Study of Factors That Influence Prediction of CO2 MMP
Prediction of minimum miscibility pressure (MMP) in miscible gas enhanced oil recovery (EOR) simulation depends on the ability of the equation of state to represent adequately the properties of components in the injected gas and oil mixtures over a wide range of conditions. Inaccurate description...
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my-utp-utpedia.10972017-01-25T09:43:17Z http://utpedia.utp.edu.my/1097/ Study of Factors That Influence Prediction of CO2 MMP Iskandar Dzulkarnain, Iskandar GB Physical geography Prediction of minimum miscibility pressure (MMP) in miscible gas enhanced oil recovery (EOR) simulation depends on the ability of the equation of state to represent adequately the properties of components in the injected gas and oil mixtures over a wide range of conditions. Inaccurate description ol, the properties will undermine the predictive ability of the LOS model. The FOS can he used to calculate the NIMP by mo methods: numerical and analytical. Numerical methods involve 1-1) slim-tube simulation and mixedcell simulation. Analytical method utilises the key tic-line length algorithm. The purpose of this work aims to understand the füctors which affect the calculation 01- M NIP fir pure C'U, injection using, analytical I: OS method. Since the method requires accurate characterir. ation of the reservoir fluid. different selection of F . 0S. different selection of the PA'"f properties to match and the different selection of 1OS variables to adjust may give different prediction of MNIP. Proper treatment of- these tacturs will reduce the inaccuracy Of the MMP calculation from the EOS model. In this ýyork the läctors are studied by looking at three aspects: 1) the selection of EOS 2) the necessary PVT properties that the FOS need to match in order to predict the NiNIP accurately, and 3) the tuning strategies which are employed to match the LOS model with the PVT data for subsequent calculation of MMP This work attempts to investigate these factors by the 1ö11owing approaches: 1) comparison of available SOS's in a commercial PVT package and their performance when calculating MMP, 2) tuning the [OS to match selected PVT data and observing the predicted MMP from the tuned IFS, and ;) comparison of diflcrent tuning strategies proposed in the literature to tune the EOS to match the experiment data and evaluating the tuned EOS calculation 01' MNIP. The selected kOS s 11or comparison studs are PR Pencloux and SRK Pcneloux. For the matchim, PVT property stud. the I. OS model is tuned to match the solution gas! oil ratio ((1OR). the liquid phase density and the oil 1,61-Illation volume Iäctor (I: V1' ). In the tunings ariahies stud. MO diIi1rcnt tunin`s procedures are compared. Ile results sho\y that Or a pure ('O- miscible gas injection scenario. the SRK Peneloux IFS can he used to obtain acceptable IN-INI prediction. Besides matching the saturation pressure accurately. matching the density is also required. It is also shown that using the tuning, variables such as critical temperature 1,critical pressure P, acentric factor and the volume shill parameter can better tune the FOS Iiar accurate prediction of NINIP. 2010 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/1097/1/iskandar_dzulkarnain.pdf Iskandar Dzulkarnain, Iskandar (2010) Study of Factors That Influence Prediction of CO2 MMP. Masters thesis, Universiti Teknologi Petronas. |
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GB Physical geography Iskandar Dzulkarnain, Iskandar Study of Factors That Influence Prediction of CO2 MMP |
description |
Prediction of minimum miscibility pressure (MMP) in miscible gas
enhanced oil recovery (EOR) simulation depends on the ability of the equation
of state to represent adequately the properties of components in the injected
gas and oil mixtures over a wide range of conditions. Inaccurate description ol,
the properties will undermine the predictive ability of the LOS model. The
FOS can he used to calculate the NIMP by mo methods: numerical and
analytical. Numerical methods involve 1-1) slim-tube simulation and mixedcell
simulation. Analytical method utilises the key tic-line length algorithm.
The purpose of this work aims to understand the füctors which affect the
calculation 01- M NIP fir pure C'U, injection using, analytical I: OS method.
Since the method requires accurate characterir. ation of the reservoir fluid.
different selection of F
.
0S. different selection of the PA'"f properties to match
and the different selection of 1OS variables to adjust may give different
prediction of MNIP. Proper treatment of- these tacturs will reduce the
inaccuracy Of the MMP calculation from the EOS model.
In this ýyork the läctors are studied by looking at three aspects: 1) the
selection of EOS 2) the necessary PVT properties that the FOS need to match
in order to predict the NiNIP accurately, and 3) the tuning strategies which are
employed to match the LOS model with the PVT data for subsequent
calculation of MMP
This work attempts to investigate these factors by the 1ö11owing
approaches: 1) comparison of available SOS's in a commercial PVT package
and their performance when calculating MMP, 2) tuning the [OS to match
selected PVT data and observing the predicted MMP from the tuned IFS, and
;) comparison of diflcrent tuning strategies proposed in the literature to tune
the EOS to match the experiment data and evaluating the tuned EOS calculation 01' MNIP. The selected kOS s 11or comparison studs are PR
Pencloux and SRK Pcneloux. For the matchim, PVT property stud. the I. OS
model is tuned to match the solution gas! oil ratio ((1OR). the liquid phase
density and the oil 1,61-Illation volume Iäctor (I: V1' ). In the tunings ariahies
stud. MO diIi1rcnt tunin`s procedures are compared.
Ile results sho\y that Or a pure ('O- miscible gas injection scenario. the
SRK Peneloux IFS can he used to obtain acceptable IN-INI prediction.
Besides matching the saturation pressure accurately. matching the density is
also required. It is also shown that using the tuning, variables such as critical
temperature 1,critical pressure P, acentric factor and the volume shill
parameter can better tune the FOS Iiar accurate prediction of NINIP. |
format |
Thesis |
author |
Iskandar Dzulkarnain, Iskandar |
author_facet |
Iskandar Dzulkarnain, Iskandar |
author_sort |
Iskandar Dzulkarnain, Iskandar |
title |
Study of Factors That Influence Prediction of CO2 MMP |
title_short |
Study of Factors That Influence Prediction of CO2 MMP |
title_full |
Study of Factors That Influence Prediction of CO2 MMP |
title_fullStr |
Study of Factors That Influence Prediction of CO2 MMP |
title_full_unstemmed |
Study of Factors That Influence Prediction of CO2 MMP |
title_sort |
study of factors that influence prediction of co2 mmp |
publishDate |
2010 |
url |
http://utpedia.utp.edu.my/1097/1/iskandar_dzulkarnain.pdf http://utpedia.utp.edu.my/1097/ |
_version_ |
1739830734355431424 |
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13.211869 |