Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment

Abstract

This study investigates the efficiency of a sodium hydroxide-modified biocomposite, synthesized from zeolite and activated carbon derived from coconut shells, for the removal of hydrocarbon from produced water. The adsorption process was optimized using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) integrated with genetic algorithms. The results indicated a hydrocarbon removal efficiency of 99.86 % with RSM and 99.99 % with ANN under optimal conditions. The ANN model demonstrated superior predictive accuracy (R² = 0.9984, MSE = 0.4004, RMSE = 0.6328) compared to RSM (R² = 0.9976, MSE = 0.5635, RMSE = 0.7507). Characterization techniques, including Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), Brunauer–Emmet–Teller (BET) analysis, and Energy Dispersive X-ray Spectroscopy (EDX), confirmed the successful integration of zeolite onto activated carbon and the presence of active functional groups favorable for hydrocarbon adsorption. The Redlich-Peterson model was identified as the best fit for the experimental data, highlighting the biocomposite's potential as an effective adsorbent for treating produced water. These findings show the promising application of NaOH-modified AC-ZE biocomposites in achieving sustainable development goals.

Keywords

• Adsorption
• Wastewater treatment
• Artificial neural network
• Response surface methodology
• Oil removal
• Coconut shell