Intelligent and Circular Drilling Wastewater Treatment: A Review Integrating Machine Learning, Uncertainty Quantification, and Resource Recovery

Document Type : Review Article

Authors
Seyed Ata Elyas Sorkhabi 1
Mohammadreza Akbari 2
Yasin Khalili 3
1 BSc. Student, Department of Petroleum and Geoenergy Engineering, Amirkabir University of Technology, Tehran, Iran
2 Assistant Professor, Department of Petroleum and Geoenergy Engineering, Amirkabir University of Technology, Tehran, Iran
3 Ph.D. Student, Department of Petroleum and Geoenergy Engineering, Amirkabir University of Technology, Tehran, Iran
20.1001.1/jgt.2026.2082269.1066
Abstract
Drilling wastewater generated during oil and gas operations presents a complex environmental challenge due to its highly variable composition, large volumes, and the presence of hazardous organic and inorganic contaminants. Conventional treatment approaches, although widely implemented, often fail to achieve consistent performance under dynamic operating conditions and increasingly stringent environmental regulations.
This review provides a comprehensive and forward-looking analysis of drilling wastewater management by integrating treatment technologies with emerging concepts of circular economy, data-driven intelligence, and uncertainty quantification. The characteristics and sources of drilling wastewater are examined to highlight their inherent variability and associated treatment challenges. Conventional, advanced, and hybrid treatment technologies are critically evaluated in terms of efficiency, limitations, and applicability for water reuse and resource recovery. Circular economy strategies, including water recycling, material recovery, and zero liquid discharge (ZLD), are also assessed from a sustainability perspective.
In addition, the role of machine learning in performance prediction, process optimization, and real-time monitoring is discussed, alongside uncertainty quantification approaches such as probabilistic modeling and Bayesian inference for risk-informed decision-making. From an industrial perspective, the integration of intelligent modeling and uncertainty-aware frameworks enables more reliable, adaptive, and efficient treatment systems.
Despite these advancements, challenges remain in data availability, model transferability, system integration, and economic feasibility. This review establishes a unified framework that bridges environmental engineering, data science, and sustainability, providing a pathway toward intelligent, circular, and resilient drilling wastewater treatment systems.
Keywords
Drilling wastewater treatment
Machine learning
Uncertainty quantification
Circular economy
Resource recovery
Oil and gas industry
Subjects

Article Title Persian

تصفیه هوشمند و چرخشی پساب حفاری: مروری بر یکپارچه‌سازی یادگیری ماشین، کمّی‌سازی عدم‌قطعیت و بازیابی منابع

Authors Persian

سید عطا الیاس سرخابی 1
محمدرضا اکبری 2
یاسین خلیلی 3
1 دانشجوی کارشناسی، دانشکده مهندسی نفت و زمین انرژی، دانشگاه صنعتی امیرکبیر، تهران، ایران
2 استادیار، دانشکده مهندسی نفت و زمین انرژی، دانشگاه صنعتی امیرکبیر، تهران، ایران
3 دانشجوی دکترا، دانشکده مهندسی نفت و زمین انرژی، دانشگاه صنعتی امیرکبیر، تهران، ایران
Abstract Persian

پساب حفاری تولیدشده در عملیات نفت و گاز، به دلیل ترکیب بسیار متغیر، حجم زیاد، و حضور آلاینده‌های خطرناک آلی و معدنی، یکی از چالش‌های پیچیده زیست‌محیطی محسوب می‌شود. روش‌های متداول تصفیه، علی‌رغم کاربرد گسترده، اغلب در دستیابی به عملکرد پایدار تحت شرایط عملیاتی دینامیک و الزامات سخت‌گیرانه زیست‌محیطی با محدودیت مواجه هستند.
