Water saturation is among important petrophysical properties of rock used to assess the initial hydrocarbon in an exploration well. This paper studies five formations from the main limestone carbonate reservoir belong to an exploration field located in the northern part of Iraq. Additionally, we review water saturation models to choose the best one to this exploration field. There are several techniques of water saturation determination applied to estimate reservoir quality. Archie equation is considered one of these techniques; however, applying this model in shale formation gives errors in water saturation estimation. Three different models of water saturation, Simandoux, Indonesian, and Modified Simandoux, were chosen to estimate water saturation in shale beds. Our results demonstrated that the water saturation obtained from the Archie equation is higher than all other models. Furthermore, the Indonesian water saturation model is higher than Simandoux and Modified Simandoux water saturation models. The outcome of the Simandoux and Modified Simandoux were lower than those of Archie and Indonesian models. The accuracy of the water saturation model is evaluated by tends to be close to that of Archie water saturation model is considered negative. The reason is there are no production test results or saturation data from core analysis. The lowest average of water saturation is found in Simandoux and Modified Simandoux models. Depending on water saturation value, the good positive model is modified Simandoux or Simandoux model due to its lowest average value of water saturation. Besides, it can be used for further reservoir studies.
The digital core analysis of petrophysical properties replace the use of conventional core analysis by reducing the required time for investigation. Also, the ability to capture pore geometries and fluid behavior at the pore-scale improves the understanding of complex reservoir structures. In this work, 53 samples of 2D thin section petrographic images were used for analyses from the core plugs taken from the Buzurgan oil field. Each sample was impregnated with blue-dyed epoxy, thin sectioned and then was stained for discrimination of carbonate minerals. Each thin section has been described in detail and illustrated by photomicrographs. The studied samples include a variety of rock types. Packstone is the most common rock type observed followed by grainstone and packstone – wackestone. Floatstone and dolostone are noted rarely in the studied interval. However, the samples of thin section images are processed and digitized, utilizing MATLAB programming and image analysis software. The entire workflow of digital core analysis from image segmentation to petrophysical rock properties determination was performed. A focused has been made on determining effective and total porosity, absolute permeability, and irreducible water saturation. Absolute permeability is estimated with the Kozeny-Carman permeability correlation model and Timur-Coates permeability correlation model. Irreducible water saturation simply is derived from total and effective porosity. Also, some pore void characteristics, such as area and perimeter, were calculated. The results of Digital 2D image analysis have been compared to laboratory core measurements to investigate the reliability and restrictions of the digital image interpretation techniques.
Porosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in resulting binary image. This paper presents the possibilities of using image processing for determining digital 2D rock samples porosity in carbonate reservoir rocks. MATLAB code created which automatically segment and determine the digital rock porosity, based on the OTSU's thresholding algorithm. In this work, twenty-two samples of 2D thin section petrographic image reservoir rocks of one Iraqi oil field are studied. The examples of thin section images are processed and digitized, utilizing MATLAB programming. In the present study, we have focused on determining of micro and macroporosity of the digital image. Also, some pore void characteristics, such as area and perimeter, were calculated. Digital 2D image analysis results are compared to laboratory core investigation results to determine the strength and restrictions of the digital image interpretation techniques. Thin microscopic image porosity determined using OTSU technique showed a moderate match with core porosity.
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