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Addressing the critical issue of water pollution, this review article emphasizes the need to remove hazardous dyes and phenolic compounds from wastewater. These pollutants pose severe risks due to their toxic, mutagenic, and carcinogenic properties. The study explores various techniques for the remediation of organic contaminants from wastewater, including an enzymatic approach. A significant challenge in enzymatic wastewater treatment is the loss of enzyme activity and difficulty in recovery post-treatment. To mitigate these issues, this review examines the strategy of immobilizing enzymes on newly developed nanostructured materials like graphene, carbon nanotubes (CNTs), and metal–organic frameworks (MOFs). These materials offer high surface areas, excellent porosity, and ample anchoring sites for effective enzyme immobilization. The review evaluates recent research on enzyme immobilization on these supports and their applications in biocatalytic nanoparticles. It also analyzes the impact of operational factors (e.g., time, pH, and temperature) on dye and phenolic compound removal from wastewater using these enzymes. Despite promising outcomes, this review acknowledges the challenges for large-scale implementation and offers recommendations for future research to tackle these obstacles. This review concludes by suggesting that enzyme immobilization on these emerging materials could present a sustainable, environmentally friendly solution to the escalating water pollution crisis. [ABSTRACT FROM AUTHOR]

The calcium carbonate (CaCO3) scale is one of the most common oilfield scales and oil and gas production bane. CaCO3 scale can lead to a sudden halt in production or, worst-case scenario, accidents; therefore, CaCO3 scale formation prevention is essential for the oil and gas industry. Scale inhibitors are chemicals that can mitigate this problem. We used two popular theoretical techniques in this study: Density Functional Theory (DFT) and Ab Initio Molecular Dynamics (AIMD). The objective was to investigate the inhibitory abilities of mixed oligomers, specifically acrylamide functionalized silica (AM-Silica). DFT studies indicate that Ca2+ does not bind readily to acryl acid and acrylamide; however, it has a good binding affinity with PAM and Silica functionalized PAM. The highest binding affinity occurs in the silica region and not the –CONH functional groups. AIMD calculations corroborate the DFT studies, as observed from the MD trajectory that Ca2+ binds to PAM-Silica by forming bonds with silicon; however, Ca2+ initially forms a bond with silicon in the presence of water molecules. This bonding does not last long, and it subsequently bonds with the oxygen atoms present in the water molecule. PAM-Silica is a suitable calcium scale inhibitor because of its high binding affinity with Ca2+. Theoretical studies (DFT and AIMD) have provided atomic insights on how AM-Silica could be used as an efficient scale inhibitor. [ABSTRACT FROM AUTHOR]

Produced water (PW) is the most significant waste stream generated in the oil and gas industries. The generated PW has the potential to be a useful water source rather than waste. While a variety of technologies can be used for the treatment of PW for reuse, biological-based technologies are an effective and sustainable remediation method. Specifically, microalgae, which are a cost-effective and sustainable process that use nutrients to eliminate organic pollutants from PW during the bioremediation process. In these treatment processes, microalgae grow in PW free of charge, eliminate pollutants, and generate clean water that can be recycled and reused. This helps to reduce CO2 levels in the atmosphere while simultaneously producing biofuels, other useful chemicals, and added-value products. As such, this review focuses on PW generation in the oil and gas industry, PW characteristics, and examines the available technologies that can be used for PW remediation, with specific attention to algal-based technologies. In addition, the various aspects of algae growth and cultivation in PW, the effect of growth conditions, water quality parameters, and the corresponding treatment performance are presented. Lastly, this review emphasizes the bioremediation of PW using algae and highlights how to harvest algae that can be processed to generate biofuels for added-value products as a sustainable approach. [ABSTRACT FROM AUTHOR]

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can be further used for hydraulic calculations. Overall, the experimental study presented in this paper, together with the proposed ML-based framework, adds valuable information to the design of PAM/PEI-based mud. The ML models allowed a wide range of rheology assessments for various drilling fluid formulations with a mean accuracy of up to 91%. The case study has shown that with the appropriate combination of materials, reasonable rheological properties could be achieved to prevent loss circulation by managing the equivalent circulating density (ECD). [ABSTRACT FROM AUTHOR]

Steelmaking is an energy-intensive process that generates considerable amounts of by-products and wastes, which often pose major environmental and economic challenges to the steel-making industry. One of these by-products is steel dust that is produced during the separation of impurities in the smelting and refining of metals in steel-making furnaces. In this study, electric arc furnace (EAF) dust has been evaluated as a potential, low-cost additive to increase the viscosity and weight of drilling muds. Currently, the cost of drilling operations typically accounts for 50 to 80% of the exploration costs and about 30 to 80% of the subsequent field development costs. Utilization of steelmaking waste in drilling fluids formulations is aimed to produce new and optimized water-based drilling formulations, which is expected to reduce the amount of bentonite and other viscosifier additives used in the drilling formulations. The results showed that in a typical water-based drilling fluid of 8.6 ppg (1030.51 kg/m3), the amount of standard drilling grade bentonite could be reduced by 30 wt.% with the addition of the proposed new additive to complete the required mud weight. The mixture proved to be stable with no phase separation. [ABSTRACT FROM AUTHOR]