Integration and Data Analysis of Conventional Core Data with NMR and CT Data to Characterize An Evaporitic Carbonate Reservoir.

Abstract

Acquisition of whole core data allows detailed rock typing profiles to be defined which are required to assign flow properties for dynamic reservoir simulation. Conventional core analysis provides lab measurements of porosity, permeability and pore size distribution sampled at plug locations with a limited sampling increment. Whole core CT scanning allows for a more continuous detailed evaluation of the cored intervals which allow the precise boundaries of specific Rock Types to be defined. This paper illustrates how novel techniques of data analysis and graphic displays of both whole core CT data and wireline NMR have been used to aid the definition of Rock Types and Flow Units. Rock Types have been categorized based on flow properties using plug porosity, permeability and MICP data. Processing of whole core CT data and wireline NMR has been performed in order to assess the heterogeneity measured by both acquisition methods. For the CT data set Heterogeneity Logs have been generated, these logs display the variation of CT density of the whole core. The logs have enabled very fine scale definition of lithotypes. In a similar manner the NMR logs were also analyzed and processed to extract specific statistical moments such as modes, magnitudes and skewness. Both sets of data were then integrated with core analysis data and thin sections. Excellent correlation between core plug, CT Heterogeneity Logs, NMR and thin section pore size distribution was observed and this has enabled the definition of Rock Types from the fine scale CT Heterogeneity Logs and Flow Units from the coarser scale wireline NMR data. The techniques described are applied to data from a heterogeneous evaporitic carbonate reservoir, where pore size distribution has a major effect on permeability and productivity. Eight Rock Types have been categorized from core analysis and these have been propagated from plug locations using the CT Heterogeneity Logs to assist manual interpretation. Neural Network and geostatistics were applied to propagate to uncored wells and throughout the geocellular model. The acquisition of core data and subsequent Heterogeneity Logs from whole core CT has proved very beneficial in the understanding of the wireline NMR tool response and has given confidence in the predictive ability of NMR to distinguish reservoir Flow Units in uncored intervals or wells.

Integrating Petrophysical and Digital Rock Analyses for Pore to Core Scale Characterization of Subsurface Flow Units

“…The heterogeneity logs thus provided a unique, high vertical resolution signatures of the depositional and diagenetic features in DQ cores (Figure 9), even those that are sometimes not obviously discerned based on visualization alone. Moreover, this creates the opportunity to improve the calibration of well log data with geological interpretations such as lithofacies associations and improved identification of boundaries of or stratigraphic units within wells (Fitzsimons et al 2016).…”

“…The application of multiscale image data for characterization of pore space in reservoir rocks has been gaining rapid momentum over the past decade (Wellington and Vinegar 1987;Carlson 2006;Fitzsimons et al 2016;Dernaika et al 2017). However, using whole core CT data for reservoir characterization has been limited to only a small number of studies over the past years (Al-Owihan et al 2014;Dernaika et al 2015Dernaika et al , 2017Victor et al 2017).…”

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

“…depth, the log value represents the number of pixels within that grey value histogram bin ( Figure 5). So low number of bins indicate homogeneous rock, while numerous bins means the rock is very heterogeneous and possibly contains multimodal pore size distributions (Fitzsimons et al 2016). The histogram logs hence show how the composition of rock varies for every slice of the core CT image.…”

“…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.…”

Pore to Core Scale Characterization of Hydraulic Flow Units Using Petrophysical and Digital Rock Analyses

“…[ 27,28 ] Moreover, the CT image data can be used to compute high‐resolution and continuous logs from the whole cores such as porosity, density, and mineralogy estimations. [ 25,29 ]…”