OPGEE: The Oil Production Greenhouse gas Emissions Estimator

- Current research suggests that GHG emissions from petroleum production can be quite variable. Some oil production facilities can have quite low emissions if they do not rely on energy intensive production methods and implement effective controls on fugitive emissions sources. In contrast, some crude oil sources can have higher GHG emissions per unit of energy produced if they rely on energy-intensive production methods or process large volumes of fluids per unit of energy produced.
The Oil Production Greenhouse gas Emissions Estimator (OPGEE) is an engineering-based life cycle assessment (LCA) tool for the measurement of greenhouse gas (GHG) emissions from the production, processing, and transport of crude petroleum. The system boundary of OPGEE extends from initial explo- ration to the refinery entrance gate.
OPGEE is built for maximum transparency, using public data sources where possible and being implemented in a user-accessible Microsoft Excel format.
Current stable model and documentation
Model development versions [not for citation or distribution - use current version above]
See the OPGEE GitHub page for the current version of the model under development: OPGEE developer page
A service called xltrail is used to track changes to the OPGEE .xlsx binary files: OPGEE xltrail edit record
Older versions [Posted for reference only, please use current version above]
- OPGEE model v2.0c - Documentation [PDF], Model [XLSM] (Released February 13th, 2018)
- OPGEE model v2.0b - Documentation [PDF], Model [XLSM] (Released July 17th, 2017)
- OPGEE model v2.0a - Documentation [PDF], Model [XLSM] (Released March 27th, 2017)
- OPGEE embodied energy supplemental calculation [XLSM] (Released September 30, 2015)
- OPGEE model v1.1 Draft E - Documentation [PDF], Model [XLSM] (Released June 4th, 2015)
- OPGEE model v1.1 Draft D - Documentation [PDF], Model [XLSM] (Released October 10th, 2014)
- OPGEE model v1.1 Draft C - Documentation [PDF], Model [XLSM] (Released July 10th, 2014)
- OPGEE model v1.1 Draft B - Documentation [PDF], Model [XLSM] (Released March 11th, 2014)
Publications
2018
*Brandt, A.R., M.S. Masnadi, J.G. Englander, J.G. Koomey, D. Gordon. Climate-wise oil choices in a world of oil abundance. Environmental Research Letters DOI: 10.1088/1748- 9326/aaae76
*Masnadi, M.S., D. Schunack, Y. Li, S.O. Roberts, A.R. Brandt, H.M. El-Houjeiri, S. Przesmitzki, M.Q. Wang. Well-to-refinery emissions and net-energy analysis of China?s crude-oil supply. Nature Energy. DOI: 10.1038/s41560-018-0090-7
2017
Cooney, G., M. Jamieson, J. Marriott, J. Bergerson, A.R. Brandt, T.J. Skone. Updating the US life cycle GHG petroleum baseline to 2014 with projections to 2014 using open-source engineering-based models. Environmental Science & Technology DOI: 10.1021/acs.est.6b02819
Gvakharia, A., E.A. Kort, M.L. Smith, J. Peischl, J.P. Schwarz, A.R. Brandt, T.B. Ryerson, C. Sweeney. Methane, black carbon, and ethane emissions from natural gas flares in the Bakken Shale, ND. Environmental Science & Technology. DOI: 10.1021/acs.est.6b05183
Masnadi, M.S., Brandt, A.R. Climate impacts of oil extraction increase significantly with oilfield age. Nature Climate Change (2017).DOI: 10.1038/nclimate3347
Wang, J., O'Donnell, J., Brandt, A.R. Potential solar energy use in the global petroleum sector (2017) Energy, 118, pp. 884-892. DOI: 10.1016/j.energy.2016.10.107
Yeh, S., Ghandi, A., Scanlon, B.R., Brandt, A.R., Cai, H., Wang, M.Q., Vafi, K., Reedy, R.C. Energy Intensity and Greenhouse Gas Emissions from Oil Production in the Eagle Ford Shale. Energy & Fuels DOI: 10.1021/acs.energyfuels.6b02916
2016
*Brandt, A.R., T. Yeskoo, S. McNally, K. Vafi, S. Yeh, H. Cai, M.Q. Wang. Energy intensity and greenhouse gas emissions from tight oil production in the Bakken formation. Energy & Fuels. DOI: 10.1021/acs.energyfuels.6b01907
Cooney, G., M. Jamieson, J. Marriott, J. Bergerson, A.R. Brandt, T.J. Skone. Updating the US life cycle GHG petroleum baseline to 2014 with projections to 2014 using open-source engineering-based models. Environmental Science & Technology DOI: 10.1021/acs.est.6b02819
2015
Brandt, A.R. (2015) Embodied energy and GHG emissions from material use in conventional and unconventional oil and gas operations. Environmental Science & Technology. DOI:10.1021/acs.est.5b03540.
