Tight sandstone reservoirs have small pore throat sizes and complex pore structures. Taking the Chang 6 tight sandstone reservoir in the Huaqing area of the Ordos Basin as an example, based on casting thin sections, nuclear magnetic resonance experiments, and modal analysis of pore size distribution characteristics, the Chang 6 tight sandstone reservoir in the study area can be divided into two types: wide bimodal mode reservoirs and asymmetric bimodal mode reservoirs. Based on the information entropy theory, the concept of “the entropy of microscale pore throats” is proposed to characterize the microscale pore throat differentiation of different reservoirs, and its influence on the distribution of movable fluid is discussed. There were significant differences in the entropy of the pore throat radius at different scales, which were mainly shown as follows: the entropy of the pore throat radius of 0.01~0.1 μm, >0.1 μm, and <0.01 μm decreased successively; that is, the complexity of the pore throat structure decreased successively. The correlation between the number of movable fluid occurrences on different scales of pore throats and the entropy of microscale pore throats in different reservoirs is also different, which is mainly shown as follows: in the intervals of >0.1 μm and 0.01~0.1 μm, the positive correlation between the occurrence quantity of movable fluid in the wide bimodal mode reservoir is better than that in the asymmetric bimodal mode reservoir. However, there was a negative correlation between the entropy of the pore throat radius and the number of fluid occurrences in the two types of reservoirs in the pore throat radius of <0.01 μm. Therefore, pore throats of >0.1 μm and 0.01~0.1 μm play a controlling role in studying the complexity of the microscopic pore throat structure and the distribution of movable fluid in the Chang 6 tight sandstone reservoir. The above results deepen the understanding of the pore throat structure of tight sandstone reservoirs and present guiding significance for classification evaluation, quantitative characterization, and efficient development of tight sandstone reservoirs.
Abstract:The power graph of a finite group is the graph whose vertex set is the group, two distinct elements being adjacent if one is a power of the other. The enhanced power graph of a finite group is the graph whose vertex set consists of all elements of the group, in which two vertices are adjacent if they generate a cyclic subgroup. In this paper, we give a complete description of finite groups with enhanced power graphs admitting a perfect code. In addition, we describe all groups in the following two classes of finite groups: the class of groups with power graphs admitting a total perfect code, and the class of groups with enhanced power graphs admitting a total perfect code. Furthermore, we characterize several families of finite groups with power graphs admitting a perfect code, and several other families of finite groups with power graphs which do not admit perfect codes.
As gasoline is the main fuel of small vehicles, the exhaust emissions from its combustion will affect air quality. The focus of gasoline cleaning is to reduce the sulfur and olefin content in gasoline while maintaining its RON as much as possible. The reduction of RON will bring great economic losses to enterprises. Therefore, it is very important for petrochemical enterprises to construct a RON loss model in the gasoline refining process. The model construction, which reduces RON loss during gasoline refining, is the main question in this paper. By Python and SPSS software, we got two variable filtering methods: the random forest importance filtering and PCA filtering, and combined with SVR and random forest models, RON of the product and sulfur content were predicted. The filtering order of the original data by Excel and Python is maximum and minimum removal, 3σ criterion removal, deletion of too many sites in incomplete data, and filling of empty values in the mean within two hours. Several RON prediction models were established with the help of Python software, and the variables selected were compared by two filtering methods: one is the SVR model based on Gaussian, linear, polynomial, and Sigmoid kernel functions; the other is the random forest model. The sulfur content and RON prediction model was constructed, which use evaluation functions such as MSE, R 2 , and RMSE to evaluate and sulfur content as the subject condition. We convert the problem into linear and nonlinear model variable optimization problems: the linear model is the variable selected by the SVR linear kernel function model and random forest; the nonlinear model is the combination of variables selected by the random forest model and random forest. Optimizing for each sample, the optimization method is to find the optimal solution for each variable and use the optimal method for each variable as the local optimal solution for the sample. The two models are evaluated from the perspectives of optimization degree, optimization rate, model running speed, etc.
The accumulation of multiple source components leads to the superposition of multiple pore throat systems and similar pore throat distribution may correspond to different seepage capacity in the mixed rock reservoir. Taking the mixed rock reservoir of III+IV oil formation in Nanyishan Oilfield, Chaidamu Basin, as an example, the development characteristics of pore throat system and its controlling factors in the mixed rock were summarized by means of thin slice, scanning electron microscopy, X-ray diffraction and high pressure mercury injection, and the reservoir physical property differences and their genetic controlling mechanism were analyzed. The results show that the reservoir space of the mixed reservoir mainly consists of intergranular pore fracture, micropore fracture, and micropore-dissolution pore. The diverse and complex pore types make the reservoir space combination type, capillary pressure curve shape and reservoir physical properties are not completely corresponding. The higher the content of brittle minerals, the higher the reservoir permeability. However, the development of iron dolomite mainly destroys the reservoir. The permeability of reservoir is mainly controlled by the development degree of macropores and the pore size which is the main contribution to permeability, and the proportion of macropores increases with the increase of permeability.
In this paper, the PEk method of solving special linear algebraic systems-block quasi-tridiagonal systems is presented. On the condition that the coefficient matrix is Hermitian positive definite, the solvability and convergence of the new method are proved, and the selection range for the parameters k is also given.
Abstract. In order to realize the data access service of Android platform for OPC,Analysis of the OPC of Android, developed a data access service system for PLC based on Android platform, described the system architecture, work flow and communication protocol, Implemented two kinds of state data access of the short connection and the long connection for PLC controller. The system has the advantages of high efficiency, convenient and practical, that engineers can receive data and control system through the android mobile devices whenever and wherever, and make use of existing resources for industrial on-site service.
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