Multiscale study of statistical fractal DFN model and corresponding seismic images

The work addresses the development of a statistical model of a discrete fracture network (DFN) using core, outcrop, and seismic data. We consider the DFN model defined by the fractal distribution of fracture centers and a power-law distribution of fracture lengths. We perform the statistical analysis of model realization on different spatial scales to investigate the possibility to evaluate the corresponding correlation fractal dimension and power exponent. Reproducing the statistical parameters estimated from seismic images is investigated by comparison with the parameters of the original model. We conclude that the analysis of the finite subdomain of the considered model of fractures system makes it possible to estimate the model's statistical characteristics with a decrease in the system's linear size by about one order of magnitude. On the other hand, the system built on the base of seismic images does not reproduce the power-law probability density of fracture length distribution. Also, the distribution of fracture centers in this system does not reflect the fractal nature and is uniform. The results obtained in this work show that data obtained from outcrops and core samples can be used to build a statistical DFN model. On the other hand, an explicit DFN model cannot be recovered based on seismic data.