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Fast 3-D large-scale gravity and magnetic modeling using unstructured grids and an adaptive multilevel fast multipole method
Cent S Univ, Key Lab Metallogen Predict Nonferrous Met & Geol, Minist Educ, Changsha, Hunan, Peoples R China.;Key Lab Nonferrous Resources & Geol Hazard Detect, Changsha, Hunan, Peoples R China.;Cent S Univ, Sch Geosci & Infophys, Changsha, Hunan, Peoples R China..
Cent S Univ, Key Lab Metallogen Predict Nonferrous Met & Geol, Minist Educ, Changsha, Hunan, Peoples R China.;Key Lab Nonferrous Resources & Geol Hazard Detect, Changsha, Hunan, Peoples R China.;Cent S Univ, Sch Geosci & Infophys, Changsha, Hunan, Peoples R China..
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.
Swiss Fed Inst Technol, Inst Geophys, Dept Earth Sci, Zurich, Switzerland..
2017 (English)In: Journal of Geophysical Research - Solid Earth, ISSN 2169-9313, E-ISSN 2169-9356, Vol. 122, no 1, 79-109 p.Article in journal (Refereed) Published
Abstract [en]

A novel fast and accurate algorithm is developed for large-scale 3-D gravity and magnetic modeling problems. An unstructured grid discretization is used to approximate sources with arbitrary mass and magnetization distributions. A novel adaptive multilevel fast multipole (AMFM) method is developed to reduce the modeling time. An observation octree is constructed on a set of arbitrarily distributed observation sites, while a source octree is constructed on a source tetrahedral grid. A novel characteristic is the independence between the observation octree and the source octree, which simplifies the implementation of different survey configurations such as airborne and ground surveys. Two synthetic models, a cubic model and a half-space model with mountain-valley topography, are tested. As compared to analytical solutions of gravity and magnetic signals, excellent agreements of the solutions verify the accuracy of our AMFM algorithm. Finally, our AMFM method is used to calculate the terrain effect on an airborne gravity data set for a realistic topography model represented by a triangular surface retrieved from a digital elevation model. Using 16 threads, more than 5800 billion interactions between 1,002,001 observation points and 5,839,830 tetrahedral elements are computed in 453.6s. A traditional first-order Gaussian quadrature approach requires 3.77days. Hence, our new AMFM algorithm not only can quickly compute the gravity and magnetic signals for complicated problems but also can substantially accelerate the solution of 3-D inversion problems.

Place, publisher, year, edition, pages
American Geophysical Union (AGU), 2017. Vol. 122, no 1, 79-109 p.
National Category
Geochemistry Geophysics
Identifiers
URN: urn:nbn:se:uu:diva-319326DOI: 10.1002/2016JB012987ISI: 000395658900005OAI: oai:DiVA.org:uu-319326DiVA: diva2:1086686
Available from: 2017-04-03 Created: 2017-04-03 Last updated: 2017-04-03Bibliographically approved

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