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Capillary force and boundary layer effect are the main causes of non-Darcy flow in tight oil reservoir. This paper proposes a non-Darcy flow dynamics characterization method for low-speed water flooding in tight oil reservoirs. It applies constant-speed mercury injection and casting thin section experiments to quantitatively characterize the micro-pore throat structure parameters, and uses the visual experimental device to measure the boundary layer thickness and fit the expression of the relationship between boundary layer thickness and displacement pressure gradient and fluid viscosity. The results show that the ratio of boundary layer thickness to microtubule radius changes exponentially with the pressure gradient and fluid viscosity and that the boundary layer thickness decreases gradually with the increase of pressure gradient. Given the capillary force and boundary layer thickness, the flow rate of single capillary is calculated. On this basis, the equation of nonlinear seepage dynamic characteristics per unit area of core is derived by taking into account the throat distribution frequency and throat size characteristics. The new seepage flow model can reflect the nonlinear seepage flow law of tight oil reservoir and provide reference for parameter formulation during water flooding development of tight oil reservoir.

It is complex and obviously different for the production characteristics of CO2 water-alternating-gas (WAG) flooding in tight reservoir and influenced by quite a few factors. Therefore, the prediction of oil production is a key matter of efficient development of CO2 WAG to be solved in tight reservoirs. In order to cope with this issue, in this paper, the production characteristics of CO2 WAG flooding are analyzed and classified in tight oil reservoir of block A as an example. On this basis, properties of reservoir, fracture factors, and operational factors are taken into account and the sensitivity of the influencing factors is carried out. Subsequently, the gray relation analysis is used to confirm the primary influencing factors. Finally, the evaluated model is established to predict oil production rapidly. The results illustrate that the wells of CO2 WAG flooding in tight reservoirs can be divided into four types of fluid production characteristics. The production is affected by permeability, reservoir thickness, amount of sand entering the ground, amount of liquid entering the ground, gas/water ratio, the injection rate, injection pressure, permeability variation coefficient, water sensitive index, acid sensitive index, and expulsion pressure. And the primary influencing factors are the amount of sand entering the ground, reservoir thickness, and amount of liquid entering the ground. The oil production can be predicted quickly based on the relation between production and comprehensive evaluation factor of production. The average relative error between the predicted results and the actual production is 8%, which proves the reliability and accuracy of this method.

Trips and failures are common occurrences in the Electric Submersible Pump (ESP) systems. The random nature of these trips and failures will lead to low industry run-life and high workover costs for ESP companies and operators. To perform early detection and take corrective actions to handle the potential incidents, ESP operation data collected from downhole and surface sensors are used to perform diagnostics and prognostics to identify trips and failures. In this study, Principal Component Analysis (PCA) method serves as a pre-processing method to retain the most essential principal components to reevaluate the initial ESP system. For a single well system, the Squared Prediction Error (SPE) and Hotelling T-square statistic (T2) equations are employed for numerical visualization in the new principal component space and therefore detection of the potential ESP trips or failures. For the whole well group, the score plot of three principal components provides a solution that enables to distinguish different clusters of stable operation, trip and failure regions, and diagnose the upcoming ESP trips and failures. In this way, the predictive model is bulit to continuously analyze the ESP operation and automatically perform health monitoring for any ESP system. This paper concludes that the predictive model has the potential to construct a real-time proactive surveillance system to identify dynamic anomalies and therefore predict developing trips or failures in the ESP system.

CO2 enhanced oil recovery (EOR) has been proven its capability to explore the unconventional tight oil reservoirs and potential for geological carbon storage. Meanwhile, the extremely low permeability pores exaggerate the difficulty CO2 EOR and geological storage processing in the actual field. This paper initiates the ultrasonic-assisted approach to facilitate the oil-gas miscibility development and finally contribute to unlock more tight oils. First, the physical properties of crude oil with and without ultrasonic treatments were experimentally analysed through gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR) and viscometer. Second, the oil-gas minimum miscibility pressures (MMPs) were measured from the slim-tube test and the miscibility developments with and without ultrasonic treatments were interpreted from the mixing-cell method. Third, the nuclear-magnetic resonance (NMR) assisted coreflood tests were conducted to physically model the recovery process in porous media and directly obtain the recovery factor. Basically, the ultrasonic treatment (40KHz and 200W for 8 hours) was found to substantially change the oil properties, with viscosity (at 60°C) reduced from 4.1 to 2.8mPa·s, contents of resin and asphaltene decreased from 27.94% and 6.03% to 14.2% and 3.79%, respectively. The FTIR spectrum shows the unsaturated C-H bond, C-O bond and C≡C bond in macromolecules were broken from ultrasonic, which caused the macromolecules (e.g., resin and asphaltenes) to be decomposed into smaller carbon-number molecules. Accordingly, the MMP was determined to be reduced from 15.8 to 14.9MPa from the slim-tube test and the oil recovery factor increased by over 10%. This study reveals the mechanisms of ultrasonic-assisted CO2 miscible EOR in producing tight oils.

