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Computational Geometry as An Aid to Data Analysis of Drilling Data

机译:计算几何有助于钻探数据的数据分析

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As the amount of real time data collected during drilling continues to rise, sophisticated methods for analyzing and displaying data are needed to make sense out of large volumes of data. This paper describes a novel use of the concepts of computational geometry to analyze and display data from a downhole drilling data tool. The use of a mathematical transformation called a convex hull allows one to create a boundary around a set (cloud) of data points. This is most easily visualized in two dimensions as putting a rubber band around the set of points. Imagine that the rubber band is such that it will be tightly stretched when it is around all the points, so that certain points in the data cloud dictate the resulting outline. A convex hull software routine, the best known of which is the“qhull” program from the University of Minnesota, fits line segments around a cloud of points in up to nine dimensions. Utilizing the convex hull output one can calculate the volume in 3-D or area in 2-D described by data clouds. The result is used as an indicator of bit and drill string behavior.
机译:随着钻井期间收集的实时数据的量继续上升,需要进行分析和显示数据的复杂方法来识别出大量数据。本文介绍了计算几何概念的新颖使用,以从井下钻探数据工具分析和显示数据。使用称为凸船的数学变换允许人们在数据点的集合(云)周围创建边界。这最容易以两个维度可视化,因为将橡皮筋放在一组点周围。想象一下,橡皮带使得当它在所有点周围时,它将紧密拉伸,因此数据云中的某些点决定了所得轮廓。凸船软件例程,最着名的是明尼苏达大学的“QHULL”程序,围绕着云点围绕九个尺寸的线段。利用凸壳输出,可以计算数据云描述的3-D中的体积或在2-D中的卷。结果用作位和钻串行为的指示器。

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