Convolutional time-lapse seismic modeling for CO_2 sequestration at the Dickman oilfield, Ness County, Kansas

摘要

Time-lapse seismic modeling is routinely used to detect the state of hydrocarbon reservoirs at periodic time intervals. The Dickman field located in the U. S. midcontinent provides two possible CO_2 sequestration targets: a regional deep saline reservoir is the primary objective, and a shallower, mature, depleted oil reservoir is a secondary objective. The goal of this work is to characterize and simulate monitoring of the CO_2 movement before, during, and after its injection into these sequestration targets, including fluid flow paths, reservoir property changes, CO_2 containment, and postinjection stability. Seismic images before, during, and after injection would improve understanding of the carbonate sequestration process and management. Our seismic simulation for time-lapse CO_2 monitoring was based on flow simulator output over a 250-year injection and simulation period. The seismic response was accomplished via convolutional (1D) forward modeling. This work will provide an evaluation for the effectiveness of 4D seismic monitoring in providing assurance of long-term CO_2 containment.