EVALUATING PETROLEUM SYSTEMS USING ADVANCED GEOCHEMISTRY AND BASIN MODELING
A DISSERTATION SUBMITTED TO THE DEPARTMENT OF GEOLOGICAL AND ENVIRONMENTAL SCIENCES AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
Meng He
May 2012
© 2012 by Meng He. All Rights Reserved. Re-distributed by Stanford University under license with the author.
This work is licensed under a Creative Commons Attribution- Noncommercial 3.0 United States License. http://creativecommons.org/licenses/by-nc/3.0/us/
This dissertation is online at: http://purl.stanford.edu/hb539ng7148
ii I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy.
Stephan Graham, Co-Adviser
I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy.
J. Moldowan, Co-Adviser
I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy.
Kenneth Peters
Approved for the Stanford University Committee on Graduate Studies. Patricia J. Gumport, Vice Provost Graduate Education
This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file in University Archives.
iii ABSTRACT
In the past decade, three-dimensional (3-D) basin and petroleum system modeling of the subsurface through geological time has evolved as a major research focus of both the petroleum industry and academia. The major oil companies have independently recognized the need for basin and petroleum system modeling to archive data, facilitate visualization of risk, convert static data into dynamic processed data, and provide an approach to evaluate potential prospects in oil and gas exploration. Basin and petroleum system modeling gives geoscientists the opportunity to examine the dynamics of sedimentary basins and their associated fluids to determine if past conditions were suitable for hydrocarbons to fill potential reservoirs and be preserved there. The success of any exploration campaign requires basin and petroleum system modeling as a methodology to predict the likelihood of success given available data and associated uncertainties. It is not guaranteed that hydrocarbons will be found by drilling a closed subsurface structure. Early petroleum system studies began more than 50 years ago. Geoscientists seek to describe how basins form, fill and deform, focusing mainly on compacting sediments and the resulting rock structures. Since then, tremendous efforts have been concentrated on developing methods to model these geological processes quantitatively. Studies such as applying mathematical algorithms to seismic, stratigraphic, palentologic, petrophysical data, and well logs were employed to reconstruct the evolution of sedimentary basins. In the early 1970s, geochemists developed methods to predict the petroleum generation potentials of source rocks in quantitative terms. After that, they began to use sedimentary basin models as geological frameworks for correlations between hydrocarbons and their potential source rocks. Since then, many concepts have been widely used in the petroleum industry, such as oil system, hydrocarbon system, hydrocarbon machine, and petroleum system. The term “petroleum system” is now commonly used in the industry. A petroleum system comprises a pod of active source rock and the oil and gas derived from it as established by geochemical correlation. The concept embodies all of the geologic elements and processes needed for oil and gas to accumulate. The essential elements include effective source rock, reservoir, seal and overburden rock. The
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processes include trap formation and the generation, migration and accumulation of petroleum. These elements and processes must occur in a proper order for the organic matter in a source rock to be converted into petroleum and then preserved. Absence of any of those elements can cause a dry prospect. In this dissertation, we use “basin and petroleum system modeling” (BPSM) as a method to track the evolution of a basin through geological time as it fills with sediments that could generate or contain hydrocarbons. We could also use it to evaluate and predict undiscovered conventional and unconventional hydrocarbon resources and to further understand the controls on petroleum generation, migration, accumulation. In deterministic forward modeling, basin and petroleum system processes are modeled from past to present using inferred starting conditions. Basin and petroleum system modeling is analogous to a reservoir simulation, but BPSM represents dynamic simulation through geological time. All of the dynamic processes in the basin and petroleum system modeling can be examined at several levels, and complexity typically increases with spatial dimensionality. The simplest is 1D modeling which examines burial history at a point location in a pseudowell. Two-dimensional modeling can be used to reconstruct oil and gas generation, migration and accumulation along a cross section. Three-dimensional modeling reconstructs petroleum systems at reservoir and basin scales and has the ability to display the output in 1D, 2D or 3D and through time. In general, which modeling approach is chosen depends on the purpose of the study and the types of problems to be resolved. Basin and petroleum system modeling continues to grow in importance as a tool to understand subsurface geology and basin evolution by integrating key aspects from geochemistry, geology, geophysics and stratigraphy. Among the above key aspects, geochemistry is the most important tool to understand the processes affecting petroleum systems. Better understanding of petroleum systems improves exploration efficiency. The first step in identifying petroleum systems is to characterize and map the geographic distribution of oil and gas types. Geochemical tools such as biomarkers, diamondoids and carbon isotope analysis are used to conduct oil-oil and oil-source correlation, which is key to understand and determine the geographic extent of petroleum systems in the basin.
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Chapter 1 offers a good example of how basin and petroleum system modeling and geochemistry improve understanding of active petroleum systems in the San Joaquin Basin, California. The modeling results indicate that there could be a deep, previously unrecognized source rock in the study area. Chapter 2 is a detailed unconventional geochemical analysis (i.e., diamondoid analysis, compound-specific isotopes of biomarkers and diamondoids) on petroleum systems in Arctic (Barents Sea and northern Timan Pechora Basin) to investigate deep sources in that area. Cutting-edge geochemical analyses were conducted in this project to identify the oil-oil and oil-source relationships and further understand reservoir filling histories and migration pathways. Since the deep source is at a great depth, thermal cracking always occurred in the source or the deeply buried reservoir, thus generating light hydrocarbons and gas. In addition, we hope to better understand the geochemical characteristics of worldwide Phanerozoic source rocks (Paleozoic source rock in Barents Sea-Timan Pechora area, Mesozoic and Cenozoic source rocks in the Vallecitos syncline in San Joaquin Basin). These results could also provide valuable input data for building basin and petroleum system models in the Arctic area once more data become available.
Chapter 1 is a study of using basin modeling and geochemical analysis to evaluate the active source rocks in the Vallecitos syncline, San Joaquin Basin, and improve our understanding of burial history and the timing of hydrocarbon generation. Our earlier 1D modeling indicated that there could be two active source rocks in the syncline: Eocene Kreyenhagen and Cretaceous Moreno formations. The results differ from earlier interpretations that the Kreyenhagen Formation was the only source rock in the Vallecitos syncline, and suggest that the bottom of the Cretaceous Moreno Formation in the syncline reached thermal maturity as early as 42 Ma. The synclinal Eocene Kreyenhagen Formation became thermally mature as early as 19 Ma. Thick (~2 km) overburden rock in the central part of the syncline with additional heating from a thermal anomaly pushed the shallow Eocene Kreyenhagen source rock into the oil window in very recent times. In contrast, the Cretaceous Moreno source rock reached extremely high maturity (past the dry gas window). The 2D model results indicate that the bottom part of the Kreyenhagen Formation is in the mature stage of hydrocarbon generation and that the
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formation remains immature on the flanks of the present-day syncline. In contrast, the bottom part of the Moreno Formation achieved the gas generation zone and is in the oil generation zone on the flanks of the syncline. Biomarker analysis was conducted on 22 oil samples from the syncline. Source-related biomarkers show two genetic groups, which originated from two different source rocks. The 2D model results are supported by biomarker geochemistry and are also consistent with our earlier 1D burial history model in the Vallecitos syncline. In addition, we identified two potential petroleum systems in the Vallecitos syncline. The basin models for this study were conducted by me and Stephan Graham, Allegra Hosford Scheirer, Carolyn Lampe, Leslie Magoon. The detailed geological data was provided by Stephan Graham. The modeling related references and fundamental data were provided by Allegra Hosford Scheirer, but I conducted the modeling. The geochemical laboratory work and data analysis has been completed by me and supervised by Mike Moldowan and Kenneth Peters. The funding for this project was contributed by Basin and Petroleum System Modeling (BPSM) and molecular organic geochemistry industrial affiliates (MOGIA) programs. This chapter was submitted to Marine and Petroleum Geology with co-authors Stephan Graham, Allegra Hosford Scheirer and Kenneth Peters. All co-authors contributed important ideas, discussion, and guidance.
Chapter 2 documents the existing deep source in the Barents Sea and northern Timan-Pechora Basin. Total thirty-four oil samples were analyzed to understand the types and distributions of effective source rocks and evaluate the geographic extent of the petroleum systems in the study area. Taxon-specific, age-related and source–related biomarkers and isotope data provided information on the depositional environment of the source rock, source input, and source age of the oil samples. A relationship between biomarker and diamondoid concentration was used to identify mixed oils having both oil- window and highly cracked components. Compound-specific isotope analyses of diamondoids and n-alkanes were used to deconvolute co-sourced oils and identify deep source rocks in the basin. The results suggest five major source rocks in the Barents Sea and the northern Timan-Pechora Basin: Upper Jurassic shale, Lower-Middle Jurassic shale, Triassic carbonate/shale, Devonian marl and Devonian carbonate. The Upper and
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Lower-Middle Jurassic source rocks are dominant in the Barents Sea. Triassic source rock consists of carbonate in the onshore part of northern Timan-Pechora Basin and marine shale in the Barents Sea. The Devonian Domanik Formation carbonate source rock extends offshore into the southern Barents Sea. High-maturity Domanik Formation could also be a secondary source rock for most of the mixed oils in the northern Timan- Pechora Basin. The geochemical laboratory work and data was completed by me and supervised by Mike Moldowan and the staff in the Molecular Organic Geochemistry Laboratory at Stanford University. The oil samples and location data were generously provided by Alla Rovenskaya in Russia. The chemometric analysis was conducted by Kenneth Peters, who provided valuable comments and revisions on the paper. The funding for this project was contributed by the Molecular Organic Geochemistry Industrial Affiliates (MOGIA) program. This chapter was published in American Association of Petroleum Geologists Bulletin in June, 2012, with co-authors Mike Moldowan, Alla Rovenskaya, and Kenneth Peters. All co-authors contributed significantly to the ideas, discussion, and scientific interpretations.
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ACKNOWLEDGEMENTS
This research would not have been possible without the help of many people that contributed in different ways. First and foremost, I would like to thank one of my advisors, J. Michael Moldowan, for giving me the opportunity to come to Stanford University for my Ph.D. study. Over the past five years, I strongly benefited from his kindness, advice, and support of my research and graduate study. Mike brought me to the fantastic world of organic geochemistry and made me fall in love with diamondoids (nanometer-sized fragments of diamond). He is the best organic geochemist I have met in the world. He always offers me advice and insight in many different disciplines. And his office is always open and I can talk to him and discuss problems anytime. He greatly contributed to all aspects of my study. Second, I would like to thank my other advisor, Steve Graham. He gave me encouragement to continue my Ph.D. study in basin and petroleum modeling, and inspired me to apply geochemistry to understand sedimentary basins. He let me apply passionate approaches to solving the scientific problems. I would like to thank him for giving me an enormous amount of support, encouragement, and most importantly, his valuable time during my years at Stanford. Steve is a great teacher and awesome sedimentologist. I really learned a lot from him and know how to acheive a balance between the huge basin and nano-diamondoids. Kenneth Peters and Jeremy E. Dahl were amazingly helpful and supportive throughout my research at Stanford. Ken offered advice and comments on each project and was active in reviewing each paper I have written. Jeremy is an expert in diamondoids and he has tremendous influence on my diamondoids research. We always have interesting conversations each time when he visits my office and lab. He showed me many new applications of diamondoids and comments on my research. His scientific enthusiasm encouraged me to seek exciting findings in my research. Great thanks go to Allegra Hosford Scheirer and Leslie Magoon. Allegra and Les gave me so much support for my basin model of the San Joaquin Basin. Allegra is a fabulous geophysist and basin modeler. Thanks to her for all the data and materials needed to build my basin model of the San Joaquin Basin. She made this basin modeling project possible for me. We met very regularly to talk about the project, and her
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amazingly patience encouraged me to make progress on my project every week. Sometimes, her strict comments on my writing discouraged me a little in the beginning, but I realized the importance of that later and it has improved my academic writing a lot. This makes publishing journal papers possible for me. Les is a very interesting person, and he is also a key person for my research. He is very patient and takes everything slowly, in the order and precisely. He always is able to identify key highlights for my project and papers. His tremendous industrial experience strongly enhanced my research project in different ways. I would also like to thank our organic geochemistry lab manager Fred Fago and staff like Paul Lipton, Shawn Moldowan, Ye Wang, and David Zinniker. They were extremely helpful for all the lab work in this dissertation. Their passions for science and their attitude made for a relaxing and pleasant time in the lab. Fred and Paul were the key people for my research projects, and they helped me not only to solve the instrumental problems in the lab, but also to guide me in designing the experiments. They always patiently explained laboratory procedures to me. It was my great pleasure to work with them and I learned a lot from them. Before I move any further, it is worth it to spend some words on Basin and Petroleum Modeling group at Stanford. I have been so honored to be a member of BPSM. I enjoyed working with all the group members, including Tess Menotti, Blair Burgreen, Danica Dralus, Keisha Durant and Oliver Schenk, and discussing science with them. We worked closely like a family, and I do like this kind of feeling in our group. I enjoyed everyday I spent on campus because of the incredible people here. I was fully influenced by the academic environment inside the group and encouraged by sharing the resources at Stanford. I believe that graduate students at Stanford are one of the best resources. People left and joined since I joined the group, but the spirit and the energy has never left the group. I learned a lot from the interactions with them at Stanford. Ph.D. research study looks like a daunting task to most people. However, my experience was enhanced by everyone in the Department of Geological and Environmental Sciences (GES) at Stanford University. Special thanks go to the staff members of GES department and the dean’s office, especially Elaine Anderson, Alyssa
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Ferree, Arlene Abucay, Leslie Honda, Yvonne Lopez, Lorraine Sandoval and Cathy Piumarta. I really appreciate their help over the past five years. Stanford is an incredible place for doing research. It has the best libraries, best literature collections, and the most advanced technologies. Branner Library is the most amazing library for geosciences I have ever seen. All of the literature for my Ph.D. study was found in the library, and I received much help from the friendly staff members in the library. Research could not proceed without funding. I feel so lucky and honored to be supported by fellowships and research grants for my Ph.D. study at Stanford. I would like to thank the following funding for my Ph.D. study in the Department of Geological and Environmental Sciences: BP Graduate Fellowship, Shell Research Fund, Chevron Research Fellowship, Thomas D. and Janice H. Barrow Fellowship, AAPG Grant Award, A.I. Levorsen Research Fellowship, W.F. Detert Fellowship, and funding from the Basin and Petroleum Modeling (BPSM) and Molecular Organic Geochemistry Industrial Affiliates (MOGIA) programs. I would also like to thank the following energy companies who offered me incredibly valuable internships in the summers over the past five years: BP, PetroChina, StatoilHydro, ExxonMobil, and ConocoPhillips. Interesting summer internships allowed me to feel real life in the industry. It also helped me learn things that I could not acquire at school and decide the correct direction for my future career. Finally, I would like to thank my parents for supporting me and giving me lots of encouragement to finish my Ph.D. study in the United States. They always taught me to keep a motivated and passionate attitude in doing everything in my life. As we all know, a Ph.D. study is not only composed of several research projects; it is a story book of a five-year life. I learned all kinds of different things during these five years at Stanford. I enjoyed every second at Stanford. I believe that I will do much better after my graduation and use everything I learned during my Ph.D. study in my future career. I give my best wishes to everyone who helped me in the past five years, my friends, colleagues, and officemates at Stanford. They made my student life far richer by sharing their experience with me over the past five years.
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TABLE OF CONTENTS
ABSTRACT ...... iv ACKNOWLEDGEMENTS ...... ix TABLE OF CONTENTS ...... xii LIST OF TABLES ...... xv LIST OF FIGURES ...... xvi
CHAPTER 1: DEEP PETROLEUM OCCURRENCE IN THE VALLECITOS SYNCLINE, SAN JOAQUIN BASIN, CALIFORNIA: A BASIN MODELING AND ORGANIC GEOCHEMICAL STUDY ...... 1
ABSTRACT ...... 2 INTRODUCTION ...... 4 GEOLOGICAL AND TECTONIC SETTING ...... 6 PETROLEUM GEOCHEMISTRY ...... 11 Samples and methods ...... 11 Results and discussion ...... 14 Oil-oil correlation and geochemical characteristics of oil families ...... 14 Kreyenhagen oil family ...... 16 Moreno oil family ...... 18 Thermal maturity ...... 19 BASIN AND PETROLEUM SYSTEM MODELING ...... 19 NUMERICAL MODELING AND INPUT ...... 21 2D model input and burial history of source rocks ...... 23 Source rocks and kinetics...... 25 Calibration data ...... 27 MODELING RESULTS AND DISCUSSION ...... 29 CONCLUSIONS...... 34 ACKNOWLEDGEMENTS ...... 35
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REFERENCES CITED ...... 36 TABLES ...... 48 FIGURES ...... 54
CHAPTER 2: OIL FAMILIES AND THEIR INFERRED SOURCE ROCKS IN THE BARENTS SEA AND NORTHERN TIMAN-PECHORA BASIN, RUSSIA………………….73
ABSTRACT ...... 74 INTRODUCTION ...... 75 METHODS ...... 77 PETROLEUM GEOLOGY ...... 81 SOURCE ROCK GEOLOGY ...... 83 Upper Devonian (Domanik facies) ...... 83 Upper Pennsylvanian-Lower Permian ...... 84 Lower to Middle Triassic ...... 85 Upper Jurassic ...... 85 RESULTS AND DISCUSSION ...... 86 Oil-oil correlation and geochemical characteristics of oil families ...... 86 Family I ...... 88 Family II...... 89 Family III ...... 89 Family IV ...... 90 Family V ...... 91 Family VI ...... 91 Source rock interpretation from oil geochemistry ...... 92 Identification and de-convolution of the mixed oils and deep source interpretations ...... 94 Distribution of oil families and oil migration ...... 98 Thermal maturity ...... 100 CONCLUSIONS...... 101
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ACKNOWLEDGEMENTS ...... 102 REFERENCES CITED ...... 103 TABLES ...... 109 FIGURES ...... 113
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LIST OF TABLES
CHAPTER 1
Table 1: Oil samples by field, well ID, reservoir age, longitude, latitude, oil type and township ...... 48
Table 2: Geochemical parameters of oil samples in the Vallecitos syncline and the reference samples ...... 49
Table 3: Identification of labeled biomarker peaks shown in Figures 2a, 2b, and 2c...... 51
Table 4: General input data for 1D and 2D models ...... 52
Table 5: Boundary condition and model calibration data from well NETEX1 for 1D and 2D models...... 53
CHAPTER 2
Table 1: Oil samples by field, depth, reservoir age, and oil family ...... 109
Table 2: Geochemical parameters of oil samples in the Barents Sea and northern Timan-Pechora Basin...... 110
Table 3: Quantification of diamondoids (ppm) and biomarker (ppm), extent of oil cracking of the oil samples from the Barents Sea and northern Timan- Pechora Basin with CSIA-D data of the selected oil samples ...... 112
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LIST OF FIGURES
CHAPTER 1
Figure 1a. Sturctural map of the top of Kreyenhagen Formation and study area with the distribution of the oil samples in the Vallecitos syncline ...... 54
Figure 1b. Generalized outcrop geology of the westside San Joaquin Basin ... 55
Figure 1c. Generalized stratigraphic column of the Vallecitos syncline ...... 56
Figure 2a. Whole-oil gas chromatogram and 191 m/z ion mass fragmentogram for Kreyenhagen source rock extract and selected Kreyenhagen oil in Vallecitos...... 57
Figure 2b. Whole-oil gas chromatogram and 191 m/z ion mass fragmentogram for Moreno end-member oil and selected Moreno oil in Vallecitos ...... 58
Figure 2c. Whole-oil gas chromatogram and 217 m/z ion mass fragmentogram for Kreyenhagen source rock extract, Moreno end-member oil, and selected Kreyenhagen and Moreno oil in Vallecitos ...... 59
Figure 3. PCA for all oil samples and seeps in our dataset based on selected biomarker and isotope ratios ...... 60
Figure 4a. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oils using different biomarkers ...... 61
Figure 4b. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oils using different biomarkers ...... 62
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Figure 4c. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oils using different biomarkers ...... 63
Figure 4d. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oils using different biomarkers ...... 64
Figure 5a. Plot of time versus vitrinite reflectance of the two source rocks for the model at 1D location ...... 65
Figure 5b. Burial history curves with transformation ratio of two source rocks for the model at 1D location ...... 66
Figure 6. Geological profile along the line GH in the Vallecitos syncline ...... 67
Figure 7a. Plot of calculated and measured % Ro versus depth for the models with three different heatflow scenarios ...... 68
Figure 7b. Plot of calculated and measured % Ro versus depth for the model...... 69
Figure 8. Modeled present-day thermal maturity of source rocks expressed as vitrinite reflectance in the 2D model ...... 70
Figure 9a. Events chart for the Kreyenhagen-Yokut(.) petroleum system shows the time of deposition of the essential elements and processes of this petroleum system...... 71
Figure 9b. Events chart for the Moreno-San Carlos(.) petroleum system shows the time of deposition of the essential elements and processes of this petroleum system...... 72
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CHAPTER 2
Figure 1a. Location map for Barents Sea and Timan-Pechora Basin shows identified oil families ...... 113
Figure 1b. Location map for Timan-Pechora Basin shows identified oil families ...... 114
Figure 2a. HCA for thirty-four oil samples based on twenty biomarkers and two stable carbon isotope ratios ...... 115
Figure 2b. PCA for thirty-four oil samples based on twenty biomarkers and two stable carbon isotope ratios ...... 116
Figure 3a. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family I and II oils ...... 117
Figure 3b. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family III and IV oils...... 118
Figure 3c. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family V and VI oils ...... 119
Figure 4. Comparison of compound-specific isotope analysis of n-alkanes in selected oil samples from each identified oil family in the Barents Sea and northern Timan-Pechora Basin ...... 120
Figure 5. Schematic relationship between concentrations of methyldiamantanes and stigmastane for oil samples from the Barents Sea and northern Timan- Pechora Basin...... 121
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Figure 6. Comparison of compound-specific isotope analysis of diamondoids in selected oils from each identified oil family in the Barents Sea and northern Timan-Pechora Basin ...... 122
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CHAPTER 1
DEEP PETROLEUM OCCURRENCE IN THE VALLECITOS SYNCLINE, SAN
JOAQUIN BASIN, CALIFORNIA: A BASIN MODELING AND ORGANIC
GEOCHEMICAL STUDY
1 Deep Petroleum Occurrence in the Vallecitos Syncline, San Joaquin Basin,
California: A Basin Modeling and Organic Geochemical Study
Meng He1, Stephan Graham1, Allegra Hosford Scheirer1, Kenneth E. Peters1,2,
1. Stanford University, Department of Geological & Environmental Sciences, Stanford,
CA, 94305, USA
2. Schlumberger, 18 Manzanita Place, Mill Valley, CA, 94941, USA
ABSTRACT
The Vallecitos syncline is a westerly structural extension of the San Joaquin Basin.
The Vallecitos oil field, comprised of eight separate areas that produce from Cretaceous
and Paleogene reservoirs, accounted for 5.4 MMB of oil and 5.6 BCF associated of gas
through 2010. However, exploration for oil and gas in the Vallecitos area is challenging due to structural complexity and limited data. The purpose of this study is to evaluate whether source rocks are active for petroleum generation in the Vallecitos syncline and improve our understanding of burial history and timing of hydrocarbon generation. We conducted biomarker analysis on twenty-two oil samples from the Vallecitos syncline.