این مطالعه مروری، تحلیلی جامع و آینده‌نگر از مدیریت پساب حفاری ارائه می‌دهد که در آن فناوری‌های تصفیه با مفاهیم نوظهور اقتصاد چرخشی، هوشمندسازی مبتنی بر داده، و کمّی‌سازی عدم‌قطعیت به‌صورت یکپارچه مورد بررسی قرار گرفته‌اند. در این راستا، ویژگی‌ها و منابع تولید پساب حفاری بررسی شده تا ماهیت متغیر آن و چالش‌های مرتبط با تصفیه مشخص گردد. همچنین، فناوری‌های متداول، پیشرفته و هیبریدی تصفیه از نظر کارایی، محدودیت‌ها، و قابلیت کاربرد در بازیافت آب و بازیابی منابع به‌صورت انتقادی ارزیابی شده‌اند. راهبردهای اقتصاد چرخشی از جمله بازچرخانی آب، بازیابی مواد، و سیستم‌های تخلیه صفر مایع نیز از منظر پایداری مورد تحلیل قرار گرفته‌اند.
علاوه بر این، نقش یادگیری ماشین در پیش‌بینی عملکرد، بهینه‌سازی فرآیند، و پایش لحظه‌ای بررسی شده و در کنار آن، روش‌های کمّی‌سازی عدم‌قطعیت مانند مدل‌سازی احتمالاتی برای پشتیبانی از تصمیم‌گیری مبتنی بر ریسک مورد بحث قرار گرفته‌اند. از دیدگاه صنعتی، یکپارچه‌سازی مدل‌های هوشمند و چارچوب‌های مبتنی بر عدم‌قطعیت می‌تواند به توسعه سیستم‌های تصفیه‌ای قابل‌اعتمادتر، تطبیق‌پذیرتر و کاراتر منجر شود.
با وجود این پیشرفت‌ها، چالش‌هایی همچون محدودیت داده‌ها، انتقال‌پذیری مدل‌ها، پیچیدگی یکپارچه‌سازی سیستم‌ها، و ملاحظات اقتصادی همچنان پابرجاست. این مطالعه با ارائه یک چارچوب یکپارچه که مهندسی محیط‌زیست، علوم داده و اصول پایداری را به هم پیوند می‌دهد، مسیر توسعه سیستم‌های تصفیه پساب حفاری هوشمند، چرخشی و مقاوم را ترسیم می‌کند.

Keywords Persian

تصفیه پساب حفاری
یادگیری ماشین
کمّی‌سازی عدم‌قطعیت
اقتصاد چرخشی
بازیابی منابع
صنعت نفت و گاز
Adedayo-Ojo, A. A., M. K. Shad, W. C. J. C. E. Poon and Sustainability (2025). "Circular Economy in the Oil and Gas Industry: A Data-Driven Bibliometric Analysis." 1-63.
Adverse, A. T. N.-Z. "INTEGRATED SUSTAINABLE URBAN WATER, ENERGY, AND SOLIDS MANAGEMENT."
Ahmed, A., A. Alsaihati, S. J. A. J. f. S. Elkatatny and Engineering (2021). "An overview of the common water-based formulations used for drilling onshore gas wells in the Middle East."  46(7): 6867-6877.
Ajao, A. (2024). "Conventional and advanced treatment technologies for microplastics in water treatment facilities."
Al-Dahidi, S., M. Alrbai, L. Al-Ghussain, A. Alahmer and H. S. J. B. T. Hayajneh (2024). "Data-driven analysis and prediction of wastewater treatment plant performance: Insights and forecasting for sustainable operations."  391: 129937.
Albusaimi, F. A., M. S. Al Dabbous, R. Al Yateem and F. P. Pretorius (2024). Circular Economy Practices Through Water Management. SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability?, SPE.
Alessi, D. S., A. Zolfaghari, S. Kletke, J. Gehman, D. M. Allen and G. G. J. C. W. R. J. R. c. d. r. h. Goss (2017). "Comparative analysis of hydraulic fracturing wastewater practices in unconventional shale development: Water sourcing, treatment and disposal practices."  42(2): 105-121.
