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Differentiation and Prediction of Shale Gas Production in Horizontal Wells: A Case Study of the Weiyuan Shale Gas Field, China

Author

Listed:
  • Lixia Kang

    (PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
    China National Shale Gas Research and Development (Experiment) Center, Langfang 065007, China)

  • Wei Guo

    (PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
    China National Shale Gas Research and Development (Experiment) Center, Langfang 065007, China)

  • Xiaowei Zhang

    (PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
    China National Shale Gas Research and Development (Experiment) Center, Langfang 065007, China)

  • Yuyang Liu

    (PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
    China National Shale Gas Research and Development (Experiment) Center, Langfang 065007, China)

  • Zhaoyuan Shao

    (PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China
    China National Shale Gas Research and Development (Experiment) Center, Langfang 065007, China)

Abstract

The estimated ultimate recovery (EUR) of shale gas is an important index for evaluating the production capacity of horizontal wells. The Weiyuan shale gas field has wells with considerable EUR differentiation, which hinders the prediction of the production capacity of new wells. Accordingly, 121 wells with highly differentiated production are used for analysis. First, the main control factors of well production are identified via single-factor and multi-factor analyses, with the EUR set as the production capacity index. Subsequently, the key factors are selected to perform the multiple linear regression of EUR, accompanied by the developed method for well production prediction. The thickness and drilled length of Long 1 1 1 (Substratum 1 of Long 1 submember, Lower Silurian Longmaxi Formation) are demonstrated to have the uttermost effects on the well production, while several other factors also play important roles, including the fractured horizontal wellbore length, gas saturation, brittle mineral content, fracturing stage quantity, and proppant injection intensity. The multiple linear regression method can help accurately predict EUR, with errors of no more than 10%, in wells that have smooth production curves and are free of artificial interference, such as casing deformation, frac hit, and sudden change in production schemes. The results of this study are expected to provide certain guiding significances for shale gas development.

Suggested Citation

  • Lixia Kang & Wei Guo & Xiaowei Zhang & Yuyang Liu & Zhaoyuan Shao, 2022. "Differentiation and Prediction of Shale Gas Production in Horizontal Wells: A Case Study of the Weiyuan Shale Gas Field, China," Energies, MDPI, vol. 15(17), pages 1-13, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6161-:d:896984
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    References listed on IDEAS

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    1. Wente Niu & Jialiang Lu & Yuping Sun, 2021. "A Production Prediction Method for Shale Gas Wells Based on Multiple Regression," Energies, MDPI, vol. 14(5), pages 1-11, March.
    2. Dongkwon Han & Sunil Kwon, 2021. "Application of Machine Learning Method of Data-Driven Deep Learning Model to Predict Well Production Rate in the Shale Gas Reservoirs," Energies, MDPI, vol. 14(12), pages 1-24, June.
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    Cited by:

    1. Jianliang Xu & Yingjie Xu & Yong Wang & Yong Tang, 2022. "Multi-Well Pressure Interference and Gas Channeling Control in W Shale Gas Reservoir Based on Numerical Simulation," Energies, MDPI, vol. 16(1), pages 1-13, December.

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