Gravity profiles interpretation applying a metaheuristic particle optimization algorithm of mineralized bodies...

Area of Science:

• Geophysics
• Mineral Exploration
• Computational Methods

Background:

• Gravity anomaly interpretation is key for identifying subsurface mineralized targets.
• Understanding density variations is crucial for distinguishing targets from surrounding structures.
• Simple geometric bodies are often used to model ore and mineral targets.

Purpose of the Study:

• To apply the particle optimization algorithm for interpreting gravity anomalies.
• To determine parameters of buried bodies modeled as finite vertical cylinders.
• To assess the algorithm's effectiveness in mineral exploration contexts.

Main Methods:

• Utilized particle optimization algorithm, a global metaheuristic method.
• Inferred gravity anomaly profiles to determine body parameters (e.g., depth, length).
• Evaluated performance on synthetic data with varying noise levels (0%, 5%, 10%) and a real Canadian mineral exploration dataset.

Main Results:

• The particle optimization algorithm demonstrated stability and accuracy.
• Performance was unaffected by noise and multi-model scenarios.
• Results from a Canadian mineral exploration case study aligned with existing geological and borehole data.

Conclusions:

• The particle optimization algorithm is a robust tool for gravity data analysis in mineral exploration.
• The method reliably identifies subsurface targets, even in the presence of noise.
• The algorithm's findings are consistent with established geological information and prior research.