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  • Open Access

    ARTICLE

    Research on Quantitative Identification of Three-Dimensional Connectivity of Fractured-Vuggy Reservoirs

    Xingliang Deng1, Peng Cao2,*, Yintao Zhang1, Yuhui Zhou3, Xiao Luo1, Liang Wang3

    Energy Engineering, Vol.121, No.5, pp. 1195-1207, 2024, DOI:10.32604/ee.2023.045870 - 30 April 2024

    Abstract The fractured-vuggy carbonate oil resources in the western basin of China are extremely rich. The connectivity of carbonate reservoirs is complex, and there is still a lack of clear understanding of the development and topological structure of the pore space in fractured-vuggy reservoirs. Thus, effective prediction of fractured-vuggy reservoirs is difficult. In view of this, this work employs adaptive point cloud technology to reproduce the shape and capture the characteristics of a fractured-vuggy reservoir. To identify the complex connectivity among pores, fractures, and vugs, a simplified one-dimensional connectivity model is established by using the meshless More >

  • Open Access

    ARTICLE

    An Improved Parameter Dimensionality Reduction Approach Based on a Fast Marching Method for Automatic History Matching

    Hairong Zhang1, Yongde Gao2, Wei Li2, Deng Liu3,*, Jing Cao3, Luoyi Huang3, Xun Zhong3

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 609-628, 2022, DOI:10.32604/fdmp.2022.019446 - 22 February 2022

    Abstract History matching is a critical step in reservoir numerical simulation algorithms. It is typically hindered by difficulties associated with the high-dimensionality of the problem and the gradient calculation approach. Here, a multi-step solving method is proposed by which, first, a Fast marching method (FMM) is used to calculate the pressure propagation time and determine the single-well sensitive area. Second, a mathematical model for history matching is implemented using a Bayesian framework. Third, an effective decomposition strategy is adopted for parameter dimensionality reduction. Finally, a localization matrix is constructed based on the single-well sensitive area data More >

  • Open Access

    ARTICLE

    Geophysical and Production Data History Matching Based on Ensemble Smoother with Multiple Data Assimilation

    Zelong Wang1, 2, 3, *, Xiangui Liu1, 2, 3, Haifa Tang3, Zhikai Lv3, Qunming Liu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 873-893, 2020, DOI:10.32604/cmes.2020.08993 - 01 May 2020

    Abstract The Ensemble Kalman Filter (EnKF), as the most popular sequential data assimilation algorithm for history matching, has the intrinsic problem of high computational cost and the potential inconsistency of state variables updated at each loop of data assimilation and its corresponding reservoir simulated result. This problem forbids the reservoir engineers to make the best use of the 4D seismic data, which provides valuable information about the fluid change inside the reservoir. Moreover, only matching the production data in the past is not enough to accurately forecast the future, and the development plan based on the… More >

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