Design And Completion Of Logging Fast Comprehensive Evaluation System

Along with the development of the methods of Logging,it is urgent to develop a Logging Software which interface is simple,the operation of this software is convenient and the speed of working is very fast.By integrating a large number of log interpretation methods,mathematical and statistical methods,computer programming,computational methods,and ultimately completed the Logging Fast Comprehensive Evaluation System.The system use C++ code to achieve rapid calculation of each function.The database server and client can be configured flexibly,based on the architecture of C/S.It can draw two-dimensional or three-dimensional graphics by using the TeeChart whick is a mature control.Design and complete the functions of chart-table linked and chart-parameter linked.Design and achieve the different data tables to store the complex logging data in database.By using the GDI,the logging curves can be drawed intuitively.After the software system requirements analysis,preliminary design,detailed design then finalize the system implementation.Software system integrates a large number of log interpretation,such as the standardization methods of histogram standardization,standardization of trend surface analysis,standardization of ckeleton value,standardization of construction depth trend,overlays standardization.It also includes the modeling of reseroir parameters such as the methods of fitting formula,classic formula,empirical formula.It also includes the methods of fluid identification such as all kinds of plate correction,method of pixler,methods of water analysis,methods of curves overlap.The formation of a tile-based linked analysis parameters platform to select the function parameters and data visualization capabilities organically combine to form a linked charts,graphs-parameters linked technical processing characteristics,the user operates under an intuitive environment,ensure the accuracy of log interpretation work.Among the entire field of pattern recognition,cluster analysis has been a hot research.By analysis of some clustering algorithm running time longer,the time cost is a high shortcoming.This paper choose K-means,Support Vector Clusering algorithms for parallel implementation apart.Execution speed can be significantly accelerated.K-means parallel algorithms using OpenMP-C++ AMP mixed acceleration architecture form,using full play to the CPU and GPU computing resources.Support Vector Clustering parallel algorithms using CUDA C architecture,using CUDA highly parallel SIMD instructions operating mode,effectively accelerate algorithm execution efficiency.