Source-related biomarkers show two genetic groups, which originated from two different source rocks. In addition, our initial 1D modeling indicated that there could be two thermally mature source rocks in the syncline: Eocene Kreyenhagen Formation and
Cretaceous Moreno Formation. The modeling results are consistent with our
2 geochemistry results for the oil samples. These results differ from earlier published interpretations that the Kreyenhagen Formation is the only source rock in the Vallecitos syncline, and suggest that the base of the Cretaceous Moreno Formation in the syncline reached thermal maturity as early as 42 Ma. The synclinal Eocene Kreyenhagen
Formation became thermally mature as early as 19 Ma. Thick (~ 2 km) overburden rock
in the central part of the syncline with additional heating due to a thermal anomaly pushed structurally shallower Eocene Kreyenhagen source rock into the oil window in very recent times. In contrast, the Cretaceous Moreno source rock reached extremely high maturity (past the dry gas window).
To better understand the petroleum systems and clarify the total active source rocks in the area, 2D burial histories were generated through the Vallecitos syncline. A
2D line along a published cross-section through the deepest part of the syncline was selected to conduct thermal history, basin evolution, and migration analyses.
Stratigraphic evidence and modeling suggest that several recent episodes of erosion due to folding and uplift removed significant overburden on the flanks of the syncline. The
2D model results indicate that the lower Kreyenhagen Formation has various maturities within the formation at different locations in the present-day syncline. The basal part of the Kreyenhagen Formation is in the dry gas window and the maturity decreases away from the central part to the flanks. It remains immature in the very shallow part of the present-day flanks. In contrast, the basal part of the Moreno Formation has achieved extremely high maturity (past the gas generation zone) and is in the oil generation zone on the flanks of the syncline at shallow depth. All of our geochemical, 1D and 2D model
3 results suggest that there are two active source rocks in the Vallecitos syncline.
Accordingly, we identified two potential petroleum systems in the Vallecitos syncline.
Keywords: basin and petroleum system modeling, burial history, calibration, oil family, oil-window maturity, oil-oil correlation, biomarker, Kreyenhagen, Moreno, Vallecitos syncline
INTRODUCTION
A calibrated 3D basin and petroleum system model through time (4D) for the San
Joaquin Basin Province of California was published by Peters et al. (2008). They used the stratigraphy determined from seismic and well log data as key input for their model. A simplified model was used where geologic layers were described as chronostratigraphic rather than lithologic units in the San Joaquin Basin. This basin contains several effective petroleum source rocks. Inexpensive geochemical screening of the source rock samples was completed using Rock-Eval pyrolysis and TOC (total organic carbon) measurements.
There are two major effective source rocks in the San Joaquin Basin: shale of the
Miocene Monterey Formation and Eocene Kreyenhagen Formation. Two minor source rocks include Eocene Tumey Formation and Cretaceous Moreno Formation. These source rocks are now at or near their maximum burial depth in parts of the basin (Peters et al., 2008).
The Vallecitos area is located on the western side and within the San Joaquin
Basin (Fig. 1a). Petroleum exploration in the Vallecitos area commenced in the late
4 1880’s. Drilling activity increased significantly thereafter (Wilkinson, 1960). By the end
of 1959, the Vallecitos field comprised eight separate producing areas (Griswold Canyon,
Franco, Cedar Flat, Ashurst, Silver Creek, Pimental Canyon, Central, and Los Pinos
Canyon) (Fig. 1a), and had produced approximately 2.2 MMB of oil and 1.5 BCF of gas
from Cretaceous and Paleogene reservoirs (Wilkinson, 1960). Cumulative oil and gas
production through 2010 in the Vallecitos area reached 5.4 MMB of oil and 5.6 BCF of
gas, respectively (CDOGGR, 2010). The Antelope shale, a member of the Monterey
Formation that produces oil prolifically in the southern San Joaquin Basin (Graham and
Williams, 1985), is absent in the Vallecitos area, implying that the Eocene Kreyenhagen
Formation is the only active source rock in the syncline according to the USGS in 2008
(Lillis and Magoon, 2008). However, our initial 1D model and geochemical results
indicate that there are two possible source rocks in the Vallecitos syncline: the
Cretaceous Moreno Formation and the Eocene Kreyenhagen Formation (He et al., 2010).
The objective of this study is to evaluate the organic matter content, type and thermal
history of the active source rocks, and petroleum systems in the Vallecitos syncline by
using basin modeling and organic geochemistry and further, to incorporate the results
into basin modeling in order to determine the timing of hydrocarbon generation. Maturity
information from well cores was used to calibrate the model. Burial history, thermal
maturity, and timing of hydrocarbon generation and expulsion were simulated in both our
1D model based on the deepest composite pseudo-well in the syncline and a 2D model
based on a published cross-section through the deepest part of syncline.
This study has implications for understanding petroleum systems in the Vallecitos
syncline. A detailed biomarker study has never been applied to this area. Such a detailed
5 geochemical study has advantages for establishing oil-oil correlations, suggesting the effective source rocks of the region, and improving previous understanding. This work provides input data that could be used for a future 3D model of the basin. In particular, the biomarker analysis helps to understand the origin of different oil types in the
Vallecitos syncline and the regional oil and gas distribution. Maps of oil and gas distributions are needed to accurately model the petroleum systems in the Vallecitos syncline and the possible flowpaths for the oil and gas migration. This work improves the previous USGS model and reduces risk for future oil and gas exploration in the Vallecitos syncline (Peters et al., 2008).
GEOLOGICAL AND TECTONIC SETTING
The Vallecitos syncline is four miles wide and fifteen miles long and is located in the southeastern part of San Benito County (Fig. 1a). It is one of the prominent echelon fold sets that characterize the west side of the San Joaquin Basin (Harding, 1976) (Fig.
1a). It is a part of the San Benito trough, which is recognized as a Tertiary seaway that connected the San Joaquin Valley area with the Pacific Ocean to the west (Clark, 1930;
Reed, 1938; Mielenz, 1939; Hoots et al., 1954; Dibblee, 1973). The San Benito trough is currently expressed as a relatively small intermountain valley whose floor has an average elevation of 0.6 km (~2000 feet).
The Vallecitos syncline is one of the folds formed on that homocline as a result of right lateral transpression and ensuing strike-slip deformation along the San Andreas fault
(e.g., Graham, 1987) (Fig. 1b). Mesozoic and Cenozoic marine sediments in the syncline
6 were deposited in a forearc basin setting with a thickness of about 9 km (Clark, 1930;
Miller, 1998). The syncline is structurally underlain by Mesozoic accretionary complex assigned to the Franciscan complex (Bailey, 1960; Page, 1981; Wahrhaftig, 1984;
Graham, 1987) (Fig. 1b). The Vallecitos area was mostly filled with marine sediments
(Donald, 1959; Anderson, 1998). Detritus from the Sierra Nevada was deposited in the
Great Valley forearc basin in Mesozoic time (Ingersoll, 1979). The Upper Jurassic through Cretaceous deposits with a thickness of 6-8 km are exposed in a homocline on the eastern flanks of the Diablo Range (Dickinson et al., 1979) (Fig. 1b). The record of mid-Cretaceous events is absent, but marine sedimentation resumed with deposition of the Panoche Formation (Campanian and Maastrichtian), although it may have been stripped from the northern part of the area before deposition of the Moreno Formation
(Enos, 1961) (Fig. 1c). Above these strata is a gradually shoaling upward succession of
Cenozoic deposits (Dibblee, 1981; Bartow, 1991). Deep water marine, organic-rich shaly source rocks and turbidite sandstones characterize Paleogene strata of the Vallecitos syncline (Fig. 1c). As a structurally confined seaway, stratigraphic relationships among
Eocene formations vary greatly over short distances, and this complicates correlation between the Vallecitos and the San Joaquin Valley (e.g., Graham and Berry, 1979;
Schulein, 1993).
The Moreno Formation (youngest Cretaceous unit –Maastrichtian in the area) is an upper Cretaceous through lower Tertiary (middle Maastrichtian through middle
Paleocene) sequence of marine sediments distributed throughout the west-central San
Joaquin Basin of California. Facies sequences within the formation contain the following elements: base-of-slope turbidite and channel sandstone facies; oxygen-deficient lower to
7 middle slope shale facies; upwelling-related anoxic upper slope diatomaceous shale
facies; and upper slope to outer shelf sandstone and shale facies (McGuire, 1988). Hence,
the Moreno Formation records the shoaling of the south-central portion of the Great
Valley forearc basin to shelf depths during latest Cretaceous to early Tertiary time
(McGuire, 1988).
The earliest manifestation of the Vallecitos syncline as a structural feature and a
distinct depositional sub-basin is found in Paleocene-lower Eocene Cantua Sandstone
member of the Lodo Formation (Anderson and Pack, 1915; Graham and Berry, 1979).
The present-day outcrop pattern suggests that a structural and bathymetric trough existed
during Paleocene through middle Miocene time (Wilson, 1943; Dibblee, 1973) (Fig. 1b).
The Paleocene Lodo Formation includes shale, mudstone, and sandstone that locally reach 1.25 km thick. These units are interpreted to have been deposited at water depths between 0.5-2 km by turbidity currents (Graham and Berry, 1979; Moxon, 1988). A study by Dibblee and Nilsen (1974) discarded the terms Martinez and Arroyo Hondo
Formations, re-adopted the name Lodo Formation, and subdivided it by lithology to include the Unnamed sandstone (San Carlos), the Cerros Shale, the Cantua Sandstone, and the Arroyo Hondo Shale members (Dibblee and Nilsen, 1974) (Fig. 1c). The San
Carlos Sandstone is a product of turbidity current deposition in a relatively channel-poor submarine fan or perhaps within a low aspect ratio of a channel system (Dibblee and
Nilsen, 1974). The Cerros Shale accumulated relatively slowly by hemipelagic/pelagic sedimentation, and probably represents deposition during a relative sea-level highstand during which coarse-grained siliciclastic sediment was largely restricted to the shelf
(McGuire, 1988). The Cantua Sandstone was deposited by high- and low-density
8 turbidity currents (Fig. 1c). The sediment was fed through Cantua Canyon, which was a
sediment transport conduit from the volcanic/meta-/magmatic Serrian Nevada arc
(Anderson, 1998). The Arroyo Hondo shale represents a transition from dominantly
siliciclastic to increasingly hemipelagic sediments and the latest stage of basin shoaling
(Anderson, 1998). Overall, the sandy units of the Cantua Sandstone record upward
shoaling (Anderson, 1998).
The overlying Domengine and Yokut Sandstone could have multiple source
terranes and were deposited in transgressive and regressive marine environments,
respectively (Schulein, 1993). The Kreyenhagen Formation was deposited on a deep marine slope (Milam, 1985). It consists mainly of biosiliceous shale that is a thick
organic-rich source rock in the Vallecitos syncline, but it also includes a deep-water
turbidite sandstone facies. Oligocene events are missing and probably were never
deposited in the Vallecitos syncline, although Oligocene rocks exist in the southernmost
San Joaquin Basin (Bartow, 1991). Neogene sedimentation in the Vallecitos area was
strongly controlled by the growing Joaquin Ridge and Cerro Benito anticlinal uplifts, as
well as the subsiding Vallecitos syncline (Rentschler, 1989). The Miocene Temblor
Formation was deposited in a shallow marine environment (Rentschler, 1989). There is
no record of Late Miocene deposits (Bartow, 1991) because the Vallecitos area emerged
from the sea at this time. As much as 2.1 km (7000 feet) of sediment accumulated in this
trough during Pliocene time (Dibblee, 1981). After Pliocene time, the Vallecitos area
remained nonmarine and likely hosted a lacustrine environment in an intermontane basin
(Bowersox, 2004). The Vallecitos syncline was an isolated, structurally controlled
9 nonmarine depocenter in the late Neogene as indicated by folded post-upper Luisian lacustrine sediments (Rentschler, 1985).
The Vallecitos syncline has a complex tectonic history due to its location at the western margin of North America where a subduction zone existed throughout the
Cenozoic. The Paleogene in California represents a transitional period between the
Mesozoic Andean-style convergent margin setting and the Neogene transform setting
(Graham, 1987; Bartow, 1991). The syncline likely initiated as a discrete feature in the
Paleocene, as suggested by the distribution of the Cantua Sandstone (e.g., Graham and
Berry, 1979). Major uplift occurred near the syncline, while subsidence in the syncline dominated the Cenozoic Era (Bartow, 1991). The Mendocino Triple Junction migrated northwestward past the Vallecitos area in the mid-Miocene, inducing a wave of extensional tectonism in nearby regions (Dickinson and Snyder, 1979; Ingersoll, 1979).
Initial folding was pre-late Saucesian, and continued uplift is reflected in the deposition of the Temblor Formation (Rentschler, 1985). The main folding of the Vallecitos syncline occurred between the early Miocene and middle Pliocene (Bartow, 1991). In summary, a complex history of erosion, uplift and sedimentation in the Vallecitos syncline resulted in petroleum-producing structural traps in the Vallecitos oil field. Cenozoic strata in the
Vallecitos syncline contain petroleum, although they are buried less than 1.5 km
(Rentschler, 1985).
The Vallecitos area underwent local volcanism in the Tertiary. An episode of volcanism occurred in the late Miocene and volcanic rocks were deposited on the eroded surface of deformed pre-Tertiary rocks near the Vallecitos area. This volcanic activity was followed by another episode of uplift and erosion of both the central and southern
10 Diablo uplifts in the beginning of Pliocene time. Local basaltic eruptions continued farther to the southeast from the central Diablo range (Dibblee, 1981). Southwest of the
Panoche Valley, a few kilometers northwest of the Vallecitos syncline, flat-lying basalt and basaltic andesite unconformably overlie the folded rocks of the Franciscan Complex and the Great Valley Group with a thickness of about 0.6 km (~2000 feet) (Dibblee, 1981)
(Fig. 1b). Those volcanic rocks have been radiometrically dated about 10 Ma or late
Miocene (Prowell, 1974). In addition, the upper part of the Pliocene sequence is composed of serpentine mudstone derived from the serpentinite of Joaquin Ridge to the south in the Vallecitos syncline. The largest and most extensive mass of serpentinite is that which forms most of the core of the Coalinga anticline of Joaquin Ridge about 5 km south of the Vallecitos syncline (Dibblee, 1981).
PETROLEUM GEOCHEMISTRY
Samples and methods
A total of twenty-two black oil samples, two oil seeps, and one gas condensate covering most of the syncline were selected for this study (Fig. 1a). Some well studied samples and end member oil samples of Kreyenhagen and Moreno shales were also used for comparison and oil-oil correlation. One Kreyenhagen source rock extract (SJ121) was included in this study to confirm the origin of oil from the Kreyenhagen source rock.
Sample SJ122 is considered to be the end member oil from Kreyenhagen source rock as well as one sample SJ119 from Big Tar Canyon near the Coalinga oil field (Fig. 1b).
Sample SJ118 is believed to be the end member oil from Moreno source rock in Oil City,
11 which has also been well studied in the literature (Peters et al., 1994; Lillis and Magoon,
2008) (Table 1; Fig. 1b). In addition, source rocks extracts from the Kreyenhagen
Formation, end member oil from Kreyenhagen Formation, and Moreno sourced oil from outside of the Vallecitos syncline were included in this study to be compared with oil samples from the Vallecitos syncline.
The chemical composition of oil is directly determined by the type of organic matter and the depositional environment of source rocks (Tissot and Welte, 1984). Oil chemistry is widely used to predict the character of the source rocks (Peters et al., 2005).
Gas chromatography (GC) and gas chromatography mass spectroscopy (GC-MS) of the oil and bitumen extract samples (Fig. 2a, 2b & 2c) were used in this study.
Compared with most bulk geochemical parameters, source-related and age-related biomarker ratios for oil samples are particularly useful to describe facies and depositional environment of the source rock, while also successfully establishing oil-oil and oil-source rock correlations. Biomarkers in oil samples can be applied to infer depositional environment, organic facies, thermal maturity and even the age of the source rock (Peters et al., 2005). These data can be extremely helpful in oil-oil correlation studies.
To increase the accuracy of biomarker analysis, a series of separations was conducted before the analysis. First, silica-gel chromatography was applied to separate the oil or extract into saturates and aromatics. Second, the zeolite ZSM-5 was used to remove normal alkanes (n-alkanes or paraffins) from the saturate fraction. Before removing normal alkanes, the saturate fractions were spiked with internal standards. For this project, a mixture of 5β-cholane and highly branched isoprenoids (HBI) having the m/z 238 mass spectral fragment were added to the saturates as an internal standard before
12 gas chromatography-mass spectrometry (GC/MS) (Seifert and Moldowan, 1979).
Saturate fractions were treated with high Si/Al Z5M-5 zeolite (silicalite) to remove n- alkanes. All of the crude oil samples were quantitatively analyzed by gas chromatography-flame ionization detection (GC-FID). The biomarkers (e.g., terpanes, steranes, aromatic steroids) in the branched, cyclic, and aromatic fractions were analyzed by selected ion recording-gas chromatography mass spectrometry (SIR-GCMS).
Chemometric analysis was used to classify and assign confidence limits for identifying genetic oil families in the Vallecitos syncline. Chemometrics is a collection of multivariate statistical methods for recognizing patterns in large data sets. It allows us to identify and remove noise from the data, show affinities among samples or parameters, and make accurate predictions about unknown samples. Principal components analysis
(PCA) is one common technique in chemometric analysis. For the chemometric analysis, we selected twenty-five biomarkers (Table 2) based on our geochemical expertise to differentiate oil families in terms of age, organic input and depositional environment of the source rocks. PCA was completed using Pirouette (Infometrix, Inc., Bothell, WA).
PCA reduces the dimensionality of the data set, while retaining most of the information in the data set. It transfers a number of possibly related variables into a smaller number of uncorrelated variables, the principal components (Fig. 3). This transformation retains the structural relationships underlying the data. The first three principal components generally describe most of the variance within the dataset. Three-dimensional plots that differentiate families are built by using the first three principal components as axes to generate the best three-dimensional separation of the samples into genetic families (Fig.
3).
13 Results and discussion
Most of the oil samples are non-biodegraded and a few show slight biodegradation. One condensate and three oil seeps that are severely biodegraded are in the oil collection for this study. Twenty-five source- and depositional environment- related biomarkers were used to construct the PCA plot (Fig. 3). The two identified oil families have broadly similar geochemical characteristics, but could originate from different source rocks or different organofacies (Jones, 1987) of the same source rock. In addition to genetic information, age, lithology and depositional environment of the source rock can be inferred from the detailed biomarker study, as discussed below. Two oil families were defined and are shown in the PCA plot (Fig. 3; Table 2). The two outliers in the PCA plot are biodegraded oil seeps from Big Tar Canyon (SJ119) and Vallecitos syncline (SJ131). The Eocene Kreyenhagen source rock extract (SJ121) clustered with inferred Kreyenhagen sourced oils. Sample SJ118 considered to be the end member oil from Moreno source rock, clustered with the inferred Moreno sourced oil in the
Vallecitos syncline (Fig. 3).
Oil-oil correlation and geochemical characteristics of oil families
Biological markers (biomarkers) are complex molecular fossils derived from once-living organisms (Peters et al., 2005). Biomarkers in crude oil inherit the recognizable carbon structures of natural products synthesized by precursor organisms.
Different assemblages of organisms live in different source rock depositional environments. Therefore, various biomarker parameters can be used to evaluate the depositional environment of the source rock. Biomarkers can be measured in both oil and source-rock extract samples, and they are helpful in oil-to-source rock correlation (Peters
14 et al., 2005). In fact, biomarkers provide a method to interpret source rock organofacies
when only oil samples are available. Biomarker fingerprints are primarily established by
the source of organic matter and depositional environment, but the overprint of
maturation is also important. Thus, numerous biomarker parameters should be taken into
consideration in order to strengthen detailed correlations.
We define a genetic oil family in this paper as a group of oil samples that were
generated and expelled from a single source rock organofacies. Some oil samples may
show evidence of mixing, but are dominated by input from only one major source rock.
Variations in oil characteristics due to maturity or post-expulsion alteration processes,
such as biodegradation and phase separation, should not alter genetic relationships.
Representative gas chromatograms and terpane mass chromatograms for each oil family
are shown in Fig. 2a, 2b, & 2c. Key biomarker and non-biomarker parameters used in this
study to differentiate oil families include pristane/phytane (Pr/Ph), C29/C30 hopane, and
C35/C34 homohopane, the distribution of C27, C28, and C29 steranes, and age-related biomarker ratios, such as the extended tricyclic terpane ratio (ETR) and triaromatic dinosteranes/(3-methystigmastane 20R) (Table2). Maturity-related biomarker ratios, such as C29 20S/ (20S+20R), C29 ββ/ (ββ+αα), and Ts/ (Ts+Tm), were also examined in this
study. Pr/Ph ratio is used as an indicator of oxicity of the water column during a given
source rock deposition (Tissot and Welte, 1984). Although higher ratios may reflect
terrigenous plant input, maturity can also increase this ratio (Mackenzie, 1984). Philp
(1994) noted that only Pr/Ph greater than four may be taken as an indicator of oxic
depositional environment. Pr/Ph ratios less than one is still widely used in the literature as
an indicator of anoxic depositional environments, whereas, Pr/Ph greater than three
15 indicates a suboxic to oxic depositional environment (Mello et al., 1988). Pr/Ph between
1.25 and 2.13 could indicate anoxic to suboxic water column at the site where the source
rock was deposited.
