Unraveling the Influence of Environmental Parameters on Methane Behavior from Below-Ground Leaks

To advance leak detection and repair methods for underground natural gas (NG) pipeline leaks, there is a critical need to understand how environmental conditions affect NG migration and how to factor this information into decision making. Although recent technology advances in methane detection have improved above-ground leak detection and repair accuracy and efficiency, these improvements do not readily transfer to subsurface leaks from pipelines due to the complex behavior of subsurface gas migration. To shed light on these concerns, an increased understanding of methane migration after NG release is required to support efficient leak response and effective use of available technologies. In this study, experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of environmental conditions on methane migration caused by leaking pipelines. A previously validated numerical model was modified and used to understand the observed methane behavior and help unravel the relative contribution of environmental parameters. Results illustrate how changes in subsurface, surface and atmospheric conditions can mask leak severity. Methane concentrations vary significantly due to changing meteorological and micrometeorological conditions, where surface concentrations are predicted to increase by as much as four times during lower winds and more stable atmospheric events. The influence of soil texture, leak rate, and moisture on subsurface methane distribution is determined by the relative contribution of advection and diffusion and closely related to the distance to the leak source. Soil moisture and texture complicate gas behavior with texture variations and elevated soil moisture conditions playing a dominant role in locally increasing methane concentrations. Understanding the gas concentration relative to the environmental conditions could assist proper leak detection and classification. In addition to the conditions tested here, many other factors, such as the effect of trenched bed systems or fractured soils should be included in the analysis of gas leakage scenarios to improve industry best practices.