonaceous and evaporite rocks (Johnson and Wood, 1956; Ramage et al., 2008).

The Poison Canyon Formation was deposited during the Paleocene as a result of rejuvenated Laramidian orogenic activity in the west. During the Late Paleocene and Early Miocene, the mountains to the west and north of Raton Mesa were again uplifted, which resulted in partial tilting and uplift of Raton Mesa and Huerfano Park

(geographic precursors to Raton Basin). This uplift caused partial erosion of the

Poison Canyon Formation and the deposition of the Huerfano Formation (EPA,

2004). Intense thrust faulting occurred during the Late Eocene, which resulted in the formation of the Sangre De Cristo and Wet Mountain Ranges, and also established the north-south trending synclinal form of the Raton Basin (Ramage et al., 2008).

After the Late Eocene, minor orogenic movement in the Wet Mountains resulted in limited erosion of the Huerfano Formation and deposition of the Farista

Conglomerate. The Devils Hole Formation was then deposited uncomfortably over the Farista Conglomerate (Johnson and Wood, 1956; EPA, 2004).

12 Structure

The Raton Basin is a roughly north-south trending asymmetrical syncline with

a steeply dipping west limb (up to 60°E) and gently dipping east limb (up to 20°W)

(EPA, 2004). Within the study area, the syncline plunges gently to the northwest;

however the basin is approximately non-plunging on a macro scale.

The western flank of the basin is bounded by a series of north-south trending

mountain ranges. The south western flank of Raton Basin is formed by the Sangre De

Cristo Mountain range (Fig. 6). The central western side of the basin is formed by the

Culebra Massif, and the north and northwestern boundaries are formed by the Wet

Mountains. The west limb of the Raton Basin dips steeply as a result of these upthrusted mountain ranges, which were thrusted into position during orogenic activity in the Late Eocene (Lorenz et al, 2003).

The eastern flank of the basin is bordered by a series of anticlinal arches. The south and southeastern boundaries are formed by the northeast trending Sierra Grande

Arch. Directly to the east of the basin’s center is the Las Animas Arch, which constitutes the western reaches of the Las Vegas Plateau. The northeastern boundary of Raton Basin is formed by the Apishapa Arch (Figs. 1, 6).

13 Igneous Rocks

Igneous activity in the northern Raton Basin is largely associated with the

Spanish Peaks mountains, located approximately 40 kilometers north of the study

area (Fig. 6). The Spanish Peaks double mountain represents the two igneous stocks

that injected no less than five hundred dikes throughout the Raton Basin in a radial

pattern. Each Spanish Peak stock is believed to have been emplaced as an

independent intrusion. The East Peak consists of white granite porphyry and

granodiorite porphyry while the West Peak consists largely of syenodiorite

(Muggleton et al., 2005).

The dikes in the Raton Basin range from 1 to 30 meters in thickness – average

thickness is approximately 4 meters. The majority of dikes are near vertical or

vertical, and few dip less than 80 degrees (Knopf, 1956). As a result, many of the

dikes outcrop on the surface as towering vertical walls protruding up to 100 feet

above their easily eroded sedimentary host rocks (Fig. 8). This phenomenon has

endowed one local mountain pass with the name “Stone Wall Pass,” and a local

bicycle ride is called “The Annual Stone Wall Century Ride.”

Figure 8. Photograph of the famous “Stone Wall” outside La Vita, Colorado Source:http://www.eugenecarsey.com/tourist/images/stonewall805402.jpg

Compositions of the dikes are regionally variable. Lamprophyre, andesite, and rhyolite sills dominate the north-western portion of the Raton Basin. Igneous rocks in the basin were intruded between 33Ma and 19.7Ma. 40Ar/39Ar dating suggests that magmatism and injection during this period was related to the Rio Grande Rift

(Miggins, 2002).

Complex systems of sills also extend horizontally throughout the basin. Oil and gas geologists working in the Raton Basin have long assumed that dikes acted as feeders to sills, and that sills extended away from dikes along planes of weakness

(Fig. 9). Research has bolstered these assumptions - the sills seem to preferentially intrude coal deposits, which exist throughout the lower Raton and upper Vermejo

Formations (Cooper et al., 2004).

15 Sill compositions vary as widely as do the compositions of their feeder dikes.

The sills also generated Pepperite intrusions, which occur when magmas vaporize the waters contained in coal beds, thus adding a volatile vapor component to intrusive bodies. It is common to find xenolithic fragments of coal or host rock churned into these vapor propelled intrusive bodies (Cornelius et al., 2004).

Figure 9. Three near vertical dikes exposed in a fifteen meter tall road cut. Dikes intrude sandstone country rock in the Raton Formation. A thin sill, potentially fed by the dikes, extends laterally through the road cut. Photograph taken in northwestern Raton Basin in July 2008.

16 Coal and Coal Bed Methane

The presence of economically significant coal reserves in the Raton Basin has been known and exploited since the middle of the nineteenth century. The majority of coals are located in Upper Cretaceous to Paleocene formations including the Trinidad,

Vermejo, and Raton Formations (Fig. 7; Clarke et al., 2004). During field surveys in

2008, coal bed thicknesses were found to range from one half meter to four meters thick. Thick coal beds extend laterally for multiple kilometers and coal rank ranges from high-volatile C bituminous to low-volatile bituminous (Keighin et al., 1995).

Coal quality varies by region, and although much of the Raton Basin contains only low grade coals containing 8 to 15 percent or more ash, high grade coking coal was discovered along the Purgatoire River west of Weston, CO. Research has suggested that heating from intrusions may have facilitated local coal rank elevation

(Cooper et al, 2007).

Coal beds in the Raton Basin have attracted the attention of Oil and Gas producers due to the coal’s vast potential as a source of natural gas. Coal bed methane

(CBM) wells have been drilled throughout the Raton Basin in efforts to discover and exploit these alternative gas source resources. Coal Bed Methane (CBM) resources in

Raton Basin have been estimated at 10.2 trillion cubic feet (EPA, 2004). Large portions of the data used in this research come from CBM wells drilled in the Raton

Basin.

Figure 10. Photograph of two meter thick sill intruding a four meter thick coal seam in Vermejo Formation. Photograph taken in northwestern Raton Basin in July 2008.

Geothermal Gradients

Limited data and minimal research has been directed towards determining geothermal gradients within the Raton Basin. Berkman & Carroll (2008) report geothermal gradients as high as 91°C/km in oil shale wells over 8000 feet deep in

Raton Basin. The coincidence of the basin’s high geothermal gradients and abundant intrusive complexes attracted the initial attention of this study; however, reliable temperature data was unavailable. The relationship between geothermal gradients and intrusion distributions remains untested; the question presents an excellent opportunity for a follow-up study if reliable temperature data becomes available.

18 Previous Research in Raton Basin

The igneous and intrusive history of the Raton Basin has been previously

studied, and a relationship between feeder dikes and off-shooting sills has been

proposed, but never tested using rigorous quantitative or statistical methods. Much of the literature centers around the effects of intrusions on coal beds. Cooper et. al

(2007) discuss the effects of coal metamorphism resulting from igneous intrusions, and also propose that hydrothermal fluid convection played a significant role in the dispersal of heat away from intrusions.

Cooper et al. (2004) apply thermal modeling to sills in the upper Vermejo and

Lower Raton Formations, and suggest that the thermal contributions of volumetrically minor intrusions (relative to the expansive basin) contributed little to the thermal evolution of the basin as a whole, but have produced elevated coal ranks in local areas. Cooper et al. (2004) also found a positive correlation between sills and coal beds, where sills preferentially intrude coal beds along planes of least resistance.

Papers by Knopf (1956), Miggins (2002), and Muggleton et al. (2005) have focused on the igneous history of the Spanish Peaks, which constitute the magma sources for intrusions throughout the Raton Basin. Muggleton (2005) uses magnetic fabrics as flow and emplacement indicators for the Spanish Peaks igneous complex.