Key biomarker parameters used to distinguish different oil families are
summarized in Table 2 and details of the biomarker parameters that characterize each oil
family are described below:
Kreyenhagen oil family
Fourteen oil and two oil seep samples in our dataset originated from the
Kreyenhagen Formation. The samples in this family are characterized by 2.2 (Fig. 2a), which typically denotes a suboxic to oxic source rock depositional environment. The samples have relatively low ratios of pristane to n-C17 and phytane to n-C18. The distribution, relative abundance, and stereochemistry of pentacyclic terpanes obtained from m/z 191 ion chromatograms are shown in Fig. 2a, 2b, & Table 3, and the derived parameters are in Table 2. Tricyclic terpanes usually occur in small amounts (maximum 5- 10% of C30 hopane). Samples in this family have low tricyclic terpane concentrations, indicating little terrigenous organic matter input. In addition, low tricyclic terpanes in the Kreyenhagen oil and Kreyenhagen source rock extract samples support an oil-source rock correlation for those samples. Significant 18α (H)-oleanane and 18β (H)- oleanane (generally coeluting with 18α (H)-oleanane) in this family (as oleanane content usually 5-10% of C30 hopane) indicates some terrigenous organic matter input from angiosperms, and suggests an Upper Cretaceous or Tertiary source rock (Moldowan et al., 1994). C29 hopane is less than C30 hopane (C29/ C30< 0.6), which could indicate a clay-rich source rock (shale). According to Mello et al. (1988), Ts/Tm below unity 16 indicates a saline environment, whereas Ts/Tm above unity indicates a brackish to fresh water environment. Homohopane distributions were widely used to assess source rock redox conditions and also can be used for correlation. When the concentration of extended homohopanes C31 to C35 decreases with poor preservation of C35 homohopane, this indicates a suboxic to oxic open marine environment. C29 25-norhopane/Ts 18α (H)- norneohopane in this family is greater than one. In addition, C29normoretane/18α (H)- oleanane is less than one (Fig. 2a). The distribution and relative abundances of steranes as well as their stereochemistry was obtained from m/z 217 ion chromatograms shown in Fig. 2c and Table 3, and derived parameters are listed in Table 2. Source and maturity related parameters in this study includes ααα 20R isomers of C27- C28-C29 steranes and diasteranes. High diasteranes indicates a clay-rich source rock (shale). Sterane ternary diagrams are used extensively to show relationships between oils and/ or source rock bitumen (Peters et al., 2005). The principal use of sterane ternary diagrams is to distinguish groups of crude oils from different source rocks or different organic facies of the same source rock. In addition, monoaromatic steroid ternary diagrams are more useful to distinguish petroleum based on the depositional setting of the source rock (Moldowan et al., 1985). On both of sterane ternary diagrams, Kreyenhagen sourced oil samples in the Vallecitos syncline cluster near the area defined by marine shale on ternary plot from Moldowan et al. (1985) (Fig. 4a & 4b). The inferred Kreyenhagen sourced oil is well correlated with Kreyenhagen source rock extract on the sterane ternary diagrams. Several plots of selected saturate and aromatic biomarker parameters, such as extended tricyclic terpanes (ETR), oleanane index, TA-Dino/ (TA- Dino+3-methylstigmastane 20R) (i.e., TA-Dino=C29 triaromatic dinosteranes), and TA 3- 17 / (3- + 4-methylstigmastane 20R), indicate that Kreyenhagen sourced oil is well separated from Moreno source oil (Fig. 4c & 4d). Moreno oil family Eight oil samples originated from the Moreno Formation in the Vallecitos syncline. This family is characterized by 1.6 suboxic water column at the site where the source rock was deposited. The samples have relatively high ratios of pristane to n-C17 and phytane to n-C18 (>2) (Fig. 2b). Samples in this family have low tricyclic terpane concentrations, indicating terrigenous organic matter input. In addition, low tricyclic terpanes in the Moreno samples from the Vallecitos syncline and Oil City oil (Fig. 1b) support an oil-oil correlation for those samples. Very low 18α (H)-oleanane and 18β (H)-oleanane in this family could also indicate little terrigenous organic matter input. C29 hopane is less than C30 hopane (C29/ C30< 0.4), which could indicate a clay-rich source rock (shale). In addition, high concentrations of diasteranes also suggest a clay-rich source rock. Concentration of extended homohopanes C31 to C35 decreases with poor preservation of C35 homohopane, indicating a suboxic to oxic open marine environment. C29 25-norhopane/Ts 18α (H)- norneohopane in this family is much less than one. In addition, C29normoretane/18α (H)- oleanane is also greater than one (Fig. 2b). On both of the sterane ternary diagrams, Moreno family samples cluster near the area defined by marine shale on the ternary plot from Moldowan et al. (1985) (Fig. 4a & 4b). The inferred Moreno samples correlate with the Oil City oil on the sterane ternary diagrams, which is believed to be from Moreno source rock (Peters et al., 1994; Lillis and Magoon, 2008). The distribution of C27 αα20R cholestane, C28 αα20R ergostane and C29 αα20R stigmastane of the Kreyenhagen and 18 Moreno samples are clearly distinguished on Fig. 2c ( peak ID 10, 16 and 20 in Table 3) and Fig. 4b. Thermal maturity Maturity of the samples was assessed using the following parameters: C29 sterane isomerization ratios C29 ααα 20S/(S+R), and C29 αββ 20(S+R)/(αββ+ααα) 20(S+R); Ts/ (Ts+Tm), TA [C20/ (C20+C28 20R)] and TA (I)/TA (I+II). The isomerization ratio at the C-20 position (20S/20S+20R) in the C29 ααα steranes, which is theoretically zero at the depositional surface, increases with thermal maturity, reaching the endpoint value of about 0.55 at peak oil generation. The αββ-iso steranes relative to ααα-normal steranes ratio increases with maturity, reaching an endpoint at ~ 0.75 (Mackenzie, 1984; Grantham, 1986). The Kreyenhagen family has C29 20S/ (20S+20R) sterane ratios of 0.3- 0.4 and C29 ββ/ (ββ+αα) 20R sterane ratios of 0.11-0.44, indicating early oil-window maturity (Table 2). Ts/ (Ts+Tm), TA (I)/TA (I+II), and TA [C20/ (C20+C28, 20R)] for the Kreyenhagen family (~43%, ~7%, and ~16%, respectively) also support this conclusion. The Moreno family mostly has typical oil-window maturity and some samples have early oil window maturity. C29 20S/ (20S+20R) for this family is ~0.32, and C29 ββ/ (ββ+αα) 20R is ~0.35. Ts/ (Ts+Tm), TA (I)/TA (I+II), and TA [C20/ (C20+C28, 20R)] for Moreno family (~42%, ~8%, and ~26%, respectively) are also consistent with this conclusion. BASIN AND PETROLEUM SYSTEM MODELING In the past decade, three-dimensional (3D) basin and petroleum system modeling (BPSM) of the subsurface through geological time has evolved as a major research focus 19 of both the petroleum industry and academia. The major oil companies have independently recognized the need for BPSM to archive data, facilitate visualization of risk, convert static data into dynamic processed data, and provide an approach to evaluate potential prospects in oil and gas exploration. BPSM includes the rigorous, structured, and full analysis of diverse geological, geophysical, geochemical, and engineering data related to the petroleum potential of a prospect into a model of one or more petroleum systems active in an area being explored. It predicts if and how a trap has been charged with hydrocarbons, including the source and timing of hydrocarbon generation, migration routes, quantities of petroleum through geologic time, and hydrocarbon type in the subsurface or at surface conditions. BPSM, a finite-element forward modeling approach in all standard commercial software, is a tool that can be used to analyze the formation and evolution of a sedimentary basin. It simulates the burial history of sediments including compaction, pressure, temperature, and maturation of organic matter (kerogen), petroleum generation, expulsion, migration and accumulation through geological time (Beha et al., 2008; Noeth et al., 2002; Tissot and Welte, 1984; Welte and Yalcin, 1988; Yalcin, et al., 1997; Yuekler et al., 1978). The first step in BPSM is to develop a conceptual model representing the basin history in a series of discrete time steps, which also determine the layers in the model. Then the layers are gridded into individual cells, for which all of the important parameters are calculated, including their effects on adjacent cells. Comparing model results with actual measured data (model calibration) is required for any numerical forward model. BPSM continues to grow in importance as a tool to understand subsurface geology and basin evolution by integrating key aspects of geochemistry, geology, 20 geophysics, and stratigraphy. Among the above, geochemistry is the most important tool to understand the processes affecting petroleum systems. A petroleum system is composed of a pod of active source rock and all related oil and gas, including all geological elements and processes: source rock, reservoir rock, seal, overburden rock, and favorable timing of petroleum generation, migration, accumulation and trap formation (Magoon and Dow, 1994). Better understanding of petroleum systems improves exploration efficiency. The first step in identifying petroleum systems is to characterize and map the geographic distribution of oil and gas types. Geochemical tools, such as biomarkers, diamondoids, and carbon isotope analysis are used to conduct oil-oil and oil-source correlation, which is the key to understand and determine the geographic extent of petroleum systems. It is recommended to start with a 1D model to solve the principal timing and understand the burial history in a particular setting. Then 2D or 3D models can be chosen based on the purpose of the study. In this study, we constructed a 1D model from one composite pseudo-well in the deepest part of the Vallecitos syncline to understand the thermal maturity of the two hypothesized source rocks. A 2D model was then created to examine scenarios of erosion thickness in more detail and to understand how sensitive the thermal maturity of source rock is to assumed erosion thickness. NUMERICAL MODELING AND INPUT Our geochemical results indicate that there are two different oil families in the study area generated from the Eocene Kreyenhagen and Cretaceous Moreno formations. 21 However, these geochemical results were anticipated based on our earlier 1D model results. The base of the Moreno Formation in the deepest part of the syncline reached thermal maturity as early as 42 Ma and the synclinal Kreyenhagen Formation became thermally mature as early as 19 Ma (Fig. 5a). The results from the 1D model show that the Moreno Formation already passed the dry gas window and part of the lower Kreyenhagen Formation is in the oil window at present-day in the deepest part of syncline (Fig. 5a). The transformation ratio (TR) shows that the Moreno Formation (TR=100%) is depleted, while most of the Kreyenhagen Formation (TR=70%) in the deepest part of the syncline is at the peak of oil generation at present-day (Fig. 5b). In addition, most of structural traps in this area were formed due to relatively recent folding and uplift of the basin (~10 Ma) (Graham and Williams, 1985; Rentschler, 1989; Peters et al., 2008). The Moreno Formation in the deepest part of syncline has a Ro=4% at the time the young traps were formed (Fig. 5a). The question is how those young traps could capture earlier generated Moreno oil. Is some part of the Moreno Formation with oil- window maturity charging the traps in the syncline at present-day? The maximum burial depth of the Kreyenhagen Formation is about 2.9 km (9,500 ft) in the syncline at present- day (Fig. 6). How did this shallow buried source rock become a major source rock in the Vallecitos study area if the deeper Moreno Formation had no contribution to the oil pools in the syncline at present-day? How can the shallowly buried Kreyenhagen Formation mature? In order to better answer these questions and understand the burial history of the source rocks in the syncline, a 2D reconstruction of the Vallecitos syncline was done using PetroMod 2D involving erosion scenarios on the flanks of the syncline, which could not be simulated in our earlier 1D model. 22 2D model input and burial history of source rocks The 2D model was developed based on a cross-section selected through the deepest part of the Vallecitos syncline (Fig. 6). Discretization was conducted by defining vertical grid and horizontal event lines. Inputs for the 2D model are geological layer thicknesses, depositional duration, and type (depositional, non-depositional and erosional) of the different modeling events. In addition, lithologies, paleowater depths, paleotemperatures, heatflow estimates, as well as hydrocarbon generation kinetics are required. These numerical data, including thickness, age at upper and lower boundary, lithological properties and heatflow were assigned to each grid cell. Source rock properties, such as total organic carbon (TOC) content, hydrogen index (HI), and kinetic parameters for petroleum generation, were also required model input. In general, all of the basic input data for the 2D model is very similar to that for the earlier 1D model, which was located in the deepest part of the Vallecitos syncline and was built from a composite pseudo-well based on the nearby the NETEX1 well (API: 06900250) (Fig. 1a; Table 4). The stratigraphy, lithostratigraphy, erosion and hiatus events were based on the USGS database (Hosford Scheirer and Magoon, 2008) and on updated studies from previous graduate studies at Stanford (e.g., Anderson, 1998; Bac, 1990; Enos, 1961; McGuire, 1988; Milam, 1985; Rentschler, 1989; Schulein, 1993) (Fig. 1c). All calibration data were obtained from the NETEX1 well (Table 5). The depositional durations of the respective units are based on published data, completion logs, and sequence stratigraphic work at Stanford (e.g., Anderson, 1998; Enos, 1961; Milam, 1985; Rentschler, 1989; Schulein, 1993). The lithologies were characterized using standard physical and chemical 23 parameters available in the PetroMod software. The thickness for each layer is determined from the cross-section profile GH (Fig. 6). All of the boundary conditions are consistent with those used in our earlier 1D model (Table 5). Paleobathymetry is critical for paleosubsurface topography and structural configurations, which affect burial and maturation of the source rocks, as well as migration pathways. Paleowater depth (PWD), one of the boundary conditions necessary for basin and petroleum system modeling, was estimated from previous graduate work in biostratigraphy at Stanford (e.g., Anderson, 1998; Bac, 1990; McGuire, 1988; Milam, 1985; Rentschler, 1989; Schulein, 1993; personal communication, James Ingle, 2009) and the literature (Graham and Berry, 1979). This allowed calculation of paleo-mean surface temperatures from the sediment-water-interface depth and paleo- latitude (Wygrala, 1989). Paleotemperatures are another important input parameter because they affect the geothermal gradient and the temperature history of the basin. Sediment-water-interface temperature (SWIT), another boundary condition for BPSM, can be derived from paleomean surface temperature and paleowater depth. Heatflow history is an important input for the 2D model, but it is difficult to determine. Heatflow is not directly measured, but related to the geothermal gradient. The present-day temperature is the only known parameter in a heatflow history. The remaining thermal history has to be determined by adjusting simulated model results to the temperature profiles (calibration data), such as vitrinite reflectance, bottom-hole temperature, and Rock-Eval Tmax temperature. An alternative way to determine heatflow history is possible based on subsidence and thermo-mechanical models (e.g., McKenzie, 1978). 24 The heat flow profile starts with basal heatflow at a certain geological time and is forward modeled through time to achieve a fit with present-day heatflow. Key for the 2D model is the erosion events proposed by Rentschler (1985). Major folding of the Vallecitos syncline occurred about 10 Ma and a series of erosion events took place on the flanks of the syncline caused by that folding (Bartow, 1991). Those erosion events could not be simulated in our 1D model. This certainly will affect the burial history of the basin and thermal history of the source rocks. Source rocks and kinetics We propose two active source rocks in the Vallecitos syncline based on our earlier 1D model and geochemical results, which differ from previously published studies. The active source rocks include shales of the Cretaceous Moreno and Eocene Kreyenhagen formations. The Moreno Formation is a marine sedimentary sequence deposited in the central San Joaquin basin during the Late Cretaceous to Early Tertiary. The Moreno Formation was deposited in an upper-slope to outer-shelf marine environment, with a portion of the unit influenced by upwelling oceanographic conditions and sedimentation under anoxic or low-oxygen conditions (McGuire, 1988). This unit covers much of the San Joaquin basin, including outcrop exposures west of Coalinga and northward to the Laguna Seca Hills; subsurface occurrences from the Kettleman Hills northward to the Chowchilla gas field; westward into the Vallecitos syncline and eastward beyond the axis of the San Joaquin basin (McGuire, 1988; Reid, 1988; Bac, 1990; Peters et al., 2007). The sediments are composed primarily of shale, mudstone, diatomaceous shale, and silty turbidite deposits. The shale in this sequence is organic-rich source rock and the silty turbidite deposits are potential reservoir rocks. The Moreno 25 Formation has highly variable marine autochthonous input from algae and bacteria (Bac, 1990). Total organic carbon (TOC) of Moreno Formation ranges from 1 to 3.95% and hydrogen index varies from 38 to 376 mg HC/gTOC (McGuire, 1988). Pyrolysis results plotted on a modified van Krevelen diagram indicate that Moreno source rock samples contain predominantly Type II kerogen (McGuire, 1988). The Kreyenhagen Formation is a widespread middle Eocene to Oligocene bathyal marine sequence of clay- and fine silt-size particles of marine microfossils and clay minerals, with subordinate coarse silt- and sand-size terrigenous clastics (Milam, 1985). The laminated character of these biogenic units and high TOC values indicate deposition under low-oxygen conditions associated with an oxygen-minimum zone (Milam, 1985). Kreyenhagen source rock is a diatomaceous and foraminiferal fine-grained shale and clay shale body within the Kreyenhagen Formation, and it covers most of the northern San Joaquin basin (Peters et al., 2007). Kreyenhagen shale contains type II/III kerogen, and consists of algal and terrigenous organic matter. Total organic carbon (TOC) of the Kreyenhagen shale ranges from 1.55 to 3.88%. The hydrogen index of the Kreyenhagen Formation ranges from 137 to 329 mg HC/gTOC (Milam, 1985). Kerogen kinetics control the calculation of hydrocarbon generation and zones of diagenesis, catagenesis, and metagenesis. Kinetics of each type of source rock (kerogen) could be understood by laboratory experiment. From laboratory pyrolysis experiments at different heating rates, activation energies and a pre-exponential factor are calculated and used for the temperature history of the relevant sediments. It is assumed that the conversion of kerogen to oil and gas is irreversible and is defined by a series of parallel pseudo-reactions. For the 1D and 2D models in this study, the organic matter is assumed 26 to be mainly of marine origin and the source rocks has an average TOC of 2.5%. HI values measured on kerogen concentrates range between 137 and 329 mg HC/g TOC for the Kreyenhagen shale, and between 38 and 376 mg HC/g TOC for Moreno shale, suggesting type II kerogen (Milam, 1985; McGuire, 1988). In this study, we used standard reaction kinetics in PetroMod for Type II kerogen based on Behar et al. (1997), average 2% TOC for Kreyenhagen Formation, and 3% TOC for Moreno Formation. The average HI for both Kreyenhagen and Moreno Formation is 305 and 350 mg HC/g TOC, repectively (Milam, 1985; McGuire, 1988). The petrophysical data, including density, initial porosity, compressibility, thermal conductivity, heat capacity, permeability, and capillary pressure, were associated with each different lithology type in PetroMod software. Those petrophysical data are recalculated in each geological time step, and reflect the dynamic model with the burial or erosion events. Calibration data Calibration of the model is required to understand the burial history and to determine the timing of petroleum generation and expulsion in the Vallecitos syncline. Various parameters can be used to achieve calibration, such as heatflow, thermal and physical properties of different rock lithologies, surface temperature, and sediment deposited (burial) or eroded (uplift). However, many of these parameters, such as thermal and physical properties, are constrained within narrow ranges of values. We used heatflow as the primary model calibration parameter because heatflow profile of this syncline is less constrained than any other parameter. Forward modeling of petroleum systems requires basal rather than surface heatflow as input. Basal heatflow may include 27 heat supplied from the deep mantle, radiogenic heat from the crust, and any transient heat provided by a thermal event. Use of two independent calibration tools, such as vitrinite reflectance (Ro, percent) and Rock-Eval Tmax is recommended for temperature history