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GEOREF RECORD

Radial-basis-function-based nuclear magnetic resonance heavy oil viscosity prediction model for a Kuwait viscous oil field

Khalid Ahmad, Faisal Hassan, Prasanta Kumar Mishra, Waleed Al-Khamees, Wei Shao, Songhua Chen, Magdalena Sandor and Yuesheng Cheng
Radial-basis-function-based nuclear magnetic resonance heavy oil viscosity prediction model for a Kuwait viscous oil field (in Advanced logs and interpretation, Yao Peng (prefacer), Vivek Anand (prefacer), Burkay Donderici (prefacer), Tie Sun (prefacer) and Xiaogang Han (prefacer))
Interpretation (Tulsa) (May 2016) 4 (2): SF81-SF92

Abstract

Characterizing heavy oil viscosity by nuclear magnetic resonance (NMR) relaxation time (T (sub 1) and T (sub 2) ) measurements is much more challenging than characterizing light oil viscosities. Crude oils contain a wide range of hydrocarbons, resulting in broad T (sub 1) and T (sub 2) distributions that vary with the oil composition. Most often, a single geometric mean value T (sub 1, gm) or T (sub 2, gm) is correlated with the crude oil viscosity, which cannot accurately account for the inherent complexity of the oil constituent information. Furthermore, as the viscosity increases, some of the protons in the oil relax too quickly to be observable by logging or laboratory NMR instruments. This results in deficiencies of relaxation time and signal amplitude that give rise to apparent T (sub 1) and T (sub 2) distributions (T (sub 1, app) and T (sub 2, app) ) and apparent hydrogen index (HI (sub app) ). Using T (sub 1, app) and T (sub 2, app) distributions in NMR viscosity models could produce erroneous heavy oil viscosity estimations. Several attempts have been made to overcome these challenges by taking into account HI (sub app) at a fixed interecho time (TE), or a TE-dependent HI (sub app) . We have developed a new radial-basis-function-based heavy oil viscosity model using the entire T (sub 2,app) distribution, rather than T (sub 2, gm) , with an option of including the NMR-derived HI (sub app) . Because both of these quantities are TE dependent, it is desirable to include multiple TE data to develop the model. In addition, the principal component analysis (PCA) method was applied to extract major variations of features embedded in the T (sub 2, app) distributions, while discarding distribution features that are derived from random noise. The coefficients of the RBFs were derived using laboratory NMR T (sub 2) measurements at ambient and elevated temperatures between 23.5 degrees C and 39.5 degrees C and corresponding viscosity measurements on 50 oil samples. These oil samples were collected from different parts of a shallow viscous oil reservoir in Kuwait. It was observed that the use of this newly developed RBF method showed significant improvement in terms of the reliability of the viscosity prediction compared to some recently published heavy oil viscosity correlations.


ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 4
Serial Issue: 2
Title: Radial-basis-function-based nuclear magnetic resonance heavy oil viscosity prediction model for a Kuwait viscous oil field
Title: Advanced logs and interpretation
Author(s): Ahmad, KhalidHassan, FaisalMishra, Prasanta KumarAl-Khamees, WaleedShao, WeiChen, SonghuaSandor, MagdalenaCheng, Yuesheng
Author(s): Peng, Yaoprefacer
Author(s): Anand, Vivekprefacer
Author(s): Donderici, Burkayprefacer
Author(s): Sun, Tieprefacer
Author(s): Han, Xiaogangprefacer
Affiliation: Kuwait Oil Company, Ahmadi, Kuwait
Affiliation: BP America, Houston, TX, United States
Pages: SF81-SF92
Published: 201605
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 20
Accession Number: 2017-001218
Categories: Economic geology, geology of energy sources
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus.
N28°30'00" - N30°15'00", E46°30'00" - E48°45'00"
Secondary Affiliation: Halliburton, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201701
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