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2-D gravity inverse modelling of anticlinal structure using improved particle swarm optimization (IPSO)

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Abstract

In this paper, the scalene triangle geometric model is considered in order to simulate the anticlinal structures as this model is closer to the reality. The required mathematical relationship is expanded to compute the gravity effect of the scalene triangle model. Furthermore, an improved particle swarm optimization algorithm, known as improved particle swarm optimization (IPSO), has been discussed which is considered as a global optimization technique, being capable of improving the global search of particles in the whole search space. The ability of finding the optimal solution is adjusted by inertia weight (w) and acceleration coefficients (c1 and c2). For testing the ability of the IPSO algorithm, a theoretical scalene triangle model was considered as z1=2 km, z2=5 km, i=70 deg., j=30 deg., and Δρ=1000 kg/m3. The IPSO inversion of the noise-free and noise-corrupted synthetic gravity data inferred the structures similar to the assumed one where the estimated objective function values are 0.0004 and 0.0817, respectively. The inverted parameters prove the stability and efficiency of the IPSO method. This method also has been applied for a real gravity data set due to an anticlinal structure from Iran which can be significant for its probable oil and gas potential. The values of the estimated parameters for the subsurface anticlinal structure from the IPSO inversion are z1=3.52 km, z2=5.37 km, i=28.93 deg., j=26.37 deg., and Δρ=346.4 kg/m3.

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Authors and Affiliations

  1. Department of Geology, University of Isfahan, Isfahan, Iran

    Ata Eshaghzadeh

  2. Department of Physics, Najafabad Branch, Islamic Azad University, Najafabad, Iran

    Alireza Hajian

Authors
  1. Ata Eshaghzadeh
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  2. Alireza Hajian
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Correspondence to Ata Eshaghzadeh.

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Responsible editor: Narasimman Sundararajan

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Eshaghzadeh, A., Hajian, A. 2-D gravity inverse modelling of anticlinal structure using improved particle swarm optimization (IPSO). Arab J Geosci 14, 1378 (2021). https://doi.org/10.1007/s12517-021-07798-6

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  • DOI: https://doi.org/10.1007/s12517-021-07798-6

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