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  • Open Access

    ARTICLE

    Assessment of Carboniferous Volcanic Horizontal Wells after Fracturing Based on Gray Correlation, Hierarchical Analysis and Fuzzy Evaluation

    Junwei Han1, Guohua Li1, Wu Zhong1, Yuchen Yang1, Maoheng Li2,3, Zhiwei Chen2,3, Ruichang Ge2,3, Lijuan Huang2,3,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2757-2773, 2024, DOI:10.32604/fdmp.2024.056130 - 23 December 2024

    Abstract A comprehensive method to evaluate the factors affecting the production capacity of horizontal wells in Carboniferous volcanic rocks after fracturing is investigated. A systematic approach combining gray correlation analysis, hierarchical analysis and fuzzy evaluation is proposed. In particular, first the incidence of reservoir properties and fracturing parameters on production capacity is assessed. These parameters include reservoir base geological parameters (porosity, permeability, oil saturation, waterproof height) as well as engineering parameters (fracture half-length, fracture height, fracture conductivity, fracture distance). Afterwards, a two-by-two comparison judgment matrix of sensitive parameters is constructed by means of hierarchical analysis, and More >

  • Open Access

    REVIEW

    Recent Advances of Deep Learning in Geological Hazard Forecasting

    Jiaqi Wang1, Pengfei Sun1, Leilei Chen2, Jianfeng Yang3, Zhenghe Liu1, Haojie Lian1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1381-1418, 2023, DOI:10.32604/cmes.2023.023693 - 26 June 2023

    Abstract Geological hazard is an adverse geological condition that can cause loss of life and property. Accurate prediction and analysis of geological hazards is an important and challenging task. In the past decade, there has been a great expansion of geohazard detection data and advancement in data-driven simulation techniques. In particular, great efforts have been made in applying deep learning to predict geohazards. To understand the recent progress in this field, this paper provides an overview of the commonly used data sources and deep neural networks in the prediction of a variety of geological hazards. More >

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