OPGEE: The Oil Production Greenhouse gas Emissions Estimator

research opgee diagram — Figure 1. Estimated upstream GHG emissions from 5 "generic" crude oil pathways modeled using OPGEE v1.0a.

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

OPGEE model v3.0b - Documentation [PDF], Model [XLSM] (Released May 14th, 2022)

Model development versions [not for citation or distribution - use current version above]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

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)

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.
Von Wald, Gregory, Kaarthik Sundbar, Evan Sherwin, Anatoly Zlotnik, and Adam Brandt. “Optimal Gas-Electric Energy System Decarbonization Planning”, Advances in Applied Energy, 6 (June 2022): 100086. https://doi.org/10.1016/j.adapen.2022.100086.
Teichgraeber, Holger, and Adam Brandt. “Time-Series Aggregation for the Optimization of Energy Systems: Goals, Challenges, Approaches, and Opportunities”, Renewable and Sustainable Energy Reviews, 157 (April 2022): 111984. https://doi.org/10.1016/j.rser.2021.111984.
Chen, Yuanlei, Evan Sherwin, Elena Berman, Brian Jones, Matthew Gordo, Erin Wetherly, Erik Kort, and Adam Brandt. “Quantifying Regional Methane Emissions in the New Mexico Permian Basin With a Comprehensive Aerial Survey”, Environmental Science & Technology, 56, no. 7 (March 23, 2022): 4317–4323. https://doi.org/10.1021/acs.est.1c06458.
Shi, Lin, Katharine Mach, Sangwon Suh, and Adam Brandt. “Functionality-Based Life Cycle Assessment Framework: An Information and Communication Technologies (ICT) Product Case Study”, Journal of Industrial Ecology, 26, no. 3 (February 15, 2022): 782-800. https://doi.org/10.1111/jiec.13240 Find it @ Stanford.
Bell, Clay, Jeff Rutherford, Adam Brandt, Evan Sherwin, Timothy Vaughn, and Daniel Zimmerle. “Single-Blind Determination of Methane Detection Limits and Quantification Accuracy Using Aircraft-Based LiDAR”, Elementa: Science of the Anthropocene, 10, no. 1 (January 4, 2022): 00080. https://doi.org/10.1525/elementa.2022.00080.
Wang, Jinfang, Jingwei Ji, Arvind Ravikumara, Silvio Savarese, and Adam Brandt. “VideoGasNet: Deep Learning for Natural Gas Methane Leak Classification Using an Infrared Camera” 238 (January 1, 2022): 121516. https://doi.org/10.1016/j.energy.2021.121516.
Teichgraeber, Holger, Lucas Küpper, and Adam Brandt. “Designing Reliable Future Energy Systems by Iteratively Including Extreme Periods in Time-Series Aggregation”, Applied Energy, 304 (December 15, 2021): 117696. https://doi.org/10.1016/j.apenergy.2021.117696.
Zhang, Zhan, Evan Sherwin, and Adam Brandt. “Estimating Global Oilfield-Specific Flaring With Uncertainty Using a Detailed Geographic Database of Oil and Gas Fields”, Environmental Research Letters, 16, no. 12 (November 30, 2021): 124039. https://doi.org/10.1088/1748-9326/ac3956.
El Abbadi, Shar, Evan Sherwin, Adam Brandt, Stephen Luby, and Craig Criddle. “Displacing Fishmeal With Protein Derived from Stranded Methane”, Nature Sustainability, 5 (November 22, 2021): 47–56. https://doi.org/10.1038/s41893-021-00796-2.
Masnadi, Mohammad, Giacomo Benini, Hassan El-Houjeiri, Alice Milivinti, James Anderson, Timothy Wallington, Robert De Kleine, Valerio Dotti, Patrick Jochem, and Adam Brandt. “Carbon Implications of Marginal Oils from Market-Derived Demand Shocks”, Nature Research, 599, no. 7883 (November 3, 2021): 80–84. https://doi.org/10.1038/s41586-021-03932-2.
Orsini, Rachel, Philip Brodrick, Adam Brandt, and Louis Durlofsky. “Computational Optimization of Solar Thermal Generation With Energy Storage”, Sustainable Energy Technologies and Assessments, 47, no. 3 (October 2021): 101342. https://doi.org/10.1016/j.seta.2021.101342.
Rutherford, Jeffrey, Evan Sherwin, Arvind Ravikumar, Gavin Heath, Jacob Englander, Daniel Cooley, Mark Omara, Quinn Lanfitt, and Adam Brandt. “Closing the Methane Gap in US Oil and Natural Gas Production Emissions Inventories”, Nature Communications, 12, no. 1 (August 5, 2021): 4715. https://doi.org/10.1038/s41467-021-25017-4.
Nie, Yuhao, Ahmed Zamzam, and Adam Brandt. “Resampling and Data Augmentation for Short-Term PV Output Prediction Based on an Imbalanced Sky Images Dataset Using Convolutional Neural Networks”, Solar Energy, 224 (August 2021): 341-54. https://doi.org/10.1016/j.solener.2021.05.095.