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  1.  9
    A Comparative Study of Texture Attributes for Characterizing Subsurface Structures in Seismic Volumes.Zhiling Long, Yazeed Alaudah, Muhammad Ali Qureshi, Yuting Hu, Zhen Wang, Motaz Alfarraj, Ghassan AlRegib, Asjad Amin, Mohamed Deriche, Suhail Al-Dharrab & Haibin Di - 2018 - Interpretation: SEG 6 (4):T1055-T1066.
    We have explored how to computationally characterize subsurface geologic structures presented in seismic volumes using texture attributes. For this purpose, we conduct a comparative study of typical texture attributes presented in the image processing literature. We focus on spatial attributes in this study and examine them in a new application for seismic interpretation, i.e., seismic volume labeling. For this application, a data volume is automatically segmented into various structures, each assigned with its corresponding label. If the labels are assigned with (...)
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  2.  9
    Improving Seismic Fault Detection by a Super-Attribute-Based Classification.Haibin Di, Muhammad Amir Shafiq, Zhen Wang & Ghassan AlRegib - forthcoming - Interpretation:1-56.
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  3.  16
    Nonlinear Gray-Level Co-Occurrence Matrix Texture Analysis for Improved Seismic Facies Interpretation.Haibin Di & Dengliang Gao - 2017 - Interpretation: SEG 5 (3):SJ31-SJ40.
    Seismic texture analysis is a useful tool for delineating subsurface geologic features from 3D seismic surveys, and the gray-level co-occurrence matrix method has been popularly applied for seismic texture discrimination since its first introduction in the 1990s. The GLCM texture analysis consists of two components: to rescale seismic amplitude by a user-defined number of gray levels and to perform statistical analysis on the spatial arrangement of gray levels within an analysis window. Traditionally, the linear transformation is simply used for amplitude (...)
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  4.  16
    3D Structural-Orientation Vector Guided Autotracking for Weak Seismic Reflections: A New Tool for Shale Reservoir Visualization and Interpretation.Haibin Di, Dengliang Gao & Ghassan AlRegib - 2018 - Interpretation: SEG 6 (4):SN47-SN56.
    Recognizing and tracking weak reflections, which are characterized by low amplitude, low signal-to-noise ratio, and low degree of lateral continuity, is a long-time issue in 3D seismic interpretation and reservoir characterization. The problem is particularly acute with unconventional, fractured shale reservoirs, in which the impedance contrast is low and/or reservoir beds are below the tuning thickness. To improve the performance of interpreting weak reflections associated with shale reservoirs, we have developed a new workflow for weak-reflection tracking guided by a robust (...)
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  5.  2
    Improving Seismic Fault Detection by Super-Attribute-Based Classification.Haibin Di, Mohammod Amir Shafiq, Zhen Wang & Ghassan AlRegib - 2019 - Interpretation 7 (3):SE251-SE267.
    Fault interpretation is one of the routine processes used for subsurface structure mapping and reservoir characterization from 3D seismic data. Various techniques have been developed for computer-aided fault imaging in the past few decades; for example, the conventional methods of edge detection, curvature analysis, red-green-blue rendering, and the popular machine-learning methods such as the support vector machine, the multilayer perceptron, and the convolutional neural network. However, most of the conventional methods are performed at the sample level with the local reflection (...)
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  6.  4
    Introduction to Special Section: Machine Learning in Seismic Data Analysis.Haibin Di, Tao Zhao, Vikram Jayaram, Xinming Wu, Lei Huang, Ghassan AlRegib, Jun Cao, Mauricio Araya-Polo, Satinder Chopra, Saleh Al-Dossary, Fangyu Li, Erwan Gloaguen, Youzuo Lin, Anne Solberg & Hongliu Zeng - 2019 - Interpretation 7 (3):SEi-SEii.
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  7.  7
    Reflector Dip Estimates Based on Seismic Waveform Curvature/Flexure Analysis.Haibin Di & Ghassan AlRegib - 2019 - Interpretation 7 (2):SC1-SC9.
    Reliable estimation of the reflector dip serves as a fundamental and essential tool for subsurface structure interpretation from 3D seismic surveys. We have developed a new method for accurate dip estimation, which consists of two major components. First, the curvature/flexure concept is adapted from the traditional reflector geometry analysis to work for the seismic waveforms, denoted as the waveform curvature and waveform flexure, respectively. Physically, both of them are capable of measuring the most and least apparent variation of the local (...)
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  8.  9
    Integrating Distributed Acoustic Sensing, Borehole 3C Geophone Array, and Surface Seismic Array Data to Identify Long-Period Long-Duration Seismic Events During Stimulation of a Marcellus Shale Gas Reservoir.Payam Kavousi Ghahfarokhi, Thomas H. Wilson, Timothy Robert Carr, Abhash Kumar, Richard Hammack & Haibin Di - 2019 - Interpretation 7 (1):SA1-SA10.
    Microseismic monitoring by downhole geophones, surface seismic, fiber-optic distributed acoustic sensing, and distributed temperature sensing observations were made during the hydraulic fracture stimulation of the MIP-3H well in the Marcellus Shale in northern West Virginia. DAS and DTS data measure the fiber strain and temperature, respectively, along a fiber-optic cable cemented behind the casing of the well. The presence of long-period long-duration events is evaluated in the borehole geophones, DAS data, and surface seismic data of one of the MIP-3H stimulated (...)
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  9.  21
    Introduction to Special Section: Seismic Geometric Attributes.Xinming Wu, Hongliu Zeng, Haibin Di, Dengliang Gao, Jinghuai Gao, Kurt Marfurt, Saleh al Dossary & Geoffrey Dorn - 2019 - Interpretation 7 (2):SCi-SCi.
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