Research Report of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

                                            [
  "019:20"
]
                                        

                                            {
  "fn": "Teresa E. Jordan",
  "@type": "vcard:Contact",
  "hasEmail": "mailto:tej1@cornell.edu"
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                                            true
                                        

                                            [
  {
    "@type": "dcat:Distribution",
    "title": "Catalog of Supporting Files and Memos.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/00GPFA-AB_CatalogOfSupportingFilesAndMemos.pdf",
    "mediaType": "application/pdf",
    "description": "READ ME.  This file lists the Catalog of Supporting Files supplementing the final report document.   In addition to a copy of the original State of Project Objectives (SOPO), the list provides a brief description and specific file names for the 18 files included within this same submission: 
1.Methodologies for GPFA-AB
2.BHT Corrections in GPFA-AB
3.Anadarko Basin Thermal Conductivities in GPFA-AB
4.Assignment of Conductivity Stratigraphy for Individual Wells using COSUNA Methodology in GPFA-AB
5.Tests of Simplified Conductivity Stratigraphy by Monte Carlo Analysis in GPFA-AB
6.Thermal Outlier Assessment in GPFA-AB
7.Thermal Resource Thresholds in GPFA-AB
8.Thermal Model Methods and Well Database Organization in GPFA-AB
9.Exploratory Data Analysis and Interpolation Methodology for Thermal Field Estimation
10. Selection of Four Counties in Each State with the Best Thermal Resources
11. Natural Reservoirs Methodology in GPFA-AB
12. Natural Reservoirs Database Inputs in GPFA-AB
13. Identifying Potentially Activatable Faults in GPFA-AB
14. Seismic Risk Map Creation Methods in GPFA-AB
15. Utilization Analysis in GPFA-AB
16. Risk Analysis in GPFA-AB
17. Combining Risk Factors in GPFA-AB
18. Permits for Geothermal District Heating Project in GPFA-AB"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Tasks and Milestones.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/0_GPFA-AB_SOPOTasksMilestones.pdf",
    "mediaType": "application/pdf",
    "description": "The project tasks and milestones as described in the original Statement of Project Objectives"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Select Best Thermal Resources Counties.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/10_GPFA-AB_SelectBestThermalResourcesCounties.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Selection of Four Counties in Each State with the Best Thermal Resources
This memo describes the methods used to select the four "best" counties in each state according to the thermal resource. This analysis complements the Play Fairway maps that are based on the combination of the other three risk factors with the thermal resource, but this analysis is specific to thermal attributes."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Natural Reservoirs Methodology.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/11_GPFA-AB_NaturalReservoirsMethodology.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Natural Reservoirs Methodology in GPFA-AB
Task 2 for this project involves the mapping and characterization of natural reservoirs within the Appalachian Basin region of New York (NY), Pennsylvania (PA), and West Virginia (WV). The intention of this memo is to present the methods that have been used for the completion of this task's milestones. The reservoir data collection and compilation methods used for NY are different than those used for PA and WV, as will be described within. Reservoir analysis and uncertainty quantification methods are consistent across the tri-state region."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Natural Reservoirs Database Inputs.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/12_GPFA-AB_NaturalReservoirsDatabaseInputs.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Natural Reservoirs Database Inputs in GPFA-AB
This document is intended to augment the "Natural Reservoirs Methodology" document, by providing more details on the original and modified database inputs for New York, Pennsylvania and West Virginia. Additionally, all research and literature that affected decisions for the reservoir data input are recorded here. This especially includes data for geologic formations in the Appalachian Basin. This memo will accompany the Tier 2 Data submission for the Natural Reservoirs Quality Analysis task. The Tier 2 Thermal Analysis data upload will contain several attached files with this memo."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Identifying Potentially Activatable Faults.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/13_GPFA-AB_IdentifyingPotentiallyActivatableFaults.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Identifying Potentially Activatable Faults in GPFA-AB