Knopf (1956) provides a map and an interpretation of the intrusive history. Miggins

(2002) focuses on the geochemistry and geochronology of each specific intrusive event. Relevant information from these papers has already been paraphrased in the

Geological History section of this study.

19 IV. Data and Sources

Data and Sources

Data for this project is organized by well name. Data points for each well

include the well’s net sill thickness, the net thickness of any discrete sill complexes,

the proximity of the nearest dike to the well, and the number of dikes within

expanding radii. Sources of this data are described in this section. The methods of

acquiring data and the potential applications of this data are explained in the

following section.

Data for this research were provided by Pioneer Natural Resources, an

American oil and gas company with operations in the northwestern quarter of the

Raton Basin. A digital data package consisting of well logs, maps, aerial gravity

surveys, and well information was sent to Middlebury College in an external hard drive in early October, 2008.

Mapping and log analysis is done using the PETRA software package developed by the software producer IHS. Middlebury College attained a student license of PETRA in October 2008. Special thanks must be given to Pioneer Natural

Resources for their aid in helping Middlebury acquire this powerful software.

The field area is rectangular, with the northwestern corner at latitude

37.2954395°N and longitude 104.9744166°W and the southeastern corner at latitude

37.1916756°N and longitude 104.7434659°W. The area covers approximately 230

square kilometers (Fig. 11). The study area was chosen on the criteria of even well

spacing to provide good data coverage, and also to provide data points with varying

proximities to the nearest dike.

Well Data

The well log data set for this project consists of 89 digital well logs. Each well log contains log curves for Gamma Ray (GM), Density of Porosity (DPOR), Bulk

Density (RHOB), and Dual Induction Resistivity (DIR) (Fig. 12). This suite of log curves allows for lithologic interpretations including the identification and measurement of sills and coal beds. Methods for identification and measurement are discussed in the Methods Section of this report.

The depths of well logs used in this research are between 500 to 1200 meters.

The Vermejo and Raton Formations are isolated because they contain the vast majority of coals and also the majority of sills (EPA, 2004). Only complete, uninterrupted well logs are included in the data set, and only logs containing the full

Raton and Vermejo Formations are included. These restrictions severely reduced the amount of usable data because many wells were drilled to target economic resources, which are frequently above the Vermejo Formation contact. However, these standards are necessary because net sill thickness data would be flawed unless the entirety of the Raton and Vermejo Formations were screened for sills.

Figure 12. Examples of each log curve in the Sebring Well. Logs include Gamma Ray (GR), Density of Porosity (DPOR), Bulk Density (RHOB), and Dual Induction Resistivity (DIR). Magnetic Data

23 Pioneer Natural Resources conducted aerial magnetic surveys (Fig. 13). To

detect and map dikes based on significant contrast in the magnetic susceptibility between the intrusive rocks and the surrounding sedimentary country rocks.

Techniques for dike identification are discussed in the Methods section. In addition to magnetic surveys, Pioneer Natural Resources also provided a map of field observations of dikes, which have been used to positively confirm the findings of aerial magnetic surveys.

Aeromagnetic surveys show that 18 dikes cut through the field area; these dikes are mapped as red lines on the field map (Fig. 11). Most dikes within the study area strike approximately east-west and dip vertically or very near vertically. The shortest dike is 4.2 kilometers long and the longest dike is 15.5 kilometers long. The shallowest dip observed in field measurements was 87 degrees.

Coal Data

Pioneer Natural Resources also delivered a computer generated analysis of coal measures in each well. The data are produced by measuring low density and low porosity strata in well logs. These data were used in an attempt to compare the locations of coal beds and intrusions; however, the data set does not include all 89 wells. The user-defined criteria for coal measures are a DPOR (Density of Porosity) log value exceeding 20% and an RHOB (Bulk Density) log value of less than 2 g/cm3. These criteria are based on empirical evidence collected by Pioneer Natural

Resources.

Figure 13. Aeromagnetic map of Raton Basin. Map highlights dikes as lineations. Circles of high magnetic gradients represent extinct volcanoes and/or ancient magma stocks. The black box signifies the study area. The indentation on the left side of the figure represents an unscanned area over East Spanish Peak.

25 V. Methods Sill Measurements

The thicknesses of sills are measured by analyzing Dual Induction Resistivity

(DIR) log curves. Sills in northwestern Raton Basin trigger very obvious spikes in the

DIR log, and this relationship has been demonstrated by comparing well logs to well cores. Rightward spikes in the DIR curve indicate rapid increases in resistivity. These jumps in resistivity are the result of decreased porosity and water in the sills.

Accordingly, intruded sills exhibit anomalously high resistivity readings when compared to the water saturated, highly conductive sedimentary country rock. Sill diagnostic spikes are identified when DIR readings jump from baseline levels of approximately 20 ohm-m to “off the scale” levels that exceed 2000 ohm-m (Figure

14).

Figure 14. Cropped log set for the Suzuka well. Logs show five DIR log spikes (identified by arrows) signifying five distinct sill limbs in the Raton Formation. Red fill signifies DIR log readings past 200 ohm-m.

26 Pioneer Natural Resources geologists have found that the thickness of DIR log curve spikes match the thicknesses of sills as measured in cores (Powell, 2008). The practice of using DIR spikes as a measurement of sill thickness is well-tested and common within the oil and gas industry in the Raton Basin (Soetrisno, 2008).

Accordingly, DIR spikes are measured and added to quantify net sill thickness for a given well.

A cutoff level of 200 ohm-m is used to standardize measurements, and all measurements are taken from the x-axis reading of 200 ohm-m. The primary measurement technique is the measure function on Petra, which allows for manual measurements using a digital ruler. Once a DIR spike is identified, the spike is enlarged through the zoom function, and then measured from top to bottom using the measure function.

Complex Identification

Some sills are grouped into complexes, which can be traced throughout the basin. Sill complexes consist of multiple sills that appear in the same pattern and thickness at approximately the same stratigraphic level throughout an area. Grouping into complexes enables the mapping of a single intrusive group, and can offer insight into the nature and extent of intrusion.

Sills are only described and mapped as a discrete complex when a distinct pattern of intrusion occurs in multiple wells at the same stratigraphic level, and when no other nearby sills can be confused or combined with the original package (Fig. 15).

To avoid confusion, multiple sills included in a complex are never farther than 5 meters from the next nearest sill.

28 Sill Measurement Error

Error in sill measurements can arise from three sources. First, the well logs may be inaccurate either because of operator error or faulty equipment. The data in this project is the same data that Pioneer Natural Resources uses to engineer its oil and gas operations. Those high stakes operations demand a high level of precision and accuracy. Accordingly, the professional well logging utilized in this study is assumed to be reliable.

Second, manual measurements involve a degree of operator error.

Measurement error is minimized by zooming in on sills until the thickness of a computer screen pixel represents less than 4 centimeters of well depth. The thickness of most sills is on the order of meters, so the error associated with imprecise measurement is minimal, typically less than 3%.

Third, the DIR log measures changes in conductivity, which can result from factors other than rock type. This error is minimized by the nature of the sedimentary country rock, which consists of poorly conductive shales, sandstones, and mudstones.

Increases in conductivity can also result from water filled pore space in the sedimentary rocks. Water may amplify the DIR signal of its host rock; however the presence of water alone could not result in a 2000+ ohm-m jump in resistivity readings – that spike can only be accounted for by iron-and-magnesium-rich rock compositions.

Dike Proximity Measurements

The map of dikes is prepared by combining field mapping surveys and by tracing lineations observed in aerial magnetic surveys. The dikes in the northwestern

29 Raton Basin produce strong magnetic signatures due to the contrasting compositions of iron and magnesium laden dikes and dominantly quartzose country rock. As a result, the dikes result in linear “magnetic ridges” in aeromagnetic surveys - those ridges are readily traced using the draw function in PETRA.

