Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Porosity Prediction from Gravity Inversion with Constraints from Resistivity Data

Version 1 : Received: 26 May 2021 / Approved: 27 May 2021 / Online: 27 May 2021 (13:16:28 CEST)

How to cite: Santos, F.A.M.; Represas, P. Porosity Prediction from Gravity Inversion with Constraints from Resistivity Data. Preprints 2021, 2021050669 (doi: 10.20944/preprints202105.0669.v1). Santos, F.A.M.; Represas, P. Porosity Prediction from Gravity Inversion with Constraints from Resistivity Data. Preprints 2021, 2021050669 (doi: 10.20944/preprints202105.0669.v1).

Abstract

This work describes a method to carry out 2-D inversion of gravity data in terms of porosity and matrix density distribution using previous DC resistivity inversion results to constraint the fractional pore-water content in the rocks. The inversion is carried out using a controlled random search (CRS) algorithm for global optimization. The method was tested on synthetic data generated from a model representing a graben, and the results show that it can estimate accurate values of contrast-density and porosity. The method was also applied to gravity and dc experimental data collected in NE Portugal, showing results that agree quite well with the known geological information.

Subject Areas

porosity prediction; pore-water prediction; gravity; resistivity; combined inversion

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