Using a genetic algorithm for 3-D inversion of gravity data in Fuerteventura (Canary Islands)

Abstract

The use of genetic algorithms in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the non-linearity inherent in such applications. We have implemented a genetic algorithm to efficiently invert a set of gravity data. Employing several fixed density contrasts, this algorithm determines the geometry of the sources of the anomaly gravity field in a 3-D context. The genetic algorithms, based on Darwin's theory of evolution, seek the optimum solution from an initial population of models, working with a set of parameters by means of modi. cations in successive iterations or generations. This searching method traditionally consists of three operators ( selection, crossover and mutation) acting on each generation, but we have added a further one, which smoothes the obtained models. In this way, we have designed an efficient inversion gravity method, confirmed by both a synthetic example and a real data set from the island of Fuerteventura. In the latter case, we identify crustal structures related to the origin and evolution of the island. The results show a clear correlation between the sources of gravity field in the model and the three volcanic complexes recognized in Fuerteventura by other geological studies.