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Current shale gas well production capacity predictions primarily rely on analytical and numerical simulation methods, which necessitate extensive calculations and manual parameter tuning and produce lowly accurate predictions. Although employing neural networks yields highly accurate predictions, they can easily fall into local optima. This paper suggests a new way to use Cuckoo Search (CS)-optimized neural networks to make shale gas well production capacity predictions more accurate and to solve the problem of local optima. It aims to assist engineers in devising more effective development plans and production strategies, optimizing resource allocation, and reducing risk. The method first analyzes the factors influencing the production capacity of shale gas wells in a block located in western China through correlation coefficients. It identifies the main factors affecting the gas test absolute open flow as organic carbon content, small-layer passage rate, fracture pressure, acid volume, pump-in fluid volume, brittle mineral content in the rock, and rock density. Subsequently, we used the CS algorithm to conduct the global training of the neural network, avoiding the problem of local optima, and established a neural network model for predicting shale gas well production capacity optimized by the CS algorithm. A comparative analysis with other relevant methods demonstrates that the CS-optimized neural network model can accurately predict production capacity, enabling a more rational and effective exploitation of shale gas resources, which lower development costs and increase the economic returns of oil and gas fields. Compared to numerical simulation, SVM, and BP neural network algorithms, the CS-optimized BP neural network (CS-BP) exhibits significantly lower prediction error. Its correlation coefficient between predicted and actual values reaches as high as 0.9924. Verification experiments conducted on another shale gas well also demonstrate that, in comparison to the BP neural network algorithm, CS-BP offers superior prediction performance, with model validation showing a prediction error of only 0.05. This study can facilitate more rational and efficient exploitation of shale gas resources, reduce development costs, and enhance the economic benefits of oil and gas fields. [ABSTRACT FROM AUTHOR]

Copper oxide and hematite (CuO/α-Fe2O3) composite catalysts were prepared by using goethite as precursor adopted impregnation way and applied to the dielectric barrier discharge (DBD) catalytic decomposition of gaseous chlorobenzene. The CuO/α-Fe2O3 composite was characterised by X-ray diffraction, Brunauer–Emmett–Teller method, scanning electron microscopy and X-ray photoelectron spectrometer technique. The decomposition efficiency and energy yield of gaseous chlorobenzene in DBD catalysis system were studied by a function of gas flow rate, initial concentration and input voltage. The results showed that the CuO/α-Fe2O3 composite catalyst exhibited remarkable performance on chlorobenzene decomposition when the molar ratio was 0.4 and calcination temperature was 450°C. When the chlorobenzene initial concentration was 230 mg m−3, the chlorobenzene decomposition efficiency and mineralisation rate on the DBD catalysis system reached 73.33% and 63.37%, respectively, its decomposition and mineralisation efficiency were enhanced about 20.5% and 16.61%, respectively, compared with the bare DBD system, and it also benefited to significantly reduce the ozone and NO2 by-products. The possible pathway of chlorobenzene decomposition in the DBD catalytic hybrid system was proposed based on the products analysis. [ABSTRACT FROM AUTHOR]

Clarifying the formation mechanism of single-atom sites guides the design of emerging single-atom catalysts (SACs) and facilitates the identification of the active sites at atomic scale. Herein, a molten-salt atomization strategy is developed for synthesizing zinc (Zn) SACs with temperature universality from 400 to 1000/1100 °C and an evolved coordination from Zn-N 2 Cl 2 to Zn-N 4 . The electrochemical tests and in situ attenuated total reflectance-surface-enhanced infrared absorption spectroscopy confirm that the Zn-N 4 atomic sites are active for electrochemical carbon dioxide (CO 2 ) conversion to carbon monoxide (CO). In a strongly acidic medium (0.2 m K 2 SO 4 , pH = 1), the Zn SAC formed at 1000 °C (Zn 1 NC) containing Zn-N 4 sites enables highly selective CO 2 electroreduction to CO, with nearly 100% selectivity toward CO product in a wide current density range of 100-600 mA cm -2 . During a 50 h continuous electrolysis at the industrial current density of 200 mA cm -2 , Zn 1 NC achieves Faradaic efficiencies greater than 95% for CO product. The work presents a temperature-universal formation of single-atom sites, which provides a novel platform for unraveling the active sites in Zn SACs for CO 2 electroreduction and extends the synthesis of SACs with controllable coordination sites., (© 2024 Wiley‐VCH GmbH.)

Copper oxide and hematite (CuO/ α -Fe 2 O 3 ) composite catalysts were prepared by using goethite as precursor adopted impregnation way and applied to the dielectric barrier discharge (DBD) catalytic decomposition of gaseous chlorobenzene. The CuO/ α -Fe 2 O 3 composite was characterised by X-ray diffraction, Brunauer-Emmett-Teller method, scanning electron microscopy and X-ray photoelectron spectrometer technique. The decomposition efficiency and energy yield of gaseous chlorobenzene in DBD catalysis system were studied by a function of gas flow rate, initial concentration and input voltage. The results showed that the CuO/ α -Fe 2 O 3 composite catalyst exhibited remarkable performance on chlorobenzene decomposition when the molar ratio was 0.4 and calcination temperature was 450°C. When the chlorobenzene initial concentration was 230 mg m -3 , the chlorobenzene decomposition efficiency and mineralisation rate on the DBD catalysis system reached 73.33% and 63.37%, respectively, its decomposition and mineralisation efficiency were enhanced about 20.5% and 16.61%, respectively, compared with the bare DBD system, and it also benefited to significantly reduce the ozone and NO 2 by-products. The possible pathway of chlorobenzene decomposition in the DBD catalytic hybrid system was proposed based on the products analysis.