Data Proc and Acqui SIG: Characterizing Dynamic Fracture Growth Using DAS-Recorded ... - Oct 11th
Complete Title: Characterizing Dynamic Fracture Growth Using DAS-Recorded Microseismic Reflections
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Speaker: Yuanyuan Ma, Dept of Geoscience, University of Calgary
Co-Authors: David W. Eaton, Chaoyi Wang, Dept of Geoscience, University of Calgary
Distributed acoustic sensing (DAS) is a rapidly developing technology that can be used for characterizing the geometry and propagation of hydraulic fractures. DAS provides observations of microseismic wavefields with high spatial resolution, which contain direct P- and S-arrivals as well as converted and reflected waves. In addition to traditional approaches for microseismic event location and source mechanism analysis, their wide aperture and high spatial resolution means that DAS recordings can be used to image induced fractures using reflected waves. The reflections may be generated by nearby hydraulic fractures from earlier treatment stages or small pre-existing faults. We use a straightforward method based on f-k filtering and ray-tracing to map reflected S-waves from the data domain to the model domain. The presentation will demonstrate the machine learning-assisted processing workflow for DAS microseismic and the detailed fracture imaging approach using field data from the Montney formation in western Canada. The results of fracture imaging indicate fracture development that is consistent with fracture-driven interactions (FDIs) interpreted from low-frequency DAS (LF-DAS) data, as well as distant fractures that do not reach the fiber and thus are not directly observed by LF-DAS. Fracture images using reflections produced by several microseismic events during the same stage provides the opportunity to observe snapshots of dynamic fracture evolution processes.
Speaker Biography: Yuanyuan Ma, Dept of Geoscience, University of Calgary
Yuanyuan Ma is currently a postdoctoral associate at University of Calgary. She received her Ph.D. in Geophysics from China University of Petroleum Beijing in 2020. Her current research focuses on DAS microseismic processing using machine learning, dynamic fracture imaging, and integrated analysis using fiber optic sensing approaches to support hydraulic fracturing operations. She has worked as a visiting student at University of California Berkeley and University of Science and Technology of China.
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