Fast multi-resolution 3D inversion of potential fields with application to high-resolution gravity and magnetic anomaly data from the Eastern Goldfields in Western Australia
We present a fast inversion algorithm tailored for high-resolution potential field (gravity or magnetic) anomaly maps. The algorithm design objectives are to optimize performance with respect to the size of problem that can be solved and computation speed. It is based on a finite element method (FEM...
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| Published in: | Computers & geosciences Vol. 157; p. 104941 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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01.12.2021
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| ISSN: | 0098-3004, 1873-7803 |
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| Abstract | We present a fast inversion algorithm tailored for high-resolution potential field (gravity or magnetic) anomaly maps. The algorithm design objectives are to optimize performance with respect to the size of problem that can be solved and computation speed. It is based on a finite element method (FEM) discretization of both the inversion and forward problems using unstructured tetrahedral meshes with coarsening at the far field. This allows a significant reduction in computational costs from a structured mesh with the same ground level resolution, as well as supporting geometrical features such as topography. Minimization of the cost function uses the Lagrange minimization approach and the resulting system of partial differential equations is solved using the integral preconditioned conjugate gradient method (I-PCG). I-PCG works naturally with an unstructured mesh FEM and can effectively precondition with the Hessian of the regularization term. In contrast to established approaches, minimization of the cost function occurs prior to discretization and using I-PCG avoids the need to invert a large dense sensitivity matrix, a major obstacle to solving large 3D problems using parallel computers. Fast solvers for the forward problem, the adjoint problem and the preconditioner make use of the smoothed aggregation algebraic multi-grid method for the preconditioner in another PCG iteration (AMG-PCG). Parallel implementation uses a domain decomposition approach to support scalability with spatial extent. The proposed method is applied to a synthetic example and tohigh-resolution data set of rastered gravity and magnetic anomaly maps from the Eastern Goldfields in Western Australia with the finest resolution of over 1 million data points and about 60 million cells for the 3D inversion. For this field application we demonstrate that the proposed algorithm achieves computation time scaling with grid size, an indication of optimal algorithm performance and delivers strong scalability with number of cores. The gravity inversion result is compared to the inversion result using the Broyden Fletcher Goldfarb Shanno (BFGS) method on a structured grid.
•Potential field inversion with effectively linear growth of costs with unknowns.•Finite element discretization, fast iterative solvers, and parallel implementation.•Over 1 million data points in a grid with horizontal extent 160 km by 270 km.•Inversion of high-resolution data sets feasible. |
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| AbstractList | We present a fast inversion algorithm tailored for high-resolution potential field (gravity or magnetic) anomaly maps. The algorithm design objectives are to optimize performance with respect to the size of problem that can be solved and computation speed. It is based on a finite element method (FEM) discretization of both the inversion and forward problems using unstructured tetrahedral meshes with coarsening at the far field. This allows a significant reduction in computational costs from a structured mesh with the same ground level resolution, as well as supporting geometrical features such as topography. Minimization of the cost function uses the Lagrange minimization approach and the resulting system of partial differential equations is solved using the integral preconditioned conjugate gradient method (I-PCG). I-PCG works naturally with an unstructured mesh FEM and can effectively precondition with the Hessian of the regularization term. In contrast to established approaches, minimization of the cost function occurs prior to discretization and using I-PCG avoids the need to invert a large dense sensitivity matrix, a major obstacle to solving large 3D problems using parallel computers. Fast solvers for the forward problem, the adjoint problem and the preconditioner make use of the smoothed aggregation algebraic multi-grid method for the preconditioner in another PCG iteration (AMG-PCG). Parallel implementation uses a domain decomposition approach to support scalability with spatial extent. The proposed method is applied to a synthetic example and tohigh-resolution data set of rastered gravity and magnetic anomaly maps from the Eastern Goldfields in Western Australia with the finest resolution of over 1 million data points and about 60 million cells for the 3D inversion. For this field application we demonstrate that the proposed algorithm achieves computation time scaling with grid size, an indication of optimal algorithm performance and delivers strong scalability with number of cores. The gravity inversion result is compared to the inversion result using the Broyden Fletcher Goldfarb Shanno (BFGS) method on a structured grid.
