78 found
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  1.  44
    Multispectral Coherence.Fangyu Li, Jie Qi, Bin Lyu & Kurt J. Marfurt - 2018 - Interpretation: SEG 6 (1):T61-T69.
    Seismic coherence is a routine measure of seismic reflection similarity for interpreters seeking structural boundary and discontinuity features that may be not properly highlighted on original amplitude volumes. One mostly wishes to use the broadest band seismic data for interpretation. However, because of thickness tuning effects, spectral components of specific frequencies can highlight features of certain thicknesses with higher signal-to-noise ratio than others. Seismic stratigraphic features may be buried in the full-bandwidth data, but can be “lit up” at certain spectral (...)
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  2.  33
    A Comparison of Classification Techniques for Seismic Facies Recognition.Tao Zhao, Vikram Jayaram, Atish Roy & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (4):SAE29-SAE58.
    During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time slice. To address this problem, several seismic facies classification algorithms including [Formula: see text]-means, self-organizing maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural networks have been successfully used to extract features of geologic interest from multiple volumes. Although (...)
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  3.  23
    Characterizing a Turbidite System in Canterbury Basin, New Zealand, Using Seismic Attributes and Distance-Preserving Self-Organizing Maps.Tao Zhao, Jing Zhang, Fangyu Li & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (1):SB79-SB89.
    Recent developments in seismic attributes and seismic facies classification techniques have greatly enhanced the capability of interpreters to delineate and characterize features that are not prominent in conventional 3D seismic amplitude volumes. The use of appropriate seismic attributes that quantify the characteristics of different geologic facies can accelerate and partially automate the interpretation process. Self-organizing maps are a popular seismic facies classification tool that extract similar patterns embedded with multiple seismic attribute volumes. By preserving the distance in the input data (...)
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  4.  38
    Brittleness Evaluation of Resource Plays by Integrating Petrophysical and Seismic Data Analysis.Bo Zhang, Tao Zhao, Xiaochun Jin & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (2):T81-T92.
    The main considerations for well planning and hydraulic fracturing in unconventional resources plays include the amount of total organic carbon and how much hydrocarbon can be extracted. Brittleness is the direct measurement of a formation about the ability to create avenues for hydrocarbons when applying hydraulic fracturing. Brittleness can be directly estimated from laboratory stress-strain measurements, rock-elastic properties, and mineral content analysis using petrophysical analysis on well logs. However, the estimated brittleness using these methods only provides “cylinder” estimates near the (...)
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  5.  29
    Estimation of Total Organic Carbon and Brittleness Volume.Sumit Verma, Tao Zhao, Kurt J. Marfurt & Deepak Devegowda - 2016 - Interpretation: SEG 4 (3):T373-T385.
    The Barnett Shale in the Fort Worth Basin is one of the most important resource plays in the USA. The total organic carbon and brittleness can help to characterize a resource play to assist in the search for sweet spots. Higher TOC or organic content are generally associated with hydrocarbon storage and with rocks that are ductile in nature. However, brittle rocks are more amenable to fracturing with the fractures faces more resistant to proppant embedment. Productive intervals within a resource (...)
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  6.  23
    Pitfalls and Limitations in Seismic Attribute Interpretation of Tectonic Features.Kurt J. Marfurt & Tiago M. Alves - 2015 - Interpretation: SEG 3 (1):SB5-SB15.
    Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small (...)
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  7.  19
    Fault Damage Zone at Subsurface: A Case Study Using 3D Seismic Attributes and a Clay Model Analog for the Anadarko Basin, Oklahoma.Zonghu Liao, Hui Liu, Zheng Jiang, Kurt J. Marfurt & Ze’ev Reches - 2017 - Interpretation: SEG 5 (2):T143-T150.
    Using 3D seismic attributes and the support of a clay model that served as an analog, we mapped and analyzed a 32 km long, north–south-striking, right-lateral fault in the Woodford Shale, Anadarko Basin, Oklahoma, USA. Volumetric coherence, dip azimuth, and curvature delineated an approximately 1.5 km wide damage zone with multiple secondary faults, folds, and flexures. The clay analog enabled us to identify these features as belonging to a complex transpressional Riedel structure. We also suggest that the damage zone contains (...)
