The problem of reconstructing time-lapse velocity anomalies using cross-well data is considered. In practice, these subsurface velocity changes can be caused by the oil production activities, and cross-well seismic is a possible tool for their monitoring. The time-lapse cross-well tomography inverts time-lapse time delay between monitor and baseline first-arrivals into a velocity change. However, the cross-well tomography has limited resolution due to specific acquisition geometry. Sometimes it may create problems for determining the lateral extent of anomalies. The use of reflections in cross-well data may improve the resolution and provide additional information to constrain velocity model. We propose to optimize the functional based on the linear combination of weighted norm of correlation of time-lapse reflection images and direct arrivals. The simple numerical experiment demonstrated that the proposed functional allows us to reduce the uncertainties in determining lateral size of an anomaly and it's velocity. Also this functional is not sensitive to possible difference in the waveforms of baseline and monitor data.


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