•Potential field inversion with effectively linear growth of costs with unknowns.•Finite element discretization, fast iterative solvers, and parallel implementation.•Over 1 million data points in a grid with horizontal extent 160 km by 270 km.•Inversion of high-resolution data sets feasible. We present a fast inversion algorithm tailored for high-resolution potential field (gravity or magnetic) anomaly maps. The algorithm design objectives are to optimize performance with respect to the size of problem that can be solved and computation speed. It is based on a finite element method (FEM) discretization of both the inversion and forward problems using unstructured tetrahedral meshes with coarsening at the far field. This allows a significant reduction in computational costs from a structured mesh with the same ground level resolution, as well as supporting geometrical features such as topography. Minimization of the cost function uses the Lagrange minimization approach and the resulting system of partial differential equations is solved using the integral preconditioned conjugate gradient method (I-PCG). I-PCG works naturally with an unstructured mesh FEM and can effectively precondition with the Hessian of the regularization term. In contrast to established approaches, minimization of the cost function occurs prior to discretization and using I-PCG avoids the need to invert a large dense sensitivity matrix, a major obstacle to solving large 3D problems using parallel computers. Fast solvers for the forward problem, the adjoint problem and the preconditioner make use of the smoothed aggregation algebraic multi-grid method for the preconditioner in another PCG iteration (AMG-PCG). Parallel implementation uses a domain decomposition approach to support scalability with spatial extent. The proposed method is applied to a synthetic example and tohigh-resolution data set of rastered gravity and magnetic anomaly maps from the Eastern Goldfields in Western Australia with the finest resolution of over 1 million data points and about 60 million cells for the 3D inversion. For this field application we demonstrate that the proposed algorithm achieves computation time scaling with grid size, an indication of optimal algorithm performance and delivers strong scalability with number of cores. The gravity inversion result is compared to the inversion result using the Broyden Fletcher Goldfarb Shanno (BFGS) method on a structured grid. |
| ArticleNumber | 104941 |
| Author | Codd, A.L. Gross, L. Aitken, A. |
| Author_xml | – sequence: 1 givenname: A.L. surname: Codd fullname: Codd, A.L. email: a.codd@uq.edu.au organization: School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD, Australia – sequence: 2 givenname: L. orcidid: 0000-0002-1102-7036 surname: Gross fullname: Gross, L. organization: School of Earth and Environmental Sciences, The University of Queensland, St Lucia QLD, Australia – sequence: 3 givenname: A. surname: Aitken fullname: Aitken, A. organization: School of Earth Sciences, The University of Western Australia, Perth, Western Australia |
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| Cites_doi | 10.1111/j.1365-246X.2006.03011.x 10.1016/j.cageo.2015.08.011 10.1109/99.660313 10.1088/1361-6420/aa8cb0 10.1016/j.cageo.2021.104864 10.1093/gji/ggx511 10.1016/0167-8191(96)00024-5 10.1016/j.cageo.2013.10.004 10.1016/j.cageo.2019.03.008 10.1029/2020JB019825 10.1016/j.cageo.2014.11.010 10.1093/gji/ggz134 10.1002/nme.2579 10.1016/j.cageo.2015.09.005 10.1016/S0377-0427(00)00516-1 10.1016/j.cageo.2021.104701 10.1186/s40623-018-0942-1 10.1186/s40623-015-0265-4 10.1016/j.cageo.2020.104653 10.1190/1.1444302 10.1088/0266-5611/17/6/319 10.1093/gji/ggaa372 10.1093/gji/ggaa425 10.1088/1742-2140/aa8caf 10.1016/j.cageo.2021.104754 10.1145/1089014.1089021 10.1190/1.2831681 10.1088/1742-2132/13/2/S59 10.1093/gji/ggaa378 10.1093/gji/ggaa518 10.5194/se-11-1121-2020 10.1093/gji/ggv396 10.1088/0266-5611/16/5/309 10.1111/j.1365-2478.2011.01052.x 10.1190/1.1443968 10.1093/gji/ggy343 10.1071/EG15041 |
