The Fugitive Emissions Abatement Simulation Toolkit or FEAST is a model to evaluate the effectiveness of methane leak detection and repair (LDAR) programs at oil and gas facilities. Recent advances in the development of new fixed and mobile (truck-, drone-, plane-, and satellite-based) methane leak detection technologies have led to growing interest in alternative LDAR programs. Thus, FEAST can also be used to compare the relative effectiveness of new technologies and methods as part of LDAR programs. FEAST uses publicly available data-sets on methane emissions and recent data from field tests of new methane leak detection technologies to simulate the performance of LDAR programs.
FEAST was initially developed at the Environmental Assessment and Optimization group at Stanford University and released in 2016 (C.Kemp et al. Environ. Sci. Tech. 50 4546 http://dx.doi.org/10.1021/acs.est.5b06068). The latest version of FEAST, version 3.1, incorporates additional emission data sets, improves parametric representations of new technologies and methods, and explicitly accounts for leaks (unintentional) and vents (intentional) within the simulated oil and gas facility.
FEAST includes a jupyter notebook that can serve as a tutorial. We host a live jupyter notebook that you can access to run FEAST examples without any software installed on your machine. If you want to try out the model quickly and do not need to save your work, follow the "quick access" link below. You may use any username to log in to the notebook. In order to save your work, you will need to have a github account and use it to log in to the jupyter notebook via the "github supported" link below.
Quick access FEAST tutorial without storage: https://feast-tmp.apps.h2.harrisburgu.cloud/
Github supported access to FEAST tutorial with persistent storage: https://feast.apps.h2.harrisburgu.cloud/
FEAST 3.0 Webinar link: https://www.youtube.com/watch?v=RWi8CmmGOPA
A sample of publications using FEAST:
Ravikumar, A., J. Wang, M. McGuire, C. Bell, D. Zimmerle, A. Brandt. "Good versus Good Enough?" Empirical Tests of Methane Leak Detection Sensitivity of a Commercial Infrared Camera. Environ. Sci. Technol. 2018. 10.1021/acs.est.7b04945.
Ravikumar, A., A. Brandt. Designing better methane mitigation policies: the challenge of distributed small sources in the natural gas sector. Environmental Researcher Letters. 2017. 10.1088/1748-9326/aa6791
Kemp, C., A Ravikumar, A. Brandt. Comparing Natural Gas Leakage Detection Technologies Using an Open-Source Virtual Gas Field Simulator. Environ. Sci. Technol. 2016. 10.1021/acs.est.5b06068
For any FEAST-related technical help, please send your questions to: feast.help [at] gmail [dot] com
FEAST is supported with a User Guide, Doc Strings, and an Example Run Script. All three resources are included in the parent directory of the FEAST 3.1 repository.