eprintid: 13794
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/37/94
datestamp: 2023-11-10 03:28:21
lastmod: 2023-11-10 03:28:21
status_changed: 2023-11-10 01:52:00
type: article
metadata_visibility: show
creators_name: Khor, C.S.
creators_name: Sofia Nurazrin, N.N.
creators_name: Hanafi, F.M.
creators_name: Asallehan, F.N.
creators_name: Rosman, N.Z.
creators_name: Leam, J.J.
creators_name: Dass, S.C.
creators_name: Zainal Abidin, S.A.
creators_name: Anuar, F.S.
title: Correlation model development for saybolt colour of condensates and light crude oils
ispublished: pub
note: cited By 3
abstract: Saybolt colour or number is a measured physical property of petroleum condensates and light crude oils which can be used as a quality indicator. As an alternative approach to the laboratory-based colour measurement method, this work aims to determine the influential physical properties in predicting Saybolt colour by applying a regression modelling approach. Data available on Saybolt colour and several physical properties are obtained from assay reports for condensates and light crude oils of Malaysian oil and gas fields. Other unavailable but potentially influential properties are estimated using a commercial process simulation software, iCON. The properties identified as explanatory variables in this study are refractive index, kinematic viscosity at 40C, and characterization factor. This machine learning problem gives rise to applying multiple linear regression techniques based on a backward elimination approach in developing a correlation to predict Saybolt colour using the identified key properties of characterization factor, kinematic viscosity at 40C, and refractive index. © 2020 Akademi Sains Malaysia.
date: 2020
publisher: Akademi Sains Malaysia
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089344913&doi=10.32802%2fASMSCJ.2020.434&partnerID=40&md5=185402307c4dae5fa0efd059be6c58fa
id_number: 10.32802/ASMSCJ.2020.434
full_text_status: none
publication: ASM Science Journal
volume: 13
refereed: TRUE
issn: 18236782
citation:   Khor, C.S. and Sofia Nurazrin, N.N. and Hanafi, F.M. and Asallehan, F.N. and Rosman, N.Z. and Leam, J.J. and Dass, S.C. and Zainal Abidin, S.A. and Anuar, F.S.  (2020) Correlation model development for saybolt colour of condensates and light crude oils.  ASM Science Journal, 13.   ISSN 18236782