Alsabaa, A., H. Gamal, S. Elkatatny and Y. J. A. o. Abdelraouf (2022). "Machine learning model for monitoring rheological properties of synthetic oil-based mud."  7(18): 15603-15614.
Anyanwu, C., J. C. Agunwamba and M. J. A. o. A. I. i. R. o. E. C. Tiza (2026). "Application of conventional methods and artificial intelligence tools for wastewater treatment: Recent advancements and future prospects." 109-149.
Aparna, K., R. J. P. S. Swarnalatha and E. Protection (2024). "Optimizing wastewater treatment plant operational efficiency through integrating machine learning predictive models and advanced control strategies."  188: 995-1008.
Aryanti, P. T. P., F. A. Nugroho, C. Ahmadi, R. Ismail, A. J. M. o. P. W. Kadier, I. Oil Field Discharges: Diagnosis and Treatment (2025). "Water Recycling at Oil Field Industry Plants." 351-402.
Asad, G. and J. Everhart (2025). "Uncertainty-Aware Predictive Maintenance: Leveraging Adaptive Machine Learning for Mechanical Components."
Bai, Y., Z. Li, J. Jiang, J. Liu, H. Wang, Q. Liu, G. Gang, Z. Kong and Y. J. E. R. Wang (2026). "Optimizing wastewater treatment through combined deep learning and deep reinforcement learning: Recent advances and future prospects." 123795123795.
Ball, A. S., R. J. Stewart, K. J. W. M. Schliephake and Research (2012). "A review of the current options for the treatment and safe disposal of drill cuttings."  30(5): 457-473.
Barcelona, M. J., J. P. Gibb and R. A. Miller (1983). A guide to the selection of materials for monitoring well construction and ground-water sampling, Illinois State Water Survey.
Basu, S., A. R. Shaw and M. Venkatesh (2025). Water Management in Petroleum Industries, Springer Nature.
Belia, E., M. B. Neumann, L. Benedetti, B. Johnson, S. Murthy and P. Vanrolleghem (2021). Uncertainty in Wastewater Treatment Design and Operation, IWA Publishing.
Cangialosi, F., E. Bruno and G. J. S. De Santis (2021). "Application of machine learning for fenceline monitoring of odor classes and concentrations at a wastewater treatment plant."  21(14): 4716.
Chang, Y.-R., Y.-J. Lee and D.-J. J. J. o. t. T. I. o. C. E. Lee (2019). "Membrane fouling during water or wastewater treatments: Current research updated."  94: 88-96.
Daramola, O. M., C. E. Apeh, J. O. Basiru, E. C. Onukwulu, P. O. J. J. o. C. E. Paul and S. L. Forthcoming (2023). "Optimizing reverse logistics for circular economy: Strategies for efficient material recovery and resource circularity."
De Maman, R., V. C. da Luz, L. Behling, A. Dervanoski, C. Dalla Rosa, G. D. L. J. E. S. Pasquali and P. Research (2022). "Electrocoagulation applied for textile wastewater oxidation using iron slag as electrodes."  29(21): 31713-31722.
Dhadumia, B., B. J. W. M. Paul and Research (2025)(2025). "A review of advanced sustainable waste management approaches of the oil and gas industry: Integrating green hybrid technologies for a cleaner future." 0734242X251385854.
Dhadumia, B., B. J. W. M. Paul and Research (2026). "A review of advanced sustainable waste management approaches of the oil and gas industry: Integrating green hybrid technologies for a cleaner future."  44(3): 237-251.
Digitemie, W. N., F. O. Onyeke, M. A. Adewoyin, I. N. J. I. J. o. M. R. Dienagha and G. Evaluation (2025). "Implementing circular economy principles in oil and gas: addressing waste management and resource reuse for sustainable operations."  6(1): 99-104.
Ejairu, U., A. T. Aderamo, H. C. Olisakwe, A. E. Esiri, U. M. Adanma, N. O. J. C. r. Solomon, r. i. Engineering and Technology (2024). "Eco-friendly wastewater treatment technologies (concept): Conceptualizing advanced, sustainable wastewater treatment designs for industrial and municipal applications."  2(1): 083-104.
