The Reverse Mass Balance Method for Distribution of Trunk Line Crude Oil Losses: Issues, Alternatives, and Recommendations

Abstract

In Nigeria, trunk lines are owned by few International Oil and Gas Companies and they are shared by independent producers, marginal field operation and some JV partners. Crude oil losses occur in these trunk lines due to use of wide range of non-compliant meters by the suppliers of crude to the trunk lines and leakages due to sabotage, aged pipeline and valve failures. These losses must be distributed among the suppliers of crude to the line (injectors). The Interim Methodology which apportioned 62% of the crude losses to measurement error and 38% to theft was promptly rejected by injectors and was replaced by the Reverse Mass balance methodology(RMBM). Less than two years of the RMBM's implementation, injectors are petitioning the DPR about unfair deductions by the trunk line owners. The aim of this research therefore is to highlight the issues with the RMBM and discuss alternatives. This study identified two alternatives to the RMBM, the use of Artificial Intelligence and Flow based models. This study found that flow based models account for both individual and group losses, unaccounted for in the RMBM, and allocates and corrects for leak volumes at the point of leak instead of at the terminal. This is a significant improvement from the RMBM, however, AI techniques, PSO and Genetic Algorithm, are purported to perform better for leak allocation.