Fluids injected during hydraulic fracturing (fracking) in unconventional shale oil and gas reservoirs, geothermal system enhancement, wastewater disposal, and carbon capture and storage can induce microearthquakes. The spatiotemporal distribution of induced earthquakes is often used to trace the growth of fractures in target layers and guides production. We analyze microseismicity behavior induced by fracking in the Montney Formation, one of the largest unconventional oil and gas reservoirs in North America. An optical fiber deployed in a horizontal well provides extensive spatial sampling and data coverage for microseismic imaging. We design median and F-k filters to predict instrumental and random noise and further suppress them by adaptive noise subtraction. An elliptical vertical transverse isotropic (VTI) velocity model is derived from the Backus-averaged well-log sonic data and is modified to match the microseismic wavefronts by a grid search. We image 41 previously cataloged microearthquakes recorded by distributed acoustic sensing (DAS) using geometric-mean reverse time migration. We find that the fiber geometry’s lack of 2-D/3-D variations increases the nonuniqueness of the image point location, and the $P$ -wave particle motions derived from three-component (3C) geophones data can effectively eliminate the location ambiguity. The spatiotemporal distribution of our updated locations agrees with the fracking schedule. Predicted $P$ - and $S$ -wave travel times from the updated locations also match with the observed waveforms. Analyzing data sensitivity to source locations confirms the potential limitations imposed on source imaging by the geometry of borehole observations and shows that relocation accuracy is directionally dependent. We also investigate the feasibility of estimating source focal mechanisms using realistic DAS and geophone observations. Our study provides guidance for characterizing microearthquake sources and optimizing observation geometry for unconventional reservoirs.
|Original language||English (US)|
|Number of pages||15|
|Journal||IEEE Transactions on Geoscience and Remote Sensing|
|State||Published - Apr 5 2023|
Bibliographical noteKAUST Repository Item: Exported on 2023-06-06
Acknowledgements: The authors thank Tariq Alkhalifah and Isao Kurosawa for their helpful discussions. They also thank the High-Performance Computing (HPC) Team, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, for providing guidance on using IBEX and Shaheen clusters. The computing for this project was partly performed at the OU Supercomputing Center for Education and Research, The University of Oklahoma (OU), Norman, OK, USA. They are also grateful to Japan Oil, Gas and Metals National Corporation, Tokyo, Japan, for their support and permission to publish this work. They also thank Ovintiv Canada ULC, Denver, CO, USA, and Cutbank Dawson Gas Resources, Ltd., Calgary, AB, Canada, for the permission to use the microseismic and well-log data.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.