Time-lapse image registration using the local similarity attribute

Conclusions

We propose a method of time-lapse image registration based on an application of the local similarity attribute. The local attribute provides a smooth continuous measure of similarity between two images. Perturbing the monitor image by stretching and squeezing it in time while picking its best match to the base image enables an effective registration algorithm. The by-product of this process is an estimate of the time-lapse seismic velocity ratios in the reservoir interval.

Using synthetic and real data examples, we have demonstrated the ability of our method to achieve an accurate time-domain image registration and to remove artifact time-lapse differences caused by velocity changes. Unlike some of the alternative cross-equalization methods, the proposed method is not influenced by amplitude differences and can account for velocity changes in the shallow overburden.