Back Analysis of Equivalent Permeability Tensor for Fractured Rock Masses from Packer Tests

A new approach to back analyze the equivalent permeability tensor for fractured rock masses, based on the fracture tensor formulation, the packer test simulation and the Artificial Neural Network (ANN) back analysis is investigated. Artificial neural network (ANN) is a mathematical model that simulates the structure and function of biological neural network. It consists of an interconnected group of artificial neurons usually with one input layer, one or several hidden layers, and one output layer. The number of single-hole packer tests should be equal or more than that of fracture sets. The directions of their test bore-holes need to be different. Each packer test requires at least one test segment to provide test data. The available in situ test results should display a linear relation between test pressure and injected flow rate, so as to ensure the laminar flow state in fractures. The Finite Element Method (FEM) has been used in numerical seepage analysis for anisotropic domain with complex boundary condition.