Fernandes, J., P. J. Ramísio and H. J. E. Puga (2024). "A comprehensive review on various phases of wastewater technologies: Trends and future perspectives."  5(4): 2633-2661.
Ferri, E. N. and L. J. A. S. Bolelli (2025). "Wastewater remediation treatments aimed at water reuse: recent outcomes from pilot-and full-scale tests."  15(5): 2448.
Fisher, O. J., Y. Wang and A. J. W. R. Ahmed (2025). "Making waves: Transforming biofilm-based wastewater treatment using machine learning-driven real-time monitoring." 124491.
Gangwar, A., S. Rawat, A. Rautela, I. Yadav, A. Singh, S. J. E. Kumar, Development and Sustainability (2025). "Current advances in produced water treatment technologies: a perspective of techno-economic analysis and life cycle assessment."  27(7): 15077-15111.
Garg, M. C., S. Kumari and S. Agarwal (2024)(2024). The integration of artificial intelligence in advanced wastewater treatment systems. The AI Cleanse: Transforming Wastewater Treatment Through Artificial Intelligence: Harnessing Data-Driven Solutions, Springer: 1-27.
Gaurina-Međimurec, N., K. Simon, K. N. Mavar, B. Pašić, P. Mijić, I. Medved, V. Brkić, L. Hrnčević and K. Žbulj (2024). The circular economy in the oil and gas industry: a solution for the sustainability of drilling and production processes. Circular Economy on Energy and Natural Resources Industries: New Processes and Applications to Reduce, Reuse and Recycle Materials and Decrease Greenhouse Gases Emissions, Springer: 115-150.
Ghasemi, K., A. Akbari, S. Jahani and Y. J. T. C. J. o. C. E. Kazemzadeh (2025). "A critical review of life cycle assessment and environmental impact of the well drilling process."  103(6): 2499-2526.
Hossain, M. E., A. Al-Majed, A. R. Adebayo, A. S. Apaleke, S. M. J. E. E. Rahman and M. Journal (2017). "A CRITICAL REVIEW OF DRILLING WASTE MANAGEMENT TOWARDS SUSTAINABLE SOLUTIONS."  16(7)(7).
Iseri, F., H. Iseri, H. Shah, E. Iakovou, E. N. J. C. Pistikopoulos and C. Engineering (2025). "Planning strategies in the energy sector: Integrating bayesian neural networks and uncertainty quantification in scenario analysis & optimization."  198: 109097.
Iskandarani, M., S. Wang, A. Srinivasan, W. Carlisle Thacker, J. Winokur and O. M. J. J. o. G. R. O. Knio (2016). "An overview of uncertainty quantification techniques with application to oceanic and oil‐spill simulations."  121(4): 2789-2808.
Jain, M., A. Majumder, P. S. Ghosal and A. K. J. J. o. E. M. Gupta (2020). "A review on treatment of petroleum refinery and petrochemical plant wastewater: a special emphasis on constructed wetlands."  272: 111057.
Jamshidi, E., S. Saen, J. Golshaghagh, P. Kianoush, A. Adib and A. J. S. R. Mohammadi (2025). "Challenges of drilling Iran’s deepest surface hole in the saddle section of Changuleh oilfield with complex structure and pressure regimes."  15(1): 25302.
Jin, J., M. Liu, B. Chen, X. Wu, L. Yao, Y. Wang, X. Xiong, L. Wei, J. Li and Q. J. S. Tan (2025). "Artificial Intelligence in Chemical Dosing for Wastewater Purification and Treatment: Current Trends and Future Perspectives."  12(9): 237.
Jin, X., L. Zhang, M. Liu, S. Hu, Z. Yao, J. Liang, R. Wang, L. Xu, X. Shi and X. J. C. Bai (2022). "Characteristics of dissolved ozone flotation for the enhanced treatment of bio-treated drilling wastewater from a gas field."  298: 134290.
