The quality of feedstock used in base oil processing depends on the source of the crude oil. Moreover, the refinery is fed with various blends of crude oil to meet the demand of the refining products. These circumstances have caused changes of quality of the feedstock for the base oil production. Often the feedstock properties deviate from the original properties measured during the process design phase. To recalculate and remodel using first principal approaches requires significant costs due to the detailed material characterizations and several pilot-plant runs requirements. To perform all material characterization and pilot plant runs every time the refinery receives a different blend of crude oil will simply multiply the costs. Due to economic reasons, only selected lab characterizations are performed, and the base oil processing plant is operated reactively based on the feedback of the lab analysis of the base oil product. However, this reactive method leads to loss in production for several hours because of the residence time as well as time required to perform the lab analysis. Hence in this paper, an alternative method is studied to minimize the production loss by reacting proactively utilizing machine learning algorithms. Support Vector Regression (SVR), Decision Tree Regression (DTR), Random Forest Regression (RFR) and Extreme Gradient Boosting (XGBoost) models are developed and studied using historical data of the plant to predict the base oil product kinematic viscosity and viscosity index based on the feedstock qualities and the process operating conditions. The XGBoost model shows the most optimal and consistent performance during validation and a 6.5 months plant testing period. Subsequent deployment at our plant facility and product recovery analysis have shown that the prediction model has facilitated in reducing the production recovery period during product transition by 40%.
Pyrenees crude oil containing high napthenic acids (NAs) content of more than 1.6 mg KOH/g oil was treated with methyltrimethylammonium methylcarbonate [N4441][MeCO3] as to reduce its acidity to the refinery permissible limit of 0.3 mg KOH/g oil. The treated crude oils are subjected to Emulsion Stability Test (EST) as to mimic the operating conditions of a desalter. The results indicate the electrostatic conditions can facilitate the recovery of the napthenate salts post neutralization with high recovery rate of more than 79.6% with basic sediments & water (BSW) to be 1.96%. The conductivity of the treated crude oil also was found to increase as a function of temperature. The ionic liquid mediated-deacidification of crude oil can be performed under existing desalting conditions should the recovery of the naphthenate salts is acceptable at 70%.
Desalting process concept was tested using methyltrimethylammonium methylcarbonate [N4441][MeCO3] treated Pyrenees crude oil (initial Total Acid Number (TAN) of 1.6 mg KOH/g oil) with the aim to gain empirical evidences on the effectiveness of in-line water washing and electrostatic aided phase separation as mean to recover the naphthenic acid derivatives for recycling. The treated crude oil (final TAN value of less than 0.3 mg KOH/g oil) was subjected to typical operating scheme such as single stage desalting and effects of water wash volumes. The novelty of the work comes from the utilisation of ionic liquids to neutralise acid components of the crude oil. Furthermore, the work is also able to test the hypothesis of whether naphthenate salts behave as is its inorganic counterpart and quantify the solubility behaviour in water as extraction medium. The effectiveness of such scheme will be measured against naphthenic acids derivative percent recovery in the wash water. The results indicate the electrostatic conditions can facilitate the recovery of the naphthenate salts post neutralization with high recovery rate of average of 70.6 % with 30 % water wash volume in a single-stage contact, observed over 12 hours steady-state operation. The water wash weight was observed to increase post separation which indicate hydrocarbon carry-over in the heavy phase due to formation of tight water – oil emulsion. The technique is viable should the amount of water required is available and the process water can be recycled safely into the desalter again without causing tripping to the desalter. Ionic liquid can be used in conjunction with desalter and the presence of electrostatic field did hasten the separation of the phases, however the amount of water used may hinder the viability of the solution.
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