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Gravity inversion of basement relief using imperialist competitive algorithm with hybrid techniques

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Abstract

Classically, local deterministic optimization techniques have been employed to solve such nonlinear gravity inversion problem. Nevertheless, local search methods can also be easily implemented and demonstrate higher rates of convergence; but in highly nonlinear cases such as geophysical problems, they require a reliable initial model which should be adequately close to the true model. Recently, global optimization methods have shown promising results as an alternative to classical inversion methods. Each of the global optimization algorithms has unique benefits and faults; therefore, applying different combinations of them is one of the proposed solutions for overcoming their distinct limitations. In this research, the design and implementation of the hybrid method based on a combination of the imperialist competitive algorithm (ICA) and firefly algorithm (FA) as tools of two-dimensional nonlinear modeling of gravity data and as a substitute for the local optimization methods were investigated. Hybrid of ICA and FA algorithm (known as ICAFA) is a modified form of the ICA algorithm based on the firefly algorithm. This modification results in an increase in the exploratory capability of the algorithm and improvement of its convergence rate. This inversion technique was first successfully tested on a synthetic gravity anomaly originated from a simulated sedimentary basin model both with and without the presence of white Gaussian noise (WGN). At last, the method was applied to the Bouguer anomaly from a real gravity profile in Moghan sedimentary basin (Iran). The results of this modeling were compatible with previously published works which consisted of both seismic analysis and other gravity interpretations. In order to estimate the uncertainty of solutions, several inversion runs were also conducted independently and the results were in line with the final solution.

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Data availability statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. These data are protected by the National Iranian Oil Company (NIOC).

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Correspondence to Alireza Arab-Amiri.

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Communicated by Michal Malinowski (CO-EDITOR-IN-CHIEF)/Teresa Grabowska, Ph.D. (ASSOCIATE EDITOR).

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Joolaei, A., Arab-Amiri, A. & Nejati, A. Gravity inversion of basement relief using imperialist competitive algorithm with hybrid techniques. Acta Geophys. 70, 2629–2646 (2022). https://doi.org/10.1007/s11600-021-00597-3

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