Application of Genetic Algorithm Optimization and Least Square Method for depth determination from residual gravity anomalies

ABSTRACT: This paper presents a combining method for depth determination of a buried structure from residual gravity anomalies along profile. Solving nonlinear equations using genetic algorithms till faces some problems. It often divert to the local solution, causing premature convergence. Also, depth determination by using least squares is low accuracy. Here, we present a method based genetic algorithm optimization and least squares to determination the model depth of simple causative sources. Validity of this method is tested by applying synthetic data with random errors. This method has also been applied to real gravity data from USA. The depth obtained by the proposed method is found to be in a very good agreement with the depth obtained from drilling information.