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Methods of Decline Curve Analysis for Shale Gas Reservoirs

Author

Listed:
  • Lei Tan

    (State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
    These authors contributed equally to this work.)

  • Lihua Zuo

    (Department of Petroleum Engineering, Texas A&M University, College Station, TX 77843, USA
    These authors contributed equally to this work.)

  • Binbin Wang

    (Geochemical & Environmental Research Group, Texas A&M University, College Station, TX 77845, USA
    These authors contributed equally to this work.)

Abstract

With help from horizontal wells and hydraulic fracturing, shale gas has made a significant contribution to the energy supply. However, due to complex fracture networks and complicated mechanisms such as gas desorption and gas slippage in shale, forecasting shale gas production is a challenging task. Despite the versatility of many simulation methods including analytical models, semi-analytical models, and numerical simulation, Decline Curve Analysis has the advantages of simplicity and efficiency for hydrocarbon production forecasting. In this article, the eight most popular deterministic decline curve methods are reviewed: Arps, Logistic Growth Model, Power Law Exponential Model, Stretched Exponential Model, Duong Model, Extended Exponential Decline Model, and Fractural Decline Curve model. This review article is dedicated to summarizing the origins, derivations, assumptions, and limitations of these eight decline curve models. This review article also describes the current status of decline curve analysis methods, which provides a comprehensive and up-to-date list of Decline Curve Analysis models for petroleum engineers in analysis of shale gas reservoirs. This work could serve as a guideline for petroleum engineers to determine which Decline Curve models should be applied to different shale gas fields and production periods.

Suggested Citation

  • Lei Tan & Lihua Zuo & Binbin Wang, 2018. "Methods of Decline Curve Analysis for Shale Gas Reservoirs," Energies, MDPI, vol. 11(3), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:552-:d:134719
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    References listed on IDEAS

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    1. Wang, Ke & Li, Haitao & Wang, Junchao & Jiang, Beibei & Bu, Chengzhong & Zhang, Qing & Luo, Wei, 2017. "Predicting production and estimated ultimate recoveries for shale gas wells: A new methodology approach," Applied Energy, Elsevier, vol. 206(C), pages 1416-1431.
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    Cited by:

    1. Xuechen Li & Xinfang Ma & Fengchao Xiao & Fei Wang & Shicheng Zhang, 2020. "Application of Gated Recurrent Unit (GRU) Neural Network for Smart Batch Production Prediction," Energies, MDPI, vol. 13(22), pages 1-22, November.
    2. Jia Liu & Jianguo Wang & Chunfai Leung & Feng Gao, 2018. "A Fully Coupled Numerical Model for Microwave Heating Enhanced Shale Gas Recovery," Energies, MDPI, vol. 11(6), pages 1-28, June.
    3. Catalin Popescu & Sorin Alexandru Gheorghiu, 2021. "Economic Analysis and Generic Algorithm for Optimizing the Investments Decision-Making Process in Oil Field Development," Energies, MDPI, vol. 14(19), pages 1-24, September.
    4. Na Wei & Wantong Sun & Yingfeng Meng & Jinzhou Zhao & Bjørn Kvamme & Shouwei Zhou & Liehui Zhang & Qingping Li & Yao Zhang & Lin Jiang & Haitao Li & Jun Pei, 2020. "Hydrate Formation and Decomposition Regularities in Offshore Gas Reservoir Production Pipelines," Energies, MDPI, vol. 13(1), pages 1-22, January.
    5. Wardana Saputra & Wissem Kirati & Tadeusz Patzek, 2020. "Physical Scaling of Oil Production Rates and Ultimate Recovery from All Horizontal Wells in the Bakken Shale," Energies, MDPI, vol. 13(8), pages 1-29, April.
    6. Louis Delannoy & Pierre-Yves Longaretti & David. J. Murphy & Emmanuel Prados, 2021. "Assessing Global Long-Term EROI of Gas: A Net-Energy Perspective on the Energy Transition," Energies, MDPI, vol. 14(16), pages 1-16, August.
    7. Zhang, Xian-min & Chen, Bai-yan-yue & Zheng, Zhuang-zhuang & Feng, Qi-hong & Fan, Bin, 2023. "New methods of coalbed methane production analysis based on the generalized gamma distribution and field applications," Applied Energy, Elsevier, vol. 350(C).
    8. Prinisha Manda & Diakanua Bavon Nkazi, 2020. "The Evaluation and Sensitivity of Decline Curve Modelling," Energies, MDPI, vol. 13(11), pages 1-16, June.
    9. Maojun Cao & Yu Dai & Ling Zhao & Yuele Jia & Yueru Jia, 2018. "Hybrid Coupled Multifracture and Multicontinuum Models for Shale Gas Simulation by Use of Semi-Analytical Approach," Energies, MDPI, vol. 11(5), pages 1-20, May.

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