Defining and Improving Accuracy, Precision, and Minimum Detection Levels, of Truck-based Gas Leak Surveys

Canada has set a goal to reduce methane emissions in the upstream oil and gas sector by 45%. An updated regulation, proposed to implement on January 1st, 2020, will require triannual leak inspections of upstream infrastructure. Traditional leak inspection methods have a high cost per inspection and require unfeasible man-hours in the field. Alternative LDAR method Emissions Attribution via Computational Techniques (ExACT), is a currently accepted truck-based leak inspection technology that can inspect hundreds of pieces of infrastructure daily, over large areas. The objective of this research is to improve the accuracy, precision, and minimum detection levels of the ExACT leak inspection technology. Improving these metrics will solidify ExACT as a leading LDAR alternative and provide industry with a realistic LDAR tool to implement their emissions reduction plan. This research will combine existing real-world data, controlled experiments, and computational analysis to verify current ExACT parameters and develop opportunities within ExACT to improve product quality and efficiency. Improving the quality and efficiency of inspection technologies like ExACT will bring Canada closer to a feasible methane emissions reduction plan and allow industry to lead the way.

Faculty Supervisor:

David Risk

Student:

Jacob Johnson;Kimberley Taylor

Partner:

Altus Geomatics

Discipline:

Geography / Geology / Earth science

Sector:

University:

St. Francis Xavier University

Program: