Crude oil blending is an important operation that provides flexibility for refineries with increasing operational complexity and constant change in feedstocks. Providing the same quality and quantity of the designed crude oil of an atmospheric distillation unit became a great challenge due to the depletion of the crude oil wells over time so, the crude oil blending is a very important operation nowadays that can provide a good match through the available crude oils.

Furthermore, the heavy crude oils are blended with lighter ones to meet the transportation specifications with lower required horse power. The challenge of such operation is the shrinkage loss in the volume of the blended crude oil so the value of shrinkage has to be calculated to assure it is in a reasonable range. The heavy conventional crude oils have a low price so some companies direct such crude oils to be blended with lighter ones with higher price to upgrade the overall price and improving the heavy crude oils marketing.

The focus of the present work is to optimize the crude oil blending strategy that feed the atmospheric distillation unit in an Egyptian refining plant that has to deliver a certain amount of long residue with some limitations on its quantity and quality. The plant has a fixed bed reformer that has to deliver certain amounts of gasolines either directly or through blending operation. The main target is to maximize the plant overall profit while fulfilling the plant commitments.

Linear programming model is used to achieve the proposed targets subject to the blended crude oil constrains affecting the required long residue. The model is a matrix of constrains describing the limitations on the variables of the optimization problem. Once the model got a feasible region of solutions, the equation of the objective function determines the optimal solution at one of the feasible region borders.

Two constrains are assigned to monitor the stability and the compatibility of the blended crude oil. The optimum crude oil blend was obtained according to different scenarios for domestic consumptions of petroleum products and for different availability of crude oils. For each scenario, the model is providing the maximum profit and fulfilling the required quantity and quality of the straight run fuel oil (long residue).