The Department of Chemical Engineering is proud to announce the Dissertation Defense of Ph.D. candidate Jing Zhou.

"Hydraulic Fracture Propagation Modeling and Data-based Fracture Identification”

Advisor: Dr. Milind Deo
Date: Thursday, October 22, 2015
Place: 2:00pm in EGI 334 (EGI Conference Room)

Successful shale gas and tight oil production is enabled by the engineering innovation of horizontal drilling and hydraulic fracturing. Hydraulically induced fractures will most likely deviate from the bi-wing planar pattern and generate complex fracture network due to the mechanical interactions and reservoir heterogeneity, both of which render the conventional fracture simulators insufficient to characterize the fractured reservoir. Moreover in reservoir with ultra-low permeability, the natural fractures are widely distributed which will result in hydraulic fractures branching and merging at the interface and consequently lead to the creation of more complex fracture network. Thus, developing a reliable hydraulic fracturing simulator including both mechanical interaction and fluid flow is critical in maximizing the hydrocarbon recovery and optimizing completion strategy in multi-stage horizontal wells.

A novel fully coupled reservoir flow and geomechanics model based on the dual-lattice system is developed to simulate multiple non- planar fractures propagation in both homogeneous and heterogeneous reservoirs with or without natural fractures. Initiation, growth and coalescence of the microcracks will lead to the generation of macroscopic fractures, which is explicitly mimicked by failure and removal of bonds between particles from the discrete element network. This physics-based modeling approach leads to realistic fracture patterns without using of empirical rock failure and fracture propagation criteria required in conventional continuum methods. Based on this model, a sensitivity study is performed to investigate the effects of perforation spacing, in-situ stress anisotropy, rock properties (Young’s modulus, Poisson’s ratio and compressive strength), fluid properties and natural fracture properties on hydraulic fracture propagation.

In addition, since that reservoirs are buried thousands feet below the surface, the parameters used in the reservoir flow simulator have large uncertainty. Those biased and uncertain parameters will result in misleading oil and gas recovery predictions. Ensemble Kalman Filter will be used to estimate and update both the state variables (pressure and saturations) and uncertain reservoir parameters (permeability). In order to directly incorporate the spatial information such as fracture location and formation heterogeneity into the algorithm, a new covariance matrix method is proposed. This new method has been applied to a simplified single phase reservoir and a complex black oil reservoir with complex structures to prove its capability in calibrating the reservoir parameters.