Solving the Multimodal Problem of 4D Seismic to Well Tying, a Comparison of 3 Different Stochastic Algorithms.

I compare different sets of solutions obtained with three stochastic algorithms to a highly multimodal inverse problem: the seismic to well tying of Time-Lapse Data. The problem is to find the perturbations of velocity and density in a layered model which explain the differences between the base and the monitor surveys. Several almost equivalent solutions exist especially if the thicknesses of the layers are thin. To explore the solution space I used three stochastic based optimizers: Simulated Annealing, Genetic Algorithms and Covariance Matrix Adaptation Evolution Strategy. In this paper, I compare the results obtained by the different algorithms not only in terms of speed and fitness but also in the way they offer the widest range of acceptable realizations.