ANISOTROPY QUANTIFICATION USING HIGH-RESOLUTION WHOLE-CORE CT-SCAN IMAGES

Spatial anisotropy and heterogeneity in petrophysical properties can significantly affect formation evaluation of hydrocarbon bearing formations. A common example is permeability anisotropy, which is a consequence of the depositional mechanisms of sediments. Additionally, the variation in spatial distribution of rock components and the effect of post-depositional processes on the physical and chemical structure of the rock constituents can strongly impact the directional dependency of petrophysical, electrical, and elastic properties. Therefore, image-based quantification of spatial distribution of rock constituents can be used for anisotropy evaluation. Assessment of anisotropy has been previously accomplished through use of pore-scale images. However, the discrete nature of this images gives a narrow picture of anisotropy in larger scales. Whole-core computed tomography (CT) scan images, despite revealing the distribution of rock components at a coarser scale, provide a continuous medium for anisotropy estimation. Assessment of anisotropy using three-dimensional (3D) CT-scan data and incorporation of that information in well-log-based formation evaluation is, however, not widely studied or practiced in the petroleum industry. The objectives of this paper are (a) to develop a method to quantify anisotropy utilizing whole-core 3D CT-scan image stacks, (b) to provide a semi-continuous measure of rock anisotropy, and (c) to show the value of the proposed method by means of estimation of directional-dependent elastic properties. First, we pre-process the raw whole-core CT-scan images to remove undesired image artifacts and to generate an image containing pixels representing only the recovered core material. Then, we segment each whole-core CT-scan image stack into distinctive phases. Then, we conduct numerical simulations of electric potential distribution in conjunction with streamline tracing techniques to quantify the electrical tortuosity of the continuous phase in each cartesian direction. We employed the tortuosity distribution values in each direction as a measure of rock anisotropy. Finally, we use a simulation model to estimate direction-dependent elastic properties. We applied the introduced method to dual energy whole-core CT-scan image stacks acquired in a siliciclastic depth interval. Estimates of rock anisotropy obtained using the proposed method agreed with the observed visual distribution of the segmented phase and the observed heterogeneity in available slabbed whole-core photos and 2D CT-scan images. Additionally, estimation of directional-dependent elastic properties demonstrated the value of the proposed method. Anisotropy results coincided with directional-dependent estimation of elastic properties. We observed measurable anisotropy in the 3D CT-scan image stacks, which is important to be quantitatively taken into account in petrophysical/ mechanical evaluation of this formation. A unique contribution of the proposed workflow is the use of core-scale image data for anisotropy estimation and the continuous nature of the anisotropy estimates when compared with workflows employing only pore-scale image data. It should also be noted that the proposed method can potentially be employed to identify the optimum locations to acquire core plugs for further assessment of rock anisotropy.