Quantitative description of characteristics of high-capacity channels in unconsolidated sandstone reservoirs using in situ production data

Quantitative description of the high-capacity channels in unconsolidated sandstone reservoirs, into which water was injected to improve oil recovery, is a hot topic in the field of reservoir development. This paper presents a novel approach to describing quantitatively the characteristics of connected macropores in unconsolidated sandstone reservoirs using in situ production data. Based on physical simulation for formation mechanisms of high capacity channels and interwell tracer test data, a mathematical model was established to describe high-capacity channels by grey correlation theory, flow mechanism of fluid in porous media and reservoir engineering, and a program was developed to describe quantitatively the channel characteristics. The predicted results were consistent with field monitoring data （80%）, so this model could be economically and effectively used to identify high-capacity channels.

Quantitative analysis of microstructure based on machine learning and its application in product research and development

The material's microstructure is the output of the material composition and production process;simultaneously, it is the key factor in the material's performance and plays an important role in the material development cycle.The digital features of microstructures that can be recognized by a computer are obtained through the quantitative description of the material's microstructure, and a mathematical model is used to associate them with the composition, process, and properties.Combining the evolution mechanism of microstructure features can help quickly to predict microstructure properties, which can be used to optimize the composition and process, accelerate product development iteration, and solve the long cycle problem of traditional research and development mode while lowering the high cost of high-frequency trial production.This paper introduces the development and application of the combination of image knowledge, computer knowledge, and expert experience in the quantification of microstructures and the practical cases of recent studies of the Mask-Regions with Convolutional Neural Network Features(RCNN) method combined with machine learning in the digital research and development of heavy plates in Baosteel, and prospects the potential application of the quantification of microstructures of materials.

Effect of different drying methods on the taste and volatile compounds,sensory characteristics of Takifugu obscurus

Pufferfish is prone to deterioration due to abundant nutrients and high moisture content.Drying technology can extend the shelf life and enhance the flavor quality of aquatic products.The study investigated the effect of hot air drying(HAD),microwave vacuum drying(MVD)and hot air assisted radio frequency drying(HARFD)on the taste and volatile profiles of Takifugu obscurus.Different drying methods had significant influence on the color,rehydration,5’-nucleotides,free amino acids and volatile components(P<0.05).The results showed that HAD and HARFD could promote the flavor of T.obscurus by producing higher equivalent umami concentration(EUC)values,which were about two times of MVD group,and more pronounced pleasant odor according to sensory analysis.HAD is more appropriate for industrial application than HARFD and MVD considering the economic benefits.This study could provide a reference for the industrial application of drying T.obscurus.

Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable

The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.

Numerical analysis of electromagnetic force field through the use of two examples

In modern processing of conducting materials, such as steel,the time-varying electromagnetic field plays a key role in obtaining the desired microstructure or eliminating solidification defects such as porosity and segregation in cast billets. Up to now,few studies on the induced electromagnetic force （also called the Lorentz force） field in liquid metal have been reported. Compared with the magnetic field, the induced force field is the real and only direct cause for flow control. The electromagnetic force is comprised of two components. One is time-independent and the other is time- dependent. The time-dependent component varies with time in both amplitude and direction. When it reaches the extreme value,it can be one dozen times larger than the time-independent component. In this paper, a new method to quantitatively describe the induced electromagnetic force in liquid metal under a harmonic electromagnetic field,including both its time- independent and dependent components, was proposed based on the formula derivation from the data of amplitude and phase angle. Through this method ,the features of the time-dependent component were discussed, including the directions of rotation and the long axis. As a result, the force pattern was described. With two example calculations, the method was explained in detail. The results of both examples show that the force field in liquid metal can be divided into several regions with different force features. Example 1 shows the effect of coil position on the evolution of the force field pattern in liquid metal. Example 2 is a kind of stirring by the travelling magnetic field ,whose results present the sub-structures in metal and show that most of them have almost the same rotating direction.

Numerical Analysis on Lorentz Force Field in φ160 Billet Under Harmonic Magnetic Field

A method was developed to quantitatively describe the time-varying Lorentz force field induced in billet under harmonic magnetic field.Based on the numerical analysis of the Lorentz force,the numeral features were concluded, which comprised of the mean force,the maximum force,the long axis,short axis and rotation direction of ellipse,the phase difference index,and so on.Using this method,the Lorentz force field in φ160 billet under 3 Hz harmonic magnetic field were analyzed.