Adaptive surface‐related multiple elimination

Geophysics ◽  
1992 ◽  
Vol 57 (9) ◽  
pp. 1166-1177 ◽  
Author(s):  
D. J. Verschuur ◽  
A. J. Berkhout ◽  
C. P. A. Wapenaar
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Simulated Data ◽  
Seismic Inversion ◽  
The Other ◽  
Inversion Process ◽  
Elimination Process ◽  
Free Data ◽  
Surface Reflectivity ◽  
Multiple Elimination

The major amount of multiple energy in seismic data is related to the large reflectivity of the surface. A method is proposed for the elimination of all surface‐related multiples by means of a process that removes the influence of the surface reflectivity from the data. An important property of the proposed multiple elimination process is that no knowledge of the subsurface is required. On the other hand, the source signature and the surface reflectivity do need to be provided. As a consequence, the proposed process has been implemented adaptively, meaning that multiple elimination is designed as an inversion process where the source and surface reflectivity properties are estimated and where the multiple‐free data equals the inversion residue. Results on simulated data and field data show that the proposed multiple elimination process should be considered as one of the key inversion steps in stepwise seismic inversion.

Multidirectional eigenvalue-based coherence attribute for discontinuity detection

Geophysics ◽  
2021 ◽  
pp. 1-48
Author(s):  
Binpeng Yan ◽  
Ruirui Fang ◽  
Xingguo Huang ◽  
Weiming Ou
Keyword(s):  
Physical Model ◽  
Seismic Data ◽  
Field Data ◽  
Seismic Interpretation ◽  
Covariance Matrices ◽  
The Other ◽  
Computationally Efficient ◽  
Discontinuity Detection ◽  
Geological Discontinuities ◽  
Parallel Direction

The conventional coherence attribute is typically applied to migrated full-stacked seismic data volumes to detect geological discontinuities. Recently, multispectral, multiazimuth, and multioffset coherence attributes have been proposed and implemented with different seismic data volumes of specific frequencies, azimuths, and offsets to enhance discontinuities. Generally, geological anomalies, such as faults and channels, will be better illuminated by a perpendicular rather than a parallel direction for computation. Therefore, we propose a multidirectional eigenvalue-based coherence attribute by establishing multiple covariance matrices along certain different directions on a single post-stack volume. We adopt two methods to compute multidirectional coherence attribute. One is to compute multiple coherence volumes in different directions and to define the minimum as the final multidirectional coherence. This method is time-consuming, but could provide partial and overall discontinuity simultaneously. The other method obtains one coherence volume by summing covariance matrices in different directions, which is computationally efficient, but only provides overall discontinuity. The performance of 3D physical model and field data volumes demonstrates that multidirectional coherence can highlight subtle geologic structures with a higher resolution than conventional coherence. This suggests that multidirectional coherence attribute may serve as an effective tool for detecting the distribution of geologic discontinuities in seismic interpretation.

scholarly journals Integrated receiver deghosting and closed-loop surface-multiple elimination

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. T133-T141 ◽  
Author(s):  
Jan-Willem Vrolijk ◽  
Eric Verschuur ◽  
Gabriel Lopez
Keyword(s):  
Large Scale ◽  
Closed Loop ◽  
Simulated Data ◽  
Sea Surface ◽  
Dipole Source ◽  
Inversion Process ◽  
Loop Surface ◽  
Imaging Algorithms ◽  
Integrated Receiver ◽  
Multiple Elimination

Accurate surface-related multiple removal is an important step in conventional seismic processing, and more recently, primaries and surface multiples are separated such that each of them is available for imaging algorithms. Current developments in the field of surface-multiple removal aim at estimating primaries in a large-scale inversion process. Using such a so-called closed-loop process, in each iteration primaries and surface multiples will be updated until they fit the measured data. The advantage of redefining surface-multiple removal as a closed-loop process is that certain preprocessing steps can be included, which can lead to an improved multiple removal. In principle, the surface-related multiple elimination process requires deghosted data as input; thus, the source and receiver ghost must be removed. We have focused on the receiver ghost effect and assume that the source is towed close to the sea surface, such that the source ghost effect is well-represented by a dipole source. The receiver ghost effect is integrated within the closed-loop primary estimation process. Thus, primaries are directly estimated without the receiver ghost effect. After receiver deghosting, the upgoing wavefield is defined at zero depth, which is the surface. We have successfully validated our method on a 2D simulated data and on a 2D subset from 3D broadband field data with a slanted cable.

