Seismic Diffraction Imaging Research Articles

DiffraPy: An open-source Python software for seismic diffraction imaging

Seismic diffraction events, often overlooked as noise in conventional seismic imaging methods, contain valuable high-resolution information about subsurface structures and heterogeneities. Furthermore, the diffractive component of the wavefield is masked by the stronger reflection events. Although the literature presents innovative methods for separating diffracted events from the total wavefield, there are currently limited options of open-source alternatives in seismic diffraction processing and imaging. In this study, we introduce DiffraPy, an open-source Python package specifically designed for performing both conventional and diffraction-oriented migrations. The main workflow involves implementing an anti-stationary phase filter in the Kirchhoff migration for enhancing energy outside the Fresnel zone. Additionally, we propose using the semblance matrix obtained from the dip field calculation as an additional weight in conventional migration. The code provides functionality for forward modeling seismic data, allowing for new testing and experimentation. We demonstrate the general workflow of the code using a toy model and evaluate its capabilities on a synthetic salt model. In both cases, the program successfully suppressed the majority of reflected energy in the diffraction-oriented image. The final image highlights the responses of small lenses, discontinuities, and faults, providing valuable insights into the subsurface for interpretation. Despite the method sensitivity to variations in the correct velocity model, we demonstrate that our code is capable of imaging diffractors even when utilizing incorrect migration velocities of up to 5%. Our wavenumber analysis reveals the diffraction image preservation of smaller wavelengths, indicating higher resolution compared to conventional products. Future implementations may include extension to 3D datasets and improve the computational efficiency of our code. We expect our code to offer the geosciences community the first freely accessible and well-documented Python alternative for testing, reproducing, and exploring diffraction imaging examples.

Conditional Denoising Diffusion Probabilistic Model for Seismic Diffraction Separation and Imaging

Conditional Denoising Diffusion Probabilistic Model for Seismic Diffraction Separation and Imaging

The Paleozoic Hydrocarbon System in the Gotland Basin (Central Baltic Sea) Leaks

AbstractThe Baltic Basin is known for its numerous Paleozoic hydrocarbon reservoirs. There is published evidence that hydrocarbons are leaking from the seafloor, however, little is known about the hydrocarbon migration pathways from Paleozoic source and reservoir rocks toward the seafloor and their escape structures. To investigate these processes, we utilize a new set of multibeam, parametric sediment sub‐bottom profiler and 2D seismic reflection data. The integrated analysis of seismic profiles, diffraction imaging and bathymetric maps allow to identify a hydrocarbon migration system within Silurian and Devonian strata that consists of layer parallel and updip migration beneath sealing layers, migration across seals along faults, and seafloor escape structures in form of elongated depressions. The general migration trend is directed updip, from the Paleozoic reservoirs below the southeastern Baltic Sea toward the Gotland Depression in the northwest. The locations of the hydrocarbon escape structures at the seafloor and their elongated shape are mainly controlled by the regional geological setting of outcropping Paleozoic layers. In addition, iceberg scouring may have facilitated hydrocarbon migration through the Quaternary deposits. The description of this hydrocarbon migration system fills the gap between the known reservoirs and the observed hydrocarbon accumulations and seepages. With regard to potential Carbon Capture and Storage projects, the identification of this hydrocarbon migration system is of great importance, as potential storage sites may be leaking.

Separation and imaging of seismic diffractions using geometric mode decomposition

Seismic diffractions from small-scale discontinuities or inhomogeneities carry key geologic information and can provide high-resolution images of these objects. Because diffractions characterized by weak energy are easily masked by strong reflections, diffraction-enhancement processing is essential before subwavelength information detection. Therefore, a novel diffraction-separation method is developed that uses the Fourier-based geometric-mode decomposition (GMDF) algorithm to remove reflections and separate diffractions in the common-offset or poststack domain. The key idea of our method is that, in the frequency-wavenumber ( f- k) domain, strong reflections concentrate linearly along a certain dip direction, whereas weak diffractions are distributed over a wide range of wavenumbers owing to their variable dips in the time-space domain. The GMDF algorithm can effectively represent reflections with directional and linear geometric features by adaptively decomposing seismic data as a combination of the band-limited modes consisting of linear characteristics in the f- k domain. The alternating direction method of the multipliers algorithm is used to solve the GMDF optimization problem and obtain linear reflections. Because this method considers the energy sparsity property and linear geometric features of reflections in the f- k domain, kinematic and dynamic differences between reflections and diffractions are exploited to separate diffractions. Applied synthetic and field examples demonstrate the good performance of our method in removing strong reflections and separating weak diffractions, providing interpreters with detailed structural and stratigraphic information.

