A Closer Look at Pore Geometry - ANU

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X-ray computed tomography has advanced the field of medicine for more than 30 years. For nearly as long ..... For more on high-resolution X-ray CT: University of Texas. High-Resolution ..... at the IADC/SPE Drilling Conference, Miami, Florida,.
A Closer Look at Pore Geometry

X-ray computed tomography has advanced the field of medicine for more than 30 years. For nearly as long, it has also been a valuable tool for geoscientists. Improvements in the technology are helping geoscientists uncover greater detail in the internal pore structure of reservoir rock and achieve a better understanding of conditions that affect production.

Andreas Kayser Cambridge, England Mark Knackstedt The Australian National University Canberra, Australia Murtaza Ziauddin Sugar Land, Texas, USA For help in preparation of this article, thanks to Veronique Barlet-Gouédard, Gabriel Marquette, Olivier Porcherie and Gaetan Rimmelé, Clamart, France; Bruno Goffé, Ecole Normale Supérieure, Paris; and Rachel Wood, The University of Edinburgh, Scotland. Inside Reality and iCenter are marks of Schlumberger.

Information gained through core analysis is invaluable for predicting the producibility of a reservoir pay zone. While other methods enable petrophysicists to estimate grain size, bulk volume, saturation, porosity and permeability of formations, core samples often serve as the benchmark against which other methods are calibrated. However, notwithstanding several hundred thousand feet of whole or slabbed core residing in core libraries around the world, most wells are not cored.

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The wealth of information obtained from cores comes at a price. Coring often increases rig time, lowers penetration rates and increases the risk of sticking the bottomhole assembly. At some wells, hostile downhole or surface conditions make coring too risky. In other cases, correlations are not sufficient to allow geologists to accurately and confidently pick coring points. Instead, many operators rely on sidewall cores obtained through prospective pay zones, and may compensate for lack of whole core data by supplementing their usual logging program with a wider range of measurements.

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As oil companies try to drain aging reservoirs more efficiently, engineers and geoscientists may come to regret earlier decisions to forgo coring. Once a well has been drilled through a pay zone, it is too late to go back to obtain whole cores, unless the well is sidetracked. However, mineralogy, grain size, saturation, permeability, porosity and other measures of rock fabric can sometimes be determined without coring. With improvements on the early medical CATscan technique developed in 1972, geoscientists can take a series of fine, closely spaced X-ray scans through a rock sample to obtain important information about a reservoir.1 Using a nondestructive technique called microcomputed tomography, a focused X-ray beam creates “virtual slices” that can be resolved to a scale of microns, not just millimeters.2 These refinements also allow the option of examining smaller samples of rock; instead of depending on whole cores for porosity and permeability measurements, geoscientists can now use formation cuttings to estimate these properties.3 Although many companies do not core their wells, they usually employ the services of a mudlogger to catch formation cuttings as they come over the shale shaker. When they don’t have core, geoscientists are finding that a sliver of rock can be highly revealing. This article reviews the development of X-ray computed tomography (CT) and the ensuing technology transfer from medical to oilfield applications. We describe how the data can be evaluated using immersive visualization techniques and discuss a range of oilfield applications that may benefit from this technology. Finally, we will see how this technology served researchers in their evaluation of casing cement and well stimulation treatments. CT Scan Technology Originally developed for medical use by Godfrey Newbold Hounsfield in 1972, computed tomography uses X-ray scans to investigate internal structures within a body, such as those of soft tissue and bone.4 CT overcomes the problem of superimposition exhibited in conventional X-ray radiography when three-dimensional features of internal organs are obscured by overlying organs and tissues imaged on two-dimensional X-ray film. Rather than projecting X-rays through a patient and onto a film plate, as with conventional X-rays, the CT process takes a different approach. The CT scanner uses a rotating gantry to which an X-ray tube is mounted opposite a detector array. The patient is

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placed in the center of the gantry, while the opposing X-ray source and detectors rotate around the patient. With the patient positioned roughly in the middle of the source-receiver plane, the rotating gantry allows a series of closely spaced radiographic scans to be obtained from multiple angles. These scans, or radiographic projections, can then be processed to obtain a 3D representation of the patient (below). CT radiographic projections are based on the differential attenuation of X-rays caused by density contrasts within a patient’s body. This

patient from this equation, attenuation is a function of the energy of the X-ray as well as the density and atomic number of the elements through which the X-ray passes. The correlation is fairly straightforward: lower-energy X-rays, higher densities and higher atomic numbers generally result in greater attenuation.5 Digital projection data are converted into a computer-generated image using tomographicreconstruction algorithms to map the distribution of attenuation coefficients.6 This distribution can be displayed in 2D slices, composed of points that are shaded according to their attenuation