OPGEE model v1.1 Draft A - Documentation [PDF], Model [XLSM] (Released March 5th, 2013)
OPGEE model v1.0 - Documentation [PDF], Model [XLSM] (Released September 17th, 2012)
OPGEE model v1.0 Draft A - Documentation [PDF], Model [XLSX] (Released June 25th, 2012)
Site content
- Saad, D, M Sodwatana, E Sherwin, and A Brandt. “Energy Storage in Combined Gas-Electric Energy Transitions Models: The Case of California”, Applied Energy, 385 (May 1, 2025): 125480. https://doi.org/10.1016/j.apenergy.2025.125480.
- Aljubran, M, D Saad, M Sodwatana, A Brandt, and R Horne. “The Value of Enhanced Geothermal Systems for the Energy Transition in California”, Sustainable Energy & Fuels, February 3, 2025. https://doi.org/10.1039/D4SE01520G.
- Mukherjee, M, J Littlefield, H Khutal, K Kirchner-Ortiz, K Davis, L Jing, F Ramadan, H El-Houjeiri, M Masnadi, and A Brandt. “Greenhouse Gas Emissions from the US Liquefied Natural Gas Operations and Shipping through Process Model Based Life Cycle Assessment”, Communications Earth & Environment, 6, no. 1 (January 19, 2025): 16. https://doi.org/10.1038/s43247-024-01988-2.
- Sodwatana, M, S Kazi, K Sundar, A Brandt, and A Zlotnik. “Locational Marginal Pricing of Energy in Pipeline Transport of Natural Gas and Hydrogen With Carbon Offset Incentives”, International Journal of Hydrogen Energy, 96 (December 27, 2024): 574-88. https://doi.org/10.1016/j.ijhydene.2024.11.191.
- Nie, Y, Q Paletta, A Scott, L Pomares, G Arbod, S Sgouridis, J Lasenby, and A Brandt. “Sky Image-Based Solar Forecasting Using Deep Learning With Heterogeneous Multi-Location Data: Dataset Fusion Versus Transfer Learning”, Applied Energy, 369 (September 1, 2024): 123467. https://doi.org/10.1016/j.apenergy.2024.123467.
- Nie, Y, E Zelikman, A Scott, Q Paletta, and A Brandt. “SkyGPT: Probabilistic Ultra-Short-Term Solar Forecasting Using Synthetic Sky Images from Physics-Constrained VideoGPT”, Advances in Applied Energy, 14 (July 15, 2024): 100172. https://doi.org/10.1016/j.adapen.2024.100172.
- Chen, Z, S El Abbadi, E Sherwin, P Burdeau, J Rutherford, Y Chen, Z Zhang, and A Brandt. “Comparing Continuous Methane Monitoring Technologies for High-Volume Emissions: A Single-Blind Controlled Release Study”, ACS ES&T Air, 1, no. 8 (June 4, 2024): 871-84. https://doi.org/10.1021/acsestair.4c00015.
- Negron, A, E Kort, G Plant, A Brandt, Y Chen, C Hausman, and M Smith. “Measurement-Based Carbon Intensity of US Offshore Oil and Gas Production”, Environmental Research Letters, 19, no. 6 (May 28, 2024): 064027. https://doi.org/10.1088/1748-9326/ad489d.
- El Abbadi, S, Z Chen, P Burdeau, J Rutherford, Y Chen, Z Zhang, E Sherwin, and A Brandt. “Technological Maturity of Aircraft-Based Methane Sensing for Greenhouse Gas Mitigation”, Environmental Science & Technology, 58, no. 22 (May 17, 2024). https://doi.org/10.1021/acs.est.4c02439.
