166
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

An Investigation of Using Different Saturation Height Functions in an Iranian Oil Reservoir

, &
Pages 412-424 | Received 22 Jan 2010, Accepted 05 Mar 2010, Published online: 27 Dec 2011
 

Abstract

An important application of the concept of capillary pressures pertains to the fluid distribution in a reservoir prior to its exploitation. The capillary pressure-saturation data can be converted into height-saturation data by using the capillary pressure equation and solving for the height (h) above the free water level. Estimation of the water saturation greatly impacts oil-in-place calculations. Saturation-height function is used to predict the saturation in the reservoir for a given height above the free water level. The authors investigate performance of eight saturation-height methods (i.e., Leverett, Cap-Log, Modified Cap-Log, Johnson, Cuddy, Modified Cuddy, Skelt-Harrison, and Sodena methods) employed in the oil industry. They collected measured capillary pressure data and core properties from a well in one of the Southern Iranian reservoirs. The authors review advantages and disadvantages of each method while comparing the output of each method with saturation obtained from the log data. The results indicate that the Skelt-Harrison and Leverett methods, with coefficients independent of core properties, would be the best and worst option, respectively.

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.