Calibration modeling of drilling fluid rheological parameters in variable temperature environment based on support...

Area of Science:

• Petroleum Engineering
• Material Science

Background:

• Traditional drilling fluid rheology measurements have significant lag and poor accuracy in variable temperature environments.
• Existing models rely on fixed temperatures and empirical formulas, failing in complex conditions and leading to prediction errors.
• Precise monitoring of drilling fluid performance is crucial for efficient drilling operations.

Purpose of the Study:

• To address the low accuracy and poor stability of drilling fluid measurements under variable temperature conditions.
• To develop a support vector machine (SVM)-based calibration model for accurate real-time rheological parameter prediction.
• To enhance the precise monitoring of drilling fluid performance in dynamic temperature environments.

Main Methods:

• Analysis of the double-tube differential pressure rheology real-time measurement device principle.
• Establishment of shear stress-shear rate relationship using differential pressure and flow rate data.
• Construction of an SVM-based calibration model optimized with the gray wolf optimization algorithm for predicting rheology correction parameters.

Main Results:

• Developed a real-time monitoring platform for drilling fluid rheology.
• Achieved maximum relative errors within ±5% for apparent viscosity, plastic viscosity, and yield point predictions.
• Obtained coefficients of determination (R2) greater than 0.95, demonstrating high prediction accuracy.

Conclusions:

• The proposed SVM-based calibration model effectively monitors drilling fluid rheological performance in variable temperature environments.
• The method significantly improves the accuracy and stability of real-time drilling fluid measurements.
• This advancement enables more precise control and optimization of drilling operations.