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  8.  10
    Independent Component Analysis for Reservoir Geomorphology and Unsupervised Seismic Facies Classification in the Taranaki Basin, New Zealand.David Lubo-Robles & Kurt J. Marfurt - 2019 - Interpretation 7 (3):SE19-SE42.
    During the past two decades, the number of volumetric seismic attributes has increased to the point at which interpreters are overwhelmed and cannot analyze all of the information that is available. Principal component analysis is one of the best-known multivariate analysis techniques that decompose the input data into second-order statistics by maximizing the variance, thus obtaining mathematically uncorrelated components. Unfortunately, projecting the information in the multiple input data volumes onto an orthogonal basis often mixes rather than separates geologic features of (...)
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  9.  15
    Attribute Selection in Seismic Facies Classification: Application to a Gulf of Mexico 3D Seismic Survey and the Barnett Shale.Yuji Kim, Robert Hardisty & Kurt J. Marfurt - 2019 - Interpretation 7 (3):SE281-SE297.
    Automated seismic facies classification using machine-learning algorithms is becoming more common in the geophysics industry. Seismic attributes are frequently used as input because they may express geologic patterns or depositional environments better than the original seismic amplitude. Selecting appropriate attributes becomes a crucial part of the seismic facies classification analysis. For unsupervised learning, principal component analysis can reduce the dimensions of the data while maintaining the highest variance possible. For supervised learning, the best attribute subset can be built by selecting (...)
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  10.  13
    Convolutional Neural Networks as Aid in Core Lithofacies Classification.Rafael Pires de Lima, Fnu Suriamin, Kurt J. Marfurt & Matthew J. Pranter - 2019 - Interpretation 7 (3):SF27-SF40.
    Artificial intelligence methods have a very wide range of applications. From speech recognition to self-driving cars, the development of modern deep-learning architectures is helping researchers to achieve new levels of accuracy in different fields. Although deep convolutional neural networks have reached or surpassed human-level performance in image recognition tasks, little has been done to transport this new image classification technology to geoscientific problems. We have developed what we believe to be the first use of CNNs to identify lithofacies in cores. (...)
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  11.  14
    Seismic Expression and Geomorphology of Igneous Bodies: A Taranaki Basin, New Zealand, Case Study.Lennon Infante-Paez & Kurt J. Marfurt - 2017 - Interpretation: SEG 5 (3):SK121-SK140.
    Very little research has been done on volcanic rocks by the oil industry due to the misconception that these rocks cannot be “good reservoirs.” However, in the past two decades, significant quantities of hydrocarbons have been produced from volcanic rocks in China, New Zealand, and Argentina. In frontier basins, volcanic piles are sometimes misinterpreted to be hydrocarbon anomalies and/or carbonate buildups. Unlike clastic and carbonate systems, the 3D seismic geomorphology of igneous systems is only partially documented. We have integrated 3D (...)
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  12.  15
    Multispectral Coherence: Which Decomposition Should We Use?Bin Lyu, Jie Qi, Fangyu Li, Ying Hu, Tao Zhao, Sumit Verma & Kurt J. Marfurt - 2020 - Interpretation 8 (1):T115-T129.
    Seismic coherence is commonly used to delineate structural and stratigraphic discontinuities. We generally use full-bandwidth seismic data to calculate coherence. However, some seismic stratigraphic features may be buried in this full-bandwidth data but can be highlighted by certain spectral components. Due to thin-bed tuning phenomena, discontinuities in a thicker stratigraphic feature may be tuned and thus better delineated at a lower frequency, whereas discontinuities in the thinner units may be tuned and thus better delineated at a higher frequency. Additionally, whether (...)
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  13.  12
    Multispectral, Multiazimuth, and Multioffset Coherence Attribute Applications.Satinder Chopra & Kurt J. Marfurt - 2019 - Interpretation 7 (2):SC21-SC32.
    The coherence attribute computation is typically carried out as a poststack application on 3D prestack migrated seismic data volumes. However, since its inception, interpreters have applied coherence to band-pass-filtered data, azimuthally limited stacks, and offset-limited stacks to enhance discontinuities seen at specific frequencies, azimuths, and offsets. The limitation of this approach is the multiplicity of coherence volumes. Of the various coherence algorithms that have evolved over the past 25 years, the energy ratio coherence computation stands apart from the others, being (...)
