Quadrilateral mesh optimisation method based on swarm intelligence optimisation

As oil and gas exploration advances, the growing complexity of geological conditions demands higher-quality quadrilateral meshes for spectral element method-based seismic simulations. For complex geological models, existing quadrilateral meshing algorithms struggle to generate high-quality meshes that meet the spectral element method's requirements, often producing initial meshes with topological errors or concave elements, which compromise simulation accuracy. To address this, we propose a swarm intelligence-based secondary optimisation method, employing particle swarm optimisation (PSO), wolf pack algorithm (WPA), and firefly algorithm (FA) to iteratively refine distorted nodes. Results demonstrate that all three algorithms eliminate initial mesh defects, with WPA achieving the highest mesh quality, PSO exhibiting the fastest convergence, and FA performing least effectively. The optimised meshes meet the high-quality standards of the spectral element method, significantly improving simulation stability and computational efficiency, and laying a foundation for the further application of the spectral element method in seismic exploration.