Gravity field inversion using Improved Particle Swarm Optimization (IPSO) for estimation of sedimentary basin basement depth

Abstract

In this paper, for the first time an Improved Particle Swarm Optimization (IPSO) algorithm, is developed to evaluate the 2.5-D basement of sedimentary basin and consequently to simulate its bottom, by using the density contrast that varies parabolically with depth simultaneously. The IPSO method is capable of improving the global search of particles in all of the search fields. Finding the optimum solution is adjusted by an inertia weight and acceleration coefficients. Here, we have examined the ability of the IPSO inversion by the synthetic gravity data due to a sedimentary basin, with and without noise. The calculated depth and gravity of the synthetic model do not differ too much from assumed values due to set limits for model parameters and are always within the range. Also, the mentioned method has been applied for the 2.5-D gravity inverse modelling of a sedimentary basin in Iran. We also have modelled the sedimentary basin in 2-D along seven profiles. Furthermore, using the depth values estimated by IPSO from all profiles, a 3-D model of the sedimentary basin was generated. The obtained maximum depth for this sedimentary basin is 2.62 km.

Fault parameters assessment from the gravity data profiles applying the global particle swarm optimization

“…The global optimization particle swarm method is well-established and has been utilized to solve many geophysical problems (Shaw and Srivastava, 2007;Göktürkler and Balkaya, 2012;Singh and Biswas, 2016;Jamasb et al, 2019;Pace et al, 2019;Essa, 2020;Loni and Mehramuz, 2020;Moura et al, 2020). The particle swarm progression is stochastic and can be outlined by a population of particles known as a swarm.…”

Evaluation of the parameters of the fault-like geologic structure from the gravity anomalies applying the particle swarm

“…A particle swarm was established and presented during the last years to explain various geophysical problems (Singh and Biswas 2016;Roshan and Singh 2017;Essa and Munschy 2019;Loni and Mehramuz 2020;Moura et al 2020).…”

3-D Gravity Modeling of Sedimentary Basin Based on Improved Particle Swarm Optimization Algorithm

“…Also, the PSO algorithm was used for gravity inversion of the 2.5-D sedimentary basin and interpretation of gravity data . To avoid premature convergence to local optimality and increase convergence speed, the authors of [Loni, Mehramuz, 2020 used the IPSO algorithm to estimate the thickness of the sedimentary basin and simulate its model using gravity data. For this aim, the inertia weight coefficient (w) and learning factors (c 1 ,c 2 ) are improved.…”