> Thoracic CAT scan. Manipulating color and opacity values of different tissues provides physicians with an unobstructed view of a patient’s lungs and skeletal system. (Image courtesy of Ajay Limaye, VizLab, The Australian National University.)

attenuation represents a decrease in energy as X-rays pass through various parts of the body. Some tissues scatter or absorb X-rays better than others: thick tissue absorbs more X-rays than thin; bone absorbs more X-rays than soft tissue, while fat, muscle or organs allow more X-rays to pass through to the detectors. Removing the

values (see “Moving from 2D Points to 3D Volumes,” page 6). Thus, in hospital scans, bone would typically be assigned a light color to correspond with its comparatively high attenuation value, while air-filled lung tissue might be assigned a darker color corresponding to low attenuation values.

1. In the medical field, the computerized axial tomography (CAT) scan is sometimes also called computer-assisted tomography, and is synonymous with computed tomography. 2. A micron, or micrometer, is equal to one millionth of a meter, or more commonly, one thousandth of a millimeter. It is abbreviated as µ, µm or mc. In English measure, a micron equals 3.937 x 10-5 in. 3. Siddiqui S, Grader AS, Touati M, Loermans AM and Funk JJ: “Techniques for Extracting Reliable Density and Porosity Data from Cuttings,” paper SPE 96918, presented at the SPE Annual Technical Conference and Exhibition, Dallas, October 9–12, 2005. Bauget F, Arns CH, Saadatfar M, Sheppard AP, Sok RM, Turner ML, Pinczewski WV and Knackstedt MA: “What

is the Characteristic Length Scale for Permeability? Direct Analysis from Microtomographic Data,” paper SPE 95950, presented at the SPE Annual Technical Conference and Exhibition, Dallas, October 9–12, 2005. 4. Hounsfield GN: “A Method of and Apparatus for Examination of a Body by Radiation such as X- or Gamma Radiation,” British Patent No. 1,283,915 (August 2, 1972). 5. For more on X-ray CT: Publication Services Department of the ODP Science Operator. http://wwwodp.tamu.edu/publications/185_SR/005/005_5.htm (accessed January 27, 2006). 6. Feldkamp LA, Davis LC and Kress JW: “Practical Cone-Beam Algorithm,” Journal of the Optical Society of America A1, no. 6 (June 1984): 612–619.

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Moving from 2D Points to 3D Volumes

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> Pixel resolution. The sharpness and clarity of an image are affected by pixel count and the size of the pixels. To increase the number of pixels within a fixed space, pixel size must be reduced. As pixel size (in white) progressively decreases (left to right), more pixels can be used to provide greater detail in the image.

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In the mid-1880s, Neo-Impressionist artist Georges Seurat perfected a revolutionary technique of painting with tiny dots of color. Like Michel Chevrul before him, Seurat recognized that from a distance, the eye would naturally blend together tiny dots of primary colors to produce secondary shades. Using tiny brush strokes, Seurat and his contemporaries captured scenes of cityscapes, harbors and people at work and leisure. This technique came to be known as pointillism. Computers use a similar technique to display text and images; however, they work at a much finer scale. Every image portrayed on a computer monitor or video screen is composed of many, almost imperceptibly tiny dots, spaced at extremely close intervals. In a 2D picture screen, each dot, or pixel (a word formed from the contraction of picture element) can be defined by its horizontal (x) and vertical (y) screen coordinates. It is also defined by its color value. In color images, each pixel is also assigned its own brightness. The number of shades that a pixel can take on depends on the computer and the number of bits per pixel (bpp) it is capable of processing. Common values range from 8 bpp (28 bits, which translates to 256 colors) to 24 bpp (224 bits, or 16,777,216 colors). On an eight-bit gray-scale image, for instance, each pixel would be assigned a value corresponding to a shade of gray, ranging from 0 to 255, where 0 represents black and 255 represents white. The number of pixels used to create an image controls its resolution (above right). As more pixels are used, the image can be portrayed in greater detail, or higher resolution. Resolution is thus initially impacted by the image acquisition system and later, by the image display system. Resolution in digital image acquisition systems is largely governed by the number of light-sensitive photoreceptor cells, known as photosites, which are used to record an image. These photosites (more commonly referred to

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> Pixel to voxel. A flat pixel (left) takes on a new dimension when the slice on which it resides is stacked with other slices to form a volume (right). Adding the z-coordinate of the slice number essentially assigns a depth-value to the pixel, thus creating a voxel within the stack of slices.