Kalhormohammadi, M. and S. J. S. R. Khoramipour.(2025) "Predictive modeling of coagulant dosing in drilling wastewater treatment using artificial neural networks."  15(1): 30003.
Kandpal, V., A. Jaswal, E. D. Santibanez Gonzalez and N. Agarwal (2024). Circular economy principles: shifting towards sustainable prosperity. Sustainable energy transition: Circular economy and sustainable financing for environmental, social and governance (ESG) practices, Springer: 125-165.
Khalili, Y., M. J. J. o. C. Ahmadi and P. Engineering (2023). "Reservoir modeling & simulation: Advancements, challenges, and future perspectives."  57(2): 343-364.
Kundu, D., D. Dutta, P. Samanta, S. Dey, K. C. Sherpa, S. Kumar and B. K. J. S. o. t. T. E. Dubey (2022). "Valorization of wastewater: A paradigm shift towards circular bioeconomy and sustainability."  848: 157709.
Lawan, M. S., R. Kumar, J. Rashid and M. A. E.-F. J. W. Barakat (2023). "Recent advancements in the treatment of petroleum refinery wastewater."  15(20): 3676.
Lebedev, A. and A. J. R. Cherepovitsyn (2024). "Waste management during the production drilling stage in the oil and gas sector: a feasibility study."  13(2): 26.
Li, C., A. Tiraferri, P. Tang, J. Ma and B. J. W. R. Liu (2025). "Current status, potential assessment, and future directions of biological treatments of unconventional oil and gas wastewater." 123217.
Lihu, L. and S. J. P. O. Jiahe (2025). "A novel strategy for resource utilization of oily drilling waste fluids in northern Shaanxi: Stepwise flotation of bentonite and barite using SDS and interfacial reaction mechanisms."  20(8): e0331415.
Lin, K., S. J. J. o. g. e. Wei and l.-c. development (2023). "Advancing the industrial circular economy: the integrative role of machine learning in resource optimization."  2(3): 122-136.
Liu, F., Y. Li, X. Wang and Z. J. M. Xia (2024). "Preparation and properties of reversible emulsion drilling fluid stabilized by modified nanocrystalline cellulose."  29(6): 1269.
Liu, H., S. Dong, J. Yang, S. Liao, S. J. J. o. H. Liu, Toxic, and R. Waste (2026). "Treatment and Disposal Technologies for Oil-Based Drilling Cuttings: An Overview and Prospects."  30(1): 03125004.
Loss, L., M. Cavali, A. Freitas, S. Kubeneck, G. Leme, A. Calvo, S. Soares, A. J. I. J. o. E. S. de Castilhos Junior and Technology (2026). "Environmental aspects of drill cuttings from oil operations: characterization, risk assessment, valorization, and treatment innovations."  23(4): 307.
Matheri, A. N., B. Mohamed, F. Ntuli, E. Nabadda, J. C. J. P. Ngila and P. a. b. c. Chemistry of the Earth (2022). "Sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant."  126: 103152.
Nagpal, M., M. A. Siddique, K. Sharma, N. Sharma, A. J. W. S. Mittal and Technology (2024). "Optimizing wastewater treatment through artificial intelligence: recent advances and future prospects."  90(3): 731-757.
Nautiyal, A., A. K. J. E. Mishra, Development and Sustainability (2025). "Machine learning approach for intelligent prediction of petroleum upstream stuck pipe challenge in oil and gas industry."  27(10).
Nooraiepour, M., M. Masoudi and H. J. S. R. Hellevang (2021). "Probabilistic nucleation governs time, amount, and location of mineral precipitation and geometry evolution in the porous medium."  11(1): 16397.
Olukoga, T., Y. J. S. D. Feng and Completion (2021). "Practical machine-learning applications in well-drilling operations."  36(04): 849-867.
