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It was established that the magnitude of saturation pressure in the reservoir could be predicted using an analysis of the tightness of the multiple correlations between saturation pressure and parameters such as well depth (H), reservoir temperature (T), Gas-Oil Ratio (GF), oil viscosity (η), the specific gravity of oil (γ), coefficient of volume expansion (b). The group accounting of arguments (MGGA) was applied to solve the problem.

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Predicting Reservoir Saturation Pressure from Available Field Information Based on the Use of Artificial Intelligence Methods

  • 会议论文

  • 发表日期：

    2025年

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  • Hacan Hajiyev Gulu,
  • Vagif Mammadov Mammadhuseyn,
  • Nijat Ismayilov Safaxan

摘要

It was established that the magnitude of saturation pressure in the reservoir could be predicted using an analysis of the tightness of the multiple correlations between saturation pressure and parameters such as well depth (H), reservoir temperature (T), Gas-Oil Ratio (GF), oil viscosity (η), the specific gravity of oil (γ), coefficient of volume expansion (b). The group accounting of arguments (MGGA) was applied to solve the problem.