COMPUTER PROGRAM FOR DETERMINING SHALE DISTRIBUTION TYPE BY NEUTRON DENSITY CROSSPLOT

Primarily, shale presence in reservoir could bring grievous problems in many aspects both in exploration and exploitation activities. Some of the problems are swelling clay in drilling operation, messed up pattern in water injection, and the most crucial one, reducing the effective porosity. In gene...

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Bibliographic Details
Main Author: Haidar Rochim, Muhammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/40377
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Primarily, shale presence in reservoir could bring grievous problems in many aspects both in exploration and exploitation activities. Some of the problems are swelling clay in drilling operation, messed up pattern in water injection, and the most crucial one, reducing the effective porosity. In general, there are 3 types of shale which could be encountered in reservoir—i.e., Dispersed Shale, Laminar Shale, and Structural Shale, which has different characteristics in affecting effective porosity and permeability of reservoir. Considering its microscopic size, clay minerals, which construct shale types, barely could be identified with naked eye; therefore, some technologies have been invented. One of the most accurate tools in identifying shale distribution type and calculating its volume is Petrography. Petrography quantifies mineralogy and visible porosity using blue resin in terms of volume percent. Because of its high expense, this tool can only observe in limited depth range. Other methods have been developed to tackle this problem, one of them is neutron density cross-plot method which can use whole well depth range logging data. Due to its complexity, neutron density crossplot needs to be generated in petrophysical software. This study has objective to make a simple program of neutron density crossplot using VBA and prove its feasibility in determining shale distribution type, shale volume, and effective porosity. it results 92.1% average accuracy in determining effective porosity and 98.7% average accuracy in determining shale volume compared to reference. Meanwhile its feasibility in determining shale distribution type is qualitatively compared to Petrography analysis and results acceptable accuracy.