Genetic Algorithm Optimization of Crude Oil Pipeline Operations for Wax Control: A Case Study of CNPC-Niger Petroleum Company

Abstract

Wax formation and deposition in crude oil pipelines pose a very significant challenge, such as flow restriction, increased cost of maintenance and potential shutdowns. The goals of this study are to reduce wax accumulation in the China National Petroleum Corporation-Niger Petroleum (CNPC-NP) pipeline network, which connects the Agadem oil fields to the SORAZ refinery, by optimizing critical operating conditions. The Reliability of Aspen HYSYS for analyzing wax behavior was validated by the simulation model that closely matched the real-world data, with a simulated flow rate of 182.49 m³/h with, only 0.27% higher than the actual 182 m³/h. The study suggested changing the operating condition using a genetic algorithm method of optimization, which indicates a slight increase in the pressure from 0.6 MPa to 0.65 MPa, while decreasing in temperature from 51°C to 48.5°C and a potential increase in the flow rate to 187.49 187.49 m³/h. Furthermore, the results of the optimization led to a decrease in wax thickness from 0.058 mm to 0.0409 mm, which indicated an improvement in pipeline operating conditions. Also, the economic analysis revealed, the total capital investment was roughly $3.3 million, and the annual operating expenses were estimated to be $2.4 million. The financial indicators include an Internal Rate of Return (IRR) of 9%, a Net Present Value (NPV) of $2.14 million and a Profitability Index (PI) of 1.99, all of which were higher than the IRR of the current CNPC-Niger Petroleum, which was 8%. The results show that the economic performance of the crude oil pipeline system can be improved, and wax formation risk can be effectively decreased by combining simulation-driven decision-making with strategic operational parameter adjustment.