Monitoring Injected CO2 Using Earthquake Waves Measured by Downhole Fibre-Optic Sensors: CO2CRC Otway Stage 3 Case Study

Sensors (Basel). 2022 Oct 16;22(20):7863. doi: 10.3390/s22207863.

Abstract

Monitoring changes of formation properties along the well bore associated with the presence of carbon dioxide can be important for both tracking the plume inside of the primary containment and detecting leakage into the zone located above the reservoir. This can be achieved with time lapse wireline logging, but this approach requires well intervention and is not always possible. If the well is permanently instrumented with an optical fibre, it can be used as a distributed seismic receiver array to detect gas behind the casing by monitoring changes in amplitude of the seismic waves generated by active or passive seismic sources. Previous research showed the efficacy of this technique using continuous seismic sources. The Stage 3 Otway Project presented an opportunity to test this technique using passive seismic recording, as downhole fibre-optic arrays recorded numerous regional earthquakes over the period of nearly 2 years before, during, and after CO2 injection. Analysis of P-wave amplitudes extracted from these downhole gathers shows a consistent amplitude anomaly at the injection level, visible in all events that occurred after the start of injection. This indicates that the anomaly is caused by changes in elastic properties in the reservoir caused by CO2 saturation. However, extracted amplitudes show significant variability between earthquakes even without subsurface changes; thus, multiple events are required to distinguish the time-lapse anomaly from time-lapse noise. Ubiquity of these events even in a tectonically quiet region (such as Australia) makes this technique a viable and cost-effective option for downhole monitoring.

Keywords: CCUS; distributed acoustic sensing; earthquake; fibre-optic; monitoring; passive seismic.

Grant support

The Otway Project received CO2CRC Ltd. funding through its industry members and research partners, the Australian Government under the CCS Flagships Programme, the Victorian State Government, and the Global CCS Institute. The authors wish to acknowledge financial assistance provided through Australian National Low Emissions Coal Research and Development. ANLEC R&D is supported by Low Emission Technology Australia (LETA) and the Australian Government through the Department of Industry, Science, Energy, and Resources. The authors acknowledge the financial support from the Department of Industry Innovation and Science for the 2021 Global Innovation Linkage (GILIII000114) grant funding the development of passive seismic data analysis techniques.