Method Addresses Difficulty of Modeling Heterogeneous Carbonate Bimodal Rocks

Abstract

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper IPTC 18587, “Heterogeneous Carbonates: A Modeling Method Ensuring Consistency Between the Saturation-Height and Permeability Models for Bimodal Rocks,” by Iulian N. Hulea, Harm Dijk, SPE, Danila Karnaukh, and Mirano Spalburg, Shell, prepared for the 2016 International Petroleum Technology Conference, Bangkok, Thailand, 14–16 November. The paper has not been peer reviewed. Copyright 2016 International Petroleum Technology Conference. Reproduced by permission. Because of their heterogeneity, carbonate reservoirs are more difficult to model than clastic reservoirs. The main difficulty comes from the number of different pore types, compared with the typical interparticle pore type in clastics. By using saturation-height models (SHMs) in combination with conventional permeability measurements, a new approach attempts to extract the fundamental properties of individual pore systems. The key idea centers on identifying the governing pore systems from capillary pressure curves and permeability measurements. The approach results in the ability to predict permeability continuously as a function of pore-system mixing ratios. Introduction Because of the presence of multiple pore types, carbonate rocks are difficult to model. To account for their heterogeneity, carbonate rocks are often modeled using rock-typing schemes. Two particularly challenging properties are permeability and saturation. Although these properties have been recognized as being closely connected, little information is available on how to handle them consistently. Even when permeability and SHMs satisfactorily describe the core measurements, it is not trivial to ensure their consistency in 3D models. One possible situation is building SHMs that impose consistency through the governing parameters. Throughout this work, a Brooks-Corey function is used because it was found to describe unimodal mercury-injection capillary pressures (MICPs) satisfactorily. For the examples discussed in this contribution (Fig. 1), microporosity (corresponding to the pore system accessible beyond pore throats of 2 µm or less) forms between 40 and 70% of the pore volume and is mostly located within the micritic grains. A significant difference between the two examples shown in Figs. 1a and 1d is the relative contribution of microporosity on average equaling 0.53 for Rock Type 1 (RT1) and 0.75 for Rock Type 2 (RT2). For RT2, microporosity can be located in the mud between the grains. Capillary Pressure Curve Data Analysis and Modeling The MICP modeling strategy relies on treating the two pore systems as independent, fitting each one of the pore systems first then looking for the best correlation to predict the Brooks-Corey parameters. On the basis of the measured individual-core-plug properties, the standard deviation for both plug porosity and the relative ratio of microporosity to total porosity was derived. By making the plots with the same fundamental inputs (SHM, porosity, permeability transform), the properties predicted by the models can be highlighted and contrasted.