Reducing Drilling Hazard Risk in a Carbonate Environment Using Seismic Processing, Diffraction Imaging and Interpretation

Buried structural anomalies within carbonate depositional environments, such as karst sinkholes, impose significant dangers for borehole integrity and drilling equipment due to rapid changes in rock properties (from tight to the porous) potentially resulting in extensive mud loss, drill bit jamming and other complications. This often leads to delays in the well construction planning and sometimes to subsequent sidetrack drilling and a dramatic increase in costs. Thus, Paleo-karst localization, prior to well planning and construction, becomes a critical task for economic optimization. However, this is a non-trivial exercise due to the relatively small scale and size of karst type features and anomalies, which are at the limit of lateral resolution of most standard surface geophysical methods. In this paper, we introduce a methodology of karst prediction based on a combination of targeted 3D seismic processing and integration of the diffracted wavefield anomalies in addition to use of conventional seismic attributes. The presented approach has been proven to be efficient to detect karsts in a real oil field and can be deployed in other regions.

Derisking Offshore Windfarm Installation by Sub-Seafloor Boulder Detection Based on Dedicated Seismic Diffraction Imaging

In order to confront climate change and reach the ambitious goals set at COP 26, established renewable energy sources like wind and solar need to expand to new frontiers. For wind, the transition to offshore environments poses unique opportunities and challenges. While offshore wind farms promise more energy efficiency, their construction demands larger investments in foundations and infrastructure. Glacial movement that transported material over the various epochs has resulted in a liberal distribution of problematic boulders in exactly the kind of areas now proving ideal for the deployment of wind farm technology. This is especially evident in large stretches of the Baltic, North Sea and North Atlantic on the east coast of North America where boulders, carried south through glacial movements during the ice ages, pose significant hazards for the construction of new offshore infrastructure. To be able to carry out subsea construction work with reduced risk, a novel ultra-high-resolution (UHR) seismic measurement system has been developed by the Fraunhofer Institute for Wind Energy Systems IWES, Bremen, Germany, and the University of Bremen, Germany. The Manta Ray G1 that has been developed is specifically designed to detect and localize these small-scale objects in marine sediments with high accuracy using seismic diffraction imaging. As these boulders pose an obvious problem for the construction work it is the ability of the system to commit to dedicated object detection, e.g., for glacial boulders, integrated into a detailed ground model of the uppermost section of the subseafloor in challenging shallow-water regimes that offers a highly advantageous solution to the problem. The system uses a unique new survey methodology for the de-risking of offshore construction sites.

Diffraction Imaging of the Fractured Crystalline Basement, Lancaster Field, UK

In this paper, we demonstrate the application of seismic diffraction imaging technology to map the distribution of faults within Hurricane Energy’s operated, fractured basement fields, offshore West of Shetland. After the reprocessing of legacy 3D seismic data in 2018, it became apparent that the reflection seismic image had limited ability to image the intra-basement structure. Intra-basement imaging is crucial for understanding the distribution, frequency and geometry of intra-basement structures which directly influence production trends in fractured basement reservoirs. Diffraction imaging is a novel seismic processing technique that can produce high-resolution images of small-scale scattering subsurface events by extracting and focusing the diffractive component of the total wavefield to its subsurface origin. Analysis of the diffraction imaging seismic volume alongside well data and other seismic products can complement conventional seismic attributes and enhance the interpretational value of the seismic data. This paper shows how the intensity of the diffraction image varies from location to location across the Rona Ridge and is seen to have a strong, positive correlation with observed well productivity. As such, the application of this technology shows great promise to provide additional information for detailed analysis of Hurricane Energy’s fractured basement reservoirs and can facilitate new well placement and trajectory design.

