A Stochastic Approach for Optimal Sequencing of Appraisal Wells
- Omar A. El Souki (American University of Beirut) | George A. Saad (American University of Beirut)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- May 2017
- Document Type
- Journal Paper
- 334 - 341
- 2017.Society of Petroleum Engineers
- uncertainty reduction method, seismic data, value of information, Appraisal Wells
- 2 in the last 30 days
- 303 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
The life of a hydrocarbon field can be distinguished by five main stages: exploration, appraisal, development, production, and abandonment. Of particular interest is the appraisal stage, where the use of seismic data in combination with appraisal wells permits the estimation of the initial hydrocarbons in place and the quantification of the associated uncertainties. Because of both the high prices of appraisal-well drilling and the opportunity of maximizing uncertainty reduction during the appraisal stage, optimizing on this stage makes it the biggest setting for maximizing project profitability. Nonetheless, with billions of dollars spent on appraisal activities, limited resources are spent on assessing the value of the gathered information.
This paper presents a comprehensive approach to determine the number of appraisal wells, their sequence of drilling, and their justification that is based on economic merit. The presented framework is based on sequentially coupling the uncertainty reduction method with value-of-information (VoI) techniques. Although the uncertainty-reduction method allows ranking locations of appraisal wells on the basis of the maximum uncertainty reduction that they can provide, the VoI analysis provides the difference between the value of developing the project with/without appraisal. The efficiency of the presented sequential appraisal well-location framework will be assessed by applying it on the Stratton gas-field data set.
|File Size||1 MB||Number of Pages||8|
Alves, F., Almeida, J. A., and Silva, A. P. 2014. Simulation of Acoustic Impedance Images by Stochastic Inversion of Post-Stack Seismic Reflection Amplitudes and Well Data. Journal of Petroleum Science and Engineering 121: 52–65. https://doi.org/10.1016/j.petrol.2014.06.006.
Bratvold, R. B., Bickel, J. E., and Lohne, H. P. 2009. Value of Information in the Oil and Gas Industry: Past, Present, and Future. Presented at the SPE Annual Technical Conference and Exhibition, Anaheim, California, 11–14 November. SPE-110378-PA. https://doi.org/10.2118/110378-PA.
Burdett, P. O. and Haskett, W. J. 2012. Reining In the Data Junkies—Having the Guts Not to Appraise. Presented at the SPE Hydrocarbon, Economics, and Evaluation Symposium, Calgary, 24–25 September. SPE-162903-MS. https://doi.org/10.2118/162903-MS.
Cairn Energy. 2015. Oil and Gas Exploration, and Production Life Cycle, http://www.cairnenergy.com/index.asp?pageid=554 (accessed 20 September 2015).
Coopersmith, E. M. and Cunningham, P. C. 2002. A Practical Approach To Evaluating the Value of Information and Real Option Decisions in the Upstream Petroleum Industry. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 29 September–2 October. SPE-77582-MS. https://doi.org/10.2118/77582-MS.
Cunningham, P. and Begg, S. 2008. Using the Value of Information To Determine Optimal Well Order in a Sequential Drilling Program. The American Association of Petroleum Geologists (AAPG) 92 (10): 1393–1402. https://doi.org/10.1306/06040808071.
Da Cruz, P. S. 2000. Reservoir Management Decision-Making in the Presence of Geological Uncertainty. PhD thesis, Stanford University, Stanford, California (March 2000).
Demirmen, F. 1996. Use of “Value of Information” Concept in Justification and Ranking of Subsurface Appraisal. Presented at the SPE Annual Technical Conference and Exhibition, Denver, 6–9 October. SPE-36631-MS. https://doi.org/10.2118/36631-MS.
Demirmen, F. 2001. Subsurface Appraisal: The Road From Reservoir Uncertainty to Better Economics. Presented at the SPE Hydrocarbon Economics and Evaluation Symposium, Dallas, 2–3 April. SPE-68603-MS. https://doi.org/10.2118/68603-MS.
Dikker, A. J. 1985. Geology in Petroleum Production. Amsterdam: Elsevier.
Earthworks Environment & Resources Ltd. and ARK CLS Ltd. 2010. MPSITM: Plugin to OpendTect Manual (Version 1.4).
Francis, A. M. 2006. Understanding Stochastic Inversion: Part 1. First Break 24 (11): 69–77. https://doi.org/10.3997/1365397.2006026.
Haskett, W. J. 2003. Optimal Appraisal Well Location Through Efficient Uncertainty Reduction and Value of Information Techniques. Presented at the SPE Annual Technical Conference and Exhibition, Denver, 5–8 October. SPE-84241-MS. https://doi.org/10.2118/84241-MS.
Jahn, F. 1998. Hydrocarbon Exploration and Production, first edition. Oxford: Elsevier.
Knoring, L. D., Gorfunkel, M. V., and Chilingarian, G. V. 1999. Strategies for Optimizing Petroleum Exploration: Evaluate Initial Potential and Forecast Reserves, first edition. Houston: Gulf Publishing Company.
Koninx, J. -P. M. 2000. Value-of-Information—From Cost-Cutting to Value-Creation. Presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Brisbane, Australia, 16–18 October. SPE-64390-MS. https://doi.org/10.2118/64390-MS.
Levey, R. A., Hardage, B. A., Edson, R. et al. 1994. 3D Seismic and Well Log Data Set, Fluvial Reservoir Systems, Stratton Field, South Texas. SW0003CD, Bureau of Economic Geology.
Nelson, H. R. Jr. 2001. Locating Profitable Hydrocarbon Deposits. Dynamic Resources Corporation, 7 September 2001, http://www.walden3d.com/dynamic/intro/ (accessed 18 September 2015).
Society of Petroleum Engineers. 2001. Guidelines for the Evaluation of Petroleum Reserves and Resources: A Supplement to the SPE/WPC Petroleum Reserves Definitions and the SPE/WPC/AAPG Petroleum Resources Definitions. Richardson, Texas: Society of Petroleum Engineers.
US Energy Information Administration Costs of Crude Oil and Natural Gas Wells Drilled [Online] //US Energy Information Administration. 2015a. 31 July 2015. 27 November 2015, http://www.eia.gov/dnav/ng/NG_ENR_WELLCOST_S1_A.htm.
US Energy Information Administration US Natural Gas Wellhead Price [Online]//US Energy Information Administration. 2015b. Natural-Gas Data. 30 October 2015. 27 November 2015, https://www.eia.gov/dnav/ng/hist/n9190us3m.htm.