A comparison of diffraction imaging to incoherence and curvature

Tyiasning, Stephanie; Merzlikin, Dmitrii; Cooke, Dennis; Fomel, Sergey

doi:10.1190/tle35010086.1

Cited by 26 publications

(3 citation statements)

References 19 publications

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“…Consequently, there exist first attempts to use diffraction imaging as a robust alternative for seismic interpretation (e.g. Tsingas et al, 2011;Sturzu et al, 2014;Schoepp et al, 2014;Decker et al, 2014;Tyiasning et al, 2016;Dell et al, 2018).…”

Section: Diffraction In Interpretationmentioning

confidence: 99%

An introduction to seismic diffraction

Schwarz

2019

Advances in Geophysics

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Despite its unique properties the diffracted seismic wavefield is still rarely exploited in common practice. Although the first works on seismic diffraction date back at least as far as the 1950s, a first rigorous theoretical framework for diffraction imaging only evolved decades later and many important questions still remain unanswered until the present day. While this comparably slow progression can partly be explained by the lack of densely sampled high quality recordings, recent advances in acquisition and dedicated processing suggest we might be at the door step to a paradigm shift in which seismic diffraction could play an important role. Despite the fact that most major progress-in terms of data acquisition and processing-has been achieved for the reflected wavefield, upon closer inspection it becomes obvious that the concept of diffraction is deeply ingrained in migration-type seismic imaging. With the aim of complementing existing contributions on the topic, this chapter is an attempt to provide an intuitive introduction to the process of seismic diffraction. Discussed are the deep conceptual roots in optics, physical links to the Kirchhoff integral as well as diffraction types and their importance in different contexts of application. By means of controlled synthetic and academic as well as industry-scale field data examples, I suggest a simple integrated framework for non-invasive diffraction separation and high-resolution imaging, which remains computationally affordable and can be reproduced by the reader. Different applications suggest that the faint diffracted background wavefield is surprisingly rich and, once it is given a voice, it announces highly resolved features such as faults, fractures, and erosional unconformities, which remain notoriously hard to image conventionally. Extending the dominant theme of high-resolution seismic imaging, I illustrate how the superior illumination due to the uniform radiation of diffraction carries the additional potential for drastically reduced acquisitions and discuss the possibility of a systematic extraction of inter-scatterer traveltimes from coda waves.

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Section: Diffraction In Interpretationmentioning

confidence: 99%

An introduction to seismic diffraction

Schwarz

2019

Advances in Geophysics

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“…The PWD filtering method can effectively eliminate artifacts and retain more diffraction energy. Therefore, it has been successfully applied to several 3D field datasets (Burnett et al, 2015;Tyiasning et al, 2016). Another advantage of the PWD filtering method is that the separated diffraction can be directly used for pre-stack migration, avoiding complex data processing.…”

Section: Introductionmentioning

confidence: 99%

Diffraction Extraction and Least-Squares Reverse Time Migration Imaging for the Fault-Karst Structure With Adaptive Sampling Strategy

et al. 2022

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The ultra-deep fault-karst structure discovered in the Tarim Basin in Western China is a fractured-vuggy carbonate reservoir with great potential for development. The diffraction generated by fractures, small-scale caves and vugs is often used for reservoir identification and seismic interpretation. Since the diffraction is much weaker than the reflection, it is difficult to separate the diffraction from the full wavefield. We use a plane-wave destruction (PWD) filter to extract the diffraction from the full data. In order to obtain a high-accuracy and amplitude-preserving imaging profile, we use the least-squares reverse time migration (LSRTM) method to image the separated diffraction. The large amount of calculation is the most challenging problem of the LSRTM algorithm. In view of this, we develop an adaptive sampling strategy to improve computing efficiency and reduce memory requirement. We use a fault model, a vugs-fractures model, and a fault-karst model to demonstrate the effectiveness and practicability of the proposed method. The numerical examples show that the proposed method can enhance the imaging resolution of the fault-karst structure and save computing cost without losing accuracy. In addition, a test on field data processing demonstrates the advantages of our algorithm.

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“…; Tyiasning et al . ). However, diffractions are usually recorded in the data with considerably weaker amplitude compared to reflections, which makes their identification difficult.…”

Section: Introductionmentioning

confidence: 99%

Diffraction imaging by prestack reverse‐time migration in the dip‐angle domain

Dafni

Symes

2017

Geophysical Prospecting

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Prestack image volumes may be decomposed into specular and non‐specular parts by filters defined in the dip‐angle domain. For space‐shift extended image volumes, the dip‐angle decomposition is derived via local Radon transform in depth and midpoint coordinates, followed by an averaging over space‐shifts. We propose to employ prestack space‐shift extended reverse‐time migration and dip‐angle decomposition for imaging small‐scale structural elements, considered as seismic diffractors, in models with arbitrary complexity. A suitable design of a specularity filter in the dip‐angle domain rejects the dominant reflectors and enhances diffractors and other non‐specular image content. The filter exploits a clear discrimination in dip between specular reflections and diffractions. The former are stationary at the specular dip, whereas the latter are non‐stationary without a preferred dip direction. While the filtered image volume features other than the diffractor images (for example, noise and truncation artefacts are also present), synthetic and field data examples suggest that diffractors tend to dominate and are readily recognisable. Averaging over space‐shifts in the filter construction makes the reflectors‧ rejection robust against migration velocity errors. Another consequence of the space‐shift extension and its angle‐domain transforms is the possibility of exploring the image in a multiple set of common‐image gathers. The filtered diffractions may be analysed simultaneously in space‐shift, scattering‐angle, and dip‐angle image gathers by means of a single migration job. The deliverables of our method obviously enrich the processed material on the interpreter's desk. We expect them to further supplement our understanding of the Earth's interior.

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A comparison of diffraction imaging to incoherence and curvature

Cited by 26 publications

References 19 publications

An introduction to seismic diffraction

An introduction to seismic diffraction

Diffraction Extraction and Least-Squares Reverse Time Migration Imaging for the Fault-Karst Structure With Adaptive Sampling Strategy

Diffraction imaging by prestack reverse‐time migration in the dip‐angle domain

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