179
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

Asphaltene Instability Trends to Predict Asphaltene Precipitation Onset Pressure: Constrained for Light and Heavy Crude Oils

, &
Pages 103-110 | Received 24 Dec 2013, Accepted 06 Jan 2014, Published online: 25 Sep 2014
 

Abstract

The study investigates asphaltene instability trends (ASISTs), originally developed by New Mexico Tech, for crude oils with different °API gravities and asphaltene contents. Different ratios of precipitants/solvents have been used to construct the ASISTs at ambient conditions. Results were extended to reservoir conditions using routine PVT data. The ASIST method was used to predict the asphaltene precipitation onset pressure at reservoir conditions. Due to the kinetic effect on asphaltene precipitation using the titration method, pressure depletion induced asphaltene precipitation experiments were carried out for the heavy oil sample. Results, using the modified Miller–Flory–Huggins model, were thermodynamically modeled to validate the ASIST observations and for finding an appropriate lag time that can correspond to reservoir conditions. Similar asphaltene precipitation and thermodynamic modeling were adapted from the literature for the light oil sample. Results suggest that, for the light oil sample, 5 hours is appropriate lag time to perform ASIST, which is in agreement with the reported trends; for the heavy oil sample, however, results suggest that even a 5 hours lag time is not short enough for the titration experiment so that it can be kinetically extended to asphaltene precipitation in the reservoir. We suggest a 1 hour lag time for the samples with low °API gravities and high asphaltene contents. More case studies from different crude oils from different geological settings are required to draw any rigid kinetic framework for the ASIST.

ACKNOWLEDGMENTS

The National Iranian Oil Company (NIOC) is acknowledged for providing the crude oil samples and permission of publishing the results.

Notes

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/ldis.

Current affiliation for S. Dolati: Department of Chemistry, Dezful Branch, Islamic Azad University, Dezful, Iran.

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 666.00 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.