north slope decision support system case studiesnsdss.ine.uaf.edu/docs/nsdss_casestudies.pdfnorth...

North Slope Decision Support System

Case Studies

Prepared for:

University of Alaska, Fairbanks

In a project sponsored by:

U.S. Dept. of Energy, National Energy Technologies Laboratory

06/30/2013

http://en.openei.org/wiki/File:NETL-Logo-Color-1.jpg

North Slope Decision Support System –Case Studies

2 | NSDSS: Case Studies

Contents Contents ...........................................................................................................................................2 Summary ..........................................................................................................................................3 1 Case Study 1: Chevron’s White Hills Ice Road .....................................................................5

1.1 Background ......................................................................................................................5 1.2 Case Study Objectives ......................................................................................................6 1.3 Process .............................................................................................................................6 1.4 Ice Road Alignment Results .............................................................................................7 1.5 Lake Water Budget Model Results ................................................................................12 1.6 Lake Water Dissolved Oxygen Model Results ................................................................16 1.7 Further Reading .............................................................................................................17

2 Case Study 2: The Road to Kavik Camp ..............................................................................18 2.1 Background ....................................................................................................................18 2.2 Case Study Objectives ....................................................................................................18 2.3 Process ...........................................................................................................................18 2.4 Landscape Suitability Analysis Results ...........................................................................19



Summary The University of Alaska Fairbanks (UAF hereafter) partnered with Texas A&M University (TAMU hereafter) and Atkins in a research project to develop the North Slope Decision Support System. The objective of the research was to develop a tool to help stakeholders manage water resources related to ice roads used for oil exploration on the North Slope of Alaska. The grant was sponsored by the National Energy Technology Laboratory (NETL), which is a national Lab under the U.S. Department of Energy (DOE). Project Personnel The project is led by Dr. William Schnabel from the UAF, by Dr. Kelly Brumbelow from Texas A&M University (TAMU), and by Stephen Bourne, from Atkins. Several other team members were included in each team. The UAF team led the natural system modeling portions of the project. The TAMU team led the decision modeling portion. The Atkins team led the technology portion. Case Study Objectives

Two cases studies were conducted in the later phases of the project. The objectives of the case study exercises were to:

1. Provide real-world examples that allowed stakeholders to see how the NSDSS tools can be used.

2. Illustrate to specific stakeholders the value of the tools. 3. Act as a ground-truthing exercise for the NSDSS tool and underlying methods. 4. Illustrate where the NSDSS databases and tools can be extended and enhanced.

Case Studies

In the first case study, the NSDSS was utilized to develop an ice road plan for an ice road that had already been permitted and constructed. In this case study, we utilized the White Hills ice road used by Chevron for oil and gas exploration in winter 2007-2008. The purpose of the case study was to evaluate how an ice road designed via the NSDSS toolkit might differ from an ice road designed in the traditional fashion. The case study included:

• An ice road planning exercise to assess how similar the NSDSS recommended route was to the Chevron route.

• A water budget model conducted on one of the source lakes, to assess the availability of water for ice road use.

• A lake dissolved oxygen model, to assess if water quality would be unacceptably impacted by water extraction.



The second case study was focused on ice road landscape suitability analysis. The purpose of this case study was to evaluate whether the landscape surrounding a hypothetical gravel road extending from the Dalton Highway to Kavik Camp would support extensive ice road development. The case study was intended to be analogous to existing discussions regarding various proposed routes for a gravel road leading to Umiat. In the case study, the NSDSS landscape suitability analysis tool was used to create a road to Kavik Camp, located on the Coastal Plain approximately 50 km from the Dalton Highway. Hypothetical ice road routes were created from starting points at approximately 10 mile intervals along the proposed road alignment. The cost-effectiveness and environmental suitability of each route was evaluated to understand which sections of the landscape were most and least suitable for ice road construction.



1 Case Study 1: Chevron’s White Hills Ice Road

1.1 Background

The White Hills ice road was built for the drilling season of 2007-2008 by Union Oil Company of California (UOCC) a wholly-owned indirect subsidiary of Chevron Corporation. Initial operations were staged from the Franklin Bluffs gravel pad at milepost 39.6 of the Dalton Highway. Ice Roads were constructed from the Franklin Bluffs staging area to the first well location, Smilodon 9-4-9; south to the second well location, Mastodon 6-3-9; and north to the third well location, Panthera 28-6-9.

1-1. The Preliminary White Hills Ice Road Design. River Crossing are marked by red circles.



