Multichannel seismic impedance inversion with anisotropic total variation regularization

2017 ◽  
Author(s):  
Dehua Wang* ◽  
Jinghuai Gao
Keyword(s):  
Total Variation ◽  
Total Variation Regularization ◽  
Impedance Inversion ◽  
Anisotropic Total Variation

Data-driven multichannel seismic impedance inversion with anisotropic total variation regularization

2018 ◽  
Vol 26 (2) ◽  
pp. 229-241 ◽  
Author(s):  
Dehua Wang ◽  
Jinghuai Gao ◽  
Hongan Zhou
Keyword(s):  
Total Variation ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Data Driven ◽  
Total Variation Regularization ◽  
Split Bregman ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Impedance Inversion ◽  
Anisotropic Total Variation

AbstractAcoustic impedance (AI) inversion is a desirable tool to extract rock-physical properties from recorded seismic data. It plays an important role in seismic interpretation and reservoir characterization. When one of recursive inversion schemes is employed to obtain the AI, the spatial coherency of the estimated reflectivity section may be damaged through the trace-by-trace processing. Meanwhile, the results are sensitive to noise in the data or inaccuracies in the generated reflectivity function. To overcome the above disadvantages, in this paper, we propose a data-driven inversion scheme to directly invert the AI from seismic reflection data. We first explain in principle that the anisotropic total variation (ATV) regularization is more suitable for inverting the impedance with sharp interfaces than the total variation (TV) regularization, and then establish the nonlinear objective function of the AI model by using anisotropic total variation (ATV) regularization. Next, we solve the nonlinear impedance inversion problem via the alternating split Bregman iterative algorithm. Finally, we illustrate the performance of the proposed method and its robustness to noise with synthetic and real seismic data examples by comparing with the conventional methods.

Multi-trace blocky reflectivity inversion with anisotropic total variation regularization

2019 ◽  
Author(s):  
Sichao Zhang ◽  
Xu Fan ◽  
Guofa Li ◽  
Xinlong Huang ◽  
Li Jiang ◽  
...  
Keyword(s):  
Total Variation ◽  
Total Variation Regularization ◽  
Reflectivity Inversion ◽  
Anisotropic Total Variation

scholarly journals Multidirectional Anisotropic Total Variation and Its Application in the Tomography of the Surrounding Rock of Coal Mining Faces

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Bo Chen ◽  
Guowei Zhu ◽  
Zhenqiang Yang
Keyword(s):  
Coal Mining ◽  
Total Variation ◽  
Regularization Method ◽  
Surrounding Rock ◽  
Total Variation Regularization ◽  
Ct Reconstruction ◽  
Traveltime Tomography ◽  
Transmitted Waves ◽  
Mining Face ◽  
Anisotropic Total Variation

The computed tomography (CT) reconstruction algorithm is one of the crucial components of the CT system. To date, total variation (TV) has been widely used in CT reconstruction algorithms. Although TV utilizes the a priori information of the longitudinal and lateral gradient sparsity of an image, it introduces some staircase artifacts. To overcome the current limitations of TV and improve imaging quality, we propose a multidirectional anisotropic total variation (MATV) that uses multidirectional gradient information. The surrounding rock of coal mining faces uses principles of tomography similar to those of medical X-rays. The velocity distribution for the surrounding rock can be obtained by the first-arrival traveltime tomography of the transmitted waves in the coal mining face. Combined with the geological data, we can interpret the geological hazards in the coal mining face. To perform traveltime tomography, we first established the objective function of the first-arrival traveltime tomography of the transmitted waves based on the MATV regularization and then used the split Bregman method to solve the objective function. The simulated data and real data show that the MATV regularization method proposed in this paper can better maintain the boundaries of geological anomalies and reduce the artifacts compared with the isotropic total variation regularization method and the anisotropic total variation regularization method. Furthermore, this approach describes the distribution of geological anomalies more accurately and effectively and improves imaging accuracy.

Step phase reconstruction using an anisotropic total variation regularization method in a diffraction phase microscopy

2019 ◽  
Vol 58 (26) ◽  
pp. 7189 ◽  
Author(s):  
Allaparthi Venkata Satya Vithin ◽  
Sreeprasad Ajithaprasad ◽  
Gannavarpu Rajshekhar
Keyword(s):  
Total Variation ◽  
Regularization Method ◽  
Total Variation Regularization ◽  
Phase Reconstruction ◽  
Phase Microscopy ◽  
Anisotropic Total Variation

Nonlinear multichannel impedance inversion by total-variation regularization

Geophysics ◽  
2015 ◽  
Vol 80 (5) ◽  
pp. R217-R224 ◽  
Author(s):  
Ali Gholami
Keyword(s):  
Total Variation ◽  
Total Variation Regularization ◽  
Impedance Inversion

scholarly journals Seismic impedance inversion using second-order overlapping group sparsity with A-ADMM

2019 ◽  
Vol 17 (1) ◽  
pp. 97-116 ◽  
Author(s):  
Hao Wu ◽  
Shu Li ◽  
Yingpin Chen ◽  
Zhenming Peng
Keyword(s):  
Total Variation ◽  
Second Order ◽  
Inversion Method ◽  
Structured Sparsity ◽  
Group Sparsity ◽  
Order Difference ◽  
Impedance Inversion ◽  
Staircase Effect ◽  
Overlapping Group Sparsity ◽  
Anisotropic Total Variation

Abstract The anisotropic total variation with overlapping group sparsity (ATV_OGS) regularisation term is an improvement on the anisotropic total variation (ATV) regularisation term. It has been employed successfully in seismic impedance inversion as it can enhance the boundary information and relieve the staircase effect by exploring the structured sparsity of seismic impedance. However, because ATV_OGS constrains only the structured sparsity of the impedance's first-order difference and ignores the structured sparsity of the second-order difference, the staircase effect still occurs in an inversion result based on ATV_OGS. To further fit the structured sparsity of the impedance's second-order gradients, we introduce the overlapping group sparsity into the second-order difference of the impedance and propose a novel second-order ATV with overlapping group sparsity (SATV_OGS) seismic impedance inversion method. The proposed method reduces the interference of the large amplitude noise and further mitigates the staircase effect of the ATV_OGS. Furthermore, the accelerated alternating direction method of multipliers (A-ADMM) framework applied to this novel method. It can increase the efficiency of inversion. The experiments are carried out on a general model data and field data. Based on the experimental results, the proposed method can obtain higher resolution impedance than some impedance inversion methods based on total variation.

CBCT Image Reconstruction via Anisotropic Total-variation Regularization

2009 ◽  
Vol 75 (3) ◽  
pp. S644
Author(s):  
K. Choi ◽  
J. Wang ◽  
L. Zhu ◽  
Y. Ye ◽  
L. Xing
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Total Variation Regularization ◽  
Cbct Image ◽  
Anisotropic Total Variation
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