Mesh-free radial-basis function-generated finite differences and its application in reverse-time migration

Geophysics ◽  
2020 ◽  
pp. 1-52
Author(s):  
Han Wu ◽  
Chengyu Sun ◽  
Shizhong Li ◽  
Jie Tang ◽  
Ning Xu

Compared with one-way wave equation migration and ray-based migration, reverse time migration (RTM) using the two-way wave propagation information can produce accurate imaging result for complex structures. Its computational accuracy and efficiency are mainly determined by numerical method for wavefield simulation. When using traditional regular grids for seismic modeling, scattering artifacts may occur due to the stepped approximation of layer interfaces and rugged topography. On the other hand, the irregular grids requires complex grid generation algorithm, despite having certain geometric flexibility. Mesh-free RTM can effectively reduce the scattered noise under regular grids and avoid the extra computation in the process of irregular grids generation. For the implementation of mesh-free RTM method, an algorithm with fast generation of node distributions is used to discretize the underground velocity model, and radial-basis function generated finite-difference (RBF-FD) is used to realize the numerical simulation of wave propagation, cross-correlation imaging condition is adopted for imaging. The mesh-free RTM method which has both flexibility of simulation region and abundance of wavefield information, reduces the storage required for reverse time migration, shows the potential of high-accuracy migration in the case of undulating surface and provides more accurate migration imaging results for oil and gas exploration under complex geological conditions.

Geophysics ◽  
2001 ◽  
Vol 66 (1) ◽  
pp. 246-255 ◽  
Author(s):  
Oong K. Youn ◽  
Hua‐wei Zhou

Depth imaging with multiples is a prestack depth migration method that uses multiples as the signal for more accurate boundary mapping and amplitude recovery. The idea is partially related to model‐based multiple‐suppression techniques and reverse‐time depth migration. Conventional reverse‐time migration uses the two‐way wave equation for the backward wave propagation of recorded seismic traces and ray tracing or the eikonal equation for the forward traveltime computation (the excitation‐time imaging principle). Consequently, reverse‐time migration differs little from most other one‐way wave equation or ray‐tracing migration methods which expect only primary reflection events. Because it is almost impossible to attenuate multiples without degrading primaries, there has been a compelling need to devise a tool to use multiples constructively in data processing rather than attempting to destroy them. Furthermore, multiples and other nonreflecting wave types can enhance boundary imaging and amplitude recovery if a full two‐way wave equation is used for migration. The new approach solves the two‐way wave equation for both forward and backward directions of wave propagation using a finite‐difference technique. Thus, it handles all types of acoustic waves such as reflection (primary and multiples), refraction, diffraction, transmission, and any combination of these waves. During the imaging process, all these different types of wavefields collapse at the boundaries where they are generated or altered. The process goes through four main steps. First, a source function (wavelet) marches forward using the full two‐way scalar wave equation from a source location toward all directions. Second, the recorded traces in a shot gather march backward using the full two‐way scalar wave equation from all receiver points in the gather toward all directions. Third, the two forward‐ and backward‐propagated wavefields are correlated and summed for all time indices. And fourth, a Laplacian image reconstruction operator is applied to the correlated image frame. This technique can be applied to all types of seismic data: surface seismic, vertical seismic profile (VSP), crosswell seismic, vertical cable seismic, ocean‐bottom cable (OBC) seismic, etc. Because it migrates all wave types, the input data require no or minimal preprocessing (demultiple should not be done, but near‐surface or acquisition‐related problems might need to be corrected). Hence, it is only a one‐step process from the raw field gathers to a final depth image. External noise in the raw data will not correlate with the forward wavefield except for some coincidental matching; therefore, it is usually unnecessary to do signal enhancement processing before the depth imaging with multiples. The input velocity model could be acquired from various methods such as iterative focusing analysis or tomography, as in other prestack depth migration methods. The new method has been applied to data sets from a simple multiple‐generating model, the Marmousi model, and a real offset VSP. The results show accurate imaging of primaries and multiples with overall significant improvements over conventionally imaged sections.


Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. S141-S152 ◽  
Author(s):  
Jeffrey Shragge

Migration of seismic data from topography using methods based on finite-difference (FD) approximation to acoustic wave propagation commonly suffers from a number of imaging drawbacks due to the difficulty of applying FD stencils to irregular computational meshes. Altering the computational geometry from Cartesian to a topographic coordinate system conformal to the data acquisition surface can circumvent many of these issues. The coordinate transformation approach allows for acoustic wave propagation and the crosscorrelation and inverse-scattering imaging conditions to be posed and computed directly in topographic coordinates. Resulting reverse time migration (RTM) images may then be interpolated back to the Cartesian domain using the known inverse mapping. Orthogonal 2D topographic coordinates can be developed using known conformal mapping transforms and serve as the computational mesh for performing migration from topography. Impulse response tests demonstrate the accuracy of the 2D generalized acoustic wave propagation. RTM imaging examples show the efficacy of performing migration from topography directly from the data acquisition surface on topographic meshes and the ability to image complex near-surface structure even in the presence of strong lateral velocity variation.


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