1.2 Case Study Objectives The objectives of the case study were:

1. Evaluate how closely the ice road routing algorithm’s recommendations came to the actual road that was designed.

2. Evaluate whether the ice road routing algorithm produced a more cost-effective route.

3. Identify the extent to which the current planning-level algorithm can take the ice road planner. It is expected that the current tool provides a general corridor in which to build the most cost-effective routes. On-the-ground features like ridges, small streams, etc. that are not captured in the tool’s digital elevation model and other GIS resources can have a large effect on budget.

4. Produce the full suite of information that the NSDSS is designed to generate for this real-

world project, including a lake water budget and associated climate-change aware forecast of water availability, and a lake dissolved oxygen model and associated forecast of water quality impacts.

1.3 Process Using data gathered from publically-available Alaska Department of Natural Resources reports on the White Hills ice road, we replicated the ice road planning scenario within the NSDSS tool. Without any knowledge of the prior route of the road, the tool was used to build an ice road to the potential oil exploration sites. In addition, we built a lake water budget model and associated water availability forecasts and risk analysis for the lake that would be used. Finally, we built a lake dissolved oxygen model to provide an estimate of the water quality impacts.



1.4 Ice Road Alignment Results The White Hills ice road was modeled using the Ice Road Planning Module within NSDSS. Because the ice road had three separate sections and the river crossings were predetermined, the ice road was split at the Smilodon junction and the tool was run separately for all three sections. The first section was from the Franklin Bluffs staging area to the well location Smilodon, the second section from Smilodon north to Panthera, and the third section from Smilodon south to Mastodon. Each river crossing was used as a waypoint between the start and endpoints. The model was run for 17 separate sections of ice road between the different waypoints. Once all of the sections of the road were modeled the results with the lowest cost for each section were combined together to analyze the road developed by NSDSS versus the preliminary route developed by Chevron. The four objectives tied to the cost of the road are travel time, construction cost, construction duration, and distance from supply points. The two routes (one designed by Chevron and one by NSDSS) were compared based on the costs associated with the route length and spatial location. The travel time, construction cost, and construction duration are all costs associated with the length of the path. The distance from supply points is associated with the spatial location of the path in relation to the permitted lakes used for water withdrawal. Each run within NSDSS produced the 10 best routes according to the costs. The table of results displays the length (miles), cost (million $), water used (million gallons), average haul distance (miles), travel time, travel time monetized ($), construction costs ($), construction duration, and construction duration monetized ($). The results table for section 12 is shown in the figure below. The results were then plotted using the length of the path, cost, and the average haul distance. The plotted results for section 12 are given in Figure 1-3.

1-2: NSDSS section 12 results. Top 10 ice road routes for section 12.



1-3: NSSS section 12 results - a plot of route length vs. haul distance, and cost.

Figure 1-3 illustrates the relationships between the length of the path, the average haul distance, and the cost of the path. From this figure you can see that the path with the shortest length is not necessarily the path with the lowest cost. When factoring in the costs associated with the haul distance, the most desirable path is one which minimizes both the length of the path as well as the haul distance. This example illustrates the role that water supply and location play in determining the best route for an ice road. To analyze the entire route the lowest cost results produced by the tool for each section were chosen and aggregated together. These results were then compared against what was designed as a preliminary route by Chevron. The NSDSS route summary is given in Table 1 and a comparison of the results is given in Table 2. The figure below illustrates the two separate routes. From the results given by NSDSS, the final route had a projected cost of $12,000,000, was 47.12 miles in length, used an estimated total of 108 million gallons of water, and had an average haul distance of 6.31 miles. We note here that the costs estimates were based upon default construction cost values programmed in to the NSDSS system. Tool users are provided an opportunity to modify the input values to more closely reflect their own observed construction costs.



1-4: Preliminary Chevron Route vs. NSDSS Route.



Table 1. NSDSS Route Summary

WHIR Section

Length (miles)

Cost (Million $)

Water Used (M gal)

Avg. Haul Distance (miles)

Start Point to Smilodon 1 4.53 1.15 10.359 1.63 2 3.26 0.86 7.454 0.68 3 1.62 0.35 3.704 5.6 4 4.57 1.16 10.444 5.2 5 3.8 1.01 8.698 7.99 6 1.7 0.41 3.893 0.54 7 4.88 1.2 11.158 6.67 8 0.73 0.19 1.668 4.9 9 0.91 0.2 2.087 0.95

10 5.22 1.32 11.944 6.39 ∑ 31.22 8 71.41 4.61

Smilodon to Pantera 11 2.14 0.52 4.889 7.3 12 2.71 0.68 6.205 11.56 13 2.05 0.54 4.682 21.09 14 2.76 0.62 6.307 3.36 15 0.62 0.2 1.423 3.29 ∑ 10.28 3 23.51 9.87