Microplastics (MPs), as pollutants of environmental concern, are correlated with increased risk of various respiratory diseases. Nevertheless, whether or not MPs have adverse influences on the interfacial properties of lung surfactant (LS), and its effect on the generation of reactive oxygen species are poorly understood. In the present study, natural LS extracted from porcine lungs was used to investigate the interaction with polystyrene as a representative MPs. The results showed that the phase behavior, surface tension, and membrane structure of the LS were altered in the presence of polystyrene. Adsorption experiments demonstrated that in the mixed system of polystyrene and LS (the main active ingredients are phospholipids and proteins), adsorption of phospholipid components by polystyrene was notably higher than that of proteins. Moreover, polystyrene can accelerate the conversion between ascorbic acid and deoxyascorbic acid, thereby producing hydrogen peroxide (HOOH) in simulated lung fluid (containing LS) and further giving rise to an increase in the content of hydroxyl radicals (•OH). This work provides new insight into the potential hazard of MPs in human respiratory system, which is helpful for deeply understanding the unfavorable physicochemical effects of MPs exposure and the role of inhaled MPs on lung health.

Carbon dioxide miscible flooding has been proven to be one of the most effective enhanced oil recovery (EOR) technologies, particularly for light and medium oil reservoirs. However, specific effects of pore structure on CO2 miscible flooding recovery in low permeability reservoir lack in-depth understandings. In this paper, pore structures are specifically studied by means of the molecular mechanics to evaluate their effects on the CO2 EOR in the low permeability reservoir. First, a series lab experiments are performed for the pore and fluid characterization. More specifically, the pore throat size and distribution frequency are measured from the high-pressure mercury injection and nuclear magnetic resonance. The minimum miscibility pressure is determined from the slim-tube tests with known oil compositions tested from gas chromatography analysis. Second, the regularity of CO2 extraction is explored on the basis of molecular mechanics and the thickness of raffinate is calculated. Finally, the raffinate volume and recovery ratio in the pores are calculated after the CO2 miscible flooding. The results show that a raffinate-layer with thickness of 0.13 μm remains on the surface of the pore after the CO2 miscible flooding, which would cause the oil to be immobile since the throat could be blocked when the throat radius is smaller than 0.26 μm. The recoveries of cores C-1 and C-2 are 70.1 % and 61.4 % from calculations and 68.4 % and 59.8 % from experiments, whose errors are 2.5 % and 2.7 %, respectively. This study would be beneficial to analyze the CO2 miscible flooding in reservoirs with different pore structures and provide technical support for improving CO2 utilization efficiency.

CO2 enhanced oil recovery (EOR) has proven its capability to explore unconventional tight oil reservoirs and the potential for geological carbon storage. Meanwhile, the extremely low permeability pores increase the difficulty of CO2 EOR and geological storage processing in the actual field. This paper initiates the ultrasonic-assisted approach to facilitate oil–gas miscibility development and finally contributes to excavating more tight oils. Firstly, the physical properties of crude oil with and without ultrasonic treatments were experimentally analyzed through gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR) and viscometer. Secondly, the oil–gas minimum miscibility pressures (MMPs) were measured from the slim-tube test and the miscibility developments with and without ultrasonic treatments were interpreted from the mixing-cell method. Thirdly, the nuclear-magnetic resonance (NMR) assisted coreflood tests were conducted to physically model the recovery process in porous media and directly obtain the recovery factor. Basically, the ultrasonic treatment (40 KHz and 200 W for 8 h) was found to substantially change the oil properties, with viscosity (at 60 °C) reduced from 4.1 to 2.8 mPa·s, contents of resin and asphaltene decreased from 27.94% and 6.03% to 14.2% and 3.79%, respectively. The FTIR spectrum showed that the unsaturated C-H bond, C-O bond and C≡C bond in macromolecules were broken from the ultrasonic, which caused the macromolecules (e.g., resin and asphaltenes) to be decomposed into smaller carbon-number molecules. Accordingly, the MMP was determined to be reduced from 15.8 to 14.9 MPa from the slim-tube test and the oil recovery factor increased by an additional 11.7%. This study reveals the mechanisms of ultrasonic-assisted CO2 miscible EOR in producing tight oils.

Stochastic Gradient Descent (SGD) is a well-received algorithm for large-scale optimization in neural networks for its low iteration cost. However, due to Gradient variance, it often has difficulty in finding optimal learning rate and thus suffers from slow convergence. Using momentum is proven to be a simple effective way of overcoming the slow convergence problem of SDG as long as momentum is properly set. According to the performance metrics, this paper proposes a novel statistical model for analyzing the performance of neural networks. The model takes into account learning rate and momentum, and the method can be used to evaluate and verify their interaction effects on neural network performance. Our study shows that the interaction effects are significant. When momentum has a value smaller than 0.5, the impact on the training time is not statistically noticeable.

The complexity of software has increased enormously with the fast development of sophisticated modern software. Thus the software structure designing would consume more time and more manpower. In this paper, we proposed an automatic generating method of software structure designing based on the ant colony planning technique which has the character of global parallel searching and the ability of convergence acceleration in the process of solution searching.