Simulation of enhanced oil recovery in naturally fractured reservoirs using dual-porosity models

Abstract

Carbonate reservoirs hold more than half of the world’s remaining oil reserves and around 40% of the world’s remaining gas reserves. Producing hydrocarbons from carbonate reservoirs can be very challenging as carbonate reservoirs are often highly heterogeneous, fractured, and with mixed- or oil-wet wettability, leading to low recovery factors after primary and secondary recovery methods. Surfactant injection is a chemically enhanced oil recovery method that can increase the recovery from fractured carbonate reservoirs by reducing the interfacial tension between wetting and non-wetting phases and reducing the capillary trapping forces. Surfactants can also change the wettability of oil- or mixed-wet reservoir rocks to more water-wet, which promote spontaneous imbibition of the wetting phase and increase the recovery. This thesis aims to identify and analyse the limitations of dual-porosity models when predicting the performance of chemically enhanced oil recovery methods in naturally fractured reservoirs. Dual-porosity models are an idealised concept used to model fractured porous media. Dual-porosity models consist of two distinctive domains: the low-permeability matrix (providing storage) and the high-permeability fractures (providing flow), which are connected via a transfer function that describes the fluid exchange between both domains. The central hypothesis of this thesis is that dual-porosity models do not capture all the underlying physiochemical processes during chemically enhanced oil recovery, and hence there is a need to develop improved solutions to model fracture-matrix transfer for these applications more accurately. This thesis demonstrates how multiple interacting continua (MINC) or vertical refinement (VR) models can be optimised without increasing the complexity of the transfer functions itself to yield significantly more accurate recovery results when modelling chemically enhanced oil recovery in fractured reservoirs compared to the classical dual-porosity model or unoptimised MINC and VR models. Furthermore, this thesis shows that accurately configured MINC and VR models are important when performing large-scale reservoir simulations because inadequately configured dual-porosity models add another uncertainty when predicting reservoir performance during waterflooding or surfactant injection in fractured reservoirs. As a key result, this thesis clearly demonstrates the potential of using optimised MINC and VR models to analyse the performance of fractured reservoirs and highlight the error associated when using unoptimised MINC and VR or classical dual-porosity models. The findings of this thesis can be applied in other scenarios, including contaminant transport in groundwater resources, heat flow in high-enthalpy geothermal applications, reactive transport during subsurface flow, or CO2 storage.