3-D Seismic Diffraction Separation and Imaging Using the Local Rank-Reduction Method

3-D Seismic Diffraction Separation and Imaging Using the Local Rank-Reduction Method

Seismic Diffraction Imaging for Improved Coal Structure Detection by a Structure-Oriented Moving Average Error Filter

Instead of dismissing seismic diffractions as interfering noise and ignoring or suppressing them, they can be used to identify small geological discontinuities such as faults, dykes, and other features that act as small scatters in the subsurface. We describe a simple, but fast and effective, structure-oriented, moving average error filter (MAEF) applied to the neighboring traces to extract diffractions from time-stack reflection seismic data or diffractors from migrated seismic data. The filter estimates the reflections with the average values of the neighboring traces along the reflection dip direction, which can be computed by the gradients of seismic data. The difference between the input data (unmigrated or migrated) and the estimated reflections yields the diffractions. By identifying diffractions, small faults and other minor features that are difficult to detect using conventional seismic reflection processing can be enhanced and detected. The effectiveness of the proposed method for diffraction extraction is demonstrated by numerical models and by applying it to a 3D seismic survey data over a partially mined-out coal deposit.

A Probabilistic Approach to Seismic Diffraction Imaging

Abstract We propose and demonstrate a probabilistic method for imaging seismic diffractions based on path-integral imaging. Our approach uses oriented velocity continuation to produce a set of slope-decomposed diffraction images over a range of plausible migration velocities. Utilizing the assumption that each partial image in slope is independent enables us to construct an object resembling a probability field from the slope-decomposed images. That field may be used to create weights for each partial image in velocity corresponding to the likelihood of a correctly migrated diffraction occurring at a location within the seismic image for that migration velocity. Stacking these weighted partial images over velocity provides us with a path-integral seismic diffraction image created using probability weights. We illustrate the principles of the method on a simple toy model, show its robustness to noise on a synthetic, and apply it to a 2D field dataset from the Nankai Trough. We find that using the proposed approach creates diffraction images that enhance diffraction signal while suppressing noise, migration artifacts, remnant reflections, and other portions of the wavefield not corresponding to seismic diffraction relative to previously developed diffraction imaging methods, while simultaneously outputting the most likely migration velocity. The method is intended to be used on data which has already had much of the reflection energy removed using a method like plane-wave destruction. Although it suppresses residual reflection energy successfully, this suppression is less effective in the presence of strong reflections typically encountered in complete field data. The approach outlined in this paper is complimentary to existing data domain methods for diffraction extraction, and the probabilistic diffraction images it generates can supplement existing reflection and diffraction imaging methods by highlighting features that have a high likelihood of being diffractions and accentuating the geologically interesting objects in the subsurface that cause those features.

Seismic Diffraction Imaging to Characterize Mass‐Transport Complexes: Examples From the Gulf of Cadiz, South West Iberian Margin

AbstractMass‐transport complexes (MTCs) are often characterized by small‐scale discontinuous internal structure, such as slide blocks, rough interfaces, faults, and truncated strata. Seismic images may not properly resolve such structure because seismic reflections are fundamentally limited in lateral resolution by the source bandwidth. The relatively weak seismic diffractions, instead, encode information on subwavelength‐scale structure, with superior illumination. In this paper, we compare diffraction imaging to conventional, full‐wavefield seismic imaging to characterize MTCs. We apply a seismic diffraction imaging workflow based on plane‐wave destruction filters to two 2D marine multichannel seismic profiles from the Gulf of Cadiz. We observe that MTCs generate a large amount of diffracted energy relative to the unfailed confining sediments. The diffraction images show that some of this energy is localized along existing discontinuities imaged by the full‐wavefield images. We demonstrate that, in combination with full‐wavefield images, diffraction images can be utilized to better discriminate the lateral extent of MTCs, particularly for thin bodies. We suggest that diffraction images may be a more physically correct alternative to commonly used seismic discontinuity attributes derived from full‐wavefield images. Finally, we outline an approach to utilize the out‐of‐plane diffractions generated by the 3D structure of MTCs, normally considered a nuisance in 2D seismic processing. We use a controlled synthetic test and a real‐data example to show that under certain conditions these out‐of‐plane diffractions might be used to constrain the minimum width of MTCs from single 2D seismic profiles.

