Assessing the impact of program selection on the accuracy of 3D geologic models

被引:4
|
作者
MacCormack, Kelsey E. [1 ]
Eyles, Carolyn H. [2 ]
机构
[1] Univ Guelph, Sch Environm Sci, Guelph, ON N1G 2W1, Canada
[2] McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON L8S 4K1, Canada
来源
GEOSPHERE | 2012年 / 8卷 / 02期
基金
加拿大自然科学与工程研究理事会;
关键词
SPATIAL INTERPOLATION; NORMALS; MAPS;
D O I
10.1130/GES00732.1
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
As the field of three-dimensional (3D) subsurface geological modeling develops at an increasingly rapid rate, so too does the number of available software programs catering to these applications, most of which offer very similar ensembles of algorithms for interpolating data. A few studies have analyzed the effect of algorithm selection on the accuracy and uncertainty of subsurface geologic models, but little consideration has been given to the uncertainty and variability introduced into the model by software program selection. In this study, inverse distance weighting (IDW) and ordinary kriging (OK) algorithms are used to interpolate identical data sets by three different software programs (ArcGIS, ROCKWORKS 2006, and VIEWLOG). The results indicate that the output of the IDW and OK interpolation algorithms are inconsistent between programs and that this variability should be considered when assessing the uncertainty associated with subsurface model results. Program selection appears to have a significant influence on model output results when modeling complex subsurface geological environments, particularly when interpolating clustered data, which are most commonly used in geological and environmental applications.
引用
收藏
页码:534 / 543
页数:10
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