reconstruction. The 1D and 2D models were calibrated by comparing measured vitrinite reflectance and Tmax in the selected wells with the corresponding values predicted by the model at those locations. The model calculates vitrinite reflectance values using the “Easy%Ro” method of Sweeney and Burnham (1990). The vitrinite reflectance and Tmax from the NETEX1 well were used in this study for heatflow calibration (Fig. 7a &7b; Table 5). Rock-Eval analyses on the cuttings have been completed by GeoMark Research, LTD. The vitrinite reflectance results are from Weatherford Laboratories. Quality control on measured Tmax data was achieved by neglecting some data affected by contamination or migrated oil, according to rules developed by Peters and Cassa (1994). We checked the quality of measured vitrinite reflectance data used for calibration by comparing it to vitrinite o reflectance (percent) calculated from Tmax ( C) using the following formula: Vitrinite reflectance (calculated) = (0.018) (Tmax)-7.16 The measured Tmax data is converted to vitrinite reflectance by using this formula as well. This formula is based on data for a collection of shales containing low-sulfur Type II or Type III kerogen (Jarvie and Lundell, 2001). The curve generated by the formula corresponds reasonably well with empirical observations of Tmax versus vitrinite reflectance for Type III kerogen (Teichmüller and Durand, 1983). Use of the formula is o not recommended for low or high maturity samples (where Tmax is less than 420 C or o greater than 500 C) or when S2 is less than 0.5 mg hydrocarbon/g rock. “Caving” of rock 28 cuttings from shallow to deeper parts of the wellbore during drilling can invalidate these calculations because the caved material represents a contaminant that is less thermally mature than the deeper rock cuttings. MODELING RESULTS AND DISCUSSION Heatflow is the most uncertain parameter among all of the model input parameters. We can model the heatflow history of the Vallecitos area by considering the effects of two possible tectonic settings. Because the Valletios syncline is located near a former subduction zone in the western US, the subduction slab may have cooled the syncline in its early history (late Cretaceous) (Dickinson and Seely, 1979; Hamilton, 1988). Later, mid-oceanic spreading center collision with North America and northward migration of the Mendocino Triple Junction may have provided additional heating to the syncline during more recent geological time (Miocene age) (Atwater and Molnar, 1973; Engebretson, 1982). Based on the above two possibilities, we propose three models with different heat flow scenarios: 1) a “hot model” with a linear regression heatflow profile followed by a thermal pulse due to the northward progression of the Mendocino Triple Junction; 2) a “cold model” with linear regression heatflow profile with low starting heat flow due to cooling by the subducted slab below the syncline; and 3) a “combination model” with low starting heatflow followed by a thermal pulse due to both northward progression of the Mendocino Triple Junction and cooling of subducted slab below the syncline. The first heat flow trend representing the “hot model” starts with a low heatflow of 46 mW/m2 and has a rapid increase of heatflow from 20 to 10 Ma, followed by a 29 decline to an average value of 68 mW/m2 at present day. The “cold model” has a low starting heatflow of 30 mW/m2 at 73.5 Ma and does not dramatically increase until 25 Ma. Then, the trend has a linear increase from 25 Ma to present day at 68 mW/m2 (Peters et. al., 2008). The “combination model” has a low starting heatflow of 30 mW/m2 at 73.5 Ma, but there is an additional heating event from 18 to 9 Ma. However, the model results based on above three scenarios all show a cooler profile than the measured vitrinite reflectance data (Fig. 7a). That could indicate that “hot model” is closer to the reality than the other two models and the Mendocino Triple Junction has stronger affect on thermal history of the syncline than cooling of the subducted slab. There is some geological evidence of additional recent thermal anomaly close to the Vallecitos syncline. Intrusive basalt located about 9 km to the northwest of the Vallecitos syncline is dated to a middle Miocene age (Dibblee, 1979) (Fig. 1b). Similarly, intrusive serpentinite diapir at New Idria area, located about 5 km south of the Vallecitos syncline, created a thermal pulse that may have provided an additional heat source in the Vallecitos syncline (Vermeesch et. al., 2006). By using vitrinite reflectance in the Joaquin Ridge #1 well (Fig. 1b), which was not affected by the thermal anomaly, we calculated maximum erosion thickness of ~1 km in the New Idria area (Vermeesch et al., 2006; Horstman, 1984). The Christie #1 well (Fig. 1b), which was affected by the New Idria thermal anomaly, has vitrinite reflectance values of ~ 1.9%-2% or maximum paleotemperature of ~ 180 oC at about 1.25 km depth (Vermeesch et. al., 2006). Using the above data as input, the calculated heatflow value was about 180 mW/m2, assuming thermal conductivity K for magmatic intrusions is 1.95 W/m/K, when Mendocino Triple Junction passed this area (Delaney, 1988). In addition, there are some modern examples 30 of high heatflow values associated with hot spots and spreading centers. The present-day heatflow in Iceland is around 220 mW/m2 (Stein and Stein, 2003). Another more reminiscent example of the Vallecitos is the Salton Sea, which represents the transition between oceanic spreading in the Gulf of California to the south and the San Andreas continental transform fault system to the north. Relative plate motion along the San Andreas faults allows the Salton Trough to have a high heatflow due to the magmatic intrusions. Heatflow values in the U.S. portion of the trough are > 100 mW/m2 (Lachenbruch et al., 1985). In addition, some isolated areas have especially high heatflow, >200 mW/m2 (Newmark et al., 1988). Recent plate reconstruction study indicates that the Mendocino Triple Junction passed the Vallecitos area around 19 Ma (Atwater, 1998). Considering all the above factors, we used 160 mW/m2 as heatflow value starting at 18 Ma and decreased it slowly over the next 9 Ma following McKenzie (1978) (Table 5) in order to make the model results match measured Ro data (Fig. 7b). Temperature (magnitude and duration) is one of the most important factors to determine the reaction rate of organic matter. The conversion of kerogen into hydrocarbons (oil and gas) (transformation ratio, TR) can be determined when the temperature history and kinetics are known. Maturity values are calculated by using the “Easy% Ro” method of Burnham and Sweeney (1989). Computed vitrinite reflectance (% Ro) values are similar to the actual measurements from the well based on the above consideration (Fig. 7b). Our 1D modeling shows that present-day transformation ratios for the basal part of the lower Kreyenhagen Formation are about 85%, whereas those for the lower Moreno Formation are greater than 90%, indicating depleted source rock (Fig. 5b). The maturation histories of the two source rocks are shown in Fig. 5a. The basal part 31 of the Kreyenhagen Formation reached oil-window maturity at about 19 Ma, and the basal part of Moreno Formation became mature at about 42 Ma, assuming a threshold of 0.6% Ro for the onset of oil generation. A sudden increase of thermal maturity in Pliocene and Pleistocene time is related to rapid sedimentation after the major uplift and folding of the syncline, as well as the thermal pulse associated with the Mendocino Triple Junction. The tectonic evolution of the region significantly influenced burial and thermal history of the study area. However, the simple 1D model fails to simulate complex tectonic events, such as subsidence, uplift and erosion. Therefore, a 2D model was created to simulate the thermal history of the source rock in the Vallecitos syncline involving proposed erosion scenarios from relatively recent folding of the syncline and the three different heatflow scenarios discussed earlier. Interestingly, the 2D modeling results show that the deepest part of the lower Kreyenhagen Formation is in the dry gas window at present-day but that the rest of the lower Kreyenhagen Formation, especially on the flanks, remains immature at the very shallow part of the lower Kreyenhagen Formation (Fig. 8), at the location of the chosen cross-section. The lower Kreyenhagen Formation has significant remaining hydrocarbon potential in the study area. The deepest part of Moreno Formation is already overmature and the shallower sections of Moreno Formation on the flanks are in the late oil window at present-day. We predicted that the Moreno Formation has exhausted its hydrocarbon potential in much of the Vallecitos syncline. We identified two potential petroleum systems: 1) Eocene petroleum system, named the Kreyenhagen-Yokut(.); and 2) Cretaceous petroleum system, named the Moreno-San Carlos(.) based on our geochemical and modeling results. The types of 32 reservoirs which the oils were produced from were marked in Fig. 1a. The Kreyenhagen- Yokut(.) is a significant petroleum system in the Vallecitos syncline. The Kreyenhagen oil type is widely distributed along the flanks of the syncline. The present-day pod of active Kreyenhagen source rock is along the flank of the syncline at a shallow depth and the possible migration paths are most likely from the center of the syncline to the flanks, where all structural traps occur at a shallow depth. The basal part of the Kreyenhagen Formation at ~2.9 km is in the dry gas window in the deepest part of the syncline based on our 2D model results and it should be less mature along the basin axis to the west at shallow depth. The young structural traps (~10 Ma) may have only capture a small portion of early generated Kreyenhagen oil, since the onset of petroleum generation for lower Kreyenhagen Formation in the deepest part of the syncline occurred at ~19 Ma shown on the burial history plot (Fig. 5a & 9a). The TR of basal lower Kreyenhagen Formation reached peak generation or expulsion very quickly at ~9 Ma and is 80% at present-day indicating remaining generation potential in the source rock (Fig. 5b). Most of the oil in the present-day traps is recently generated oil from Kreyenhagen source rock. There is still significant remaining potential for oil generation from the Kreyenhagen Formation in the syncline at present-day. The Moreno-San Carlos(.) is probably a gas- prone system in the syncline. Moreno oil is restricted to the flanks at a shallow depth. The burial history of Moreno Formation shows that the onset of petroleum generation started at 39 Ma at the deepest part of the syncline and reached peak generation at about 34 Ma (Fig. 5a & 5b). The results show that Moreno Formation is mostly depleted and only the very top part of Moreno Formation on the flank is still in the late oil window at present- day. Most parts of Moreno Formation are in the wet gas zone in the deepest part of the 33 syncline at present-day (Fig. 8). The Moreno Formation could be a major source for gas accumulations in the syncline. The earlier generated Moreno oil could be lost due to structural damage of the old traps or lack of accumulation in the traps, which have younger age and could preserve the recent generated Moreno oil from the top part of the flank in the syncline (Fig. 9b). Moreno oil also could be cracked into gas at high maturity stage. The Moreno-San Carlos(.) petroleum system should have little oil generation potential at present-day, but could be a major gas system in this area. CONCLUSIONS A numerical 2D model of the Vallecitos syncline was developed based on thorough analysis of stratigraphy and basin evolution. The model results have significant value to evaluate the timing and magnitude of hydrocarbon generation and the remaining hydrocarbon potential in the Vallecitos syncline. In general, organic-rich potential source rocks can not become thermally mature without significant burial. However, the Vallecitos syncline appears to be exception of that shallowly buried source rock matured as a result of a thermal anomaly without deep burial. Geological relations in this area and our detailed model results suggest that the passage of the Mendocino Triple Junction by the Vallecitos syncline had a tremendous thermal impact on the maturity of both source rock sequences at shallow depth in the syncline. The current distributions of the oil families from our geochemical study of the syncline support the modeling results suggesting that a thermal anomaly passed near the syncline in the middle Miocene. The young structural traps seem to preserve the recently generated Kreyenhagen and Moreno 34 oil. The 2D modeling results predict that the deepest part of lower Kreyenhagen Formation is in the dry gas window at present-day, but the rest of the lower Kreyenhagen Formation, especially on the flanks, is less mature. Kreyenhagen source rock remains immature in the very shallow parts of the syncline, at least at the location of the cross- section. The BPSM model and detailed geochemical results show that both the Eocene Kreyenhagen and Cretaceous Moreno formations were active source rocks in the Vallecitos syncline. The geographic extent of the both active source rocks likely covers most of the deeper syncline. The two different oil families originated from the Kreyenhagen and Moreno formations, based on biomarker analyses of oil samples collected in the Vallecitos syncline. In addition, the Eocene Kreyenhagen Formation still has great potential for petroleum generation, especially in those areas buried at shallow depth. The Cretaceous Moreno Formation is a depleted source rock for oil generation at present-day, but it could be a source rock for hydrocarbon gas in the Vallecitos syncline. ACKNOWLEDGMENTS This work was completed with financial support from the Basin and Petroleum System Modeling (BPSM) and the Molecular Organic Geochemistry Industrial Affiliates (MOGIA) programs at Stanford University. We greatly appreciate the assistance from Professor Mike Moldowan and staff in sample separation, GC, and GC-MS in Molecular Organic Geochemistry laboratory at Stanford University. 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One-dimensional model to simulate geologic, hydrodynamic and thermodynamic development of a sedimentary basin. Geologische Rundschau 67, 960–979. 47 Table 1. Oil samples by field, well ID, reservoir age, longitude, latitude, oil type and township. Oil Sample Formation ID Field Name Well API Well Name Reservoir Age Name Longitude Latitude Oil Type Sec-Twn-Rng Yokut SJ102 Vallecitos 4069200250 Bunker 34-4 Eocene Sandstone -120.75057 36.50051 EK 34-16S-11E Kreyenhagen SJ104 Vallecitos 4069000290 Ashurst 1A-5 Eocene Formation -120.78556 36.48111 EK 5-17S-11E Kreyenhagen SJ105 Vallecitos 4069001710 Ashurst 43-5 Eocene Formation -120.78944 36.483268 EK 5-17S-11E Yokut SJ106 Vallecitos 4069001 550 F & I 37-31 Eocene Sandstone -120.80945 36.49057 EK 31-16S-11E Yokut SJ107 Vallecitos 4069000030 Bryant-U S L 16A-28 Eocene Sandstone -120.77813 36.50562 EK 28-16S-11E Yokut SJ108 Vallecitos 4069000030 Bryant-U S L 16A-28 Eocene Sandstone -120.77813 36.50562 EK 28-16S-11E Yokut SJ109 Vallecitos 4069200310 Ashurst 38-28 Eocene Sandstone -120.77214 36.50236 EK 28-16S-11E Cal-O-Tex Exploration Kreyenhagen SJ112 Vallecitos 4069001030 Co. 1 Eoce ne Formation -120.78793 36.461361 EK 8-17S-11E Tannehill Oil Co F&I SJ117 Vallecitos 4069200560 12X well. unknown unknown -120.797183 36.484441 EK 5-17S-11E SJ119 Big Tar Canoy 4031006810 Seep surface unknown -120.170633 35.933485 EK 18-23S-17E SJ121 Kreyenhagen extract(5) N/A N/A N/A N/A N/A N/A EK N/A SJ122 Stanford3(kreyenhagen) N/A N/A unknown unknown N/A N/A EK N/A Ashurst 52A-33(Pfau, SJ124 Vallecitos 4069001350 Pfau &fau ,LLC ) unknown unknown -120.768901 36.499554 EK 33-16S-11E Yokut SJ125 Vallecitos 4069001670 F&I 86-29 unknown Sandstone -120.77945 36.50484 EK 29-16S-11E F&I 16-31(Patriot Yokut SJ126 Vallecitos 4069001500 Resources LLC) unknown Sandstone -120.815045 36.492078 EK 31-16S-11E F&I 26-31(Patriot Yokut SJ128 Vallecitos 4069001510 Resources LLC) unknown Sandstone -120.812963 36.492338 EK 31-16S-11E 16B-28(Panoche SJ129 Vallecitos 4069000040 Vallecitos oil unknown unknown -120.779128 36.505529 EK 28-16S-11E company) SJ130 Vallecitos N/A Seep 1 (F&I) surface unknown -120.80866 36.49139 EK N/A SJ131 Vallecitos N/A Seep 2(F&I) surface unknown -120.80822 36.47607 EK N/A Lodo SJ103 Vallecitos 4069001870 Ashurst 2 Paleocene Formation -120.75949 36.51058 CM 27-16S-11E Moreno SJ110 Vallecitos 4069200470 Olson-McDonald 1 Late Cretaceous Formation -120.81325 36.52833 CM 19-16S-11E Lodo SJ111 Vallecit os 4069001120 Panoche 1 Paleocene Formation -120.82552 36.52622 CM 24-16S-10E Lodo SJ113 Vallecitos N/A Ash 1,2,3,5,6,9 Paleocene Formation -120.672 36.502 CM 28-16S-12E Lodo SJ114 Vallecitos 4069000900 Ash 6 Paleocene Formation -120.67026 36.50278 CM 28-16S-12E Lodo SJ115 Vallecitos 4069000950 Nicholas 5 Paleocene Formation -120.670265 36.502308 CM 28-16S-12E Coast Range Oil Co. 1 More no SJ118 Coalinga 4019004400 well (Oil City) unknown Formation -120.3668 36.269198 CM 17-19S-15E SJ123 Vallecitos 4069001870 Ashurst 2-27 unknown San Carlos -120.75989 36.51021 CM 27-16S-11E SJ127 Vallecitos 4069000940 Nicholas 3 unknown San Carlos -120.672139 36.503302 CM 28-16S-12E 48 *N/A: not applicable. EK= Eocene Kreyenhagen, CM= Cretaceous Moreno. Table 2. Geochemical parameters of oil samples in the Vallecitos syncline and the reference samples. Sample *C19/C19+ *C29/C30 *DiaH/(H*C35/(C34 Family *C22/C21 *C24/C23 *C26/C25 *Tet/C23 *%C27 *%C28 *%C29 *ETR *C31R/H *GA/H *Diast *OI ID C23 Hop +diaH) +C35)Hop SJ102 EK 0.17 0.21 0.58 1.11 0.61 0.32 0.34 0.34 1.75 0.30 0.49 0.04 0.39 0.02 0.25 0.20 SJ104 EK 0.12 0.18 0.50 1.02 0.68 0.33 0.35 0.32 1.64 0.25 0.51 0.03 0.42 0.02 0.27 0.16 SJ105 EK 0.14 0.13 0.61 1.20 0.55 0.33 0.36 0.31 1.80 0.24 0.46 0.05 0.42 0.03 0.26 0.16 SJ106 EK 0.15 0.16 0.69 1.14 0.70 0.32 0.35 0.33 1.49 0.29 0.57 0.04 0.49 0.03 0.28 0.16 SJ107 EK 0.16 0.19 0.46 0.96 0.79 0.33 0.34 0.33 2.07 0.40 0.61 0.03 0.41 0.01 0.26 0.23 SJ109 EK 0.15 0.22 0.47 0.98 0.79 0.32 0.34 0.34 1.71 0.35 0.56 0.02 0.37 0.01 0.25 0.21 SJ112 EK 0.13 0.15 0.68 1.18 0.56 0.32 0.35 0.33 1.52 0.22 0.43 0.04 0.40 0.01 0.30 0.11 SJ117 EK 0.15 0.16 0.69 1.22 0.47 0.32 0.35 0.32 1.93 0.23 0.46 0.05 0.39 0.02 0.31 0.15 SJ119 EK 0.10 0.23 0.64 0.90 0.39 0.46 0.38 0.16 20.51 0.40 0.80 0.62 0.19 0.78 0.68 0.82 SJ121 EK 0.12 0.21 0.50 0.88 0.68 0.31 0.36 0.33 1.28 0.26 0.49 0.03 0.41 0.01 0.39 0.15 SJ122 EK 0.12 0.11 0.77 1.11 0.28 0.33 0.36 0.31 2.16 0.24 0.43 0.07 0.44 0.02 0.35 0.17 SJ124 EK 0.16 0.16 0.50 1.06 0.74 0.33 0.34 0.34 1.58 0.48 0.54 0.02 0.41 0.01 0.25 0.24 SJ125 EK 0.14 0.14 0.48 0.88 0.82 0.34 0.35 0.31 1.39 0.39 0.53 0.03 0.44 0.02 0.28 0.23 SJ126 EK 0.13 0.12 0.66 1.08 0.45 0.32 0.37 0.31 1.76 0.26 0.46 0.05 0.40 0.01 0.31 0.19 SJ128 EK 0.13 0.16 0.60 1.14 0.48 0.32 0.37 0.32 1.99 0.26 0.45 0.04 0.42 0.01 0.30 0.20 SJ129 EK 0.16 0.15 0.45 1.06 0.77 0.32 0.35 0.33 1.61 0.42 0.53 0.02 0.41 0.02 0.23 0.23 SJ130 EK 0.14 0.09 0.71 1.14 0.45 0.32 0.37 0.30 1.89 0.27 0.45 0.05 0.42 0.01 0.30 0.19 SJ131 EK 0.12 0.24 0.56 1.43 0.71 0.18 0.37 0.44 0.99 0.48 5.79 0.37 0.38 0.21 0.64 0.53 SJ103 CM 0.09 0.22 0.47 0.96 0.35 0.32 0.45 0.24 2.91 0.24 0.45 0.03 0.47 0.02 0.30 0.08 SJ110 CM 0.10 0.18 0.70 1.00 0.29 0.34 0.42 0.25 3.69 0.21 0.42 0.06 0.43 0.01 0.35 0.08 SJ111 CM 0.08 0.15 0.74 1.02 0.27 0.33 0.42 0.25 3.52 0.21 0.42 0.07 0.42 0.01 0.37 0.08 SJ113 CM 0.10 0.24 0.53 1.08 0.33 0.33 0.41 0.25 2.60 0.22 0.42 0.06 0.42 0.02 0.36 0.08 SJ114 CM 0.08 0.25 0.55 1.08 0.31 0.34 0.42 0.24 2.31 0.23 0.43 0.06 0.43 0.01 0.37 0.08 SJ115 CM 0.07 0.23 0.52 1.02 0.32 0.33 0.42 0.25 2.39 0.22 0.43 0.06 0.42 0.01 0.35 0.06 SJ118 CM 0.42 0.25 0.42 0.88 0.58 0.34 0.41 0.24 2.96 0.22 0.58 0.04 0.36 0.01 0.36 0.06 SJ123 CM 0.07 0.11 0.44 0.86 0.36 0.32 0.44 0.24 2.74 0.27 0.43 0.03 0.49 0.02 0.31 0.08 SJ127 CM 0.09 0.30 0.56 1.06 0.33 0.34 0.41 0.24 2.30 0.24 0.42 0.06 0.42 0.01 0.35 0.08 *Parameter was used in the chemometric analysis. C19/C19+C23, C22/C21, C24/C23, and C26/C25 tricyclic terpanes; Tet/C23=C24 tetracyclic terpane/C23 tricyclic terpane; %C27=%C27 steranes/(%C27 to %C29 steranes); %C28=%C28 steranes/(%C27 to %C29 steranes); %C29=%C29 steranes/(%C27 to %C29 steranes); ETR=(C28+C29 tricyclics)/ trisnorneohopane; C31R/H=C31 homohopane/hopane; C29/C30Hop=C29 30-norhopane/hopane; DiaH/(H+diaH)=C30 diahopane/(hopane+diahopane); C35/(C34+C35)Hop=C35 homohopanes/(C34+C35 homohopanes); GA/H=gammacerane/hopane; Diast=diasterane/(diasteranes+sterane); OI=oleanane/(oleanane+hopane). Many of these parameters are discussed in Peters et al. (2005). 49 Table 2. Geochemical parameters of oil samples in the Vallecitos syncline and the reference samples (continued). *TA- C29 TA C / *Bisnor *TA- *24TET/ 3-/(3- + 4- C29 20 TA(I)/TA(I Sample ID Family *25-Nor DMD3/ *Pr/Ph *27MA *28MA *29MA C T/Ts Ts/(Ts+Tm) ββ/(ββ +αα) (C +C , H Dino H 26 MeS 20R) 20S(20S+ 20 28 +II) C28S 20R) 20R) SJ102 EK 0.16 0.06 0.09 0.74 0.03 2.60 0.22 0.51 0.27 0.43 0.51 0.39 0.33 0.34 0.16 0.09 SJ104 EK 0.15 0.01 0.10 0.80 0.02 2.40 0.23 0.52 0.25 0.41 0.42 0.39 0.27 0.34 0.12 0.06 SJ105 EK 0.27 0.02 0.10 0.81 0.03 2.00 0.24 0.51 0.25 0.52 0.40 0.44 0.32 0.33 0.15 0.08 SJ106 EK 0.12 0.06 0.09 0.75 0.04 2.30 0.22 0.50 0.27 0.36 0.49 0.48 0.37 0.42 0.25 0.15 SJ107 EK 0.21 0.07 0.09 0.77 0.03 2.64 0.21 0.50 0.29 0.48 0.46 0.29 0.28 0.32 0.08 0.04 SJ109 EK 0.23 0.09 0.09 0.73 0.03 2.80 0.22 0.46 0.32 0.44 0.51 0.33 0.29 0.35 0.11 0.06 SJ112 EK 0.15 0.02 0.10 0.74 0.03 2.10 0.24 0.51 0.24 0.44 0.52 0.54 0.44 0.46 0.10 0.10 SJ117 EK 0.11 0.06 0.09 0.72 0.03 2.46 0.25 0.49 0.26 0.56 0.53 0.46 0.39 0.42 0.26 0.16 SJ119 EK 0.57 3.99 0.09 0.74 0.88 1.50 0.25 0.49 0.26 5.81 0.51 0. 