Temporal dynamics and predictive modeling of produced water quality in Niger Delta oil fields

Management of produced water in the Niger Delta is becoming complicated due to varying effluent characteristics as a result of seasonal and long-term variations in the environment. Successful treatment and compliance with regulations demand precise understanding of these temporal dynamics. In this study, trends, seasonal cycles, and abrupt changes in oil in water (OIW), total dissolved solids (TDS), and conductivity in major fields in the Niger Delta of Nigeria have been examined using Time-series methods in R. A 7-year dataset from 15 crude oil formations’ produced water was characterized with several statistical tools. Seasonality of OIW concentrations was significant, with peak concentrations in the wet season ranging from 45 to 180 mg L⁻¹ and a long-term increasing trend of 2.3 mg L⁻¹ yr ⁻¹ (p < 0.001). TDS had a 0.34 coefficient of variation and significant structural changes in 2019 and 2022. Both SARIMAX and Prophet Models had robust forecast performance, but the Prophet Model was marginally superior to SARIMAX. The results indicate that present treatment facilities respond too inadequately to seasonal stressors, while it accommodates base loads; it is insufficient for peak conditions. Incorporating the use of predictive models with adaptive treatment regimes could make operations more efficient in the oil-producing facilities by 23–31 %, allowing more proactive management and more robust environmental compliance for all facilities in the oil industry.