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CompGeo Seminar: "Microseismic 3D Elastic Velocity Inversion: A Marcellus Shale Case Study" with Jeffrey Shragge (Colorado School of Mines)
Title: Microseismic 3D Elastic Velocity Inversion: A Marcellus Shale Case Study
Abstract: Detection and location of small (microseismic) earthquakes is critical due to increasing subsurface fluid injection activities. Accurately locating recorded earthquakes is paramount for improving productivity and reducing potential hazards. A fundamental parameter for either location scenario is the 3D elastic velocity model. Current 3D seismic velocity building techniques are largely based on large magnitude earthquakes and rely on high signal-to-noise data. In this talk I present a new method to jointly invert for the 3D P- and S-wave velocity structure using small-magnitude earthquakes (i.e., -1.15 < Mw < 0.24) without requiring a priori knowledge of the microseismic source initiation time or location. I present a 3D case study from eastern Ohio using a microseismic data set acquired over the prolific Marcellus Shale unit. The success of this method suggests that it is likely applicable in a variety of scenarios ranging from induced seismicity monitoring and regional crustal investigations to earthquake tremor and cryoseismology.
Speaker Bio: Jeffrey Shragge an Associate Professor in the Geophysics Department at the Colorado School of Mines (CSM), and a co-Leader of the Center for Wave Phenomena (CWP) research consortium. He was formerly the Woodside Professor in Computational Geoscience, and an Associate Professor jointly appointed in the School of Earth and Environment and School of Physics at the University of Western Australia. Jeffrey received a BScH (Physics) from Queen’s University, an MSc (Geophysics) from the University of British Columbia, and a PhD (Geophysics) from the Stanford Exploration Project at Stanford University. Jeffrey’s research interests include 3D wave propagation, 3D/4D seismic imaging and velocity inversion, near-surface geophysics, and scientific high-performance computing.