Separation and imaging of seismic diffractions using a localized rank-reduction method with adaptively selected ranks

Seismic diffractions are weak seismic events hidden within the more dominant reflection events in a seismic profile. Separating diffraction energy from the poststack seismic profiles can help infer the subsurface discontinuities that generate the diffraction events. The separated seismic diffractions can be migrated with a traditional seismic imaging method or a specifically designed migration method to highlight the diffractors, that is, the diffraction image. Traditional diffraction separation methods based on the underlying plane-wave assumption are limited by either the inaccurate slope estimation or the plane-wave assumption of the plane-wave destruction filter and thus will cause reflection leakage into the separated diffraction profile. The leaked reflection energy will deteriorate the resolution of the subsequent diffraction imaging result. We have adopted a new diffraction separation method based on a localized rank-reduction (LRR) method. The LRR method assumes the reflection events to be locally low-rank and the diffraction energy can be separated by a rank-reduction operation. Compared to the global rank-reduction method, the LRR method is more constrained in selecting the rank and is free of separation artifacts. We use a carefully designed synthetic example to demonstrate that the LRR method can help separate the diffraction energy from a poststack seismic profile with kinematically and dynamically accurate performance.

When There Is No Offset: A Demonstration of Seismic Diffraction Imaging and Depth‐Velocity Model Building in the Southern Aegean Sea

AbstractA vast majority of marine geological research is based on academic seismic data collected with single‐channel systems or short‐offset multichannel seismic cables, which often lack reflection moveout for conventional velocity analysis. Consequently, our understanding of Earth processes often relies on seismic time sections, which hampers quantitative analysis in terms of depth, formation thicknesses, or dip angles of faults. In order to overcome these limitations, we present a robust diffraction extraction scheme that models and adaptively subtracts the reflected wavefield from the data. We use diffractions to estimate insightful wavefront attributes and perform wavefront tomography to obtain laterally resolved seismic velocity information in depth. Using diffraction focusing as a quality control tool, we perform an interpretation‐driven refinement to derive a geologically plausible depth‐velocity model. In a final step, we perform depth migration to arrive at a spatial reconstruction of the shallow crust. Further, we focus the diffracted wavefield to demonstrate how these diffraction images can be used as physics‐guided attribute maps to support the identification of faults and unconformities. We demonstrate the potential of this processing scheme by its application to a seismic line from the Santorini Amorgos Tectonic Zone, located on the Hellenic Volcanic Arc, which is notorious for its catastrophic volcanic eruptions, earthquakes, and tsunamis. The resulting depth image allows a refined fault pattern delineation and, for the first time, a quantitative analysis of the basin stratigraphy. We conclude that diffraction‐based data analysis has a high potential, especially when the acquisition geometry of seismic data does not allow conventional velocity analysis.

Seismic diffraction imaging for improved coal structure detection in complex geological environments

To provide a “no major surprises” guarantee of coal seam conditions, reflection seismic surveying is often used for delineation of faults and dykes that have the potential to disrupt underground coal mining operations. Although reflection seismic methods are usually effective for locating faults with throws greater than 5-10 m for 2D and 2-5 m for 3D seismic data, detection of faults with smaller throws, shears and dykes with widths of a few metres remains a challenge to seismic methods.Instead of ignoring or suppressing diffractions by conventional seismic data processing, it has been demonstrated that diffractions contain valuable information, which can be used for identification of subtle coal seam structures. In this paper, we describe a moving average error filter (MAEF) applied in the neighbouring traces to extract diffractions from post-stack reflection seismic data. The filter estimates the reflections with the average values of the neighbouring traces along the reflection direction or dip, which can be computed by the gradients of seismic data. The difference (or error) between the original data and the estimated reflections, yields the diffractions. By identifying diffractions, small faults and other minor features that are difficult to detect using conventional seismic reflection processing can be detected. Numerical and real data examples are used to illustrate the effectiveness of the proposed method in coal seam structure detection by extracting diffractions from reflection seismic data in a relatively complex geological environment.

