Comparing Natural Gas Leakage Detection Technologies Using an Open-Source “Virtual Gas Field” Simulator

We present a tool for modeling the
performance of methane leak
detection and repair programs that can be used to evaluate the effectiveness
of detection technologies and proposed mitigation policies. The tool
uses a two-state Markov model to simulate the evolution of methane
leakage from an artificial natural gas field. Leaks are created stochastically,
drawing from the current understanding of the frequency and size distributions
at production facilities. Various leak detection and repair programs
can be simulated to determine the rate at which each would identify
and repair leaks. Integrating the methane leakage over time enables
a meaningful comparison between technologies, using both economic
and environmental metrics. We simulate four existing or proposed detection
technologies: flame ionization detection, manual infrared camera,
automated infrared drone, and distributed detectors. Comparing these
four technologies, we found that over 80% of simulated leakage could
be mitigated with a positive net present value, although the maximum
benefit is realized by selectively targeting larger leaks. Our results
show that low-cost leak detection programs can rely on high-cost technology,
as long as it is applied in a way that allows for rapid detection
of large leaks. Any strategy to reduce leakage should require a careful
consideration of the differences between low-cost technologies and
low-cost programs.