Historical data provide low-cost estimating tool

Nov. 20, 2006
Historical data can help develop surrogate cost estimates for pipeline construction, potentially replacing a more costly full engineering study.

Historical data can help develop surrogate cost estimates for pipeline construction, potentially replacing a more costly full engineering study.

A complete engineering package likely provides the best cost estimate, but such packages are expensive and sometimes this investment is unwarranted. And even with such an effort, construction surprises, delays, and shortages of materials or labor can still add unexpected costs.

Uncertainty surrounds any advance estimate of pipeline construction costs. But the ability to calculate reasonably accurate cost estimates for large pipeline projects without the cost of an engineering effort can help in decision making both in terms of policy and regulatory processes. Such calculations may also serve as a screening criterion for prospective projects. Table 1 provides publicly available cost estimates for a variety of currently discussed pipeline projects.

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The database of natural gas pipeline construction-permit application filings of the US Federal Energy Regulatory Commission (FERC) provides a useful source of both historical and forecast data. Rigorous engineering efforts typically provide the basis for these filings, making them usable for deriving average estimates of construction costs and providing a basis for cost projection of future pipeline projects.

These data provided the basis for a surrogate to estimate construction costs for large-diameter natural gas pipelines. Recent filings have the added benefit of capturing recent trends in construction costs. The structure of construction costs, however, can evolve rapidly. Preconstruction filing data can also differ from actual costs.

Nevertheless, the technique, though fairly simple, yields accurate cost estimates when compared with actual costs of proposed international pipelines.

Onshore construction cost

US FERC construction permit applications from July 1, 2004, and June 30, 2005 (OGJ, Sept. 12, 2005, p. 50), provide the basis for developing a simple approach to estimating natural gas pipeline-construction costs. Using a subset of onshore pipelines with nominal OD greater than or equal to 30 in. avoids including modeling biases from small-diameter natural gas pipelines when developing a model for large natural gas pipelines with high flow rates and great lengths.

Fig. 1 shows the construction costs per mile of natural gas pipeline inferred from the OGJ data.

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CEE separated the construction costs into three groups: high project costs, mean project costs, and low project costs, using the data set’s maximum, mean, and minimum values for each diameter. Fig. 2’s three lines represent high, mean, and low project cost estimates.

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The high-cost line captures projects that were affected by higher material costs, more expensive rights-of-way (ROW), higher construction costs, or other factors. Some or all of these variables could reflect environmentally sensitive locations along the pipeline route or related conditions that affect pipeline approvals and development.

Per-mile natural gas pipeline costs increase in near linear fashion with pipeline diameter. This near-linear relationship, at least within the range of diameters (and projects) used, indicates that pipeline diameter is an appropriate scaling factor for total costs.

The data represent total costs. A model could also break pipeline project costs into different categories (materials, rights-of-way, labor, etc.) and then scale these according to specific models. The good correlation of total costs to OD implies that discrete costs can be assumed to scale similarly with the same variables (pipeline length and pipeline diameter) and that any discrepancies cancel each other out, save for exceptional situations.

Cost analogs

The historical data model must address the applicability of continental US data from FERC filings to other projects, including those of different scales. CEE compared model-estimated pipeline costs for a series of analog pipelines presented in Table 2 and also included for visual reference in Fig. 3. Projects that cross international boundaries, traverse complicated terrains, or are subject to severe-weather environments tend to lie near the high-cost project limit.

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This set of guidelines provided the basis for an estimate of the construction cost of the proposed Great Southern Gas Pipeline, running from Venezuela to Argentina. Publicly available cost estimates fall short of our estimated costs, given that the pipeline would go through extremely environmentally sensitive areas.

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Projects being constructed using existing rights of way or that do not have to be built in environmentally sensitive or physically challenging areas tend to fall in the mean cost estimate (e.g., the Rockies Express Pipeline LLC project).

Alaska pipeline

Using the agreement between the model and the different reported cost estimates for large pipelines, CEE applied the model to estimate the cost of the proposed Trans-Alaska Gas Pipeline. In May 2006, Alaska’s Department of Revenue published its Preliminary Findings and Estimations, which included $18.4 billion for the pipeline portion of the project.

The pipeline can be divided into two segments, one from Prudhoe Bay to Alberta (2,140 miles) and one from Alberta to Chicago (1,500 miles). The pipeline also crosses different environments. The segment from Prudhoe Bay to Alberta would be the first natural gas pipeline constructed along that right-of-way. It would most likely also use new materials and be subject to strict environmental construction limitations, such as limited schedules in periods of melting permafrost.

Based on these observations, CEE suggests that the high-cost model be used for the stretch from Alaska to Alberta (Table 3).

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Significant pipeline networks, however, are operating in or near the proposed Alberta-to-Chicago natural gas pipeline right-of-way. If the high-cost model is used for the Alaska-to-Alberta segment, there may be opportunities for cost reduction in the Alberta-to-Chicago leg.

