摘要
三维地震属性数据巨大,在实际应用中一般采用局域克里金插值算法进行插值。目前常用的指定距离半径、指定点数、kd-tree等搜索算法均涉及距离计算、遍历已知点,相对较为费时。对此,提出一种无须距离计算、无须遍历已知点而直接利用待插值点位置的增减实现邻域点的选取方法(VAOS),以高效实现克里金插值。经过实验验证,在同精度下,该算法比距离半径搜索法快数十倍。
The 3 D seismic attribute data is huge.In practical applications,local Kriging interpolation algorithm is generally used to interpolate.At present,the commonly used search algorithms such as designated distance radius,designated points and Kd-tree involve distance calculation and traversal of known points,which is relatively time-consuming.This paper proposes a method of selecting neighborhood points(VAOS),which does not need distance calculation and traversal of known points,but directly uses the increase or decrease of the position of the points to be interpolated to achieve efficient Kriging interpolation.Through the actual data verification,our algorithm is dozens of times faster than the distance radius search method under the same precision.
作者
王美琪
李建
Wang Meiqi;Li Jian(School of Computer Science,Southwest Petroleum University,Chengdu 610500,Sichuan,China)
出处
《计算机应用与软件》
北大核心
2021年第1期246-249,共4页
Computer Applications and Software
基金
国家科技重大专项项目(2016ZX05020-006)。
关键词
三维地震属性
平面图克里金算法
距离半径搜索算法
待插值点位置的增减算法
3D seismic attribute
Kriging algorithm for planar map
Search algorithm for distance radius
Increment and subtraction algorithm for position of interpolated points
