GIS-based Geostatistics and Multi-Criteria Evaluation of Steel Casing Failure
Jing Chen, Yiliang Liu, Qingjie Zhu
Available Online August 2015.
- https://doi.org/10.2991/ic3me-15.2015.290How to use a DOI?
- Spatial dependency, Geostatistics, kriging interpolating, Predictive model, GIS
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ic3me-15.2015.290 DO - https://doi.org/10.2991/ic3me-15.2015.290 ID - Chen2015/08 ER -