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A nonlinear model of multifractured horizontal wells in heterogeneous gas reservoirs considering the effect of stress sensitivity

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  • Tian, Feng
  • Wang, Junlei
  • Xu, Zhenhua
  • Xiong, Fansheng
  • Xia, Peng

Abstract

Tight gas reservoirs are usually heterogeneous and associated with notable stress sensitivity during the production, directly influencing long-term development. This paper proposes a nonlinear model of multifractured horizontal wells in heterogeneous gas reservoirs considering stress-sensitive effects. Based on the linearization by stress-dependent pseudopressure and pseudotime functions, the boundary element method and Green's solution are applied to solve the model semianalytically. The effects of the stress sensitivity, production settings and subblock number are analyzed. The stress sensitivity is mainly reflected at the middle and later production stages, imposing a notable negative effect on bottomhole pressure, reducing the bottomhole pressure in a two-block reservoir by approximately 1%–28.2%. The recoveries in a two-block reservoir with different production settings under a terminal pressure vary from 16.3% to 42.49%, and thus a reasonable rate should be set to weaken the stress-sensitive effects on pressure loss to obtain a higher cumulative production within a given time. For a three-block reservoir, the proper increase of the fracture parameters in low permeability blocks can weaken the influences of heterogeneity and make the development more uniformly. This paper provides a theoretical basis for improving gas production performance forecasting for efficient development of natural gas.

Suggested Citation

  • Tian, Feng & Wang, Junlei & Xu, Zhenhua & Xiong, Fansheng & Xia, Peng, 2023. "A nonlinear model of multifractured horizontal wells in heterogeneous gas reservoirs considering the effect of stress sensitivity," Energy, Elsevier, vol. 263(PD).
  • Handle: RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222028651
    DOI: 10.1016/j.energy.2022.125979
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    References listed on IDEAS

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    1. Solarin, Sakiru Adebola & Gil-Alana, Luis A. & Lafuente, Carmen, 2020. "An investigation of long range reliance on shale oil and shale gas production in the U.S. market," Energy, Elsevier, vol. 195(C).
    2. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
    3. Yang, Jinghua & Wang, Min & Wu, Lei & Liu, Yanwei & Qiu, Shuxia & Xu, Peng, 2021. "A novel Monte Carlo simulation on gas flow in fractal shale reservoir," Energy, Elsevier, vol. 236(C).
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