Appalachian Basin Play Fairway Analysis: Thermal Quality Analysis in Low-Temperature Geothermal Play Fairway Analysis (GPFA-AB) RScriptsForSortingDataAndRemovingOutliers.zip

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS).

This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain item description documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations.

Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015.

Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted.

UPDATE: Newer version of the Thermal Quality Analysis has been added here: https://gdr.openei.org/submissions/879 (Also linked below) Newer version of the Combined Risk Factor Analysis has been added here: https://gdr.openei.org/submissions/880 (Also linked below) This is one of seven .zip files associated files relating to thermal outlier assessment within the Thermal Quality Analysis task of the Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. This file contains the R script mentioned below in the summary of the seven associated files.

The seven files contain the well data sorted for outliers, and the R scripts used to process the data. Before running the outlier identification, wells in AASG_Thermed.xlsx (may be found within ThermalQualityAnalysisThermalModelDataFilesStateWellTemperatureDatabases.zip) were checked for the same spatial location. Only the deepest well in a given location is used for quality purposes. The R script SortingWells.R contains two functions that were developed to sort the data according to these specifications. Further details about the data processing are provided in 9_GPFA-AB_InterpolationThermalFieldEstimation.pdf (Smith, 2015), provided within the project final report submitted on 10/16/2015. Outlier identification is done using the local identification function in Whealton and Smith (2015) with a 32 km searching radius for points. The nearest 25 points are used to check for outliers. Details about the algorithm are provided in 6_GPFA-AB_ThermalOutlierAssessment.pdf (Whealton and Stedinger, 2015), again within the final report.

For ease in setting up the data for outlier identification, a function was written in R script DataArrangementAndRunOutlierAnalysis.R. This function sets up the data and runs the outlier identification function.

Data and Resources

Metadata Source

Additional Info

Field Value
Citation Date 2015-09-30T00:00:00-06:00

Harvest Information

Original ID f0000019-58cc-4372-a567-000000000638
Index Date 2020-01-13T10:59:50-07:00
Original Format ISO-USGIN
Original Version 1.2

Author

Name Teresa E. Jordan
Position primary contact
Organization Cornell University
Email tej1@cornell.edu

Geographic Extent

North Bound 43.5
South Bound 37
East Bound -74.5
West Bound -82.5