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Magnetic anomaly inversion through the novel barnacles mating optimization algorithm.

Hanbing Ai1, Khalid S Essa2, Yunus Levent Ekinci3

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This summary is machine-generated.

The Barnacles Mating Optimizer (BMO) effectively interprets magnetic anomalies by exploring more of the model space. This global optimization method offers a robust alternative to standard algorithms for geophysical inverse problems.

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Area of Science:

  • Geophysics
  • Inverse Problems
  • Optimization Algorithms

Background:

  • Geophysical inverse problems are often ill-posed and non-unique, requiring regularization and prior information when using local optimizers.
  • Local search algorithms are sensitive to initial model selection, while global optimization methods offer broader exploration without this constraint.
  • Global optimization and metaheuristic algorithms are increasingly adopted in geophysics for parameter estimation.

Purpose of the Study:

  • To introduce and apply the Barnacles Mating Optimizer (BMO), a novel global optimizer, to the geophysical inverse problem of magnetic anomaly interpretation.
  • To evaluate BMO's performance against a standard algorithm (sPSO) in terms of convergence, stability, robustness, and accuracy.
  • To assess the effectiveness of a second moving average (SMA) scheme for regional anomaly removal and to perform post-inversion uncertainty analysis.

Main Methods:

  • Application of the Barnacles Mating Optimizer (BMO), a bio-inspired global optimization algorithm.
  • Testing on simulated magnetic anomalies and real-world data from chromite, uranium deposits, and a Mesozoic dike.
  • Utilizing a second moving average (SMA) scheme for regional anomaly removal and conducting uncertainty assessment analyses.

Main Results:

  • BMO demonstrated an ability to scan the model parameter space more extensively than standard Particle Swarm Optimization (sPSO).
  • The algorithm consistently approached the unique global minimum without compromising accuracy or stability.
  • The SMA scheme was certified for regional anomaly elimination, and uncertainty analyses confirmed the reliability of BMO's solutions.

Conclusions:

  • The Barnacles Mating Optimizer (BMO) is a competitive and effective tool for geophysical inverse problems, particularly magnetic anomaly interpretation.
  • BMO offers advantages in exploring the solution space and achieving reliable results compared to traditional methods like sPSO.
  • The study recommends the use of BMO for model parameter estimation in various geophysical applications.