Reservoir quality determination and modelling of unconsolidated Canadian Oil Sands reservoir following analytical techniques

Abstract

Canadian Oil Sands covering an area of 142,000KM2 boasts one of the largest heavy oil proven reserves standing at 166 Bbbl. This volume makes it a promising prospect for the future of the oil and gas industry. Though, having large reserves it is not the easiest to produce from. The oil in this region is categorized as heavy, extra heavy to bituminous which means that it is highly viscous and incapable of flowing without reducing viscosity. Furthermore, the Geology for this reservoir is heterogeneous with bioturbated sections which adds to the complexity. Additionally, lack of cementing matrix within formation makes this reservoir an unconsolidated reservoir. The unconsolidated nature introduces challenges during routine core analysis leading to the inaccurate results and in certain cases questions reliability of the methodology followed to assess this reservoir. The lack of any reliable work flow with methodologies act as a primary research gas for this thesis.

Owing to aforementioned reasons, this study aims to establish a new workflow to determine properties from unconsolidated reservoirs, that includes use of Thin section analysis, Scanning Electron Microscopy (SEM), micro-CT techniques followed by image analysis to determine morphological and reservoir properties to simulate the reservoir to test applicability of the said workflow.

To achieve set aims this research has made good use of thin sections that were
prepared from outcrop samples and has followed further with detailed studies on core samples. Analysis of the thin sections has demonstrated arrangements. SEM and micro CT are able to provide properties more reliably than RCAL analysis. The simulations developed to test applicability of the properties followed has demonstrated variations to the recovery that can be observed by applying variety of porosity and permeability determined following the workflow of this thesis. Furthermore, the effect of bioturbation can also be observed with variation to the production volume observed as part of the simulation results.

Date of Award	Feb 2018
Original language	English
Awarding Institution	University of Portsmouth
Supervisor	Mohamed Hassan Sayed (Supervisor), Richard Wheaton (Supervisor) & David Franklin (Supervisor)