DESCRIBING THE GEOMETRY OF 3D FRACTURE SYSTEMS BY CORRECTING FOR LINEAR SAMPLING BIAS

Abstract

Analyzing the geometric bias inherent to linear sampling of natural fracture systems is a prerequisite to any attempt of structural modeling. In this paper, the basic parameters of 1D-sampled fracture sets, i.e. orientation, density, and size, are interpreted in terms of geometric probabilities. Weighting factors are derived which allow the 3D restitution of a moderately variable fracture network from a single borehole. The proposed method is applied to well core data from a granitic rock mass, and the efficiency of the proposed corrections is illustrated through random disc simulations tested by virtual scanlines analogous to the real borehole. This approach aims to reduce the prospecting effort in exploration, and to criticize assumption of structural homogeneity by rigorously comparing fracture populations collected from nonparallel boreholes. Then a parametric study of fracture size is performed and a range of mean size leading to fully connected networks is identified.