Modelling of hydraulic fracturing in unconventional reservoirs

Hydraulic fracturing (HF) is a process of fluid injection into the well in order to create tensile stresses in the rock to overcome the tensile strength of the formation. In this study, the development and application of a fuzzy model to predict the efficiency of hydraulic fracturing is presented with application in a coal mine as an unconventional reservoir. The most important parameters affecting the HF process of a coal seam are: dip, thickness, seam uniformity, roof and floor conditions, reserve of coal seam and coal strength. In the developed model, the efficiency of hydraulic fracturing of coal seams is calculated as a dimensionless numerical index within the range 0-100. The suggested numerical scale categorizes the efficiency of HF of seams to very low, low, medium, high and very high, each one being specified by a numerical range as a subset of the above range (0-100). HF in the coal bed in PARVADEH 4 Tabas mine in Iran is investigated as a case study. The results show that the developed model can be used to identify seams that have high potential for HF Moreover, a three-phase hydro-mechanical model is developed for simulating hydraulic fracturing. The three phases include: porous solid, fracturing fluid and reservoir fluid. Two numerical simulators (ANSYS Fluent for fluid flow and ANSYS Mechanical for geomechanical analysis) are coupled together to model multiphase fluid flow in hydraulically fractured rock undergoing deformations, ranging from linear elastic to large, nonlinear inelastic deformations. The two solvers are coupled, using system coupling in ANSYS Workbench. The coupled problem of fluid flow and fracture propagation is solved numerically. The fluid flow model involves solving the Navier-Stokes equations using the finite volume method. The flow model is coupled with the geomechanics model to simulate the interaction between fluid flow inside the fracture with rock deformations. For any time step, the pore pressures from the flow model are used as input for the geomechanics model for the determination of stresses, strains, and displacements. The strains derived from the gomechanics model are in turn used to calculate changes to the reservoir parameters that are fed as input to the flow model. This iterative process continues until both (fluid and solid) models are converged. The laboratory-scale study of hydraulic fracturing in the Second White Specks (SWS) shale was simulated using the developed model. The numerical and experimental results were compared. Comprison of the results shows that the numerical model can predict the behaviour of the shale under hydraulic fracturing with a good accuracy

Developing a risk assessment model using fuzzy logic to assess groundwater contamination from hydraulic fracturing

Technological advances in directional drilling has led to rapid exploitation of onshore unconventional hydrocarbons using a technique known as hydraulic fracturing. This process took off initially in the US, with Canada following closely behind, but brought with it controversial debates over environmental protection, particularly in relation to groundwater contamination and well integrity failure. Prospective shale gas regions lie across areas in Europe but countries such as the UK are facing public and government turmoil surrounding their potential exploitation. This extent of energy development requires detailed risk analysis to eliminate or mitigate damage to the natural environment. Subsurface energy activities involve complex processes and uncertain data, making comprehensive, quantitative risk assessments a challenge to develop. A new, alternative methodology was applied to onshore hydraulic fracturing to assess the risk of groundwater contamination during well injection and production. The techniques used deterministic models to construct failure scenarios with respect to groundwater contamination, stochastic approaches to determine component failures of a well, and fuzzy logic to address insufficiency or complexity in data. The framework was successfully developed using available data and regulations in British Columbia (BC), Canada. Fuzzy Fault Tree Analysis (FFTA) was demonstrated as a more robust technique compared with conventional Fault Tree Analysis (FTA) and implemented successfully to quantify cement failure. A collection of known risk analysis methods such as Event Tree Analysis (ETA), Time at Risk Failure (TRF) and Mean Time To Failure (MTTF) models were successfully applied to well integrity failure during injection, with the novel addition of quantifying cement failures. An analytical model for Surface Casing Pressure (SCP) during well production highlighted data gaps on well constructions so a fuzzy logic model was built to a 93% accuracy to determine the location of cement in a well. This novel application of fuzzy logic allowed the calculation of gas flow rate into an annulus and hence the probability of well integrity failure during production using ETA. The framework quantified several risk pathways across multiple stages of a well using site-specific data, but was successfully applied to a UK case study where there existed significant differences in geology, well construction and regulations. The application required little extra work and demonstrated the success and limitations of the model and where future work could improve model development. This research indicated that risks to groundwater from hydraulic fracturing differ substantially depending on well construction. Weighing up the risk to groundwater compared with financial gain for well construction will be essential for decision-makers and policy. To reduce the social anxiety of hydraulic fracturing in the UK, decision-makers who face criticism must ensure information is disseminated properly to the public with a well-defined risk analysis which can be interpreted easily without prerequisite knowledge. Finally, although this research is based on onshore hydraulic fracturing, the risk assessment techniques are generic enough to allow application of this research to other subsurface activities such as CO2 sequestration, waste injection disposal and geothermal energy.Engineering and Physical Sciences Research Council (EPSRC