3D Characterisation of Potential CO2 Reservoir and Seal Rocks
Golab, Alexandra¹; Romeyn, Rowan²; Averdunk, Holger²; Knackstedt, Mark¹; Senden, Tim²
¹Digitalcore Pty Ltd, Canberra, ACT, Australia.
²Applied Mathematics, Australian National University, Canberra, ACT, Australia.
Digital core analysis incorporating 3D microfocus X-ray computed tomography (μCT) imaging in 3D, and registration of 2D Scanning Electron Microscope (SEM) and SEM-Energy Dispersive X-ray Spectra (EDS) images into the 3D tomograms, offers an extensive and unique toolbox for characterising potential CO&sub2; reservoir and seal candidates. μCT imaging can be performed at multiple scales on nested cylinders of plugs to characterise features at different scales. The plug can also be imaged in different states after flooding to characterise in 3D, e.g. connected porosity, mineral reactivity, or residual trapping. From μCT imaging one can calculate connected porosity and subsequently properties such as permeability, formation factor, Archie's cementation component, drainage capillary pressure, and Swi can be determined digitally and pore-throat network models can be generated. Sub-micron scale features in the 3D image can be directly correlated with high-resolution SEM images, at the nanometre scale, using 2D-to-3D image registration. Additionally, the in situ mineralogy can be quantified by using an automated mineral and petrological analysis (SEM-EDS) system. The mineralogy determined in 2D by SEM-EDS can then be interpolated into the 3D tomogram for the direct identification of minerals due to contrasting X-ray attenuation. The 3D data can be readily displayed using 3D visualisations that show the pore connectivity, 3D mineralogy, geological structures, and incorporating the pore-throat network model, SEM, and 2D in situ mineral map. Additionally the porosity and flow pathways of a potential seal rock can be characterised at the nanoscale (pores 10-30 nm) using Focussed Ion Beam SEM (FIBSEM) imaging. The behaviour of the potential reservoir and seal rocks during interaction with supercritical CO&sub2; and water can be directly investigated by coupling digital core analysis with a high pressure cell. Multiple images can be collected of the same plug before, during and after interaction with CO&sub2; and water to directly characterise in 3D the CO&sub2; trapping, and changes to the pore/throat geometries and mineralogy due to interactions with the CO&sub2;. Examples of multiple scale digital core analysis of different lithologies of potential reservoir and seal rocks will be discussed.
X-ray micro-computed tomography (μCT) involves three-dimensional X-ray imaging, like medical CT scans but on a smaller scale, and with higher resolution. μCT is an established and rapidly evolving technology routinely used for a wide variety of materials at micron scales including petroleum geology, e.g. clastic (Golab et al. 2010) and carbonate (Arns et al. 2005b), and coal (Golab et al. 2012). Developments are ongoing in the area of digital imaging of core material at the pore scale in 3D using μCT, enabling the understanding of petrophysical response, multiphase flow properties and geological heterogeneity (Arns et al. 2005a). μCT is a non-destructive imaging method that achieves resolutions in the range of 50µm down to 0.5µm (Varslot et al. 2011). The X-ray attenuation of any material is a function of both its physical density and effective atomic number (Van Geet et al. 2001). Within a tomogram, the X-ray attenuation of a material determines its brightness, i.e. voids are black, while Fe-bearing minerals are usually light grey due to high X-ray opacity and Al-bearing minerals are usually mid-grey due to intermediate X-ray opacity.
The images shown in this extended abstract were acquired using the high-resolution and large-field X-ray μCT facility of ANU/Digitalcore Pty Ltd, Canberra. This facility is unique in that it performs helical μCT imaging with theoretically exact reconstruction methods at very high cone-angles (Varslot et al. 2011). The plugs shown in this abstract were imaged using μCT analysis yielding >2000³ voxels, by the methodology described in Varslot et al. (2010, 2011).
Carbon capture and storage schemes designed to decrease CO&sub2; emissions require comprehensive characterisation of the reservoir and seal. This is a challenging because CO&sub2; has different characteristics to the fluids it would replace such as water, brine, oil and gas. For example, in its supercritical state, CO&sub2; has a lower density than water, lower surface tension and a viscosity around ten times less which together indicate that supercritical CO&sub2; could penetrate through confining layers more easily than water. Further, CO&sub2; when dissolved as carbonic acid, is reactive and could therefore change the permeability, storage capacity, and sealing effectiveness of the reservoir. Clearly detailed knowledge of the behaviour of CO&sub2; at the pore scale is vital and imaging by μCT has the capacity to help in this area.
