Upscaled Permeability and Rock Types in a Heterogeneous Carbonate Core from the Middle East

Abstract

Determination of Reservoir Rock Types (RRT) is one of the main parameters in the process of reservoir modelling and simulation. In carbonate reservoirs, the rock typing process is challenging due to multiscale heterogeneity with varying pore types and complex microstructures. The objective in this paper is to select representative samples from a heterogeneous core (350 feet) and establish unique reservoir rock types as well as model permeability along the entire core length based on textural analysis, geological interpretations and petrophysical measurements. Representative core plugs were selected in a full-diameter heterogeneous core from a carbonate reservoir in the Middle East. The sample selection was based on statistical distribution of porosity and CT-textures in the core. The porosity and textural variations were determined along the core length at 0.5 mm resolution using advanced dual energy X-ray CT imaging. Plug-scale rock types were established based on micro-textures and pore types using thin-section photomicrographs, mercury injection analysis and poroperm measurements. The micro-texture analysis (grainy, muddy, mixed) and pore types were linked to the poroperm data. The micro-texture information was then upscaled to the entire core length using CT-textural analysis. The porosity and permeability data were fitted into unique trends that were derived from the detailed textural analysis. This process provided the link between the poroperm trends and the different textures in the core enabling permeability and rock types to be upscaled to the entire whole core intervals. Variation of reservoir rock types was studied for each poro-perm trend. The different trends were mainly controlled by the different rock micro-textures whereas the extent of the trend was due to different diagenesis processes (i.e. dissolution, cementation & compaction). This paper describes a novel approach of combining textures with porosity to model permeability and rock types at the plug scale and core level. A unique dual energy CT technique was used to ensure that all the core property variations were well represented in the plug-scale core analysis measurements.

Numerical Simulation Modeling of Carbonate Reservoir Based on Rock Type

“…Its primary pore structure changes dramatically, and the reservoir physical property distribution has strong heterogeneity. Rock typing is an essential step in the process of the carbonate reservoir characterization and geological modeling, and it is the method of classifying reservoir rocks which have the same fluid flow features into groups [1][2][3][4][5][6]. Rock typing is an effective way to obtain accurate permeability, and it enables us to get better understanding of the fluid movement and to enhance oil recovery [7][8][9][10][11].…”

Improved Reservoir Characterization Through Rapid Visualization and Analysis of Multiscale Image Data Using A Digital Core Analysis Ecosystem

“…There has been an accelerated increase in the application of whole core CT data for reservoir characterization over the past years (Victor et al 2017;Dernaika et al 2017;Al-Owihan, et al 2014). Hurst (1984) took a significant step forward to adapt medical CT scanner to oil and gas industry lab studies, followed by Shell scientists' (Vinegar and Wellington 1987) pioneering work, who modified medical CT scanner for core analysis.…”

“…The understanding of petrophysical and multiphase flow properties is essential for the assessment and exploitation of hydrocarbon reserves and these properties in turn are dependent on the 3D geometric and connectivity properties of the pore space. The application of multiscale image data for characterization of pore space in reservoir rocks has been gaining momentum over the past decade (Wellington and Vinegar 1987;Carlson 2006;Fitzsimons et al 2016;Dernaika et al 2017). Efficient utilization of multi-scale image and petrophysical data for characterizing complex rock formations requires a common platform that can handle large amounts of data to enable rapid visualization and analysis.…”

Upscaling Strategy to Simulate Permeability in a Carbonate Sample Using Machine Learning and 3D Printing

“…This step is especially complex when dealing with carbonate rocks because of their inherent heterogeneities at several length scales. Indeed, deposition and diagenesis produce heterogeneous poreshaped geometries that may have a significant impact on petrophysical properties [1]- [2]. For example, two core plug samples extracted from adjacent locations in a carbonate core may have significantly different rock properties.…”