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  1.  14
    Seismic Sequence Stratigraphy and Sedimentary Evolution of Carbonate Reservoirs in the Sinian Dengying Formation, Middle Sichuan Basin, Southwest China.Guangfa Zhong, Yalin Li & Dingjin Liu - 2013 - Interpretation: SEG 1 (1):SA21-SA34.
    The Sinian Dengying Formation in the Sichuan Basin, southwest China, mainly consisting of dolomites, is one of the most ancient gas-producing series in the world. During the past half-century, gas exploration in the formation has been largely based on the lithostratigraphic correlation, but a regional correlation scheme of time significance is usually insufficient, resulting in the difficulty of lateral correlation of strata between gas fields. Aiming to overcome the problem, we completed an interpretation of about 2500-km 2D regional seismic lines (...)
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    Novel Strategies for Complex Foothills Seismic Imaging — Part 1: Mega-Near-Surface Velocity Estimation.Yalin Li, Xianhuai Zhu, Gengxin Peng, Liansheng Liu & Wensheng Duan - 2020 - Interpretation 8 (3):T651-T665.
    Seismic imaging in foothills areas is challenging because of the complexity of the near-surface and subsurface structures. Single seismic surveys often are not adequate in a foothill-exploration area, and multiple phases with different acquisition designs within the same block are required over time to get desired sampling in space and azimuths for optimizing noise attenuation, velocity estimation, and migration. This is partly because of economic concerns, and it is partly because technology is progressing over time, creating the need for unified (...)
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    Collaborative Sleep Electroencephalogram Data Analysis Based on Improved Empirical Mode Decomposition and Clustering Algorithm.Xiangwei Zheng, Xiaochun Yin, Xuexiao Shao, Yalin Li & Xiaomei Yu - 2020 - Complexity 2020:1-14.
    Sleep-related diseases seriously affect the life quality of patients. Sleep stage classification, which studies the human sleep process and classifies the sleep stages, is an important reference to the diagnosis and study of sleep disorders. Many scholars have conducted a series of sleep staging studies, but the correlation between different sleep stages and the accuracy of classification still needs to be improved. Therefore, this paper proposes an automatic sleep stage classification based on EEG. By constructing an improved empirical mode decomposition (...)
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