Identification of minerals
For minerals to be directly identified in tomographic images there must be contrasts in X-ray attenuation, however minerals with similar composition commonly overlap e.g. quartz and alkali feldspar (Tsuchiyama et al. 2000). When detailed 2D mineralogical images (SEM-EDS and/or SEM) are coupled with μCT images this extends the mineral identification capacity of μCT (e.g. Fig. 1).
Challenges Associated with Seals
Seal rock quality cannot be predicted accurately from porosity alone, especially in rock units with significant diagenesis (Rushing et al. 2008). To understand and predict the integrity of a potential seal, the various porosity types need to be differentiated and quantified, and the connectivity in 3D and contribution to overall porosity and flow needs to be characterised. A multi-scale 3D approach to the characterisation of the porosity, pore and throat size distribution, pore connectivity, permeability and petrophysical response is required to better characterise seal candidates. This will include characterising the heterogeneity and connectivity of the key constituents (e.g., porosity, cements, clays, minerals) at the micron to millimetre scale and imaging and analysing the porosity, pore throats and connectivity at the nanoscale of these different constituent phases (Golab et al., In Press).
Characterisation of Reservoir Candidates
To characterise potential reservoir rocks by digital core analysis, plugs of usually 25-38mm diameter are used. Heterogeneous plugs are imaged by 3D μCT analysis at the full plug scale by the methodology described in Varslot et al. (2010, 2011). These 3D images are then used to select a region to extract a sub-plug (2-10mm diameter) for the calculation of petrophysical properties. The sub-plug is then imaged by μCT analysis yielding >2000³ voxels at <2μm resolution. For example, Fig. 1 shows a slice in the Z-plane from the tomogram of an 8mm diameter sub-plug of a quartz sandstone potential reservoir. The 3D image was digitally segmented into key phases based on the X-ray attenuation, yielding the volume percentages of each phase, in this case 22.1% porosity. The connectivity of the porosity is determined in 3D in this case 99% connected and properties can be calculated such as permeability, formation factor, Archie's cementation component, drainage capillary pressure, and Swi and pore-throat network models can be generated, as described in Arns et al. (2005a).
2D-to-3D image registration allows one to investigate sub-micron scale features in the 3D image using high-resolution microscopy data. This is achieved by cutting the sub-plug along a plane of interest within the 3D field of view and polishing the face for imaging by Scanning Electron Microscope (SEM) (e.g. Fig. 1). Latham et al. (2008) described the 2D-to-3D registration technique used to register the 2D SEM image to the corresponding slice of the tomogram into perfect geometric alignment, whereby the software searches throughout the entire >2000³ voxel block for the exact slice that matches the SEM. The higher-resolution SEM image (nm scales can be probed) allows the evaluation of pore-filling material and identification of microporous regions. The polished section can also be analysed by an automated mineral and petrological analysis (SEM-EDS) system that quantifies the in situ mineralogy (Gottlieb et al. 2000). The quantified in situ mineralogy map of the registered polished section (e.g. Fig. 1) allows one to directly calibrate the mineralogy to the tomogram and SEM. The 3D image data can be displayed using 3D visualisations that show the pore connectivity, 3D mineralogy (e.g. Fig 2), geological structures, and can incorporate the pore-throat network model, SEM, and 2D in situ mineral map (Knackstedt et al., 2010).
Characterisation of Seal Candidate
Numerous aspects of a seal need to be characterised in 3D, including the geometry and nature of porosity, the connectivity of the porosity and fractures, and the distribution and nature of organics and mineral components and digital core analysis allows this to be done at multiple scales. As for a reservoir rock, the seal can be imaged by μCT (e.g. Fig. 3) and the porosity can be investigated in 3D. Subsequently an SEM image can be acquired for a polished section and the images can be registered to one another (e.g. Fig. 3). Also, automated SEM-EDS can be used to quantify the in situ mineralogy and by registering the mineral map, it is possible to determine which minerals are porous (e.g. Fig. 3). The mineralogy can also be interpolated into the 3D μCT image block to check on the connectivity of microporous minerals. Additionally the porosity and flow pathways of the seal rock can be characterised at the nanoscale (pores 10-30 nm) using FIBSEM imaging.
