Correlation model development for saybolt colour of condensates and light crude oils

Cheng Seong Khor*, Nur Nelly Sofia Nurazrin, Fatimah Mohd Hanafi, Fatin Nadhirah Asallehan, Nur Zawani Rosman, Jia Jia Leam, Sarat C. Dass, Shahrul Azman Zainal Abidin, Farah Syamim Anuar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Article number434
JournalASM Science Journal
Publication statusPublished - 24 Jun 2020


  • Condensates
  • Kinematic viscosity
  • Linear regression
  • Liquid refractive index
  • Modelling
  • Saybolt number

ASJC Scopus subject areas

  • General


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