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  14.  40
    Seismic Attenuation Attributes with Applications on Conventional and Unconventional Reservoirs.Fangyu Li, Sumit Verma, Huailai Zhou, Tao Zhao & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (1):SB63-SB77.
    Seismic attenuation, generally related to the presence of hydrocarbon accumulation, fluid-saturated fractures, and rugosity, is extremely useful for reservoir characterization. The classic constant attenuation estimation model, focusing on intrinsic attenuation, detects the seismic energy loss because of the presence of hydrocarbons, but it works poorly when spectral anomalies exist, due to rugosity, fractures, thin layers, and so on. Instead of trying to adjust the constant attenuation model to such phenomena, we have evaluated a suite of seismic spectral attenuation attributes to (...)
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  15.  13
    Characterizing a Mississippian Tripolitic Chert Reservoir Using 3D Unsupervised and Supervised Multiattribute Seismic Facies Analysis: An Example From Osage County, Oklahoma.Atish Roy, Benjamin L. Dowdell & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (2):SB109-SB124.
    Seismic interpretation is based on the identification of reflector configuration and continuity, with coherent reflectors having a distinct amplitude, frequency, and phase. Skilled interpreters may classify reflector configurations as parallel, converging, truncated, or hummocky, and use their expertise to identify stratigraphic packages and unconformities. In principal, a given pattern can be explicitly defined as a combination of waveform and reflector configuration properties, although such “clustering” is often done subconsciously. Computer-assisted classification of seismic attribute volumes builds on the same concepts. Seismic (...)
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  16.  21
    Constraining Self-Organizing Map Facies Analysis with Stratigraphy: An Approach to Increase the Credibility in Automatic Seismic Facies Classification.Tao Zhao, Fangyu Li & Kurt J. Marfurt - 2017 - Interpretation: SEG 5 (2):T163-T171.
    Pattern recognition-based seismic facies analysis techniques are commonly used in modern quantitative seismic interpretation. However, interpreters often treat techniques such as artificial neural networks and self-organizing maps as a “black box” that somehow correlates a suite of attributes to a desired geomorphological or geomechanical facies. Even when the statistical correlations are good, the inability to explain such correlations through principles of geology or physics results in suspicion of the results. The most common multiattribute facies analysis begins by correlating a suite (...)
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  17.  19
    Techniques and Best Practices in Multiattribute Display.Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (1):B1-B23.
    All color monitors display images by mixing red, green, and blue components. These RGB components can be defined mathematically in terms of hue, lightness, and saturation components. A fourth alpha-blending component provides a means to corender multiple images. Most, but not all, modern commercial interpretation workstation software vendors provide multiattribute display tools using an opacity model. A smaller subset of vendors provide tools to interactively display two or three attributes using HLS, CMY, and RGB color models. I evaluated a technique (...)
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  18.  9
    Generative Topographic Mapping for Seismic Facies Estimation of a Carbonate Wash, Veracruz Basin, Southern Mexico.Atish Roy, Araceli S. Romero-Peláez, Tim J. Kwiatkowski & Kurt J. Marfurt - 2014 - Interpretation: SEG 2 (1):SA31-SA47.
    Seismic facies estimation is a critical component in understanding the stratigraphy and lithology of hydrocarbon reservoirs. With the adoption of 3D technology and increasing survey size, manual techniques of facies classification have become increasingly time consuming. Besides, the numbers of seismic attributes have increased dramatically, providing increasingly accurate measurements of reflector morphology. However, these seismic attributes add multiple “dimensions” to the data greatly expanding the amount of data to be analyzed. Principal component analysis and self-organizing maps are popular techniques to (...)
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  19.  13
    Display and Enhancement of Volumetric Fault Images.Gabriel Machado, Abdulmohsen Alali, Bryce Hutchinson, Oluwatobi Olorunsola & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (1):SB51-SB61.
    Fault picking is a critical, but human-labor-intensive component of seismic interpretation. In a bid to improve fault imaging in seismic data, we have applied a directional Laplacian of a Gaussian operator to sharpen fault features within a coherence volume. We computed an [Formula: see text] matrix of the second moment tensor distance-weighted coherence values that fell within a 3D analysis window about each voxel. The eigenvectors of this matrix defined the orientation of planar discontinuities, whereas the corresponding eigenvalues determined whether (...)
