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Time-lapse seismic monitoring of carbon storage and sequestration is oftenchallenging because the time-lapse signature of the growth of CO2 plumes isweak in amplitude and therefore difficult to detect seismically. This situationis compounded by the fact that the surveys are often coarsely sampled and notreplicated to reduce costs. As a result, images obtained for different vintages(baseline and monitor surveys) often contain artifacts that may be attributedwrongly to time-lapse changes. To address these issues, we propose to invertthe baseline and monitor surveys jointly. By using the joint recovery model, weexploit information shared between multiple time-lapse surveys. Contrary toother time-lapse methods, our approach does not rely on replicating the surveysto detect time-lapse changes. To illustrate this advantage, we present anumerical sensitivity study where CO2 is injected in a realistic syntheticmodel. This model is representative of the geology in the southeast of theNorth Sea, an area currently considered for carbon sequestration. Our exampledemonstrates that the joint recovery model improves the quality of time-lapseimages allowing us to monitor the CO2 plume seismically.

Compressive time-lapse seismic monitoring of carbon storage and sequestration with the joint recovery model