Affiliation:
1. Research Center for Computational and Exploration Geophysics, State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan China
2. Department of Earth and Space Sciences Southern University of Science and Technology Shenzhen China
Abstract
AbstractThe imaging condition is a crucial component of the reverse time migration. In its conventional form, it involves cross‐correlating the extrapolated source‐ and receiver‐side wavefields. Effective imaging conditions are usually developed to suppress imaging artefacts (e.g. low‐wavenumber artefacts) and enhance the image quality. For acoustic reverse time migration, not only the scalar pressure but also their spatial and/or time derivatives are used in the imaging condition, similar to the gradient terms of adjoint tomography. These operations implicitly introduce additional angle‐domain weighting factors to the image results. In this study, based on an analysis of angle‐dependent properties of the existing imaging conditions, we propose a new imaging condition tailored for acoustic reverse time migration. It can be implemented efficiently using the variables within the finite‐difference solver. Without explicitly measuring wave propagation directions, the proposed imaging condition can naturally suppress the low‐wavenumber artefacts while maintaining a relatively wider imaging aperture, thereby corresponding to a broader wavenumber sampling range. Additionally, the evolved imaging conditions for imaging elastic P–P and S–S scattering and reflections are also formulated. In the angle domain, we conduct a comparative analysis between existing imaging conditions and the newly proposed ones. Various numerical examples are provided to demonstrate the advantages of the new imaging conditions. A comprehensive understanding of their angle‐domain properties may be further beneficial to constructing reasonable inversion strategies for full waveform inversion.
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation