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

In: Contributions to Geophysics and Geodesy, vol. 50, no. 3
Soudeh Loni Číslo ORCID - Mahmoud Mehramuz Číslo ORCID
Detaily:
Rok, strany: 2020, 303 - 323
Jazyk: eng
Kľúčové slová:
IPSO, inverse modelling, gravity data, sedimentary basin
O článku:
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.
Ako citovať:
ISO 690:
Loni, S., Mehramuz, M. 2020. Gravity field inversion using Improved Particle Swarm Optimization (IPSO) for estimation of sedimentary basin basement depth. In Contributions to Geophysics and Geodesy, vol. 50, no.3, pp. 303-323. 1338-0540. DOI: https://doi.org/10.31577/congeo.2020.50.3.2

APA:
Loni, S., Mehramuz, M. (2020). Gravity field inversion using Improved Particle Swarm Optimization (IPSO) for estimation of sedimentary basin basement depth. Contributions to Geophysics and Geodesy, 50(3), 303-323. 1338-0540. DOI: https://doi.org/10.31577/congeo.2020.50.3.2
O vydaní:
Vydavateľ: ESI SAS
Publikované: 22. 9. 2020
Verejná licencia:
CC BY-NC-ND