Automatic velocity analysis by differential semblance optimization

摘要

We present a method for automatic velocity analysis of sesmic data based on differential semblance optimiza- tion(DSO). The data are mapped for each offset from the time domain to the depth domain by a Born migra- tion scheme using ray tracing with the efficient wavefront construction method. The DSO cost functional is eval- uated by taking differences of the migration images for neighboring offsets. The gradient of this functional with respect to the underlying velocity model is obtained by a first-order approximation of the adjoint-state method, leading to an optimal complexity: the cost of evaluating the gradient is about the same as that of evaluating the functional.