Depth, horizontal length and starting point (𝑋0) parameters of the inclined sheet model were obtained within low error limits compared with the iteration methods for model and real field data.
📌 3 Key Takeaways
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Objective & Hypothesis:Usage of the least squares and inversion methods are commonly applied to the geophysical data analysis.
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Key Findings & Data:Solution of the theoretical anomalies of inclined sheet like bodies for the self-potential method were compared by writing a Fortran based computer program which is using simple iterative methods with damped least squares (Marquardt-Levenberg) algorithm.
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Conclusion & Impact:Depth, horizontal length and starting point (𝑋0) parameters of the inclined sheet model were obtained within low error limits compared with the iteration methods for model and real field data.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Self-Potential · Inclined sheet model · Least Squares
Abstract
Usage of the least squares and inversion methods are commonly applied to the geophysical data analysis. Solution of the theoretical anomalies of inclined sheet like bodies for the self-potential method were compared by writing a Fortran based computer program which is using simple iterative methods with damped least squares (Marquardt-Levenberg) algorithm. As a result of theoretical model studies, model parameters have been reached with very little number of iterations at the small error limits. Applied Marquardt-Levenberg method damping factor has been carried out automatically in the program depending on converging and non-converging conditions. Depth, horizontal length and starting point (𝑋0) parameters of the inclined sheet model were obtained within low error limits compared with the iteration methods for model and real field data.
SARI, C., TİMUR, E. (2020). Evaluation of SP anomalies caused by two dimensional sheet like structures with different inversion techniques. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, Cilt: 26 - Sayı: 6, 1164–1169. https://ajindex.com/articles/100579
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