scholarly journals Improving Seismic Inversion Robustness via Deformed Jackson Gaussian

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1081
Author(s):  
Suzane A. Silva ◽  
Sérgio Luiz E. F. da Silva ◽  
Renato F. de Souza ◽  
Andre A. Marinho ◽  
João M. de Araújo ◽  
...  
Keyword(s):  
Gaussian Distribution ◽  
Seismic Data ◽  
Seismic Inversion ◽  
Seismic Sources ◽  
Model Estimation ◽  
Inversion Process ◽  
Scientific Communities ◽  
Significant Challenge ◽  
Data Inversion ◽  
Robust Formulation

The seismic data inversion from observations contaminated by spurious measures (outliers) remains a significant challenge for the industrial and scientific communities. This difficulty is due to slow processing work to mitigate the influence of the outliers. In this work, we introduce a robust formulation to mitigate the influence of spurious measurements in the seismic inversion process. In this regard, we put forth an outlier-resistant seismic inversion methodology for model estimation based on the deformed Jackson Gaussian distribution. To demonstrate the effectiveness of our proposal, we investigated a classic geophysical data-inverse problem in three different scenarios: (i) in the first one, we analyzed the sensitivity of the seismic inversion to incorrect seismic sources; (ii) in the second one, we considered a dataset polluted by Gaussian errors with different noise intensities; and (iii) in the last one we considered a dataset contaminated by many outliers. The results reveal that the deformed Jackson Gaussian outperforms the classical approach, which is based on the standard Gaussian distribution.

scholarly journals A field data example of Marchenko multiple elimination

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. S65-S70 ◽  
Author(s):  
Lele Zhang ◽  
Evert Slob
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Field Data ◽  
Multiple Reflections ◽  
Coherent Noise ◽  
Data Set ◽  
Model Independent ◽  
Multiple Elimination

Internal multiple reflections have been widely considered as coherent noise in measured seismic data, and many approaches have been developed for their attenuation. The Marchenko multiple elimination (MME) scheme eliminates internal multiple reflections without model information or adaptive subtraction. This scheme was originally derived from coupled Marchenko equations, but it was modified to make it model independent. It filters primary reflections with their two-way traveltimes and physical amplitudes from measured seismic data. The MME scheme is applied to a deepwater field data set from the Norwegian North Sea to evaluate its success in removing internal multiple reflections. The result indicates that most internal multiple reflections are successfully removed and primary reflections masked by overlapping internal multiple reflections are recovered.

Time-variant wavelet extraction with a local-attribute-based time-frequency decomposition for seismic inversion

2017 ◽  
Vol 5 (1) ◽  
pp. SC9-SC16 ◽  
Author(s):  
Rui Zhang ◽  
Sergey Fomel
Keyword(s):  
Frequency Spectrum ◽  
Seismic Data ◽  
Field Data ◽  
Seismic Signal ◽  
Seismic Inversion ◽  
Kernel Matrix ◽  
Time Frequency ◽  
Seismic Wavelet ◽  
Frequency Decomposition ◽  
Noise Contamination

Seismic impedance inversion has been widely used to estimate subsurface properties. Conventional inversion assumes that seismic data are the convolution result of seismic wavelet and reflectivity, implying that seismic data are stationary when a constant wavelet is considered. However, seismic data are nonstationary because of noise contamination and attenuation during wave propagation, which means that the frequency spectrum of the seismic signal changes from shallow to deep formations. We have developed a time-variant wavelet extraction method by using a local-attribute-based spectral decomposition technique. Time-variant wavelets are generated according to the local frequency spectrum, which can be used to construct a time-variant wavelet kernel matrix. By using this time-variant kernel matrix, we can obtain a better correlation between synthetic and extracted seismograms than by using constant wavelet on a field data example. Using this example, we have also compared the time-variant and constant wavelets for inverting the field data to estimate subsurface acoustic impedance. Our results showed improved resolution and a better fit to well-log-measured impedance by using the time-variant wavelets.