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| References | Astic, Heagy, Oldenburg (b4) 2020; 224 Pallero, Fernández-Martínez, Fernández-Muñiz, Bonvalot, Gabalda, Nalpas (b33) 2021; 146 Jia, Lv, Wang, Carranza, Chen, Wei, Zhang (b24) 2021; 151 Xu, Zou, Wei, Tian, Yuan (b49) 2020 Meng, Li, Xu, Huang, Zhang (b31) 2017; 48 Schaa, Gross, Plessis (b36) 2016; 13 Wang, Ma, Li, Dailei, Zhou, Jin (b47) 2017 Tian, Wang (b40) 2020; 11 Tian, Wang (b39) 2018; 70 Gross, Altinay, Shaw (b16) 2015; 84 Brenner, Scott (b5) 1994 Briggs, Henson, McCormick (b6) 2000 Tian, Ke, Wang (b38) 2018; 15 Ji, Li, Gao, Zhang, Hao (b23) 2018; 215 Liu, Hu, Xi, Liu (b28) 2015; 76 Stuben (b37) 2001; 128 Haber, Ascher, Oldenburg (b20) 2000; 16 Hightower, Gurnis, Van Avendonk (b22) 2020; 223 Farquharson, Ash, Miller (b11) 2008; 27 Li, Oldenburg (b27) 1998; 63 Codd, Gross (b8) 2021 Saad (b35) 2003 Vigneron, Hulot, Olsen, Léger, Jager, Brocco, Sirol, Coïsson, Lalanne, Chulliat, Bertrand, Boness, Fratter (b46) 2015; 67 Aitken, Ramos, Roberts, Greenbaum, Jong, Young, Blankenship (b2) 2020; 125 Codd, Gross (b7) 2017; 212 Wang, Meng, Li (b48) 2015; 85 Geuzaine, Remacle (b13) 2009; 79 Dagum, Menon (b9) 1998; 5 Čuma, Wilson, Zhdanov (b44) 2012; 60 Nearmap (b32) 2019 Lamichhane, Gross (b25) 2017; 33 Martin, Giraud, Ogarko, Chevrot, Beller, Gégout, Jessell (b29) 2020 Tuminaro (b42) 2000 Guo, Li, Jessell, Giraud, Li, Wu, Li, Liu (b18) 2021; 149 Aitken, Altinay, Gross (b1) 2015; 203 Ellery, Codd, Gross (b10) 2020 Geological Survey of Western Australia (b12) 2019 Haber, Ascher (b19) 2001; 17 Heroux, Bartlett, Howle, Hoekstra, Hu, Kolda, Lehoucq, Long, Pawlowski, Phipps, Salinger, Thornquist, Tuminaro, Willenbring, Williams, Stanley (b21) 2005; 31 Renaut, Hogue, Vatankhah, Liu (b34) 2020; 223 Vatankhah, Ardestani, Niri, Renaut, Kabirzadeh (b43) 2019; 128 Gropp, Lusk, Doss, Skjellum (b14) 1996; 22 Anon (b3) 2021 Guenther, Rücker, Spitzer (b17) 2006; 166 Tikhonov, Arsenin (b41) 1977 Gross (b15) 2019; 217 Mayer-Gürr, Behzadpour, Eicker, Ellmer, Koch, Krauss, Pock, Rieser, Strasser, Süsser-Rechberger, Zehentner, Kvas (b30) 2021; 155 Li, Oldenburg (b26) 1996; 61 Čuma, Zhdanov (b45) 2014; 62 Schaa (10.1016/j.cageo.2021.104941_b36) 2016; 13 Aitken (10.1016/j.cageo.2021.104941_b2) 2020; 125 Codd (10.1016/j.cageo.2021.104941_b8) 2021 Heroux (10.1016/j.cageo.2021.104941_b21) 2005; 31 Ji (10.1016/j.cageo.2021.104941_b23) 2018; 215 Čuma (10.1016/j.cageo.2021.104941_b44) 2012; 60 Meng (10.1016/j.cageo.2021.104941_b31) 2017; 48 Guo (10.1016/j.cageo.2021.104941_b18) 2021; 149 Vigneron (10.1016/j.cageo.2021.104941_b46) 2015; 67 Tian (10.1016/j.cageo.2021.104941_b40) 2020; 11 Aitken (10.1016/j.cageo.2021.104941_b1) 2015; 203 Wang (10.1016/j.cageo.2021.104941_b47) 2017 Farquharson (10.1016/j.cageo.2021.104941_b11) 2008; 27 Li (10.1016/j.cageo.2021.104941_b27) 1998; 63 Gross (10.1016/j.cageo.2021.104941_b16) 2015; 84 Stuben (10.1016/j.cageo.2021.104941_b37) 2001; 128 Hightower (10.1016/j.cageo.2021.104941_b22) 2020; 223 Haber (10.1016/j.cageo.2021.104941_b19) 2001; 17 Nearmap (10.1016/j.cageo.2021.104941_b32) 2019 Vatankhah (10.1016/j.cageo.2021.104941_b43) 2019; 128 Gropp (10.1016/j.cageo.2021.104941_b14) 1996; 22 Codd (10.1016/j.cageo.2021.104941_b7) 2017; 212 Briggs (10.1016/j.cageo.2021.104941_b6) 2000 Renaut (10.1016/j.cageo.2021.104941_b34) 2020; 223 Geological Survey of Western Australia (10.1016/j.cageo.2021.104941_b12) 2019 Lamichhane (10.1016/j.cageo.2021.104941_b25) 2017; 33 Liu (10.1016/j.cageo.2021.104941_b28) 2015; 76 Guenther (10.1016/j.cageo.2021.104941_b17) 2006; 166 Geuzaine (10.1016/j.cageo.2021.104941_b13) 2009; 79 Mayer-Gürr (10.1016/j.cageo.2021.104941_b30) 2021; 155 Xu (10.1016/j.cageo.2021.104941_b49) 2020 Astic (10.1016/j.cageo.2021.104941_b4) 2020; 224 Gross (10.1016/j.cageo.2021.104941_b15) 2019; 217 Čuma (10.1016/j.cageo.2021.104941_b45) 2014; 62 Anon (10.1016/j.cageo.2021.104941_b3) 2021 Martin (10.1016/j.cageo.2021.104941_b29) 2020 Tikhonov (10.1016/j.cageo.2021.104941_b41) 1977 Tian (10.1016/j.cageo.2021.104941_b38) 2018; 15 Ellery (10.1016/j.cageo.2021.104941_b10) 2020 Haber (10.1016/j.cageo.2021.104941_b20) 2000; 16 Tuminaro (10.1016/j.cageo.2021.104941_b42) 2000 Wang (10.1016/j.cageo.2021.104941_b48) 2015; 85 Li (10.1016/j.cageo.2021.104941_b26) 1996; 61 Pallero (10.1016/j.cageo.2021.104941_b33) 2021; 146 Brenner (10.1016/j.cageo.2021.104941_b5) 1994 Jia (10.1016/j.cageo.2021.104941_b24) 2021; 151 Tian (10.1016/j.cageo.2021.104941_b39) 2018; 70 Dagum (10.1016/j.cageo.2021.104941_b9) 1998; 5 Saad (10.1016/j.cageo.2021.104941_b35) 2003 |
