New Models for Predicting Pore Pressure and Fracture Pressure while Drilling in Mixed Lithologies Using Artificial Neural Networks
Samir Khaled, Ahmed Ashraf Soliman, Abdulrahman Mohamed, Sayed Gomaa, Attia Mahmoud Attia
Abstract
values of 0.90 and 0.99, respectively. This work demonstrates the validity and reliability of the developed models to calculate pore and fracture pressures from real-time surface drilling parameters by considering the formation type to overcome the limitation of previous models.
Topics & Concepts
Artificial neural networkPore water pressurePetroleum engineeringGeologyOil shaleDrillingFracture (geology)LithologyHydraulic fracturingDrilling fluidCompactionGeotechnical engineeringArtificial intelligenceEngineeringComputer sciencePetrologyMechanical engineeringPaleontologyDrilling and Well EngineeringHydraulic Fracturing and Reservoir AnalysisHydrocarbon exploration and reservoir analysis