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.

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
   

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2. IPAS: Infrastructure Placement
   Analysis System
   Purpose:
   Integrate current technologies and
   practices to minimize adverse
   environmental impacts
   

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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?
   

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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?
   

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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
   

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6. IPAS: System design
   

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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
    

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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
    

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18. http://www.flickr.com/photos/b-tal/163450213/
    

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19. IPAS: Uncertainty
    ℎ ×
    12 ℎ/ =
    

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20. Soils: digitized at 24K  40 foot inner and
    outer buffer
    IPAS: Uncertainty
    1
    50 × 24,000
    12 = 40
    ℎ ×
    12 ℎ/ =
    

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21. IPAS: Uncertainty
    

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22. IPAS: Uncertainty
    

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23. IPAS: Uncertainty
    

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24. IPAS: Uncertainty
    

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25. IPAS: Uncertainty
    

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26. IPAS: Uncertainty
    

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27. IPAS: Uncertainty
    Likelihood of
    impact
    

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

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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
    

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30. IPAS: Uncertainty
    Likelihood of
    impact:
    Slight –
    “uncertainty
    zones” of both
    feature and
    sensitive area
    

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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
    

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49. www.lingo.cast.uark.edu/LINGOPUBLIC
    

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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
    

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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
    

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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
    

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