Dike maps produced from magnetic surveys were verified and corrected during the summer of 2008 during a series of three field expeditions. Additionally,

Pioneer Natural Resources has employed field geologists to construct maps of dikes observed in the basin, and those maps serve not only as error checks, but also as additional data points. The dike maps used in this study are the combined set of magnetic surveys and field observations.

Dike proximity is evaluated in two ways for each well. First, the distance to the nearest dike is measured using the measure function in PETRA. Second, the number of dikes within circles of expanding radii (centered on the well) is counted.

Circles with radii of 500m, 1,000m, 1,500m, 2,000m, 2,500m, 3,000m, 3,500m,

4,000m, 4.500m, and 5,000m are used.

Dike Measurement Error

Errors in dike measurement may arise from two sources. First, the magnetic survey may be inaccurate. This possibility is minimized by cross checking the magnetic surveys with field observations and maps created from professional field surveys.

Second, the dikes dip slightly, so surface manifestations of dikes may be laterally offset from their position at depth. Fortunately, the vast majority of dikes in northwestern Raton Basin dip vertically or near vertically. During the 2008 summer

30 field trip, the shallowest dip recorded was three degrees away from vertical. The

Raton and Vermejo Formations are between 500 to 750 meters deep, so a dip angle of

three degrees would result in a lateral offset of between 70 and 120 meters. This

could be a significant source of error, so the circles of expanding radii are used as a secondary dike proximity measuring tool, which will dilute the error of a single dipping dike by accounting for the proximity of multiple dikes.

31 VI. Results

The following data were collected for the 89 wells analyzed as a part of this

study: (1) measurements of sill thicknesses in five stratigraphic categories (Raton

Formation, Vermejo Formation, Upper Raton Sill Complex, Lower Raton Sill

Complex, and Total Raton to Vermejo Sequence), (2) nearest dike proximity, and (3)

number of dikes within ten different radii categories from 500 to 5000m (Appendix

A). A separate table was prepared for the analysis of average sill thickness and

numbers of dikes within radii categories (Appendix B).

The relationship between dike proximity and sill thickness is analyzed using

two quantitative methods and one qualitative method. Quantitative studies include

comparisons of sill thickness to nearest dike proximity and comparisons of sill

thickness to number of dikes within varying proximities. For both quantitative

methods, regression analysis provides an equation and correlation coefficient

representing the relationship and strength in any data trends. A ranked Spearman analysis also checked the results’ significance. Data is analyzed qualitatively by interpreting isopach maps of net Vermejo Formation sills, net Raton Formation sills, and total sills – patterns of sill occurrence are then compared to patterns of dike occurrence.

Nearest Dike Proximity

The first quantitative method consists of scatter plots and regression analyses of nearest dike proximity and net sill thickness within a given stratigraphic category

(Figures 16-20). Each graph was prepared to analyze a different stratigraphic category and the relationship between sill abundance in that category and dike proximity. By

32 setting sill abundance in the Y axis and nearest dike proximity in the X axis, the graphs produce an effective measure of this relationship.

Figure 16. Total Combined Sill Thickness in Vermejo and Raton Formations Compared to Nearest Dike Proximity

30 y = 0.0011x + 14.929 R 2 = 0.0065 25

Thickness of Sills (meters) Sills of Thickness 15

0 0 500 1000 1500 2000 2500 Nearest Dike Proximity (meters)

Figure 17. Total Thickness of Sills in Raton Formation Compared to Proximity of Well to Nearest Dike

20 y = 0.0014x + 11.334 R 2 = 0.012

Total Sill Thickness in Raton (meters) Raton in Thickness Sill Total 10

0 0 500 1000 1500 2000 2500 Proximity to Nearest Dike (meters)

Figure 18. Total Sill Thickness in Vermejo Formation Compared to Nearest Dike Proximity

y = -0.0007x + 3.9477 R 2 = 0.0135 Thickness of Sills in Vermejo Formation (meters) Vermejo in of Sills Thickness 4

0 0 500 1000 1500 2000 2500 Nearest Dike Proximity (meters)

Figure 19. Thickness of Sills in Lower Raton Formation Compared to Nearest Dike Proximity

Net Sill Thickness in Lower Raton (meters) Lower Raton in Sill Thickness Net y = 0.0004x + 4.4483 R 2 = 0.0048

0 0 500 1000 1500 2000 2500 Proximity to Nearest Dike (meters)

Figure 20. Thickness of Sills in Upper Raton Compared to Proximity of Well to Nearest Dike 10

5 y = 0.0004x + 2.7063 2 R = 0.009 4

NetRaton Upper Sill in (meters) Thickness 2

0 0 500 1000 1500 2000 2500 Proximity to Nearest Dike (meters)

Figure 14 displays the broadest stratigraphic category; the graph compares net

sill thickness for the entirety of the Raton and Vermejo Formations to the proximity

of the nearest dike to a well. Each data point represents this relationship for a distinct

well. The chart yields an insignificant positive correlation between X and Y variables

and suggests that dike proximity has no bearing on the abundance of sills at a

particular locality. Analysis of specific stratigraphic intervals (Figs. 17-20) produces

similar negative results and indicates no stratigraphic control on sill abundance.

Figures 17 and 18 represent the next degree of sub-grouping and resolution for

the dike proximity relationship test. Figure 17 analyzes sill abundance and dike

proximity relationships in the Raton Formation while Figure 18 studies the same

relationship in the thinner, deeper, and older Vermejo Formation. Both charts produce

35 very weak (insignificant) correlations. Figure 17 shows a weakly positive relationship

while Figure 18 shows a weakly negative relationship. Again, the data suggest no

relationship between dike proximity and sill abundance.

Figures 19 and 20 add a final level of resolution to the analysis by studying

very narrow bands within the Raton Formation. Figure 19 plots sill abundance in the

Lower Raton Sill Complex against dike proximity while Figure 20 plots sill

abundance in the Upper Raton Complex against dike proximity. These stratigraphic

categories track discrete sill complexes throughout the study area by linking

structurally flattened cross sections and tracking sill limb thickness patterns.

Regression analysis shows insignificant relationships between X and Y variables -

even within the same sill complex there appears to be no relationship between intrusion thickness and proximity to nearest dike.

Frequency of Dikes within Varying Proximity Ranges

The second quantitative analysis consists of a series of regression-analyzed bar graphs showing relationships between average sill thicknesses by stratigraphic category in comparison to the number of dikes within various radii from a well

(Figures 21-24). These charts were prepared by summing the sill thickness within each stratigraphic category for each “grouping.” A grouping includes all wells with the same number of dikes within the specified dike proximity. The summed sill thicknesses were then divided by the number of wells in the grouping to produce averages. Average sill thicknesses were then graphed in relation to the number of

36 dikes occurring within the grounping’s proximity radius. This data is presented in

Appendix B.