| References_xml | – volume: 67 start-page: 95 year: 2015 ident: b46 article-title: A 2015 International Geomagnetic Reference Field (IGRF) candidate model based on Swarm’s experimental absolute magnetometer vector mode data publication-title: Earth Planets Space – volume: 85 start-page: 102 year: 2015 end-page: 111 ident: b48 article-title: A computationally efficient scheme for the inversion of large scale potential field data: Application to synthetic and real data publication-title: Comput. Geosci. – year: 2020 ident: b10 article-title: esys-escript 5.5 – volume: 223 start-page: 1378 year: 2020 end-page: 1397 ident: b34 article-title: A fast methodology for large-scale focusing inversion of gravity and magnetic data using the structured model matrix and the 2-D fast Fourier transform publication-title: Geophys. J. Int. – volume: 76 start-page: 18 year: 2015 end-page: 30 ident: b28 article-title: 2D inverse modeling for potential fields on rugged observation surface using constrained Delaunay triangulation publication-title: Comput. Geosci. – volume: 13 start-page: S59 year: 2016 end-page: S73 ident: b36 article-title: PDE-based geophysical modelling using finite elements: examples from 3D resistivity and 2D magnetotellurics publication-title: J. Geophys. Eng. – year: 2021 ident: b8 article-title: 3D inversion for sparse potential data using first-order system least squares with application to gravity anomalies in Western Queensland – volume: 16 start-page: 1263 year: 2000 end-page: 1280 ident: b20 article-title: On optimization techniques for solving nonlinear inverse problems publication-title: Inverse Problems – year: 2021 ident: b3 article-title: GeoVIEW – volume: 33 year: 2017 ident: b25 article-title: Inversion of geophysical potential field data using the finite element method publication-title: Inverse Problems – year: 2003 ident: b35 article-title: Iterative Methods for Sparse Linear Systems – year: 2017 ident: b47 article-title: Fast inversion of FTG data with an improved PCG algorithm publication-title: 2017 SEG International Exposition and Annual Meeting – volume: 155 year: 2021 ident: b30 article-title: GROOPS: A software toolkit for gravity field recovery and GNSS processing publication-title: Comput. Geosci. – year: 1994 ident: b5 publication-title: the Mathematical Theory of Finite Element Methods – year: 2000 ident: b6 article-title: A Multigrid Tutorial – volume: 11 start-page: 1121 year: 2020 end-page: 1144 ident: b40 article-title: Sequential inversion of GOCE satellite gravity gradient data and terrestrial gravity data for the lithospheric density structure in the North China craton publication-title: Solid Earth – year: 2000 ident: b42 article-title: Parallel smoothed aggregation multigrid: Aggregation strategies on massively parallel machines publication-title: Proceedings of the 2000 ACM/IEEE Conference on Supercomputing – volume: 48 start-page: 294 year: 2017 end-page: 304 ident: b31 article-title: Fast inversion of gravity data using the symmetric successive over-relaxation (SSOR) preconditioned conjugate gradient algorithm publication-title: Explor. Geophys. – volume: 62 start-page: 80 year: 2014 end-page: 87 ident: b45 article-title: Massively parallel regularized 3D inversion of potential fields on CPUs and GPUs publication-title: Comput. Geosci. – year: 1977 ident: b41 article-title: Methods for Solving Ill-Posed Problems – year: 2020 ident: b29 article-title: Three-dimensional gravity anomaly inversion in the Pyrenees using compressional seismic velocity model as structural similarity constraints publication-title: Geophys. J. Int. – volume: 