Well Sequencing and Managing Reservoir Stress Response in the Permian: Implications for Child-Well Completions Using High-Resolution Microseismic Analysis
In this case study, three sequential well pads were designed, stimulated and monitored to evaluate 1. Treatment order of stacked wells across multiple benches, 2. Completions optimization in proximity to a parent well and 3. The efficacy of treatment sequence in proximity to parent wells. Microseismic data were evaluated in conjunction with tracer and pressure data to provide a more detailed understanding of reservoir deformation and well connectivity using statistical approaches that consider the collective behavior of seismicity. High-resolution microseismic involves analyzing spatio-temporal trends in seismicity rather than reliance on microseismic event clouds to provide more meaningful assessment of hydraulically-linked seismicity vs. stress-driven seismicity. The findings of the first two case studies were applied to the stimulation of the third well pad to demonstrate the role of well sequencing in proximity to depleted zones and the impacts of completions design in managing well communication. Here we discuss the benefit of high-resolution microseismic in assessing perceived well interference by delineating the difference between hydraulically-linked and stress-driven seismicity recorded during multi-well hydraulic fracturing programs. In applying knowledge of reservoir deformation processes to customize stimulation programs, operators have additional tools to help manage reservoir stress, limit unwanted well communication and optimize production.
Mike Preiksaitis is a Geophysical Specialist with ESG’s global energy services division, where he is a senior resource to processing and interpretation teams for hydraulic fracture monitoring projects.
Mike joined ESG in 2011 as a geophysicist and has played an integral role in the growth of ESG’s FRACMAP® monitoring and processing services, with experience in microseismic array design, advanced processing and interpretation.
He graduated from the Geophysics program at the University of Alberta in Canada and is currently a registered professional geoscientist (P.Geo). Prior to joining ESG, Mike worked as a geophysical processor at CGG where he processed conventional 2D/3D seismic data.
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