Application of diffracted wave analysis to time‐lapse seismic data for CO2 leakage detection

Abstract

ABSTRACTTime‐lapse seismic analysis is utilized in CO2 geosequestration to verify the CO2 containment within a reservoir. A major risk associated with geosequestration is a possible leakage of CO2 from the storage formation into overlaying formations. To mitigate this risk, the deployment of carbon capture and storage projects requires fast and reliable detection of relatively small volumes of CO2 outside the storage formation. To do this, it is necessary to predict typical seepage scenarios and improve subsurface seepage detection methods. In this work we present a technique for CO2 monitoring based on the detection of diffracted waves in time‐lapse seismic data. In the case of CO2 seepage, the migrating plume might form small secondary accumulations that would produce diffracted, rather than reflected waves. From time‐lapse data analysis, we are able to separate the diffracted waves from the predominant reflections in order to image the small CO2 plumes. To explore possibilities to detect relatively small amounts of CO2, we performed synthetic time‐lapse seismic modelling based on the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) Otway project data. The detection method is based on defining the CO2 location by measuring the coherency of the signal along diffraction offset‐traveltime curves. The technique is applied to a time‐lapse stacked section using a stacking velocity to construct offset‐traveltime curves. Given the amount of noise found in the surface seismic data, the predicted minimum detectable amount of CO2 is 1000–2000 tonnes. This method was also applied to real data obtained from a time‐lapse seismic physical model. The use of diffractions rather than reflections for monitoring small amounts of CO2 can enhance the capability of subsurface monitoring in CO2 geosequestration projects.