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Abstract
The understanding of multiphase flow properties is essential for the exploitation of hydrocarbon reserves in a reservoir; these properties in turn are dependent on the geometric properties and connectivity of the pore space. The determination of the pore size distribution in carbonate reservoirs remains challenging; carbonates exhibit complex pore structures comprising length scales from nanometers to several centimeters. A major challenge to the accurate evaluation of these reservoirs is accounting for pore scale heterogeneity on multiple scales. This is the topic of this thesis.
Conventionally, this micron scale information is achieved either by building stochastic models using 2D images or by combining log and laboratory data to classify pore types and their behaviour. None of these capture the true 3D connectivity vital for flow characterisation. We present here an approach to build realistic 3D network models across a range of scales to improve property estimation through employment of X-ray micro-Computed Tomography (μCT) and Focussed Ion Beam Tomography (FIBT). The submicron, or microporous, regions are delineated through a differential imaging technique undertaken on x-ray CT providing a qualitative description of microporosity. Various 3-Phase segmentation methods are then applied for quantitative characterisation of those regions utilising the attenuation coefficient values from the 3D tomographic images. X-ray micro-CT is resolution limited and can not resolve the detailed geometrical features of the submicron pores. FIB tomography is used to image the 3D pore structure of submicron pores down to a scale of tens of nanometers. We describe the experimental development and subsequent image processing including issues and difficulties resolved at various stages.
The developed methodology is implemented on cores from producing wackstone and grainstone reservoirs. Pore network models are generated to characterise the 3D interconnectivity of pores. We perform the simulations of petrophysical properties (permeability and formation resistivity) directly on the submicron scale image data. Simulated drainage capillary pressure curves are matched with the experimental data. We also present some preliminary results for the integration of multiscale pore information to build dual-scale network models. The integration of multiscale data allows one to select appropriate effective medium theories to incorporate sub-micron structure into property calculations at macro scale giving a more realistic estimation of properties.