New Energy Research Results Guide Induced Seismicity Modelling; Improve Machine Learning

Vancouver, BC – November 4, 2021 – A new public report and data from Geoscience BC energy research will help to improve models that predict induced seismicity through the use of machine learning techniques applied to northeast British Columbia’s Montney Play.

The project is one of a series of four research projects started in December 2019 to further investigate how and why, in certain circumstances, earthquakes can be caused by hydraulic fracturing and wastewater disposal during natural gas development.

A key finding of the Development of an Induced Seismicity Susceptibility Framework and Map for NEBC using an Integrated Machine Learning and Mechanistic Validation Approach project is that, in general, the local geological conditions are more important than the operational features when building models to predict induced seismicity.

Led by University of British Columbia Professor of Geological Engineering Dr. Erik Eberhardt, the project combined multiple data sets in a machine learning and advanced numerical analysis review, together with laboratory rock data and numerical simulations, to model the relationship between natural gas well hydraulic completions, geology and seismic activity in the Montney Play.

Geoscience BC Executive Vice President & Chief Scientific Officer Carlos Salas said: “Along with other projects in our induced seismicity program, this research is generating ever-improving information to guide regulators and the natural gas sector to help assess risk from hydraulic fracturing and wastewater disposal operations. The same information is also being shared with communities and Indigenous groups to help to answer their questions.”

A final report and data are accompanied by maps showing which areas are more likely susceptible to induced seismicity. The report includes recommendations and guidelines to improve modelling and improve use of machine learning to generate seismicity susceptibility maps.

Accessing Data
View the project page (2019-014) for more information.

View project page             View project in Earth Science Viewer

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For more information, please contact:
Richard Truman
Geoscience BC