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.

Original languageEnglish
Pages (from-to)189-200
Number of pages12
JournalJournal of Applied Geophysics
Publication statusPublished - Jan 2018


  • Black hole algorithm
  • Estimation model
  • Model uncertainty
  • Self-potential data


Dive into the research topics of 'Black hole algorithm for determining model parameter in self-potential data'. Together they form a unique fingerprint.

Cite this