- Sherwin, E, J Rutherford, Z Zhang, Y Chen, E Wetherley, P Yakovlev, E Berman, B Jones, D Cusworth, A Thorpe, A Ayasse, R Duren, and A Brandt. “US Oil and Gas System Emissions from Nearly One Million Aerial Site Measurements”, Nature, 627, no. 8003 (March 13, 2024): 328-34. https://doi.org/10.1038/s41586-024-07117-5.
- Shin, L, A Brandt, D Iancu, K Mach, C Field, M-J Cho, M Ng, K Chey, N Ram, T Robinson, and B Reeves. “Climate Impacts of Digital Use Supply Chains”, Environmental Research: Climate, 3, no. 1 (March 5, 2024): 015009. https://doi.org/10.1088/2752-5295/ad22eb.
- Wang, J, B Barlow, W Funk, C Robinson, A Brandt, and A Ravikumar. “Large-Scale Controlled Experiment Demonstrates Effectiveness of Methane Leak Detection and Repair Programs at Oil and Gas Facilities”, Environmental Science & Technology, 58, no. 7 (February 5, 2024). https://doi.org/10.1021/acs.est.3c09147.
- Nie, Y, X Li, Q Paletta, M Aragon, A Scott, and A Brandt. “Open-Source Sky Image Datasets for Solar Forecasting With Deep Learning: A Comprehensive Survey”, Renewable and Sustainable Energy Reviews, 189 (January 15, 2024): 113977. https://doi.org/10.1016/j.rser.2023.113977.
- Sherwin, Evan, Jeffrey Rutherford, Yuanlei Chen, Sam Aminfard, Eric Kort, Robert Jackson, and Adam Brandt. “Single-Blind Validation of Space-Based Point-Source Detection and Quantification of Onshore Methane Emissions”, Scientific Reports, 13 (March 7, 2023): 3836. https://doi.org/10.1038/s41598-023-30761-2.
- Jing, Liang, Hassan El-Houjeiri, Jean-Christophe Monfort, James Littlefield, Amjaad Al-Qahtani, Yash Dixit, Raymond Speth, Adam Brandt, Mohammad Masnadi, Heather MacLean, William Peltier, Deborah Gordon, and Joule Bergerson. “Understanding Variability in Petroleum Jet Fuel Life Cycle Greenhouse Gas Emissions to Inform Aviation Decarbonization”, Nature Communications, 13, no. 1 (December 21, 2022): 7853. https://doi.org/10.1038/s41467-022-35392-1.
- Zhang, Zhan, Evan Sherwin, Daniel Varon, and Adam Brandt. “Detecting and Quantifying Methane Emissions from Oil and Gas Production: Algorithm Development With Ground-Truth Calibration Based on Sentinel-2 Satellite Imagery”, Atmospheric Measurement Techniques, 15, no. 23 (December 13, 2022): 7155-69. https://doi.org/10.5194/amt-15-7155-2022.
- Sherwin, Evand, Ernest Lever, and Adam Brandt. “Low-Cost Representative Sampling for a Natural Gas Distribution System in Transition”, ACS Omega, 7, no. 48 (November 23, 2022): 43973–43980. https://doi.org/10.1021/acsomega.2c05314.
- Yu, Jevan, Benjamin Hmiel, David Lyon, Jack Warren, Daniel Cusworth, Riley Duren, Yuanlei Chen, Erin Murphy, and Adam Brandt. “Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin”, Environmental Science & Technology Letters, 9, no. 11 (October 4, 2022): 969–974. https://doi.org/10.1021/acs.estlett.2c00380.
- Kuepper, Lucas, Holger Teichgraeber, Nils Baumgärtner, André Bardow, and Adam Brandt. “Wind Data Introduce Error in Time-Series Reduction for Capacity Expansion Modelling”, Energy, 256 (October 1, 2022): 124467. https://doi.org/10.1016/j.energy.2022.124467.
- Plant, Genevieve, Eric Kort, Adam Brandt, Yuanlei Chen, Graham Fordice, Alan Gorchov Negron, Stefan Schwietzke, Mackenzie Smith, and Daniel Zavala-Araiza. “Inefficient and Unlit Natural Gas Flares Both Emit Large Quantities of Methane”, Science, Report: Methane Emissions, 377, no. 6614 (September 29, 2022): 1566-71. https://doi.org/10.1126/science.abq0385.