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3-D GRAVITY MODELING OF SEDIMENTARY BASIN BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
Islamic Azad University
Journal: Geophysical research
Tome: 25
Number: 1
Year: 2024
Pages: 69-85
UDK: 550.831.015
DOI: 10.21455/gr2024.1-5
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Loni
M S. 3-D GRAVITY MODELING OF SEDIMENTARY BASIN BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM // . 2024. Т. 25. № 1. С. 69-85. DOI: 10.21455/gr2024.1-5
@article{Loni
M3-D2024,
author = "Loni
M, S.",
title = "3-D GRAVITY MODELING OF SEDIMENTARY BASIN BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM",
journal = "Geophysical research",
year = 2024,
volume = "25",
number = "1",
pages = "69-85",
doi = "10.21455/gr2024.1-5",
language = "English"
}
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Keywords: IPSO, sedimentary basin, gravity anomaly, density contrast.
Аnnotation: In this research, we utilized the Improved Particle Swarm Optimization (IPSO) algorithm to esti-mate the depth and simulate the 3-D shape of the sedimentary basin with a density contrast that varies parabolically with depth simultaneously. The IPSO algorithm 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 inver-sion 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. We assume the measured gravity fields have been distributed on a horizontal plane and also sedimentary basin is combined of juxtaposition 3-D cubic prisms. The measurement stations of the gravity field (grid nodes) co-incide with center blocks. The initial depth is computed using gravity data and the estimated depths are adjusted with iteration. The above-mentioned algorithm was also used in the Northeast region of Iran for the 3-D gravity inverse modeling of a sedimentary basin. The obtained maximum depth of this sedimentary basin is 2.4 km.
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Chakravarthi V., Gravity interpretation of nonoutcropping sedimentary basins in which the den-sity contrast decreases parabolically with depth, Pure and Applied Geophysics, 1995, vol. 145, pp. 327-335.
Chakravarthi V., Raghuram H.M., Singh S.B., 3-D forward gravity modeling of basement inter-faces above which the density contrast varies continuously with depth, Computers & Geo-sciences, 2002, vol. 28, no. 1, pp. 53-57. https://doi.org/10.1016/S0098-3004(01)00080-2
Chakravarthi V., Singh S.B., Ashok Babu G., INVER2DBASE-A program to compute basement depths of density interfaces above which the density contrast varies with depth, Computers & Geosciences, 2001, vol. 27, no. 10, pp. 1127-1133.
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Chakravarthi V., Sundararajan N., Marquardt optimization of gravity anomalies of anticlinal and synclinal structures with prescribed depth-dependent density, Geophysical Prospecting, 2007, vol. 55, no. 4, pp. 571-587.
Essa K.S., Elhussein M., Gravity Data Interpretation Using Different New Algorithms: A Com-parative Study in Gravity-Geoscience Applications, Industrial Technology, and Quantum Aspect, London, InTechOpen, 2018, 226 p.
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Loni S., Mehramuz M., Comparison of improved particle swarm optimization with Marquardt Algorithm for simulation of sedimentary basin with parabolic density contrast using gravity data, J. Ind. Geophys. Union, 2022, vol. 26, no. 1, pp. 1-15.
Martín Atienza B., Modelado e inversión en 2D y 3D de anomalías gravimétricas producidas por cuerpos cuya geometría y densidad de masa se describen utilizando funciones polinómicas: aplicaciones a datos gravimétricos de Canadá y México, Ph.D. Dissertation, Madrid: Uni-versidad Complutense de Madrid, Espagne, 2001, 465 p.
Monteiro Santos F.A., Inversion of self-potential of idealized bodies’ anomalies using particle swarm optimization, Computers & Geosciences, 2010, vol. 36, no. 9, pp. 1185-1190. https://doi.org/10.1016/j.cageo.2010.01.011
Nickabadi A., Ebadzadeh M.M., Safabakhsh R., A novel particle swarm optimization algorithm with adaptive inertia weight, Applied Soft Computing, 2011, vol. 11, no. 4, pp. 3658 3670. https://doi.org/10.1016/j.asoc.2011.01.037
Pallero J.L.G., Fernández-Martínez J.L., Bonvalot S., Fudym O., Gravity inversion and uncer-tainty assessment of basement relief via Particle Swarm Optimization, Journal of Applied Geophysics, 2015, vol. 116, pp. 180-191.
