Modeling natural fracture network using object-based simulation

We implemented the object-based method using marked point processes to generate a natural fracture network honoring an assumed fracture characteristics' distribution where the fractures are two-dimensional zero-thickness circular disks. Fractures are divided into two groups based on their alignment which is acquired by Monte Carlo sampling from two Gaussian distributions with 90-degree shift in the mean value; this hypothesis is validated considering the frequently observed checker-board fracture patterns in the outcrops. The growth of the fractures in the second group or the secondary (daughter) fractures can be terminated by a criterion derived from the distribution of the fractures in the first group or the primary (parent) fractures. For data assimilation purposes, a smooth seismic distribution for fracture density is mimicked by simple krigging which inherently possesses a smoothing nature. Then, the generated seismic data is honored by revising the fracture distribution such that in areas with less fracture density we have fewer fractures. This work provides a novel, yet easy and fast workflow to stochastically model a natural fracture network following the attributes offered by seismic data and concludes an orthogonal or bidirectional fracture pattern. This pattern can be easily extended for multi-directional fracture patterns using the proposed framework.