A new scheme for velocity analysis and imaging of diffractions

Seismic diffractions are the responses of small-scale inhomogeneities or discontinuous geological features, which play a vital role in the exploitation and development of oil and gas reservoirs. However, diffractions are generally ignored and considered as interference noise in conventional data processing. In this paper, a new scheme for velocity analysis and imaging of seismic diffractions is proposed. Two steps compose of this scheme in our application. First, the plane-wave destruction method is used to separate diffractions from specular reflections in the prestack domain. Second, in order to accurately estimate migration velocity of the diffractions, the time-domain dip-angle gathers are derived from a Kirchhoff-based angle prestack time migration using separated diffractions. Diffraction events appear flat in the dip-angle gathers when imaged above the diffraction point with selected accurate migration velocity for diffractions. The selected migration velocity helps to produce the desired prestack imaging of diffractions. Synthetic and field examples are applied to test the validity of the new scheme. The diffraction imaging results indicate that the proposed scheme for velocity analysis and imaging of diffractions can provide more detailed information about small-scale geologic features for seismic interpretation.

Unconventional-Reservoir Characterization With Azimuthal Seismic Diffraction Imaging

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 2695232, “Unconventional-Reservoir Characterization With Azimuthal Seismic Diffraction Imaging,” by Dmitrii Merzlikin, Sergey Fomel, Xinming Wu, and Mason Phillips, The University of Texas at Austin, prepared for the 2017 Unconventional Resources Technology Conference, Austin, Texas, USA, 24–26 July. The paper has not been peer reviewed. The complete paper proposes an azimuthal plane-wave-destruction (AzPWD) seismic-diffraction-imaging work flow to efficiently emphasize small-scale features associated with subsurface discontinuities such as faults, channel edges, and fracture swarms and to determine their orientation by properly accounting for edge-diffraction phenomena. The work flow is applied to characterize an unconventional tight-gas-sand reservoir in the Cooper Basin in Western Australia. Extracted orientations of edges provide valuable additional information, which can be used by the interpreter to locate finer-scale features and distinguish them from noise. Introduction Unconventional reservoirs may exhibit high structural variability, which is difficult to characterize with a discrete wells network. 3D reflection seismology allows the extraction of additional information about the subsurface with significantly denser spatial sampling intervals. However, conventional images of the subsurface have low spatial resolution and are dominated by continuous and smooth reflections, which carry the information associated with only large-scale heterogeneities. Diffraction images are more capable than conventional reflection images in emphasizing small-scale features associated with subsurface discontinuities. Many studies employ diffraction images as a source of additional information for interpretation. Past work has proposed an AzPWD work flow, which extends a plane-wave destruction diffraction imaging framework to account for edge-diffraction orientation and allows efficient extraction of these orientations on the basis of scanning of different azimuths. Two modifications to the previously proposed AzPWD work flow are considered in this paper. Edge-diffraction-orientation determination is performed through a structure-tensor estimation based on PWD. A PWD-based structure tensor allows determination of edge-diffraction orientation from two volumes corresponding with PWDs applied in inline and crossline directions. Thus, no scanning over the PWD azimuth is required. Because reflection/diffraction separation is performed on the basis of the PWD filter in the data domain, the approach pertains to a diffraction imaging framework. The structure-tensor estimation approach has been applied previously in the image space on the basis of image gradients, the highest contribution to which is connected with strong and coherent reflection events masking diffractions. The second improvement presented by the AzPWD work flow is based on additional smoothing along the edge orientation, which makes the diffraction/ reflection-separation operator equivalent to the structure-oriented Sobel filter.