Smilodon to Mastodon 16 3.51 0.85 8.026 3.6 17 2.11 0.55 4.823 18.56 ∑ 5.62 1 12.85 9.22

Total 47.12 12 107.76 6.31



Table 2. Route Length Comparison

WHIR Section

Preliminary Design Route

NSDSS Route

Length (miles) Start Point to Smilodon

1 4.91 4.88 2 3.78 3.43 3 1.95 1.75 4 4.53 4.84 5 4.24 4.13 6 1.86 1.91 7 5.27 5.19 8 1.02 0.76 9 1.01 0.97

10 5.24 5.24 ∑ 33.81 33.09

Smilodon to Pantera 11 2.22 2.34 12 2.65 2.62 13 1.78 2.11 14 0.93 2.84 15 0.61 0.61 ∑ 8.20 10.52

Smilodon to Mastodon 16 3.53 3.70 17 2.04 2.19 ∑ 5.58 5.89

Total 47.58 49.50

In order to compare the two routes the map of the White Hills ice road preliminary design developed by Chevron, and the routes developed by NSDSS were digitized and georeferenced within ArcGIS. After this the routes were analyzed using tools within GIS. The preliminary route had a total length of 47.58 miles. The route developed by NSDSS had a total length of 49.50 miles, 2.38 miles longer than the preliminary Chevron route. This difference can be attributed to the error in digitizing and georeferencing the map within GIS. The results developed by the tool were similar in length and estimated cost to the preliminary route developed by Chevron. With further information containing the as-built plans of the White Hills ice road and the final water use and cost of the road, a more thorough analysis of the performance of the tool could be performed. However, the tool performed well when comparing the results against the preliminary route developed by Chevron. These results demonstrate the ability of the tool to create routes for a planning level analysis. Using this tool an ice road planner can develop a suite of alternative routes to reach a given destination, and



evaluate those alternatives based upon projected water needs, water availability, length, and anticipated costs.

1.5 Lake Water Budget Model Results

Lake 25935 was modeled as a possible lake to be used in the White Hills case study. The environmental analysis widget in the NSDSS tool was used, and a simple water budget model workflow was used.

1-5: Lake 25935 was used as a possible lake to be used in the White Hills Case Study



Climate-change Aware Modeling

The modeling intent was set to Future, to indicate that a climate-change aware assessment was required that took into account possible changes in temperature and precipitation from 2010-2100.

The approach takes the assumption that, after suitable localization using nearby historic weather site data, the range of temperature and precipitation projected by general circulation models (GCM) is plausible, even for the coming year. As such, an ensemble of GCM models is used, each with its own temperature and precipitation projection. The projections are used as fluxes in a simple water budget model set up for the lake. Many of the projections have trends in both precipitation and temperature, as can be seen in the figure below.

1-6: Precipitation and Temperature Ensemble Projections from GCMs



Lake Storage based on Permitted Extraction

Also contained in the water budget model is an extraction term, which is governed by the current practice. For example, for lakes that don’t freeze to the bottom, the amount of extraction permitted is 15% of the under-ice volume, where the ice is assumed to be 7 feet thick.

The final term calculated by the water budget is Lake Storage, which is shown in the figure below. The figure shows that, even with extraction, the lake storage in large part increases over the century. There is considerable variability across models, however, in lake storage, some predicting large drops in storage over time if the lake is used regularly for ice road construction, and the maximum permitted extraction is made.

1-7: Ensemble Lake Storage Water Budget Model Result.



Risk Assessment to Determine Future Water Availability

To fully understand how the lake storage projections impact ice road construction, the water budget model can be used in the ice road planning tool to build risk analysis. The figure below shows the analysis for one section of the White Hills case study. The analysis shows that the water required (black line) is approximately 55M gallons. The median GCM projections of lake storage (blue line) show that the 55M gallons will always be available (since the blue line does not cross the black line). However, the driest GCM projections (red line) indicate that the 55M gallons will not be available 65% of the time.

1-8: Water Availability Risk Analysis



1.6 Lake Water Dissolved Oxygen Model Results

The environmental analyst widget was also used to create a dissolved oxygen (DO) model. Once frozen over, the DO concentration in the lake is reduced over the winter as the oxygen is depleted by lake inhabitants. Extracting water reduces the DO even more, and can have a large impact on lake health.

The DO model was constructed to understand if sufficient DO will be available. The major input to the model is temperature. To understand the full range of possible temperature in the coming season, historic temperature at a nearby site is used. The data is collapsed into an ensemble forecast for the next exploration season, as shown in the figure below.

