An approach for random media parameter estimation using seismic reflection data

The traditional approach in seismic imaging assumes homogeneous layers with constant seismic velocities. In the real Earth, layers have numerous small-scale variations of properties (e.g., the seismic P-wave velocity) which are so irregularly distributed that they can no longer be described by deterministic models; statistical approaches have to be used instead. They can be described only by their stochastic properties. In this paper, every distinctive layer is described by its mean velocity, its variance, and a spatial autocorrelation function. This velocity model is transformed into a model for the autocorrelation of the corresponding impulse response. The parameters for this model are then estimated by the minimum least square method using stacked and migrated seismic sections as input. The method is applied to a real seismic data set. Additional borehole data is used to estimate one of the parameters independently and thus to test the approach