A Transient Model for Prediction of Asphaltene Deposition Along Tubing String: Enhanced Petroleum Production Implications

2020

Closed access Metadata (CSL-JSON)
DOI 10.4043/30095-ms
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Abstract Prediction of asphaltene deposition in production system and design of production parameters adequately to control this issue is inevitable. We presented a transient model to predict asphaltene deposition along the tubing string in the production system. An accurate two-phase fluid flow model was coupled with a solid asphaltene precipitation model and a sub-layer particle deposition model in turbulent flow with the ability to predict the deposition of particles in vertical surfaces. Our procedure shows good agreement with the experimental work previously done to measure the rate of deposition of flocculated asphaltene particles via an accurate thermal apparatus at different temperatures and flow rates. The developed model was used to simulate the deposition of asphaltene in a real field. The results suggest that even with high flow rates, the deposited asphaltene caused a 2.5% reduction in wellhead pressure after 30 days of production. The developed model can predict the transient location of the asphaltene, onset pressure, and the profile of the deposited asphaltene in a wellbore versus time. In practice, the proposed model can be used for analysis of different production scenarios in a given well to minimize the possibility and extent of asphaltene deposition and enhance the production rate.