A Simulation Method for Methane Leak Detection and Repair Technologies
Abstract/Contents
- Abstract
- We present a new tool for understanding and predicting the performance of methane leak detection and repair (LDAR) programs. The tool uses a two state Markov model to simulate the evolution of leakage from a natural gas field through time. Leaks are created stochastically at each time step. Leak detection technologies are simulated to determine which leaks can be detected. A Gaussian plume model is used to simulate the dispersion of leaked gas downwind. The tool is applied to a flame ionization detector (FID) method, a manually operated infrared camera (MIR) method, an automated infrared camera (AIR) method, and a distributed detector (DD) method. We compare the performance of each LDAR program and identify the most critical performance indicators. Of the programs simulated here, the AIR method has the highest net present value. All LDAR programs except the FID program have positive mean NPVs over many Markov model realizations. The FID program has negative expected NPV due to its labor intensive detection process, as well as excessive sensitivity which results in costly repair of many small leaks that reduce the economic value of the FID LDAR program. The variance in model results to input assumptions is explored in a sensitivity analysis. Results are found to be most sensitive to the rate of leak production in the natural gas field. The LDAR programs` performances are also sensitive to parameters that are unique to each detection technology, such as the minimum concentration detection limit for the distributed detector method.
Description
| Type of resource | text |
|---|---|
| Date created | July 2015 |
Creators/Contributors
| Author | Kemp, Chandler |
|---|---|
| Primary advisor | Brandt, Adam R. |
| Degree granting institution | Stanford University, Department of Energy Resources Engineering |
Subjects
| Subject | School of Earth Energy & Environmental Sciences |
|---|---|
| Genre | Thesis |
Bibliographic information
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Preferred citation
- Preferred Citation
- Kemp, Chandler. (2015). A Simulation Method for Methane Leak Detection and Repair Technologies. Stanford Digital Repository. Available at: https://purl.stanford.edu/dq879bd1291
Collection
Master's Theses, Doerr School of Sustainability
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- Contact
- brannerlibrary@stanford.edu
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