Examples of seismic diffraction imaging from the Austin Chalk and Eagle Ford Shale, Maverick Basin, South Texas

Diffraction events are recorded along with reflection data during seismic acquisition. However, after processing, final migrated stack data are devoid of diffraction events, which have been collapsed to discrete points, smoothed out, and overshadowed by reflection events. Thus, diffraction events that ought to be available for analysis of the subsurface are lost.In this study, we extract diffractions from 3D stack and then build a 3D diffraction volume that not only images faults but also contains amplitude information used to examine lithological composition in fault zones within the Austin Chalk and Eagle Ford Shale in South Texas. We then transform the diffraction data into amplitude envelope volume. This seismic attribute, together with clay volume (Vclay) data, is extracted along interpreted horizons and fault planes. Cross plots between seismic attributes and Vclay show that Vclay increases with increasing diffraction energy. In addition, we observe that the higher the diffraction energies, the higher the fluid saturation, suggesting higher impedance contrast at diffraction points. Furthermore, cross plots between instantaneous dominant frequencies extracted from the diffraction-image volume and amplitude envelope show that within the hydrocarbon-saturated zones, the dominant frequency is approximately constant and in the low-frequency range between 25 and 33 Hz. However, outside the hydrocarbon zones, the dominant frequency increases as the amplitude envelope decreases. Maps of instantaneous dominant frequency extracted from the upper and lower Eagle Ford Shale reveal that areal distribution of low-dominant-frequency zones is coincident with high diffraction energy and hydrocarbon saturation. Based on the foregoing, we conclude that by analyzing diffraction data, it is possible to infer likely sediment variation and hydrocarbon sweet spots within the Eagle Ford Shale and other shale resource plays.

Enhancing the detection of small coal structures by seismic diffraction imaging

Faults are the most important geological structures that need to be detected in any modern underground coal mining project. Even a fault with a throw of a few metres can create safety issues and lead to costly delays in mine production. While seismic surveys are usually successful at locating faults with throws greater than 5-10m, reliable techniques for resolving more subtle faults, dykes and other minor features are yet to be developed.In seismic data, there are two types of seismic energy signatures that can be used for subsurface imaging: specular reflections and diffractions. Specular reflections are created by relatively smooth surfaces between layers of differing impedance contrasts such as at coal-rock interfaces. Specular reflections are used in conventional seismic reflection surveys. Diffractions are generated by local discontinuities caused by surface roughness, faults, dykes and fractures. In this paper, we describe the use of a moving average error filter which, along with a process of reflection event flattening for accommodation of dips and undulations of coal seam reflections, can be used to effectively extract diffraction signals from post-stack reflection seismic data. By identifying diffractions, small faults and other minor features that are elusive using conventional seismic reflection processing can be detected, suggesting that diffraction imaging may be a superior method to seismic reflection imaging. Both synthetic and real (2D and 3D) coal seismic data are used to illustrate the feasibility of diffraction imaging for small fault detection. It is demonstrated from synthetic examples that the extracted diffractions can be used to detect faults with a throw of 1m while a real data example shows that it is possible to detect igneous dykes with widths of just 4m.

Diffraction imaging and time-migration velocity analysis using oriented velocity continuation

We perform seismic diffraction imaging and time-migration velocity analysis by separating diffractions from specular reflections and decomposing them into slope components. We image the slope components using migration velocity extrapolation in time-space-slope coordinates. The extrapolation is described by a convection-type partial differential equation and implemented in a highly parallel manner in the Fourier domain. Synthetic and field data experiments show that the proposed algorithms are able to detect accurate time-migration velocities by measuring the flatness of diffraction events in slope gathers for single- and multiple-offset data.

Analytical path-summation imaging of seismic diffractions

Diffraction imaging aims to emphasize small subsurface objects, such as faults, fracture swarms, and channels. Similar to classical reflection imaging, velocity analysis is crucially important for accurate diffraction imaging. Path-summation migration provides an imaging method that produces an image of the subsurface without picking a velocity model. Previous methods of path-summation imaging involve a discrete summation of the images corresponding to all possible migration velocity distributions within a predefined integration range and thus involve a significant computational cost. We have developed a direct analytical formula for path-summation imaging based on the continuous integration of the images along the velocity dimension, which reduces the cost to that of only two fast Fourier transforms. The analytic approach also enabled automatic migration velocity extraction from diffractions using a double path-summation migration framework. Synthetic and field data examples confirm the efficiency of the proposed techniques.