These analyses attempt to highlight the risk of induced seismicity related to a geothermal project. Absent a regionally complete map of deep faults, gravity and magnetic data are analyzed to extract a multi-scale-edge Poisson wavelet representation of the locations of rocks of laterally contrasting physical properties. Among these lateral rock property boundaries are a subset that are candidates for future fault slip, if fluid pressures change and if a plane of weakness is properly oriented in space. To narrow the focus of this analysis onto rock property boundaries of greater concern (e.g., faults with demonstrated propensity to slip), a second step was to identify the co-occurrence of rock-property-boundaries at depths of 3-4 km and seismic activity registered in earthquake catalogs or by EarthScope. One approach to exploring the likelihood that some of the faults in the region might be reactivated if subsurface pressures change is an analysis of tendency to slip, which is based on determination of the spatial orientation of a structure (plane of weakness) relative to the direction of the regional principal compressive stress. This method will produce interesting results that foster further investigation although at this stage the results will be of low reliability as indicators of the risk of induced seismicity. Collection of pertinent data during Phase 2 is vital to create more reliable risk results."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Seismic Risk Map Creation Methods.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/14_GPFA-AB_SeismicRiskMapCreationMethods.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Seismic Risk Map Creation Methods in GPFA-AB
This memo describes the methods used to process the seismic data gathered and generated for this project into a Risk of Seismicity. Detailed methodology used to convert the seismic risk data (i.e. distance to nearest earthquake, and angle to critical stress) into a two independent seismic risk maps is presented. This memo will accompany the Tier 2 Data submission."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Utilization Analysis SCLOH.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/15_GPFA-AB_UtililzationAnalysisSCLOH.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Utilization Analysis in GPFA-AB
Task four of Phase 1 of the project assesses the utilization demand for geothermal heat. This was done in two parallel efforts: 1) calculation of the Surface Levelized Cost of Heat (SLCOH) for Census Places exceeding a population threshold of 4,000 people and 2) identification of prospective users of geothermal heat, including larger commercial and/or industrial users. Intended to accompany the Tier 2 data submission which will include a number of files:
1) MATLAB code for interchange with GEOPHIRES
2) Result table for Census Places
3) Result table of Prospective Users
4) Shape file of Map showing Census Places and Prospective User locations"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Risk Analysis And Risk Factor Descriptions.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/16_GPFA-AB_RiskAnalysisAndRiskFactorDescriptions.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Risk Analysis in GPFA-AB
This memo builds upon the 1 April 2015 memo entitled "Combining Risk Factors." The relevant discussion from the previous memo is retained, when applicable. One difference here is an emphasis that map colors for 3-color or 5-color maps should be related to the actual acceptability of a location measured on that risk index at the scale of the analysis. They are not relative metrics providing just a comparison to other locations or projects, but absolute evaluations of project acceptability. This makes it reasonable to consider the minimum value across risk indices as a criterion for project acceptability. This memo outlines the required map data format for the individual risk factor maps, and the information that will be required. That includes thresholds used for scaling. The memo also describes some of the ways to represent uncertainty in the analyses and visualization tools that may be used in our final analyses. This memo summarizes some methods that we thought would be applicable to combining risk factors, but it does not represent the final methods used in the analysis. The next memo gives the final results and describes the methods used."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Combining Risk Factors.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/17_GPFA-AB_CombiningRiskFactors.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Combining Risk Factors in GPFA-AB
This memo provides details and extended results related to the play fairway computations. The results include values used in converting each risk factor into the play fairway scale (scaled risk factor) and extended results on different methods of combining risk factors. The robustness of the different combination methods is briefly discussed. Calculations of uncertainty are discussed, including methods used to approximate the uncertainty in a scaled risk factor and a combined map. Detailed graphics for project locations are provided. The general principles of the combinations were outlined in the previous memo, but this document gives details on the computations and actual results from the analysis. Note: this is the lower resolution version of the file; a higher resolution version is available, but is >40MB."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Permitting Geothermal District Heating.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/18_GPFA-AB_PermittingGeothermalDistrictHeating.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Permits for Geothermal District Heating Project in GPFA-AB
Permits will be required for any new drilling associated with a geothermal district heating project. This memo summarizes the anticipated permitting requirements and associated effort for subsequent phases of the project."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Methodology.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/1_GPFA-AB_Phase1Methodology.pdf",
    "mediaType": "application/pdf",
    "description": "Supplementary detail on the analysis methodologies employed throughout the project.   

