3D Constraint Inversion Of Gravity Based On Genetic Algorithm

With the continuous development of current geophysical methods, gravity prospecting of mineral exploration as an important approach has its irreplaceable status and value. The physical properties of the inversion of gravity data interpretation is important and difficult. The key is to take advantage of inversion constraints and a priori geological information to avoid multiple equations. Currently, genetic algorithm in geophysical inversion of seismic wave field and mainly seen in terms of the electromagnetic field inversion and in the gravitational potential field inverse problems is seldom used. Noting Compared with traditional optimization methods, global convergence, high search efficiency, not counting the objective function partial derivatives and implicit parallel computing, etc., which will play the role of gravity inversion. Therefore, this article focuses on the three-dimensional gravity anomalies constrained inversion, introduces genetic algorithms and a variety of means of restraint in the inversion technique, compared to a theoretical effect of constrained inversion in different models, and verified by real data constrained inversion good results.First, on the study of the basic theory of the gravitational field, focusing pushed to the gravity anomaly field source cube calculation methods to obtain the gravity anomalies cube forward formula, written in C language program to achieve forward calculation. And in-depth study on how to optimize multi-cube forward computation speed, lay the foundation for the inversion.Secondly, to study the genetic algorithm and Levenberg-Marquardt least squares method. Construction of the underground space and the objective function for a reasonable meshing. And the depth of the weighting introduced into the objective function, overcoming skin effect kernels. Finally joined the upper and lower bounds definite constraints and parameters, making the inversion results more in line with the law of the geophysical field.Again theoretical models were designed more than a single cube model, the double cube models using genetic algorithms for each model inversion and add depth weighted definite constraint parameter constraints. Comparative analysis of the presence or absence of constraint inversion effect, certainly the constraint effect.Finally, the actual gravity inversion method for processing data mining, to verify the validity of the method.