56 0.55 0.77 0.06 0.03 SJ121 EK 0.03 0.03 0.11 0.81 0.02 1.00 0.23 0.48 0.29 0.33 0.42 0.50 0.37 0.50 0.48 0.07 SJ122 EK 0.04 0.04 0.10 0.76 0.04 1.75 0.30 0.44 0.26 0.73 0.48 0.63 0.30 0.50 0.34 0.24 SJ124 EK 0.23 0.04 0.10 0.75 0.03 2.61 0.24 0.49 0.27 0.46 0.50 0.43 0.11 0.33 0.09 0.05 SJ125 EK 0.23 0.01 0.09 0.79 0.03 2.25 0.22 0.51 0.26 0.45 0.44 0.45 0.16 0.33 0.08 0.04 SJ126 EK 0.15 0.01 0.09 0.77 0.03 2.34 0.25 0.52 0.24 0.61 0.46 0.47 0.26 0.37 0.22 0.13 SJ128 EK 0.14 0.00 0.10 0.76 0.03 2.36 0.23 0.51 0.27 0.56 0.49 0.43 0.30 0.39 0.22 0.13 SJ129 EK 0.20 0.06 0.09 0.78 0.03 2.36 0.22 0.49 0.29 0.46 0.46 0.32 0.26 0.31 0.08 0.04 SJ130 EK 0.15 0.02 0.10 0.77 0.03 1.56 0.22 0.52 0.26 0.58 0.47 0.51 0.30 0.40 0.22 0.13 SJ131 EK 0.48 0.16 0.09 0.67 0.45 1.00 0.22 0.52 0.25 0.33 0.60 0.47 0.58 0.77 0.04 0.03 SJ103 CM 0.09 0.07 0.09 0.88 0.02 2.13 0.19 0.64 0.18 0.89 0.28 0.32 0.30 0.24 0.06 0.03 SJ110 CM 0.04 0.03 0.11 0.84 0.03 2.09 0.20 0.61 0.19 1.00 0.36 0.36 0.39 0.37 0.31 0.16 SJ111 CM 0.06 0.02 0.11 0.84 0.03 2.00 0.20 0.61 0.19 1.00 0.36 0.46 0.37 0.40 0.31 0.16 SJ113 CM 0.10 0.05 0.10 0.85 0.03 1.90 0.22 0.59 0.20 0.76 0.34 0.49 0.39 0.38 0.27 0.14 SJ114 CM 0.10 0.05 0.10 0.85 0.02 2.00 0.21 0.59 0.20 0.70 0.34 0.50 0.37 0.37 0.28 0.14 SJ115 CM 0.08 0.05 0.10 0.85 0.03 1.70 0.22 0.59 0.20 0.71 0.34 0.49 0.34 0.38 0.27 0.13 SJ118 CM 0.08 0.06 0.09 0.85 0.05 3.20 0.20 0.61 0.19 1.00 0.34 0.31 0.32 0.39 0.21 0.10 SJ123 CM 0.06 0.08 0.09 0.89 0.02 1.72 0.18 0.63 0.19 0.8 4 0.26 0.34 0.30 0.23 0.06 0.03 SJ127 CM 0.09 0.05 0.11 0.85 0.03 1.96 0.22 0.58 0.19 0.75 0.34 0.48 0.36 0.39 0.25 0.13 *Parameter was used in the chemometric analysis. BisnorH= bisnorhopane/hopane; 25-Nor=25-nor-hopane/hopane; TA-DMD3/C28S=C28 triaromatic demethyldinosterane/C28 stigmastane; TA-Dino=C29 triaromatic dinosteranes/(C29 dinosteranes+3-methylstigmastane 20R); 24TET/H=C24 tetracyclics/hopane; 27MA=monoaromaticC27/monoaromatic(C27+C28+C29); 28MA=monoaromaticC28/monoaromatic(C27+C28+C29); 29MA=monoaromaticC29/monoaromatic(C27+C28+C29); C26T/Ts=C26 tricyclic terpane/trisnorneohopane; 3-/(3-+4-MeS 20R)=3-/(3-+4-methylstigmastane 20R); C24Tet/C26=C24 tetracyclics/C26 trycyclics; TA C20/(C20+C28, 20R)=desmethyl triaromatic steroids; 50 TA(I)/TA(I+II)=(C21+C22)/(C21+C22+C26+C27+C28)desmethyl triaromatic steroids. Many of these parameters are discussed in Peters et al. (2005). See EK & CM in Table 1. Table 3. Identification of labeled biomarker peaks shown in Figures 2a, 2b, and 2c. Peak ID Sterane m/z = 217 Peak ID Terpane m/z = 191 1 C27 βα 20S diacholestane 1 Ts 18α(H)-trisnorhopane 2 C27 βα 20R diacholestane 2 Tm 17α(H)-trisnorhopane 3 C28 βα 20S diasterane a 3 C28 17α,18α,21β(H)-bisnorhopane 4 C28 βα 20S diasterane b 4 C29 25-nor-hopane 5 C28 βα 20R diasterane a 5 C29 Ts 18α(H)-norneohopane 6 C28 βα 20R diasterane b 6 C30 17α(H)-diahopane 7 C27 αα 20S cholestane 7 C29 normoretane 8 C27 ββ 20R cholestane 8 α-oleanane 9 C27 ββ 20S cholestane 9 β-oleanane 10 C27 αα 20R cholestane 10 C30 17α(H) hopane 11 C29 βα 20R diastigmastane 11 C31 22S 17α(H) homohopane 12 C28 αα 20S ergostane 12 C31 22R 17α(H) homohopane 13 C28 αα 20S ergostane 13 C32 22S 17α(H) bishhomohopane 14 C28 ββ 20R ergostane 14 C32 22R 17α(H) bishhomohopane 15 C28 ββ 20S ergostane 15 C33 22S 17α(H) trishomohopane 16 C28 αα 20R ergostane 16 C33 22R 17α(H) trishomohopane 17 C29 αα 20S stigmastane 17 C34 22S 17α(H) extended hopane 18 C29 ββ 20R stigmastane 18 C34 22R 17α(H) extended hopane 19 C29 ββ 20S stigmastane 19 C35 22S 17α(H) extended hopane 20 C29 αα 20R stigmastane 20 C35 22R 17α(H) extended hopane 51 Table 4. General input data for 1D and 2D models. Present Erosion Petroleum PetroMod Deposition Erosion/H Age of Interval Thicknes thicknes Lithology System Stratigraphic Unit (Ma) iatus (Ma) s (M) s (M) Element From To From To Sandstone Unnamed 0.6 0.2 0 0.2 0 25 (typical) Overburden Pliocene Unnamed 2.5 2 0 2 0.6 381 Shale (typical) Rock San Joaquin Fm. 4.5 3 0 3 2.5 381 Shale (typical) Miocene to Sandstone Etchegoin Fm. 5.5 4.5 1570.3 Reservoir Rock Pliocene (typical) Overburden Monterey Fm. 05.531 )lacipyt(elahS Rock Miocene Sandstone Temblor Fm. 22 14 701 14 13 152 Reservoir Rock (clay poor) Oligocene Unnamed 37 30 0 30 22 610 Shale(typical) Overburden Sandstone(clay Rock ic U. Kreyenhagen Fm. 7547334 rich) Shale(organic Eocene L. Kreyenhagen Fm. 48.5 43 366 Source Rock rich) Sandstone Tertiary Domengine Fm. 49 48.6 46 48.6 48.5 23 (tyical) Cenozo Reservoir Rock Sandstone Yokut Sandstone 49.5 49 213 (clay poor) Arroyo Hondo shale Shale (organic 51.5 49.5 183 Seal Rock (Lodo Fm.) lean) Paleocene to Cantua Sandstone Sandstone 53 51.5 427 Reservoir Rock Eocene (Lodo Fm.) (clay poor) Cerros Shale (Lodo Shale (organic 55.5 53 107 Seal Rock Fm.) lean) San Carlos Sandstone Sandstone 58.5 55.5 274 Reservoir Rock (Lodo Fm.) (clay poor) Shale (organic Moreno Fm. 73.5 61 594 61 58.5 100 Source Rock zoic Cretaceous to rich) Paleocene Shale (organic Underburden 52 Panoche Fm. 83.5 73.5 1000 Moso lean) Rock Table 5. Boundary conditions and model calibration data from the NETEX1 well for 1D and 2D models. Model SWIT (sediment- Ro% Paleowater HF (Heat Age (Ma) Age (Ma) water interface Depth (m) Ro% Tmax(oC) (converted depth (m) Age (Ma) flow, Mw/ temperature) from Tmax) m2) 0 051- 0 3.71 0 86 0011 824 45.0 4.5 -100 4.5 16.3 9 145 1119 0.54 426 0.51 5.5 -80 5.5 16.33 14 155 8221 724 35.0 16 -50 16 20.4 16 155 1301 0.59 18 600 18 5.69 18 160 7431 234 26.0 73 0001 73 74.42 52 57 3931 134 6.0 34 006 34 7.21 03 07 0341 034 85.0 48.5 200 48.5 19.48 35 65 1503 0.61 94 0001 94 6.42 04 06 2151 134 6.0 5.94 0001 5.94 23.31 54 5.45 9351 234 26.0 5.15 0001 5.15 36.31 05 35 4951 434 56.0 35 0001 35 88.31 55 5.15 6461 234 26.0 5.55 0001 5.55 71.41 06 05 3761 334 36.0 58.5 1000 58.5 24.13 65 48.5 73.5 1000 73.5 14.82 73.5 46 53 After California Division of Oil and Gas (CDOG), 1982 M M H KK K M M K M M K K M Seep 1 K K K API:06900250 K Ne-Tex Corp. Seep 2 K “NETEX1” K K 0 6000 12000 FT. G Figure 1a. Structural map of the top of Kreyenhagen Formation and study area with the distribution of the oil samples in the Vallecitos syncline. Star symbol indicates the 1D model location. GH is the 2D model cross-section line. NETEX1 well is the calibration well. K shows Kreyenhagen oils and M shows 54 Moreno oils. Open symbol shows the reservoir where the oil is produced from. Blue rectangle indicates Yokut reservoir. Red circle indicates San Carlos reservoir. Green polygon indicates unknown reservoir. Outcrop geology, westside San Joaquin Basin Diablo Range Panoche Valley Tumey Gulch Tumey Hills Miocene Basalt Vallecitos Syncline 1 Joaquin Ridge #1 New Idria 2 Christie #1 2 Oil City 1 Serpentinite Diapir San Andreas Fault Coalinga San Joaquin Valley Kettleman North Dome Reef Ridge Temblor Range Kettleman Middle Dome Pyramid Hills Kettleman South Dome N 0 5 10 20 miles Devil's Den King 0 5 10 20 kilometers Canyon Antelope Valley Antelope Hills / N. Belridge oil field Packwood Outcrop Geology Key Creek Media Agua Creek Chico Martinez Creek Faults (dashed where inferred) Stone Corral Canyon Temblor Creek Carneros Pliocene and Younger Strata Creek Oligocene - Miocene Strata Zemorra Creek Eocene Strata Paleocene Strata Upper Cretaceous Marine Strata Cretaceous and Older, Undifferentiated (includes basement rocks and Franciscan Complex) After Johnson and Graham, 2006 Figure 7b. Plot of calculated (line) and measured (symbols) %Ro versus depth for the model. Open circles indicate measured %Ro data, cross symbols indicate converted Ro from measured Tmax data in Figure 1b. Generalized outcrop geologythe NETEX1 of the westsidewell. San Joaquin Basin. 55 Vallecitos Syncline, San Joaquin Basin Province SYSTEM Mega- SERIES sequences West East Ma (2nd order) STAGE syncline axis 0 unnamed PLEIS. unnamed San Joaquin Fm PLIO. 5 Etchegoin Fm Trans- pression Reef Ridge Sh Mbr Monterey Fm DEL. McLure Shale Mbr 10 MOHNIAN EOG ENE N LUI. 15 Temblor Fm migration MIOCENE REL. Triple junction Triple 20 SAUCESIAN 25 unnamed 30 Subduction and magmatism ZEMORRIAN OLIG OCENE REF. Leda sd 35 Tumey formation 40 Kreyenhagen Formation EOCENE 45 subsidence Diablo Range uplift and basin Yokut Domengine Fm Ss 50 LEOG ENE Gatchell sd Arroyo Hondo Sh Mbr PA Cantua Ss Mbr PENUTIAN ULATSIAN NARIZIAN 55 Lodo Fm TIAN BULI- orogeny San Carlos sd Oil reservoir rock Gas reservoir rock and Laramide ZIAN YNE- Potential marine Nonmarine reservoir rock coarse grained 60 rock Clay/shale/ ~ ~ Coast Range LE OCENE mudstone/ ~ ~ ophiolite/ Granitic basement Moreno Fm biosiliceous Flat slab subduction PA Oil-prone source Hiatus or loss by rock/ erosion CHENEYIAN Gas-prone source 65 rock 121˚W 120˚W 119˚W 70 MAASTRICH. 38˚N miles Br own Mtn ss Stockton Arch Ragged Valley silt basin axis San Joaquin0 Basin Province 25 75 Joaquin Ridge Ss Mbr ANIAN COAST RANGES E T Panoche Fm North A 80 L SIERRA NEVADA CAM P 37˚N SANT. 85 ? and gin CON. ma tism SAN ANDREAS FAULT Central 90 ma r TUR. undifferentiated Cretaceous marine and nonmarine strata DCN CRETACEOUS 36˚N DR DC 95 T PH South DD J CENO. Bakers eld Arch rgent ve rgent 100 mag err an Si Paci c 160 Ma 120 Ma WWF 105 Con Ocean EARLY Basement rocks 35˚N ALBIAN SAN EMIGDIO,TECHAPI MOUNTAINS 110 After Hosford Scheirer and Magoon, 2008 Figure 1c. Generalized stratigraphic column of the Vallecitos syncline. 56 Whole-Oil Gas Chromatography Biomarkers Ion 191.00 (190.70 to 191.70): SJ121S.D FID1 A, (DAVID\SJ122.D) PA Abundance 10 2000 Pr 200000 1750 1500 Ph 150000 1250 1000 extract 750 100000 source source rock 11 Kreyenhagen Kreyenhagen 500 12 13 250 50000 15 5 14 16 1 2 8 17 0 7 9 18 19 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 min 3 4 6 20 0 Time--> 75.00 80.00 85.00 90.00 95.00 Time (min) Ion 191.00 (190.70 to 191.70): SJ112S.D Abundance 10 FID1 A, (MENG\SJ112.D) PA 30000 1400 25000 1200 1000 20000 Pr 800 (SJ112) 15000 600 in Vallecitos in 11 Ph 10000 Kreyenhagen oil Kreyenhagen 12 400 13 5 14 15 5000 1 2 4 8 16 200 7 17 3 6 9 18 19 20 0 0 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 min Time--> 57 75.00 80.00 85.00 90.00 95.00 Time (min) Figure 2a. Whole-oil gas chromatogram and 191 m/z ion mass fragmentogram for Kreyenhagen source rock extract and selected Kreyenhagen oil in Vallecitos. Whole-Oil Gas Chromatography Biomarkers Ion 191.00 (190.70 to 191.70): SJ118S.D FID1 A, (SHAUN\SJ118.D) PA Abundance 10 3000 8000 7000 2500 6000 2000 5000 1500 Moreno Pr 4000 1000 end-member oil (Oil City (Oil City oil) oil 3000 11 Ph 12 500 2000 13 15 2 5 14 7 16 17 18 19 20 0 1 3 4 8 1000 9 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 min 6 0 Time--> 75.00 80.00 85.00 90.00 95.00 Time (min) Ion 191.00 (190.70 to 191.70): SJ103S.D FID1 A, (MENG\SJ103.D) Abundance PA 10 1000 Pr 50000 800 40000 Ph 600 30000 (SJ103) 400 Moreno oil Moreno 11 in Vallecitos in 20000 12 200 2 13 10000 1 5 7 14 15 4 8 16 3 17 18 19 20 6 9 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 min Time--> 0 58 75.00 80.00 85.00 90.00 95.00 Time (min) Figure 2b. Whole-oil gas chromatogram and 191 m/z ion mass fragmentogram for Moreno end-member oil and selected Moreno oil in Vallecitos. Ion 217.00 (216.70 to 217.70): SJ121S.D Biomarkers Ion 217.00 (216.70 to 217.70): SJ118S.D Abundance Abundance Moreno 35000 Kreyenhagen 3200 10 end member source rock 3000 10 2800 oil (Oil City oil) 30000 extract 2600 1 16 1 2400 25000 2200 3 16 17 20 4 2000 3 8 4 6 7 20000 7 15 20 1800 8 11 14 6 19 1600 2 5 9 11 14 15000 18 1400 2 5 13 1200 13 15 17 12 1000 12 10000 9 19 800 18 600 5000 400 200 0 0 Time--> 64.00 66.00 68.00 70.00 72.00 74.00 76.00 78.00 80.00 Time--> 64.00 66.00 68.00 70.00 72.00 74.00 76.00 78.00 80.00 Moreno oil Ion 217.00 (216.70 to 217.70): SJ112S.D Kreyenhagen oil Ion 217.00 (216.70 to 217.70): SJ113S.D Abundance in Vallecos Abundance 10 in Vallecitos 5500 11000 5000 10 10000 16 4500 9000 8 15 8000 4000 1 16 7 17 8 20 19 7000 1 3500 9 20 3 4 3 14 18 7 11 6000 3000 4 14 6 11 2500 5000 5 6 13 15 2000 2 5 4000 9 13 17 12 2 12 1500 3000 18 19 1000 2000 500 1000 59 0 0 Time--> 64.00 66.00 68.00 70.00 72.00 74.00 76.00 78.00 80.00 Time--> 64.00 66.00 68.00 70.00 72.00 74.00 76.00 78.00 80.00 Figure 2c. Whole-oil gas chromatogram and 217 m/z ion mass fragmentogram for Kreyenhagen source rock extract, Moreno end-member oil, and selected Kreyenhagen and Moreno oils in Vallecitos. PC1 SJ110(CM) SJ118(CM) SJ122(EK) Seep 2 PC3 SJ119(EK) PC2 Oils(CM) Oils(EK) SJ121(EKE) Figure 3. PCA for all oil samples and seeps in our dataset based on selected biomarker and isotope ratios (Table 2). CM: oil from Cretaceous Moreno Formation; EK: oil from Eocene Kreyenhagen Formation; EKE: Eocene Kreyenhagen source rock extract. Open diamond and solid square symbols indicate the oil samples in 60 the Vallecitos syncline. Biomarkers have been altered in biodegraded Seep 2 and SJ119. Ternary diagram of C 27-C 29 C-ring monoaromatic steroid distributions in crude oils and rock extract Legend 0 1 SJ110(Moreno Reservoir) SJ118(CM) SJ122(EK)&121(EKE) SJ119(EK) 0.2 0.8 Oil(CM) Oil(EK) 0.4 0.6 %C27 %C 28 0.6 0.4 0.8 0.2 1 0 0 0.2 0.4 0.6 0.8 1 %C 29 Figure 4a. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oil samples. Open symbols indicate the oil samples in the 61 Vallecitos syncline (see Figure 3 for CM, EK, and EKE). Regular steraneαααR (m/z=217) ternary diagram 0 1 Legend SJ110(Moreno Reservoir) SJ118(CM) SJ122(EK) &121(EKE) 0.2 0.8 Oil(CM) Oil(EK) % 2 aR 8 a 0.4 0.6 a a a 9 a 2 R % 0.6 Seep 2 0.4 0.8 0.2 1 0 0 0.2 0.4 0.6 0.8 1 %27 aaaR % C27 αααR Figure 4b. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oils. Open symbols indicate the oil samples in the 62 Vallecitos syncline (see Figure 3 for CM, EK, and EKE). 0.95 0.90 0.85 0.80 0.75 0.70 TA-Dino/(TA-Dino+3MeStig) 0.65 0.2 0.3 0.4 0.5 0.6 0.7 3-/(3- + 4-methylstigmastane 20R) Figure 4c. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oil samples. Open 63 symbols indicate the oil samples in the Vallecitos syncline (legend see Figure 4a). 4.0 Condensate 3.0 2.0 ETR 1.0 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Oleanane Index Figure 4d. Comparison of oils from the Vallecitos syncline with well studied Kreyenhagen and Moreno oil samples. Open 64 symbols indicate the oil samples in the Vallecitos syncline (legend see Figure 4a). Moreno L. Kreyenhagen 42 Ma %Ro=0.6 19 Ma Ro=0.6 65 Figure 5a. Plot of time versus vitrinite reflectance of the two source rocks for the calibrated model at 1D location. 66 Figure 5b. Burial history curves with transformation ratio (TR) of two source rocks for the calibrated model at 1D location. After California Division of Oil and Gas (CDOG), 1982 G 1D Model Location H Kreyenhagen Fm. Yokut Ss 67 Figure 6. Geological profile along the line GH (Figure 1a) in the Vallecitos syncline. Hot Model Cold Model Combination Model Figure 7a. Plot of calculated (line) and measured (symbols) %Ro versus depth for the models with three different heatflow scenarios. Open circles indicate measured %Ro data, cross symbols indicate converted Ro from measured Tmax data in the NETEX1 well. 68 Figure 7b. Plot of calculated (line) and measured (symbols) %Ro versus depth for the model. Open circles indicate measured %Ro data, cross symbols indicate converted Ro from measured Tmax data in the NETEX1 well. 69 L. KreyenhagenFm. Moreno Fm. Immature(0.25-0.55) Early Oil(0.55-0.7) Main Oil(0.7-1.0) Late Oil(1.0-1.3) Wet Gas(1.3-2) Dry Gas(2-4) Overmature(>4) 70 Figure 8. Modeled present-day thermal maturity of source rocks expressed as vitrinite reflectance (% Ro) in the 2D calibrated model. Kreyenhagen-Yokut(.) Petroleum System Events Chart U. KreyenhagenFm, L. KreyenhagenFm, San Joaquin Fm. Etchegoin Fm. Monterey Fm. Monterey aoh Fm. Panoche Arroyo Hondo Hondo ArroyoShale Temblor Fm. Temblor Moreno Fm. CantuaSandstone San Carlos Yokut Yokut Sandstone Sandstone Domengine Fm, Unnamed unnamed unnamed Cerros Shale Cerros structural Not Studied Not Studied 71 Figure 9a. Events chart for the Kreyenhagen-Yokut(.) petroleum system shows the time of deposition of the essential elements and processses of this petroleum system. Moreno-San Carlos(.) Petroleum System Events Chart U. KreyenhagenFm, L. KreyenhagenFm, San Joaquin Fm. Etchegoin Fm. Monterey Fm. Monterey Panoche Fm. Arroyo Hondo Hondo ArroyoShale Temblor Fm. Temblor Moreno Fm. CantuaSandstone San Carlos Yokut Yokut Sandstone Sandstone Domengine Fm, Unnamed unnamed unnamed Cerros Shale Cerros structural Not Studied Not Studied 72 Figure 9b. Events chart for the Moreno-San Carlos(.) petroleum system shows the time of deposition of the essential elements and processses of this petroleum system. CHAPTER 2 OIL FAMILIES AND THEIR INFERRED SOURCE ROCKS IN THE BARENTS SEA AND NORTHERN TIMAN-PECHORA BASIN, RUSSIA 73 OIL FAMILIES AND THEIR INFERRED SOURCE ROCKS IN THE BARENTS SEA AND NORTHERN TIMAN-PECHORA BASIN, RUSSIA Meng He1, J. Michael Moldowan1, Alla Rovenskaya2, Kenneth E. Peters1,3 1. Stanford University, Department of Geological & Environmental Sciences, Stanford, CA, 94305, USA 2. The Foundation for East-West Cooperation, Moscow, 119234, Russia 3. Schlumberger, 18 Manzanita Place, Mill Valley, CA, 94941, USA ABSTRACT A geochemical study of thirty-four oil samples was conducted to understand the types and distributions of effective source rocks and evaluate the geographic extent of the petroleum systems in the Barents Sea and northern Timan-Pechora Basin. Taxon-specific, age-related and source–related biomarkers and isotope data provided information on the depositional environment of the source rock, source input, and source age of the oil samples. A relationship between biomarker and diamondoid concentrations was used to identify mixed oils having both oil-window and highly cracked components. Compound- specific isotope analyses of diamondoids and n-alkanes were used to deconvolute co- sourced oils and identify deep source rocks in the basin. Results suggest five major source rocks in the Barents Sea and the northern Timan-Pechora Basin: Upper Jurassic shale, Lower-Middle Jurassic shale, Triassic carbonate/shale, Devonian marl and Devonian carbonate. The Upper and Lower-Middle Jurassic source rocks are dominant in 74 the Barents Sea. Triassic source rock consists of carbonate in the onshore part of northern Timan-Pechora Basin, and marine shale in the Barents Sea. The Devonian Domanik Formation carbonate source rock extends offshore into the southern Barents Sea. High- maturity Domanik Formation could also be a secondary source rock for most of the mixed oils in the northern Timan-Pechora Basin. This detailed geochemical study provides new understanding of petroleum systems in the Barents Sea and northern Timan-Pechora Basin. Keywords: Barents Sea, age-related biomarker, oil-oil correlation, maturity, oil family, diamondoids, cracking extent, mixed oil, deep source, compound-specific isotope analysis INTRODUCTION The former Soviet Union is the largest producer of petroleum in the world and it still has considerable potential for oil and gas exploration. The Timan-Pechora Basin has been a prolific producer of oil, condensate and gas in the Arctic coastal region of northern Russia (Figure 1a & 1b). The well-established hydrocarbon trend onshore suggests an offshore extension that remains little studied and relatively unexplored. The Barents Sea includes the north Norwegian and Russian coasts, Novaya Zemlya, Franz Joseph Land, Svalbard archipelago, and the eastern margin of the Atlantic Ocean, an area covering about 1.25 million km2 (Figure 1a). Petroleum geologists and geochemists are becoming more interested in the Barents Sea Basin (especially the Russian Barents Sea) because of 75 the increasing value of petroleum and the great potential for oil and gas in this area. The literature from studies of this area is limited. Since the former Soviet Union only recently opened to the West, little information is available about the petroleum geochemistry of most Russian basins. To better evaluate the prospects in this basin requires understanding of the types and distributions of effective source rocks (Peters and Cassa, 1994), and the geographic extent of the petroleum systems (Magoon and Dow, 1994). According to Dalland et al. (1988), Larsen et al. (1993), Ostisty and Cheredeev (1993), Bjorøy et al. (1978), Johansen et al. (1993) and Ulmishek (1982), there are numerous potential source rocks in the Barents Sea region. These include marine Devonian, Upper Pennsylvanian-Permian, Triassic, and Jurassic strata. However, most publications on petroleum systems focus on the Norwegian Barents Sea rather than the Russian Barents Sea. The previous studies do not fully consider or document deep source rocks and mixed oils composed of high and low maturity contributions from multiple source rocks or from a single source rock. We conducted biomarker and diamondoid studies in the Barents Sea and northern Timan-Pechora Basin. In the biomarker study, we performed oil-oil correlation to identify oil families having one source rock using age- and source-related biomarkers. In addition, we also recognized mixed oils from multiple source rocks based on biomarker data and compound-specific isotope analysis of n-alkanes. In the diamondoid study, we identified the mixed oil samples that contain oil-window maturity oil and highly cracked oil components. Compound-specific isotope analysis of diamondoids (CSIA-D) is used to identify the deep source contributions to those mixed oil samples. Thirty-four oil samples from the Russian Barents Sea and northern Timan-Pechora Basin (Figure 1a & 1b; Table 76 1) were analyzed in the Molecular Organic Geochemistry (MOG) laboratory at