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  20.  32
    Improving the Quality of Prestack Inversion by Prestack Data Conditioning.Bo Zhang, Deshuang Chang, Tengfei Lin & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (1):T5-T12.
    Prestack seismic inversion techniques provide valuable information of rock properties, lithology, and fluid content for reservoir characterization. The confidence of inverted results increases with increasing incident angle of seismic gathers. The most accurate result of simultaneous prestack inversion of P-wave seismic data is P-impedance. S-impedance estimation becomes reliable with incident angles approaching 30°, whereas density evaluation becomes reliable with incident angles approaching 45°. As the offset increases, we often encounter “hockey sticks” and severe stretch at large offsets. Hockey sticks and (...)
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  21.  44
    Vector Correlation of Amplitude Variation with Azimuth and Curvature in a Post-Hydraulic-Fracture Barnett Shale Survey.Shiguang Guo, Sumit Verma, Qing Wang, Bo Zhang & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (1):SB23-SB35.
    Knowledge of induced fractures can help to evaluate the success of reservoir stimulation. Seismic P-waves through fracturing media can exhibit azimuthal variation in traveltime, amplitude, and thin-bed tuning, so amplitude variation with azimuth can be used to evaluate the hydraulic-fracturing-caused anisotropy. The Barnett Shale of the Fort Worth Basin was the first large-scale commercial shale gas play. We have analyzed two adjacent Barnett Shale seismic surveys: one acquired before hydraulic fracturing and the other acquired after hydraulic fracturing by more than (...)
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  22.  4
    Exhaustive Probabilistic Neural Network for Attribute Selection and Supervised Seismic Facies Classification.David Lubo-Robles, Thang Ha, Sivaramakrishnan Lakshmivarahan, Kurt J. Marfurt & Matthew J. Pranter - 2021 - Interpretation 9 (2):T421-T441.
    Machine learning algorithms, such as principal component analysis, independent component analysis, self-organizing maps, and artificial neural networks, have been used by geoscientists to not only accelerate the interpretation of their data, but also to provide a more quantitative estimate of the likelihood that any voxel belongs to a given facies. Identifying the best combination of attributes needed to perform either supervised or unsupervised ML tasks continues to be the most-asked question by interpreters. In the past decades, stepwise regression and genetic (...)
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  23.  8
    Resolving Subtle Stratigraphic Features Using Spectral Ridges and Phase Residues.Oswaldo Davogustto, Marcílio Castro de Matos, Carlos Cabarcas, Toan Dao & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (1):SA93-SA108.
    Seismic interpretation is dependent on the quality and resolution of seismic data. Unfortunately, seismic amplitude data are often insufficient for detailed sequence stratigraphy interpretation. We reviewed a method to derive high-resolution seismic attributes based upon complex continuous wavelet transform pseudodeconvolution and phase-residue techniques. The PD method is based upon an assumption of a blocky earth model that allowed us to increase the frequency content of seismic data that, for our data, better matched the well log control. The phase-residue technique allowed (...)
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  24.  25
    Noise Suppression of Time-Migrated Gathers Using Prestack Structure-Oriented Filtering.Bo Zhang, Tengfei Lin, Shiguang Guo, Oswaldo E. Davogustto & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (2):SG19-SG29.
    Prestack seismic analysis provides information on rock properties, lithology, fluid content, and the orientation and intensity of anisotropy. However, such analysis demands high-quality seismic data. Unfortunately, noise is always present in seismic data even after careful processing. Noise in the prestack gathers may not only contaminate the seismic image, thereby lowering the quality of seismic interpretation, but it may also bias the seismic prestack inversion for rock properties, such as acoustic- and shear-impedance estimation. Common postmigration data conditioning includes running window (...)
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  25.  18
    Identification of Brittle/Ductile Areas in Unconventional Reservoirs Using Seismic and Microseismic Data: Application to the Barnett Shale.Roderick Perez Altamar & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (4):T233-T243.
    Brittleness in unconventional reservoirs is mainly controlled by mineralogy, and it increases with quartz and dolomite content, whereas an increase in the clay content represents an increase in ductility. To generate regional brittleness maps, we have correlated the mineralogy-based brittleness index to elastic parameters measured from well logs. This correlation can then be used to predict the brittleness from surface seismic elastic parameter estimates of [Formula: see text] and [Formula: see text]. We applied the workflow to a 3D seismic survey (...)