Figure 21. Average Sill Thicknesses vs. Number of Dikes within 500 meter

2 Tail Sig = .614 P Value = .146

Figure 22. Average Sill Thicknesses vs. Number of Dikes within 1000 meters

20 y = 0.002x + 16.6 18 R 2 = 3E-06

12 y = -0.6452x + 15.622 R 2 = 0.2081 10

8 Average Sill Thickness (meters) Thickness Sill Average Average Net Sills in TRU and VRM vs. Dikes 6 Within 1000m y = 0.6471x + 0.9777 Average Net Sills in TRU vs. Dikes R 2 = 0.3002 Within1000m 4 Average Net Sills in VRM vs. Dikes Within 1000m Linear (Average Net Sills in TRU and VRM 2 vs. Dikes Within 1000m) Linear (Average Net Sills in VRM vs. Dikes Within 1000m) 0 Linear (Average Net Sills in TRU vs. Dikes 0 1 2 3 4 Within1000m) Number of Dikes within 1000m

Figure 23. Average Sill Thicknesses vs. Number of Dikes within 2500m

y = -0.2742x + 18.763 R 2 = 0.0591 Average Net Sills in TRU and VRM vs. Dikes Within 2500m Average Net Sills in TRU vs. Dikes Within 15 2500m Average Net Sills in VRM vs. Dikes Within 2500m y = -0.3677x + 16.171 2 Linear (Average Net Sills in TRU and VRM R = 0.0781 vs. Dikes Within 2500m) Linear (Average Net Sills in TRU vs. Dikes 10 Within 2500m) Average Sill Thickness (meters) Thickness Sill Average Linear (Average Net Sills in VRM vs. Dikes Within 2500m) y = 0.0934x + 2.5916 R2 = 0.0241 5

0 1 2 3 4 5 6 7 8 Number of Dikes within 2500m

Figure 24. Average Sill Thicknesses vs. Number of Dikes within 5000m

20 y = -0.4716x + 19.616 2 R = 0.2424 Average Net Sills in TRU and VRM vs. Dikes Within 5000m Average Net Sills in TRU vs. Dikes Within 15 5000m Average Net Sills in VRM vs. Dikes Within 5000m Linear (Average Net Sills in TRU and VRM vs. Dikes Within 5000m) Linear (Average Net Sills in TRU vs. Dikes y = -0.5882x + 17.965 10 Average Sill Thickness (meters) Thickness Sill Average Within 5000m) R2 = 0.4101 Linear (Average Net Sills in VRM vs. Dikes Within 5000m)

y = 0.1166x + 1.6506 R 2 = 0.0759 5

0 2 3 4 5 6 7 8 9 10 11 12 13 14 16 17 Number of Dikes within 5000m

38 Figure 21 shows a positive relationship with a correlation of R2 = 0.614 for

combined Raton and Vermejo sill thickness averages plotted against dike frequency

within 500m. A spearman rank analysis confirmed that positive correlation as more

than chance occurrence and yielded a P value of 0.146. The Raton Formation alone

shows a positive correlation with R2 = 0.51, and the Vermejo Formation alone has a weakly positive relationship to dike frequency within 500m and an R2 = 0.47.

Figure 22 shows a near-zero correlation between sill abundance and the number of dikes within 1000m. The chart was prepared by averaging the total thickness of sills within stratigraphic categories for five dike frequency groups. Dike frequency groups consist of wells with 0, 1, 2, 3, and 4 dikes within 1000 meters. The average sill thickness for each dike frequency group was then compared against the number of dikes associated with the group. The result, a correlation value of 0.000003 for sill abundance in both formations versus dike frequency, is a resounding confirmation that sill thickness is not controlled by the number of dikes within one kilometer of a well.

The negative result is repeated in regression analyses of the Raton and

Vermejo Formations’ individual correlations to dike frequency in the 1000m proximity radius. The Raton Formation correlates at an R2 value of 0.28. The

Vermejo Formation shows a similarly low correlation to dike frequency of R2 = 0.30.

Figures 23 and 24 produce similar negative results for the 2500m and 5000m radii. The correlation coefficients for all stratigraphic categories vs. 2500m and

5000m dike frequencies all fall below R2 = 0.08. One exception exists, which is an R2 value of 0.41 for net Raton sills versus the number of sills within 5000m; however,

39 this correlation is still too small to infer any meaningful correlation between sill abundance and dike proximity.

Sill Isopach Mapping

Sill data are qualitatively analyzed using isopach maps of sill thicknesses overlain on maps of dikes. Isopach maps (Figures 25-26) were created using PETRA zone functions. A zone item for sill thicknesses in each stratigraphic category was added by uploading Excel data tables into PETRA. Zone items were then converted to isopach thickness data sets and overlain on the study area map as a contour profile. These isopach maps are useful for understanding where abundant sill concentrations occur in relation to dikes. Note that PETRA data in these maps is presented in imperial units as a result of imperial measurements taken by Pioneer Natural Resources. Figure 25 shows sill thicknesses for the Raton Formation. This map shows several patterns between the spatial distribution of sills and dikes. Nine sill concentration zones are identified as areas where net sill thickness exceeds 55 feet (~ 17 m). Sills concentration zones generally occur where multiple dikes intersect or come in close proximity to one another. Of nine observed sill concentration zones, seven occur within 1 km of a dike. Five of nine occur where multiple dikes converge. Only two sill concentrations (near the Mustang and Heyden wells in the eastern central section of Figure 25) occur over 2km from nearest dikes and in the absence of dike swarms. Another important observation is that sills seem to be confined to the eastern three quarters of the study area. Wells like Exodus, Einstein, Zen, Spyglass, and other western wells are all devoid of sills. There exists a clear north-south trending boundary spanning the western third of the map which confines sills in the Raton Formation.

42 Figure 26 illustrates cumulative thickness of sills in the Vermejo Formation.

In the northern half of the map, sill concentration zones in the Vermejo Formation largely coincide with concentration zones in the Raton Formation. In the southern half, however, sill concentration zones are more diffuse. Vermejo Formation concentration zones are defined by sill thickness exceeding 20 feet (~ 6 m). Again, most concentrations occur where multiple dikes converge. The same two concentrations in the eastern-central section of Figure 25 also persist in the absence of nearby dikes in Figure 26.

Unlike the Raton Formation, Vermejo sills extend throughout the western wells. Vermejo sills do not, however, reach the eastern extent of the map. Wells like

TYL, Boxter, Trimax, and other eastern wells show no sill thickness in the Vermejo

Formation (Fig. 26).

Coal Isopach Mapping

As discussed in the introduction, data used for isopach mapping of sills was not collected as a part of this thesis. The data are derived from Pioneer Natural

Resources’ data files.

Figure 27 shows net coal thickness for the Raton formation. Coals in the

Raton Formation appear to be distributed evenly throughout the mapped area. Dike proximity exerts no noticeable affect on sill distribution – some coal concentrations occur in the absence of nearby dikes while other abundant coal zones occur where multiple dikes converge.

Figure 28 shows net coal thickness in the Vermejo Formation. The Vermejo formation displays more variability in coal thickness. Five sill hotspots are identified

43 in the mapped area. One concentration occurs in the middle eastern section of the map, two on the southern part of the map, one on the middle western section, and one at the north. All of these coal concentrations occur within one kilometer of two dikes, and four occur within three dikes. The easternmost coal concentration extends from the Starbucks well to the Boxter well, which spans a dike-free zone between two dike swarms.

Coal concentrations in the Vermejo Formation do not appear to coincide with

Raton Formation hotspots. The zones of greatest coal abundance in the Raton

Formation (near the Didcot and Jenifer wells) overlie the zone of lowest coal abundance in the Vermejo Formation. Similarly, the zones of greatest coal abundance in the Vermejo Formation underlie the areas of lowest coal abundance in the Raton

Formation (compare eastern sections of Figures 25 and 26).

46 VII. Discussion

This study set out to test the relationship between sills and dikes, and specifically, to assess whether dikes in the Raton Basin acted as feeders for sills. The hypothesis was tested by collecting dike location data from aeromagnetic surveys and sill thickness data from well logs. Sill abundance is compared to (1) nearest dike proximity and (2) the number of dikes within varying proximities to a well. In addition to the original hypothesis, the relationship between sills and coal beds has also been tested through isopach mapping. Coal and sill mapping was produced as an effort to assess the pattern of sills preferentially intruding coals, which has been suggested in previous research and was observed during well log analysis in this project. The implications of these results are discussed in the following section, which. also offers suggestions and recommendations for future studies that might be completed to further test the original hypothesis.

