Magnetic data interpretation for 2D dikes by the metaheuristic bat algorithm: sustainable development cases

Area of Science:

• Geophysics
• Computational Intelligence

Background:

• Metaheuristic algorithms are vital for global optimal solutions in magnetic data inversion and modeling.
• Accurate estimation of subsurface source parameters is crucial for geological resource exploration.

Purpose of the Study:

• To introduce and evaluate the Bat Algorithm Optimization (BAO) for magnetic data inversion.
• To estimate dimensional source parameters of 2D magnetic anomalies caused by dikes.

Main Methods:

• The Bat Algorithm Optimization (BAO) technique, inspired by bat echolocation, was employed.
• BAO was applied to synthetic and real-world magnetic data for 2D dipping and vertical dikes.
• Parameters estimated include depth, location, amplitude, magnetization angle, and dike width.

Main Results:

• BAO successfully estimated source parameters for single and multiple dike structures with high accuracy and stability.
• The method performed well on both noise-free and noisy synthetic magnetic data.
• Field applications in China and Egypt for iron ore and metavolcanic basalt yielded results consistent with geological data.

Conclusions:

• The Bat Algorithm Optimization (BAO) is a robust and effective tool for 2D magnetic data inversion.
• BAO provides reliable estimations of geological source parameters, aiding in resource exploration and geological mapping.