Hybrid optimization for DC resistivity imaging via intelligible-in-time logic and the interior point method

Area of Science:

• Geophysics
• Earth Sciences
• Computational Geophysics

Background:

• Geophysical DC resistivity imaging is vital for subsurface exploration but faces challenges with traditional inversion methods due to data nonlinearities.
• Accurate resolution of complex subsurface features remains a significant hurdle in geophysical data interpretation.
• Existing techniques often struggle with balancing global search and local refinement for optimal inversion results.

Purpose of the Study:

• To develop and validate a novel hybrid optimization approach for geophysical DC resistivity inversion.
• To improve the accuracy, efficiency, and resolution of subsurface imaging techniques.
• To overcome the limitations of traditional inversion methods in handling complex geological models and large datasets.

Main Methods:

• A hybrid optimization strategy combining incomprehensible but intelligible-in-time (IbI) logic with the interior point method (IPM).
• Utilizing the IbI logic algorithm (ILA) for initial global search to identify promising solution spaces.
• Employing the IPM for local optimization to refine solutions, ensuring robustness and efficiency.
• Formulating an objective function with data misfit and model regularization terms for accurate and smooth models.

Main Results:

• The hybrid approach demonstrated superior performance in resolving subsurface anomalies using synthetic data.
• Application to real DC resistivity data successfully identified geological fault zones, aligning with prior research.
• The combined IbI-IPM method significantly enhanced the resolution of subsurface structures compared to traditional methods.
• Effective balancing of exploration and refinement phases optimized computation time and model delineation precision.

Conclusions:

• The proposed hybrid optimization algorithm offers a robust and efficient solution for geophysical DC resistivity inversion.
• This novel approach significantly improves the accuracy and resolution of subsurface imaging, advancing geophysical data interpretation practices.
• The synergy between IbI logic and IPM provides a powerful tool for analyzing complex geological scenarios and large-scale datasets.