as pixels) accumulate charges corresponding to the amount of light passing through the lens and onto each cell.1 As more light falls onto a photosite, the charge grows. Light is shut off to the lens once the shutter closes, at

which point the charge in each cell is recorded by a processing chip and converted to a digital value that determines the color and intensity of individual pixels used to display the image on screen. Resolution in these

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devices is often expressed not in terms of photosites, but rather in megapixels. A 1.2-megapixel device, for instance, might have an area of 1,280 x 960 (1,228,800 pixels), while higher resolution would be attained by a 3.1megapixel device measuring 2,048 x 1,536 (3,145,728 pixels). Image resolution can then be affected by the medium on which it is displayed. A relatively low-resolution computer monitor might be described as a 640 x 480 display. This means that the monitor has a width of 640 pixels, spread across a height of 480 lines, totaling 307,200 pixels. If those pixels were spread across a 15-inch monitor, then any image displayed on that monitor would be allotted 50 dots per inch. To increase resolution, either the screen size must be reduced or more pixels must be packed into the screen. Modern applications generally take both approaches, squeezing a huge number of pixels into a smaller area. To image a 3D object, the pixel is expanded into another dimension. A third coordinate (z) is added to the x-y location to precisely define the pixel’s position within the volume of a 3D object, thereby creating a voxel— short for volume pixel. In CT images, the z-coordinate often denotes depth, and is dictated merely by the position that a tomographic slice holds within a volume formed by stacking together numerous closely spaced slices (previous page, bottom). In addition to x, y and z coordinates, a voxel can define a point by a given attribute value. In the case of CT scans, that value is density, which is a function of the sample’s transparency to X-rays. Density values can be tied to a color spectrum, while a range of intensities can control the opacity of a voxel on a computer screen. With this information and 3D rendering software, a two-dimensional image of a 3D object can be generated for viewing at various angles on a computer screen.

Evolving to Industrial Strength Density contrasts within a rock body can be imaged just as they can within a human body (below). By the mid 1980s, CT technology was making significant inroads into geoscience applications. In addition to quantitative determination of bulk density of rock samples, CT scanning was adapted to visualize microbial desulfurization of coal, displacement of heavy oil, and oil flow through carbonate cores.7

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It didn’t take long for those outside the medical field to recognize the potential of CT technology for nondestructive evaluation of materials. Geoscientists soon joined the ranks of other researchers, particularly those in the field of materials testing, who sought increasingly finer detail for imaging internal structures. This capability has largely been realized through development of industrial-strength CT systems, which can employ more powerful X-rays, a tighter focal point and longer exposure times than those used in the medical field.8 Mineral

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> Density values of various minerals commonly found in sedimentary rock. X-rays used to visualize rock structures are affected, in part, by differences in density and mineralogy within a sample.

In the early days of CT rock scans, it was not unusual for geoscientists to work out agreements with the only institution in town that could provide access to such sophisticated technology. Often in the dark of night, with as little attention as possible, core samples from the oilpatch would be wheeled into the pristine and sterile setting of a hospital CAT-scanning facility for imaging and analysis (below).

7. Kayser A, Kellner A, Holzapfel H-W, van der Bilt G, Warner S and Gras R: “3D Visualization of a Rock Sample,” in Doré AG and Vining BA (eds): Petroleum Geology: North-West Europe and Global Perspectives – Proceedings of the 6th Petroleum Geology Conference. London: The Geological Society (2005): 1613–1620. Vinegar HJ: “X-ray CT and NMR Imaging of Rocks,” Journal of Petroleum Technology 38, no. 3 (March 1986): 257–259. 8. For more on high-resolution X-ray CT: University of Texas High-Resolution X-ray Computed Tomography Facility. http://www.ctlab.geo.utexas.edu/overview/index.php# anchor1-1 (accessed January 30, 2006).

1. Although experts may correctly assert that photosites are not actually pixels, the terms are becoming increasingly interchangeable in the popular vernacular, thanks largely to the broad appeal of digital photography, in which manufacturers of digital cameras describe resolution in terms of megapixels.

> A different kind of patient. A section of whole core is placed on a sliding gurney prior to imaging at a hospital CAT-scan facility.