Stanford University. Our interpretations assume that all field samples from the study area were properly labeled as to origin and we found no evidence to the contrary. There are no source rock samples in this study. All of the fluid samples have different physical properties, but we refer to them simply as oils. Our data provide an excellent opportunity to evaluate the hydrocarbon resource potential of the Barents Sea and northern Timan-Pechora Basin. The results of this study provide a better understanding of the petroleum systems in this region. In addition, this study identifies new petroleum systems related to deeply buried source rocks. Improved understanding of such source rocks can provide new exploration targets for oil, condensate, and gas in this frontier petroleum province. Such new insights may also be crucial for making exploration decisions both within the province and in neighboring blocks as they become available for exploration. Finally, we show that some of the non- routine molecular geochemical methods employed in this study can open new vistas for oil and gas exploration in any basin. METHODS Compared with most bulk geochemical parameters, source- and age-related biomarker ratios for oil samples are particularly useful to describe facies and depositional environment of the source rock, while also successfully establishing oil-oil and oil-source correlations. Biomarkers in oil samples can be applied to infer depositional environment, 77 organic facies, thermal maturity and even the age of the source rock (Peters et al., 2005). These data can be extremely helpful in oil-oil correlation studies. Oil cracking is a process where complex hydrocarbons are cracked to smaller molecules by heating (Schoell and Carlson, 1999; Dahl et al., 1999). We use a method that employs quantitative analysis of both biomarkers and diamondoids (Dahl et al., 1999) to better understand oil cracking. The extent of thermal alteration can be assessed by quantitative analysis of diamondoids, which have a diamond structure that displays high thermal stability. During oil cracking, the concentration of diamondoids in oil increases. In contrast, most biomarkers have relatively low thermal stability and their abundance decreases during cracking. Biomarkers are also useful to describe the extent of oil cracking. The C29 ααα20R sterane (stigmastane) was selected for analyses of oil cracking by Dahl et al. (1999) because it decreases to near the detection limit during oil cracking while the concentration of certain diamondoids (3- and 4-methydiamantanes) dramatically increases. Thus, mixtures of non-cracked (low maturity) and cracked (high maturity) oils show both significant stigmastane concentration and elevated diamondoid concentrations. To increase the accuracy of biomarker analysis, a series of separations was conducted before the analysis. First, silica-gel chromatography was applied to separate oil into saturates and aromatics. Second, the zeolite ZSM-5 was used to remove normal alkanes (n-alkanes or paraffins) from the saturate fraction. Before removing normal alkanes, saturate fractions were spiked with internal standards. For this project, a mixture of 5β-cholane and highly branched isoprenoids (HBI) having a m/z 238 mass spectral fragment was added to the saturates as an internal standard before gas chromatography- 78 mass spectrometry (GC/MS) (Seifert and Moldowan, 1979). Saturate fractions were treated with high Si/Al Z5M-5 zeolite (silicalite) to remove n-alkanes. All of the crude oils were quantitatively analyzed by gas chromatography-flame ionization detection (GC- FID). The biomarkers (terpanes) and diamondoids in the branched, cyclic, and aromatic fractions were analyzed by selected ion recording-gas chromatography mass spectrometry (SIR-GCMS). Quantitative metastable reaction monitoring (MRM-GCMS) was used to analyze steranes (e.g., regular steranes, such as cholestanes, ergostanes and stigmastanes, diasteranes, dinosteranes), as well as certain terpanes (e.g., bicandinanes, tetracyclic polyprenoids, diterpanes) (Moldowan et al., 2004). Stable carbon isotope analyses of crude oils and saturate and aromatic fractions (Table 2) were completed in the Stable Isotope Biogeochemistry Laboratory (SIBL) at Stanford University. Analysis of diamondoids was conducted using the saturate fraction of each oil sample. A deuterated diamondoid internal standard containing D4 adamantane, D3 1- methyladamantane, D4 diamantane, D3 methyldiamantane, D5 ethyldiamantane, cholane and D4 triamantane was added to each oil sample before the silica-gel chromatography separation. SIR-GCMS analysis of saturate fractions was carried out to measure the distribution of diamondoids in each saturate fraction. Adamantanes and diamantanes were quantitatively analyzed by monitoring m/z 135, 136, 149 and 187, 188, 201 mass chromatograms, respectively (Wingert, 1992). Quantification of diamondoids was achieved by integration of peak heights with reference to the standards. Compound- specific isotope analyses of diamondoids (CSIA-D) and n-alkanes were completed by GB Scientific Inc. on selected oil samples. 79 Chemometric analysis was used to classify and assign confidence limits for identifying genetic oil families in the Barents Sea and northern Timan-Pechora Basin. Chemometircs is a collection of multivariate statistical methods for recognizing patterns in large data sets. It allows us to identify and remove noise from the data, show affinities among parameters, better understand the true structural relationship behind the data and make accurate predictions about unknown samples. Two common techniques in chemometric analysis are hierarchical cluster analysis (HCA) and principal components analysis (PCA). For the chemometric analysis, we selected twenty biomarker and two isotope ratios (Table 2) based on our geochemical expertise to differentiate oil families in terms of age, organic input and depositional environment of the source rocks. HCA and PCA were completed using Pirouette (Infometrix, Inc.). Cluster distances between samples in HCA were calculated and visualized in a dendrogram (Figure 2a). The cluster distance is a relative measure of the degree of similarity among samples. In HCA for this study, each different parameter (biomarker or isotope ratio) has equal weight or significance. The Pirouette HCA used autoscale preprocessing, Euclidean metric distance, and incremental linkage options. PCA reduces the dimensionality of a data set that is composed of many variables, while retaining most of the information in the data set. It transfers a number of possibly related variables into a smaller number of uncorrelated variables, the principal components (Figure 2b). This transformation does not change the structural relationships underlying the data. The first three principal components generally describe most of the variance within the dataset. Three-dimensional plots are built by using the first three principal components as axes to generate the best three- dimensional separation of the samples into genetic families (Figure 2b). 80 PETROLEUM GEOLOGY The Barents Sea Basin was considered a foredeep basin of the Uralian tectonic belt and acted as a major catchment area for sediments shed from the Ural Mountains in the Late Paleozoic-Mesozoic (Gramberg, 1988). With an average water depth about 350 m, it is one of the largest areas of continental shelf on the globe, covering about 230,000 sq. km. The Barents Sea Basin formed by two major continental collisions (about 400 Ma and 240 Ma) and subsequently opened by continental separation. Because of the two collisions, the basement of this basin is dominated by Caledonian and Uralian trends, while extensional tectonic movements dominate its later Paleozoic and Mesozoic history. These tectonic events created the major rift basin traversing the Barents shelf and the platforms (Dore, 1995). Due to its special geographic location, this basin was strongly influenced by a marine depositional environment affected by the tectonic setting and climate changes. Carbonate deposition with some episodes of evaporite deposition prevailed over wide areas of the shelf in the Late Paleozoic. Clastic deposition under more temperate conditions became dominant through the Mesozoic. The basin is characterized by an impressive thickness of ~12 km of Permian and younger sediments, especially Triassic deposits, which locally reach ~6-8 km in thickness (Dore, 1995). The western margin of the Barents Sea shelf was characterized by Cenozoic tectonics and sedimentation associated with the northern Atlantic continental separation. Thick Cenozoic sediments were deposited before and after the beginning of passive continental drifting in the Oligocene (Johansen et al., 1993). Sediment accumulation in 81 this area of the basin was accelerated by uplift and erosion of the Barents Sea shelf to the east (Nyland et al., 1992). Erosion and redepositon were intense during the Pleistocene glaciations (Dore, 1995). Lower-Middle Jurassic sandstone is the major reservoir rock, having high porosity and permeability in the Barents Sea Basin (Dore, 1995). However, Triassic sandstone also exists in this area, although it has inferior reservoir quality compared with the Jurassic sandstone. Ninety-seven percent of the known recoverable reserves are from Jurassic reservoirs in the eastern Barents Sea Basin (Petroconsultants, 1996). Thick and widespread Jurassic and Triassic shales provide good local to regional seal rocks, as do Lower Cretaceous shales (Johansen et al., 1993). Fault-bounded and dome-like structural traps are dominant in the Barents Sea Basin because of the intense tectonics. On the Russian side of the southern part of the Barents Sea Basin, the prolific northern Timan- Pechora Basin provided a major incentive to extend exploration offshore. The offshore part accounts for 30% of the total area of the Timan-Pechora Basin Province, ~131,700 km2, which includes islands up to 5400 km2 in total area (Lindquist, 1999b). This offshore segment has not been studied as well as the onshore part of the Timan-Pechora Basin. However, with its wide shelf, it has great potential for oil and gas exploration. Paleozoic carbonate rocks comprise the principal reservoirs for the onshore Timan- Pechora Basin. Oil and gas are found in Paleozoic reservoirs ranging in age from Ordovician to Permian. Lower Mississippian and Permian carbonate (limestone and dolomite) reservoirs formed in the offshore part of the northern Timan-Pechora Basin extending into the Barents Sea shelf, as in the Prirazlomnoye oil field. Trapping is generally within bioherm structures (reef-like organic build-ups). The bioherms were 82 exposed subaerially and underwent leaching by meteoric water, which can enhance reservoir properties (Wilson, 1975). Siliciclastic and carbonate reservoirs are the main reservoir types in the northern Timan-Pechora Basin. The siliciclastic reservoirs average 16% porosity and 154 md permeability, and the carbonate reservoirs average 13% porosity and 208 md permeability (Petroconsultants, 1996). The Triassic sandstone reservoirs have superior reservoir properties compared with the other reservoir types in the northern Timan-Pechora Basin, but they are thin and discontinuous in the Barents Sea Basin. The Triassic sandstone reservoirs in the northern Timan-Pechora Basin have the highest porosity at 28% and average permeability from 75 to 345 md (Lindquist, 1999b). In the Barents Sea Basin, thick overburden rock and complicated tectonics created a variable thermal history. Mesozoic rifting produced the highest regional thermal gradient, and Cenozoic uplift resulted in significant thermal cooling with possibly hundreds of meters of erosion. Petroleum could have been generated by Late Triassic time from the rapidly buried Lower and Middle Triassic source rocks (Lindquist, 1999a). SOURCE-ROCK GEOLOGY Published source rock and organic geochemistry studies of the Barents Sea Basin are limited, especially for the Russian Barents Sea. The Lower Paleozoic strata in the Russian Barents Sea are poorly studied. Four different source rock intervals in the Barents Sea and northern Timan-Pechora Basin are described in the literature, as discussed below. Upper Devonian (Domanik facies) 83 Upper Devonian (Frasnian) Domanik Formation, organic-rich strata in the northern Timan-Pechora Basin are generally considered to be the main hydrocarbon source rock in this region. The Domanik Formation is composed of black, siliceous shales and limestones. It contains Type II oil-prone kerogen and has total organic carbon (TOC) up to 20%. The Domanik Formation was deposited in a tectonically controlled deep-water trough and was gradually filled by prograding clastic wedges between carbonate intervals during Late Devonian-Tournaisian time (Ulmishek, 1982). Due to its areal distribution and the history of formation of clastic wedges on margins of the deep- water trough, the Domanik facies might extend a short distance offshore along the continuation of the Devonian graben-rift (Ulmishek, 1985). Because of its high economic importance, much speculation has been made as to whether the Domanik broadens westward and northward into the Barents Sea Basin. Upper Pennsylvanian-Lower Permian The Upper Pennsylvanian- Lower Permian strata have various facies in the Barents Sea and northern Timan-Pechora Basin. On Spitsbergen and Bear Islands, the Upper Pennsylvanian-Lower Permian layers are present as a carbonate sequence, which may have been deposited in local lagoons behind reefs. This carbonate sequence was deposited by a widespread marine transgression in arid climatic conditions. Restricted distribution and low TOC do not permit the Upper Pennsylvanian –Lower Permian strata to be significant source rocks. The Upper Pennsylvanian –Lower Permian strata in the northeastern Timan-Pechora Basin are composed of black marine shale with TOC in the range 0.75-1.00% (Ulmishek, 1982). This facies may extend a short distance into the southeastern corner of the Barents Shelf. 84 Lower to Middle Triassic The Triassic section is the primary source rock interval in the Barents Sea. It is composed of black organic-rich shale with TOC in the range of 2-8% and a tendency to increase eastward. Almost 8%-10% of the TOC can be extracted as bitumen from the source rock. The Triassic section contains mostly type II kerogen deposited under anoxic conditions in the gradually deepening sea (Ulmishek, 1982). The basinal, deep-water facies continue far to the east and cover a significant part of the Barents Sea. Shallow marine and nearshore Triassic facies occur in the South Barents and North Novaya Zemlya depressions. The organic matter in the source rock in this area probably has poor quality. The Triassic section in the northern Timan-Pechora Basin was likely deposited in a paleo-shelf setting and contains both sapropelic and humic organic matter (Zakcharov and Kulibakina, 1996). However, Triassic source rock could be early mature in the onshore part of northern Timan-Pechora Basin (Zakharov and Kulibakina, 1996; Kuranova et al., 1998). The Triassic source rock on northern Kolguyev Island and the adjoining shelf may be buried sufficiently to be mature. Lacustrine and estuarine facies are dominant in this area (Ulmishek, 1985). Upper Jurassic Upper Jurassic black organic-rich shale is also a good source rock in the Barents Sea Basin. It was deposited in a deep-water anoxic environment. Low dilution of organic matter by sediment and restricted circulation of bottom water resulted in a high content of organic matter. These black shales are analogous to the Kimmeridgian Shale in the North Sea and Bazhenov Shale in West Siberia that are both highly productive oil source rocks. The rock has a high content of type II kerogen and the organic-rich facies covers all of 85 the Barents Shelf with the probable exception of narrow marginal areas. In the northern Barents Sea Basin, the Upper Jurassic shale ranges from hundreds to over 1,000 m thick, having TOC 1-9%. In contrast, the Jurassic shale in the central and southern Barents Sea is just 20-30 m thick with TOC of 15-25% (Leith et al., 1993). This organic-rich shale is immature in the eastern Barents Sea Basin. RESULTS AND DISCUSSION The hierarchical cluster analysis (HCA, Figure 2a) dendrogram identifies six oil families based on geochemical data for thirty-four oil samples from the Barents Sea and northern Timan-Pechora Basin. Highly thermally mature oil samples were excluded because secondary processes obscure genetic relationships by altering geochemical parameters. Most of the oil samples are non-biodegraded and a few show light biodegradation. Twenty source-related biomarkers and two isotope parameters were used to construct the dendrogram (Figure 2a). The six identified oil families have broadly similar geochemical characteristics, but may originate from different source rocks or different organofacies (Jones, 1987) of the same source rock. In addition to genetic information, age, lithology and depositional environment of the source rock can be inferred from the detailed biomarker study, as discussed below. Six oil families were defined and can also be shown in the PCA plot (Figure 2b; Table 1). Oil-oil correlation and geochemical characteristics of oil families Biological markers (biomarkers) are complex molecular fossils derived from once-living organisms (Peters et al., 2005). Biomarkers in crude oil inherit the 86 recognizable carbon structures of natural products synthesized by precursor organisms. Different assemblages of organisms live in different source rock depositional environments. Therefore, various biomarker parameters can be used to evaluate the depositional environment of the source rock. Biomarkers can be measured in both oil and source rock extracts, and they are helpful in source rock-to-oil correlation. In fact, biomarkers provide a method to interpret source rock organofacies when only oil samples are available. Biomarker fingerprints are primarily established by the source of organic matter and depositional environment, but the overprint of maturation is also important. Thus, numerous biomarker parameters should be taken into consideration in order to strengthen detailed correlations. We define a genetic oil family in this paper as a group of oils that were generated and expelled from a single source rock organofacies. Some oil samples may show evidence of mixing, but may be dominated by input from only one major source rock. Variations in oil characteristics due to maturity or post-expulsion alteration processes, such as biodegradation and phase separation, should not alter genetic relationships. Representative gas chromatograms and terpane mass chromatograms for each oil family are shown in Figure 3a, 3b, & 3c. Key biomarker and non-biomarker parameters used in this study to differentiate oil families include Pr/Ph (pristane/phytane), C29/C30 hopane, C33/C34 and C35/C34 homohopane, the distribution of C27, C28, and C29 steranes, and age- related biomarker ratios, such as ETR (extended tricyclic terpane ratio) and triaromatic dinosteranes/(4-methystigmastane or 3-methystigmastane 20R). Maturity-related biomarkers, such as C29 20S/ (20S+20R), C29 ββ/ (ββ+αα), and Ts/ (Ts+Tm) (Ts: 18α-22, 87 29, 30-trisnorneohopane; Tm: 17α-22, 29, 30-trinorhopane) ratios are also examined in this study. Key biomarker parameters used to distinguish different oil families are summarized in Table 2 and details of the biomarker parameters that characterize each oil family are described below: Family I Family I contains eight oil samples from Upper Pennsylvanian, Lower Permian and Triassic reservoirs from Spitsbergen Island, Kolguyev Island and the northern Timan- Pechora Basin (Figure 1a & 1b; Table 1). The oils in this family are characterized by pristane greater than phytane (Figure 3a), which typically denotes a dysoxic to oxic depositional environment. The oils have relatively low ratios of pristane to n-C17 and phytane to n-C18, and stable carbon isotope values of crude oil -27.71 to -29.76‰, saturates -26.52 to -29.83‰, and aromatics -27.55 to -29.66‰. Oils in this family have normal to average tricyclic terpane concentrations, C29 hopane is less than C30, C33 homohopanes are more abundant than C34, and C34 homohopanes are greater than C35. Triaromatic 3-/ (3- + 4-methylstigmastane 20R) is approximately one. A high ETR value (>2) is consistent with Triassic source rock (Holba et al., 2001). However, the biomarkers suggest that there are two different lithofacies of source rock in this family. Samples 91, 67, and 102(1) from northern Timan-Pechora Basin have high C29/C30 hopane ratios (~0.89), while samples 52(1), 78, 12 and 526(a) from Kolguyev Island, onshore of Timan-Pechora, and Spitsbergen Island show low C29/C30 hopane ratios (~0.42). High TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (i.e., TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA- 88 DMD3/C28S) ratios suggest Mesozoic and younger source rocks (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). Family II Family II consists of eight oils from Lower and Upper Devonian reservoirs in the northern Timan-Pechora Basin (Figure 1b; Table 1). This family of oils probably originated from Devonian Domanik source rocks. Oil samples in this family have very negative stable carbon isotopic ratios of crude oil -30.94 to -32.34‰, saturates -31.59 to - 33.13‰, and aromatics -30.25 to -32.03‰. Some classic geochemical parameters, such as pristane/phytane and the distribution of n-alkanes, indicate an oxic depositional environment and terrigenous input to the source rock (Peters et al., 2005; Figure 3a, 3b and 3c). Low C27/C29 and C28/C29 sterane ratios support higher-plant input and high C29/C30 hopane ratios suggest a marl source rock (Peters et al., 2005; Table 2). The C34 homohopanes are more abundant than either the C33 or C35 homohopanes. Low ETR (~ 0.45) and low TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA- DMD3/C28S) ratios imply Paleozoic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). The Family II oil samples have peak oil window maturity based on the maturity-related biomarkers. Family III Family III consists of five oil samples from Devonian and Lower Permian reservoirs in the Pechora Sea and the northern Timan-Pechora Basin (Figure 1b; Table 1). This family of oils probably originated from a different organofacies of the Domanik Formation than Family II. The oils in this family display biomarker distribution similar 89 to Family II oils. Pristane/phytane ratios less than one (Figure 3b) for this family indicate an anoxic depositional environment. The stable carbon isotopic ratios for crude oils in this family are -30.10 to -31.54‰, saturates -30.97 to -31.87‰, and aromatics - 28.64 to -30.47‰. Low TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA-DMD3/C28S) ratios imply Paleozoic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). However, high C29/C30 (> 70%) hopane ratios strongly indicate a carbonate source rock for this oil family. The ETR ratios for this oil family (~ 1) are higher than those of Family II (~0.45). The C19/ (C19+C23) and C24 tetracyclic terpane/C23 tricyclic terpane (Tet/C23) ratios for Family III are lower than those of Family II. Family III has higher C22/C21 ratios than Family II. Family IV Family IV contains six oil samples in Devonian and Lower Permian reservoirs from the northern Timan-Pechora Basin (Figure 1b; Table 1). The oils in this family are characterized by pristane/phytane ratios greater than one (Figure 3b), which indicates a dysoxic to oxic depositional environment. The isotope values for crude oils are -28.8 to - 30.48‰, saturates -28.81 to -30.97‰, and aromatics -28.64 to -30.22‰. Most oils in this group were slightly biodegraded, as evidenced by an unresolved mixture (hump) on gas chromatograms. Low C27/C29 and C28/C29 ratios indicate terrigenous source input. Low TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA-DMD3/C28S) ratios also probably imply a Paleozoic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). 