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COUNTY AND LOCAL ROAD NEEDS 2012. Previous Studies (2010-11). Additional Road Investments Needed to Support Oil and Gas Production and Development in North Dakota Rural Road Investment Needs to Support Agricultural Logistics and Economic Development in North Dakota. SB 2325.
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Previous Studies (2010-11) • Additional Road Investments Needed to Support Oil and Gas Production and Development in North Dakota • Rural Road Investment Needs to Support Agricultural Logistics and Economic Development in North Dakota
SB 2325 • “The purpose of updating and maintaining reports for transportation infrastructure needs for all county and township roads in the state, for the biennium beginning July 1, 2011 and ending June 30, 2013”
Analysis Process • Traffic Volume • Existing Structure • Existing Condition • Costs and Practices
Traffic Volume • Locations • Volumes • Forecasts • Routing • Optimization • Results
Traffic Types Modeled • Oil Development • Agricultural Movements
Location Assignment • Data Collection • Network: Federal, State, Local • Locations: • Spacing Units (Oil & Gas) • Input Sources (NDDOT, Oil & Gas, SWC) • Output Destinations (NDDOT, Oil & Gas, SWC) • Elevators (UGPTI) • Townships (Census) • Volumes: • Oil – (Oil & Gas) • Agriculture (NDPSC Grain Movement) • Forecasts: • Oil – (Oil & Gas) • Agriculture (NDSU – Ag Extension)
Volumes • Oil • Based upon NDDOT white paper (2,300 trucks per well) • Overloads estimated based upon internal assumptions and verified using weigh station data • Oil Related ESAL assumptions taken from NDDOT estimates • Agriculture • Based upon average truck yield and throughput data from NDPSC Grain Movement Database
Forecasts • Oil • Developed from forecasts provided by Oil & Gas • Agriculture • Based upon discussions with NDSU Extension, Industry organizations
Future Well Locations • Drilling • Zonal Plan/Forecasts • Area Density • Frequency of Drilling in a Spacing Unit • Age of Well • Subject to • Zonal Plan/Forecasts • Number of Wells in a spacing unit
Route Generation • ESRI Network Analyst was used to generate routes between: • Spacing Units (fronthauland backhaul) • Freshwater • Oil transload facilities • Sand locations • Cities • SWD • Spacing Units • Townships (fronthaul and backhaul) • Elevators • Ethanol Facilities • Processors • Elevators (fronthaul and backhaul) • Elevators • Ethanol Facilities • Processors • Final Destinations
Sample Routing • Inbound • Sand • Water • Pipe • Outbound • Oil • Rail Transload • Pipe Transload • SWD
Agricultural Analysis Known Crop Production Predict Truck Trips and Routes Known Elevator & Plant Demands Estimate Segment Specific Traffic Data: Crop Production (NASS), Elevator Volumes (NDPSC), In-State Processors (Survey), Road Network (NDDOT-GIS Hub), Local Road Data (2008 Survey)
Distribution Model • Each township connected to nearest 150 elevators • Elevators connected to each other • Elevators connected to plants • Fastest and shortest route algorithms • Objective: meet the demands at elevators and in-state processing plants with minimal hauling distances (trucking cost)
Network Optimization • Constrained Optimization Model • Freshwater to Wells • Sand to Wells • Gravel to Wells • Pipe to Wells • Equipment to Wells • Supplies to Wells • Agricultural Commodities to Elevators and Processors • Wheat • Soybeans • Corn • Lentils/Dry Edible Beans • Barley • Oats • Sunflower
Network Optimization • Thirteen separate optimization models were estimated for each year of the analysis (260 in total) • Volumes from all optimization runs were aggregated to individual roadway segments
Existing Structure • Surface Type obtained from GIS Shapefiles • Surface Type verified by county officials • Independent verification • Graded roadway width – survey
Existing Condition • 1,000 miles of paved CMC roads were scored using the NDDOT deduct scoring system • The approximately 4,500 remaining paved CMC roads were given condition ratings by county officials using a 5 category condition assessment • Both condition assessment methods were converted to Present Serviceability Rating (PSR) scores
Costs and Practices • Data collected through survey of county road managers
Improvement Types • Paved • Condition scores converted to PSR • SN information, where available, calculated or estimated based upon past responses/typical structure • AASHTO models used to simulate pavement deterioration and improvement types
Improvement Types • Paved • Resurfacing • Reconstruction due to condition • Sliver widening due to roadway width
Improvement Types - Gravel • Types of Practices • Graveling and Blading • Normal Levels (Example: regraveling every 5 years, blade once per month) • Increased Levels (Example: regraveling every 3-4 years, blade twice per month) • High Levels (Example: regraveling every 2-3 years, blade once per week) • Usage of Dust Suppressant on Impacted Roads • Graveling and Base Stabilization • Base 1 • Permazyme • Concrete • Graveling and Base Stabilization with Armor Coat • Base 1 • Permazyme • Concrete • Asphalt Surface
Improvement Types - Gravel • Traffic model results will be segmented based upon traffic levels • Levels broken into increments of 50 AADT • 0-50 • 50-100 • 100-150 • 150-200 • 200-250 • 250+ • County specific practices will be used as the base maintenance practices • Life cycle costs of each maintenance practice will be calculated (i.e. 20 year cost of graveling) • Maintenance Type/Improvement selected for each AADT class based upon minimum life cycle cost
Draft Report • The full report can be found at www.ugpti.org – look in the upper right portion of the webpage • Alan Dybing • alan.dybing@ndsu.edu • 701.231.5988