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Interactive Map of Marcellus and Utica Shale in Pennsylvania: Depth and Thickness Analysis

This project presents an interactive web map showcasing the thickness and depth variations of the Marcellus and Utica Shale formations within Pennsylvania. Developed by Dr. Jay Parrish and Derek W. Kobre, it aims to provide insights into the shale's geological significance and resources. The map utilizes geostatistical analysis with ArcGIS and MySQL databases, making it a valuable tool for researchers, energy companies, and policy makers. It highlights the importance of shale gas production and the methods used in horizontal and hydraulic fracking.

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Interactive Map of Marcellus and Utica Shale in Pennsylvania: Depth and Thickness Analysis

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  1. Interactive Web Map of Marcellus and Utica Shale Showing Thickness and Depth within the State of PA Adviser: Dr. Jay Parrish Derege W. Kobre

  2. INTRODUCTION • Objective? • Why I have chosen this project ? • Who will benefit from the project ? • What is Marcellus Shale and why it is important? • What is Utica Shale and why it is important?

  3. INTRODUCTION • The recent change in drilling and production • What is Horizontal Fracking ? • What is Hydraulic Fracking ? • What is the estimated resource from the Marcellus Shale? • What is the estimated resource from the Utica Shale? Vertical Fractures Or Pores

  4. WORKFLOW SOURCE DATA EXCEL SPREAD SHEET FILE FORMAT GEOSTATISTICAL ANALYSIS ArcGIS DESKTOP TEXT & TABLE FILE FORMATS(.csv and .dbs for geometry and attributes respectively) ACCESS MySQL SERVER PHP XML FILE FORMAT WEB DEVELOPMENT CLIENT

  5. METHODOLOGY • Source Data (EXL Spread Sheet) • MWELLHEADER.xls • Marcellus_tops.xls • Utica_tops.xls • Algorithm • Data Preparation (ACCESS database)

  6. METHODOLOGY • Source Data (EXL Spread Sheet) • Algorithm • Data Preparation (ACCESS database) • Create query1 from the joined MWELLHEADER table and Marcellus_tops table based on UWI and MTOP values (1795 RETURNS) • Create query2 from the joined MWELLHEADER table and Marcellus_tops table based on UWI and MBOT values (1753 RETURNS) • Create query3 that will change query1 to a table named WELLMTOP • Create query4 that will change query2 to a table named WELLMBOT

  7. METHODOLOGY • Source Data • Algorithm • Data Preparation (ACCESS database) • Geoprocessing (ArcGIS) • Add coordinate data to the WELLMTOP table (x y events) & save as a shapefile • Join the rest of the table to it to include the fields MTOP and MBOT and name the combined shapefile WELLCOMB • Add the fields MTHICK and MDEPTH • Use the field calculator to update the records (e.g MTHICK = [MBOT]-[MTOP] )

  8. Geoprocessing (ArcGIS) • Do Geostatistical Analysis from Geostatistical Wizard using Kriging method for each fields to create a prediction map layer of polygon shape • right click on the kriging layer • Click data >> export to vector • Confirm that "GA Layer To Contour" dialogue box pops up allowing to make a polygon shape file of filled contours that showed both the prediction map and prediction standard error map for each field • Use Natural Neigbour method for the Utica data • Reclassify raster output • Change raster to polygon

  9. Geoprocessing (ArcGIS) • Export the shapefiles out to Access database. • MWELL.shp • UWELL.shp • MTHICK.shp • MDEPTH.shp • MTHICKERR.shp • MDEPTHERR.shp • Uthick.shp • Udepth.shp • The shapfiles are exported out in two forms • Text (use export shapefile to csv tool created by Jim Detwiler from my toolbox) Note: to append the geometry data • Table (dbase IV) Note: to append the attributes

  10. METHODOLOGY • Source Data • Algorithm • Data Preparation (ACCESS database) • Geoprocessing (ArcGIS) • Create Tables (MySQL database) • Form XML data using PHP server side scripting language

  11. METHODOLOGY • Source Data • Algorithm • Data Preparation (ACCESS database) • Geoprocessing (ArcGIS) • Create Tables (MySQL database) • Form XML data using PHP server side scripting language

  12. METHODOLOGY • Source Data • Algorithm • Data Preparation (ACCESS database) • Geoprocessing (ArcGIS) • Create Tables (MySQL database) • Form XML data using PHP server side scripting language • Create the point and polygon maps using Google Engine, HTML and JavaScript client side programming language • Repeat the above two steps for each layer

  13. ANTICIPATED RESULTS

  14. ANTICIPATED RESULTS

  15. ANTICIPATED RESULTS

  16. ANTICIPATED RESULTS

  17. CONCLUSION • Challenges • Improving result with more data • Future prospect in improved methodology • Sample demonstration

  18. CONFERENCE • GSA Northeastern Section • 49th Annual Meeting • 23 to 25 March 2014 • GSA • Abstract deadline: 10 Dec. 2013

  19. REFERENCES • David O'Sullivan, P., & Unwin, D. J. (2010). Geographic Information Analysis (2nd ed.). New Jersey: John Wiley & Sons, Inc. • King, H. (n.d.). Marcellus Shale - Appalachian Basin Natural Gas Play. Retrieved 12 01, 2013, from Geology.com: http://geology.com/articles/marcellus-shale.shtml • Maps and Digital Data. (n.d.). Retrieved from DCNR Pennsylvania Department of Conservation and Natural Resources: http://www.dcnr.state.pa.us/topogeo/econresource/oilandgas/marcellus/marcellus_maps/index.htm • NETL. (2007, 1 31). Natural Gas Program Archive. Retrieved from U.S. Department of Energy: Office of Fossil Energy: National Energy Technology Laboratory: http://www.netl.doe.gov/KMD/Forms/CdDvdRetrieval.aspx

  20. QUESTIONS? Your comments and feedbacks are appreciated

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