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The EERC is testing a new seismic method for detecting and tracking the carbon dioxide (CO2) injected into oil reservoirs to increase oil production through enhanced oil recovery. By monitoring for physical changes occurring at specific points within a reservoir related to the passing of a CO2 plume, the proof-of-concept technology may provide engineers with useful information about where CO2is moving in a more timely manner than traditional methods.

A seismic source (left picture) at a fixed location periodically sends sonic waves into the subsurface. Reflected energy from the reservoir and other geologic layers returns to an array of separate surface receivers and is recorded for analysis. During injection, as the CO2plume moves through the formation past monitored reflection points, the recorded waveforms from the reservoir reflection should exhibit detectable changes, providing a means of determining when the CO2 plume has moved past the monitored reflection points.

A total of 96 seismic recorders with three-component geophones are being deployed for this test. Each unit is battery-powered and can operate autonomously for up to 60 days with a minimal environmental footprint. The complete array of receivers offers great flexibility in deploying, removing, and servicing the units.

Conventional seismic monitoring methods can provide excellent interpretive results to locate pressure fronts and gas plumes. However, they have some challenges, including high operation costs, large impacts to the survey area because of the great number of receiver locations and source locations required, and long time lapses between surveys.

To address these issues, the EERC method employs a sparse array of strategically placed receivers in conjunction with a single seismic source location. Over the course of a year, the source will be remotely operated at weekly intervals, and a series of time-lapse records from monitored reflection points will be collected and processed monthly. Simple processing allows for a fast turnaround of results. The ability to recognize and act on changes observed to be occurring in the reservoir in near real time is anticipated to offer a significant improvement compared to traditional time-lapse seismic methods. The potential exists for both data collection and processing to eventually be automated for even greater efficiencies.