A Comprehensive Study of Local, Global, and Combined Optimization Methods on Synthetic Seismic Refraction and Direct Current Resistivity Data

Paul Edigbue, Ismail Demirci, Irfan Akca, Hamdan Ali Hamdan, Panagiotis Kirmizakis, Pantelis Soupios*, Emin Candansayar, Sherif Hanafy, Abdullatif Al-Shuhail

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Most geophysical inversions face the problem of non-uniqueness, which poses a challenge in the mapping and delineation of the subsurface anomalies. To tackle this challenge, a combined local and global optimization approach is considered for jointly inverting two-dimensional direct current resistivity (DCR) and seismic refraction (SR) data that aim to estimate the corresponding physical model parameters. In this combined approach, the output of the local optimization method is used to determine the search space and tuning parameters for the global optimization algorithm. The multi-objective genetic algorithm (non-dominated sorting genetic algorithm) was utilized to jointly optimize the objective functions of two different methods. Because the genetic algorithm is a population-based optimization method, it requires numerous forward calculations. To deal with the expected high computational cost associated with this approach, parallel computing was utilized for the forward function evaluations to reduce the run time of the entire process. The proposed approach was tested using synthetic two-dimensional resistivity and velocity models that had three different types of anomalies (dyke, positive, and combined positive and negative). The results showed an improvement in the anomaly delineation in the output of the combined local and global optimization method compared with the local optimization method. Additionally, similar synthetic models were tested using only the single objective global optimization algorithm (conventional global optimization), which showed promising anomaly delineation.

Original languageEnglish
Article number11589
JournalApplied Sciences (Switzerland)
Issue number22
StatePublished - Nov 2022

Bibliographical note

Funding Information:
This research was funded by the start-up grant SF18060 from the College of Petroleum Engineering and Geosciences (CPG) at King Fahd University of Petroleum and Minerals (KFUPM).

Publisher Copyright:
© 2022 by the authors.


  • combined local and global optimization
  • direct current resistivity
  • individual inversion
  • joint inversion
  • seismic refraction

ASJC Scopus subject areas

  • Materials Science (all)
  • Instrumentation
  • Engineering (all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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