Abstract

Carbonate rocks are a synonym for heterogeneity and predicting fundamental properties, such as permeability or capillary pressure, is considerably more challenging as compared to the clastic rocks. Attempts to characterize carbonate reservoirs follow various rock-typing routes in order to predict the two main elements of any subsurface model: saturation and permeability. While these two properties are modeled on parallel working streams (based on routine core analysis, special core analysis or log analysis outcome) we attempt to show the level of consistency they should attain using a quantitative approach. Using reliable saturation-height models an accurate permeability prediction can be made. As a result, a new method for quality control and ensuring consistency between static and dynamic properties will be presented. Where core permeability is not available, we show that a permeability curve can be derived based on input data already available in the model: via the saturation-height model. The advantage of this method is that it can be calibrated directly to well performance in case limited information is available, such as wireline formation testing or drillstem tests.

The rock-typing methods focus mainly on special core analysis (SCAL) output where core-derived permeability and capillary pressures play a central role. In this work, we show that by using fluid-mobility data from wireline formation testing (WFT) pressure measurements the accuracy of rock-typing-predicted permeability can be improved by comparing mobility against the predicted permeability obtained via various averaging methods.

Introduction

Rock typing is a process that attempts to differentiate volumes of rock that have contrasting reservoir properties (e.g., permeability, saturation, flow) represented in a 3D model (Lucia, 1995; Hulea and Nicholls, 2012; Xu and Torres-Verdin, 2012; Skalinski and Kenter, 2015).

A ‘rock type’ is here defined as a volume of rock that contains a distinctive pore/combination of pore-type networks whose spatial distribution is related to one or a combination of depositional and diagenetic processes and whose petrophysical character is predictable, expressed in terms of porosity, permeability and capillary properties.

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