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  1.  56
    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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  2.  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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  3.  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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  4.  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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  5.  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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  6.  11
    Geometric Seismic Attribute Estimation Using Data-Adaptive Windows.Tengfei Lin, Bo Zhang & Kurt Marfurt - 2019 - Interpretation 7 (2):SC33-SC43.
    Geometric seismic attributes such as coherence are routinely used for highlighting geologic features such as faults and channels. Traditionally, we use a single user-defined analysis window of fixed size to calculate attributes for the entire seismic volume. In general, smaller windows produce sharper geologic edges, but they are more sensitive to noise. In contrast, larger windows reduce the effect of random noise, but they might laterally smear faults and channel edges and vertically mix the stratigraphy. The vertical and lateral resolutions (...)
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