CORRELATION ANALYSIS OF EFFECTIVE PORE CONNECTIVITY INDEX AND PETROPHYSICAL PARAMETER OF 3 DIMENSION ROCK MODEL

Digital rock physics (DRP) is a branch of petrophysics that learns about rock samples by means of digital imaging techniques. These digital images will be processed and analyzed to acquire the physical parameters of the samples. The parameter used as the reference of gas and oil's prospect on r...

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Bibliographic Details
Main Author: Fatih Haunan, Muhammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/63199
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Digital rock physics (DRP) is a branch of petrophysics that learns about rock samples by means of digital imaging techniques. These digital images will be processed and analyzed to acquire the physical parameters of the samples. The parameter used as the reference of gas and oil's prospect on rocks is permeability. Lattice Boltzmann Method-based fluid flow simulation is one of the methods used in permeability estimation, which is done using computer simulation on a digital image medium. LBM's superiority over other estimation methods is that it is non-invasive and replicable. LBM's inferiority is it needs a considerable amount of computing power and simulation time. A previous experiment by Sun developed an Effective Pore Connectivity Index (EPCI) algorithm to predict permeability based on pore connectivity of 3-dimensional digital rock images scanned using micro-computed tomography (micro-CT). This study aims to estimate permeability based on EPCI and then determine the correlation between permeability, microstructural parameters, and EPCI on random partially penetrable grain models. Three-dimensional rock models are generated, simulated with LBM, analyzed with CTAn software and EPCI software to acquire permeability, EPCI, and microstructural parameters. Results show that permeability and microstructural parameters distribution are significantly affected by grain radius and sample dimensions. The distribution tends to be more consistent if the sample size is enlarged and the grain radius is reduced. Furthermore, permeability estimation based on EPCI is applied, and the error is calculated. Based on the error, polynomial estimation model yields less error and smallest error on each 7px, 11px, and 15px grain radius is obtained at (100px)3 , (200px)3 , dan (300px)3 sample size.