Nearest Dike Proximity

Scatter plotting and regression analysis shows no correlation between sill abundance and nearest dike proximity. Five different stratigraphic intervals were analyzed (Figs. 16-20) and the highest correlation coefficient for any category was for net Vermejo Formation sill thickness compared against nearest dike proximity, which produced a coefficient of R2 = 0.0135 (Fig. 18). Considering all five stratigraphic intervals, the correlations between sill abundance and nearest dike proximity are between a low of R2 = 0.0048 and a high of R2 = 0.0135.

Furthermore, no pattern emerges from the slopes of plotted trend lines. Figure

18 shows a negative relationship between sill abundance and dike proximity while

47 figures 16, 17, 19 and 20 show contrasting positive trends. The correlation coefficients between sill abundance and dike proximity are uniformly low and strongly suggested that the proximity of a well to the nearest dike has no bearing on the abundance of intrusive sills in the Raton or Vermejo Formations in this portion of the Raton Basin.

These findings do not, however, disprove the hypothesis proposed by Cooper et al. (2004), who suggest that dikes acted as feeders for sills. Instead, the data presented here indicates that sill thicknesses do not increase or decrease significantly in relation to the proximity of the nearest dike. This may be explained by multiple models, many of which could be tested in future studies. A later section of this thesis will discuss the opportunities for future work.

The first explanation of negative proximity test results is that the nearest dike to a well is not necessarily the primary feeder of sills in that well. Dikes and sills in the Raton Basin intruded in seven distinct generations (Miggins, 2002), so it is possible that an early dike may have fed many of the sills in a well, then a later dike could have intruded closer to the well, but not contributed a significant amount of sills to the stratigraphic interval analyzed (Fig. 29). In this situation, a measurement taken from a well to the closest dike would measure the distance to a non-feeder dike.

This possibility could be explored by comparing the petrology and geochemistry of dikes and sills to provide constraints on which dikes fed which sills.

Figure 29. Diagrammatic cross section of an intrusion situation in which the closest dike to a well contributes minimally to the net thickness of sills in that well.

A second plausible explanation for the study’s negative result could be that sill thickness is determined largely by coal bed or fracture aperture. Cornelius et al.

(2004) argue that intrusions formed pepperite flows by vaporizing the water in coal seams. The high temperature, high pressure vapor helped blast intrusive material through country rock, preferentially intruding coal beds as planes of least resistance.

It seems possible that the thickness and abundance of coal seams in a particular stratigraphic interval could have had an effect on the net thickness of sills.

49 Similarly, the aperture of any fractures being intruded would likely affect sill

thickness. Not all dikes intrude coal beds, and a likely alternative plane of intrusion

would be horizontal fractures and separations between bedding planes. Exhumation,

heating, and uplift often result in separation or fracturing along bedding planes, so the

orogenic activity, uplift, and magmatism of the Raton Basin’s geologic history likely

generated bedrock fracturing. Dikes may have fed magmas into those fractures, in

which case sill abundance would be constrained by the frequency and aperture of

fractures, not dike proximity. This hypothesis is testable in future work by comparing

sill thicknesses to coal seam thicknesses and proximities, but was not testable using

the well log data available to this project. More thorough recommendations for future

work will be presented in the “Recommendations for Future Studies” section of this

chapter.

Frequency of Dikes within Varying Proximity Ranges

The data show a positive correlation between sill abundance and the number of dikes within 500m (Figure 21). The correlation of dike frequency and sill abundance decays as the proximity radius expands. Figures 21-24 were prepared to compare the number of dikes within ten proximity ranges from a well against the well’s sill abundance in five stratigraphic intervals. With the exception of Figure 21, regression analysis showed insignificant relationships between the number of dikes within a given distance to a well and the abundance of sills within that well.

Figures 21-24 show that sill abundance in the Total Well stratigraphic intervals (Raton and Vermejo Formations combined) and the isolated Raton

Formation interval both uniformly correlate positively to dike frequency across all

50 proximity ranges. However, the correlations fall below significance (R2 > 0.5) at radii

greater than 500m. Similarly, sill abundance in the Vermejo Formation is only

positively correlated to dike frequency within 500m (Fig. 21); sill abundance in the

Vermejo Formation shows a negative relationship to dike frequency outside of 500m

(Figs. 22-24).

These findings suggest that the number of dikes very close to a well (within

500m) have a significant effect on sill abundance in that well. The effect is most

pronounced when analyzing net sill abundance in the Raton and Vermejo Formations

combined. Decreasing correlations to dike frequency for individual sill complexes

may be the result of processes similar to those explained in the Dike Proximity

section (sills preferentially intruding a specific fracture or coal bed). Also, discrete sill

complexes may be fed by a single dike, and the relationship to that single feeder dike

will be obscured by comparing the sill complex’s thickness to larger numbers of dikes

within a radius.

Positive Correlation between Sill Thickness and Dikes within 500 Meters

The positive correlation in Figure 21 begs an explanation. It is possible that areas of increased dike frequency occur as the result of more fracture-prone bedrock.

The Raton and Vermejo formations are dominated by lithified clastic sediments, which have been subjected to various stresses during millions of years of uplift, orogeny, and intrusion. Cooper et al., (2004) suggest that natural fracturing patterns in the Raton Basin are controlled by (1) lithological variation and (2) differential stress regimes.

51 The Raton Basin is dominated by mostly east-west striking shear fractures that

formed normal to the thrust front responsible for the Sangre de Cristo Range.

However, Cooper et al. (2004) find localized examples of extensional fracturing and

conjugate fracture systems. Regional strain regime variation likely results from the many generations of orogeny, uplift, and intrusion in the Raton Basin’s history.

Lorenz et al. (2003) discuss how zones of intense compressional stress within Raton

Basin resulted in “bedding-parallel displacements in the shallow strata well east of the thrust front,” and suggest that bedding separation varied depending on local stress regimes. Accordingly, it is conceivable that certain areas within the basin contain

more stress-induced fractures than others, and that increased fracturing may have accounted for dike convergence and coincident sill intrusion.

Lithologic variation also contributes to a rock’s propensity to fracture. Cooper

et al. (2004) discuss how fluvial sandstones in the Raton Formation exhibit different

fracture patterns from the laterally extensive Trinidad Sandstone or Niobrara

Limestone. Rocks within individual formations in the Raton Basin are far from

homogeneous, and thus lithologic variation may have resulted in zones of increased

vertical and horizontal fracturing.

This model proposes that sills and dikes will be most abundant in the most

highly fractured areas of bedrock. The causes of vertical and horizontal fractures are

different - tectonic stresses (orogeny and folding) likely account for most vertical

fractures while horizontal fractures likely derive from bedding plane separation

during exhumation. Despite the primary causal differences between vertical and

horizontal fractures, it is possible that local changes in rock composition or local

52 differences in stress magnitude and orientations could produce more or less fracturing in both fracture orientations.

Another possibility in this model is that the process of dike intrusion weakened rocks within a small radius. The heating from intruded magmas would have caused expansion, which could in turn cause fracturing. That fracturing could then account for increased sub-horizontal intrusion around a dike. This model would explain why areas where multiple dikes converge have increased net sill thickness – dike convergence increased local fracturing. In this scenario, vertical fracturing is the dominant control on sill abundance; areas strained such that vertical fractures were more abundant would have attracted more dikes and thus accrued more sills.

Sill Isopach Mapping

Isopach maps in Figures 25 and 26 show the net thickness of sills in the Raton and Vermejo Formations, respectively. The locations of dikes have been superimposed on the sill thickness isopach maps to qualitatively compare the relationships between dikes (proximity and quantity) and sills.