90 Family V Family V consists of three oils samples from Permian and Lower Triassic reservoirs on the Pechora shelf and Kolguyev Island (Figure 1a; Table 1). These oils are characterized by high pristane/phytane ratios that indicate a dysoxic to oxic depositional environment (Figure 3c). The stable carbon isotopic values of crude oils are -28.07 to - 29.22‰, saturates -27.67 to -29.3‰, and aromatics -26.13 to -28.27‰. Bimodal gas chromatograms for these oils indicate terrigenous source input. High C29/C27 and C29/C28 sterane ratios also show higher-plant input to this family of oils. Relatively low C33, C34 and C35 homohopane peaks on the m/z 191 ion chromatogram also indicate dysoxic to oxic depositional conditions in the source rock of Family V (Figure 3c). These oils have reached peak oil window maturity. Bicadinane exists in this family. Low ETR, (<2) and high TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA- DMD3/C28S) ratios indicate that this oil family could be from Jurassic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). The low C26 tricyclic terpane ratios (C26T/Ts< 1.0) for this family are diagnostic of Jurassic or younger source rocks (Peters et al., 2007). Family VI Family VI contains four oil samples from Lower and Middle Jurassic reservoirs. Three of the samples are from Shtokmanovskoye field in the Barents Sea from Lower Jurassic (one) and Middle Jurassic (two) reservoir rocks and one oil sample is from Spitsbergen Island (Figure 1a; Table 1). Family VI oil samples are characterized by high pristane/phytane ratios (>3) that indicate an oxic depositional environment (Figure 3c). 91 The stable carbon isotope values of crude oils are -27.92 to -29.47‰, saturates -28.8 to - 30.07‰, and aromatics -26.79 to -29.14‰. Gas chromatograms of these oils show a small hump indicating light biodegradation. This family has 13C-rich stable carbon isotope ratios for crude oil (-28.07 to-29.47‰), saturate hydrocarbons (-28.80 to - 30.07‰), and aromatic hydrocarbons (-27.31 to-29.14‰). The high C19/ (C19+C23), low C22/C21 and high C24/C23 tricyclic terpane ratios and elevated %C29 steranes may indicate paralic deltaic marine shale source rock with higher plant-input (Peters et al., 2005). The elevated C29/C30 hopane ratio suggests a marine marl source rock. Low ETR (<2) and high TA-Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA- DMD3/C28S) ratios indicate that this oil family could originate from Jurassic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). Source rock interpretation from oil geochemistry Since no source rock samples were analyzed in this study, direct oil-source correlation could not be conducted. However, geochemical characteristics of the oil samples were used to infer the source rock organofacies (Peters et al., 2005). In addition, understanding of the depositional environment of source rock can be improved by comparison of the data with published source rock and oil data from the general area of the study. The extended tricyclic terpane ratio (ETR) can be used to distinguish crude oil generated from Triassic and Middle-Upper Jurassic source rocks (Holba et al., 2001). Families I and IV have ETR ≥2 and therefore could be generated from Triassic source rock. Two lithofacies for the source rocks of Family I are indicated by the biomarker 92 parameters: a carbonate facies in the onshore part of northern Timan-Pechora Basin, and a deep marine shale facies in the Pechora Sea and Spitsbergen. Families II, III, V and VI show ETR ≤ 2 with most < 1.2, which could indicate Jurassic source rock. Triaromatic dinosteroids are generally abundant in Mesozoic samples, but are below detection limits for the vast majority of Paleozoic marine samples (Moldowan et al., 2001). High TA- Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA-DMD3/C28S) ratios in Families I, V, and VI suggest Mesozoic and younger source rock. In contrast, low TA- Dino/ (TA-Dino+3-methylstigmastane 20R) (TA-Dino=C29 triaromatic dinosteranes) and C28 triaromatic desmethyldinosterane/C28 stigmastane (TA-DMD3/C28S) ratios in Families II, III, and IV imply Paleozoic source rock (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). Bicadinanes may be derived from resins produced by some angiosperms (van Aarssen et al., 1992). They tend to be absent or below detection limits in oils generated from pre-Jurassic source rock, and begin to occur and increase in younger oil samples (personal communication, Barbanti and Moldowan, 2002, unpublished data). Summons et al. (1995) report significant bicadinanes in all of the Jurassic oil samples that they studied from the Perth Basin. The high bicadinane index for Family V indicates that they originated from Jurassic or younger source rock. In addition, the geochemical characteristics of Family V oils are similar to those of oils and rock extracts from the Upper Jurassic Bazhenov Formation in nearby Western Siberia, such as high C26 tricyclic terpane ratios, low C19/ (C19+C23), low C22/C21, high C24/C23, high % C29 steranes, low C28/C29 sterane ratios, low C29/C30 hopane ratios (Peters et al., 1993, 1994, 2007). 93 Although the oil samples in Families V and VI are similar, distinct biomarker ratios of Family VI, such as higher C26 tricyclic terpane ratios, % C29 steranes, C19/ (C19+C23), and C29/C30 hopane ratios, and lower C22/C21, C24/C23, and C28/C29 sterane ratios than those of Family V (Table 2), are similar to published geochemical features of the Lower-Middle Jurassic Tyumen Formation (Peters et al., 1993, 1994, 2007). Family II and III oils show low pristane/phytane ratios (<2), dominant C28 and C29 steranes, C24 tetracyclic > C26 tricyclic terpanes, and C29 < C30 hopanes (Table 2). These two oil families have smooth distributions of normal alkanes with maxima at C11-C15. These geochemical characteristics are similar to those of source rock extracts from the Upper Devonian Domanik Formation (Abrams et al., 1999). This suggests that Families II and III originated from the Domanik Formation. Similar compound-specific isotope analyses of n-alkanes for selected oil samples from both families support the Domanik source rock (Figure 4). However, the families could be from different organofacies of the Domanik Formation because Family III has a high C29/C30 hopane ratios (>0.85), indicating carbonate source rock, while Family II has low values indicating marl source rock. Age-related biomarker ratios show that Family IV oil samples may originate from Paleozoic source rock. However, the geochemical features of Family IV differ from those of Families II and III. Compound-specific isotope analyses of n-alkanes and diamondoids for selected oil samples indicate that Family IV represents mixed input from Domanik and Triassic or Domanik and Jurassic source rocks, as discussed below. Identification and de-convolution of the mixed oils and deep source interpretations 94 Mixing of oil types can be investigated using gas chromatography, mass chromatograms of biomarkers, stable carbon isotope ratios, and chemometrics. Age- and lithology-related biomarker parameters and oil-oil correlation ternary plots are also powerful tools to identify oil mixtures (Peters et al., 2005). In the principal components analysis (PCA) of the data set, samples 144, 81(3) and 81(2) show features that suggest mixing (Figure 2b). The high TA-Dino and TA-DMD3/C28S ratios for sample 81(3) indicate a Mesozoic co-source for this oil. Many of the biomarker ratios indicate that samples 80(1) and 81(2) were mostly generated from the Domanik Formation, but elevated TA-Dino and TA-DMD3/C28S for these samples 80(1) and 81(2) reflect a minor Mesozoic co-source (Moldowan et al., 1996; Moldowan et al., 2001; Barbanti et al., 2011; Table 2). By combining age-related biomarker ratios with PCA results for these two oil samples, it can be concluded that sample 80(1) may have minor Triassic source input and sample 81(2) may have minor Jurassic source input. This result is also supported by compound-specific isotope analysis (CSIA) of the n-alkanes. End-member oil samples representing each oil family and proposed mixed oils were selected for CSIA of n-alkanes (Figure 4). These CSIA results show similar isotopic ratios for Families II and III, supporting the interpretation that both of families are from the Domanik Formation. PCA together with the CSIA data show that for samples 144, 44, and 81(3) from Family IV, the Triassic is most likely the major source rock, while the Devonian Domanik is a secondary source. For sample 50 from Family III, the Domanik is a major source and the Triassic is a secondary source (Figure 2b & 4). In addition, sample 144 appears to have a Jurassic co-source due to the presence of bicadinane. 95 Based on the relationship between the two diamondoids (3- and 4- methyldiamantanes) and stigmastane (Dahl et al., 1999) fourteen oil samples in this data set can be interpreted as mixtures of low to moderate maturity oil containing biomarkers and high-maturity cracked oil rich in diamondoids (Figure 5). The quantities of individual diamondoids in the oil samples are shown in Table 3. Before the extent of oil cracking is estimated, the diamondoid baseline for each oil family is determined by using the concentration of 3- and 4-methyldiamantanes in a group of non-cracked, non-biodegraded and non-fractionated oil samples from the same source rock. Due to the limited number of samples from each family, we determined the approximate diamondoid baseline using the minimum diamondoid concentration for oil samples generated from the same source rock. The extent of oil cracking for each sample was calculated using the formula (1-C0/Cc)*100, where C0 is the diamondoid baseline and Cc is the measured methyldiamantane concentration in any oil sample. The diamondoid baseline for each oil family and the extent of oil cracking are listed in Table 3. Samples 91, 67, 102(1) and 12 from Family I, samples 54, 274, 81(4) and 44 from Family IV, and sample 151 from Family V have high concentrations of diamondoids and relatively high concentrations of biomarkers, indicating strongly cracked oil mixed with low maturity oil. Samples 526(a) from Family I, 81(2) from Family II, 81(3) from Family IV, 150 from Family V and 146 from Family VI could be mixtures of light to moderately cracked oil with low maturity oil due to the relatively low concentrations of diamondoids and biomarkers in these samples. The remaining oil samples have not undergone cracking. In this study, compound-specific isotope analysis of diamondoids (CSIA-D) was used to identify the highly cracked component in mixtures of high- and low-maturity oil. 96 Non-cracked oil from each oil family (end member oil) and some representative mixtures were selected for CSIA-D (Figure 6). Jurassic oil samples show diamondoids that are enriched in 13C, while the proposed Domanik oil samples are relatively depleted in 13C (Figure 6; Table 3). Triassic oil samples show diamondoid isotope values intermediate between those of the putative Jurassic and Domanik oil samples. Sample 151, which contains a highly cracked oil, and sample 220, a Jurassic-sourced end member, show similar diamondoid isotope values, which indicates that the highly cracked portion of sample 151 is from deep high-maturity Jurassic source rock. Different CSIA-D results between Triassic-sourced samples 78 (end member oil) and 52(1) and mixed samples 102(1) and 67 from Triassic source rock with highly cracked components indicate that there is a deep, high-maturity source providing components to the Triassic low-maturity oil samples. The logical deep-source candidate is the Domanik Formation generating at high maturity. In addition, the Triassic is not buried deeply enough to be a deep-source candidate in the onshore part of northern Timan-Pechora Basin where samples 102(1) and 67 were obtained (Zakcharov and Kulibakina, 1996). The CSIA-D data also support this conclusion. The CSIA-D data for samples 102(1) and 67 are between the Triassic end- member sample 78 and the Domanik end-member sample 22(2). In addition, PCA (Figure 2b) and CSIA of n-alkanes (Figure 4) results are also consistent with this conclusion. Samples144, 44 and 274 from Family IV are proposed as mixtures of Triassic and Domanik sources based on biomarker parameters. The CSIA-D results for those three samples are between the Triassic and Domanik end-members, in agreement with the biomarker results (Figure 2b & 6). Sample 144 has very low concentrations of diamondoids and the CSIA-D result for sample 144 is very similar to that of Triassic oil 97 samples (Figure 6), which supports the biomarker evidence above that this oil has a major contribution from Triassic source rock and minor contributions from Domanik and Jurassic source rock. Sample 81(2) is a mixture of Jurassic and Domanik input based on both biomarkers and the CSIA-D results (Figure 6). In sum, the high-maturity Domanik source rock could be the deep source for several mixed oils having both highly cracked and normal maturity components from Families I and IV in the northern Timan-Pechora Basin. Distribution of oil families and oil migration Integration of the geology and the geochemical data for each oil family can help to predict the areal and stratigraphic distribution of source rocks, which can help to determine the geographic extent of petroleum systems in the Barents Sea and northern Timan-Pechora Basins. The geographic distribution of the six oil families is shown on Figure 1a & 1b and summarized in Table 1. Based on the geochemical data, we propose that Family I, which includes oils from the northern Timan-Pechora Basin, Kolguyev Island and Spitsbergen Island, originated from Triassic source rock. Our result supports the contention that the Triassic sequence covers all of the Barents Sea and northern Timan-Pechora Basin (Ulmishek, 1985). The Triassic source rock in the north onshore part of Timan-Pechora Basin was a carbonate deposited on a paleo-shelf. Most of the source rocks for oil samples from the northern Timan-Pechora Basin and Pechora Shelf were deposited in the transition zones from continental to marine facies, while the Triassic source rock in the Barents Sea and Spitsbergen Island has a deep marine shale facies (Zakharov and Kulibakina, 1996). The thickness of Triassic deposits on the Pechora Shelf increases from south to north. The 98 structure high of the Timan-Pechora Basin resulted from repeated tectonic movement during the Late Permian and Mesozoic, but this activity did not bury the Triassic source rock deeply enough to allow cracking in the northern Timan-Pechora Basin (Zakharov and Kulibakina, 1996). Thus, the Triassic source rock could not be a high-maturity deep source in the northern Timan-Pechora Basin. However, the Domanik Formation was active as a deep high-maturity source rock in this area. The Triassic section also contains good local clay seals, which tend to prevent vertical migration in the offshore part of northern Timan-Pechora Basin (including Tarskoye and Pechano-Ozerskoye fields on Kolguyev Island) and on Spitsbergen Island (including Barentsburg field). However, vertical and lateral migration took place frequently in the the Kolva Megaswell (including Kharyaginskoye, Khylchuyuskoye and Yareyyuskoye fields) and Adzva-Varandey structural area (including Varandey, Trebsa, Naulskoye and Toboiskoye fields), which is where most of the onshore Triassic (Family I) and mixed Triassic-Domanik (Family IV) oils are located (Figure 1b and 2b; Table 1). Oil samples from Families V and VI presumably originated from Upper Jurassic and Lower-Middle Jurassic source rocks, respectively. The oils in Family V are mostly from the Pechora Shelf. Upper Jurassic claystone having thickness of 50-150 m in this area is a good regional seal (Zakharov and Kulibakina, 1996), which makes vertical migration difficult. That may explain why the Family V oil samples from this area are not mixed with oil from other sources. Since the Upper Jurassic source rock is thinner (~20- 30 m) in the central and southern Barents Sea, and has low maturity in the eastern Barents Sea, it is likely not a major source rock for the Shtokmanovskoye field in the southern Barents Sea Basin. Our interpreted results show that the three oil samples from 99 the Shtokmanovskoye field belong to Family VI. Family VI is interpreted to originate from Lower-Middle Jurassic source rock, which may also extend further north to Spitsbergen Island where one Family VI oil sample was collected. Family II and III oils originated from the Domanik Formation, which is generally thought to be the main source rock in the Timan-Pechora Basin. The Domanik Formation consists largely of organic-rich black, siliceous shales and limestones with high TOC, which fits the geochemical characteristics of Family II in this study. In addition, our study proposes a carbonate facies of the Domanik Formation. The oil samples in Family III originated from this carbonate Domanik source rock and are primarily located on the Pechora Shelf and near offshore of the northern Timan-Pechora Basin. Because of the economic importance of the Domanik Formation, many speculate that it extends offshore and broadens westward and northward into the Barents Sea Basin. Our results suggest that the Domanik Formation extends offshore into the Pechora Sea, and that there is a corresponding facies change into carbonate from the onshore siliceous shales. CSIA-D results in this study indicate that the Domanik Formation on the Pechora Shelf has high maturity and is active as a deep source for the mixed oils in this area. Thermal maturity Maturity levels of the oils were assessed based on the following parameters: C29 sterane isomerization ratios, Ts/ (Ts+Tm), TA [C20/ (C20+C28, 20R)] and TA (I)/TA (I+II). The Family I oil samples have a C29 20S/ (20S+20R) sterane ratios of ~55.4% and C29 ββ/ (ββ+αα) 20R sterane ratios of ~65.2%, indicating peak to late oil-window maturity (Table 2). The ratios of Ts/ (Ts+Tm), TA (I)/TA (I+II), and TA [C20/ (C20+C28, 20R)] for Family I oils (~61%, ~45%, and ~44%, respectively) also support this conclusion. 