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May 6, 2026American Journal of Chemical Engineering0 citationsOpen Access

Mathematical Modeling of Bio-Unit System for Oilfield Produced Water Treatment

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DNDarlington NwokomaKDKenneth Dagde

Key Points

  • This research aims to develop mathematical models to optimize a bio-oxidation system for treating produced water in oilfields.
  • Formulated mathematical models incorporating biokinetic coefficients and operating parameters.
  • Used fourth-order Runge-Kutta algorithm for numerical integration of the models.
  • Conducted linear regression to validate model predictions against measured values.
  • Model predicted outlet COD values with 4.3% deviation from measurements.
  • Achieved 98.3% COD and 98.5% TOC removal with specified retention times.
  • Linear regression showed high correlation with R² values of 0.9923 for COD.

Abstract

The Nigerian oil and gas extraction faces the challenge of treating excessive co-extracted Produced Water (PW) to fulfil reinjection or disposal specifications. Deploying a proposed modular bio-oxidation system (Bio-Unit) to treat PW necessitates predictive model for this biotreatment process. Thus, this work aimed at formulating mathematical models for predicting and simulating the Bio-Unit system. Experimentally determined biokinetic coefficients and other operating parameters were incorporated into the developed models and integrated numerically using fourth-order Runge-Kutta algorithm. Model predicted values of outlet chemical oxygen demand (COD), total organic carbon (TOC), and bioagent suspended solids (MLSS) were 14.7 mg/l, 7.02 mg/l, and 3252.0 mg/l, respectively. The percentage deviation of model predicted values from measured values was 4.3%, 3.1% and 7.9% for COD, TOC and MLSS, respectively. Linear regression between measured values and model predicted values gave the best fit value (iR/iisup2/sup/i) of 0.9923, 0.9890, and 0.9831 for COD, TOC, and MLSS, respectively, which indicates that the formulated model had a significant correlation with the Bio-Unit data and is 99.2%, 98.9%, and 98.3% dependable in predicting the parameters. The mean bias error for predicted MLSS, COD and TOC concentrations were -3.67, 4.79 and 3.24, respectively, which indicates that the model under-predicted the MLSS, while the COD and TOC concentrations were over-predicted. Model simulation showed that biosolid retention time of 21 days and hydraulic retention time of 1.0 day resulted in 98.3% and 98.5% COD and TOC removal. Hence, the formulated models are adequate and recommended for predicting and optimizing the Bio-Unit system.

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Cite This Study

Nwokoma et al. (2026) studied this question.

synapsesocial.com/papers/69fa8eac04f884e66b531010https://doi.org/10.11648/j.ajche.20261402.12
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