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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.  18
    Coherence Attribute at Different Spectral Scales.Fangyu Li & Wenkai Lu - 2014 - Interpretation: SEG 2 (1):SA99-SA106.
    In general, we wish to interpret the most broadband data possible. However, broadband data do not always provide the best insight for seismic attribute analysis. Obviously, spectral bands contaminated by noise should be eliminated. However, tuning gives rise to spectral bands with higher signal-to-noise ratios. To quantify geologic discontinuities in different scales, we combined spectral decomposition and coherence. Using spectral decomposition, the spectral amplitudes corresponding to a given scale geologic discontinuity, as well as some subtle features, which would otherwise be (...)
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  3.  22
    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.  55
    Semisupervised Multiattribute Seismic Facies Analysis.Jie Qi, Tengfei Lin, Tao Zhao, Fangyu Li & Kurt Marfurt - 2016 - Interpretation: SEG 4 (1):SB91-SB106.
    One of the key components of traditional seismic interpretation is to associate or “label” a specific seismic amplitude package of reflectors with an appropriate seismic or geologic facies. The object of seismic clustering algorithms is to use a computer to accelerate this process, allowing one to generate interpreted facies for large 3D volumes. Determining which attributes best quantify a specific amplitude or morphology component seen by the human interpreter is critical to successful clustering. Unfortunately, many patterns, such as coherence images (...)
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  5.  39
    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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  6.  14
    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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  7.  20
    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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  8.  23
    Seismic Time-Frequency Decomposition by Using a Hybrid Basis-Matching Pursuit Technique.Xingjian Wang, Bo Zhang, Fangyu Li, Jie Qi & Bo Bai - 2016 - Interpretation: SEG 4 (2):T239-T248.
    Analyzing the time-frequency features of seismic traces plays an important role in seismic stratigraphy analysis and hydrocarbon detection. The current popular time-spectrum analysis methods include short-time Fourier transform, continuous wavelet transform, S-transform, and matching pursuit, among which MP is the most tolerant of the window/scalar effect. However, current MP algorithms do not consider the interfering effects of seismic events on the estimation of optimal wavelets in each decomposition iteration. The interfered reflection seismic events may result in inaccurate estimation of optimal (...)
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  9.  28
    Incremental Correlation of Multiple Well Logs Following Geologically Optimal Neighbors.Xinming Wu, Yunzhi Shi, Sergey Fomel & Fangyu Li - 2018 - Interpretation 6 (3):T713-T722.
    Well-log correlation is a crucial step to construct cross sections in estimating structures between wells and building subsurface models. Manually correlating multiple logs can be highly subjective and labor intensive. We have developed a weighted incremental correlation method to efficiently correlate multiple well logs following a geologically optimal path. In this method, we first automatically compute an optimal path that starts with longer logs and follows geologically continuous structures. Then, we use the dynamic warping technique to sequentially correlate the logs (...)
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  10.  15
    Incremental Correlation of Multiple Well Logs Following Geologically Optimal Neighbors.Xinming Wu, Yunzhi Shi, Sergey Fomel & Fangyu Li - 2018 - Interpretation: SEG 6 (3):T713-T722.
    Well-log correlation is a crucial step to construct cross sections in estimating structures between wells and building subsurface models. Manually correlating multiple logs can be highly subjective and labor intensive. We have developed a weighted incremental correlation method to efficiently correlate multiple well logs following a geologically optimal path. In this method, we first automatically compute an optimal path that starts with longer logs and follows geologically continuous structures. Then, we use the dynamic warping technique to sequentially correlate the logs (...)
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  11.  3
    Seismic Geologic Structure Characterization Using a High-Order Spectrum-Coherence Attribute.Naihao Liu, Zhen Li, Fengyuan Sun, Fangyu Li & Jinghuai Gao - 2020 - Interpretation 8 (2):T391-T401.
    Characterization of seismic geologic structures, such as describing fluvial channels and geologic faults, is significant for seismic reservoir prediction. The coherence algorithm is one of the widely used techniques for describing discontinuous seismic geologic structures. However, precise coherence attributes between adjacent seismic traces are difficult to compute due to the nonstationary and non-Gaussian property of seismic data. To describe seismic geologic structures accurately, we define a high-order spectrum-coherence attribute. First, we have developed a time-frequency analysis method to compute a constant-frequency (...)
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  12.  9
    Value of Nonstationary Wavelet Spectral Balancing in Mapping a Faulted Fluvial System, Bohai Gulf, China.Huailai Zhou, Yuanjun Wang, Tengfei Lin, Fangyu Li & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (3):SS1-SS13.
    Seismic data with enhanced resolution allow interpreters to effectively delineate and interpret architectural components of stratigraphically thin geologic features. We used a recently developed time-frequency domain deconvolution method to spectrally balance nonstationary seismic data. The method was based on polynomial fitting of seismic wavelet magnitude spectra. The deconvolution increased the spectral bandwidth but did not amplify random noise. We compared our new spectral modeling algorithm with existing time-variant spectral-whitening and inverse [Formula: see text]-filtering algorithms using a 3D offshore survey acquired (...)
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  13.  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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  14.  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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  15. Revisit Seismic Attenuation Attributes: Influences of the Spectral Balancing Operation on Seismic Attenuation Analysis.Fangyu Li, Rongchang Liu, Yihuai Lou & Naihao Liu - forthcoming - Interpretation:1-50.
    Seismic attenuation analysis is important for seismic processing and quantitative interpretation. Nevertheless, the classic quality factor estimation methods make certain assumptions that may be invalid for a given geologic target and seismic volume. For this reason, seismic attenuation attribute analysis, which reduces some of the theoretical assumptions, can serve as a practical alternative in apparent attenuation characterization. Unfortunately, most of the published literature defines seismic attenuation attributes based on a specific source wavelet assumption, such as the Ricker wavelet, rather than (...)
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  16. Introduction to Special Section: Permian Basin Challenges and Opportunities.Sumit Verma, Olga Nedorub, Fangyu Li, Tao Zhao, Mohamed Zobaa, Robert Trentham, Ron Bianco & Vikram Jayaram - 2019 - Interpretation 7 (4):SKi-SKi.
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