Analyzing the status of the Kalateh Khij fault using genetic algorithm method using gravity data

Articles in Press

Authors

1 Department of Geophysics, Hamedan Branch, Islamic Azad University, Hamedan, Iran

2 Faculty of Mining, Petroleum and Geophysical Engineering, Shahrood University of Technology

3 Department of Electrical Engineering, Bu-Ali-Sina University, Hamedan, Iran

Abstract

In inverse problems, optimization methods are used to find some physical and geometric parameters of underground structures. In this paper, using gravity data, genetic algorithm is used as an optimization method to estimate the parameters of a fault with finite thickness. For this purpose, synthetic data without and with Gaussian noise from normal and reverse faults are generated in the direction perpendicular to the anomaly strike, and then, with the genetic algorithm, parameters including thickness, upper depth, lower depth, and fault dip angle are obtained. The assumed initial population size is one of the variables affecting the convergence speed of the algorithm and the accuracy of the results. With this method, the parameters of the normal fault model were obtained with noise-free data with an error of less than 1 percent, with data with 5 percent noise with an error of less than 6 percent, and with data with 10 percent noise with an error of less than 10 percent. In the next step, to improve the quality of the estimated parameters, a second-order moving average smoothing filter was used for the reverse fault, which led to improved results and increased the convergence speed of the algorithm. In this case, the parameters were obtained with data with 10% noise with an estimation error of less than 2%. Finally, the algorithm was applied to the real gravity data of the Kalateh-Khij fault, and the results obtained were in acceptable agreement with the geological evidence.

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Articles in Press, Accepted Manuscript
Available Online from 07 June 2025

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