.png){kind=icon}
.png){kind=icon}
Return
Full-wave seismic illumination and resolution analyses: A Poynting-vector-based method
.png){kind=icon}
PRE
AI
DOI：10.1190/GEO2016-0003.1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Illumination and resolution analysis provides vital information regarding the response of an imaging system to subsurface structures. However, generating the resolution function is often computationally intensive, which prevents it from being widely used in practice. This problem is particularly severe for the time-domain migration method, such as reverse time migration (RTM). To solve this problem, we have developed a fast full-wave-based illumination and resolution analysis method. The source-and receiver-side waves are extrapolated to the subsurface for simulating the imaging process. To create the relations linking the incident and scattering directions to the target wavenumber components, we have adopted an efficient Poynting-vector-based method for wavefield angle decomposition. By taking the approximation that the time-domain wavefield preserves the source spectrum during propagation, massive input/output and trace-by-trace Fourier transform can be avoided and the finite-frequency calculated broadband signal can be directly converted to the wavenumber domain for calculating the point spreading functions (PSFs). Combining these approaches, the resulting method avoids intensive calculations, massive input/output, and huge storage requirements commonly involved in generating the illumination and resolution functions. The method is highly efficient and particularly suitable to team with RTM for resolution analysis. Numerical examples are used to validate this method. We have determined how to calculate the acquisition dip response and PSFs, based on which, the quality of the depth image can be significantly improved.
Keywords:
REVERSE-TIME MIGRATION
ACQUISITION APERTURE CORRECTION
COMMON-IMAGE GATHERS
ANGLE-DOMAIN
BEAMLET DECOMPOSITION
DEPTH MIGRATION
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.2
Papers:
8.4K
Citations:
3.3W
