INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS

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KARIMI A.; MORADZADEH A.; KamkarRoohani A.; Allamehzadeh m.

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Seminar Paper

Paper Information

Seminar: IRANIAN GEOPHYSICS CONFERENCE
Year:2006 | Issue:12

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Title

INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS

Author(s)

KARIMI A. | MORADZADEH A. | KamkarRoohani A. | Allamehzadeh m.

Keywords

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Abstract

INVERSE MODELING OF GEOELECTRICAL DATA IS AN IMPORTANT METHOD EXPLORATION AND UNDERGROUND WATER STUDIES. INTRINSIC NONLINEAR NATURE OF GEOPHYSICAL DATA IS OBSTACLE IN MODELING PROCEDURE. HERE WE DESCRIBE A STUDY OF THE APPLICABILITY OF NEURAL NETWORKS TO SOLVING SOME GEOPHYSICAL INVERSE PROBLEMS. IN PARTICULAR, WE STUDY THE PROBLEM OF OBTAINING FORMATION RESISTIVITIES AND LAYER THICKNESSES FROM VERTICAL ELECTRICAL SOUNDING (VES) DATA.

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APA: Copy

KARIMI, A., MORADZADEH, A., KamkarRoohani, A., & Allamehzadeh, m.. (2006). INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS. IRANIAN GEOPHYSICS CONFERENCE. SID. https://sid.ir/paper/905504/en

Vancouver: Copy

KARIMI A., MORADZADEH A., KamkarRoohani A., Allamehzadeh m.. INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS. 2006. Available from: https://sid.ir/paper/905504/en

IEEE: Copy

A. KARIMI, A. MORADZADEH, A. KamkarRoohani, and m. Allamehzadeh, “INVERSE MODELING OF RESISTIVITY SOUNDING DATA USING ARTIFICIAL NEURAL NETWORKS,” presented at the IRANIAN GEOPHYSICS CONFERENCE. 2006, [Online]. Available: https://sid.ir/paper/905504/en

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