GIS-based Geostatistics and Multi-Criteria Evaluation of Steel Casing Failure

DOI

10.2991/ic3me-15.2015.290How to use a DOI?

Keywords

Spatial dependency, Geostatistics, kriging interpolating, Predictive model, GIS

Abstract

Geostatistics is a very important tool of surface analysis in GIS application. Firstly, spatial dependency that represents the similar extent of neighboring points is used to analyze spatial data values and their locations. Spatial variability is calculated to assess spatial data in terms of distance and direction. Then, calculating results is used to create new surface images of spatial data values with kriging interpolating. As an example application, four sample data sets of oil wells, such as injection pressure, times of injection, injection temperature, and total injection, are analyzed. Predictive model of steel casing failure is constructed with four surface images that represent influence factors. Finally, the predictive distribution of steel casing failure is worked out, and some advice is proposed.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Chen
AU  - Yiliang Liu
AU  - Qingjie Zhu
PY  - 2015/08
DA  - 2015/08
TI  - GIS-based Geostatistics and Multi-Criteria Evaluation of Steel Casing Failure
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 1506
EP  - 1511
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.290
DO  - 10.2991/ic3me-15.2015.290
ID  - Chen2015/08
ER  -