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With the development of microCT (µCT), researchers are attaining much higher resolutions.9 Using µCT, researchers are sometimes able to image their samples with voxel sizes as low as 2.5 µm. Depending on the size of a sample and the number of pixels used to image it, voxel sizes of one-thousandth of the sample size are being attained. For example, a 1-megapixel camera using 1,000 x 1,000 pixels could conceivably resolve a 1-cubic centimeter sample to about 10 µm. Similarly, a 16-megapixel camera (4,000 x 4,000 pixels) can resolve the same sample to 2.5 µm. At such resolutions, geoscientists can distinguish density or porosity contrasts inside a rock sample and can study pore space and pore connectivity in great detail. This µCT technology permits recognition of grains or cements with different mineralogical compositions (right). It has even been used to differentiate grains of the same type, such as those found in carbonates, where microporosity may vary between different grain types in the same rock.10 The Scanning Process The scanning process to acquire µCT data is in some respects analogous to acquiring 3D seismic data. A seismic crew shoots a series of regularly spaced seismic lines. Coordinates of the starting and ending points of each line are surveyed, making it possible to infer the distance between each line in the series. It is therefore possible to determine the position of any point along any line as well as the distance between points within the series of lines. With this knowledge, a position between any two points or lines can be interpolated when the data are processed. For µCT, a regular series of closely spaced scans are acquired to obtain high-resolution virtual slices of a sample. Each pixel in the slice represents a scanned point and has coordinates that correspond to an actual point in the sample. Because coordinates of each point are known, distances between each point and each slice can be determined. And just like the seismic line, points or slices can be interpolated between existing slices. By stacking the series of slices close together to make up a volume of data, each pixel in a slice becomes part of the stack and takes on a third dimension. In this way, each pixel can be treated as a voxel. The scanning process is carried out by highly specialized X-ray systems. Though several companies offer research-grade systems, many X-ray microtomography devices are custom-built. Regardless of whether they are off-the-shelf or specially designed, all rely on three primary

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Barite cement: 1%

Pore space:16% Sandstone grains and quartz cement: 78%

Calcite cement: 5%

> Three-dimensional quantification and spatial distribution of sandstone components. While most sandstones consist primarily of quartz grains and cement, X-ray imagery helps put other components into perspective. Differences in X-ray attenuation throughout the sample indicate changes in density caused by porosity and various mineral constituents of the rock. Once mapped, these characteristics can be isolated for further scrutiny.

components: an X-ray source, a rotating stage on which the sample is placed and an X-ray camera to record the pattern of X-ray attenuation within a sample. To scan a sample, it must be placed on the rotating stage, positioned between the X-ray source and the camera. X-rays emitted from the source are attenuated through scattering or absorption before being recorded by the camera.11 The camera then records a large series of radiographs as the sample rotates incrementally on its stage through 360°. A computer program stacks the digital projection data while maintaining true spacing between pixels and slices. CT algorithms are applied to these data to reconstruct the internal structure of the sample and preserve its scale in three dimensions. One such device was built in 2002 by The Australian National University in Canberra (next

page, top). Its source generates X-rays with a 2to 5-µm focal spot. The X-ray beam expands from the focal point, creating a cone-beam geometry.12 Because magnification of the sample increases with proximity to the X-ray source, the rotating stage and camera are designed to slide separately on a rail, allowing researchers to adjust distances between source, sample and camera. The sample stage can rotate the sample with millidegree accuracy and can support up to 120 kg [265 lbm] of sample and associated test equipment.13 At this facility, the X-ray “camera” consists of a scintillator that fluoresces green in response to X-rays, and a charge-coupled device (CCD) that converts this green light into electric signals.14 The camera has a 70-mm2 active area, containing 4.1 megapixels (2,048 x 2,048 pixels). The system’s large field of view allows researchers to

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> A high-resolution X-ray tomography device at The Australian National University. The rotating sample stage and charge-coupled device (CCD) camera slide on a track, enabling adjustment of the distance between the camera, sample and X-ray source. With this device, a sample can be magnified from 1.1 to more than 100 times its original size. The stage rotates with millidegree accuracy and can be fitted with fluid pumps for imaging flow through porous media. (Figure courtesy of The Australian National University.)

