There have been multiple recent advances in geophysical technologies for application in seismic monitoring for CO2 sequestration: Aramco recently conducted a CO2 enhanced oil recovery (CO2-EOR) monitoring pilot project where 1000 geophones were deployed at a depth of 70 m, which enabled a meaningful interpretation of gas plume geometry. Time-lapse distributed acoustic sensing (DAS) has been proven recently as a viable technology for CO2 monitoring; full-waveform inversion (FWI) and machine learning (ML) methods have become robust and practical tools in multiple applications in general, and in CO2 monitoring in particular. All these advances enable us to see the road ahead in fit-forpurpose acquisition designs for surface and borehole DAS, also leveraging FWI and ML in hybrid workflows for optimizing quality of monitoring vs. cost. To highlight this combination we performed a synthetic survey evaluation design (SED) study based on an experimental setup of the DAS equipped test well in Houston.

This content is only available via PDF.
You can access this article if you purchase or spend a download.