SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH

<p align="justify">The secondary wave velocity (Vs) is one of the most important parts of the well data. However, it is often found data that a well does not have Vs data or even having unreliable Vs data, for example when the Vs obtained results in a negative Poisson’s Ratio valu...

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Main Author: Elsa Lorenza Nasution- NIM : 12314016, Rurry
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/30729
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:30729
spelling id-itb.:307292018-09-18T14:32:00ZSECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH Elsa Lorenza Nasution- NIM : 12314016, Rurry Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/30729 <p align="justify">The secondary wave velocity (Vs) is one of the most important parts of the well data. However, it is often found data that a well does not have Vs data or even having unreliable Vs data, for example when the Vs obtained results in a negative Poisson’s Ratio value or too high Poisson’s Ratio value in hydrocarbons bearing rocks. Some reservoirs have deltaic facies; thus, a lot of rocks will have clay content. Clay content will form shaly sand or sandy shale rock. Reservoirs that are formed do not always have good qualities such as clean sand, and it is possible that the composites cointain clay content. This study used real data to make a model of several lithology like clean sand and shaly sand that represents the behavior of the secondary wave velocity trend occurring. The data were modeled using rock physics methods such as Hashin-Strikman lower bound and Hertz-Mindlin. The model made requires Vpdry, Vsdry, clay content XRD, grain density, and total porosity data. The model is a representative for the real data in general, it is used as the reference model to see the suitability of some empirical method in predicting the secondary wave velocity. The prediction of secondary wave velocity using rock physics modeling is quite complex, thus this study performed comparisons of several empirical methods such as Greenberg-Castagna, Vernik, Williams, Dvorkin, and Krief, which are simpler to predict secondary wave velocities corresponding to forward modeling as well as real data. The results showed that the simplest and most robust method to predict Vs are Greenberg-Castagna (1992) and Vernik (2002), both showed small errors. Greenberg-Castagna’s formulation can predict Vs better than any methods because they accommodate the fraction for both composites, sand and shale. Whereas, Vernik’s formulation only accomodate Vp as the input and yet still gave one of the best result among any other methods.<p align="justify"> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <p align="justify">The secondary wave velocity (Vs) is one of the most important parts of the well data. However, it is often found data that a well does not have Vs data or even having unreliable Vs data, for example when the Vs obtained results in a negative Poisson’s Ratio value or too high Poisson’s Ratio value in hydrocarbons bearing rocks. Some reservoirs have deltaic facies; thus, a lot of rocks will have clay content. Clay content will form shaly sand or sandy shale rock. Reservoirs that are formed do not always have good qualities such as clean sand, and it is possible that the composites cointain clay content. This study used real data to make a model of several lithology like clean sand and shaly sand that represents the behavior of the secondary wave velocity trend occurring. The data were modeled using rock physics methods such as Hashin-Strikman lower bound and Hertz-Mindlin. The model made requires Vpdry, Vsdry, clay content XRD, grain density, and total porosity data. The model is a representative for the real data in general, it is used as the reference model to see the suitability of some empirical method in predicting the secondary wave velocity. The prediction of secondary wave velocity using rock physics modeling is quite complex, thus this study performed comparisons of several empirical methods such as Greenberg-Castagna, Vernik, Williams, Dvorkin, and Krief, which are simpler to predict secondary wave velocities corresponding to forward modeling as well as real data. The results showed that the simplest and most robust method to predict Vs are Greenberg-Castagna (1992) and Vernik (2002), both showed small errors. Greenberg-Castagna’s formulation can predict Vs better than any methods because they accommodate the fraction for both composites, sand and shale. Whereas, Vernik’s formulation only accomodate Vp as the input and yet still gave one of the best result among any other methods.<p align="justify">
format Final Project
author Elsa Lorenza Nasution- NIM : 12314016, Rurry
spellingShingle Elsa Lorenza Nasution- NIM : 12314016, Rurry
SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
author_facet Elsa Lorenza Nasution- NIM : 12314016, Rurry
author_sort Elsa Lorenza Nasution- NIM : 12314016, Rurry
title SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
title_short SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
title_full SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
title_fullStr SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
title_full_unstemmed SECONDARY WAVE VELOCITY PREDICTION THROUGH ROCK PHYSICS AND EMPIRICAL APPROACH
title_sort secondary wave velocity prediction through rock physics and empirical approach
url https://digilib.itb.ac.id/gdl/view/30729
_version_ 1821995846253674496