Research and Application of Rod Pump Working Condition Diagnosis and Virtual Production Metering Based on Electric Parameters

The conventional configurations of pumping well IOT consist of electric parameter indicator and dynamometer. The current, voltage, power, and other electrical parameters are easy to access, low costs, stable, and acquired daily during pumping well operation. If the working condition diagnosis and virtual production metering of pumping well can be realized through electrical parameters, the utilization of dynamometers can be cancelled or reduced, which is of great significance to reduce the investment and improve the coverage of IOT in oil wells. The conventional methods of diagnosis and analysis based on electrical parameters and virtual production metering are lack of theoretical basis. The combination of deep learning technology of big data and traditional methods will provide solutions to solve related technical problems. Considering that there are many energy transmission segments from the motor to the downhole pump, the characteristics of the electric parameter curve are more sophisticated and difficult to identify compared with dynamometer card due to the influence of the unbalance, pump fullness, rod/tube vibration, wax deposition and leakage. The shape characteristics of the electric parameter curve of the pumping well are analyzed in the time domain and frequency domain, which provides the basis for further diagnosis, analysis and production measurement. In this paper, an integrated multi-model diagnosis method is proposed. For the working conditions with a large scale of samples, the electrical parameters are converted to dynamometer cards for diagnosis by using the deep learning technology of big data. For the working conditions with sparse samples, the machine learning model is used to diagnosis directly with electrical parameters. The deep learning electric parameter model for production measurement is established. Through the combination of the big data model of electric parameters to dynamometer card, 3D mechanical model of rod string, and big data model of plunger leakage coefficient, the virtual production metering function of pumping well based on electrical parameters is successfully realized. The diagnosis and virtual production metering method and software based on electrical parameters have been applied in many oilfields of CNPC. The accuracy of identifying the upper and lower dead points of electric parameters is 98.0%; the coincidence rate of working condition diagnosis under electrical parameters is 92.0%; the average error of virtual production metering with electric parameters is 13.4%. The dynamometer and gauging room have been canceled in the demonstration area. The application of electrical parameters to diagnose working conditions and meter the production of pumping wells is the key to the low-cost IOT construction. Traditional mathematical and physical methods are difficult to solve this problem, but the application of big data analysis technology could do the job successfully.

In-Place Characterization of On-State Voltage for SiC MOSFETs: Controlled Shoot-Through vs. Film Heater

The on-state voltage of MOSFETs is a convenient and powerful temperature-sensitive electric parameter (TSEP) to determine the junction temperature, thus enabling device monitoring, protection, diagnostics and prognostics. The main hurdle in the use of the on-state voltage as a TSEP is the per-device characterization procedure, to be carried out in a controlled environment, with high costs. In this paper, we compare two novel techniques for MOSFET junction temperature estimation: controlled shoot-through and direct heating by resistive heaters embedded in two Kapton (polyimide) films. Both allow in-place characterization of the TSEP curve with the device mounted in its final circuit and assembly, including the working heat sink. The two methods are also validated against the conventional procedure in a thermal chamber.

In-place Characterization of On-state Voltage for SiC MOSFETs: Controlled Shoot-through vs. Film Heater

The on-state voltage of MOSFETs is a convenient and powerful temperature-sensitive electric parameter (TSEP) to determine the junction temperature, thus enabling device monitoring, protection, diagnostics and prognostics. The main hurdle in the use of the on-state voltage as a TSEP is the per-device characterization procedure, to be carried out in a controlled environment, with high costs. In this paper we compare two novel techniques for MOSFET junction temperature estimation: controlled shoot-through and direct heating by resistive heaters embedded in two Kapton (polyimide) films. Both allow in-place characterization of the TSEP curve with the device mounted in its final circuit and assembly, including the working heat sink. The two methods are also validated against the conventional procedure in a thermal chamber.