image a 60-mm specimen with a 30-micron pixel size. They can also zoom in for high-resolution scanning to image a 4-mm specimen with 2-micron pixels. Approximately 3,000 projections are needed to generate a 2,0483 voxel tomogram. Between each projection, the sample stage is rotated 0.12°. The entire process takes 12 to 24 hours, depending on the type of sample and the filtering steps required to reduce sampling artifacts. The resulting 24 gigabytes of projection data are 9. Abbreviations for microcomputerized tomography range from µCT (where the Greek letter mu is a standard symbol for the prefix “micro”) to uCT (where u is a substitute for mu) to mCT (where the m stands for micro) to XMT for X-ray Microtomography. 10. Kayser A, Gras R, Curtis A and Wood R: “Visualizing Internal Rock Structures: New Approach Spans Five Scale-Orders,” Offshore 64, no. 8 (August 2004): 129–131. 11. Ketcham RA and Carlson WD: “Acquisition, Optimization and Interpretation of X-Ray Computed Tomographic Imagery: Applications to the Geosciences,” Computers & Geosciences 27, no. 4 (May 2001): 381–400. 12. Sakellariou A, Sawkins TJ, Senden TJ and Limaye A: “X-Ray Tomography for Mesoscale Physics Applications,” Physica A 339, no. 1-2 (August 2004): 152–158. Sakellariou A, Sawkins TJ, Senden TJ, Knackstedt MA, Turner ML, Jones AC, Saadatfar M, Roberts RJ, Limaye A, Arns CA, Sheppard AP and Sok RM: “An X-Ray Tomography Facility for Quantitative Prediction of Mechanical and Transport Properties in Geological, Biological and Synthetic Systems,” in Bonse U (ed): Developments in X-Ray Tomography IV, Proceedings of SPIE—The International Society for Optical Engineering, Vol. 5535. Bellingham, Washington, USA: SPIE Press (2004): 473–474. 13. This test equipment includes pumps or other devices used to study fluid flow or mechanical compaction. 14. Rather than exposing film to light, CCD technology captures images in a technique similar to common digital photography. A CCD uses a thin silicon wafer to record light pulses given off by a scintillator. The CCD silicon wafer is divided into several thousand individual light-sensitive cells. When a light pulse from the scintillator impinges on one of these cells, the photoelectric effect converts the light to a tiny electrical charge. The charge within a cell increases with every light pulse that hits the cell. Each cell on the CCD silicon wafer corresponds in size and location to an image pixel. The pixel’s intensity is determined by the magnitude of the charge within a corresponding cell.

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processed by supercomputer, and it takes 128 central processing units about 2 hours to generate the tomogram. Visualization Technology Once individual radiographic projections have been compiled into a 3D data volume file, the data can be loaded into an immersive visualization environment for detailed examination. With Inside Reality virtual reality technology, the data can be imaged and manipulated like any other volume of 3D data. Originally developed to help visualize seismic volumes based on miles or kilometers of data, Inside Reality technology can also handle data volumes based on much finer, submillimeter scales. Geoscientists utilize this advanced visualization technology to view a data volume from any direction. This capability enables bedding planes

and fracture planes of rock samples to be viewed orthogonally, even when the physical sample has been cut obliquely to these planes. Sedimentary and structural features of the rock sample are typically analyzed in the form of slices or transparency views through a volume. While the scanning process relies on density differences to distinguish features within a sample, the visualization process depends largely on opacity differences. One way to expose features deep within a volume comprising millions of voxels is to render surrounding voxels invisible. Opacity rendering is the key to visualization. Each voxel is assigned a value along a transparency-opacity spectrum, thus making some voxels stand out while others fade away. Without this capability, the opacity of outer voxels would hide all features lying within the volume. Voxel-based technology can be used to determine the volume and geometry of rock grains, cement, matrix and pore space within a sample. Using Inside Reality opacity-rendering tools, geoscientists can assign different values of the opacity-transparency spectrum to various components within a volume. This technique allows geoscientists to distinguish between materials of different density values. For example, the distribution of cement between mineral grains shows up as a distinctive color, while setting pore space to zero-opacity makes it transparent, thus showing the spaces between grains. This allows the viewer to separate rock grains from cement, matrix and pore space to reveal internal sedimentary and structural features (below).

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> Sandstone pores. An opacity filter is used to render different features in volume windows using Inside Reality software. The left window above and behind the yellow arrow shows only quartz grains (light green) in this eolian sandstone from the Rotliegendes formation in Germany. A volume showing only pore space (blue) is in the background on the right. The smaller volume in the foreground on the right shows late diagenetic barite cement (red). The slice making up the base image indicates quartz (gray), pore space (blue), barite (red) and carbonate cement (orange). The yellow arrow for scale is 1 mm long.

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> Sandstone tracking. An opacity filter has been used to highlight quartz grains in sandstone from a Rotliegendes gas reservoir in Germany. In the volume (light gray), interconnected porosity (blue) is imaged using the volume-grower tool provided by Inside Reality software. Fringe (red) along the edge of the porosity indicates possible connections to neighboring pores detected automatically by the software. Carbonate cement (orange) is also shown in the volume. The horizontal slice shows quartz grains (dark gray), pore space (black), carbonate cement (medium gray), and barite cement (white).

> Visualization using Inside Reality technology. Bringing sample volumes into an iCenter secure networked collaborative environment allows asset teams to become immersed in their data. Stereo projection creates a perception of depth, providing a different perspective on the 3D nature of the rock and its microstructure. Inside Reality visualization software provides a detailed image of a foraminifera fossil measuring 1.5 x 1.0 mm (inset). This 3D visualization allows examination of the fossil from many different angles. The animated avatar mirrors the pointing motions and actions of another viewer who is interacting with these data from a remote site.

