Computation of geophysical magnetic data for a buried 3‐D hexahedral prism using the Gauss–Legendre quadrature method

2020 ◽  
Vol 18 (5) ◽  
pp. 575-588 ◽  
Author(s):  
Hassan Mohamed ◽  
Hideki Mizunaga ◽  
Hakim Saibi
Keyword(s):  
Magnetic Data ◽  
Quadrature Method ◽  
Legendre Quadrature

scholarly journals Implementation of Two-point Quadrature Gauss-Legendre Method on 2D Gravity Anomaly Modeling in Basins with Density Distribution Varied Polynomially as a Function of Depth

2018 ◽  
Vol 16 (2) ◽  
pp. 11
Author(s):  
Wahyu Srigutomo ◽  
Sesri Santurima ◽  
Cahyo Aji Hapsoro ◽  
Hairil Anwar ◽  
I Gede Putu Fadjar Soerya Djaja
Keyword(s):  
Density Distribution ◽  
Gravity Anomaly ◽  
Surface Topography ◽  
2D Gravity ◽  
Gravity Anomalies ◽  
Density Contrast ◽  
Quadrature Method ◽  
Gravity Method ◽  
Basin Geometry ◽  
Legendre Quadrature

Study of basin geometry basin is important in geosciences and geophysical exploration. Gravity method can be used to address this issue by measuring gravity anomalies on the surface caused by density contrast between the bedrock and the sediment that fills the basin, geometry of the basin and surface topography. Numerically, gravity anomaly modeling can be conducted using two-point rule Gauss-Legendre Quadrature method, for a case where density contrast varies with depth exponentially. Within the scope of this study, gravity anomalies on the surface are significantly affected by the geometry of the curvature of the bedrock as well as the topographic elevation of the surface and the selected density contrast, and are not significantly affected by the undulation of the bedrock curvature.  

An Augmented Iteratively Re-weighted and Refined Least Squares Method for lp Minimization Problem in Inverse Modeling of Potential Field Magnetic Data

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Maysam Abedi
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
Least Squares ◽  
Minimization Problem ◽  
Potential Field ◽  
Field Data ◽  
Least Squares Method ◽  
Porphyry Copper ◽  
Magnetic Data ◽  
Magnetic Field Data

The presented work examines application of an Augmented Iteratively Re-weighted and Refined Least Squares method (AIRRLS) to construct a 3D magnetic susceptibility property from potential field magnetic anomalies. This algorithm replaces an lp minimization problem by a sequence of weighted linear systems in which the retrieved magnetic susceptibility model is successively converged to an optimum solution, while the regularization parameter is the stopping iteration numbers. To avoid the natural tendency of causative magnetic sources to concentrate at shallow depth, a prior depth weighting function is incorporated in the original formulation of the objective function. The speed of lp minimization problem is increased by inserting a pre-conditioner conjugate gradient method (PCCG) to solve the central system of equation in cases of large scale magnetic field data. It is assumed that there is no remanent magnetization since this study focuses on inversion of a geological structure with low magnetic susceptibility property. The method is applied on a multi-source noise-corrupted synthetic magnetic field data to demonstrate its suitability for 3D inversion, and then is applied to a real data pertaining to a geologically plausible porphyry copper unit.  The real case study located in  Semnan province of  Iran  consists  of  an arc-shaped  porphyry  andesite  covered  by  sedimentary  units  which  may  have  potential  of  mineral  occurrences, especially  porphyry copper. It is demonstrated that such structure extends down at depth, and consequently exploratory drilling is highly recommended for acquiring more pieces of information about its potential for ore-bearing mineralization.

High-Resolution Seismic-Reflection and Marine Magnetic Data Along the Hosgri Fault Zone, Central California

2009 ◽  
Author(s):  
Ray W. Sliter ◽  
Peter J. Triezenberg ◽  
Patrick E. Hart ◽  
Janet T. Watt ◽  
Samuel Y. Johnson ◽  
...  
Keyword(s):  
High Resolution ◽  
Fault Zone ◽  
Seismic Reflection ◽  
Magnetic Data ◽  
Central California
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