The Research Of Depth Correction Of Completion Based On Hausdorff Distance

The study of depth correction of completion is the research hot topics of completion practices. The success and recovery rate of oil drilling is influenced directly by the accuracy of the value of depth correction. The difficult problem of the research of depth correction is the description of logging curve shape, and the calculation of depth correction.This paper focused on the research about the difficult problem of curve shape description and calculating, the comparison and calculation of curve shape by means of improved mathematical algorithms, the description of the shape of characteristics curve segment by statistics. Meanwhile, in order to receive efficient achievements, the method is used in the research of depth correction, developed the visual software and analyzed its practical application effect.This paper mainly studies the content as follows:Ⅰ. Based on the advantages and disadvantages of modified forms of any hausdorff distance, the paper puts forward a method to improve the efficiency of hausdorff distance. The idea focus narrowed calculation scope every times; Improved the calculation method of the unidirectional hausdorff distance by approximate thoughts; Shorten the search time through the search path. The original algorithm and the improved algorithm are used in the comparasion of operation efficiency, it is validated the feasibility of improvement.Ⅱ. Aiming at amplitude of peak curve segment, the paper analyzed the role and effect about the shape description by the skewness and the kurtosis, and puts forward a kind of parameter, which described the characteristics of the amplitude of peak curve segment, it is skewness -kurtosis. Through experiment, the parameters combined with skewness and kurtosis characteristics, used to choose towering and the peak curve segment of data amplitude value distribution.Ⅲ. Combined with these research, which is applied in depth correction, and offered the visualizations application software. Compared the calculated data and real data to verify its feasibility, efficiency and practical of the application.