Inverse Fracture Model Integrating Fracture Statistics and Well-testing Data
Abstract
Heterogeneity and poor connectivity of fractures make it difficult to characterize fracture networks and predict flow behavior on them. Previous studies have introduced inversion models integrating the observed pressure data to describe flow patterns. However, they could not consider the statistical properties of fractures because the models are based on regular lattice or continuum approaches. A new inverse fracture model, which simultaneously integrates fracture characteristics, fluid flow, and solute transport data, is proposed. Discretization for the fracture-occurrence points makes it possible to incorporate fracture properties in the inversion. Fluid flow is implemented by the cubic law, and a semi-analytical method is used to include the solute transport data due to its efficient performance. The model can interpret the characteristics of the geometry and conductivity between wells within fractured reservoirs, since the inverse fracture network not only has the same fracture characteristics as observed data, but also reproduces the fluid flow and solute transport data. It is demonstrated that the fracture network that is developed makes responses for additional flow and transport predicted within a reasonable error range.