The ability to manipulate opacity values plays an important role in the seedpoint and volumegrower tools featured as part of the Inside Reality toolbox. Using the seedpoint tool, the viewer selects a point within a slice or volume. This

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point has a certain X-ray attenuation value. Once a point is selected, the program can automatically pick all neighboring voxels of a similar value that are connected to that point. This feature can help a geoscientist pick a point

within a volume known to represent porosity, for example, and the volume-grower tool will display all interconnected porosity within the volume (left). Because each voxel is defined in part by its coordinates, the distance between any two voxels can be measured. To facilitate this process, the Inside Reality system uses a ruler tool to provide a visual scale. This tool can be used to measure grain or pore size in three dimensions, helping geoscientists estimate pore-volume proportions and connectivity. Taking rock samples from the laboratory to an immersive visualization environment enables an asset team to share important information and concepts about reservoir samples so they can make more informed decisions. Inside Reality virtual reality technology lets geoscientists share 3D virtual core data with those in remote sites to help asset teams collaborate with company experts and partners around the world (below left). Applications Rock fabric and textural data provide geologists with key information used in analyzing facies and in determining depositional environments. Geologists and petrophysicists can now obtain important information about grain size, shape and matrix from digital scans of core or core fragments. A single core-fragment image can yield thousands of individual grains. By digitally disaggregating grains in a scanned sample, analysts can obtain coordinates of all voxels composing each grain, the number of neighboring grains and grain-overlap information.15 From such a dataset, geologists can derive a comprehensive analysis of grain sizes and distribution to obtain a full suite of statistical 15. Saadatfar M, Turner ML, Arns CH, Averdunk H, Senden TJ, Sheppard AP, Sok RM, Pinczewski WV, Kelly J and Knackstedt MA: “Rock Fabric and Texture from Digital Core Analysis,” Transactions of the SPWLA 46th Annual Logging Symposium, New Orleans, June 26–29, 2005, paper ZZ. 16. Both the Udden-Wentworth and the Krumbein scales are used to classify rock samples according to diameter; the former is a verbal classification while the latter is numerical. According to the Udden-Wentworth scale, sedimentary particles larger than 64 mm in diameter are classified as cobbles. Smaller particles are pebbles, granules, sand and silt. Those smaller than 0.0039 mm are designated as clay. Several other grain-size scales are in use, but the Udden-Wentworth scale (commonly called the Wentworth scale) is the one that is most frequently used in geology. The Krumbein scale is a logarithmic scale, which assigns a value designated as phi to classify the size of the sediment. Phi is computed by the equation: ø = –log2 (grain size in mm). 17. Arns CH, Averdunk H, Bauget F, Sakellariou A, Senden TJ, Sheppard AP, Sok RM, Pinczewski WV and Knackstedt MA: “Digital Core Laboratory: Analysis of Reservoir Core Fragments from 3D Images,” Transactions of the SPWLA 45th Annual Logging Symposium, Noordwijk, The Netherlands, June 6–9, 2004, paper EEE. 18. Bennaceur K, Gupta N, Monea M, Ramakrishnan TS, Tanden T, Sakurai S and Whittaker S: “CO2 Capture and Storage—A Solution Within,” Oilfield Review 16, no. 3 (Autumn 2004): 44–61.

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> Statistics obtained from a single slice of a sample. More than 4,100 grains were virtually disaggregated from a single slice, allowing researchers to compile detailed statistical data used to characterize rock fabric and texture. When compared with other samples, these statistical measures can help geologists sort out the depositional environment of the rock. (Adapted from Saadatfar et al, reference 15.)

measurements (above left). Grain volume is measured by counting the voxels in each distinct grain, from which size is derived and then graded against standard Udden-Wentworth or Krumbein scales of grain sizes.16 Automated programs can track and classify individual grains according to grain shape characteristics of sphericity and roundness or classify according to textural categories, such as sorting, grain contacts, and matrix or grain-support. Some programs can also measure anisotropy in grain orientation to help geoscientists ascertain sedimenttransport direction. More important than the detailed measurement of rock grains is the analysis of the space between the grains and the contents therein. Opacity-rendering tools work particularly well in showing what is not rock—that is, its porosity. Researchers can obtain a good picture of porosity by decreasing the opacity of dense voxels representing rock grains and cements, while simultaneously increasing the opacity of lowdensity voxels (right). This same opacityrendering technique highlights the extent of interconnected porosity within the rock. Once the porosity is brought up on screen, geoscientists can measure the size of pore spaces and pore throats using the ruler tool. Pore interconnectivity can also be charted, using pore network models based on tomographic imaging (above right). Pore-throat and pore-size distribution, along with interconnectivity, figure