Estimation of multiple scattering by iterative inversion, Part II: Practical aspects and examples

Geophysics ◽  
1997 ◽  
Vol 62 (5) ◽  
pp. 1596-1611 ◽  
Author(s):  
D. J. Verschuur ◽  
A. J. Berkhout
Keyword(s):  
Iteration Step ◽  
Linear Least Squares ◽  
Data Set ◽  
Elimination Method ◽  
Elimination Process ◽  
Free Data ◽  
Iterative Inversion ◽  
Multiple Elimination ◽  
Directivity Effects ◽  
Generating System

A surface‐related multiple‐elimination method can be formulated as an iterative procedure: the output of one iteration step is used as input for the next iteration step (part I of this paper). In this paper (part II) it is shown that the procedure can be made very efficient if a good initial estimate of the multiple‐free data set can be provided in the first iteration, and in many situations, the Radon‐based multiple‐elimination method may provide such an estimate. It is also shown that for each iteration, the inverse source wavelet can be accurately estimated by a linear (least‐squares) inversion process. Optionally, source and detector variations and directivity effects can be included, although the examples are given without these options. The iterative multiple elimination process, together with the source wavelet estimation, are illustrated with numerical experiments as well as with field data examples. The results show that the surface‐related multiple‐elimination process is very effective in time gates where the moveout properties of primaries and multiples are very similar (generally deep data), as well as for situations with a complex multiple‐generating system.

scholarly journals Deblending by direct inversion

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. A9-A12 ◽  
Author(s):  
Kees Wapenaar ◽  
Joost van der Neut ◽  
Jan Thorbecke
Keyword(s):  
Inverse Problem ◽  
Seismic Data ◽  
Iterative Procedure ◽  
Inversion Process ◽  
Direct Inversion ◽  
Source Data ◽  
Band Limited ◽  
Blended Data ◽  
Simultaneous Source ◽  
Additional Constraints

Deblending of simultaneous-source data is usually considered to be an underdetermined inverse problem, which can be solved by an iterative procedure, assuming additional constraints like sparsity and coherency. By exploiting the fact that seismic data are spatially band-limited, deblending of densely sampled sources can be carried out as a direct inversion process without imposing these constraints. We applied the method with numerically modeled data and it suppressed the crosstalk well, when the blended data consisted of responses to adjacent, densely sampled sources.

Integrated VTI model building with seismic data, geologic information, and rock-physics modeling — Part 1: Theory and synthetic test

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. C177-C191 ◽  
Author(s):  
Yunyue Li ◽  
Biondo Biondi ◽  
Robert Clapp ◽  
Dave Nichols
Keyword(s):  
Seismic Data ◽  
Seismic Anisotropy ◽  
Model Building ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Additional Information ◽  
Synthetic Test ◽  
Rock Physics Modeling ◽  
Physics Modeling ◽  
Geologic Information

Seismic anisotropy plays an important role in structural imaging and lithologic interpretation. However, anisotropic model building is a challenging underdetermined inverse problem. It is well-understood that single component pressure wave seismic data recorded on the upper surface are insufficient to resolve a unique solution for velocity and anisotropy parameters. To overcome the limitations of seismic data, we have developed an integrated model building scheme based on Bayesian inference to consider seismic data, geologic information, and rock-physics knowledge simultaneously. We have performed the prestack seismic inversion using wave-equation migration velocity analysis (WEMVA) for vertical transverse isotropic (VTI) models. This image-space method enabled automatic geologic interpretation. We have integrated the geologic information as spatial model correlations, applied on each parameter individually. We integrate the rock-physics information as lithologic model correlations, bringing additional information, so that the parameters weakly constrained by seismic are updated as well as the strongly constrained parameters. The constraints provided by the additional information help the inversion converge faster, mitigate the ambiguities among the parameters, and yield VTI models that were consistent with the underlying geologic and lithologic assumptions. We have developed the theoretical framework for the proposed integrated WEMVA for VTI models and determined the added information contained in the regularization terms, especially the rock-physics constraints.

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