Several options currently under consideration include the use of significant portions of existing infrastructure. Even where existing pipeline cannot be used, however, both the breadth of the region’s network and lessons learned from laying the existing pipe can be applied to obtain costs closer to that of the mean-cost model (Table 4).

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CEE used functions for the high and mean construction costs to estimate the construction cost of the proposed 52-in. pipeline. The model predictions can serve as a guide for the overall construction cost of the pipeline, given that different segments will most likely have different per mile costs.

Uncertainty, overruns

Uncertainty in material costs, labor costs, project time lines, and, in general, the risk of cost overruns must all be considered when evaluating the economics of a major pipeline project.

Because projects as large as the Alaska natural gas pipeline are few, a track record of cost estimation and actual construction costs is not readily available. Other pipeline projects, however, can serve as analogs for estimating the potential for and extent of cost overruns. For example, the BP-operated Baku-Tbilisi-Ceyhan pipeline cost nearly $3 billion. Cost overruns totaled an estimated $1 billion, or 33% of the overall project cost.

Costs for the Shell-led Sakhalin Energy Investment Co. Ltd.’s Sakhalin II project, with similar weather conditions to Alaska (but also with offshore upstream facilities), have grown to an estimated $20 billion from $10 billion: a 100% cost overrun. Many other examples of mega-projects exist with considerable cost overruns.

It is doubtful costs for the Alaska natural gas pipeline can fall below the mean estimated cost example. Cost overruns, however, have no predefined limit other than those set in advance by the developers.

No construction-cost reduction is expected, apart from those inherent in the Alberta-to-Chicago segment. It is also unlikely that all cost-reduction opportunities will be captured, creating a hard lower bound for the total cost estimate of $18.1 billion (Table 5).

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The most probable construction cost is that shown by the mean-construction-cost model: $20.3 billion. But cost-overrun probabilities for the Alaska-to-Alberta portion are high and could have a significant impact.

Further testing with actual pipeline cost data should be performed to fully calibrate our technique. Comparison with older but comparable data sets could also be done to develop cost-escalation models.

The construction-cost models illustrated here by FERC data can provide estimates of natural gas pipeline costs in other regions of the world, so long as the distinction can be made between challenging and higher cost projects and more routine pipeline projects, suggesting that the cost structure for large natural gas pipeline projects reflects global (rather than regional or local) prices of materials, engineering and construction, capital, and other variables, especially for the largest projects.

The authors

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Mariano E. Gurfinkel ([email protected]) is associate head of the Center for Energy Economics of the Bureau of Economic Geology, University of Texas at Austin. His main area of interest is the development and implementation of technology for unconventional resources, with special focus on heavy oil. Before joining CEE, Gurfinkel was responsible for the establishment of the Center for Energy and Technology of the Americas with support of the Department of Energy. Prior to CETA, Gurfinkel led technology development efforts on heavy oil at the research and development center of PDVSA. He holds PhD and MS degrees in mechanical engineering from the Massachusetts Institute of Technology and a BS degree with honors in mechanical engineering from Universidad Simon Bolivar, Venezuela.

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Gürcan Gülen ([email protected]) is a senior energy economist at the CEE. Gülen co-manages a five-year cooperative agreement with the USAID, focusing on capacity building in energy sectors of emerging economies in Africa. He also directs content development for the New Era in Oil, Gas & Power Value Creation, CEE’s international capacity building program. He served as an officer in both the Houston and National Chapters of the International Association for Energy Economics. He received a PhD in economics from Boston College and a BA in economics from Bosphorus University in Istanbul, Turkey.

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Dmitry Volkov ([email protected]) joined the CEE in October 2003. Volkov is involved in various research projects, including LNG and carbon sequestration value chains, as well as studies of FSU energy sector development and international energy data systems. He is an active member of the Association of International Petroleum Negotiators (AIPN). Volkov holds degrees from University of Houston (MBA, accounting and finance) and Moscow State University, Institute of Asian and African studies (BS, Arabic studies and history).

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Michelle Michot Foss ([email protected]) is chief energy economist and head of the CEE. She directs and conducts research on energy fuels, markets, infrastructure and associated investment frameworks; advises US and international energy companies; publishes and speaks widely on energy issues; and provides public commentary and government testimonies. Previously, she was a director of research at the investment bank Simmons & Co.; director of research at Rice Center, an urban regional economics, energy, and transportation research group; and was engaged in Denver-based energy and environmental research and consulting. Michot Foss is a member of the Council on Foreign Relations, AIPN, USAEE/IAEE, Women’s Energy Network, and a partner in Harvest Gas Management, a Texas-based exploration company. Michot Foss holds a PhD in political science from the University of Houston, an MS in economics from the Colorado School of Mines, and a BS in biology, with a geology minor, from the University of Louisiana-Lafayette.