Open AccessImproved Fast Adaptive IDW Interpolation Algorithm based on the Borehole Data Sample Characteristic and Its Application
Author(s) -
Liming Sun,
Yingqi Wei,
Hong Cai,
Jun Yan,
Jun Xiao
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1284/1/012074
Subject(s) - interpolation (computer graphics) , borehole , raster graphics , algorithm , sampling (signal processing) , grid , multivariate interpolation , inverse distance weighting , computer science , trilinear interpolation , adaptive sampling , position (finance) , point (geometry) , mathematics , geology , bilinear interpolation , geometry , artificial intelligence , computer vision , statistics , monte carlo method , motion (physics) , geotechnical engineering , filter (signal processing) , finance , economics
The inverse distance weighted algorithm (IDW) is one of the most widely used algorithms in geoscience calculation based on its university and simple theory. However, in the practical application based on borehole sampling data, the distance between boreholes is further than the sampling distance along the bedding direction of one borehole, and it needs to search all the near points through a large number of distance calculation, and the process is very slow, so this lacks practicality in the spatial interpolation of the large amount and non-uniform distribution data. Based on the special features of the borehole sampling data, this paper presents a fast adaptive and improved inverse distance weighted interpolation method. And firstly the sample point position could be indexed by the adaptive cube grid raster, then determine the index grid in the horizontal and vertical directions of the interpolation point, and combine these grids for the finally IDW calculation, which significantly improves the search speed of the adjacent interpolation calculation points. It can improve the engineering applicability of the IDW method, especially the three-dimensional spatial interpolation and computing has a good application prospect.