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> Pore-scale information derived from tomographic images. Pore centers (blue spheres), connected by pore throats (blue cylinders), are used to model porosity within a sample of carbonate rock (yellow). The size and location of pore centers and pore throats in this network reflect actual conditions within the rock microstructure. The complexity and heterogeneity of carbonate pore networks are brought to the forefront as part of the rock matrix is rendered semitransparent while pore space is rendered opaque. (Image courtesy of The Australian National University.)

prominently in determining relative permeability and recovery estimates in reservoir samples— parameters that can be hard to quantify when different fluids compete to flow through the same opening. A variety of other measurements can be taken from tomographic images, from which important information is derived. Analysts can directly correlate image data on pore structure and connectivity to measures of formation factor, permeability and capillary drainage pressures. Comparisons of results obtained from µCT images and conventional laboratory measurements on the same core material have generally shown good agreement.17

Studying Effects of Carbon Dioxide on Casing Cement In an important application beyond the realm of conventional petrophysics, µCT was used to study the effects of carbon dioxide [CO2] on casing cement. Greenhouse gases, particularly CO2, have been linked to rising temperatures around the world. Capturing CO2 emissions and sequestering them in the subsurface have been proposed as a measure to reduce atmospheric greenhouse-gas concentrations until lowemission energy sources become viable.18 However, CO2 becomes supercritical when temperature and pressure conditions exceed

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Pores and pore throats

> A whole lot of nothing. By manipulating the opacity of a scanned sample image, it is easy to visually examine either sand grains (green) or pore space (blue). In many evaluations, this detailed analysis of pore space can reveal critical clues to future performance of a reservoir.

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31.1°C and 73.8 bar [87.9°F and 1,070 psi]— conditions that are easily exceeded in most medium to deep wells.19 Therefore, an important aspect of any CO2 sequestration project is to know how downhole materials will react to supercritical CO2 (scCO2). Scientists at Schlumberger Cambridge Research in England have collaborated with their counterparts at Schlumberger Riboud Product Center in Clamart, France, to investigate long-term effects of CO2 storage on wellbore integrity. One such experiment sought to determine how scCO2 would react with casing cement.20 Long used in oil and gas wells to hydraulically isolate pay zones from the surface and other permeable zones, portland-based cements play a critical role in wellbore integrity. This study focused on a sample of neat cement.21 The cylindrical cement sample was cured for three days at 90°C and 280 bar [194°F and 4,061 psi]. Scientists obtained CT scans of the cement cylinder before exposing it to scCO2. The cement was then subjected to a wet scCO2 environment and kept at 90°C and 280 bar for 30 days. Two sample plugs were cut from the original cylinder and then scanned. Using Inside Reality software, researchers were able to manipulate the data volume to visualize porosity and microfractures and arbitrarily slice through zones of interest. By comparing scans acquired before and after treatment, researchers noted significant changes to the cement plug, resulting from scCO2 attack. Of particular interest were the formation and distribution of microfractures, along with a zone of aragonite replacement and a zone of mineral alteration characterized by high secondary porosity. The reaction between scCO2 and cement produced an irregular carbonation front, extending 4 mm [0.16 in.] from the outer edge of the core toward its center. This lighter colored carbonation front was readily apparent in the gray-scale 3D volume, and in a color-coded slice (above right). Subsequent X-ray diffraction analysis determined that the alteration front had a different composition than the original cement, which had been replaced by aragonite. Porosity was clearly enhanced in the regions around the microfractures and the aragonite front (right). The tests suggested that exposure to scCO2 may cause conventional cement to lose more than 65% of its strength after only six weeks. These important observations provided an impetus for creating new blends of cement. Schlumberger researchers have developed new scCO2-resistant cementing materials that display

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good mechanical behavior after exposure to scCO2 gas. Laboratory tests on these new materials show only a slight decrease in compressive strength during the first two days, and essentially no loss for the subsequent three months.

Sample Plug

Examining Wormholes Caused by Stimulation Treatments Researchers have also used CT imaging to study the effects of heterogeneity on carbonate matrix stimulation. In one experiment, it was instrumental in visualizing the effects of the original porosity distribution on acid-dissolution patterns.

CT Image

Alteration front Carbonation front Zone of very low porosity Air bubble (Diameter 0.5 mm) Dissolution front Zone of very high porosity Filled microfracture 0

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> A sample plug of neat cement. Only a few centimeters in length, this sample revealed important information concerning the behavior of supercritical CO2 on portland cement. The tomographic grayscale image of the cement sample (right), scanned with a resolution of 18.33 µm, shows a high concentration of aragonite along the edge of a carbonation front, accompanied by an alteration front. An additional dissolution front of high porosity extends farther into the core. Circular holes with a diameter of 500 µm may represent air bubbles. Microfractures are filled with aragonite crystals. Lighter features represent higher CT values, signifying different mineralogy in the case of the filled microfracture, or different amounts of microporosity, in the case of the alteration front.