Parsopoulos K.E., Vrahatis M.N., Recent approaches to global optimization problems through Particle Swarm Optimization, Natural Computing, 2002, vol. 1, pp. 235-306.
Rao D.B., Analysis of gravity anomalies of sedimentary basins by an asymmetrical trapezoidal model with quadratic density function, Geophysics, 1990, vol. 55, pp. 226-231.
Rao C.V., Chakravarthi V., Raju M.L., Parabolic density function in sedimentary basin model-ing, Pure an Applied Geophysics, 1993, vol. 140, pp. 493-501.
Rao C.V., Chakravarthi V., Raju M.L., Forward modelling: gravity anomalies of two-dimensional bodies of arbitrary shape with hyperbolic and parabolic density functions, Computers & Geosciences, 1994, vol. 20, no. 5, pp. 873-880.
Rao C.V., Raju M.L., Chakravarthi V., Gravity modeling of an interface above which the densi-ty contrast decreases hyperbolically with depth, Journal of Applied Geophysics, 1995, vol. 34, iss. 1, pp. 63-67.
Shi Y., Eberhart R.C., A Modified Particle Swarm Optimizer, in International Conference of Evolutionary Computation Proceedings, Anchorage, Alaska, USA, IEEE, 1998, pp. 69-73
Silva J.B.C., Costa D.C.L., Barbosa V.C.F., Gravity inversion of basement relief and estimation of density contrast variation with depth, Geophysics, 2006, vol. 71, pp. J51-J58.
Singh K.K., Singh U.K., Application of Particle Swarm Optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast, Geoscientific Instrumentation, Methods and Data Systems, 2017, vol. 6, no. 1, pp. 193-198.
Sweilam N.H., El-Metwally K., Abdelazeem M., Self potential signal inversion to simple polar-ized bodies using the Particle Swarm Optimization method: A visibility study, Journal of Applied Geophysics, Egyptian Society of Applied Petrophysics, 2007, vol. 6, iss. 1, pp. 195-208.
Xin J., Chen G., Hai Y., A Particle Swarm Optimizer with Multistage Linearly-Decreasing Inertia Weight, in International Joint Conference on Computational Sciences and Optimization, Sanya, China, USA, IEEE, 2009, pp. 505-508.
Yi L., Study on an Improved PSO Algorithm and its Application for Solving Function Problem, International Journal of Smart Home, 2016, vol. 10, no. 3, pp. 51-62.
Chakravarthi V., Gravity interpretation of nonoutcropping sedimentary basins in which the den-sity contrast decreases parabolically with depth, Pure and Applied Geophysics, 1995, vol. 145, pp. 327-335.
Chakravarthi V., Raghuram H.M., Singh S.B., 3-D forward gravity modeling of basement inter-faces above which the density contrast varies continuously with depth, Computers & Geo-sciences, 2002, vol. 28, no. 1, pp. 53-57. https://doi.org/10.1016/S0098-3004(01)00080-2
Chakravarthi V., Singh S.B., Ashok Babu G., INVER2DBASE-A program to compute basement depths of density interfaces above which the density contrast varies with depth, Computers & Geosciences, 2001, vol. 27, no. 10, pp. 1127-1133.
Chakravarthi V., Sundararajan N., Gravity modeling of 21/2-D sedimentary basins–a case of var-iable density contrast, Computers & Geosciences, 2005, vol. 31, no. 7, pp. 820-827. https://doi.org/10.1016/j.cageo.2005.01.018
Chakravarthi V., Sundararajan N., Marquardt optimization of gravity anomalies of anticlinal and synclinal structures with prescribed depth-dependent density, Geophysical Prospecting, 2007, vol. 55, no. 4, pp. 571-587.
Essa K.S., Elhussein M., Gravity Data Interpretation Using Different New Algorithms: A Com-parative Study in Gravity-Geoscience Applications, Industrial Technology, and Quantum Aspect, London, InTechOpen, 2018, 226 p.