1-9: Ensemble Temperature forecast based on historical site data.

The DO model is then calculated for the each temperature forecast, and an ensemble forecast of DO is created. The figure below shows the forecast. Note that the DO does fall over the season. It does not, however, go below 4 mg/L (horizontal line in the chart), which is considered the minimum concentration necessary to maintain healthy fish populations.



1-10: DO model results indicate the DO level will not go below the regulated minimum of 4 mg/L over the season.

1.7 Further Reading

This report provides a summary of results from the White Hills Case Study. Additional detail into the case study, as well as general white papers on water budget modeling and lake dissolved oxygen modeling can be found in the case study report on the NSDSS website at:

http://nsdss.ine.uaf.edu

Additionally, the tools used for ice road planning, water budget modeling, and dissolved oxygen modeling have been further enhanced and refined since the development of the case study. An example is the addition of an ice road schedule tool, which provides the approximate week-by-week schedule of tundra opening, ice road construction, road usage, and tundra closing. The reader is referred to the final NSDSS Design document for more details.

http://nsdss.ine.uaf.edu/docs/NSDSS_SoftwareRequirementandDesign.pdf

http://nsdss.ine.uaf.edu/

http://nsdss.ine.uaf.edu/docs/NSDSS_SoftwareRequirementandDesign.pdf



2 Case Study 2: The Road to Kavik Camp

2.1 Background As part of the third workshop of the NSDSS series, stakeholders were asked for possible case studies that could be conducted with the NSDSS tools. One of the case studies recommended was the Road to Umiat. This is a proposed permanent gravel road. It would be one of few on the North Slope. One question that arises in the design of a permanent road on the North Slope is the suitability of that road for acting as start point for ice roads. As the road is intended to become a critical part of the oil exploration process, its alignment should be as advantageous as possible to ensuring cost effective ice road construction. The Road to Umiat discussion initiated the enhancement of the NSDSS ice road planning tool with an Ice Road Landscape Suitability Analysis workflow. This workflow allows the planner to specify the alignment of the new permanent road, and then creates ice road spurs from the permanent road to end points that are a user-specified distance away from the road. The base ice road optimization algorithm is used to find the best ice road routes for each spur. The result is an array of ice roads that cover the landscape and provide an idea of the variability of ice road construction cost. NSDSS planners can use this information to better plan out their exploration strategy, and their operations during oil production.

2.2 Case Study Objectives The objectives of the case study were:

1. Test the ice road landscape suitability analysis tool with a realistic case study, similar to the Road to Umiat.

2. Identify specific lakes to use for each spur.

3. Develop understanding of cost variability along the route.

4. Develop understanding of other key ice road construction parameters.

2.3 Process The specific example used in the case study was a hypothetical road to Kavik Camp, which is approximately 50 km east from the Dalton Highway on the coastal plain of the North Slope. A qualitative survey of the land along the route was made to understand the density of lakes, length of the needed road, and so on. A proposed route for the permanent road was created.



Ice road start points were placed every 50,000 feet along the route. End points 25,000 feet from the route were established on both sides. The figure below illustrates the study set up.

2-1: Road to Kavik Camp

2.4 Landscape Suitability Analysis Results Once the route and spur start and end points were set up, the landscape suitability analysis was run. The resulting best ice road routes are shown in the figure above. The blue dots illustrate the lakes that were used for each route. As we can see, with the Coastal Plain’s relative flatness, most routes are straight-line roads. Some routes do curve, indicating they are being placed closer to the lakes they are using as source water.



The selected route also displays lake richness at the beginning and end of the route, with a scarcity of usable lakes at about the mid-way point of the route. This explains why the routes are most curved at the midway point. The figure below illustrates the top routes and associated costs for each spur. The table indicates the routes range between 5.1 miles and 6.61 miles. The costs range from $0.71M to $1.1M. The water required ranges from 11.7 M gallons to 15.1 M gallons. Finally, the average haul distance ranges substantially from 2.23 mi. to 48 mi. This large range in haul distance stems from the variability in lake density along the route. For the routes with much longer average haul distance, substantial cost and time will be required to transport water to the road for construction.

In summary, this case study demonstrates the ability of the NSDSS system to evaluate a proposed transportation corridor with respect to its suitability to support ice road development. In practice, a user might evaluate the suitability of numerous gravel road options with respect to their ability to support ice road extensions. As with the previous case study, the estimated costs of the ice roads were based upon default system values, and can be modified with more precise user-defined construction costs.

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