Underground natural gas (NG) pipeline leakage can result in methane (CH4) buildup and migration through the soil. What is not well understood in such scenarios is how the soil conditions affect the gas migration behavior, particularly in regard to the relative contributions of specific soil properties such as soil moisture content. The objective of this study was to investigate the effects of soil properties on CH4 concentration and migration from leaking underground NG pipelines. Site characteristics such as surface cover and spatial dimensions, soil samples, and gas concentration data were collected from over 70 gas leakage sites across the United States using a standardized sampling method. Soil samples were collected from excavation sites that were 1.5′–5′ in depth. The collected soil samples were analyzed in the laboratory to measure the soil texture, permeability, and moisture. Statistical analysis was performed to evaluate the effects of soil properties on CH4 migration distance and concentration. Soil texture was consistent across geographic locations due to standardized pipeline backfill protocols, allowing for the analysis of gas concentration and transport data with respect to soil conditions. Soil moisture content was the dominant influence on the gas concentration and spreading distance. High soil moisture content was associated with reduced lateral diffusion and elevated concentrations near the leak point, whereas dry conditions were associated with reduced concentrations and greater spreading distance. Increasing soil moisture content reduced the lateral diffusion of CH4 into the soil due to water-induced tortuosity, resulting in elevated concentrations close to the leak point. Lateral migration of CH4 was suspected to be by diffusion, starting at 5 m from the leaks, while transport within the immediate vicinity of the leak was controlled by advection. These findings demonstrate a pronounced effect of soil moisture content and permeability on CH4 migration distance and concentration, providing key insight into the effects of soil conditions on NG migration and how to account for such effects in leak detection surveys.
Wide-area aerial methods provide comprehensive screening of methane emissions from oil and gas (O&G) facilities in production basins. Emissions detections (`plumes') from these studies are also frequently scaled to basin level. However, little information exists to determine if plumes detected fugitive emissions or known, reported, maintenance activities. This study analyzed an aircraft field study in the Denver-Julesberg basin to quantify how often plumes identified maintenance events, using a geospatial inventory of 12,629 O&G facilities with facility outlines. Study partners (7 midstream and production operators) provided timing and location of 5910 maintenance events that occurred in a 6-week period. Results indicated three substantial uncertainties with potential bias unaddressed by current prior studies. First, plumes often detect maintenance events, which short-duration, large, and poorly estimated by aircraft methods: 9.2% to 48% [35% to 62%] of plumes on production were likely due to known maintenance events. Second, data indicated that plumes on midstream facilities were both infrequent and unpredictable, calling into question whether these estimates were representative of midstream emissions. Finally, 4 plumes attributed to O&G, representing 19% of all emissions, were not aligned with any location that would logically create emissions. While it is unclear how frequently this occurs, in this study it had material impact on emissions estimates and was detectable only with complete geospatial information. While aircraft emissions detection remains a powerful tool for identifying methane emissions on oil and gas facilities, this study indicates that additional data inputs, such as detailed GIS data, a more nuanced analysis of emission persistence and frequency, and improved sampling strategies are required to accurately scale plume estimates to basin emissions.
In November 2019, a joint team from Colorado State University and the University of Rwanda intervened to repair a failed pico-hydropower plant in southwestern Rwanda. In a common outside-intervention model, the plant had been constructed by U.S. university team that later, for unknown reasons, couldn't provide additional intervention. The system had failed in 2016 after three years of operation. The qualitative analysis completed during the repair visit identified three primary issues which led to system failure: shortage of local management and technical skills resulting in poor maintenance and no financial reserves, poor local availability of common materials and tools needed for maintenance, and lack of community education to manage the plant. The analysis also includes an assessment of progress on these issues. While immediate technical issues have been resolved and training improved, fundamental operational processes require substantial additional work. The objective of this paper is to highlight, as is too infrequently the case, a failed village electrification project. Only by illuminating what isn't working can the development community learn the best practices.
In this first-of-its-kind Mid-Continent Methane Emissions Study, researchers from across the region, universities, government agencies, and industries joined forces determined to reconcile discrepancies between measurement methods in methane loss rates from onshore oil and gas developments in multiple basins. Seeking to bring public and private sectors better understanding of this issue, the combined resources of these groups resulted in weeks of field study and conclusive data. This team discovered that in other studies, top-down measurements reported much higher methane leak rates than bottom-up methods. Equipped with that knowledge this team used paired measurements from the same natural gas sources to determine the inconsistencies in measurement methods. The result of a field campaign, which happened over a five week period from late September to early October, 2015 is described in the study overview.
Worldwide, more than one billion people lack access to electricity. Village electrification using microgrids has the potential to provide rural households with reliable electricity that not only delivers light but also creates opportunities to use electricity for productive uses that enable economic development. Using a stochastic simulation model, we demonstrate that costs can be reduced by designing for less than 100% reliability, but the cost tradeoff is significantly impacted by the capital investment in distribution systems. Models also illustrate how active encouragement of productive use can transition microgrids from demonstration projects to `bankable' investments. Modeling indicates that load growth of 9% annually for 8 years - an achievable goal with proper information and access to capital - lowers the cost of electricity supply by greater than 25%. Growth models also illustrate that higher total growth should be coupled with diversification of both generation and loads. Our results have several important policy implications. First, rural electrification can be cost effectively achieved if integrated with rural development, and conversely, electrification without sufficient attention to development is unlikely to produce economically sustainable systems. Second, regulators should consider standards requiring that private providers of electricity have effective processes for both cost minimization & encouragement of local development.