Findings in Figures 25 and 26 support the findings from Figure 21 – sill thickness often increases in areas where many dikes converge. Figure 21 establishes a positive relationship between sill abundance and the number of dikes within 500 meters. Figures 25 and 26 present a qualitative confirmation of this finding. Seven of nine sill hotspots (net sill thickness > 55 feet (~ 17 m)) in the Raton Formation occur near dike convergence centers, and seven of ten Vermejo Formation hotspots occur in dike convergence centers.

53 As previously discussed, hotspots of sills and convergences of dikes may

coincide as the result of lithologic or paleostress controls. Alternatively, dike

intrusion may have heated, expanded, and fractured rocks, and then filled those

fractures with sills, thereby producing increased sill thickness in the immediate

vicinity of dikes.

This possibility is reinforced by the boundaries that prevent sills from extending west in the Raton Formation and east in the Vermejo Formation. Sills

appear to be confined to the central zone, perhaps as a result of increased fracturing in the central region of the study area. This possibility could be tested in future work by studying fracture patterns and compositional variation. Such tests might reveal potential sill controls and boundaries to intrusion.

Coal Isopach Mapping

Figures 25 and 26 are included as an attempt to identify any relationships between coal thickness and sill thickness. The maps respond to the observation that sills consistently coincide with coal seams in well logs, and that the same sills appear to follow the same coals throughout cross sections. This pattern may be the source of the discrete sill complexes – sills may intrude a close grouping of coal seams throughout a finite area, thus producing a similar intrusion pattern in the wells that penetrate the intruded coals.

Figure 25 shows a slight “bull’s eye” pattern, where concentric isopach circles form around wells. This phenomenon occurs for datasets with many outliers, which prevent the construction of a smooth gradient. The bull’s eye pattern suggests either

54 drastic variability in coal thickness over short distances, or, more likely, inconsistent data collection. The Pioneer data set only contained coal thickness data for 56 wells, and the methods for assessing those data seem to have been based on arbitrary (but generally effective) macro sensor criteria.

As discussed in the introduction section, the accuracy of coal thickness data is uncertain because the data collection process was not done for or by this research effort. These maps are presented as an experiment in testing the coal-sill relationship, and ultimately, these maps should not be viewed as grounding for scientific interpretation or analysis. However, the maps may serve as an example of possibilities for future research, which are discussed the following sections.

Additional Controls

Given unlimited resources, several additional pieces of data could help to better constrain the relationship between dikes and sills. Ideally, petrologic and/or geochemical analysis of dikes and sills could potentially constrain those sills that are genetically related to certain dikes. It would first need to be established whether distinct differences exist in the petrology and geochemistry of different generations of dikes in the region, as suggested by (Miggins, 2002). Once this is established, comparisons of sill petrology and geochemistry in wells with dikes in close proximity could reveal which dikes are in fact the feeders to sills within an individual well. If sills are in fact derived from dikes, then sill petrology should parallel feeder dike petrology.

55 Tighter well control would also allow for more confident tracking of discrete

sill complexes. The widely varying spacing of wells within Raton Basin is a product

of the economics of natural gas recovery; an ideal study area would be gridded and

planned for uniform data coverage. This study infers sill complex continuity across

distances sometimes greater than one kilometer – the result is a series of isopach

maps with “bull’s-eye” hotspots over isolated wells and an unavoidable degree of

error involved for the stratigraphic categories of Upper and Lower Raton sill

complexes. A grid of wells with 500 meter spacing would allow for more accurate

isopach mapping and three-dimensional mapping of sills. The ability to track sills,

identify their boundaries, “pinch outs,” and thickest points of sill complexes would help assess relationships to dike locations.

The initial goal of this research was to test the relationship between sill abundance and heat. The initial project planned to derive geothermal gradients and heat flow from accurate bottom hole temperature (BHT) data. Unfortunately, BHT data in Pioneer’s data set was corrupted by taking temperatures within moments of drill bit removal, and the result was temperature data with no correlation to ambient rock temperature. Ideally, drillers would allow adequate cooling time before taking temperature measurements, which would allow for comparisons between temperature and various intrusion abundance categories. This information would enable quantification and mapping of geothermal potential, and could potentially serve as a basis for geothermal energy development projects in the Raton Basin.

56 Recommendations for Future Studies

The most immediate actionable study on this data set would be a comparison

of sill abundance to coal abundance. Cooper et al. (2004) and Cornelius et al. (2004)

suggest a close relationship between the two features, and PETRA log analysis

software provides an appropriate testing ground for those hypotheses. Methods for coal and sill identification in PETRA are discussed in Appendix C. In the course of producing this study and analyzing hundreds of well logs, there appeared to be a

strong correlation between both the thickness and stratigraphic location of sills and

the thickness and location of coal seams. Thicker coal seams were correlated with

thicker sills, and sills often occur in or near coals. Isopach mapping in this research

provides a qualitative assessment, but a rigorous quantitative study could provide

much more useful information.

A study of the coal-sill relationship might find some useful analogies in the

methods of this thesis. One could quantify the proximity of each sill in a well to the

nearest coal seam in a well. Additionally, one might count the number of coal seams

within expanding proximity boundaries from a sill. Other important information

might include measuring the thickness of sills and the thickness of the nearest coal

beds. This data would allow for studies designed to isolate the influence of coal

thickness, proximity, and frequency on sill limb thickness. Regression analysis,

scatter plotting, and category-averaged bar graphing could also be useful methods of

analysis for a coal-sill project.

57 VIII. Conclusions

The feeder dike hypothesis proposed in previous research (Cooper et al.,

2004; Cornelius et al., 2004) has been confirmed through quantitative and qualitative

testing of sill abundance and dike proximity relationships. Within this area in the

Raton Basin, sill abundance in the Raton and Vermejo Formations increases

significantly in areas within 500 meters of dike convergence zones.

No correlation was found between sill abundance and the number of dikes

outside of the 500 meter radius. Furthermore, the proximity of the nearest dike has no

significant bearing on sill abundance.

The confirmation of a positively correlated sill-dike relationship may lead to

further tests of coal-sill and temperature-sill relationships. Further research may

expand on the data sets available to Middlebury College and utilize the PETRA software now permanently available to Middlebury College researchers.

The implications of this study’s findings are manifold – results may be useful for academic and industrial applications. The knowledge of intrusion behavior may help geothermal energy explorers avoid wasting hundreds of thousands of dollars and many hours exploring for heat resources. Where multiple dikes converge on the surface, a geothermal producer may expect to find increased sill abundance, and that sill abundance has been suggested to facilitate the movement of hydrothermal fluids and radiation of heat. Accordingly, geothermal producers my sink their wells near dike convergence zones and have increased probabilities of encountering economic geothermal resources.

58 Coal Bed Methane producers may also apply this research to their production efforts. Sills destroy the economic potential of coals, a fact that frequently frustrates

CBM producers with non-producing or poorly producing wells that perforate “over cooked” coal seams. CBM producers may now target areas of the Raton Basin that are removed from dike convergence zones. In this way, CBM producers will have a greater chance of avoiding sill abundant areas and over cooked coal resources.

59 References Cited

Berkman, F.E., and Carrol, C.J., 2007, Interpreted Geothermal Heat Flow Map of Colorado: Denver, CO, Colorado Geological Survey, p 1-5.

Carter, D.A., 1956, Coal Deposits of The Raton Basin, in Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geologists, p. 89-94.

Clarke, P., Cornelius, C., and Turner, P., 2004, A Refined Lithostratigraphy for the Raton Formation Implications for Alluvial Heterogeneity, Coal-Forming Environments and Coal Bed Distribution – Raton Basin: p. 1-5.

Cobban, W.A., 1956, The Pierre Shale and Older Cretaceous Rocks in Southeastern Colorado, in McGinnis, C.J., ed., Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geologists, p. 25-28.