60 start-page: 1186 year: 2012 end-page: 1199 ident: b44 article-title: Large-scale 3D inversion of potential field data publication-title: Geophys. Prospect. – volume: 203 start-page: 1961 year: 2015 end-page: 1976 ident: b1 article-title: Australia’s lithospheric density field, and its isostatic equilibration publication-title: Geophys. J. Int. – volume: 5 start-page: 46 year: 1998 end-page: 55 ident: b9 article-title: OpenMP: An industry-standard API for shared-memory programming publication-title: IEEE Comput. Sci. Eng. – volume: 151 year: 2021 ident: b24 article-title: A stacking methodology of machine learning for 3D geological modeling with geological-geophysical datasets, Laochang Sn camp, Gejiu (China) publication-title: Comput. Geosci. – volume: 22 start-page: 789 year: 1996 end-page: 828 ident: b14 article-title: A high-performance, portable implementation of the MPI message passing interface standard publication-title: Parallel Comput. – volume: 223 start-page: 1899 year: 2020 end-page: 1918 ident: b22 article-title: A Bayesian 3-D linear gravity inversion for complex density distributions: application to the Puysegur subduction system publication-title: Geophys. J. Int. – year: 2020 ident: b49 article-title: Focusing joint inversion of gravity and magnetic data using a clustering stabilizer in a space of weighted parameters publication-title: Geophys. J. Int. – volume: 146 year: 2021 ident: b33 article-title: GravPSO2D: A Matlab package for 2D gravity inversion in sedimentary basins using the Particle Swarm Optimization algorithm publication-title: Comput. Geosci. – volume: 224 start-page: 40 year: 2020 end-page: 68 ident: b4 article-title: Petrophysically and geologically guided multi-physics inversion using a dynamic Gaussian mixture model publication-title: Geophys. J. Int. – year: 2019 ident: b12 – volume: 166 start-page: 506 year: 2006 end-page: 517 ident: b17 article-title: Three-dimensional modelling and inversion of dc resistivity data incorporating topography — II. Inversion publication-title: Geophys. J. Int. – year: 2019 ident: b32 article-title: Nearmap Australia pty ltd – volume: 31 start-page: 397 year: 2005 end-page: 423 ident: b21 article-title: An overview of the Trilinos project publication-title: ACM Trans. Math. Software – volume: 70 start-page: 1 year: 2018 end-page: 22 ident: b39 article-title: Inversion of the density structure of the lithosphere in the North China Craton from GOCE satellite gravity gradient data publication-title: Earth Planets Space – volume: 79 start-page: 1309 year: 2009 end-page: 1331 ident: b13 article-title: Gmsh: a three-dimensional finite element mesh generator with built-in pre- and post-processing facilities publication-title: Internat. J. Numer. Methods Engrg. – volume: 15 start-page: 354 year: 2018 end-page: 365 ident: b38 article-title: DenInv3D: a geophysical software for three-dimensional density inversion of gravity field data publication-title: J. Geophys. Eng. – volume: 128 start-page: 19 year: 2019 end-page: 29 ident: b43 article-title: IGUG: A MATLAB package for 3D inversion of gravity data using graph theory publication-title: Comput. Geosci. – volume: 27 start-page: 64 year: 2008 end-page: 69 ident: b11 article-title: Geologically constrained gravity inversion for the Voisey’s Bay ovoid deposit publication-title: Lead. Edge – volume: 84 start-page: 61 year: 2015 end-page: 71 ident: b16 article-title: Inversion of potential field data using the finite element method on parallel computers publication-title: Comput. Geosci. – volume: 61 start-page: 394 year: 1996 end-page: 408 ident: b26 article-title: 3-D inversion of magnetic data publication-title: Geophysics – volume: 149 year: 2021 ident: b18 article-title: 3D geological structure inversion from Noddy-generated magnetic data using deep learning methods publication-title: Comput. Geosci. – volume: 217 start-page: 2035 year: 2019 end-page: 2046 ident: b15 article-title: Weighted cross-gradient function for joint inversion with the application to regional 3-D gravity and magnetic anomalies