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Published on: November 7, 2017
Characterizing Subsurface Environments Using Borehole Magnetic Gradiometry
Mohammad Forman Asgharzadeh1,2, Hasan Ghasemzadeh2, Ralph von Frese1
1School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA.
This study introduces a new method for calculating magnetic field gradients from cylindrical bodies, enhancing subsurface exploration. The research also proposes a novel borehole instrument for detecting magnetic source directions.
Area of Science:
- Geophysics
- Computational electromagnetics
Background:
- Magnetic anomaly inversion relies on forward modeling to estimate subsurface magnetization.
- Accurate modeling of magnetic field components is crucial for geophysical interpretation.
Purpose of the Study:
- To develop and validate a numerical method for calculating magnetic potential, anomaly, and gradient components of cylindrical prisms.
- To quantify magnetic gradient components for cylindrical bodies, enabling new interpretation applications.
- To propose a conceptual design for a borehole instrument measuring magnetic gradient effects.
Main Methods:
- Numerical least-squares Gauss-Legendre quadrature (GLQ) integration was employed.
- The method was used to evaluate magnetic potential, anomaly, and gradient components of a cylindrical prism.
- Computational performance was compared to existing methods for full cylinder analysis.
Main Results:
- The study quantifies magnetic gradient components for cylindrical bodies for the first time.
- The GLQ integration method demonstrates comparable or improved computational accuracy and speed.
- A conceptual design for a borehole magnetic gradient instrument is presented.
Conclusions:
- The developed GLQ method offers an accurate and efficient approach for modeling magnetic effects of cylindrical sources.
- The proposed borehole instrument can determine azimuthal directions of magnetic sources, improving borehole geophysics.
- This work advances the interpretation of cylindrical geological structures and borehole magnetic data.
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