Black hole algorithm for determining model parameter in self-potential data

作     者：Sungkono Warnana, Dwa Desa 

作者机构：Inst Teknol Sepuluh Nopember Dept Phys Kampus ITS Sukolilo Surabaya 60111 Indonesia Inst Teknol Sepuluh Nopember Dept Geophys Engn Kampus ITS Sukolilo Surabaya 60111 Indonesia 

出 版 物：《JOURNAL OF APPLIED GEOPHYSICS》 (应用地球物理学杂志)

年 卷 期：2018年第148卷

页      面：189-200页

核心收录：

学科分类：0819[工学-矿业工程] 07[理学] 0708[理学-地球物理学] 

基　　金：Institute for Research and Community Services of Institut Teknologi Sepuluh Nopember  Surabaya [876/PKS/ITS/2017] 

主　　题：Black hole algorithm Estimation model Model uncertainty Self-potential data 

摘      要：Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion. (C) 2017 Elsevier B.V. All rights reserved.