FEAST: Fugitive emissions abatement simulation testbed

The Fugitive Emissions Abatement Simulation Testbed (FEAST) allows users to estimate the costs and benefits of various methane leak detection and repair (LDAR) programs. FEAST simulates a virtual gas field, in which leaks are created over time using a random process supported by empirical leak datasets. The model then simulates the application of various LDAR technologies against this virtual gas field, determining which leaks will be fixed and repaired using a given technology.

To maximize the usefulness of this model, we have made the FEAST model and extensive model documentation available as open-source tools for community use. Please use as desired with proper attribution.

Materials

Try FEAST with an interactive browser-based tutorial: [Link to IPython Notebook]

The open-source FEAST model files (Python) are available here: [Link to GitHub]

The open-source FEAST model documentation is available here: [PDF]

Copyright and license

FEAST: Fugitive Emissions Abatement Simulation Toolkit. Copyright (2016), Chandler E. Kemp; Arvind P. Ravikumar; Adam R. Brandt.

FEAST is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. FEAST is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Outdated FEAST model versions [for archival purposes only, use current version above]

Original MATLAB version: [Link to Dropbox]

Publications

2018

Ravikumar, A.P., J. Wang, M. McGuire, C. Bell, D. Zimmerle, A.R. Brandt. “Good versus Good Enough?” Empirical tests of methane leak detection sensitivity of a commercial infrared camera. Environmental Science & Technology. DOI: 10.1021/acs.est.7b04945

2017

Ravikumar, A.P., A.R. Brandt. Designing better methane mitigation policies: The challenge of distributed small sources in the natural gas sector. Environmental Research Letters 12 044023

Ravikumar, A.P., Wang, J., Brandt, A.R. Are Optical Gas Imaging Technologies Effective for Methane Leak Detection? (2017) Environmental Science and Technology, 51 (1), pp. 718-724. DOI: 10.1021/acs.est.6b03906.

2016

Kemp, C.E., Ravikumar, A.P., Brandt, A.R. (2016) Comparing natural gas leakage detection technologies using an open-source “virtual gas field” simulator. Environmental Science & Technology. DOI: 10.1021/acs.est.5b06068.

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.