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• W4317754410 endingPage "105297" @default.
• W4317754410 startingPage "105297" @default.
• W4317754410 abstract "A fully numerical forward model for estimating gravity anomalies in the Fourier domain is presented for irregular topographic mass distributions. Modified Parker’s formula using the Gauss-FFT method is utilized for getting better accuracy than the standard FFT algorithm. Existing frequency domain forward modeling for topographic surfaces uses common analytically derivable density functions for evaluating gravity anomalies. But in the real scenario, subsurface mass distributions can take any functional form of depth. Our presented algorithm provides a generalized approach for evaluating forward gravity anomalies due to any horizontal and vertical variation of density distributions. The computational cost depends on the irregularities of the topographic surfaces and the complexity of the functional form of density distributions. The presented algorithm is compared with analytical solutions and space domain prismatic model approximation. A complex, analytically non-integrable density distribution was also considered and compared with the space domain model. The presented algorithm accurately estimates gravity anomalies in all cases, and the results are close to the space domain prismatic model. Finally, an observed gravity anomaly of the real sedimentary basin and its corresponding inverted basement depth for parabolic density variation is considered to evaluate forward anomalies using our presented algorithm. The estimated gravity anomalies provide close approximations to observed gravity anomalies, revealing the proposed algorithm’s reliability for any 3D topographic forward modeling." @default.
• W4317754410 created "2023-01-23" @default.
• W4317754410 creator A5058445854 @default.
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• W4317754410 date "2023-03-01" @default.
• W4317754410 modified "2023-10-18" @default.
• W4317754410 title "Generalized Gauss-FFT 3D forward gravity modeling for irregular topographic mass having any 3D variable density contrast" @default.
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• W4317754410 doi "https://doi.org/10.1016/j.cageo.2023.105297" @default.
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