SPE Live: Causal Inferencing for Subsurface Engineering Applications

Join this SPE Live with Professor Sid Misra and discover the transformative power of causal inferencing in subsurface engineering. While widely employed in fields like medicine and econometrics, the application of causal inference in the oil industry remains untapped. In this SPE Live, we explore how causal inference techniques can unlock invaluable insights and optimize processes, particularly in microseismic data analysis and fracture monitoring. By unraveling cause-and-effect relationships within complex datasets, we can pinpoint the key factors that significantly impact fracture propagation and large microseismic events, enabling more informed decision-making. Key topics include the Average Treatment Effect (ATE) and Double Machine Learning (DML) method, empowering accurate quantification of causal relationships while addressing confounding variables. We showcase the advantages of causal inference by comparing its results with traditional statistical associations and correlations. Moreover, we introduce a groundbreaking knowledge-driven causal-inference model designed to extract causal signatures of fracture propagation and identify large magnitude seismic events during hydraulic fracturing. This innovative approach will revolutionize fracture monitoring practices.

Speaker: Dr. Sid Misra, Associate Professor at Texas A&M University.
Moderated by Rui Liu, Research Assistant at Texas A&M University.

Held on Wednesday, May 31, 2023