Oilfield development and operations planning under geophysical uncertainty

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Abstract

The oil and gas industry nowadays is challenged by dealing with nonconventional reserves and offshore environments. Decision-making associated with projects in the petroleum sector has to handle various technological issues, risks, and uncertainty. The Smart Fields approach was introduced to cope with complicated production conditions and make the production of hydrocarbons economically efficient. A significant part of this approach is proactive planning which implies taking into account the uncertainty, or lack of knowledge of the recoverable reserves, future hydrocarbon prices and various operational issues inherent in the projects. In this study, a multi-stage stochastic programming approach is employed to cover the relevant engineering issues of oilfield development and petroleum production while addressing the geophysical uncertainty related to the developed deposit. The proposed model covers such aspects as well drilling, gathering pipeline infrastructure planning, capacity selection for the infrastructure and the processing units, as well as planning the production operations with consideration of artificial lift efficiency. The model aims to optimise the entire field lifecycle, given the chosen planning criterion, that is an economic criterion of the project’s net present value. The contribution of the developed model to the area of planning in the petroleum industry is the detailed consideration of the technology: the flows and pressures in the planned infrastructure, reservoir behaviour, and the artificial lift performance. The goal of including these technological details is to apprehend the economic tradeoff between investments, operating costs and the prospective revenues, given the lack of knowledge of the geophysical properties of the developed deposit. The stochastic modelling implemented in this study is relevant to the development projects in nonconventional environments, where several deposits of various sizes are present; however, not each deposit's properties get to be studied in detail.

Aronofsky, J. S., & Williams, A. C. (1962). The use of linear programming and mathematical models in underground oil production. Management Science, 8(4), 394-407. doi: 10.1287/mnsc.8.4.394

Bai, Y., & Bai, Q. (2012). Subsea engineering handbook. Waltham, USA: Gulf Professional Publishing.

Bellout, M. C., Ciaurri, D. E., Durlofsky, L. J., Foss, B., & Kleppe, J. (2012). Joint optimization of oil well placement and controls. Computational Geosciences, 16(4), 1061-1079. doi: 10.1007/s10596-012-9303-5

Centrilift. (1997). Submersible pump handbook. Claremore, USA: Baker-Hughes Inc.

Cullick, S., Heath, D., Narayanan, K., April, J., & Kelly, J. (2004). Optimizing multiple-field scheduling and production strategy with reduced risk. Journal of petroleum technology, 56(11), 77-83. doi: 10.2118/88991-JPT

Dawson, R. G., & Fuller, J. D. (1999). A mixed integer nonlinear program for oilfield production planning. INFOR: Information Systems and Operational Research, 37(2), 121-140. doi: 10.1080/03155986.1999.11732375

Devine, M. D., & Lesso, W. G. (1972). Models for the minimum cost development of offshore oil fields. Management Science, 18(8), 378-387. doi: 10.1287/mnsc.18.8.B378

Frair, L., & Devine, M. (1975). Economic optimization of offshore petroleum development. Management Science, 21(12), 1370-1379. doi: 10.1287/mnsc.21.12.1370

Goel, V., & Grossmann, I. E. (2004). A stochastic programming approach to planning of offshore gas field developments under uncertainty in reserves. Computers & chemical engineering, 28(8), 1409-1429. doi: 10.1016/j.compchemeng.2003.10.005

Gupta, V., & Grossmann, I. E. (2014). Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties. Journal of Petroleum Science and Engineering, 124, 180-97. doi: 10.1016/j.petrol.2014.10.006

Haugen, K. K. (1996). A stochastic dynamic programming model for scheduling of offshore petroleum fields with resource uncertainty. European Journal of Operational Research, 88(1), 88-100. doi: 10.1016/0377-2217(94)00192-8

Iyer, R. R., Grossmann, I. E., Vasantharajan, S., & Cullick, A. S. (1998). Optimal planning and scheduling of offshore oil field infrastructure investment and operations. Industrial & Engineering Chemistry Research, 37(4), 1380-1397. doi: 10.1021/ie970532x

Jonsbråten, T. W. (1998a). Optimization models for petroleum field exploitation [PhD thesis]. Bergen, Norway: Norwegian School of Economics and Business Administration.

Jonsbråten, T. W. (1998b). Oil field optimization under price uncertainty. Journal of the operational research society, 49(8), 811-818. doi: 10.1057/palgrave.jors.2600562

Mathieson, D. (2007). Forces That Will Shape Intelligent-Wells Development. Journal of Petroleum Technology, 1(8), 14-16. doi: 10.2118/0807-0014-JPT

Redutskiy, Y. (2017a). Conceptualization of smart solutions in oil and gas industry. Procedia Computer Science, 109, 745-753. doi: 10.1016/j.procs.2017.05.435

Redutskiy, Y. (2017b). Optimization of Safety Instrumented System Design and Maintenance Frequency for Oil and Gas Industry Processes. Management and Production Engineering Review, 8(1), 46-59. doi: 10.1515/mper-2017-0006

Takács, G. (2009). Electrical submersible pumps manual: design, operations, and maintenance. Burlington, USA: Gulf professional publishing.

Tarhan, B., & Grossmann, I. E. (2008). A multistage stochastic programming approach with strategies for uncertainty reduction in the synthesis of process networks with uncertain yields. Computers & Chemical Engineering, 32(4), 766-788. doi: 10.1016/j.compchemeng.2007.03.003

Tarhan, B., Grossmann, I. E., & Goel, V. (2009). Stochastic programming approach for the planning of offshore oil or gas field infrastructure under decision-dependent uncertainty. Industrial & Engineering Chemistry Research, 48(6), 3078-3097. doi: 10.1021/ie8013549

Van den Heever, S. A., Grossmann, I. E., Vasantharajan, S., & Edwards, K. (2001). A Lagrangean decomposition heuristic for the design and planning of offshore hydrocarbon field infrastructures with complex economic objectives. Industrial & Engineering Chemistry Research. 40(13), 2857-2875. doi: 10.1016/j.compchemeng.2011.03.026

Wang, P., Litvak, M., & Aziz, K. (2002). Optimization of Production Operations in Petroleum Fields. Society of Petroleum Engineers, 77658, 1-12. doi: 10.2118/77658-MS

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