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

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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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Page 1: IPAS: An ArcGIS Server-based framework for oil and gas E and P decision support

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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IPAS: Infrastructure Placement Analysis System• LINGO Low Impact Natural Gas and

Oil• DOE funded• NETL (National Energy Technology Laboratory)

• Integrates current technologies and practices to minimize adverse environmental impacts

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“Closed” web-based decision support system• Drillers and regulators share:• Geographic view of proposed infrastructure• Environmental and sensitive area data• Models of potential impacts• Secure environment

• Increases communication efficiency• Speeds up permitting

• Increases transparency – regulators/producers

IPAS: Infrastructure Placement Analysis System

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Architecture• 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

• Will be ported to AGS 10.x

IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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Required datasets• Wells (we harvest some well data)• Sensitive areas/species• Hydrography – NHD high-res preferably• Soils – SSURGO (must be preprocessed)• DEM• Pipelines• Typical cultural/base layers

IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

• Uncertainty• An attempt to deal with inaccuracies in spatial

data• Used in sensitive area analyses and feature

digitization• 90% confidence interval as defined by National

Map Accuracy Standards• Created as inner and outer buffers

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• Uncertainty• 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

• Soils: digitized at 24K 40 foot inner and outer buffer

• For digitized features, further zoomed out, greater the uncertainty

IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

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IPAS: Infrastructure Placement Analysis System

Likelihood ofimpact

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IPAS: Infrastructure Placement Analysis System

Likelihood ofimpact:Strong – “certain” area offeature and “certain”sensitive area

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IPAS: Infrastructure Placement Analysis System

Likelihood ofimpact:Moderate – “certain” area offeature and “uncertain”sensitive area (1), or “uncertain” area of feature and “certain”sensitive area (2)

1

2

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IPAS: Infrastructure Placement Analysis System

Likelihood ofimpact:Slight – “uncertainty zones” of both feature and sensitive area

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IPAS: Infrastructure Placement Analysis System

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• Other features• Collaboration system• Operator to regulator• Emailing• Could be for internal use only as well

• Audit tracking• Public informational sites

IPAS: Infrastructure Placement Analysis System

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www.lingo.cast.uark.edu/LINGOPUBLIC

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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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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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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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www.cast.uark.edu


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