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  26.  21
    Pitfalls in Seismic Processing: An Application of Seismic Modeling to Investigate Acquisition Footprint.Marcus P. Cahoj, Sumit Verma, Bryce Hutchinson & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (2):SG1-SG9.
    The term acquisition footprint is commonly used to define patterns in seismic time and horizon slices that are closely correlated to the acquisition geometry. Seismic attributes often exacerbate footprint artifacts and may pose pitfalls to the less experienced interpreter. Although removal of the acquisition footprint is the focus of considerable research, the sources of such artifact acquisition footprint are less commonly discussed or illustrated. Based on real data examples, we have hypothesized possible causes of footprint occurrence and created them through (...)
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  27.  11
    Using Machine Learning as an Aid to Seismic Geomorphology, Which Attributes Are the Best Input?Lennon Infante-Paez & Kurt J. Marfurt - 2019 - Interpretation 7 (3):SE1-SE18.
    Volcanic rocks with intermediate magma composition indicate distinctive patterns in seismic amplitude data. Depending on the processes by which they were extruded to the surface, these patterns may be chaotic, moderate-amplitude reflectors or continuous high-amplitude reflectors. We have identified appropriate seismic attributes that highlight the characteristics of such patterns and use them as input to self-organizing maps to isolate these volcanic facies from their clastic counterpart. Our analysis indicates that such clustering is possible when the patterns are approximately self-similar, such (...)
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  28.  18
    Seismic-Petrophysical Reservoir Characterization in the Northern Part of the Chicontepec Basin, Mexico.Supratik Sarkar, Sumit Verma & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (3):T403-T417.
    The Chicontepec Formation in east-central Mexico is comprised of complex unconventional reservoirs consisting of low-permeability disconnected turbidite reservoir facies. Hydraulic fracturing increases permeability and joins these otherwise tight reservoirs. We use a recently acquired 3D seismic survey and well control to divide the Chicontepec reservoir interval in the northern part of the basin into five stratigraphic units, equivalent to global third-order seismic sequences. By combining well-log and core information with principles of seismic geomorphology, we are able to map deepwater facies (...)
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  29.  9
    Pitfalls and Implementation of Data Conditioning, Attribute Analysis, and Self-Organizing Maps to 2D Data: Application to the Exmouth Plateau, North Carnarvon Basin, Australia.Thang N. Ha, Kurt J. Marfurt, Bradley C. Wallet & Bryce Hutchinson - 2019 - Interpretation 7 (3):SG23-SG42.
    Recent developments in attribute analysis and machine learning have significantly enhanced interpretation workflows of 3D seismic surveys. Nevertheless, even in 2018, many sedimentary basins are only covered by grids of 2D seismic lines. These 2D surveys are suitable for regional feature mapping and often identify targets in areas not covered by 3D surveys. With continuing pressure to cut costs in the hydrocarbon industry, it is crucial to extract as much information as possible from these 2D surveys. Unfortunately, much if not (...)
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  30.  1
    Attribute-Assisted Characterization of Basement Faulting and the Associated Sedimentary Sequence Deformation in North-Central Oklahoma.Max Firkins, Folarin Kolawole, Kurt J. Marfurt & Brett M. Carpenter - 2020 - Interpretation 8 (4):SP175-SP189.
    Patterns of recent seismogenic fault reactivation in the granitic basement of north-central Oklahoma necessitate an understanding of the structural characteristics of the inherited basement-rooted faults. Here, we focus on the Nemaha Uplift & Fault Zone and the surrounding areas, within which we analyze the top-basement and intrabasement structures in eight poststack time-migrated 3D seismic reflection data sets. Overall, our results reveal 115 fault traces at the top of the Precambrian basement with sub-vertical dips, and dominant trends of west-northwest–east-southeast, northeast–southwest, and (...)
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  31.  16
    Volumetric Fault Image Enhancement — Some Applications.Satinder Chopra & Kurt J. Marfurt - 2017 - Interpretation: SEG 5 (2):T151-T161.
