Innovations and improvements in hydraulic fracturing and horizontal well technologies have contributed to the success of the shale gas industry; however, the industry is also challenged by freshwater use and environmental health issues, and this makes precise quantification of water consumption important. The objective of this study was to better understand water sustainability and availability of the projected shale gas from 2018 to 2030 in the Weiyuan play, China. The water footprint framework was used to quantify the potential water use and environmental impacts on different time scales. The results showed that the water use per well ranged from 11,300 to 60,660 m³, with a median of 36,014 m³, totaling ~ 3.44 Mm³ for 97 wells. Yearly evaluation results showed that the gray water footprint was the main contributor and accounted for 83.82% to 96.76%, which was dependent on the different treatment percentage scenario. The monthly environmental impact results indicated that the annual streamflow statistics were more likely to prevent water withdrawal. Water quality issues may be alleviated through recycling and retreatment measures that improve current waste water management strategies. Resource regulators should manage their water resources by matching water demand to water availability or replenishment.

In the last decade, low-quality unconventional oil and gas resources have become the primary source for domestic oil and gas storage and production, and hydraulic fracturing has become a crucial method for modifying unconventional reservoirs. This paper puts forward a framework for predicting hydraulic fracture parameters. It combines eXtreme Gradient Boosting and Bayesian optimization to explore data-driven machine learning techniques in fracture simulation models. Analyzing fracture propagation through mathematical models can be both time-consuming and costly under conventional conditions. In this study, we predicted the physical parameters and three-dimensional morphology of fractures across multiple time series. The physical parameters encompass fracture width, pressure, proppant concentration, and inflow capacity. Our results demonstrate that the fusion model applied can significantly improve fracture morphology prediction accuracy, exceeding 0.95, while simultaneously reducing computation time. This method enhances standard numerical calculation techniques used for predicting hydraulic fracturing while encouraging research on the extraction of unconventional oil and gas resources.

Innovations and improvements in hydraulic fracturing and horizontal well technologies have contributed to the success of the shale gas industry; however, the industry is also challenged by freshwater use and environmental health issues. Increasing water impact makes precise quantification of water consumption important. The objective in this study was to better understand water sustainability and availability of the projected shale gas from 2018 to 2030 in the Weiyuan play, China. The water footprint framework was used to quantify the potential water use and environmental impacts on different time scales. The results showed that the water use per well ranged from 11351.3 to 60664.73 m3, with a median of 36013.94 m3, totaling ~3.44 Mm3 for 97 wells. Yearly evaluation results showed that the gray water footprint was the main contributor and accounted for 83.82% to 96.76%, which was dependent on different scenarios of treatment percentages. The monthly environmental impact results indicated that the annual streamflow statistics were more likely to prevent water withdrawal. Water quality issues may be alleviated through recycling and retreatment measures that improve current waste water management strategies. Resource regulators should manage their water resources by matching water demand to water availability or replenishment.

Geothermal resource is one of the most promising renewable energies, which is successfully accessed by the enhanced geothermal system (EGS) characterized by a complex fracture network. Therefore, complex fracture networks with hydraulic and natural fractures of different fracture orientations and intensities are established in this study. The natural fractures are randomly distributed in the geothermal reservoir. The working fluid flowing and heat exchange in the geothermal reservoir are simulated by coupling model, considering the effects of temperature variation on the density, viscosity, thermal conductivity and specific heat capacity of working fluid, and the permeability of reservoir matrix. Effects of natural fracture orientation and intensity, position of injection and production wells, and geothermal reservoir permeability on the heat production behavior are analyzed. The simulation reveals that the low-temperature region in the geothermal reservoir could breakthrough along natural fractures. When the direction of injection and production wells is consistent with the orientation range of natural fractures, the reservoir exploitation ratio and the heat extraction rate are the largest, but the temperature stability time of the produced fluid is the shortest and the cooling rate is the fastest. Increasing the intensity of natural fractures is helpful to increase the heat extraction rate, but the temperature of production wells decreases more easily. Increasing the distance perpendicular to the hydraulic fracture can better improve the performance of production wells. High reservoir permeability is not conducive to the stability of production fluid temperature, but can greatly increase the exploitation ratio of the geothermal reservoir.

In order to further improve the efficiency and economic benefits of multi-stage fracturing of unconventional oil and gas horizontal wells, it is urgently needed to conduct comprehensive reservoir quality evaluation research on the whole horizontal well section. Firstly, based on logging data, focusing on reservoir quality and completion quality, and comprehensively considering key factors such as reservoir physical property indexes and fracability indexes, a subjective and objective coupled evaluation model of the entropy weight method (EWM) and the analytic hierarchy process (AHP) without bias is established to obtain the composite reservoir quality index. Then, unsupervised gaussian mixture model (GMM) clustering algorithms are used to classify the reservoir comprehensive quality index and finally four grades of fracturing stages are established. Taking shale oil well A and B of the Permian Lucaogou Formation in Jimsar Sag, Junggar Basin, as examples, the comprehensive reservoir quality evaluation and clustering model training, testing, and prediction were carried out. By comparing the clustering results with the actual fracturing stages and oil production, it is found that the evaluation results obtained by the GMM clustering algorithms based on the coupled evaluation model of EWM and AHP can identify the good fracturing grades. The algorithm can also predict the fracturing grades of other wells in the same block. It proves the accuracy of the method proposed in this paper and provides a favorable technical basis for determining the placement of multi-cluster fracturing perforation.