Question #1: How does dissolution change with scale?
The core scale velocity ﬁeld of Portland (A) perpendicular to the axis of ﬂow with Sections 2, 4, 6, and 8 outlined in red. The probability density function of the velocity, PDF, is shown for each section and for the whole system in the sections along with all regions (B). The velocity ﬁelds of the corresponding pore scale experiments are shown in C for times 0, 30and 90 mins (C.1–3). The PDFs are plotted in D for times 0, 30, 60 and 90 mins.
Abstract: We have experimentally investigated the impact of heterogeneity on the dissolution of two limestones, characterised by distinct degrees of ﬂow heterogeneity at both the pore and core scales. The two rocks were reacted with reservoir-condition CO2-saturated brine at both scales and scanned dynamically during dissolution. First, 1 cm long 4 mm diameter cores were scanned during reactive ﬂow with a 4 μm voxel size between 10 and 71 times using 4D X-ray micro-tomography (μ-CT) over the course of 90 min. Second, 3.8 cm diameter, 8 cm longcores were reacted at the same conditions inside a reservoir-condition ﬂow apparatus and imaged using amedical-grade X-ray computed tomography scanner (XCT). Each sample was imaged ~13 times over the courseof 90 min at a 250 × 250 × 500 μm resolution. These larger cores were then scanned inside a μ-CT at a 27 μmv oxel size to assess the alteration pore-space heterogeneity after reaction. Both rock types exhibited channel widening at the mm scale and progressive high porosity pathway dissolution at the cm scale. In the more heterogeneous rock, dissolution was more focussed and progressed along the direction of ﬂow. Additionally, the dissolution pathways contained a distinct microstructure captured with the μ-CT that was not visible at the resolution of the XCT, where the reactive ﬂuid had not completely dissolved the internal pore-structure. This microstructure was further analyzed by performing a direct simulation of the ﬂow ﬁeld and streamline tracing on the image voxels.
We found that at the larger scales the interplay between ﬂow and reaction signiﬁcantly affects ﬂow in the unreacted regions of the core. When ﬂow is focussed in large reacted channels, this focusing is carried through to the unreacted parts of the rock where ﬂow continues to be conﬁned to preferential pathways after passing the reaction front. This focussing effect is greater with increasing pore space heterogeneity indicating that the representative elementary volume (REV) for dissolution is far greater than the dissolution front itself. This study of scale dependence using in situ 4D tomography provides insight into the mechanisms that control local reactionrates at the mm and cm scales. Furthermore, this work suggests that under these conditions at larger scales it is likely to be structural heterogeneity that dominates the pattern of dissolution and therefore the evolution of high permeability pathways.
Question #2: How can we upscale flow through microporosity to accurately predict permeability and relative permeability?
A core of Estalliades is scanned in the μCT (A) and the pores (red), solid grains (blue), and microporous grains (yellow) are identified. An interesting subsection is identified (B) and milled (C). A section of the milled section (D) is then scanned in the nano-CT (E). Figure Credit: Dr. Matthew G. Andrew.
The image processing workflow. The dry scan (A) is segmented using machine learning (B). The doped scan (C) is subtracted from the dry scan to get the difference image (D). The difference image greysale is then thresholded to 12 different porosity values and grains and then the pore space of segmented dry scan (B) is masked to create the 14-phase segmentation of solid grains, 12 types of microporous grains, and pores (E) Figure Credit: Dr. Hannah Menke
Significance: Understanding how micro porosity effects flow when upscaling to the pore-scale is imperative for accurate predictive modelling of flow in porous media. However, it is not currently possible to image at nanoscale resolutions on larger scales. Furthermore, models with trillions of voxels are computationally expensive, requiring high performance computing to solve their vast geometries. Carbonate rocks in particular often have complex and multiscale porosity structures that are poorly understood. In this study we use a combined experimental, modelling, and pore space generation methods to tackle the impact of micro porosity on the bulk flow properties of Estalliades limestone. First, a micro core of rock was scanned using x-ray microtomography (μCT) and a representative microporous region was identified. A nano core of rock was then milled using a laser lathe and scanned using x-ray nano tomography (Nano CT). The Nano CT scan was then used as input into the pore space generator and the permeability field was simulated for a range of porosities to create a synthetic Kozeny-Carman porosity-permeability relationship for micro porosity. We found a good match between experimental and simulated Mercury Intrusion Capillary Pressure (MICP) range in the imaged geometry and a good match between the imaged and object generated permeabilities and MICP.