The Molecular Organic Geochemistry Industrial Affiliates

(MOGIA) Program

& its relationship to

The Basin and Petroleum System Modeling Affiliates

(BPSM) Program

MOGIA program functions ● Conduct fundamental & applied research on organic

geochemistry

MOGIA delivers Educational – ● Professional / scientific training (M.Ss & Ph.Ds) in energy-

related geosciences Scientific – ● Novel technology to determine petroleum provenance and

basin development ● Detailed petroleum systems studies that can reduce risk and

expand potential for exploration and development

MOGIA link with BPSM ● Sound basin models require in-depth understanding of petroleum systems: hydrocarbon sources, migration, maturation, biodegradation risk

Participants in Research of the Molecular Organic Geochemistry Laboratory

Stanford faculty Prof. Mike Moldowan, Director Prof. Stephen Graham Dr. Kenneth Peters (Consulting Prof.) Prof. Christopher Francis

Laboratory staff and students Dr. Jeremy Dahl Fred Fago Ye Wang (Ph.D.) Meng He (Ph.D.) Keisha Durant (M.S.) Paul Lipton Dr. Peter Denisevich Shaun Moldowan

Visiting Scholars and Researchers Dr. David Zinniker

Dr. Zhonghong Chen (China) Waleed Bazeed (Ph.D.)(Egypt)

Furat Saleh (Ph.D.)(Iraq)

Other Research Participants Dr. Frank Picha

Gerard Demaison Dr. Alla Rovenskaya

Dr. Marcio Mello Dr. Andre Bender

Dr. Silvana Barbanti

Participants in Research of the Molecular Organic Geochemistry Laboratory

Affiliate members (2008 and/or 2009) Aramco (Saudi Arabia) Ecopetrol (Colombia) ENI (Italy) HRT petroleum (Brazil) JOGMEC (Japan) Petrobrás (Brazil) PetroChina (China) Shell (International) StatoilHydro (Norway)

Participating laboratories and organizations

Petrobrás (Brazil) ChevronTexaco (USA)

l’Université Louis Pasteur (France) GB Scientific, Inc. (USA)

Shell (International) United States Geological Survey

Aramco (Saudi Arabia) RIPED (PetroChina)

HRTpetroleum (Brazil)

Fundamental Research Topics of MOGIA of Possible Interest to BPSM

Ultra high maturity assessment/oil cracking to gas Determine oil cracking to gas Identify oil and gas/condensate mixes Determine sources of the mix components Model kinetics using individual compounds

Oil degradation Thermochemical sulfate reduction (H2S prediction) Reservoir continuity of biodegraded/heavy oil Anaerobic versus aerobic biodegradation Factors influencing thermal degradation Tracing biodegradation levels in detail

Age-related biomarkers for oil-source age determination

Applications to specific basins or regions

Alaska North Slope – reported to MOGIA Barents Sea, Timan-Pechora – in progress Ghana, West Africa – postponed/planned Talara Basin, Peru - pub. AAPG Bull Nigeria – in progress Saudi Arabia - reported to MOGIA West Siberia - planned (focus northern area) Iraq - beginning and in progress Egypt - in progress China - numerous basins reported

Current research protocols in basin studies

1. Perform high quality molecular/biomarker correlation

2. Assess mixes using combined biomarker and compound specific isotope analysis (CSIA)

3. Focus on black oil contributed by sources in the oil window mixed with post oil-window condensate/gas

Diamondoid-biomarker cracking method

Low Maturity No Cracking

High Maturity No Cracking

Slightly Cracked Intensely Cracked

Diamondoids

Biomarkers

Dahl et al., Nature, 1999

Oil Window Source Rock

Gas Window Source Rock

Deep gas and condensate bubble up through the oil reservoir.

Diamondoids and light hydrocarbons from deep

source dissolve in the oil.

 Problem: We Can Only See the Less-Mature Source

Mixed Oils from High and Low Maturity Sources Contain Abundant Diamondoids and Biomarkers

High Diamondoids Low Biomarkers

High Biomarkers Low Diamondoids

OIL MIXING: BIOMARKERS AND DIAMONDOIDS

Cracked Oil “Black Oil”

Recognition of Mixed Oils

Low Maturity No Cracking

High Maturity No Cracking

Slightly Cracked Intensely Cracked

Mixed oils from Normal Maturity and

Highly Cracked Sources

Diamondoids

Biomarkers

Dahl et al., Nature, 1999

Deep Source Identification Leads to New Oil and Gas Plays Through More

Accurate Basin Models

Contribution from

Márcio R. Mello (HRT) André A. Bender (HRT)

52.8 Ma

Accumulations in the One SR Scenario, Albian/marine

Evolution of Flowpaths and Accumulations When Only the Shallow Source Is Considered

0 Ma

Accumulations in the One SR Scenario , Albian/marine

Evolution of Flowpaths and Accumulations When Only the Shallow Source Is Considered

52.8 Ma

Evolution of Flowpaths and Accumulations When Deep Source Is Included

Accumulations in the TWO SRs Scenario, Albian + Coquina

0 Ma

Accumulations in the TWO SRs Scenario , Albian + Coquina

Evolution of Flowpaths and Accumulations When Deep Source Is Included

Accumulations -> One SR Scenario

The same accumulation has smaller GOR and volume in the One SR scenario. The right pizza diagram shows clearly the additional amount of gas that originated from the deep sources.

ONE SR TWO SRs

CONCLUSION

Recognizing the deep source dramatically changes the basin model