Loni S., Mehramuz M., Gravity field inversion using Improved Particle Swarm Optimization (IPSO) for estimation of sedimentary basin basement depth, Contributions to Geophysics & Geodesy, 2020, vol. 50, no. 3, pp. 303-323.
Loni S., Mehramuz M., Comparison of improved particle swarm optimization with Marquardt Algorithm for simulation of sedimentary basin with parabolic density contrast using gravity data, J. Ind. Geophys. Union, 2022, vol. 26, no. 1, pp. 1-15.
Martín Atienza B., Modelado e inversión en 2D y 3D de anomalías gravimétricas producidas por cuerpos cuya geometría y densidad de masa se describen utilizando funciones polinómicas: aplicaciones a datos gravimétricos de Canadá y México, Ph.D. Dissertation, Madrid: Uni-versidad Complutense de Madrid, Espagne, 2001, 465 p.
Monteiro Santos F.A., Inversion of self-potential of idealized bodies’ anomalies using particle swarm optimization, Computers & Geosciences, 2010, vol. 36, no. 9, pp. 1185-1190. https://doi.org/10.1016/j.cageo.2010.01.011
Nickabadi A., Ebadzadeh M.M., Safabakhsh R., A novel particle swarm optimization algorithm with adaptive inertia weight, Applied Soft Computing, 2011, vol. 11, no. 4, pp. 3658 3670. https://doi.org/10.1016/j.asoc.2011.01.037
Pallero J.L.G., Fernández-Martínez J.L., Bonvalot S., Fudym O., Gravity inversion and uncer-tainty assessment of basement relief via Particle Swarm Optimization, Journal of Applied Geophysics, 2015, vol. 116, pp. 180-191.
Parsopoulos K.E., Vrahatis M.N., Recent approaches to global optimization problems through Particle Swarm Optimization, Natural Computing, 2002, vol. 1, pp. 235-306.
Rao D.B., Analysis of gravity anomalies of sedimentary basins by an asymmetrical trapezoidal model with quadratic density function, Geophysics, 1990, vol. 55, pp. 226-231.
Rao C.V., Chakravarthi V., Raju M.L., Parabolic density function in sedimentary basin model-ing, Pure an Applied Geophysics, 1993, vol. 140, pp. 493-501.
Rao C.V., Chakravarthi V., Raju M.L., Forward modelling: gravity anomalies of two-dimensional bodies of arbitrary shape with hyperbolic and parabolic density functions, Computers & Geosciences, 1994, vol. 20, no. 5, pp. 873-880.
Rao C.V., Raju M.L., Chakravarthi V., Gravity modeling of an interface above which the densi-ty contrast decreases hyperbolically with depth, Journal of Applied Geophysics, 1995, vol. 34, iss. 1, pp. 63-67.
Shi Y., Eberhart R.C., A Modified Particle Swarm Optimizer, in International Conference of Evolutionary Computation Proceedings, Anchorage, Alaska, USA, IEEE, 1998, pp. 69-73
Silva J.B.C., Costa D.C.L., Barbosa V.C.F., Gravity inversion of basement relief and estimation of density contrast variation with depth, Geophysics, 2006, vol. 71, pp. J51-J58.
Singh K.K., Singh U.K., Application of Particle Swarm Optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast, Geoscientific Instrumentation, Methods and Data Systems, 2017, vol. 6, no. 1, pp. 193-198.
Sweilam N.H., El-Metwally K., Abdelazeem M., Self potential signal inversion to simple polar-ized bodies using the Particle Swarm Optimization method: A visibility study, Journal of Applied Geophysics, Egyptian Society of Applied Petrophysics, 2007, vol. 6, iss. 1, pp. 195-208.
Xin J., Chen G., Hai Y., A Particle Swarm Optimizer with Multistage Linearly-Decreasing Inertia Weight, in International Joint Conference on Computational Sciences and Optimization, Sanya, China, USA, IEEE, 2009, pp. 505-508.
Yi L., Study on an Improved PSO Algorithm and its Application for Solving Function Problem, International Journal of Smart Home, 2016, vol. 10, no. 3, pp. 51-62.
