Application of full factorial design to screen the factors influencing the wax deposition of Malaysian crude oil

• Main Authors: Elarbe, Basem, Elganidi, Ibrahim, Norida, Ridzuan, Kamal, Yusoh, Norhayati, Abdullah, Vijaya Kumar, Shamala
• Format: Article
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2021
• Subjects: QD Chemistry; T Technology (General); TA Engineering (General). Civil engineering (General); TP Chemical technology
• Online Access: http://umpir.ump.edu.my/id/eprint/33393/1/Application%20of%20full%20factorial%20design%20to%20screen%20the%20factors%20influencing%20the%20wax.pdf; http://umpir.ump.edu.my/id/eprint/33393/; https://doi.org/10.1007/s13202-021-01431-8; https://doi.org/10.1007/s13202-021-01431-8

Wax deposition in production pipelines and transportation tubing from offshore to onshore is critical in the petroleum industry due to low-temperature conditions. The most significant popular approach to solve this issue is by inserting a wax inhibitor into the channel. This research aims to reduce the amount of wax formation of Malaysian crude oil by estimating the effective parameters using Design-Expert by full factorial design (FFD) method. Five parameters have been investigated, which are rotation speed (A), cold finger temperature (B), duration of experimental (C), the concentration of poly (stearyl acrylate-co-behenyl acrylate) (SABA) (D), and concentration of nano-silica SiO2 (E). The optimum conditions for reducing the amount of wax deposit have been identified using FFD at 300 rpm, 10 ℃, 1 h, 1200 ppm and 400 ppm, respectively. The amount of wax deposit estimated is 0.12 g. The regression model’s variance results revealed that the R2 value of 0.9876, showing 98.76% of the data variation, can be described by the model. The lack of fit is not important in comparison to the pure error, which is good. The lack of fit F value of 12.85 means that there is only a 7.41% probability that this huge can occur because of noise. The influence of cold finger temperature was reported as the main contributing factor in the formation of wax deposits compared to other factors. In addition, the interaction between factor B and factor C revealed the highest interaction effect on the wax deposition. In conclusion, the best interaction variables for wax inhibition can be determined using FFD. It is a valued tool to measure and detect the unique relations of two or more variables. As a result, the findings of this study can be used to develop a reliable model for predicting optimum conditions for reducing wax deposits and the associated costs and processing time.