100 However, Samples 67, 91 and 102(1) have relatively low maturity compared with other oil samples in Family I based on these parameters. The relatively high tricyclic terpanes/ hopanes, high Ts/ (Ts+Tm) (Ts: 18α-22, 29, 30-trisnorneohopane; Tm: 17α-22, 29, 30- trinorhopane), high diasteranes content and low concentrations of other biomarker compounds also indicate that some of the oils in Family I have late oil-window maturity. The Family II and III oil samples have typical “oil-window” maturities and some have reached the peak to late oil generation stage. The oil samples in Family IV exhibit early to peak oil window maturity range based on biomarker maturity parameters. The oil samples in Family V show peak oil maturity and those in Family VI have oil window maturity. CONCLUSIONS Based on molecular and isotope evidence we interpreted six oil families representing five major source rocks in the Barents Sea and northern Timan-Pechora Basin. The oil samples in Family I are from Triassic source rock, which is mostly an organic-rich black shale. The Triassic sequence covers most of the Barents Sea and northern Timan-Pechora Basin and representatives of Family I are located in the northern Timan-Pechora Basin, Kolguyev Island and Spitsbergen Island. The Triassic source rock has low maturity and a carbonate lithofacies in the north onshore part of Timan-Pechora Basin. The Triassic source rock in the Barents Sea and Spitsbergen Island consists of deep marine shale facies. The Triassic section also contains good local clay seals, which prevent vertical migration in the offshore part of northern Timan-Pechora Basin 101 (including Tarskoye and Pechano-Ozerskoye fields on Kolguyev Island) and on Spitsbergen Island (including Barentsburg field) (Figure 1b and 2b; Table 1). The oil samples in Families II and III originated from different organofacies of the Devonian Domanik Formation. Our geochemical results show that the Domanik Formation is an effective source rock in the northern Timan-Pechora Basin, which suggests that it extends offshore into the Pechora Sea, having a carbonate lithofacies. The oil samples in Family V originated from Upper Jurassic source rocks located in the Pechora Shelf and southern Barents Sea. Good clay seals in the Jurassic section in this area militate against the mixing of Jurassic oil with other sources. The oil samples in the Shtokmanovskoye field are assigned to Family VI and probably originated from a Lower-Middle Jurassic source rock that may extend further north to Spitsbergen Island based on our geochemical study. Mixed oils were recognized in this study by using biomarker and compound- specific isotope data. The oil samples in Family IV are mostly co-sourced by Triassic and Domanik source rocks and are located in the Pechora Shelf and Adzva-Varandey structural area (including Varandey, Trebsa, Naulskoye and Toboiskoye fields). Active vertical and lateral migration took place in this area, possibly because good local Triassic clay seals do not exist. We believe that the deep source rock for the oils in the northern Timan-Pechora Basin is high-maturity Domanik Formation. ACKNOWLEDGMENTS This work was completed with financial support from the Stanford University Molecular Organic Geochemistry Industrial Affiliates (MOGIA) Program and A.I. 102 Levorsen Research Grant. 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F ield/Area Region Depth (m) Family Age of Re servoir Inferred Source Rock Top Bottom 1 526a Barentsb urg Spitsbergen Island co al mine co al mine Early Perm ian Triassic I 2 52(1) Pechano-Oz erskoye Kolguyev Is land 1554.4 1566.8 Ea rly Triassic Triassic I 3 152 Pechano-Oz erskoye Kolguyev Is land 1538 1561 Ea rly Triassic Triassic I 4 78 Tarskoye Kolguyev Is land 1734 1740 Ea rly Triassic Triassic I 5 67 Severo-Kharyaginkoye Timan P echora (Northern Part) 1554.4 1566.8 Early Triassic Triassic I 6 91 Khylchuyuskoye Timan P echora (Northern Part) 1660 1675 Early Tria ssic Triassic I 7 12 Vostochno-Vasilykovskoye Timan Pechora (North ern Part) 2457 2539 Late Pennsylvania n Triassic I 8 102(1) Yareyyuskoye Timan Pechora (Northern Part) 1735 1741 Early Permian Triassic I 9 22(1) Zapadno-Lekkeyyaginskoye Timan Pechora (Northern Part) 2560 2571 Late Devonnian Devonian Marl II 10 22(2) Zapadno-Lekkeyyaginskoye Timan Pechora (Northern Part) 3050 3097 N/A Devonian Marl II 11 22(3) Zapadno-Lekkeyyaginskoye Timan Pechora (Northern Part) 3118 3183 Early Devonian Devonian Marl II 12 43 Myadseiskoye Timan Pechora (Northern Part) Bottom Hole Bottom Hole N/A Devonian M arl II 13 65 Severo-Saremboiskoye Timan Pechora (Northern Part) 3056 3110 Early Devonian Devonian Marl II 14 80(2) Toboiskoye Timan P echora (Northern Part) 4145 4196 Early Devonian Devonian Marl II 15 81(2) Trebsa Timan Pechora (Northern Part) 3669 3683 Late Devonian Devonian Marl II 16 87 Ust-Talo tinskoye Timan Pechora (North ern Part) 3945 3977 N/A Devonian Marl II 17 10 2(2) Yareyyuskoye Timan Pechora (Northern Part) 1990 2000 Early Permian Devonian Carbonate III 18 50 Passedskoye Timan Pechora (Northern Part) 3696.7 3743 Late Devonian Devonian Carbonate III 19 8 0(1) Toboiskoye Timan P echora (Northern Part) 2640 2710 Late Devonian Devonian Carbonate III 20 41 Medynskoye Pechora Shelf 2837 2882 Early Devonian Devonian Carbonate III 21 880 Medynskoye Pechora Shelf 2857 2882 Early Devonian Devonian Carbonate III 22 144 N.Gulyaevskoye Pechora Shelf 2012 2049 Late Permian Triassic/Devonian Carbonate IV 23 44 Naulskoye Timan Pechora (Northern Part) 1240 1250 Late Permian Triassic/Devonian Carbonate IV 24 54 Prirazlomnoye Pechora Shelf 2406 2460 Early Permian Triassic/Devonian Ca rbonate IV 25 274 Varandey Pechora Sea 4464 4490 E arly Devonian Triassic/Devonian Carbon ate IV 26 81(3) Trebsa Timan P echora (Northern Part) 3636 3707 Late Devo nian Triassic/Devo nian Carbon ate IV 27 81(4) Trebsa Timan P echora (Northern Part) 3855 3910 Late Devo nian Triassic/Devo nian Carbon ate IV 28 220 Pechano-Oz erskoye Kolguyev Is land 1601 1605 Ea rly Triassic Upper J urassic V 29 150 N.Gulyaevskoye Pechora Shelf 2112 2249 Late Permian Uppe r Jurassic V 30 151 Prirazlomnoye Pechora Shelf 2368 2438 Early Permian Uppe r Jurassic V 31 146 Shtokmanovskoye Barents Sea 1812 1880 M iddle Jurassic Lower- Middle Jurassic VI 32 149 Shtokmanovskoye Barents Sea 1886 1961 M iddle Jurassic Lower- Middle Jurassic VI 33 147 Shtokmanovskoye Barents Sea 2237 2257 E arly Jurassic Lower- Middle Jurassic VI 109 34 561 Spitsbergen Spitsbergen Is land N/A N/A N/A Lower-Midd le Jurassic VI *N/A: not applicable Table 2. Geochemical parameters of oil samples in the Barents Sea and northern Timan-Pechora Basin. Sample *C19/C19+ *C29/C30 *DiaH/(H*C35/(C34 Family *C22/C21 *C24/C23 *C26/C25 *Tet/C23 *%C27 *%C28 *%C29 *ETR *C31R/H *GA/H *S/H *Bicad ID C23 Hop +diaH) +C35)Hop 152 I 0.20 0.40 0.56 0.92 0.12 0.329 0.343 0.329 3.21 0.24 0.53 0.22 0.66 0.02 0.43 0 102(1) I 0.12 0.32 0.63 1.06 0.28 0.297 0.255 0.447 4.43 0.32 0.93 0.02 0.54 0.09 0.27 0 91 I 0.14 0.34 0.65 1.06 0.27 0.286 0.236 0.478 4.03 0.33 0.8010 0.51 0. 0.12 0.56 0 67 I 0.12 0.37 0.60 1.02 0.29 0.284 0.358 0.358 4.37 0.31 0.93 0.07 0.50 0.10 0.24 0 12 I 0.11 0.31 0.68 1.16 0.16 0.341 0.287 0.372 4.81 0.26 0.45 0.11 0.48 0.06 0.59 0 78 I 0.10 0.51 0.79 1.48 0.08 0.286 0.261 0.454 2.70 0.34 0.35 0.29 0.48 0.07 0.31 0 52(1) I 0.04 0.48 0.77 1.46 0.08 0.301 0.301 0.398 3.63 0.31 0.38 0.27 0.49 0.04 0.30 0 526a I 0.16 0.25 0.75 1.18 0.14 0.285 0.219 0.470 4.12 0.31 0.54 0.46 0.50 0.19 1.05 0 81(2) II 0.48 0.27 0.78 1.06 1.77 0.244 0.333 0.423 0.56.31 0 0.57 0.14 0.34 0.13 0.11 0 87 II 0.27 0.44 0.76 1.03 1.54 0.292 0.350 0.358 0.61 0.31 0.65 0.04 0.37 0.14 0.08 0 22(1) II 0.32 0.32 0.77 0.99 1.67 0.220 0.390 0.390 0.48 0.30 0.70 0.05 0.38 0.12 0.16 0 80(2) II 0.39 0.30 0.66 0.98 1.53 0.217 0.313 0.469 0.45 0.32 0.64 0.11 0.35 0.13 0.09 0 65 II 0.29 0.28 0.77 0.86 1.64 0.184 0.354 0.462 0.43 0.31 0.63 0.06 0.34 0.12 0.07 0 22(3) II 0.32 0.30 0.70 0.99 1.94 0.201 0.303 0.495 0.34 0.31 0.63 0.05 0.35 0.09 0.07 0 22(2) II 0.31 0.29 0.70 0.88 1.86 0.201.341 0 0.459 0.38 0.31 0.65 0.05 0.35 0.10 0.07 0 43 II 0.43 0.30 0.73 0.94 1.75 0.171 0.275 0.554 0.32 0.34 0.53 0.14 0.30 0.27 0.06 0 50 III 0.06 0.47 0.58 0.84 0.33 0.300 0.186 0.514 2.99 0.42 0.77 0.01 0.51 0.09 0.09 0 880 III 0.10 0.57 0.47 0.86 0.52 0.279 0.245 0.476 0.86 0.39 0.89 0.02 0.44 0.09 0.07 0 41 III 0.11 0.59 0.47 0.85 0.53 0.272 0.259 0.470 0.97 0.41 0.85 0.03 0.46 0.10 0.13 0 102(2) III 0.10 0.57 0.46 0.90 0.51 0.312 0.264 0.425 0.86 0.41 0.88 0.02 0.43 0.10 0.14 0 80(1) III 0.09 0.55 0.4990 0. 0.40 0.308229 0. 0.463 1.37 0.41 0.73 0.02 0.45 0.09 0.08 0 274 IV 0.10 0.48 0.51 0.96 0.43 0.284 0.242 0.474 2.68 0.36 1.21 0.04 0.49 0.15 0.10 0 44 IV 0.12 0.46 0.52 0.96 0.41 0.290 0.222 0.488 2.86 0.37 1.18 0.03 0.51 0.14 0.11 0 81(4) IV 0.10 0.48 0.52 0.91 0.45 0.262 0.237 0.501 2.44 0.38 1.30 0.04 0.50 0.16 0.09 0 54 IV 0.09 0.49 0.53 0.93 0.45 0.274 0.235 0.492 2.46 0.38 1.29 0.02 0.49 0.13 0.08 0 81(3) IV 0.11 0.47 0.53 0.97 0.44 0.261 0.302 0.436 2.27 0.41 0.90.03 0.5 01 0.12 0.12 0 144 IV 0.10 0.38 0.56 1.12 0.36 0.269 0.236 0.495 2.75 0.34 1.13 0.04 0.50 0.11 0.11 0.013 151 V 0.68 0.19 0.81 1.29 1.94 0.246 0.392 0.362 0.76 0.22 0.34 0.15 0.37 0.01 0.11 0.008 220 V 0.41 0.31 0.83 1.08 0.57 0.155 0.291 0.555 1.57 0.26 0.36 0.11 0.45 0.02 0.34 0.013 150 V 0.58 0.35 0.84 1.10 1.51 0.199 0.353 0.448 0.94 0.22 0.37 0.14 0.40 0.00 0.34 0.016 561 VI 0.91 0.25 0.62 1.03 0.38 0.032 0.148 0.820 0.95 0.44 0.54 0.10 0.30 0.01 0.10 0.003 147 VI 0.83 0.32 0.48 0.95 0.92 0.333 0.295.371 0 0.98 0.30 0.73 0.10 0.19 0.01 0.53 0 146 VI 0.48 0.25 0.58 0.71 0.31 0.295 0.180 0.525 1.47 0.30 0.77 0.06 0.33 0.01 0.22 0 149 VI 0.76 0.18 0.51 0.43 0.84 0.201 0.232 0.567 0.80 0.23 0.71 0.03 0.53 0.02 0.20 0 *Parameter was used in the chemometric analysis. C 19/C19+C 23, C 22/C21, C 24/C23, and C 26/C25 tricyclic terpanes; Tet/C 23=C 24 tetracyclic terpane/C 23 tricyclic terpane; %C 27=%C 27 110 steranes/(%C 27 to %C 29 steranes); %C 28=%C 28 steranes/(%C 27 to %C 29 steranes); %C 29=%C 29 steranes/(%C 27 to %C 29 steranes); ETR=(C 28+C 29 tricyclics)/ trisnorneohopane; C 31R/H=C 31 homohopane/hopane; C 29/C30Hop=C 29 30-norhopane/hopane; DiaH/(H+diaH)=C 30 diahopane/(hopane+diahopane); C 35/(C 34+C 35)Hop=C 35 homohopanes/(C 34+C 35 homohopanes); GA/H=gammacerane/hopane; S/H=steranes/hopanes; Bicad=bicadinane/(bicadinane+hopane). Many of these parameters are discussed in Peters et al., 2005. Table 2. Geochemical parameters of oil samples in the Barents Sea and northern Timan-Pechora Basin (continued). *C30 *TA- 3-/(3- + C29 C29 TA C 20/ *TA- 13 13 13 C24 TA(I)/TA( Sample I D Family *NDR /(C27- DMD3/ *δ Csat *δ Caro δ Coil C28/C29 C26T/Ts 4-MeS Ts/(Ts+Tm) ββ/(ββ+αα 20S(20S (C20+C28, Dino Tet/C 26 I+II) 30)diaS C28S 20R) ) +20R) 20R) 152 I 0.18 0.05 0.11 0.55 -28.49 -28.75 -28.80 1.04 1.72 0.74 0.33 0.60 0.65 0.58 0.64 0.57 102(1) I 0.14 0.06 0.05 0.11 -28.88 -28.56 -28.48 0.57 1.83 0.95 0.50 0.54 0.62 0.54 0.50 0.49 91 I 0.18 0.06 0.04 0.17 -28.09 -28.38 -28.29 0.49 1.64 0.96 0.50 0.59 0.65 0.55 0.45 0.45 67 I 0.14 0.07 0.03 0.12 -28.86 -28.50 -28.53 1.00 1.82 0.95 0.55 0.50 0.71 0.59 0.44 0.44 12 I 0.23 0.02 0.02 0.20 -28.53 -28.40 -28.72 0.77 1.79 0.93 0.23 0.60 0.74 0.59 0.42 0.42 78 I 0.18 0.08 0.05 0 .18 -27.18 -27.55 -27.73 0.57 1.06 0.96 0.08 0.80 0.74 0.57 0.63 0.55 52(1) I 0.18 0.10 0.00 0.44 -26.52 -27.57 -27.71 0.76 1.35 0.77 0.08 0.73 0.65 0.55 0.51 0.45 526a I 0.15 0.07 0.06 0.43 -29.83 -29.66 -29.76 0.47 1.33 0.92 0.18 0.61 0.66 0.57 0.64 0.60 81(2) II 0.14 0.00 0.04 0.23 -31.41 -30.25 -31.11 0.79 0.25 0.98 2.55 0.57 0.71 0.62 0.31 0.37 87 II 0.12 0.00 0.01 0.10 -31.77 -30.85 -30.94 0.98 0.31 0.95 2.17 0.43 0.65 0.59 0.08 0.08 22(1) II 0.14 0.00 0.01 0.12 -33.13 -31.24 -32.33 1.00 0.24 0.98 2.04 0.51 0.51 0.51 0.07 0.07 80(2) II 0.12 0.00 0.02 0.08 -31.77 -31.41 -31.51 0.67 0.20 0.97 2.21 0.56 0.60 0.54 0.10 0.12 65 II 0.13 0.00 0.01 0.06 -32.32 -31.63 -32.11 0.77 0.18 0.97 2.33 0.48 0.63 0.55 0.06 0.07 22(3) II 0.11 0.00 0.01 0.07 -32.68 -31.92 -31.97 0.61 0.18 0.98 2.49 0.50 0.59 0.54 0.06 0.07 22(2) II 0.11 0.00 0.01 0.07 -32.52 -32.03 -32.34 0.74 0.17 0.96 2.54 0.49 0.58 0.55 0.06 0.07 43 II 0.11 0.00 0.02 0.07 -31.59 -30.63 -31.04 0.50 0.11 0.97 2.09 0.68 0 .76 0.59 0.11 0.14 50 III 0.11 0.01 0.02 0.10 - 30.97 -28.64 -30.10 0.36 1.24 0.95 0.81 0.19 0.68 0.57 0.08 0.10 880 III 0.13 0.00 0.01 0.07 -31.70 -30.30 -30.62 0.51 0.39 0.98 1.30 0.32 0.67 0.55 0.05 0.07 41 III 0.14 0.01 0.01 0.04 -31.76 -30.25 -30.25 0.55 0.40 0.99 1.25 0.32 0.69 0.57 0.05 0.06 102(2) III 0.11 0.00 0.01 0.08 -31.82 -30.47 -30.62 0.62 0.41 0.98 1.26 0.32 0.72 0.60 0.05 0.06 80(1) III 0.12 0.01 0.01 0.24 -31.87 -30.27 -30.76 0.49 0.46 0.98 1.01 0.31 0.67 0.55 0.06 0.07 274 IV 0.14 0.03 0.02 0.07 -29.63 -29.30 -29.14 0.51 1.11 0.97 1.08 0.31 0.67 0.57 0.21 0.23 44 IV 0.14 0.03 0.03 0.04 - 28.81 -29.29 -28.95 0.45 1.16 0.99 0.98 0.31 0.69 0.58 0.21 0.22 81(4) IV 0.13 0.02 0.02 0.05 -29.40 -29.10 -29.45 0.47 1.13 0.98 1.15 0.29 0.68 0.56 0.23 0.24 54 IV 0.13 0.02 0.01 0.06 -29.88 -29.49 -29.94 0.48 0.96 0.98 1.20 0.27 0.69 0.58 0.22 0.23 81(3) IV 0.14 0.05 0.03 0.57 -30.60 -30.22 -30.48 0.69 0.94 0.70 1.03 0.31 0.63 0.55 0.19 0.19 144 IV 0.15 0.04 0.02 0.07 -28. 93 -28.93 -28.80 0.48 1.17 0.98 0.76 0.36 0.70 0.59 0.19 0.19 151 V 0.15 0.05 0.04 0.60 -27.67 -26.13 -28.07 1.08 0.19 0.68 1.86 0.52 0.66 0.58 0.34 0.38 220 V 0.19 0.04 0.07 0.72 -29.30 - 28.27 -29.22 0.52 0.45 0.55 0.65 0.54 0.74 0.59 0.45 0.44 150 V 0.17 0.02 0.08 0.71 -28.22 -26.92 -28.08 0.79 0.30 0.59 1.41 0.49 0.67 0.59 0.40 0.41 561 VI 0.25 0.00 0.06 0.59 -28.87 -26.79 -27.92 0.18 0.10 0.80 0.61 0.11 0.64 0.57 0.17 0.22 147 VI 0.19 0.01 0.03 0.69 -28.80 -27.31 -28.07 0.79 0.74 0.64 2.48 0.22 0.24 0.31 0.36 0.31 146 VI 0.19 0.00 0.07 0.50 -30.07 -29.06 -29.36 0.34 1.47 0.74 1.19 0.36 0.61 0.47 0.58 0.54 149 VI 0.24 0.00 0.17 0.86 -29.93 - 29.14 -29.47 0.41 0.29 0.27 3.87 0.38 0.54 0.51 0.14 0.16 *Parameter was used in the chemometric analysis. NDR=24-nordiacholestanes/(24- +27-nordiacholestanes); C 30/(C 27-30 )diaS= C 30 diasteranes/(C 27 toC 30 diasteranes); TA-DMD3/C 28S=C 28 111 triaromatic demethyldinosterane/C 28 stigmastane; TA-Dino=C 29 triaromatic dinosteranes/(C 29 dinosteranes+3-methylstigmastane 20R); C 28/C29=C 28 steranes/C 29steranes; C 26T/Ts=C 26 tricyclic terpane/trisnorneohopane; 3-/(3-+4-MeS 20R)=3-/(3-+4-methylstigmastane 20R); C 24Tet/C 26=C 24 tetracyclics/C 26 trycyclics; TA C 20/(C 20+C 28, 20R)=desmethyl triaromatic steroids; TA(I)/TA(I+II)=(C 21+C 22)/(C 21+C 22+C 26+C 27+C 28)desmethyl triaromatic steroids. Many of these parameters are discussed in Peters et al., 2005. Table 3. Quantification of diamondoids (ppm) and biomarker (ppm), extent of oil cracking of the oil samples from the Barents Sea and northern Timan- Pechora Basin with CSIA-D data of the selected oil samples. 3-+4- 1,4- 1,4- 1,3- 1,3,4- 1,3,4- 1,3,6- 1,3,5- 3- C29 1- methyldiam Diamondoid Cracking Dimethylada Dimethylada Dimethylada Trimethylad Trimethylada Trimethylada Trimethylada Dimethyldia Sample ID Family Stigmastan Methyladama antanes(pp baseline(ppm) extent mantane(cis), mantane(tran mantane,δ13C amantane(cis mantane(trans mantane,δ13C mantane,δ13C mantane,δ13C e(ppm) ntane, δ13C‰ m) δ13C‰ s),δ13C‰ ‰ ),δ13C‰ ), δ13C‰ ‰ ‰ ‰ 152 I 6.05 2.23 4.82 20.36 102(1) I 64.99 15.57 4.82 92.58 -19.56 -21.84 -21.6823.06 - -24.03 -24.30 -24.09 -25.2729.19 - 91 I 45.77 11.69 4.82 89.47 67 I 61.57 18.92 4.82 92.17 -19.75 -21.91 -21.8622.86 - -23.73 -23.81 -24.19 -25.3928.77 - 12 I 66.06 15.89 4.82 92.70 78 I 4.82 3.67 4.82 0.00 -18.72 -21.26 -21.8122.73 - -23.94 -24.12 -22.76 -24.8928.17 - 52(1) I 6.70 2.87 4.82 28.09 -19.38 -22.13 -22.2123.05 - -23.56 -23.63 -23.82 -25.2129.50 - 526a I 16.24 13.99 4.82 70.32 81(2) II 11.78 31.35 2.39 79.72 -20.51 -23.13 -23.5123.43 - 24.02 - -24.10 -24.47 -25.4628.75 - 87 II 3.40 121.81 2.39 29.77 22(1) II 4.01 107.92 2.39 40.37 80(2) II 3.92 38.88 2.39 38.96 65 II 5.13 129.53 2.39 53.39 22(3) II 5.12 114.88 2.39 53.30 22(2) II 93.233.82144.5 64.52-91.42-92.42-67.12-50.65 81.03-27.62-16.52- 43 II 2.39 45.52 2.39 0.19 50 III 3.07 72.91 2.57 16.36 880 III 4.93 160.69 2.57 47.85 41 III 3.68 98.63 2.57 30.26 102(2) III 75.207.10147.3 82.13 45.92-39.52-61.52-07.62-56.62-08.42-33.42- 80(1) III 2.57 82.01 2.57 0.00 274 IV 38.30 67.56 7.44 80.57 -19.97 -23.24 -23.2823.38 - -23.76 -24.20 -25.11 -26.0729.81 - 44 IV 44.47 48.99 7.44 83.27 -20.81 -22.46 -22.7824.07 - -24.23 -24.48 -24.41 -26.2729.79 - 81(4) IV 26.57 41.90 7.44 72.00 54 IV 25.82 73.06 7.44 71.19 81(3) IV 10.77 44.20 7.44 30.91 144 IV 7.44 21.94 7.44 0.00 -20.49 -22.41 -22.2223.58 - -24.44 -24.51 -24.49 -25.9329.79 - 151 V 22.75 18.87 7.15 68.57 -18.52 -20.75 -21.1521.49 - -22.56 -22.51 -21.61 -23.6326.80 - 220 V 7.15 11.26 7.15 0.00 -18.840.71 -2 -21.1920.85 - -22.72 -22.58 -22.24 -23.5726.87 - 150 V 16.61 32.14 7.15 56.96 561 VI 2.35 95.98 2.35 0.00 147 VI 8.56 2.30 2.35 72.55 146 VI 14.05 1.34 2.35 83.28 149 VI 6.93 0.00 2.35 66.07 112 0 o 15 o 30 o 45 o 60 o 75 o 90 o Franz Joseph Land (Russia) Spitsbergen 561 Svalbard 75 o 526(a) (Norway) Novaya Kara Sea Oil and Gas Fields Zemlya Oil Family I Barents Sea Oil Family V Oil Family VI Shtokmanovskoye Sample ID Norwegian Sea 146 147 149 Snøhvit 146 Prirazlomnoye Kolguyev 152 Island 220 78 52(1) Sverige (Sweden) Suomi Timan-Pechora Norge (Finland) basin (Norway) Russia 113 Figure 1a. Location map for Barents Sea and Timan-Pechora Basin shows identified oil families. o o o o 40 45 50 55 Barents Sea Kanin Novaya-Zemlya Peninsula Kolguyev Island Pechora Sea Kara Sea Arctic Circle 150 144 Prirazlomnoye Vaygach Island 151 54 880 41 91 274 81(2) 80(1,2) o o Pay-Khoy Ridge 70 65 12 81(3,4) 43 102(1) 50 102(2) 44 22(1,2,3) Kolva Megaswell Khoreyver 65 Depression Pechora 67 Adzva-Varandey 87 Zone Timan - Kanin Ridge Depression Ural Mountains o Chukchi 180 Sea N Islands Canadian Arctic Laptev Nordic Sea Sea BARENTS 0 SEA Kara Sea 1000 km o 65 100 km EURASIA 90o E o o 65o 70o Oil Family I 60 Oil Family IV Structural regions after Ulmishek (1982) Oil Family II Oil Family V and Lindquist (1999b). Oil Family III 146 Sample ID Figure 1b. Location map for Timan-Pechora Basin shows identified oil families. 114 561 147 VI 146 34 Oil Samples 149 151 V 220 150 152 102(1) 91 67 I 12 78 52(1) 526(a) 274 44 81(4) 54 IV 81(3) 144 50 880 III 41 102(2) 80(1) 81(2) 87 22(1) 80(2) 65 II 22(3) Barents Sea and northern Timan-Pechora Basin oil families Timan-Pechora Basin oil Barents Sea and northern 22(2) 43 115 Fiugre 2a. HCA for thirty-four oil samples based on twenty biomarkers and two stable carbon isotope ratios. 52(1) 526(a) Family I 78 152 PC1 Family II Family III 12 Family IV 151 91 150 Family V PC2 220 Family VI 67 102(1) PC3 147 144 149 561 146 44 81(3) 274 81(4) 50 54 81(2) 80(1) 22(1) 41 87 102(2) 880 80(2) 65 22(3) 43 116 22(2) Figure 2b. PCA for thirty-four oil samples based on twenty biomarkers and two stable carbon isotope ratios. Whole-Oil Gas Chromatography Biomarkers ( ) pA 1000 11 Ion 191.00 (190.70 to 191.70): MHSAT011.D Sample 91 Abundance Sample 91 M/Z 191 30H 34000 32000 800 30000 29H 28000 Family 26000 PENTACYCLIC 15 24000 TRICYCLICS TRITERPANES I 600 22000 20000 18000 16000 Ts 400 20 14000 Pr 12000 Tm Ph 10000 25 200 8000 30 6000 4000 2000 0 Time--> 0 Time (min) 70.00 75.00 80.00 85.00 90.00 Ion 191.00 (190.70 to 191.70): MHSAT009.D pA Sample 22(2) Abundance Sample 87 30H 600 M/Z 191 400000 15 11 500 350000 29H 300000 PENTACYCLIC 400 TRICYCLICS TRITERPANES Family 250000 300 II 200000 20 25 30 200 Pr 150000 Tm Ph Ts 100000 100 50000 0 117 0 Time--> 70.00 75.00 80.00 85.00 90.00 Time (min) Figure 3a. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family I and Family II oils. Whole-Oil Gas Chromatography Biomarkers Ion 191.00 (190.70 to 191.70): MHSAT032.D Sample 880 Abundance Sample 880 pA 11 M/Z 191 30H 450000 500 29H 400000 350000 Family 400 15 300000 TRICYCLICS PENTACYCLIC III TRITERPANES 300 250000 20 200000 25 Tm 200 P r 150000 30 P h 100000 Ts 100 50000 0 Time--> 70.00 75.00 80.00 85.00 90.00 Time (min) Ion 191.00 (190.70 to 191.70): MHSAT029.D Sample 144 Abundance Sample 54 pA 11 1600 00 M/Z 191 29H 600 1500 00 1400 00 30H 1300 00 500 1200 00 11 00 00 15 PENTACYCLIC 400 25 1000 00 20 TRITERPANES Family 90000 TRICYCLICS 80000 300 IV 30 70000 Tm P r 60000 P h 200 50000 40000 Ts 30000 100 20000 10000 0 0 Time--> 70.00 75.00 80.00 85.00 90.00 118 Time (min) Figure 3b. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family III and Family IV oils. Whole-Oil Gas Chromatography Biomarkers Ion 191.00 (190.70 to 191.70): MHSAT039. Sample 151 Abundance Sample 151 pA 25 60000 M/Z 191 30H 600 55000 50000 500 20 45000 Family 30 40000 400 11 PENTACYCLIC V 35000 TRICYCLICS TRITERPANES 15 30000 300 29H 25000 200 20000 Pr 15000 Ts Ph Tm 100 10000 5000 0 0 Time--> 70.00 75.00 80.00 85.00 90.00 Time (min) ,( ) Ion 191.00 (190.70 to 191.70): MHSAT038.D pA Sample 146 Abundance Sample 561 260000 M/Z 191 30H 240000 800 15 220000 200000 11 600 180000 PENTACYCLIC Family 160000 TRICYCLICS 29H TRITERPANES VI 140000 400 120000 100000 Pr 80000 Ph 20 Tm 200 60000 40000 Ts 25 20000 119 0 0 5 7 5 10 12 5 15 17 5 20 22 5 25 27 5 Time--> Time (min) 70.00 75.00 80.00 85.00 90.00 Figure 3c. Representative whole-oil gas chromatograms and 191 m/z ion mass fragmentograms for Family V and Family VI oils. -27.00 67 Family I -28.00 526(a) 22(3) -29.00 81(2) Family II -30.00 65 -31.00 80(1) C‰ Family III 13 -32.00 50 δ 144 -33.00 274 -34.00 Family IV 81(3) -35.00 44 150 Family V -36.00 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 No. C atoms in molecule Figure 4. Comparision of compound-specific isotope analysis of n-alkanes in selected oil samples from 120 each identified oil family in the Barents Sea and northern Timan-Pechora Basin. 200 No Light to cracking moderate cracking 880 160 Family I 65 Family II 120 22(2) 87 22(3) Family III 102(2) 22(1) 41 561 80 80(1) 54 Strongly to Family IV 274 severely 50 cracked 44 mixed oils Family V 43 81(3) 81(4) Stigmastane (ppm) 80(2) 40 81(2) 150 29 144 67102(1) Family VI 151 C 526 220 91 12 152 52(1) 0 78 146 147149 0 10 20 30 40 50 60 70 3- and 4 -methyldiamantanes (ppm) 121 Figure 5. Schematic relationship between concentrations of methyldiamantanes and stigmastane (5α, 14α, 17α (H)-24-ethylcholestane 20R) for oil samples from the Barents Sea and northern Timan-Pechora Basin. -18.0 -19.0 1 2 3 4 5 6 7 8 9 52(1) -20.0 78 -21.0 Family I 102(1) -22.0 67 -23.0 22(2) Family II -24.0 81(2) C‰ -25.0 102(2) Family III 13 144 δ -26.0 44 Family IV -27.0 274 -28.0 220 Family V -29.0 151 -30.0 -31.0 Figure 6. Comparison of compound-specific isotope analysis of diamondoids in selected oils from each identified oil family in the Barents Sea and northern Timan-Pechora Basin. 1) 1-methyladamantane, 2) 1,4-dimethyladamantane(cis), 3) 1,4-dimethyladamantane(trans), 4) 1,3-dimethyladamantane, 5) 1,3,4-trimethyladamantane(cis), 122 6) 1,3,4-trimethyladamantane(trans),7) 1,3,6-trimethyladamantane, 8) 1,3,5-trimethyladamantane(cis), 9) 3-dimethyldiamantane.