Phase 1 of the project consisted of a series of 7 tasks, the first 5 of which justify detailed explanation of the methods. Tasks one through four evaluated 4 criteria in the context of risk: thermal resources, natural reservoir quality, seismicity, and utilization. The fifth task combined these risk elements into a series of combined risk maps in order to identify geothermal play fairways. This document describes the methodology for each of these five major tasks, making some references to additional research memos contained within this section."
  },
  {
    "@type": "dcat:Distribution",
    "title": "BHT Corrections.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/2_GPFA-AB_BHTCorrections.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Determination of heat flow is a crucial element in estimating geothermal resource potential. Geothermal gradient is one of the key components in calculating heat flow. The oil and gas industry activity within the Appalachian Basin is a wealth of temperature at depth data, as 'raw' or uncorrected Bottom Hole Temperature (BHT) values are routinely collected during the oil and gas drilling and/or extraction process. However, BHT can differ from true in-situ rock values due to drilling disturbances, circulation of fluids, and other human induced factors. Additionally, extreme terrain variations as seen in mountainous areas can impact accurate determination of geothermal gradient. For these reasons, BHT values are generally ‘corrected’ to approximate an equilibrium temperature-depth profile. Over the years, several approaches to BHT corrections have been used in heat flow determinations and geothermal resource estimations. This memo describes the BHT correction methodology used in this GPFA-AB project."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Anadarko Basin Thermal Conductivity.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/3_GPFA-AB_AnadarkoBasinThermalConductivity.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

One of the key components in calculating heat flow and temperatures at depth is the thermal conductivity of the rock layers. The thermal conductivity values of rocks within the Anadarko Basin have been studied in greater detail than many other sedimentary basins. While this GPFA is focused on the Appalachian Basin, values from the Anadarko Basin have been used as a proxy where measured values unavailable within the Appalachian Basin. This memo describes the results of a resampling of Anadarko Basin thermal conductivities from Carter et al. (1998). Methods for assigning specific thermal conductivity values to each Appalachian Basin formation are discussed in an appendix to the memo entitled Assignment of Conductivity Stratigraphy for Individual Wells using COSUNA Methodology in GPFA-AB. The thermal conductivity values for each formation will be provided as an NGDS data submission."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Thermal Conductivity Stratigraphy COSUNA.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/4_GPFA-AB_ThermalConductivityStratigraphyCOSUNA.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Tests of Simplified Conductivity Stratigraphy by Monte Carlo Analysis in GPFA-AB
The simplification of well geology using the COSUNA approximation is tested by using Monte Carlo analysis to examine the potential differences of the thermal model outcomes for the COSUNA simplification compared to a full analysis of each well. For 77 wells, thermal model outcomes of the conductivity stratigraphy based on well details are compared to thermal model outcomes for the same locations if the COSUNA approximation is used instead. This memo first describes the approach of selecting a smaller subset of wells from the large collection to better understand the Basin's characteristics. Criteria were established for well selection based on availability of better lithology detail, multiple temperature-depth readings at appropriate depths, spatial distribution throughout the region of interest, etc. against which to test the COSUNA-based thermal model. The memo then describes the Monte Carlo simulation parameters. The results of the analysis are that the differences between the COSUNA stratigraphy with Carter conductivities and the detailed stratigraphy are generally minor when compared over the whole region."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Conductivity Stratigraphy Monte Carlo Analysis.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/5_GPFA-AB_ConductivityStratigraphyMonteCarloAnalysis.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

In order to determine properties of the thermal field at depth, the thermal conductivity stratigraphy of the basin must be known everywhere. In practice, it is infeasible to know the conductivity stratigraphy everywhere, so approximations are needed. For this project, the Correlation of Stratigraphic Units of North America (COSUNA) stratigraphic columns, available from the American Association of Petroleum Geologists were used as approximations of the stratigraphy because 1) well specific stratigraphy is not available for every well, and 2) the time constraints of Phase 1 would not be conducive to implementing specific geology to each well. COSUNA provides information on stratigraphy for 'sections' throughout the continent, including approximate thicknesses of different rock types. A weighted average of thermal conductivity for the entire wellbore can be approximated by consulting COSUNA charts for the various rock types and thicknesses encountered within the well. This memo documents the approach, assumptions, limitations, advantages, etc. of the COSUNA methodology for assignment of thermal conductivity and formation thicknesses to each well."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Thermal Outlier Assessment.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/6_GPFA-AB_ThermalOutlierAssessment.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

