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Seismic characterization and monitoring of a deep CO2 storage reservoir with 3D VSP using direct shear waves

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Abstract We show a low-cost option for shear wave imaging of CO 2 storage reservoirs that utilizes seismic waves that have been ignored by reflection seismologists for decades. These overlooked… Click to show full abstract

Abstract We show a low-cost option for shear wave imaging of CO 2 storage reservoirs that utilizes seismic waves that have been ignored by reflection seismologists for decades. These overlooked waves are direct-S waves generated by vertical-displacement vibrators and explosive sources. Shear waves are known to be helpful for detecting fractures and subtle faults which is critical for evaluating of CO 2 storage capacity and sealing properties of the caprock. Utilizing direct-S waves produced by P-wave sources provides these benefits with no need to deploy special shear-wave sources. In addition, the SV-P mode, which is the upgoing P-wave produced by SV-to-P conversion, makes it possible to utilize S-wave attributes with data recorded by vertical geophones only. We developed a processing workflow to extract SV-SV and SV-P seismic modes from 3D VSP data acquired over a CO 2 storage reservoir at Decatur, Illinois and tested these modes for seismic imaging and monitoring of the reservoir. In addition, we inspected an SH-SH mode that appeared interpretable in our data. We observed that direct-S images were consistent with traditional VSP direct-P images and calibration synthetic seismograms. A joint analysis of all available seismic modes allowed a constrained interpretation of faults within the reservoir. Direct-S waves appeared to not be advantageous for CO 2 plume growth monitoring in the Decatur project. The SV-P mode demonstrated low sensitivity to CO 2 concentration. The time-lapse difference for the SV-SV mode was uninterpretable due to the low signal-to-noise ratio of that mode.

Keywords: storage; mode; reservoir; vsp; shear waves; storage reservoir

Journal Title: Journal of Petroleum Science and Engineering
Year Published: 2017

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