3D Generation of Discrete Fracture Network by Geostatistical Approach

Summary Simulating a rock fracture distribution is an important issue, which is common in various fields of geosciences. This issue is of particular importance in determination of hydraulic conductivity of rock mass and forecasting the amount of water entering the underground spaces. Theoretical studies has been demonstrated that the result of three-dimensional (3D) modeling discrete fracture network is closer to reality than other models. One of the limitations of the statistical methods for modeling fracture network is the lack of spatial behavior considerations of modeling fracture network parameters. In other words, based on Monte Carlo algorithm in statistical methods, generation of fracture network parameters are based on probability distribution functions, and are carried out randomly. In this study, a computational GFracIUT code is developed. In order to generate the 3D discrete fracture network and considering geometrical parameters of the fractures surveyed from the outcrops and boreholes, probability density functions are developed using geostatistical methods. In the mentioned code, initially the density of micro-fractures are conjectured using sequential Gaussian simulation. Then, the locations of the centres of the micro-fractures are determined by Poisson’s process. When the center locations of the micro-fractures are determined orientation components estimated using geostatistical approaches. The developed program is capable of modeling fractures with various geometrical shapes according to operator’s desired specifications. As examples in this regard, disc and quadrilateral shapes have been considered in this paper. In order to practically apply the program, an area in Gachsaran oil field has been considered as a case study.   Introduction Fracture is one of the main characteristics of the rock mass. Fracture network modeling by statistical method has some limitations. One of the limitations of the statistical methods for modeling fracture network is the lack of spatial behavior considerations of modeling fracture network parameters. Geostatistical methods can be employed to spatially characterize fracture network.   Methodology and Approaches First, using the GFracIUT code, we obtain the fracture density map by employing sequential Gaussian simulation method. Then, the location of the centre of each micro-fracture by Poisson’s process is determined using the software. Finally, the micro-fractures orientation component is estimated by geostatistical methods.   Results and Conclusions In this study, a computational GFracIUT code is developed. The GFracIUT code is composed of two steps: positioning the centers of fractures using the fractures density data by sequential Gaussian simulation, and assigning the directions (strikes and dips) of the fractures. In order to practically apply the software, an area in Gachsaran oil field has been considered as a case study.