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A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique

Fahd Saeed Alakbari1, Mysara Eissa Mohyaldinn1, Mohammed Abdalla Ayoub1

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This study introduces a new Adaptive Neuro-Fuzzy Inference System (ANFIS) model for accurately predicting bubble point pressure (Pb). The ANFIS model demonstrates superior performance and correct physical behavior compared to 21 existing models.

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Area of Science:

  • Petroleum Engineering
  • Thermodynamics
  • Artificial Intelligence

Background:

  • Pressure-volume-temperature (PVT) measurements are standard for determining bubble point pressure (Pb).
  • Experimental determination of Pb is time-consuming, costly, and challenging under high-pressure-high-temperature conditions.
  • Existing predictive models for Pb often lack trend analysis, failing to demonstrate correct physical behavior.

Purpose of the Study:

  • To develop a robust and accurate model for predicting bubble point pressure (Pb).
  • To introduce the Adaptive Neuro-Fuzzy Inference System (ANFIS) combined with trend analysis for Pb prediction.
  • To validate the physical behavior and accuracy of the proposed ANFIS model against existing methods.

Main Methods:

  • Utilized a dataset of over 700 global experimental data points for model development and validation.
  • Employed the Adaptive Neuro-Fuzzy Inference System (ANFIS) for predictive modeling.
  • Conducted trend analysis to ensure the model reflects correct physical relationships between parameters.
  • Performed comparative analysis against 21 existing models using statistical error metrics (R, SD, AAPRE, APRE, RMSE).

Main Results:

  • The ANFIS model accurately predicts bubble point pressure (Pb), demonstrating correct physical behavior.
  • Achieved a correlation coefficient (R) of 0.994, with the lowest Average Absolute Percentage Relative Error (AAPRE) of 6.38%, Average Percentage Relative Error (APRE) of -0.99%, Standard Deviation (SD) of 0.074 psi, and Root Mean Square Error (RMSE) of 9.73 psi.
  • Outperformed all 21 previously studied models in accuracy and physical representation.

Conclusions:

  • The proposed ANFIS model is a validated, highly accurate tool for predicting bubble point pressure (Pb).
  • The ANFIS model successfully captures the physical behavior governing bubble point pressure.
  • This approach offers a superior alternative to existing models for estimating Pb, especially under challenging experimental conditions.