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The use of natural gas as an energy source is increasing significantly due to its low greenhouse gas emissions. However, the common methods of natural gas storage and transportation, such as liquefied or compressed natural gas, are limited in their applications because they require extreme conditions. Gas hydrate technology can be a promising alternative to conventional approaches, as artificially synthesized hydrates provide an economical, environmentally friendly, and safe medium to store energy. Nevertheless, the low rate of hydrate formation is a critical problem that hinders the industrial application of this technology. Therefore, chemical promoters are being developed to accelerate the kinetics of gas hydrate formation. In this paper, the effect of new sodium sulfosuccinate compounds, synthesized based on glycerol and pentaerythritol, on methane hydrate formation was studied. Experiments under dynamic conditions using high-pressure autoclaves demonstrated that the conversion of water-to-hydrate forms increased from 62 ± 5% in pure water to 86 ± 4% for the best promoter at concentration 500 ppm. In addition, the rate of hydrate formation increases 2–4 times for different concentrations. Moreover, none of the synthesized reagents formed foam, compared to sodium dodecyl sulfate, in which the foam rate was 3.7 ± 0.2. The obtained reagents showed good promotional properties and did not form foam, which makes them promising promoters for gas hydrate technology.

With the proliferation of large-scale grid-connected wind farms, subsynchronous oscillation (SSO) incidents associated with Type-4 wind turbines (WTs) with a permanent magnet synchronous generator (PMSG) have occurred frequently. These incidents have caused severe reliability risks to the power grid. Conventionally, P-Q capability charts are utilized to ensure the safety operating region of a synchronous generator. However, a PMSG WT exhibits completely different and dynamic P-Q capability characteristics due to the difference in energy conversion technique and several critical factors related to the WT power converters. This paper presents a comprehensive dynamic P-Q capability study of a PMSG WT with sufficient and accurate considerations of the WT control and operation in the dq reference frame, its power converter constraints, and grid dynamics. Models of a PMSG WT are first developed based on its control principle in the dq reference frame. Then, algorithms for obtaining the P-Q capability charts of the WT are developed with the considerations of complete WT constraints in different aspects. The study analyzes the root cause of many abnormal operations of grid-connected PMSG WTs, reported in the literature, from the dynamic P-Q capability perspectives. The proposed study is verified via an electromagnetic transient (EMT) model of a grid-connected Type-4 WT.

Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of oilfields, which is an important basis to ensure the stable production of the oilfield. Due to existing oilfield development index prediction methods being difficult to accurately reflect the complex nonlinear problem in the oil field development process, using the artificial neural network, which can predict the oilfield development index with the function of infinitely close to any non-linear function, will be the most ideal prediction method at present. This article summarizes four commonly used artificial neural networks: the BP neural network, the radial basis neural network, the generalized regression neural network, and the wavelet neural network, and mainly introduces their network structure, function types, calculation process and prediction results. Four kinds of artificial neural networks are optimized through various intelligent algorithms, and the principle and essence of optimization are analyzed. Furthermore, the advantages and disadvantages of the four artificial neural networks are summarized and compared. Finally, based on the application of artificial neural networks in other fields and on existing problems, a future development direction is proposed which can serve as a reference and guide for the research on accurate prediction of oilfield development indicators.

Most of the current Russian oil production comes from mature fields. The application of enhanced oil recovery methods on oil fields increases recovery efficiency. This article presents an analysis of the increased field development efficiency methods of the Volga-Ural oil and gas region, which allows the full and efficient development of last-stage fields with unconventional reserves and production stabilization. The selection of the optimum method for a given field is a complex procedure consisting of many stages, from collecting data about the field, through more advanced data interpretation, to working out a detailed proposal for the most efficient extraction method. In this article the instantaneous and average annual growth above wells average was taken as a performance criterion for enhanced oil recovery methods. Based on the performed analysis, it follows that candidate wells for enhanced oil recovery method use must meet the I group parameters (high values of the remaining recoverable reserves and improved reservoir properties, low water cut, obtained oil rate increase). In order to assess the possible increase in production rate after enhanced oil recovery methods hydrodynamic modeling of radial drilling, acid treatment and water-alternated-gas injection for two oil fields of the Volga-Ural oil and gas region were performed.

The thermal masses of components influence the performance of many adsorption heat pump systems. However, typically when experimental adsorption systems are reported, data on thermal mass are missing or incomplete. This work provides original measurements of the thermal masses for experimental sorption heat exchanger hardware. Much of this hardware was previously reported in the literature, but without detailed thermal mass data. The data reported in this work are the first values reported in the literature to thoroughly account for all thermal masses, including heat transfer fluid. The impact of thermal mass on system performance is also discussed, with detailed calculation left for future work. The degree to which heat transfer fluid contributes to overall effective thermal mass is also discussed, with detailed calculation left for future work. This work provides a framework for future reporting of experimental thermal masses. The utilization of this framework will enrich the data available for model validation and provide a more thorough accounting of adsorption heat pumps.

This article deals with the creation of a power supply system of wireless sensors which take measurements and transmit data at time intervals, the duration of which is considerably less than the activation period of sensors. The specific feature of the power supply system is the combined use of devices based on various physical phenomena. Electrical energy is generated by thermoelectrochemical cells. The temperature gradient on the sides of these cells is created by a vortex tube. A special boost DC/DC converter provides an increase in the output voltage of thermoelectrochemical cells up to the voltage that is necessary to power electronic devices. A supercapacitor is used to store energy in the time intervals between sensor activation. A study of an experimental sample of the power supply system for wireless sensors was conducted. Using the model in MATLAB + Simulink program, the possibility and conditions for creating the considered system for a particular type of wireless sensor were shown.