Potential field data interpretation to detect the parameters of buried geometries by applying a nonlinear least-squares approach

Gravity profiles interpretation applying a metaheuristic particle optimization algorithm of mineralized bodies resembled by finite elements

“…Gravity anomalies are frequently characterized by variations in rock density, and the inversion of this data is crucial for determining the mass properties and depths of the subsurface. Over the years, numerous geophysical methods for solving inverse problems have been developed, including robust simultaneous joint inversion [ 1 ], fair-function minimization [ 2 ], the s-curves method [ 3 ], non-linear least-squares [ 4 , 5 ], derivative-based approaches [ 6 , 7 ], moving average methods [ 8 , 9 ], multiple-linear regression [ 10 ], R-parameter imaging [ 11 ], and the Lanczos bidiagonalization method [ 12 ]. Metaheuristic optimization algorithms, such as genetic algorithms [ 13 ], particle swarm optimization [ [14] , [15] , [16] , [17] ], simulated annealing [ 18 ], cuckoo optimization algorithm [ 19 ], and ant colony algorithm [ 20 ], have also been used recently for gravity data inversion.…”

A Novel Metaheuristic Strategy for the Elucidation of Gravity Anomalies with Application to Geothermal Energy Investigations and Volcanic Activity Studies: Hunger Games Search (HGS)

“…The gravity method in geophysics, a traditional, passive, non-invasive, and costefficient method, measuring the variation in the Earth's gravitational field caused by the difference of rock mass properties at a certain position, has been applied in a large spectrum of projects such as ore/mineral exploration (Hinze, 2013;Chen et al, 2015;Li et al, 2019; Essa and Abo-Ezz, 2021) [1][2][3][4] , archaeology investigation (Branston and Styles, 2006;Batayneh et al, 2010; Sarlak and Aghajani, 2017) [5][6][7] , radioactive waste management (An et al, 2013) [8] , weapons and unexploded ordnances detection (Abedi et al, 2014) [9] , Hydrocarbon/reservoir (oil and gas) recognition (Yuan et al, 2018; Saghafi and Yarveicy, 2019; Cho et al, 2020) [10][11][12] , geothermal energy and volcanic activity study (Altwegg et al, 2015; Uwiduhaye et al, 2018; Essa and Diab, 2022) [13][14][15] , underground cavities or tunnels identification (Pazzi et [16][17][18] , geotechnical and engineering application (Debeglia and Dupont, 2002;Arisona et al, 2018) [19,20] , groundwater monitoring (Frappart and Ramillien, 2018; Delobbe et al, 2018) [21,22] , landfills mapping (Silva et al, 2009;Dumont et al, 2017) [23,24] , subsurface structures imaging...…”

Epikarst water detection using integrated geophysical methods

“…As a potential field, all potential field data processing methods can be used for reference in the process of self-potential data processing. Least square method [ [17] , [18] , [19] , [20] , [21] , [22] , [23] ]、Particle Swarm Optimization (PSO) [ 24 , 25 ], Very Fast Simulated Annealing (VFSA) overall optimization algorithm [ 26 , 27 ] 、Potential-field separation [ 28 ] 、 field source rapid imaging method [ 29 , 30 ] and Bat optimizing algorithm (BOA) [ 31 ]are some common methods in the process of self-potential data processing. Potential field separation can improve the accuracy of detection, and the fast imaging method of potential field source can provide relevant information of field source.…”