About LDAR-Sim

To reduce fugitive methane emissions from the oil and gas (O&G) industry, companies implement leak detection and repair (LDAR) programs across their asset base. Traditionally, regulators have specified the use of close-range methods such as the U.S. Environmental Protection Agency's (EPA) Method 21 or Optical Gas Imaging (OGI) cameras for component-level surveys in LDAR programs. New methane detection and measurement technologies that incorporate satellites, aircraft, drones, fixed sensors, and vehicle-based systems have also emerged recently to find leaks and expand the LDAR toolkit. Before applying these technologies and their work practices in LDAR programs, operators and regulators may wish to estimate anticipated emissions reductions and costs. Regulators sometimes require demonstration of equivalence – that the proposed alternative will achieve at least the same emissions reductions as incumbent regulatory methods.

To support this process, the Leak Detection and Repair Simulator (LDAR-Sim) was developed at the University of Calgary (UofC) to evaluate the emissions reduction potential of alternative LDAR programs. The official first version of LDAR-Sim was developed by Thomas Fox, Mozhou Gao, Thomas Barchyn, and Chris Hugenholtz. Details on the original version of LDAR-Sim can be found in thispeer-reviewed article. More recently, the model's functionality and accessibility has been expanded through the IM3S project, a collaboration among the University of Calgary and Highwood Emissions Management, with funding and direction from Petroleum Technology Alliance Canada, Alberta Innovates, Canadian Natural Resources, and the Alberta Energy Regulator. To learn more about LDAR-Sim, please visit the Github page by clicking here.

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Contributors

The LDAR-Sim web app was developed by researchers from the University of Calgary in collaboration with Highwood Emissions Management. Contributions were made by: Soroush Ojagh (UofC), Keegan Shaw (Highwood), Thomas Fox (Highwood), Coleman Vollrath (UofC), Mozhou Gao (UofC), Tyler Gough (UofC), Thomas Barchyn (UofC), and Chris Hugenholtz (UofC).

Research funding for the web app was provided by the Alberta Upstream Petroleum Research Fund and Alberta Innovates.