(52a) Measurements and Calculations of Asphaltene Deposition  | AIChE

(52a) Measurements and Calculations of Asphaltene Deposition 

Authors 

Elsharkawy, A. - Presenter, Kuwait University
Al-Matrouk, M., Kuwait Oil Company
Asphaltene precipitation and deposition have been recognized as curtailing and vital problems in oil and gas fields. Asphaltene precipitation and deposition affect production, transmission and processing facilities in different and tremendous ways. These problems lead to system interruptions and have become a crucial part of flow assurance studies. One way to mitigate these problems is to keep the production system free of wax and asphaltenes.

Different approaches have been implemented in the oil and gas industries to predict asphaltene precipitation or deposition conditions. Predicting the asphaltene onset pressure (AOP) requires the presence of pressurized down-hole samples with very low or no oil–based mud contamination, which is not an easy task.

Several models have been introduced in the oil industry; some of them are considered costly and time consuming since they require experimental work to come up with an accurate prediction.

The asphaltene precipitation conditions in Kuwait oil fields from both South East Kuwait (SEK) and West Kuwait (WK) were studied extensively to develop a fast and low-cost model with acceptable accuracy.

This study has three phases. The first phase is a literature review regarding the available approaches to predict the AOP. Later, a new model is introduced to overcome the current industrial obstacles. The new model, which relies on basic reservoir data such as the temperature, pressure, bubble point and a SARA analysis, was tested using lab measurements.

In the final stage, PIPESIM software was used to predict the AOP for eighteen Kuwaiti oil wells. The accuracy of the proposed model as well as the PIPESIM predictions indicated that both approaches resulted in some error compared with the measured values of the AOP. The model developed in this study has an average absolute error of 12% compared to 7.50% by PIPESIM. However, the proposed model is easy to be used and does not need commercial license.