Cooper, J.R., Crelling, J.C., Rimmer, S.M., and Whittington, A.G., 2007, Coal metamorphism by igneous intrusion in the Raton Basin, CO and NM; implications for generation of volatiles; TSOP 2005; papers from the 22nd annual meeting of TSOP: International Journal of Coal Geology, v. 71, p. 15-27.

Cooper, J.R., Whittington, A., and Crelling, J.C., 2004, Intrusion geometry and coalbed methane generation; regional thermal effects of volumetrically minor sills in the Raton Basin, Colorado-New Mexico; Geological Society of America, 2004 annual meeting: Abstracts with Programs - Geological Society of America, v. 36, p. 215.

Cornelius, C., Clarke, P., and Turner, P., 2004, Basin scale peperites in Cretaceous coals; host rock fluidization ca. 30 million years after lithification; Geological Society of America, Rocky Mountain Section, 56th annual meeting; Geological Society of America, Cordilleran Section, 100th annual meeting: Abstracts with Programs - Geological Society of America, v. 36, p. 85.

EPA, 2004, Attachment 9: Raton Basin, in Evaluation of Impacts to Underground Sources of Drinking Water by Hydraulic Fracturing of Coalbed Methane Reservoirs: Washington D.C., Environmental Protection Agency, p. A9-7, 3.

Gabelman, J.W., 1956, Tectonic History of the Raton Basin Region, in Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geologists, p. 35-39.

60 Johnson, R.B., and Wood, G.H., 1956, Stratigraphy of Upper Cretaceous and Tertiary Rocks of Raton Basin, Colorado and New Mexico, in McGinnis, C.J., ed., Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geology, p. 28-34.

Keighin, William C., Rice, Dudley D., Finn, Thomas M., 1995, National Assessment of United States Oil and Gas Resources: Raton Basin-Sierra Grande Uplift Province (041), U.S. Geological Survey Circular 1118, United States Government Printing Office, Washington, p. 4-6.

Knopf, A., 1956, Igneous Geology of the Spanish Peaks Region, Colorado, in McGinnis, C.J., ed., Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geologists, p. 56-57.

Lorenz, J.C., Cooper, S.P., Keefe, R.G., and Chidsey, T.C., Jr (chairperson), 2003, Syn-sedimentary deformation in the central Raton Basin, Colorado and New Mexico; a potential control on sandbody orientation; 2003 AAPG annual convention with SEPM: Annual Meeting Expanded Abstracts - American Association of Petroleum Geologists, v. 12, p. 107.

Macartney, H., 2008, Personal Communication: Pioneer Natural Resources Energy Consumption and Costs.

Miggins, D.P., 2002, Chronologic, geochemical, and isotopic framework of igneous rocks within the Raton Basin and adjacent Rio Grande Rift, south-central Colorado and northern New Mexico: United States (USA), University of Colorado at Boulder, Boulder, CO, United States (USA), p. 1-2.

Mims, Christopher. "Can Geothermal Power Compete with Coal on Price?" Scientific American 2 Mar. 2009: 1-3.

Mudge, M.R., and Orial, S.S., 1956, Problems of Lower Mesozoic Stratigraphy in Southeastern Colorado, in McGinnis, C.J., ed., Guidebook to the Geology of the Raton Basin, Colorado: Denver, CO, Rocky Mountain Association of Geologists, p. 19-24.

Muggleton, S.R., Geissman, J., and Wawrzyniec, T.F., 2005, Magnetic fabrics as indicators of magma flow and emplacement mechanisms for the Spanish Peaks igneous complex (south-central Colorado); Geological Society of America, 2005 annual meeting: Abstracts with Programs - Geological Society of America, v. 37, p. 556.

61 Pillmore, C. L., Nichols, D. J., and Fleming, R. F., 1999, Field guide to the continental Cretaceous-Tertiary boundary in the Raton basin, Colorado and New Mexico: Geological Society of America, Field Guide 1.

Powell, K., 2008, Personal Communication: Use of Dual Induction Resistivity Logs to Approximate Sill Thicknesses.

Ramage, J.K., Murphy, M.A., and Blankenship, E.L., 2008, Structural evolution of the sangre de cristo uplift, south-central Colorado; Geological Society of America, 2008 annual meeting: Abstracts with Programs - Geological Society of America, v. 40, p. 155.

Shaw, G.L., 1956, Sub-Surface Stratigraphy of the Permian-Pennsylvanian Beds, Raton Basin, Colorado, in McGinnis, C.J., ed., Guide Book to the Geology of The Raton Basin, Colorado: Denver, CO, Rocky Mountain Assosciation of Geologists, p. 14-18.

Soetrisno, H., 2008, Personal Communication: Reliability of DIR Log for Identifying Intrusions.

Tester, J.W., Anderson, B.J., Batchelor, A.S., Blackwell, D.D., DiPippo, R., Drake, E.M., Garnish, J., Livesay, B., Moore, M.C., Nichols, K., Petty, S., Toksöz, M.N., and Veatch, R.W., 2006, The Future of Geothermal Energy: Impact of Enhanced Geothermal Systems (EGS) on the United States in the 21st Century: Massachusetts Institute of Technology.

62 Appendix A Sill Thickness Data By Well and Stratigraphic Interval

Net Net TRU3 Net TRU2 Other Raton Net Raton Net Vermejo Total Well Name Sills Sills Sills Sills Sills Sills upper lower complex complex (meters) (meters) (meters) (meters) (meters) (meters) Avant 14-3 6.92 3.84 0.00 10.76 8.14 18.90 Aviator 12-4 2.99 0.00 1.07 4.05 11.28 15.33 Banker 32-16 3.04 9.35 3.51 15.90 0.00 15.90 Beacon 11-18 5.59 4.34 10.80 20.73 4.75 25.48 Biber 44-21V 3.87 3.33 14.32 21.53 0.00 21.53 Black Cloud 23-3 2.77 21.90 0.00 24.68 3.98 28.66 Blade Runner 23-21 5.96 7.67 0.00 13.62 0.00 13.62 Boxster 12-23 5.34 5.30 6.91 17.55 0.00 17.55 Carroll 32-27 6.04 5.97 0.00 12.01 0.00 12.01 Chevelle 21-9 6.68 5.74 11.28 23.70 0.00 23.70 Cluck 21-25 0.00 2.97 2.92 5.90 6.48 12.38 Cobblestone 24- 14 0.00 0.00 0.00 0.00 2.25 2.25 Comet 31-3 4.60 5.27 0.00 9.88 11.83 21.70 Condor 14-23 2.13 3.47 6.17 11.77 0.00 11.77 Cordillera 34-7 2.44 4.02 9.09 15.55 2.90 18.45 Cotter 44-32 3.28 9.90 6.10 19.28 5.13 24.41 Crist 21-11 3.29 2.53 7.77 13.59 0.00 13.59 Croc 42-9 5.79 4.39 9.27 19.46 0.00 19.46 Crossword 41-36 0.00 0.00 0.00 0.00 2.53 2.53 Cruiser 32-12 4.83 5.88 12.60 23.31 4.70 28.01 Cuda 31-4 0.00 6.08 1.70 7.79 2.88 10.67 Didcot 42-9 4.39 12.05 1.89 18.34 8.76 27.10 Dolomite 32-1 3.14 7.44 6.99 17.57 0.00 17.57 EINSTEIN 34-11 R 0.00 0.00 0.00 0.00 5.53 5.53 Evelyn 43-33 6.19 0.00 0.00 6.19 7.59 13.78 Exodus 44-13 0.00 0.00 0.00 0.00 4.62 4.62 Fandango 14-28 5.64 7.32 0.00 12.95 0.00 12.95 Fat Cat 13-21 0.00 3.95 9.59 13.54 3.60 17.14 Flat Spot 33-2 0.00 6.17 2.37 8.54 5.07 13.61 Flying Horse 12- 11 4.11 8.52 10.44 23.07 0.00 23.07 Getem 21-23 0.00 9.48 0.00 9.48 2.42 11.90 Ginetta 32-35 3.84 5.09 11.88 20.82 0.00 20.82 Greenhorn 12-24 0.00 8.86 3.92 12.78 6.55 19.33 Grolsch 44-7 0.00 0.00 0.00 0.00 5.07 5.07 Hat Trick 41-6 3.12 4.96 8.18 16.26 0.00 16.26 Heidsick 11-2 0.00 4.02 3.64 7.65 0.00 7.65 Heyden 11-22 4.11 3.94 7.58 15.64 0.00 15.64 Hill 33-22 4.72 3.65 5.55 13.92 0.00 13.92

