Observations from field monitoring indicate the presence of existing fracture networks significantly affect, and may control, the history of hydraulic treatments. Existing fractures allow pathways for treatment fluids to migrate efficiently through the formation, stimulating connectivity to larger reservoir volumes. This paper examines the relationship between hydraulic treatments and fracture networks, and investigates the ability to engineer the hydraulic conductivity of the stimulated volume. Fracture network engineering (FNE) involves the engineering design of rock mass disturbance through the use of advanced techniques to model fractured rock masses numerically, and then correlate field observations with simulated fractures generated within the models. Modeling algorithms accurately address the hydromechanical physics of hydraulic treatments developed across a range of applications in rock engineering.
A Synthetic Rock Mass (SRM) model is constructed by explicitly defining a discrete fracture network within a modeled rock matrix. Hydraulic treatment into the SRM allows fracture dilatancy, propagation and shearing to be realized in the emergent behavior of the bonded particle model in three dimensions and at the scale of the treated volume. Simulated microseismicity is generated when the fractures are disturbed or propagated providing a method for correlation with field observations. Illustrative models show how hydraulic treatments stimulate fracture networks and generate new hydraulic fractures in volumes not expected in conventional design analysis connecting existing fractures with preferential alignment. By combining SRM models with field observations it is possible to investigate the relation and sensitivity of hydraulic treatments to existing fracture networks, and therefore, engineer the most optimal use of these fractures in the performance of a given project. Developmental challenges are discussed, including the sensitivity of the techniques to fracture network uncertainties and the accurate representation of microseismic source data within the models.