Marchenko multiple elimination of a laboratory example

Zhang, Lele; Slob, Evert

doi:10.1093/gji/ggaa062

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…Later, Zhang and Slob [4] used a set of measured laboratory data to evaluate the performance of the MME. The same authors [5] showed the first example of applying the MME on a field data set from the Norwegian North Sea, which validated the capabilities of the MME schemes and showed that it could effectively eliminate internal multiples. Aiming to explore the potential of the MME approach, many techniques went on to be developed, such as the transmission-compensated Marchenko multiple eliminations (T-MME) derived by Zhang and colleagues [6], which is a scheme that eliminates multiple internal reflections and compensates for two-way transmission losses contained in primary reflections.…”

Section: Introductionmentioning

confidence: 79%

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A Comparison Between Different Solutions for the Marchenko Multiple Eliminations Scheme

Santos¹,

Revelo²,

Pestana³

et al. 2023

JBTH

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Seismic reflection data can be used to generate high-resolution in-depth images capable of facilitating, with high precision, the correct positioning of wells in hydrocarbon exploration and production. However, images produced by migrating seismic data are often contaminated by artifacts due to multiple internal reflections. Different schemes can be used to avoid problems caused by these noises and to attenuate them, such as the Marchenko multiple elimination scheme (MME). Various solutions based on the MME method have been proposed in the literature. Therefore, in this work, we explore the MME based on the least-squares schemes (LSMME), the MME as Neumann series approximation solution (NMME), and the MME based on beyond Neumann method (BNMME), and compare them in terms of effectiveness and efficiency in different numerical examples.

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Section: Introductionmentioning

confidence: 79%

“…The Marchenko multiple eliminations based on Equation (4) are conventionally named by the MME scheme. However, we must remember that the solution based on the Neumann series approximation converges only if (5) Marchenko Multiple Eliminations Scheme…”

Section: Neumann Series Solutionmentioning

confidence: 99%

A Comparison Between Different Solutions for the Marchenko Multiple Eliminations Scheme

Santos¹,

Revelo²,

Pestana³

et al. 2023

JBTH

View full text Add to dashboard Cite

show abstract

“…In that case, internal multiple reflections contained in input shot gather cannot be removed or attenuated effectively. The measured laboratory dataset used in Zhang and Slob (2019b) can be taken as an example. The MME scheme was applied to remove internal multiple reflections contained in the measured laboratory dataset, although some internal multiple reflections were successfully removed or attenuated, some internal multiple reflections were present with opposite polarity or even stronger after the processing because of the low-quality of the input dataset.…”

Section: Discussionmentioning

confidence: 99%

A field data example of Marchenko multiple elimination

Zhang

Slob

2019

SEG Technical Program Expanded Abstracts 2019

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Multiple reflections are often considered as noise in seismic data. Dealing with them has attracted much attention from industry and academia. A variety of schemes have been developed for removal of free-surface multiple reflections and success has been achieved in numerical and field datasets. However, less attention has been directed toward internal multiple reflection removal. The Marchenko multiple elimination scheme is capable to eliminate internal multiple reflections without model information or adaptive subtraction. This scheme is derived from coupled Marchenko-type equations by projecting the focusing functions from the focusing level back to the acquisition surface. Primary reflections are filtered from acquired seismic data. We apply the Marchenko multiple elimination scheme to a deep water 2D field dataset from the Norwegian North Sea to test the performance. We show that the Marchenko multiple elimination scheme is an appropriate method for removing internal multiple reflections when high-quality pre-processing is performed.

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“…This simple model is chosen to keep the number of events limited and to allow for an explanation that can be followed more easily. The method is not limited to simple models and can successfully be applied to complicated 3D media as well (see for example Zhang and Slob (2020c)).…”

Section: Introductionmentioning

confidence: 99%

Implementation of the Marchenko multiple elimination algorithm

et al. 2021

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The Marchenko multiple elimination and transmission compensation schemes retrieve primary reflections in the two-way traveltime domain without model information or using adaptive subtraction. Both schemes are derived from projected Marchenko equations and similar to each other, but use different time-domain truncation operators. The Marchenko multiple elimination scheme retrieves a new dataset without internal multiple reflections. The transmission compensated Marchenko multiple elimination scheme does the same and additionally compensates for transmission losses in the primary reflections. Both schemes can be solved with an iterative algorithm based on a Neumann series. At each iteration, a convolution or correlation between the projected focusing function and the measured reflection response are performed and after each convolution or correlation, a truncation in the time domain is applied. After convergence, the resulting projected focusing function is used for retrieving the transmission compensated primary reflections and the projected Green’s function is used for the physical primary reflections. We demonstrate that internal multiples are removed by using time-windowed input data that only contain primary reflections. We evaluate both schemes in detail and develop an iterative implementation that reproduces the presented numerical examples. The software is part of our open-source suite of programs and fits into the Seismic Unix software suite of the Colorado School of Mines.

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Marchenko multiple elimination of a laboratory example

Cited by 8 publications

References 24 publications

A Comparison Between Different Solutions for the Marchenko Multiple Eliminations Scheme

A Comparison Between Different Solutions for the Marchenko Multiple Eliminations Scheme

A field data example of Marchenko multiple elimination

Implementation of the Marchenko multiple elimination algorithm

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