Panagopoulos, A. and P. J. M. Michailidis (2025). "Membrane technologies for sustainable wastewater treatment: Advances, challenges, and applications in zero liquid discharge (zld) and minimal liquid discharge (mld) systems."  15(2): 64.
Pandey, A. K. J. E. S. W. R. and Technology (2025). "Sustainable water management through integrated technologies and circular resource recovery."  11(8): 1822-1846.
Pereira, L. B., C. M. Sad, E. V. Castro, P. R. Filgueiras and V. J. F. Lacerda Jr (2022). "Environmental impacts related to drilling fluid waste and treatment methods: A critical review."  310: 122301.
Pouran Manjily, H., M. Alborzi, T. Behrouz, S. M. J. J. o. S. Seyed-Hosseini and T. P. Management (2024). "Intelligent oil field technology maturity level assessment: using the technology readiness level criteria."  15(6): 1223-1246.
Rasouli, M. A., M. Karimpour-Fard, S. L. J. J. o. t. A. Machado and W. M. Association (2025). "An assessment of the uncertainties of methane generation in landfills."  75(6): 464-482.
Reichert, P. J. W. S. and Technology (2020). "Towards a comprehensive uncertainty assessment in environmental research and decision support."  81(8): 1588-1596.
Rotan, K., Q. Goettel, K. Smith, A. Gonzalez, U. Onyemaobi and M. Yurukcu (2024). "AI/ML Technology for Water Treatment in Oil and Gas Industry: A Review Paper."
Sajib, M., A. Jaman, M. A. Ullah, M. A. B. H. Susan and M. S. Miran (2025). AI Technologies for Treating Petroleum Wastewater. Management of Petroleum Wastewater and Oil Field Discharges: Diagnosis, Impacts and Treatment, Springer: 81-118.
Sangamnere, R., T. Misra, H. Bherwani, A. Kapley and R. J. S. W. R. M. Kumar (2023). "A critical review of conventional and emerging wastewater treatment technologies."  9(2): 58.
Scheidt, C., L. Li and J. Caers (2018). Quantifying uncertainty in subsurface systems, John Wiley & Sons.
Shaaban, Y. A. (2025). Wastewater Treatment: Using AI and Response Surface Methodology to Predict and Optimize. Management of Petroleum Wastewater and Oil Field Discharges: Diagnosis, Impacts and Treatment, Springer: 27-45.
Shokir, E. M., S. Sallam and M. M. J. A. o. Abdelhafiz (2024). "Comprehensive Wellbore Stability Modeling by Integrating Poroelastic, Thermal, and Chemical Effects with Advanced Numerical Techniques."  9(52): 51536-51553.
Sircar, A., K. Yadav, K. Rayavarapu, N. Bist and H. J. P. R. Oza (2021). "Application of machine learning and artificial intelligence in oil and gas industry."  6(4): 379-391.
Smol, M., C. Adam, M. J. J. o. M. C. Preisner and W. Management (2020). "Circular economy model framework in the European water and wastewater sector."  22(3): 682-697.
Sundui, B., O. A. Ramirez Calderon, O. M. Abdeldayem, J. Lázaro-Gil, E. R. Rene, U. J. C. T. Sambuu and E. Policy (2021). "Applications of machine learning algorithms for biological wastewater treatment: updates and perspectives."  23(1): 127-143.
Tawfik, M. J. P. o. (2024). "Optimized intrusion detection in IoT and fog computing using ensemble learning and advanced feature selection."  19(8): e0304082.
Teodoriu, C. and O. J. E. Bello (2021). "An outlook of drilling technologies and innovations: Present status and future trends."  14(15): 4499.
Thacker, J. B., D. D. Carlton Jr, Z. L. Hildenbrand, A. F. Kadjo and K. A. J. W. Schug (2015). "Chemical analysis of wastewater from unconventional drilling operations."  7(4): 1568-1579.
Thompson, M. and B. J. W. E. R. Dvorak (2024). "Wastewater reuse benefits for municipal complete retention lagoons: Life cycle assessment and dynamic modeling."  96(8): e11098.