63 Hughes 21-30 0.00 5.58 5.60 11.18 11.18 22.36 Hyon 23-32 1.18 3.40 17.93 22.50 3.50 26.00 Interceptor 43-13 Kv 2.79 4.54 8.61 15.94 8.01 23.95 J & J 42-5 1.60 3.37 14.39 19.35 0.00 19.35 James 11-27 4.83 10.93 0.00 15.76 1.65 17.40 Keiko 14-6 0.00 6.86 0.00 6.86 2.51 9.37 Lola 21-3 5.29 4.91 10.81 21.02 3.39 24.41 Lynch 43-30 0.00 0.00 0.00 0.00 2.59 2.59 Lynn 32-4 7.32 0.00 0.00 7.32 6.61 13.93 Masters 33-32 0.00 0.00 0.00 0.00 3.26 3.26 Miata 14-27 4.30 4.22 4.09 12.62 0.00 12.62 Monterey 33-6 0.00 15.62 0.00 15.62 6.18 21.80 Moo Moo 31-36 0.00 5.47 0.00 5.47 4.43 9.91 Mustang 41-30 3.96 4.41 16.58 24.95 8.55 33.50 Nash 34-23 0.00 4.15 3.23 7.38 6.86 14.23 Nuggett 44-2 5.55 3.72 2.90 12.16 2.56 14.72 Oswald 11-16 8.89 4.28 2.60 15.77 0.00 15.77 Paradise 13-8 3.39 3.00 7.07 13.46 3.52 16.98 Parnelli 44-4 3.68 8.97 11.99 24.63 4.00 28.63 Parrothead 31- 31 0.00 7.95 6.77 14.72 6.92 21.63 Pawley Canyon 24-26 5.12 5.79 0.00 10.91 9.02 19.93 Pioneer 34-27 4.27 2.74 0.00 7.01 10.82 17.83 Quinten 13-15 4.48 4.55 6.12 15.15 0.00 15.15 Rainwater 11-10 4.92 2.61 13.60 21.13 0.00 21.13 REDNECK 3.76 3.56 4.60 11.92 6.38 18.30 Reynard 34-34 2.45 3.62 13.15 19.21 0.00 19.21 Robinson 11-34 4.05 3.66 0.00 7.71 5.94 13.66 Rover 21-28 3.63 3.54 7.69 14.86 0.00 14.86 Royale 32-3 0.00 4.15 7.40 11.55 3.41 14.95 Skip 23-10 4.14 3.97 6.42 14.52 0.00 14.52 Slate 23-30 0.00 0.00 0.00 0.00 4.18 4.18 SMASH HIT 3.70 3.40 5.00 12.11 4.29 16.39 Sparton 21-9 3.98 3.18 15.71 22.87 2.17 25.05 Speedway 41-1 5.18 6.22 0.00 11.40 11.01 22.40 Spyglass 13-30 0.00 0.00 0.00 0.00 2.87 2.87 Stacie 41-2 3.13 0.00 0.00 3.13 0.00 3.13 Starbucks 42-34 3.26 3.26 4.22 10.74 0.00 10.74 Studebaker 3.86 2.92 10.36 17.14 5.38 22.52 Supernova 44-3 0.00 6.42 5.75 14.12 0.00 14.12 Suzuka 6.10 3.96 0.00 10.06 7.32 17.37 T.Y.L. 42-27 3.31 4.33 8.76 16.39 0.00 16.39 Thoroughman 42-35V 4.81 4.47 0.00 9.28 4.04 13.31 Tiaga 23-14 4.79 6.13 6.26 17.18 0.00 17.18 TOP DOG 4.30 3.66 2.64 10.60 2.63 13.23 Tornado 44-18 0.00 0.00 0.00 0.00 3.58 3.58 Trimax 44-23 3.01 7.52 8.45 18.97 0.00 18.97

64 Trommeter 44- 20 6.79 6.38 3.86 17.03 6.19 23.22 Vagabond 31-29 0.00 2.68 0.00 2.68 0.00 2.68 VENDETTA 32-1 0.00 0.00 0.00 0.00 7.18 7.18 Vertigo 44-6 5.07 3.01 13.16 21.24 4.52 25.77 Viper 42-24 0.00 10.32 8.46 18.78 0.00 18.78 Whinny 42-2 5.86 4.43 0.00 10.29 4.39 14.68 Williams 13-22 6.37 11.14 0.00 17.51 4.47 21.99 Zen 42-14 0.00 0.00 0.00 0.00 5.76 5.76

67 Appendix C

PETRA Instructions for Continued Research

This appendix will serve as a catalogue of important directories, file names, and data lists associated with this research project. This will not (and cannot) serve as a complete user manual or instruction guide for PETRA software. Note that the

PETRA technical support hotline (918-971-7071) is extremely helpful; the representatives on this hotline can actually send an email link that enables them to view your screen. Do not hesitate to contact them as it is toll free and has repeatedly helped in the negotiation of data and software problems during this research.

Software

PETRA SERIAL #: 4800332

Faculty recipient of product: Dave West

Hasp Bitlock Key: A purple USB “key” akin to a pen drive that must be inserted into the computer tower before PETRA will open.

Thesis operating file: Z:\PetraDBI\Raton Basin Copy Oct2008

Overlay file: AAA generic Overlay

Projection

U.T.M. (Northern Hemisphere) Projection, Zone 13

XY Units : FEET

Ellipsoid: Clarke 1866

68 Using the Software

Note: all materials delivered with the initial software package (including the purple Hasp Bitlock key) will be given to Dave West at the end of this research. Any researcher desiring to continue using this PETRA software will have to do the following:

1) Renew PETRA license if necessary. Middlebury owns an annually renewable license with the right to infinite free renewals. Dave must send a brief email to [email protected] or [email protected] or [email protected] requesting the renewal and giving an “academic use statement.” An example of the academic use statement is included in the materials delivered with the initial software package - it is on the second page of the Certificate of Support.

2) Get the installation CD from Dave and install the CD on a computer

3) Insert the Hasp Bitlock Key

4) Direct PETRA to the operating file listed above (call the PETRA help hotline for assistance if this step becomes overly complicated).

From this point, the program will be ready to use and data will be ready to analyze. The best way to learn the program will be a combination of experimentation, help guide reading, and hotline calling.

69 Important Functions

Map Making: from the main screen, select the desired wells and click “mapping” to display all the wells. Zoom according to data range.

Overlay files: turn these on and off to display things like county zones or production units. Create new files to define your own study area polygon or cordon off specific zones of the map.

Posted Data: display any relevant information under a well.

Attribute maps: create colored or scaled bubble maps or pie chart maps.

Contours: useful for isopach mapping or profiling any data feature.

Zones: A key feature of the program – this is where data is stored for each well. Add new zone items to add new data categories, which can later be mapped or analyzed.

FM Tops: specify an elevation as a “formation top” within a well and the program will connect it to any of the same tops in contiguous cross sections.

Cross Sections: select any number of wells in map view and click the “create cross section button” to display their logs side by side. The program will automatically connect any formation tops you have specified.