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Отправлено: 27.09.17 12:20. Заголовок: A NEW RESISTIVITY-BASED MODEL FOR IMPROVED HYDROCARBON SATURATION ASSESSMENT IN CLAY-RICH
A NEW RESISTIVITY-BASED MODEL FOR IMPROVED HYDROCARBON SATURATION ASSESSMENT IN CLAY-RICH FORMATIONS USING QUANTITATIVE CLAY NETWORK GEOMETRY AND ROCK FABRIC Aitur Posenato Garcia, Aichana Jagadisan. Ameneh Rostami. and Zoya Heidari. The University of Texas at Austin The importance of the clay-network conductivity in resistivity-based saturation assessment has been well recognized over the years. The existing shaly sand models are oversimplified by assuming that the clays are present m the rock predominantly as laminated, dispersed, or structural. This assumption, however, is not reliable in many day-rich formations. Because, m nature, clay minerals can have complex spatial distributions. Furthermore, die conventional shaly sand resistivity models such as Waxman-Smits. Dual-Water. Simandoux, and Indonesia do not take into account spatial distribution and connectivity of clay network. Spatial distribution of clay network can significandy affect resistivity of clay-rich formations and oversimplifying this distribution can lead to huge uncertainties m estimates of water saturation in such formations. In dus paper, we introduce a new resistivity-based model which quantitatively takes into account the actual clay-network geometry and distribution and type of clay minerals. Reliable incorporation of spatial distribution of clay network (i.e., not limited to extreme cases of dispersed, layered, and structural) improves reserves evaluation m clay-rich formations with complex clay network structure. The new resistivity model incorporates directional pore-network connectivity of each conductive component of the rock that forms a percolating network. The directional connectivity is calculated as a function of the volumetric fractions and rock fabnc features such as directional tortuosity and constriction factor of each rock component. The aforementioned rock fabnc features are quantitatively evaluated from the three-dimensional (3D) pore-scale images. We scan core samples from clay-rich formations using a high-resolution micro-Computed Tomography (CT) scanner. Then, we perform trainable segmentation on each set of two-dimensional (2D) raw images to identity different rock components and pores. The 2D segmented images are then converted mto a 3D volume. We apply a semi-analytical streamline model to estimate the network connectivity and tortuosity of the conductive components from the 3D binary images, which will be inputs to the introduced model. We successfully apphed the introduced model in several synthetic rock samples as well in actual clay-rich rock samples including a shaly formation and an organic-nch mudrock. The electrical conductivity, estimated from numerical simulations, was in agreement with the resistivity estimates from die new model. Comparison of die results against conventional methods showed that saturation estimates were unproved by up to 50% in more than 60% of the samples after quantitatively taking mto account spatial distribution of clay network. The outcomes of dus paper are promising for successful application of the introduced model for improved in-situ assessment of hydrocarbon saturation through assimilating the impacts of rock fabric and spatial distribution of clay networks on electrical resistivity measurements.
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