    The interpretation of faults on 3D seismic data is often aided by the use of geometric attributes such as coherence and curvature. Unfortunately, these same attributes also delineate stratigraphic boundaries and apparent discontinuities due to cross-cutting seismic noise. Effective fault mapping thus requires enhancing piecewise continuous faults and suppressing stratabound edges and unconformities as well as seismic noise. To achieve this objective, we apply two passes of edge-preserving structure-oriented filtering followed by a recently developed fault enhancement algorithm based on a (...)
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  32.  7
    A Window Into the Proterozoic: Integrating 3D Seismic, Gravity, and Magnetic Data to Image Subbasement Structures in the Southeast Fort Worth Basin.Murari Khatiwada, G. Randy Keller & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (2):T125-T141.
    The Fort Worth basin is one of the most fully developed shale gas fields in North America. Although there are hundreds of drilled wells in the basin, almost none of them reach the Precambrian basement. Imaged by perhaps 100 3D seismic surveys, the focus on the relatively shallow, flat-lying Barnett Shale objective has resulted in little published work on the basement structures underlying the Lower Paleozoic strata. Subtle folds and systems of large joints are present in almost all 3D seismic (...)
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  33.  24
    Seismic Azimuthal Anisotropy Analysis After Hydraulic Fracturing.Kui Zhang, Yanxia Guo, Bo Zhang, Amanda M. Trumbo & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (2):SB27-SB36.
    Many tight sandstone, limestone, and shale reservoirs require hydraulic fracturing to provide pathways that allow hydrocarbons to reach the well bore. Most of these tight reservoirs are now produced using multiple stages of fracturing through horizontal wells drilled perpendicular to the present-day azimuth of maximum horizontal stress. In a homogeneous media, the induced fractures are thought to propagate perpendicularly to the well, parallel to the azimuth of maximum horizontal stress, thereby efficiently fracturing the rock and draining the reservoir. We evaluated (...)
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  34.  23
    Data Conditioning of Legacy Seismic Using Migration-Driven 5D Interpolation.Sumit Verma, Shiguang Guo & Kurt J. Marfurt - 2016 - Interpretation: SEG 4 (2):SG31-SG40.
    Legacy seismic surveys cover much of the midcontinent USA and Texas, with almost all 3D surveys acquired in the 1990s considered today to be low fold. Fortunately, recent advances in 5D interpolation have not only enhanced the quality of structural and stratigraphic images, but they have also improved the data sufficiently to allow more quantitative interpretation, such as impedance inversion. Although normal-moveout-corrected, common-midpoint-based 5D interpolation does an excellent job of amplitude balancing and the suppression of acquisition footprint, it appears to (...)
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  35.  9
    In-Context Interpretation: Avoiding Pitfalls in Misidentification of Igneous Bodies in Seismic Data.Lennon Infante-Paez & Kurt J. Marfurt - 2018 - Interpretation: SEG 6 (4):SL29-SL42.
    In the past few decades, many exploration wells have been drilled into igneous rocks because of their similar seismic expressions to common exploration targets, such as carbonate mounds, sheet sands, and sand-prone sinuous channels. In cases in which interpreters cannot clearly delineate sedimentary features such as channels or fans, the interpretation may be driven primarily by bright spot anomalies, in which a poor understanding of the wavelet polarity may lead to an erroneous interpretation. Although many wells drilled into igneous rocks (...)
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  36.  23
    Seismic Attribute Driven Integrated Characterization of the Woodford Shale in West-Central Oklahoma.Nabanita Gupta, Supratik Sarkar & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (2):SB85-SB96.
    The organic-rich, silty Woodford Shale in west-central Oklahoma is a prolific resource play producing gas and liquid hydrocarbons. We calibrated seismic attributes and prestack inversion using well logs and core information within a seismic geomorphologic framework to define the overall basin architecture, major stratigraphic changes, and related variations in lithologies. Core measurements of elastic moduli and total organic content indicated that the Woodford Shale can be broken into three elastic petrotypes important to well completion and hydrocarbon enrichment. Upscaling these measurements (...)
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  37.  6
    Improving Seismic Resolution of Prestack Time-Migrated Data.Onur Mutlu & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (4):T245-T255.
