The Oil & Gas sector is globally regarded as the 3rd largest industry after Health Insurance and Pension Funds, generating a revenue close to USD $3.3 trillion over the last 5 years. It is widely considered as the lifeline to sustain the businesses of major industries such as Defense, Aviation and Transportation.
Crude oil, commonly known as “black gold” is a scarce resource which when carefully distilled in a refinery passing through series of chemical processes, synthesizes to produce useful products that run our daily lives such as Petrol (or Motor Spirit), Diesel, Kerosene, Paraffins, Jet Fuel, etc. It is due to this global scarcity of crude combined with several geographic, technical and socio-political challenges of setting up complexed processes in a refinery that makes oil companies around the globe to lock horns with each other in order to gain worldwide dominance.
One of the ways for an already constrained organization, to gain a competitive edge over other candidates in the Oil & Gas industry is through ‘crude blending’ or simply stated, the process of combining different grades of crude oil in varying ratios to produce products for distribution by maximizing it’s profit margin and satisfying their customers’ daily demand without compromising the quality of product or causing any significant impact to the environment. Through this article, we will try to gain a basic step-by-step understanding of how blending operations in a refinery can be modelled as a linear programming problem in Python and solve it to obtain the optimal blending proportions.