ThermalQualityAnalysisThermalResourceInterpolat...
This is one of sixteen associated .zip files relating to thermal resource interpolation results within the Thermal Quality Analysis task of the Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. This file contains the binary grid (raster) for the error associated with the predicted temperature at 2.5km.
The sixteen files contain the results of the thermal resource interpolation as binary grid (raster) files, images (.png) of the rasters, and toolbox of ArcGIS Models used. Note that raster files ending in "pred" are the predicted mean for that resource, and files ending in "err" are the standard error of the predicted mean for that resource. Leave one out cross validation results are provided for each thermal resource.
Several models were built in order to process the well database with outliers removed. ArcGIS toolbox ThermalRiskFactorModels contains the ArcGIS processing tools used. First, the WellClipsToWormSections model was used to clip the wells to the worm sections (interpolation regions). Then, the 1 square km gridded regions (see series of 14 Worm Based Interpolation Boundaries .zip files) along with the wells in those regions were loaded into R using the rgdal package. Then, a stratified kriging algorithm implemented in the R gstat package was used to create rasters of the predicted mean and the standard error of the predicted mean. The code used to make these rasters is called StratifiedKrigingInterpolation.R Details about the interpolation, and exploratory data analysis on the well data is provided in 9_GPFA-AB_InterpolationThermalFieldEstimation.pdf (Smith, 2015), contained within the final report.
The output rasters from R are brought into ArcGIS for further spatial processing. First, the BufferedRasterToClippedRaster tool is used to clip the interpolations back to the Worm Sections. Then, the Mosaic tool in ArcGIS is used to merge all predicted mean rasters into a single raster, and all error rasters into a single raster for each thermal resource.
A leave one out cross validation was performed on each of the thermal resources. The code used to implement the cross validation is provided in the R script LeaveOneOutCrossValidation.R. The results of the cross validation are given for each thermal resource.
Other tools provided in this toolbox are useful for creating cross sections of the thermal resource. ExtractThermalPropertiesToCrossSection model extracts the predicted mean and the standard error of predicted mean to the attribute table of a line of cross section. The AddExtraInfoToCrossSection model is then used to add any other desired information, such as state and county boundaries, to the cross section attribute table. These two functions can be combined as a single function, as provided by the CrossSectionExtraction model.
About this Resource
| Last updated | unknown |
|---|---|
| Created | unknown |
| Name | ThermalQualityAnalysisThermalResourceInterpolationResultsDataTempAt2500mErr.zip |
| Format | Zip File |
| License | Creative Commons Attribution |
| Created | 1 year ago |
| Media type | application/zip |
| has views | False |
| id | 70678185-b591-4c83-a7e2-e43b652289f3 |
| metadata modified | 1 year ago |
| package id | a061cc34-8149-4ce2-955a-8a611a160edd |
| position | 37 |
| state | active |
| tracking summary | {'total': 0, 'recent': 0} |