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Target-oriented joint inversion of incomplete time-lapse seismic data sets

Gboyega Ayeni and Biondo Biondi


We propose a joint inversion method, based on linear least-squares wave-equation inversion, for imaging incomplete time-lapse seismic data sets. Such data sets can arise from presence of production facilities or intentional sparse sampling. These data sets generate undesirable artifacts that degrade the quality of time-lapse seismic images, making them unreliable indicators of production-related changes in reservoir properties. To solve this problem, we pose time-lapse imaging as a joint linear inverse problem that utilizes concatenations of target-oriented approximations to the least-squares imaging Hessian. Using a subset of the 2D Marmousi model, we show that the proposed method gives reliable time-lapse seismic images from incomplete seismic data sets.