A Data-estimation Based Approach for Quasi-continuous Reservoir Monitoring using Sparse Surface Seismic Data

In this paper, we present a quasi-continuous monitoring strategy for monitoring carbon dioxide sequestered in geologic reservoirs using surface seismic data. With our approach, the sequestered carbon dioxide can be monitored using migrated images or reconstructed velocity models. In this paper, we show how quasi-continuous monitoring using migrated images compares with quasi-continuous monitoring using reconstructed velocity models obtained through reflection tomography. The proposed quasi-continuous monitoring strategy involves acquiring spatially sparse data at small time intervals. These sparse incremental datasets could be as little as 5-10% of conventional seismic survey datasets. At each incremental time-step, unrecorded data are estimated using the acquired dataset and datasets from other time-steps. Data acquired at earlier and later times are used in the spatio-temporal estimation process. The combined sparse and estimated data are then used to reconstruct the geophysical model of the subsurface.