Vector elastic deconvolution migration with dual wavefield decomposition
Elastic-wave imaging using multi-component data can provide more useful subsurface information than acoustic-wave imaging, but is usually algorithmically challenging. We develop a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method employs a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform, and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically demonstrate that our new method produces notably higher-resolution and more amplitude-balanced elastic images compared with a cross-correlation-based vector elastic reverse-time migration method.