publication-title: Geophys. J. Int. – volume: 212 start-page: 2073 year: 2017 end-page: 2087 ident: b7 article-title: Electrical Resistivity Tomography using a finite element based bfgs algorithm with algebraic multigrid preconditioning publication-title: Geophys. J. Int. – volume: 63 start-page: 109 year: 1998 end-page: —119 ident: b27 article-title: 3D inversion of gravity data publication-title: Geophysics – volume: 215 start-page: 1241 year: 2018 end-page: 1256 ident: b23 article-title: 3-D density structure of the Ross Sea basins, West Antarctica from constrained gravity inversion and their tectonic implications publication-title: Geophys. J. Int. – volume: 17 start-page: 1847 year: 2001 end-page: 1864 ident: b19 article-title: Preconditioned all-at-once methods for large, sparse parameter estimation problems publication-title: Inverse Problems – volume: 125 year: 2020 ident: b2 article-title: A magnetic data correction workflow for sparse, four-dimensional data publication-title: J. Geophys. Res. Solid Earth – volume: 128 start-page: 281 year: 2001 end-page: 309 ident: b37 article-title: A review of algebraic multigrid publication-title: J. Comput. Appl. Math. – year: 2020 ident: 10.1016/j.cageo.2021.104941_b29 article-title: Three-dimensional gravity anomaly inversion in the Pyrenees using compressional seismic velocity model as structural similarity constraints publication-title: Geophys. J. Int. – year: 2020 ident: 10.1016/j.cageo.2021.104941_b10 – volume: 166 start-page: 506 issue: 2 year: 2006 ident: 10.1016/j.cageo.2021.104941_b17 article-title: Three-dimensional modelling and inversion of dc resistivity data incorporating topography — II. Inversion publication-title: Geophys. J. Int. doi: 10.1111/j.1365-246X.2006.03011.x – volume: 84 start-page: 61 year: 2015 ident: 10.1016/j.cageo.2021.104941_b16 article-title: Inversion of potential field data using the finite element method on parallel computers publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2015.08.011 – volume: 5 start-page: 46 issue: 1 year: 1998 ident: 10.1016/j.cageo.2021.104941_b9 article-title: OpenMP: An industry-standard API for shared-memory programming publication-title: IEEE Comput. Sci. Eng. doi: 10.1109/99.660313 – volume: 33 issue: 12 year: 2017 ident: 10.1016/j.cageo.2021.104941_b25 article-title: Inversion of geophysical potential field data using the finite element method publication-title: Inverse Problems doi: 10.1088/1361-6420/aa8cb0 – volume: 155 year: 2021 ident: 10.1016/j.cageo.2021.104941_b30 article-title: GROOPS: A software toolkit for gravity field recovery and GNSS processing publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2021.104864 – volume: 212 start-page: 2073 issue: 3 year: 2017 ident: 10.1016/j.cageo.2021.104941_b7 article-title: Electrical Resistivity Tomography using a finite element based bfgs algorithm with algebraic multigrid preconditioning publication-title: Geophys. J. Int. doi: 10.1093/gji/ggx511 – volume: 22 start-page: 789 issue: 6 year: 1996 ident: 10.1016/j.cageo.2021.104941_b14 article-title: A high-performance, portable implementation of the MPI message passing interface standard publication-title: Parallel Comput. doi: 10.1016/0167-8191(96)00024-5 – year: 2000 ident: 10.1016/j.cageo.2021.104941_b6 – year: 2021 ident: 10.1016/j.cageo.2021.104941_b3 – volume: 62 start-page: 80 issue: C year: 2014 ident: 10.1016/j.cageo.2021.104941_b45 article-title: Massively parallel regularized 3D inversion of potential fields on CPUs and GPUs publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2013.10.004 – volume: 128 start-page: 19 year: 2019 ident: 10.1016/j.cageo.2021.104941_b43 article-title: IGUG: A MATLAB package for 3D inversion of gravity data using graph theory publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2019.03.008 – year: 2021 ident: 10.1016/j.cageo.2021.104941_b8 – volume: 125 issue: 10 year: 2020 ident: 10.1016/j.cageo.2021.104941_b2 article-title: A magnetic data correction workflow for sparse, four-dimensional data publication-title: J. Geophys. Res. Solid Earth