Least‐squares seimic data regularization with t‐k domain prestack time migration

2009 ◽  
Author(s):  
Yaxun Tang ◽  
Huazhong Wang ◽  
Xiaopeng Zheng
Keyword(s):  
Least Squares ◽  
Time Migration ◽  
Data Regularization ◽  
Prestack Time Migration

Least-squares migration with a blockwise Hessian matrix: A prestack time-migration approach

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. R625-R640 ◽  
Author(s):  
Bowu Jiang ◽  
Jianfeng Zhang
Keyword(s):  
Least Squares ◽  
Field Data ◽  
Hessian Matrix ◽  
Total Variation Regularization ◽  
Data Sets ◽  
Reflection Point ◽  
Inverse Approach ◽  
Time Migration ◽  
Prestack Time Migration ◽  
Least Squares Migration

We have developed an explicit inverse approach with a Hessian matrix for the least-squares (LS) implementation of prestack time migration (PSTM). A full Hessian matrix is divided into a series of computationally tractable small-sized matrices using a localized approach, thus significantly reducing the size of the inversion. The scheme is implemented by dividing the imaging volume into a series of subvolumes related to the blockwise Hessian matrices that govern the mapping relationship between the migrated result and corresponding reflectivity. The proposed blockwise LS-PSTM can be implemented in a target-oriented fashion. The localized approach that we use to modify the Hessian matrix can eliminate the boundary effects originating from the blockwise implementation. We derive the explicit formula of the offset-dependent Hessian matrix using the deconvolution imaging condition with an analytical Green’s function of PSTM. This avoids the challenging task of estimating the source wavelet. Moreover, migrated gathers can be generated with the proposed scheme. The smaller size of the blockwise Hessian matrix makes it possible to incorporate the total-variation regularization into the inversion, thus attenuating noises significantly. We revealed the proposed blockwise LS-PSTM with synthetic and field data sets. Higher quality common-reflection-point gathers of the field data are obtained.

Improving prestack time migration by least-squares equivalent offset method

2021 ◽  
pp. 1-10
Author(s):  
Dan Wu ◽  
Haili Wu ◽  
Qun Li ◽  
Congbin Wang ◽  
Yufeng Lu
Keyword(s):  
Least Squares ◽  
Time Migration ◽  
Prestack Time Migration

scholarly journals Noise suppression using preconditioned least-squares prestack time migration: application to the Mississippian limestone

2016 ◽  
Vol 13 (4) ◽  
pp. 441-453 ◽  
Author(s):  
Shiguang Guo ◽  
Bo Zhang ◽  
Qing Wang ◽  
Alejandro Cabrales-Vargas ◽  
Kurt J Marfurt
Keyword(s):  
Least Squares ◽  
Noise Suppression ◽  
Time Migration ◽  
Prestack Time Migration ◽  
Mississippian Limestone

scholarly journals Viscoacoustic least-squares migration with a blockwise Hessian matrix: an effective Q approach

2020 ◽  
Author(s):  
Mingpeng Song ◽  
Jianfeng Zhang ◽  
Jiangjie Zhang
Keyword(s):  
Least Squares ◽  
Field Data ◽  
Hessian Matrix ◽  
Data Sets ◽  
Matrix Approach ◽  
Inverse Approach ◽  
Time Migration ◽  
Q Model ◽  
Prestack Time Migration ◽  
Least Squares Migration

Abstract We present an explicit inverse approach using a Hessian matrix for least-squares migration (LSM) with Q compensation. The scheme is developed by incorporating an effective Q-based solution of the viscoacoustic wave equation into a blockwise approximation to the Hessian in LSM, which is implemented after the so-called deabsorption prestack time migration (PSTM). The effective Q model used fully accounts for frequency-dependent traveltime and amplitude at the same imaging location. We can extract the effective Q parameters by scanning during previous deabsorption PSTM. This avoids the challenging task of building the Q model. The blockwise Hessian matrix approach decomposes the full Hessian matrix into a series of computationally tractable small-sized matrices using a localised approach. We derive the explicit formula of the offset-dependent Hessian matrix using an analytical Green's function obtained from deabsorption PSTM. In this way, we can approximate a reflectivity imaging for the targeted zone by a spatial deconvolution of the migrated result with an explicit inverse. The resulting scheme broadens the frequency-band of imaging by deabsorption, and improves the subsurface illumination and spatial resolution through the inverse Hessian. A high-resolution, true-amplitude migrated gather can then be obtained. Synthetic and field data sets demonstrate the proposed blockwise LS-QPSTM.

A comparative study of common-reflection-surface prestack time migration and data regularization: Application in crooked-line data

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. S355-S364
Author(s):  
German Garabito
Keyword(s):  
Comparative Study ◽  
Time Domain ◽  
High Signal ◽  
Data Set ◽  
Prestack Migration ◽  
Time Migration ◽  
Data Regularization ◽  
Common Reflection Surface ◽  
Prestack Time Migration ◽  
The Time Domain

To improve the time-domain imaging of poor-quality seismic data, the common-reflection-surface (CRS) stack method was introduced to simulate zero-offset (ZO) stacked sections from a multicoverage data set based on automatic coherence analysis of seismic signals. This method produces improved ZO stacked sections with a high signal-to-noise ratio (S/N) and good continuity of reflection events. However, the stacking results may have some undesirable artifacts that can degrade the poststack migrated image. To overcome these drawbacks, I have developed a prestack data regularization method, based on CRS partial stacks, which produces prestack data with high S/N and enhanced reflection events. The regularized data are usually applied for velocity analysis and conventional prestack migration in the time and depth domains. Recently, the CRS stacking operator has also been applied for developing a new type of prestack beam migration. This new migration combines the classic Kirchhoff migration with the CRS stack method, in which the beam-forming process stacks locally coherent events that are performed using the CRS operator during migration. This work reviews this CRS-based prestack migration method in the time domain and presents a comparative study with the main standard applications of the CRS stack method, such as CRS stacking plus poststack time migration and CRS-based regularization plus prestack time migration (PSTM). To evaluate its effectiveness and reliability, CRS-based PSTM and CRS-based prestack data regularization were applied in a crooked line. The time-migrated image resulting from the regularized data has strong migration artifacts due to the crookedness of the seismic line; in contrast, the CRS-based time migration provides a good-quality image without migration artifacts.

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