    Seismic resolution significantly affects the quality of seismic interpretation. Processing parameters that effect resolution such as picking velocities in the presence of interbed multiples benefit from an understanding of the underlying geology. Three-dimensional migration is almost always performed by an external service company or internal specialty processing group, with the “final” product being migrated gathers and the final migration-stack section. In the Chicontepec Basin, Mexico, we have evaluated improvements in data quality made after 3D prestack time migration. By first mapping (...)
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  38.  1
    Mississippian Meramec Lithologies and Petrophysical Property Variability, Stack Trend, Anadarko Basin, Oklahoma.Michael J. Miller, Matthew J. Pranter, Ishank Gupta, Deepak Devegowda, Kurt J. Marfurt, Carl Sondergeld, Chandra Rai, Chris T. McLain, James Larese & Richard E. Packwood - 2021 - Interpretation 9 (2):SE1-SE21.
    Mississippian Meramec reservoirs of the Sooner Trend in the Anadarko in Canadian and Kingfisher Counties play are comprised of silty limestones, calcareous siltstones, argillaceous calcareous siltstones, argillaceous siltstones, and mudstones. We found that core-defined reservoir lithologies are related to petrophysics-based rock types derived from porosity-permeability relationships using a flow-zone indicator approach. We classified lithologies and rock types in noncored wells using an artificial neural network with overall accuracies of 93% and 70%, respectively. We observed that mudstone-rich rock type 1 exhibits (...)
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  39.  9
    Quantifying the Significance of Coherence Anomalies.Tengfei Lin, Thang Ha, Kurt J. Marfurt & Kevin L. Deal - 2016 - Interpretation: SEG 4 (2):T205-T213.
    Semblance and other coherence measures are routinely used in seismic processing, such as velocity spectra analysis, in seismic interpretation to estimate volumetric dip and to delineate geologic boundaries, and in poststack and prestack data conditioning such as edge-preserving structure-oriented filtering. Although interpreters readily understand the significance of outliers for such measures as seismic amplitude being described by a Gaussian distribution, and root-mean-square amplitude by a log-normal distribution, the measurement significance of a given coherence of poststack seismic data is much more (...)
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  40.  1
    Seismic Reservoir Characterization of the Gassum Formation in the Stenlille Aquifer Gas Storage, Denmark — Part 1.Satinder Chopra, Ritesh Kumar Sharma, Kenneth Bredesen & Kurt J. Marfurt - 2022 - Interpretation 10 (4):T693-T705.
    Seismic reservoir characterization plays an important role in carbon capture and storage analysis. The Havnsø anticlinal structure in Denmark is a prospective CO2 storage site due to its proximity to two large emission sources—a coal-fired power station and a nearby refinery. Although legacy 2D seismic lines over the area outline the anticlinal structure, their quality is insufficient for quantitative interpretation. Earlier studies have shown that the natural gas stored in the Stenlille aquifer exhibits a seismic response similar to the modeled (...)
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  41.  4
    Coherence Attribute Applications on Seismic Data in Various Guises — Part 1.Satinder Chopra & Kurt J. Marfurt - 2018 - Interpretation: SEG 6 (3):T521-T529.
    The iconic coherence attribute is very useful for imaging geologic features such as faults, deltas, submarine canyons, karst collapse, mass-transport complexes, and more. In addition to its preconditioning, the interpretation of discrete stratigraphic features on seismic data is also limited by its bandwidth, where in general the data with higher bandwidth yield crisper features than data with lower bandwidth. Some form of spectral balancing applied to the seismic amplitude data can help in achieving such an objective so that coherence run (...)
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  42.  12
    Seismic Characterization of a Mississippi Lime Resource Play in Osage County, Oklahoma, USA.Benjamin L. Dowdell, J. Tim Kwiatkowski & Kurt J. Marfurt - 2013 - Interpretation: SEG 1 (2):SB97-SB108.
    With the advent of horizontal drilling and hydraulic fracturing in the Midcontinent, USA, fields once thought to be exhausted are now experiencing renewed exploitation. However, traditional Midcontinent seismic analysis techniques no longer provide satisfactory reservoir characterization for these unconventional plays; new seismic analysis methods are needed to properly characterize these radically innovative play concepts. Time processing and filtering is applied to a raw 3D seismic data set from Osage County, Oklahoma, paying careful attention to velocity analysis, residual statics, and coherent (...)
