Prediction Model for Advanced Detection of Water-Rich Faults Using 3D Anisotropic Resistivity Modeling and Monte Carlo Methods

Abstract

During tunnel excavation, water hazards in faults, especially steep water rich faults, pose a serious threat to safe construction in some complex mountains, which leads to low economic growth and development in these areas. Direct current resistivity method, which has high resolution and sensitivity to the low resistivity body is widely used to predict the water-bearing structures in the front of tunnel face. The current prediction models are based on the resistivity isotropic medium, however, the resistivity of water bearing fault is often anisotropic due to rock fracture. The prediction model neglecting the anisotropy is obviously inaccurate, which brings potential threats to safe construction. We develop a three-dimensional resistivity modeling for anisotropic media using unstructured finite element method. The algorithm is proved to be accurate by comparison of numerical results and analytical solutions for a whole-space model. Another classical anisotropic model also demonstrated the reliability of our code from a physical point of view. Then we propose a prediction equation to predict the position of a vertical fault with anisotropic resistivity in the front of tunnel face by the finite element simulations. The parallel Monte Carlo method is used to test and evaluate the quality of our prediction equation by simulations of 10000 random vertical fault models, results counted by the histogram showed 85.36% of the results are predicted within 10% of the error. Besides, 93.17% of the results are predicted within 15% of the error using the equation for random faults with 75 degree dip angle, which shows that our prediction model can effectively forecast steeply dipping water-rich faults or fracture zones.