102
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Development of PVT Correlations According to Geography

, , &
Pages 991-999 | Published online: 24 Feb 2014
 

Abstract

An enormous number of pressure–volume–temperature (PVT) correlations have been developed over the years for different types of hydrocarbon systems. However, the accuracy of these correlations is often limited due to crude oil compositional difference, impurities, etc., from different geographical locations. The literature has revealed that the predictive capabilities of the previously developed PVT correlations for Nigerian crude oil system are still associated with large errors and as the accurate determination of the PVT properties is uncompromising, it is of great importance to develop new models for the Niger Delta region. In this study, we present new empirical PVT correlations for calculating bubble point pressure (Pb ) and bubble point oil formation volume factor (Bob ) using Niger Delta crude oil data based on multiple regression methods. Performance prediction based on statistical and graphical methods was carried out. The performance prediction results of the developed Pb and Bob correlations, when used to predict PVT data of crude oil system from different geographical locations, showed very high relative errors. This implies that in order to predict PVT data for a crude oil systems with high accuracy, local PVT correlations need to be developed.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 855.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.