doi: 10.1029/2020JB019825 – year: 2000 ident: 10.1016/j.cageo.2021.104941_b42 article-title: Parallel smoothed aggregation multigrid: Aggregation strategies on massively parallel machines – volume: 76 start-page: 18 issue: C year: 2015 ident: 10.1016/j.cageo.2021.104941_b28 article-title: 2D inverse modeling for potential fields on rugged observation surface using constrained Delaunay triangulation publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2014.11.010 – year: 2019 ident: 10.1016/j.cageo.2021.104941_b12 – volume: 217 start-page: 2035 issue: 3 year: 2019 ident: 10.1016/j.cageo.2021.104941_b15 article-title: Weighted cross-gradient function for joint inversion with the application to regional 3-D gravity and magnetic anomalies publication-title: Geophys. J. Int. doi: 10.1093/gji/ggz134 – volume: 79 start-page: 1309 issue: 11 year: 2009 ident: 10.1016/j.cageo.2021.104941_b13 article-title: Gmsh: a three-dimensional finite element mesh generator with built-in pre- and post-processing facilities publication-title: Internat. J. Numer. Methods Engrg. doi: 10.1002/nme.2579 – year: 1994 ident: 10.1016/j.cageo.2021.104941_b5 – year: 2003 ident: 10.1016/j.cageo.2021.104941_b35 – year: 1977 ident: 10.1016/j.cageo.2021.104941_b41 – volume: 85 start-page: 102 year: 2015 ident: 10.1016/j.cageo.2021.104941_b48 article-title: A computationally efficient scheme for the inversion of large scale potential field data: Application to synthetic and real data publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2015.09.005 – volume: 128 start-page: 281 issue: 1–2 year: 2001 ident: 10.1016/j.cageo.2021.104941_b37 article-title: A review of algebraic multigrid publication-title: J. Comput. Appl. Math. doi: 10.1016/S0377-0427(00)00516-1 – volume: 149 year: 2021 ident: 10.1016/j.cageo.2021.104941_b18 article-title: 3D geological structure inversion from Noddy-generated magnetic data using deep learning methods publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2021.104701 – volume: 70 start-page: 1 issue: 1 year: 2018 ident: 10.1016/j.cageo.2021.104941_b39 article-title: Inversion of the density structure of the lithosphere in the North China Craton from GOCE satellite gravity gradient data publication-title: Earth Planets Space doi: 10.1186/s40623-018-0942-1 – volume: 67 start-page: 95 issue: 1 year: 2015 ident: 10.1016/j.cageo.2021.104941_b46 article-title: A 2015 International Geomagnetic Reference Field (IGRF) candidate model based on Swarm’s experimental absolute magnetometer vector mode data publication-title: Earth Planets Space doi: 10.1186/s40623-015-0265-4 – volume: 146 year: 2021 ident: 10.1016/j.cageo.2021.104941_b33 article-title: GravPSO2D: A Matlab package for 2D gravity inversion in sedimentary basins using the Particle Swarm Optimization algorithm publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2020.104653 – volume: 63 start-page: 109 year: 1998 ident: 10.1016/j.cageo.2021.104941_b27 article-title: 3D inversion of gravity data publication-title: Geophysics doi: 10.1190/1.1444302 – year: 2017 ident: 10.1016/j.cageo.2021.104941_b47 article-title: Fast inversion of FTG data with an improved PCG algorithm – volume: 17 start-page: 1847 issue: 6 year: 2001 ident: 10.1016/j.cageo.2021.104941_b19 article-title: Preconditioned all-at-once methods for large, sparse parameter estimation problems publication-title: Inverse Problems doi: 10.1088/0266-5611/17/6/319 – volume: 223 start-page: 1378 issue: 2 year: 2020 ident: 10.1016/j.cageo.2021.104941_b34 article-title: A fast methodology for large-scale focusing inversion of gravity and magnetic data using the structured model matrix and the 2-D fast Fourier transform publication-title: Geophys. J. Int. doi: 10.1093/gji/ggaa372 – year: 2019 ident: 10.1016/j.cageo.2021.104941_b32 – volume: 223 start-page: 1899 issue: 3 year: 2020 ident: 10.1016/j.cageo.2021.104941_b22 article-title: A Bayesian 3-D linear gravity inversion for complex density distributions: application to the Puysegur subduction system publication-title: Geophys. J. Int. doi: 10.1093/gji/ggaa425 – volume: 15 start-page: 354 issue: 2 year: 2018 ident: 10.1016/j.cageo.2021.104941_b38 article-title: DenInv3D: a geophysical software for three-dimensional density inversion of gravity field data publication-title: J. Geophys. Eng. doi: 10.1088/1742-2140/aa8caf – volume: 151 year: 2021 ident: 10.1016/j.cageo.2021.104941_b24 article-title: A stacking methodology of machine learning for 3D geological modeling with geological-geophysical datasets, Laochang Sn camp, Gejiu (China) publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2021.104754 – volume: 31 start-page: 397 issue: 3 year: 2005 ident: 10.1016/j.cageo.2021.104941_b21 article-title: An overview of the Trilinos project publication-title: ACM Trans. Math. Software doi: 10.1145/1089014.1089021 – volume: 27 start-page: 64 issue: 1 year: 2008 ident: 10.1016/j.cageo.2021.104941_b11 article-title: Geologically constrained gravity inversion for the Voisey’s Bay ovoid deposit publication-title: Lead. Edge doi: 10.1190/1.2831681 – volume: 13 start-page: S59 issue: 2 year: 2016 ident: 10.1016/j.cageo.2021.104941_b36 article-title: PDE-based geophysical modelling using finite elements: examples from 3D resistivity and 2D magnetotellurics publication-title: J. Geophys. Eng. doi: 10.1088/1742-2132/13/2/S59 – volume: 224 start-page: 40 issue: 1 year: 2020 ident: 10.1016/j.cageo.2021.104941_b4 article-title: Petrophysically and geologically guided multi-physics inversion using a dynamic Gaussian mixture model publication-title: Geophys. J. Int. doi: 10.1093/gji/ggaa378 – year: 2020 ident: 10.1016/j.cageo.2021.104941_b49 article-title: Focusing joint inversion of gravity and magnetic data using a clustering stabilizer in a space of weighted parameters publication-title: Geophys. J. Int. doi: 10.1093/gji/ggaa518 – volume: 11 start-page: 1121 issue: 3 year: 2020 ident: 10.1016/j.cageo.2021.104941_b40 article-title: Sequential inversion of GOCE satellite gravity gradient data and terrestrial gravity data for the lithospheric density structure in the North China craton publication-title: Solid Earth doi: 10.5194/se-11-1121-2020 – volume: 203 start-page: 1961 issue: 3 year: 2015 ident: 10.1016/j.cageo.2021.104941_b1 article-title: Australia’s lithospheric density field, and its isostatic equilibration publication-title: Geophys. J. Int. doi: 10.1093/gji/ggv396 – volume: 16 start-page: 1263 issue: 5 year: 2000 ident: 10.1016/j.cageo.2021.104941_b20 article-title: On optimization techniques for solving nonlinear inverse problems publication-title: Inverse Problems doi: 10.1088/0266-5611/16/5/309 – volume: 60 start-page: 1186 issue: 6 year: 2012 ident: 10.1016/j.cageo.2021.104941_b44 article-title: Large-scale 3D inversion of potential field data publication-title: Geophys. Prospect. doi: 10.1111/j.1365-2478.2011.01052.x – volume: 61 start-page: 394 issue: 2 year: 1996 ident: 10.1016/j.cageo.2021.104941_b26 article-title: 3-D inversion of magnetic data publication-title: Geophysics doi: 10.1190/1.1443968 – volume: 215 start-page: 1241 issue: 2 year: 2018 ident: 10.1016/j.cageo.2021.104941_b23 article-title: 3-D density structure of the Ross Sea basins, West Antarctica from constrained gravity inversion and their tectonic implications publication-title: Geophys. J. Int. doi: 10.1093/gji/ggy343 – volume: 48 start-page: 294 issue: 3 year: 2017 ident: 10.1016/j.cageo.2021.104941_b31 article-title: Fast inversion of gravity data using the symmetric successive over-relaxation (SSOR) preconditioned conjugate gradient algorithm publication-title: Explor. Geophys. doi: 10.1071/EG15041 |
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| SubjectTerms | algorithms data collection finite element analysis Finite element method gravity Gravity anomaly inversion Magnetic anomaly inversion magnetism Multi-grid Parallel computing topography Western Australia |
| Title | Fast multi-resolution 3D inversion of potential fields with application to high-resolution gravity and magnetic anomaly data from the Eastern Goldfields in Western Australia |
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