A method has also been developed that allows the determination of connectivity of pores that are smaller than the resolution of the μCT imaging technique and this is described in Golab et al. (2010). Briefly the plug is imaged in 3D in its native state by μCT and then saturated with an X-ray dense fluid and imaged again by μCT. The two 3D images are then registered to one another using the method described in Latham et al. (2008). Image registration brings into geometric alignment two or more images, taken at different times, from different orientations and/or by different instruments. In the case of 3D-to-3D registration, the entire overlapping blocks of >2000³ voxels are aligned to one another in all three dimensions, so that all voxels within an image coincide in each tomogram. By comparing the two images with one another it is possible to characterise the connectivity of pores and fractures in 3D because only those features that are connected will have become saturated with the attenuating fluid.
Carbonic Acid Reactivity Study
Some of the injected CO&sub2; will dissolve in the pore fluid forming carbonic acid, which may react with certain minerals causing the mechanical or hydraulic properties of the rock to change. Muller (2010) demonstrated the importance of the aqueous phase to the reactivity observed in CO&sub2; sequestration scenarios. A simple single phase carbonic acid experiment was designed to give an indication of CO&sub2; reactivity relevant to sequestration scenarios. Mardie Greensand which contains an array of reactive minerals including ankerite, siderite, and iron-rich glauconitic clays was selected to investigate changes induced by exposure to carbonic acid. A 4 mm subplug of the sample was treated to make it water wet and then imaged (Fig. 4). The sample was subsequently partially immersed in a 10 g/L NaCl brine solution so that it was saturated via capillary rise. The vessel containing the solution and sample was subjected to 1000 kPa pCO&sub2; at room temperature for 329 hours. The subplug was flushed with deionised water for 3 days and then re-imaged (Fig. 4) using the methodology described in Golab et al. (In Press).
The temperature and pressure conditions were milder than those typical of geological CO&sub2; storage scenarios but some reactivity was observed following the two weeks of exposure. This is clearly demonstrated by comparing the tomographic images (Fig. 4) and the difference tomogram created after 3D to 3D registration (Fig. 4). The difference tomogram illustrates that the changes induced by carbonic acid exposure occurred in localised regions of the plug and were dominated by a loss of material. In addition to being spatially disjointed, the observed reactivity was heterogeneous mineralogically, i.e. not all grains of a particular mineral exhibited similar reactivity. Regions of ankerite-glauconite intergrowth, as shown in Fig. 4, seem to be particularly susceptible to dissolution by carbonic acid. The reactive glauconite pellets tend to exhibit significant internal porosity that may present a large reactive surface area and subsequently promote attack by carbonic acid. Some disaggregation of glauconite particles from the larger pellets may occur as the contact surfaces between the particles are dissolved, enhancing the visible degradation of the pellet.
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Fig. 1. Registered images of a horizontal plane through a plug of potential reservoir rock; (top left) slice of 3D tomogram, (top right) segmentation into pore (black), clay (dark grey), and grain (light grey and white), (bottom left) matching SEM, and (bottom right) matching SEM-EDS mineralogy map. Horizontal FOV = 4mm.
Fig. 2. Example of 3D visualisation of a potential reservoir rock: (left) distribution of porosity (blue), clay (green), carbonate (purple) and heavy mineral (red); (middle) distribution of clay (green), carbonate (purple) and heavy mineral (red); and (right) distribution of porosity (blue). Sub-plug diameter = 6mm.
Fig. 3. Registered images of a selected region of a potential seal rock: (top left) slice of 3D tomogram, (top right) matching SEM, and (bottom left) matching SEM-EDS mineralogy map. Horizontal FOV = 3mm. (After Golab et al. In Press).
Fig. 4. Registered μCT images of a selected region of the horizontal plane through a 4mm sub-plug of Mardie Greensand (after Golab et al., In Press): (left) initial state, (middle) following treatment with carbonic acid for 329 hours under 1MPa pCO&sub2; and room temperature, and (right) the difference between the two tomograms; dark regions represent a loss of material (e.g. dissolution or particle removal) and light regions indicate material has been gained (e.g. precipitation or particle dislocation). FOV = 0.8 x 0.7mm.
AAPG Search and Discovery Article #90155©2012 AAPG International Conference & Exhibition, Singapore, 16-19 September 2012