Coupling Fluid Flow and Geomechanical Deformation Using AI & FEM Approaches

Abstract

Abstract Coupling fluid flow and geomechanical deformation is a complex and challenging problem in geomechanics and reservoir engineering. The objective of this study is to develop a robust and accurate numerical model for coupling fluid flow and geomechanical deformation using machine learning (ML) and artificial intelligence (AI) techniques in combination with elastoplastic and finite element method (FEM) approaches. The study involves developing an elastoplastic model to simulate the deformation of geologic materials under stress and incorporating fluid flow equations into the model using FEM techniques. The two simulators are coupled sequentially. During every sequential coupling step, the flow simulator sends pore pressures to the geomechanics simulator and receives back updated porosity and permeability values. The frequency of the coupling steps is problem-dependent and subject to further optimization and research. In addition, ML and AI techniques are used to reduce the frequency of the coupling steps, which can lead to substantial computational time savings given the fact that solving the geomechanical model numerically is a computationally intensive task. Furthermore, ML and IA techniques can also be used to optimize the input parameters, improve the accuracy of the model, and reduce overall runtime. The AI-based coupled model is tested against the traditional coupled model to validate the results. The study demonstrates that coupling fluid flow and geomechanical deformation using ML and AI elastoplastic and FEM approaches is a promising area of research that can revolutionize our understanding of complex geological processes. The AI-based numerical model developed in this study provides an efficient and accurate tool for predicting the behavior of geologic materials under stress and can aid in developing more effective strategies for managing natural resources. The use of ML and AI techniques in combination with elastoplastic and FEM approaches provides an innovative and efficient method for coupling fluid flow and geomechanical deformation. The AI-based numerical model developed in this study is a significant contribution to the field of geomechanics. It has potential applications in various industries, including oil and gas exploration, mining, and geothermal energy.