The project team must determine which algorithm should be used to identify outliers in the geospatial datasets. Outliers pose a problem for non-robust regression schemes because they would have high squared residuals. Many regression techniques seek to minimize the squared residuals, so an outlier can have undue influence on the results of the analysis. This memo outlines the recommended outlier detection algorithm and contains several appendices within it. Appendix 1 outlines the previous work on outlier algorithms for the NY and PA geothermal dataset. Appendix 2 illustrates the sensitivity of the final results to algorithm parameters over a reasonable range of values. Appendix 3 provides Monte Carlo type I error rates for different distributions with known shape (e.g. normal, student t, uniform). The type I errors were derived empirically using Monte Carlo simulation for sample size of 25. In addition to references, appendices for this memo include:
1. Appendix 1: Summary of Outlier Algorithms Used at Cornell
2. Appendix 2: Sensitivity Analysis of Recommended Algorithm
3. Appendix 3: Type I Error Rates"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Thermal Resource Thresholds.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/7_GPFA-AB_ThermalResourceThresholds.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

The thermal risk factor needs to have thresholds assigned for visualizing the map in the discrete play-fairway color scheme. These thresholds should be objectively defined to reflect actual acceptability of the resource at that threshold level. Using this method, the resulting risk factor maps will reflect the favorability of the site. This memo discusses how the risk thresholds were determined for the Thermal Risk Factor, and the methods are transferrable to other risk factors."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Thermal Model Methods.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/8_GPFA-AB_ThermalModelMethods.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Thermal Model Methods and Well Database Organization in GPFA-AB
This memo describes the reorganization of the GPFA well database into a format with additional data fields that are necessary to run the thermal model. It also describes the methods, assumptions, and equations used in the thermal model. These methods were used for creating the 3rd quarter and final thermal maps for this project. This memo will accompany the Tier 2 Data submission for the Thermal Analysis task, including a Derivation of 1-D Conduction Heat Balance. The Tier 2 Thermal Analysis data upload will contain several attached files with this memo:
1) Well Databases Folder
2) Trenton-Black River Sediment Thickness Map
3) Influence of Annual Temperature Fluctuation on Near-Surface Temperatures
4) Drilling Fluid Query in SQL
5) Probabilistic assignment of Drilling Fluid based on Nearest Neighbor Wells"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Interpolation Thermal Field Estimation.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/9_GPFA-AB_InterpolationThermalFieldEstimation.pdf",
    "mediaType": "application/pdf",
    "description": "One of several project memos supplementing the final report.  

Exploratory Data Analysis and Interpolation Methodology for Thermal Field Estimation
This memo describes the methods, including formulas and assumptions, used to interpolate the geotherm data at each well to create the thermal risk factor and uncertainty maps for the project. Included in this memo is an exploratory data analysis on wells after processing in the thermal model."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Phase 1 Final Report.pdf",
    "format": "pdf",
    "accessURL": "https://gdr.openei.org/files/682/Phase%201%20Final%20Report%20Jan2016_UploadedToGDR.pdf",
    "mediaType": "application/pdf",
    "description": "Final phase 1 report for the Appalachian Basin Play Fairway Analysis project."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Updated Phase 1 Final Report and Additional Data",
    "format": "HTML",
    "accessURL": "https://gdr.openei.org/submissions/899",
    "mediaType": "text/html",
    "description": "Link to newer GDR submission with updated final report and full list of links to additional data on GDR."
  }
]
                                        

                                            [
  "Appalachian Basin",
  "DDU",
  "Monte Carlo",
  "New York",
  "PFA",
  "Pennsylvania",
  "West Virginia",
  "analysis",
  "characterization",
  "deep direct use",
  "exploration",
  "final report",
  "geothermal",
  "geothermal play fairway analysis",
  "low temperature",
  "phase 1",
  "play fairway"
]
                                        

                                            [
  "019:006"
]
                                        

                                            {
  "name": "Cornell University",
  "@type": "org:Organization"
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