An ArcGIS Server-based framework for oil and gas E&P decision support

An ArcGIS Server-based framework for oil and gas E&P decision support

Presented at the 2012 ESRI PUG in Houston and the 2012 OK SCAUG meeting

Exploration and production activities can reap significant benefits from the use of GIS-based decision support tools, yet it is rarely practical to distribute desktop GIS tools to every potential user in an organization. The Center for Advanced Spatial Technologies (CAST), in collaboration with the University of Arkansas Department of Chemical Engineering and Argonne National Lab, has created a robust framework centered on ArcGIS Server which allows the integration of geoprocessing models both from within ArcGIS and from external platforms, while providing secure, distributed access across organizations. Funded by the Department of Energy National Energy Technology Laboratory (DOE-NETL) and from The Research Partnership to Secure Energy for America (RPSEA), pilot implementations have been developed for both the Fayetteville and Haynesville shale gas plays.

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Chad Cooper

May 19, 2013
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Transcript

  1. An ArcGIS Server-based framework for oil and gas E&P decision

    support Chad Cooper, Peter Smith, Malcolm Williamson, Jackson Cothren Center for Advanced Spatial Technologies University of Arkansas
  2. IPAS: Infrastructure Placement Analysis System Purpose: Integrate current technologies and

    practices to minimize adverse environmental impacts
  3. “Closed” web-based decision support system (DSS) • Operators and regulators

    share: • Geographic view of proposed infrastructure • Environmental and sensitive area data • Models of potential impacts • Secure environment – only see your data IPAS: What is it?
  4. • GIS-based infrastructure planning • well pads, gathering lines, lease

    roads • use sensitive and environmental data • Increased communication efficiency • Speeds up permitting = $$$ saved • Increased transparency between regulators and producers • User-friendly interface IPAS: What does it provide?
  5. • Ver. 1: 9.2 Web ADF • Ver. 2: 9.3.1

    ArcGIS Server • JavaScript API • Lots o’ custom code • SQL Server 2008 Spatial • Spatial datatypes • Python – geoprocessing • Matlab – spill modeling • Being ported to AGS 10.0 (v3) IPAS: Architecture
  6. IPAS: System design

  7. • Wells (we harvest some well data) • Sensitive areas/species

    – hard to get • Hydrography – NHD high-res preferably • Soils – SSURGO (must be preprocessed) • DEM • Pipelines – hard for CAST to get • Typical cultural/base layers IPAS: Required datasets
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  16. IPAS: Uncertainty • An attempt to deal with inaccuracies in

    spatial data • Used in sensitive area analyses and feature digitization (further zoomed out, greater the uncertainty) • 90% confidence interval as defined by National Map Accuracy Standards
  17. “For maps on publication scales > 1:20,000, not more than

    10% of the points shall be in error by more than 1/30 inch, measured on the publication scale; for maps on publication scales of <= 1:20,000, 1/50 inch” IPAS: Uncertainty and National Map Accuracy Standards
  18. http://www.flickr.com/photos/b-tal/163450213/

  19. IPAS: Uncertainty ℎ × 12 ℎ/ =

  20. Soils: digitized at 24K  40 foot inner and outer

    buffer IPAS: Uncertainty 1 50 × 24,000 12 = 40 ℎ × 12 ℎ/ =
  21. IPAS: Uncertainty

  22. IPAS: Uncertainty

  23. IPAS: Uncertainty

  24. IPAS: Uncertainty

  25. IPAS: Uncertainty

  26. IPAS: Uncertainty

  27. IPAS: Uncertainty Likelihood of impact

  28. IPAS: Uncertainty Likelihood of impact: Strong – “certain” area of

    feature and “certain” sensitive area feature = pad sensitive area = soil
  29. IPAS: Uncertainty Likelihood of impact: Moderate – “certain” area of

    feature and “uncertain” sensitive area (1), or “uncertain” area of feature and “certain” sensitive area (2) 1 2
  30. IPAS: Uncertainty Likelihood of impact: Slight – “uncertainty zones” of

    both feature and sensitive area
  31. IPAS: Uncertainty

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  48. • Collaboration system • Operator to regulator • Emailing •

    Could be for internal use only as well • Audit tracking • Public informational sites IPAS: Features
  49. www.lingo.cast.uark.edu/LINGOPUBLIC

  50. IPAS: New Directions Haynesville Shale play • Funded through Houston

    Advanced Research Center/Environmentally Friendly Drilling program • Port the app across plays • Challenges of multi-state regulations and data
  51. IPAS: New Directions Water modeling in the Fayetteville play •

    Blacklands Research & Extension Center, Texas A&M – (modified) SWAT model • DOE funding through NETL • Focus on surface water • AR Natural Resources Commission • Improved understanding of available water • Faster permitting with peace of mind
  52. IPAS: New Directions NHD high-resolution water layer (yellow). Water (blue)

    extracted from the color- infrared imagery. Object-based classification using Trimble eCognition.
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  54. Wanna beta test? chad@cast.uark.edu cast.uark.edu