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  43.  21
    Recent Progress in Analysis of Seismically Thin Beds.Hongliu Zeng & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (3):SS15-SS22.
    Various approaches exist for quantitative or qualitative predictions of seismically thin beds and their physical properties. The evolving definition of thin beds, the use of seismic attributes indicative of thin beds, thin-bed imaging on geologic-time surfaces, and thin-bed thickness estimation represent some of the most active aspects of the research and application. We reviewed some theoretical and technological developments in thin-bed analysis over recent decades. We also reviewed the data processing steps that affect seismic resolution and thin-bed evaluation.
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  44. Tomographic Velocity Analysis and Wave-Equation Depth Migration in an Overthrust Terrain: A Case Study From the Tuha Basin, China.Bin Lyu, Qin Su & Kurt J. Marfurt - 2018 - Interpretation 6 (1):T1-T13.
    Although the structures associated with overthrust terrains form important targets in many basins, accurately imaging remains challenging. Steep dips and strong lateral velocity variations associated with these complex structures require prestack depth migration instead of simpler time migration. The associated rough topography, coupled with older, more indurated, and thus high-velocity rocks near or outcropping at the surface often lead to seismic data that suffer from severe statics problems, strong head waves, and backscattered energy from the shallow section, giving rise to (...)
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  45.  1
    An in-Depth Analysis of Logarithmic Data Transformation and Per-Class Normalization in Machine Learning: Application to Unsupervised Classification of a Turbidite System in the Canterbury Basin, New Zealand, and Supervised Classification of Salt in the Eugene Island Minibasin, Gulf of Mexico.Thang N. Ha, David Lubo-Robles, Kurt J. Marfurt & Bradley C. Wallet - 2021 - Interpretation 9 (3):T685-T710.
    In a machine-learning workflow, data normalization is a crucial step that compensates for the large variation in data ranges and averages associated with different types of input measured with different units. However, most machine-learning implementations do not provide data normalization beyond the z-score algorithm, which subtracts the mean from the distribution and then scales the result by dividing by the standard deviation. Although the z-score converts data with Gaussian behavior to have the same shape and size, many of our seismic (...)
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  46.  15
    Coherence Attribute Applications on Seismic Data in Various Guises — Part 2.Satinder Chopra & Kurt J. Marfurt - 2018 - Interpretation: SEG 6 (3):T613-T623.
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  47.  10
    Calibration of Attribute Anomalies Through Prestack Seismic Modeling.Sumit Verma, Onur Mutlu, Thang Ha, William Bailey & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (4):SAC55-SAC70.
    Seismic modeling is commonly used in determining subsurface illumination of alternative seismic survey designs, in the calibration of seismic processing and imaging algorithms, and in the design of effective processing workflows. Seismic modeling also forms the mathematical kernel of impedance inversion and is routinely used to predict the amplitude-variation-with-offset response as a function of rock and fluid properties. However, the use of seismic modeling in seismic attribute studies is less common. We have evaluated four case studies in which 2D synthetic (...)
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  48.  9
    Strategies on Obtaining Permission to Publish.Kurt J. Marfurt, Don Herron, Brad Wallet, Balazs Nemeth & Oswaldo Davogustto-Cataldo - 2018 - Interpretation: SEG 6 (4):1N-3N.
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  49.  9
    Tomographic Velocity Analysis and Wave Equation Depth Migration in an Overthrust Terrain: A Case Study From the Tuha Basin, China.Bin Lyu, Qin Su & Kurt J. Marfurt - 2018 - Interpretation: SEG 6 (1):T1-T13.
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  50.  18
    Depositional Sequence Characterization Based on Seismic Variational Mode Decomposition.Fangyu Li, Bo Zhang, Rui Zhai, Huailai Zhou & Kurt J. Marfurt - 2017 - Interpretation: SEG 5 (2):SE97-SE106.
    Subtle variations in otherwise similar seismic data can be highlighted in specific spectral components. Our goal is to highlight repetitive sequence boundaries to help define the depositional environment, which in turn provides an interpretation framework. Variational mode decomposition is a novel data-driven signal decomposition method that provides several useful features compared with the commonly used time-frequency analysis. Rather than using predefined spectral bands, the VMD method adaptively decomposes a signal into an ensemble of band-limited intrinsic mode functions, each with its (...)
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