Modeling the Effect of Random Environmental Perturbation on Data Precision in Niger Delta Crude Oil Production

Abstract

Decision-makers most times rely on data precision to support their decision-making processes. There is also a strong belief, however, that data quality or data precision problems are widespread in practice and that reliance on poor data quality or wrong data sets can lead to devastating consequences on crude oil production and financing. This study applies the Runge-Kutta numerical method of order 45 (ordinary differential equation of order 45) to examine the effect of data precision index on the Niger Delta crude oil production due to the variation of the initial condition. The study has found out that the initial condition four (4), (IC 4) with a data precision index value of 0.0118 ranked best in the first crude oil well, the initial condition (IC) 15 with a data precision index value of 0.0021 ranked best in the second crude oil well, the initial condition (IC) 17 with a data precision index value of 0.0021 ranked best in the third crude oil well and the initial condition (IC) 20 with a data precision index value of 0.0234 ranked best in the fourth crude oil well. The study has observed that each crude oil data is associated with a best-fit-value of the data precision index.