1
University of Tehran, Institute of Geophysics, North Kargar Ave. Tehran
2
Tehran University
10.22050/ijogst.2026.536869.1747
Abstract
Accurate pore pressure estimation is a critical component of geomechanical modeling, essential for maintaining wellbore stability and optimizing drilling fluid density. This study proposes a Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM) workflow to predict pore pressure in a complex carbonate reservoir in southwestern Iran. While traditional empirical correlations like Eaton and Bowers are widely used, their reliance on continuous calibration can be challenging. To address this, discrete Repeating Formation Test (RFT) pressure points were utilized to calibrate baseline empirical trends, creating continuous reference profiles for the entire depth. The GWO-SVM model was then deployed to automate the replication of these calibrated baselines from standard petrophysical logs (sonic, density, resistivity, porosity, and shale volume). Using a dataset from five wells (four for training, one for blind validation), the GWO optimally tuned the Support Vector Regression (SVR) hyperparameters. The model demonstrated exceptional fidelity in replicating the calibrated baseline on the blind test well, achieving an RMSE=37.96psi and an R^2=0.998. Finally, the 1D well-based predictions were integrated into a 3D geostatistical model using co-kriging to visualize pressure compartmentalization influenced by the local tectonic stress regime. This workflow offers a replicable, high-precision alternative for pre-drill pore pressure modeling in data-limited reservoir settings.
Hosseini,M. , Riahi,M. A. , Jamab,A. and Fakhari,M. G. (2026). Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM). (e244262). Iranian Journal of Oil and Gas Science and Technology, (), e244262 doi: 10.22050/ijogst.2026.536869.1747
MLA
Hosseini,M. , , Riahi,M. A. , , Jamab,A. , and Fakhari,M. G. . "Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM)" .e244262 , Iranian Journal of Oil and Gas Science and Technology, , , 2026, e244262. doi: 10.22050/ijogst.2026.536869.1747
HARVARD
Hosseini M., Riahi M. A., Jamab A., Fakhari M. G. (2026). 'Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM)', Iranian Journal of Oil and Gas Science and Technology, (), e244262. doi: 10.22050/ijogst.2026.536869.1747
CHICAGO
M. Hosseini, M. A. Riahi, A. Jamab and M. G. Fakhari, "Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM)," Iranian Journal of Oil and Gas Science and Technology, (2026): e244262, doi: 10.22050/ijogst.2026.536869.1747
VANCOUVER
Hosseini M., Riahi M. A., Jamab A., Fakhari M. G. Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM). IJOGST, 2026; (): e244262. doi: 10.22050/ijogst.2026.536869.1747
