Estimating depths and dimensions of gravity sources through optimized support vector classifier (SVC)

Annals of Geophysics

Vahid Ebrahimzadeh Ardestani¹  Mohammad Ali Riahi²  Ayyub Memar Koucheh Bagh²  Mohammad Ehsan Hekmatian³ 

[1] Nuclear Fuel Cycle Research School, Nuclear Science and Technology Research Institute (NSTRI), Tehran,;Institute of Geophysics, University of Tehran, Tehran,;Islamic Azad University, Faculty of Basic Sciences, Science and Research Branch, Tehran, Iran;

关键词: Gravity sources depths and dimensions;    Gravity profile;    SVC;    Feature;    FS;   

DOI  :  10.4401/ag-7029

来源: DOAJ

【 摘 要 】

By researching and applying new methods we will be able to improve significantly estimation of shapes, dimensions and depths of gravity sources. After shapes estimation of gravity sources through support vector classifier (SVC) in our last research [Hekmatian et al. 2015], in this paper SVC is applied for estimating depths and dimensions of gravity sources. These estimations give us logical and complete initial guesses regarding shapes, depths and dimensions of gravity sources which are needed in more precise interpretations and inversions of gravity sources. Also for better application of SVC, we selected more proper features using the technique called feature selection (FS). In this paper, we trained SVC with 320 synthetic gravity profiles for estimation of dimensions and depths of gravity sources. We tested the trained SVC codes by about 200 other synthetic and some real gravity profiles. The depths and dimensions of a well along with two ore bodies (three real gravity sources) are estimated during the testing process.

【 授权许可】

Unknown