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> Highlighting the extent of supercritical CO2 alteration. Color-coding enhances features that may not be readily apparent in gray-scale imaging. Microfractures formed during the supercritical CO2 attack served as conduits for further aragonite alteration. The concentration of aragonite along the fractures and the edge of the alteration front can be visually distinguished using color-coding provided by Inside Reality software. Materials imaged are unaltered neat cement (green), an alteration front (yellow), and mineral-filled microfractures or carbonation front (red). Increased porosity (blue) marks the extent of various dissolution patterns.

Oilfield Review

Stimulation treatments are commonly performed in wells where poor permeability limits production due to naturally tight formations or formation damage. A common stimulation technique involves the injection of acid into carbonate formations. Acid dissolves some of the formation matrix material and creates flow channels that increase the permeability of the matrix. The efficiency of this process depends on the type of acid used, reaction rates, formation properties and injection conditions. While dissolution increases formation permeability, the relative increase in permeability for a given amount of acid is greatly influenced by injection

formation to facilitate the flow of oil. Better still, wormholes require only a small volume of acid to produce significant increases in permeability. Researchers are therefore investigating factors that influence production of wormholes. CT scanning has proved instrumental in determining the effects that injection rate and spatial distribution of porosity have on dissolution patterns formed during stimulation experiments (below). Because it is nondestructive, this technique allows for characterization of the core before and after the treatment experiment so the development and shape of the wormhole can be evaluated.

applications, it is easy to envision the potential spread of new applications for µCT. The technology will no doubt prove instrumental in improving the interpretation and application of laboratory and log data. As an increasingly important tool in nondestructive testing, its application can be extended to laboratory testing of unconsolidated or friable formation samples. The combination of µCT imaging with numerical calculations may lead to more accurate predictions of a wide range of rock properties crucial to exploration, reservoir characterization and recovery calculations. Further applications include development of improved cross-property correlations and development of libraries of 3D images that will

> Visualizing wormhole development. A sample of Winterset limestone was scanned by CT before (bottom) and after (top) acid injection. This data volume is displayed using Inside Reality visualization technology, in which pore space is rendered opaque, while surrounding voxels are rendered transparent. Initial distribution of pores (bottom) shows discrete clusters of pores (blue) along the long axis of the core. After acidizing (top), the core shows increased porosity, with a dissolution pattern extending from right to left that further marks the flow of acid during injection.

conditions. At extremely low injection rates, acid is spent soon after it contacts the formation, resulting in relatively shallow dissolution along the face of the injection zone. High flow rates produce a uniform dissolution pattern because the acid reacts over a large region. In either case, the resulting gains in permeability require relatively large expenditures of acid. However, at intermediate flow rates, long conductive channels known as wormholes are formed. These channels penetrate deep into the

Peering into the Future Tomography is not new to the oil industry. At the upstream end of the tomography spectrum lies crosswell seismic tomography; at the downstream end is industrial process tomography for refineries. As a research tool, µCT is used across a broad suite of industrial applications to monitor performance of polymer-enhanced foams and polyethylene resins or to view phase separation and pore-space characterization in formation samples. Across this range of tomographic

19. Above its critical point at 31.1°C and 73.8 bar, CO2 becomes a supercritical fluid. In this compressed state, its properties lie between those of a gas and a liquid. With a lower surface tension than its liquid form, supercritical CO2 can easily penetrate cracks and crevices. Unlike CO2 gas, however, it can dissolve substances that are soluble in liquid CO2.

20. Barlet-Gouédard V, Rimmelé G, Goffé B and Porcherie O: “Mitigation Strategies for the Risk of CO2 Migration Through Wellbores,” paper IADC/SPE 98924, presented at the IADC/SPE Drilling Conference, Miami, Florida, USA, February 21–23, 2006. 21. Neat cement has no additives that would alter its setting time or rheological properties.

Spring 2006

allow a more rigorous and quantitative description of rock type and texture. These quantitative descriptions can be integrated with classical sedimentological descriptions. The technology can also make a significant contribution to the study of elastic behavior, porosity-permeability trends and multiphase flow properties such as capillary pressure, relative permeability and residual saturations. Future technological innovations will probably include higher resolution to overcome problems in predicting porosity when micropores fall below the detection capability of the present technique. With the improving resolution of their samples, µCT technology is helping today’s geoscientists to better see their world in a grain of sand. —MV

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