Regressions allow development of compressor cost estimation models

Jan. 9, 2012

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Limitations, suggestion

Data used in this article included a large number of compressor stations built between 1992 and 2008. But some regions, such as the Midwest, still have relatively few pipelines. Among all compressor stations, 57% have capacities less than 8,000 hp, and only 2.73% are more than 40,000 hp.1 Uneven distribution and a limited number of compressor stations with large capacities may cause estimation biases.

An unknown starting year and unknown construction period cause a biased cost by adjusting along with the chemical plant index. US natural gas pipelines’ region definitions are based on federal regions of the US Bureau of Labor Statistics. Other region definitions, however, may be better for the distribution of US compressor stations.

The lack of some variables that produce cost differences, such as types of compressors and terrain, prevents conducting certain quantitative analyses. Missing data also include type of compressor station ownership: private or public.

Future work should collect more observations with more detailed information on the missing variables to improve the effectiveness of the cost estimation models.

References

1. Rui, Z., Metz, A.P., Chen, G., Zhou, X., and Wang, X., "US Pipeline Compressor Station Cost Analysis," internal report, University of Alaska Fairbanks, 2011.

2. IEA Greenhouse Gas R&D Programme, "Transmission of CO2 and Energy," Report No. PH4/6, 2002.

3. Oil & Gas Journal Databook, Tulsa: PennWell Corp., 1992-2010.

4. Chemical Engineering, Plant Cost Index, http://www.che.com/pci, accessed July 2010.

5. Energy Information Administration, http://www.eia.doe.gov, accessed July 2010.

6. McCoy, S.T., and Rubin, E.S., "An Engineering-Economic Model of Pipeline Transport of CO2 with Application to Carbon Capture and Storage," International Journal of Greenhouse Gas Control, Vol. 2, No. 2, pp. 219-29, 2008.

7. UCLA, "Regression with Stata," http://www.ats.ucla.edu/stat/stata/webbooks/reg/chapter2/statareg2.htm, accessed July 2010.

8. Rui, Z., Metz, A.P., Reynolds, B.D., and Chen, G., "An Analysis of Inaccuracy in Pipeline Construction Cost Estimation," International Journal of Oil, Gas and Coal Technology, Vo. 5, No. 1, pp. 29-46, 2012.

9. Markridakis, S.G., Wheelright, S.C., and McGee, V., "Forecasting, Methods and Applications," New York: Wiley, 1983.

10. Neter, J., Kutner, M., and Nachtsheim, C., "Applied Linear Statistical Models," New York: McGraw-Hill, 1996.

11. Wilkinson, N., "Managerial Economics: A Problem-solving Approach," Cambridge University Press, 2005.

12. Bordat, C., McCullouch, B., Sinha, K., and Labi, S., "An Analysis of Cost Overruns and Time Delays of INDOT Projects," Joint Transportation Research Program, Paper No. 11, 2004.

13. Interstate Natural Gas Association of America (INGAA), "Interstate Natural Gas Pipeline Efficiency," 2010.

The authors

Zhenhua Rui ([email protected]) is a research analyst at Independent Project Analysis Inc. He earned a PhD in energy engineering management, an MBA, and an MS in petroleum engineering from the University of Alaska Fairbanks. He also holds an MS in geophysics from China University of Petroleum, Beijing. He is a member of the Society of Petroleum Engineers and International Association of Energy Economics .
Paul A. Metz ([email protected]) is a professor of geological engineering at the department of mining and geological engineering of UAF. He received his PhD from Imperial College of Science Technology and Medicine, London.
Gang Chen ([email protected]) is a professor of mining engineering at the department of mining and geological engineering of the University of Alaska Fairbanks. He received his PhD in mining engineering from Virginia Polytechnic Institute and State University, Blacksburg, Va. He is a member of the Society of Mining, Metallurgy & Exploration.
Xiyu Zhou ([email protected]) is an associate professor of finance at the school of management of the University of Alaska Fairbanks. He received his PhD of business administration (finance) from the University of North Carolina. He is a member of the American Finance Association.
Xiaoqing Wang ([email protected]) is an MBA candidate in capital markets at the school of management of UAF. She holds a BS in design from Tianjin University of Science and Technology, China. She is a member of Students Who Enjoy Economic Thinking.

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