The heterogeneity in carbonate rocks made it hard for Geoscientist to define a universal classification methodology that is able to honor the critical static and dynamic properties. Most classifications like lithofacies, capillarity & textural methods base their rock typing on one or two static properties then try to find analog in other static properties to cluster or group them, then populate rock types across the whole field. However; from field observations and experiences of utilizing these conventional techniques, it's obvious that they suffered from several gaps, like inability to have the properties analog consistent through out the whole reservoir, moreover, the groups or clusters have big dispersion that produces overlaps, then theoretically they could not fully honor physics in a way deficiency in the classification definition is recognized and finally a major gap in solving for complex grain sorting effect on flow dynamic properties always existed.

Therefore, in this study, rock typing is made to honor static and dynamic properties all together through changing the classification concept to resolve for the gaps of the traditional methodologies. The ultimate objective of all reservoir characterization and rock classification is to enable building geological and simulation models with optimum honoring of both rock static properties and rock-fluid dynamic flow properties that allow history matching to succeed. To achieve this objective, the framework established in this paper is based on analyzing the effects of each of the rock properties on another and the value and impact that each can add to the models most critical parameters. By this technique, the gap of pore and pore-throat network is resolved through Multiple Properties Intersection.

This Integrated Carbonate Rock Typing technique starts with capturing the heterogeneity of carbonate rock by generating matrix of core permeability, capillary pressure (end point, threshold pressure & Plateau), pore-throat size distribution, porosity and formation factor. Then intersecting this matrix to construct weighted links between these properties and identify unique groups. Resulted classes entered to feedback analysis node to explore and validate the logic of linked physics to tune the classes’ thresholds. Finally for utilizing this technique in non-cored wells, an analog with logging data is structured.

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