Tian, D., W. Ma, L. Du, H. Chen, Y. Zhou, J. Tan, P. Zhang, Y. Sun, B. Xiao, Y. J. W. Qu, Air, and S. Pollution (2026). "Challenges and Opportunities in Tunnel Wastewater Treatment: Engineering Perspectives for Sustainable Management."  237(6): 387.
Tsolakis, N., T. S. Harrington, J. S. J. P. P. Srai and Control (2023). "Digital supply network design: a Circular Economy 4.0 decision-making system for real-world challenges."  34(10): 941-966.
Wang, Z., S. Li, Z. Xu, S. A. Aryana and J. J. C. Cai (2025). "Advances and challenges in foam stability: Applications, mechanisms, and future directions."  15(3): 58-73.
Warsinger, D. M., S. Chakraborty, E. W. Tow, M. H. Plumlee, C. Bellona, S. Loutatidou, L. Karimi, A. M. Mikelonis, A. Achilli and A. J. P. i. p. s. Ghassemi (2018). "A review of polymeric membranes and processes for potable water reuse."  81: 209-237.
Waware, S. Y., N. K. Nagalli, S. Sugumaran, P. D. Patil, R. Biradar, A. A. Kadam, K. B. Ghunake, S. S. Kore, G. Murali, A. S. J. N.-J. o. S. Kurhade and T. Research (2025). "AI-Driven Innovations in the Exploration, Extraction, and Processing of Minerals, Metals, and Petroleum: A Review."  7(4): 209-227.
Wei, X., S. Zhang, Y. Han and F. A. J. W. E. R. Wolfe (2019). "Treatment of petrochemical wastewater and produced water from oil and gas."  91(10): 1025-1033.
Yang, H., H. Diao, Y. Zhang and S. J. J. o. e. m. Xia (2022). "Treatment and novel resource-utilization methods for shale gas oil based drill cuttings–A review."  317: 115462.
Yang, J., J. Sun, R. Wang, Y. J. E. s. Qu and p. research (2023). "Treatment of drilling fluid waste during oil and gas drilling: A review."  30(8): 19662-19682.
Yuan, H. and Z. J. B. t. He (2015). "Integrating membrane filtration into bioelectrochemical systems as next generation energy-efficient wastewater treatment technologies for water reclamation: A review."  195: 202-209.
Zhang, T. J. W. (2025). Sustainable wastewater treatment and the circular economy, MDPI. 17: 335.
Zhang, W., Q. Li, S. Dong, H. Liu, K. Dong, X. Wu, M. Sui and F. J. J. o. W. P. E. Zhang (2024). "Synthesis of mixed-base active material from drilling fluid solid waste and biomass for oil wastewater adsorption and its mechanism."  66: 106076.
Zhang, Y., P. Xu, M. Xu, L. Pu and X. J. A. o. Wang (2022). "Properties of bentonite slurry drilling fluid in shallow formations of deepwater wells and the optimization of its wellbore strengthening ability while drilling."  7(44): 39860-39874.
Zhou, J., T. Shi, Q. Qian, C. He and J. J. S. p. Ren (2023). "Protocol for the design and accelerated optimization of a waste-to-energy system using AI tools."  4(4): 102685.
Zhou, Y., C. Deng, X. Chen, Y. He, G. Fang, Z. Jin, Y. J. W. M. Liu and Research (2025). "Engineering design and application of large-scale oil-based drilling cuttings treatment project."  43(2): 282-292.
Zidaoui, I. (2024). Advanced data validation methods for wastewater sensors using Artificial Intelligence, Université de Strasbourg.
Zong, Z. and Y. J. J. o. t. k. e. Guan (2025). "AI-driven intelligent data analytics and predictive analysis in Industry 4.0: Transforming knowledge, innovation, and efficiency."  16(1): (1): 864864--903903.
Journal of Gas Technology
Volume 10, Issue 2 - Serial Number 15
December 2025
Pages 88-118