PVT Properties for Yemeni Reservoirs Using an Intelligent Approach

PVT empirical correlations and Artificial Intelligence (AI) techniques become the best alternative when laboratory PVT analysis is not ready or very expensive to obtain. The objective of this paper is to determine the most frequently used oil viscosity (μo), formation volume factor (βo), and gas s...

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Main Authors: Baarimah, S.O., Baarimah, A.O.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29136 /
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125091614&doi=10.1109%2fIEEECONF53624.2021.9668185&partnerID=40&md5=7fd2a30f9e29746e3f2619ccf3928557
http://eprints.utp.edu.my/29136/
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spelling utp-eprints.291362022-03-25T01:03:21Z PVT Properties for Yemeni Reservoirs Using an Intelligent Approach Baarimah, S.O. Baarimah, A.O. PVT empirical correlations and Artificial Intelligence (AI) techniques become the best alternative when laboratory PVT analysis is not ready or very expensive to obtain. The objective of this paper is to determine the most frequently used oil viscosity (μo), formation volume factor (βo), and gas solubility (Rs) PVT properties of Yemeni reservoirs using the bottom hole fluid samples from different wells such as Well-BSWS-1, Well-BSWS-2, Well-BSWS-3, and Well-BSWS-4. Both Fuzzy Logic (FL) technique and a set of statistical error analysis were used to validate and compare the performance and accuracy of the generated reservoir fluid properties correlations. A total of 200 data sets of different crude oils from Yemeni reservoirs were used. The accuracy of the new Fuzzy Logic (FL) was compared with existing real measured bottom hole fluid samples data sets. The graphical plots showed that the predicted oil viscosity, formation volume factor, and gas solubility Fuzzy Logic curves have excellent matching with the experimental curves. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125091614&doi=10.1109%2fIEEECONF53624.2021.9668185&partnerID=40&md5=7fd2a30f9e29746e3f2619ccf3928557 Baarimah, S.O. and Baarimah, A.O. (2021) PVT Properties for Yemeni Reservoirs Using an Intelligent Approach. In: UNSPECIFIED. http://eprints.utp.edu.my/29136/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description PVT empirical correlations and Artificial Intelligence (AI) techniques become the best alternative when laboratory PVT analysis is not ready or very expensive to obtain. The objective of this paper is to determine the most frequently used oil viscosity (μo), formation volume factor (βo), and gas solubility (Rs) PVT properties of Yemeni reservoirs using the bottom hole fluid samples from different wells such as Well-BSWS-1, Well-BSWS-2, Well-BSWS-3, and Well-BSWS-4. Both Fuzzy Logic (FL) technique and a set of statistical error analysis were used to validate and compare the performance and accuracy of the generated reservoir fluid properties correlations. A total of 200 data sets of different crude oils from Yemeni reservoirs were used. The accuracy of the new Fuzzy Logic (FL) was compared with existing real measured bottom hole fluid samples data sets. The graphical plots showed that the predicted oil viscosity, formation volume factor, and gas solubility Fuzzy Logic curves have excellent matching with the experimental curves. © 2021 IEEE.
format Conference or Workshop Item
author Baarimah, S.O.
Baarimah, A.O.
spellingShingle Baarimah, S.O.
Baarimah, A.O.
PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
author_sort Baarimah, S.O.
title PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
title_short PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
title_full PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
title_fullStr PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
title_full_unstemmed PVT Properties for Yemeni Reservoirs Using an Intelligent Approach
title_sort pvt properties for yemeni reservoirs using an intelligent approach
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125091614&doi=10.1109%2fIEEECONF53624.2021.9668185&partnerID=40&md5=7fd2a30f9e29746e3f2619ccf3928557
http://eprints.utp.edu.my/29136/
_version_ 1741197194353967104
score 11.62408

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