Abstract
AbstractKnowledge of fracture stiffness, in situ stresses, and elastic parameters is essential to the development of efficient well patterns and enhanced geothermal systems. In this paper, an artificial neural network (ANN)–genetic algorithm (GA)-based displacement back analysis is presented for estimation of these parameters. Firstly, the ANN model is developed to map the nonlinear relationship between the fracture stiffness, in situ stresses, elastic parameters, and borehole displacements. A two-dimensional discrete element model is used to conduct borehole stability analysis and provide training samples for the ANN model. The GA is used to estimate the fracture stiffness (kn, Ks), horizontal in situ stresses (σH, σh), and elastic parameters (E, v) based on the objective function that is established by combining the ANN model with monitoring displacements. Preliminary results of a numerical experiment show that the ANN-GA-based displacement back analysis method can effectively estimate the fracture stif...
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.