Silver Sintering for Silicon Carbide Die Attach: Process Optimization and Structural Modeling

The increasing demand in automotive markets is leading the semiconductor industries to develop high-performance and highly reliable power devices. Silicon carbide MOSFET chips are replacing silicon-based solutions through their improved electric and thermal capabilities. In order to support the development of these novel semiconductors, packaging technologies are evolving to provide enough reliable products. Silver sintering is one of the most promising technologies for die attach. Due to their superior reliability properties with respect to conventional soft solder compounds, dedicated reliability flow and physical analyses should be designed and employed for sintering process optimization and durability assessment. This paper proposes an experimental methodology to optimize the pressure value applied during the silver sintering manufacturing of a silicon carbide power MOSFET molded package. The evaluation of the best pressure value is based on scanning electron microscopy performed after a liquid-to-liquid thermal shock reliability test. Furthermore, the sintering layer degradation is monitored during durability stress by scanning the acoustic microscopy and electric measurement of a temperature sensitive electric parameter. Moreover, mechanical elastoplastic behavior is characterized by uniaxial tensile test for a bulk sample and finite element analysis is developed to predict the mechanical behavior as a function of void fraction inside sintering layer.

Electromagnetic and non-Darcian effects on a micropolar non-Newtonian fluid boundary-layer flow with heat and mass transfer

The purpose of this paper is to investogate the ectromagnetic and micropolar properties on biviscosity fluid flow with heat and mass transfer through a non-Darcy porous medium. Morever, The heat source, viscous dissipation, thermal diffusion and chemical reaction are taken into consideration. The system of non linear equations which govern the motion is transformed into ordinary differential equations by using a suitable similarity transformations. These equations are solved by making use of Rung–Kutta–Merson method in a shooting and matching technique. The numerical solutions of the velocity, microtation velocity, temperature and concentration are obtained as a functions of the physical parameters of the problem. Moreover the effects of these parameters on these solutions are discussed numerically and depicted graphically. It is found that the microtation velocity increases or deceases as the electric parameter, Hartman parameter and the microrotation parameter increase. Morever, the temperature increases as Forschheimer number, Eckert number increase.

Exploration Disaster Source of Mine Water by Electromagnetic Radiation

geological hazard in deep underground mining. Before the rock mass explosion, electromagnetic energy will radiate outward during the deformation and rupture of the coal rocks. Hence, it is possible to use the electromagnetic radiation to predict geological disasters in coal mines. A challenging task using the active source electromagnetic survey technique is to detect geological anomalies, such as disaster water sources and geological structures. To this end, this paper proposes a new electromagnetic radiation solution based on the forward and inversion theory to detect geological anomalies in the coal seam. Based on typical coal mine geological models, the forward modelling and inversion modelling have been performed, respectively. The forward modelling explained the geological anomalies inside the coal seam, which were very sensitive to the response of the radiated electromagnetic field; especially, for the water-bearing geological anomalies. The inversion modelling discovered that the inversion geo-electric parameter distribution agreed well with the actual model. As a result, the proposed method is feasible for geological anomalies detection.

On the Numerical Analysis of Unsteady MHD Boundary Layer Flow of Williamson Fluid Over a Stretching Sheet and Heat and Mass Transfers

A thorough and detailed investigation of an unsteady free convection boundary layer flow of an incompressible electrically conducting Williamson fluid over a stretching sheet saturated with a porous medium has been numerically carried out. The partial governing equations are transferred into a system of non-linear dimensionless ordinary differential equations by employing suitable similarity transformations. The resultant equations are then numerically solved using the spectral quasi-linearization method. Numerical solutions are obtained in terms of the velocity, temperature and concentration profiles, as well as the skin friction, heat and mass transfers. These numerical results are presented graphically and in tabular forms. From the results, it is found out that the Weissenberg number, local electric parameter, the unsteadiness parameter, the magnetic, porosity and the buoyancy parameters have significant effects on the flow properties.