Additional Road Investments Needed to Support Oil Gas .ppt
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1、Additional Road Investments Needed to Support Oil & Gas Production and Distribution in North Dakota,Upper Great Plains Transportation Institute North Dakota State University,Presentation Topics,Overview of study and results Details of analysis Details of unpaved road analysis Types of improvements a
2、nd analysis methods Details of paved road analysis Types of improvements, costs, and effects Conclusions and discussion,2,Study Overview,Purpose: Forecast road investment needs in oil and gas producing counties of North Dakota over the next 20 years Objective: Quantify the additional investments nec
3、essary for efficient year-round transportation for the oil industry while providing travelers with acceptable roadway service,3,Study Overview,Scope: The focus is on roads owned or maintained by local governments e.g. counties and townships. Study Area: 17 oil and gas producing counties Counties inc
4、lude: Billings, Bottineau, Bowman, Burke, Divide, Dunn, Golden Valley, McHenry, McKenzie, Mclean, Mercer, Mountrail, Renville, Slope, Stark, Ward, and Williams,4,Primary Data Sources,Analysis based on: oil production forecasts, traffic data, county road surveys Types of roads analyzed: paved, gravel
5、ed, and graded & drained 2010 survey information on impacted routes and conditions 2008 survey information on typical road characteristics,5,Production Forecasting,Oil &Gas Division of North Dakota Industrial Commission Existing and near-term drilling locations Based upon current rig activity and pe
6、rmit applications through end of 2010 Future locations of rigs estimated from lease data from North Dakota Land Department,6,Drilling Phases,Initial phase: lease expirations 2010-2015 Assume drilling begins in final year of lease Fill-in phase: 3-5 additional wells placed Private leases will occur i
7、n same areas as public leases 21,250 wells drilled in next 10-20 years Assume 1,500/year14 years to drill 21,250 wells,7,Traffic Prediction Model,Forecasted output of wells is routed over road network using detailed GIS model Oil movements converted to equivalent truck trips following least-cost rou
8、tes Projected inputs (e.g., sand and water) and outbound movements (salt water) similarly routed Movements of specialized equipment (such as workover rigs) included,8,Road Investment Analysis,Predicted inbound and outbound movements accumulated for each impacted segment Oil-related trips combined wi
9、th baseline (non-oil) traffic to estimate total traffic load on each road Economic/engineering methods used to estimate additional investment needs,9,Field Data: Traffic Counts,Counters deployed at 100 locations Raw data adjustedTo represent traffic for 24-hour periodMonthly variation ADT=145; Truck
10、s=61 (26 multi-units) Paved roads 100 trucks/day Data used to calibrate trip model and estimate baseline traffic loads,10,Estimated Investment Needs 2012-2013 - 2030-2031 (Millions),11,Investment Needs by Biennium (Millions),12,Details of Analysis,Data Collection Network Flow Modeling Unpaved Analys
11、is Paved Analysis,13,Data Collection,Roadway Data Traffic Classification Traffic Counts Condition Data Cost and Practices Data Oil Development Data Number and Locations of Wells Inputs to Production Origins and Destinations Production Output Origins and Destinations,14,Roadway Data,Traffic Classific
12、ation Maps sent to county point person with instructions to classify roadways by traffic levels Used to identify potential sample traffic count sites Traffic Counts Selected using the classification data provided by the county point people Used to calibrate the GIS network routing model and to verif
13、y vehicle classification Photos were taken of many of the road segments where counters were placed, and used to verify surface type and condition data,15,Cost and Practices Data,Survey of County Contacts Component costs - Unpaved Gravel Blading Location Delivery Placement Dust suppressant Paving cos
14、ts,16,Cost and Practices Data,Survey of County Contacts Maintenance Practices Gravel Overlay Interval Gravel Overlay Thickness Blading Interval Dust Suppressant Usage,17,Cost and Practices Data,County Level Cost Calculations Due to the variations in reported costs and practices, unpaved costs were c
15、alculated at the county level Reflects actual practices and actual costs at the time of the analysis,18,Roadway Data,Condition Data Maps were sent to the county point person with instructions to classify roadways by surface condition Specific classification instructions were given, per the South Dak
16、ota Pavement Condition Survey Guide 692 miles listed as either poor or very poor condition,19,Oil Development Data,Numbers and Locations of Wells Initial rig and well locations obtained from NDIC Oil & Gas Division website Forecasted locations estimated from ND Land Department GIS shapefiles of publ
17、ic land leases Leases for public lands only Private land development assumed to be in the same geographic region as the public leases Buffer public lands to estimate development areas on private land,20,Oil Development Data,Forecasted locations estimated from ND Land Department GIS shapefiles of pub
18、lic land leases ND Land Department data has lease expiration dates Assumption that drilling will occur in the final year of the lease, and is a single well Oil & Gas estimates 1,450-2,940 wells/year 2,140 expected, 21,250 in 10 to 20 years Lease expirations available through 2015 Post 2015 filling i
19、n phase of drilling 4-6 additional wells on the site,21,Oil Development Data,Inputs Data collected from Oil & Gas, NDDOT, and industry representatives The goal was to quantify the number and type of truck trips that the well drilling process generates The major trip generators were water, equipment
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