Volume 41 Issue 3
Jun.  2024
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Article Navigation >  DRILLING FLUID & COMPLETION FLUID  > 2024  >  41(3): 330-336
LIAO Gaolong, LIANG Hao, MA Shuangzheng, et al.Prediction of gas well productivity based on attribution analysis of controllable factors of hem water-based drilling fluid to gas reservoir damage[J]. Drilling Fluid & Completion Fluid，2024, 41（3）：330-336 doi: 10.12358/j.issn.1001-5620.2024.03.007
Citation: LIAO Gaolong, LIANG Hao, MA Shuangzheng, et al.Prediction of gas well productivity based on attribution analysis of controllable factors of hem water-based drilling fluid to gas reservoir damage[J]. Drilling Fluid & Completion Fluid，2024, 41（3）：330-336 doi: 10.12358/j.issn.1001-5620.2024.03.007
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Prediction of Gas Well Productivity Based on Attribution Analysis of Controllable Factors of HEM Water-Based Drilling Fluid to Gas Reservoir Damage

doi: 10.12358/j.issn.1001-5620.2024.03.007
  • 1.

    Hainan Branch of CNOOC Petroleum Co., Ltd., Haikou, Hainan 570311

  • 2.

    CNOOC Energy Development Co., Ltd. Engineering Technology Branch, Zhanjiang, Guangdong 524057

  • 3.

    China University of Petroleum (Beijing), Beijing 102249

  • Received Date: 2024-01-05
  • Rev Recd Date: 2024-02-13
  • Publish Date: 2024-06-30
    Abstract
  • As the depth of drilling increases, the prevention and control of reservoir damage caused by drilling fluids has become increasingly prominent, and reservoir protection has become a key factor in the full release of gas field production capacity. As the well depth deepens, the various properties of the deepwater drilling fluid change, causing the degree of reservoir damage to intensify and the direction of reservoir protection performance optimization becomes unclear. Therefore, this paper combines Pearson correlation analysis and grey relational analysis to perform attribution analysis of controllable factors of drilling fluids in reservoir damage, identify the main controlling factors, and establish a gas well productivity model. The results show that the solid particle size, surface tension, mineralization degree, and high-temperature and high-pressure fluid loss of drilling fluids are the main controlling factors causing reservoir damage. According to the attribution analysis results, an optimization method using a composite of different particle size distributions of calcium carbonate as a weighting agent is proposed, which increases the permeability recovery of drilling fluids by 12.1 to 19.68%. The applicability of the model is verified by collecting field parameters from wells Y8 and Y9, and the results show that the accuracy of the model established in this paper is over 94%.

     

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