2.5D geoelectric inversion method using series expansion
Anikó Gyulai, É. Tolnai
Abstract
Anikó Gyulai, É. Tolnai
Abstract
This paper presents the principles of a new inversion method used for the determination of 3D geological structures. The horizontal variations of the layer parameters i.e. layer thicknesses and resistivities are discretized in the form of series expansion. The unknown coefficients of the series expansion are determined by an iterative linearized inversion method using weights specified by the Most Frequent Value Method (MFV). The result of the inversion is estimated from the data of the bi-directional VES (Vertical Electric Sounding) measurements with Schlumberger array in each profile and in multiple profiles. A 3D Finite Difference method was applied to forward modelling, however, the structure is approximated along the profile with a 2D model discretized by single-variable series expansion. The 3D forward modeling procedure gives the opportunity to calculate data measured in two or multiple directions. The suggested interpretation method gives an approximate solution. Proceeding more accurate 3D inversion will be provided by the binary series expansion.
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This paper presents the principles of a new inversion method used for the determination of 3D geological structures. The horizontal variations of the layer parameters i.e. layer thicknesses and resistivities are discretized in the form of series expansion. The unknown coefficients of the series expansion are determined by an iterative linearized inversion method using weights specified by the Most Frequent Value Method (MFV). The result of the inversion is estimated from the data of the bi-directional VES (Vertical Electric Sounding) measurements with Schlumberger array in each profile and in multiple profiles. A 3D Finite Difference method was applied to forward modelling, however, the structure is approximated along the profile with a 2D model discretized by single-variable series expansion. The 3D forward modeling procedure gives the opportunity to calculate data measured in two or multiple directions. The suggested interpretation method gives an approximate solution. Proceeding more accurate 3D inversion will be provided by the binary series expansion.
Key concepts: Inversion (geology), Discretization, Depth sounding, Series (stratigraphy), Geology, Binary number, Inverse transform sampling, Mathematical analysis