An introduction to Marchenko methods for imaging

Lomas, Angus; Curtis, Andrew

doi:10.1190/geo2018-0068.1

Cited by 32 publications

(17 citation statements)

References 45 publications

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“…"Marchenko" is a set of data-driven methods that help us to project surface seismic data to points in the subsurface. It relates the Green's function from a virtual source inside a medium to the reflection response at the surface of that medium [10,11]. The "Markov"-chain-based approach is able to account for the change in seismic response of damaged structures [12], and it correlates with the occurrence of the word "seismicity."…”

Section: Processing and Data Acquisition Methodsmentioning

confidence: 99%

Text Analysis Reveals Major Trends in Exploration Geophysics

Eltsov¹,

Yutkin²,

Patzek³

2020

Energies

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Evolution of professional language reveals advances in geophysics: researchers enthusiastically describe new methods of surveying, data processing techniques, and objects of their study. Geophysicists publish their cutting-edge research in the proceedings of international conferences to share their achievements with the world. Tracking changes in the professional language allows one to identify trends and current state of science. Here, we explain our text analysis of the last 30 annual conferences organized by the Society of Exploration Geophysicists (SEG). These conferences are among the largest geophysical gatherings worldwide. We split the 21,864 SEG articles into 52 million words and phrases, and analyze changes in their usage frequency over time. For example, we find that in 2019, the phrase “neural network” was used more often than “field data.” The word “shale” became less commonly used, but the term “unconventional” grew in frequency. An analysis of conference materials and metadata allows one to identify trends in a specific field of knowledge and predict its development in the near future.

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Section: Processing and Data Acquisition Methodsmentioning

confidence: 99%

Text Analysis Reveals Major Trends in Exploration Geophysics

Eltsov¹,

Yutkin²,

Patzek³

2020

Energies

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“…However, this is only the case in a truncated medium which is defined to be equal to the true medium above the boundary ∂D i , and is homogeneous below this depth. We calculate these functions using the iterative solution to the coupled Marchenko equations (Wapenaar et al, 2014) and we refer readers to Lomas and Curtis (2019) for an intuitive introduction and more details on this method.…”

Section: Marchenko Receiver Redatumingmentioning

confidence: 99%

Imaging vertical structures using Marchenko methods with vertical seismic-profile data

2020

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Marchenko methods use seismic data acquired at or near the surface of the earth to estimate seismic signals as if the receiver (now a virtual receiver) was at an arbitrary point inside the subsurface of the earth. This process is called redatuming, and it is central to subsurface imaging. Marchenko methods estimate the multiply scattered components of these redatumed signals, which is not the case for most other redatuming techniques that are based on single-scattering assumptions. As a result, images created using Marchenko redatumed signals contain a reduction in the artifacts that usually contaminate migrated seismic images due to improper handling of internal multiples. We exploit recent theoretical advances that enable virtual sources and virtual receivers to be placed at arbitrary points inside the subsurface as a means to incorporate vertical seismic profile (VSP) data into Marchenko methods. The advantage of including this type of data is that the additional acquisition boundary increases subsurface illumination, which in turn enables vertical interfaces and steeply dipping structures to be imaged. We develop this methodology using two synthetic data sets. The first is created using a simple variable density but constant velocity subsurface model. In this example, we find that our newly devised VSP Marchenko imaging methodology enables imaging of horizontal and vertical structures and that optimal results are achieved by combining these images with those created using standard Marchenko imaging. A second example demonstrates that the method can be applied to more realistic subsurface structures, in this case a modified version of the Marmousi 2 model. We determine the applicability of the methods to image fault structures with the final imaging result containing reduced contamination due to internal multiples and an improvement in the imaging of fault structures when compared to other standard imaging methods alone.

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“…Therefore, to solve for G + and G − we require a method that enables an estimate of the focusing functions to be obtained. An elegant algorithmic way to solve this problem is first described by Slob et al (2014) and Wapenaar et al (2014), discussions of the mathematical foundation of the algorithm are described by van der Neut et al (2015a), and an intuitive demonstration of how this method works is given by van der Neut et al (2015c), Cui et al (2018b) and Lomas & Curtis (2019). The algorithm is an iterative procedure which requires as input both an estimate of the reflectivity (R), and an estimate of the direct arrival between the chosen virtual receiver (location x i ) and the surface sources (denoted T d ).…”

Section: Theorymentioning

confidence: 99%

Marchenko methods in a 3-D world

Lomas

Curtis

2019

Geophysical Journal International

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SUMMARYMarchenko methods are a suite of geophysical techniques that convert seismograms of energy created by surface sources and measured by surface receivers into seismograms that would have been recorded by a virtual receiver at an arbitrary point inside the subsurface—an operation called redatuming. In principle these redatumed seismograms contain all contributions from direct, primary (singly-reflected) and multiply-reflected waves that would have been recorded by a real subsurface receiver, without requiring prior information about interfaces that generated the reflections. The potential of these methods for seismic imaging and redatuming has been demonstrated extensively in previous literature, but only using 1-D and 2-D Marchenko methods. There remain aspects of the methods that are poorly understood when applied in a 3-D world, so we investigate the application of Marchenko methods to 3-D data, subsurface structures and wavefields. We first show that for waves propagating in three dimensions, Marchenko methods can be applied to seismic data collected using both linear (so-called 2-D seismic) and areal (3-D seismic) acquisition arrays. However, for 2-D acquisition arrays the Marchenko workflow requires additional dimensionality correction factors to obtain accurate solutions, even in a subsurface that only varies with depth. Without these correction factors phase errors occur in redatumed Marchenko estimates; these errors propagate through the Marchenko algorithm and create depth errors in the Marchenko images. Furthermore, applying Marchenko methods to fully 3-D seismic wavefields recorded by linear (2-D seismic) arrays that contain out-of-plane reflections deteriorates surface-to-subsurface Green’s function estimates with spurious energy and resulting images are less accurate than those created using ‘conventional’ imaging methods. The application of fully 3-D Marchenko methods using data recorded on areal arrays solves both of the above problems, creating accurately redatumed wavefields and images with reduced artefact contamination. However, it appears that source–receiver spacing at most of $\lambda _A /4$ is required for accurate results using existing Marchenko methods, where λA is the dominant wavelength and in many real 3-D seismic acquisition scenarios this is impractical.

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An introduction to Marchenko methods for imaging

Cited by 32 publications

References 45 publications

Text Analysis Reveals Major Trends in Exploration Geophysics

Text Analysis Reveals Major Trends in Exploration Geophysics

Imaging vertical structures using Marchenko methods with vertical seismic-profile data

Marchenko methods in a 3-D world

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