A mathematical solution of optimal partition of production loops for subsea wells in the layout of daisy chains

Abstract

The daisy chain is one of the main layout types of the subsea production system in the development of deepwater oil and gas fields. The number of production loops, length of subsea pipelines, and partition of subsea wells are the main concerns in pigging loop design, pipeline laying, and flow assurance, which become important factors for the capital and operating expenditures and the risk management of deepwater fields. This article focuses on the basic optimal partition problem of production loops for subsea wells in the layout of daisy chains. It proposes to find the optimal partition method at the lowest layout cost, where a mathematical model is proposed and its dedicated algorithm is developed. Numerical simulations are conducted to evaluate the validity of the proposed model and the performance of the algorithm. The results show that the model can accurately describe the optimal partition problem of daisy chains in practice, and a mathematical solution to the optimal partition can be obtained by the algorithm programmed in MATLAB, which can provide the engineers a quantitative reference for the layout of daisy chains in engineering.

Keywords

Subsea production system daisy chain layout optimal partition mathematical model optimization algorithm

Get full access to this article

View all access options for this article.

References

Kelly

Strauss

. Agbami field development—subsea equipment systems, trees, manifolds and controls. In: Proceedings of the Offshore Technology Conference, Houston, TX, 4–7 May 2009, Offshore Technology Conference, paper no. 19919-MS.

Robinson

Grass

. Design challenges of a 48-inch pipeline subsea manifold. In: Proceedings of the Offshore Technology Conference, Houston, TX, 5–8 May 2003, Offshore Technology Conference, paper no. 15275-MS.

Lee

. Design and installation of deepwater petroleum pipelines. In: Proceedings of the World Congress of Korean and Korean ethnic scientists and engineers, Seoul, Korea, 8–13 July, 2002, Korean Federation of Science and Technology Societies.

Nengkoda

Supranto

Sulistyo

. A current mapping and predicting of Indonesian flow assurance challenges based on fluid physical characteristics. In: Proceedings of the Society of Petroleum Engineers, Jakarta, Indonesia, 20–22 September 2011, Society of Petroleum Engineers, paper no. 144639-MS.

Zhang

Bai

Badaruddin

. Quantitative risk assessment & leak detection criteria for a subsea oil export pipeline. J Mar Sci Appl 2009; 8: 168–174.

Beverley

. Surface production system options for deepwater. In: Proceedings of OMAE ’02, 21st international conference on Offshore Mechanics and Arctic Engineering, American Society of Mechanical Engineers, Oslo, 23–27 June 2002, paper no. 2002-28143, pp.277–289.

Underwood

Odina

Hansen

. Integrated subsea design: an informed and practical approach. In: Proceedings of the ASME 27th international conference on Offshore Mechanics and Arctic Engineering, Estoril, 15–20 June 2008, American Society of Mechanical Engineers, paper no. 57207-MS, pp.175–182.

Wang

Duan

. A mathematical model for subsea wells partition in the layout of cluster manifolds. Appl Ocean Res 2012; 36: 26–35.

Campozana

Almeida

Madeira

. Optimization of surface network and platform location using a next generation reservoir simulator coupled with an integrated asset optimizer—an application to an offshore deep water oil field in Brazil. In: Proceedings of the International Petroleum Technology Conference, Kuala Lumpur, Malaysia, 3–5 December 2008, paper no. 12500-MS.

10.

Park

Lim

Roh

. Production-system optimization of gas fields using hybrid fuzzy/genetic approach. SPE J 2010; 15: 417–425.

11.

Nwakile

Schulze-Riegert

Trick

. Gas field production system optimization using coupled reservoir-network simulator and optimization framework. In: Proceedings of the Society of Petroleum Engineers, Abuja, Nigeria, 30 July–3 August 2011, paper no. 150770-MS.

12.

Cormen

Leiserson

Rivest

. Introduction to algorithms. 2nd ed. The MIT Press (Cambridge, Massachusetts London, England ) and McGraw-Hill Book Company (Boston, Burr Ridge, IL Dubuque, IA Madison, WI New York, San Francisco, St. Louis, Montre’al and Toronto) 2003, pp.561–579.

13.

Fredman

Willard

. Trans-dichotomous algorithms for minimum spanning trees and shortest paths. J Comput Syst Sci 1994; 48: 533–551.

14.

Pettie

Ramachandran

. An optimal minimum spanning tree algorithm. J Assoc Comput Mach 2002; 49: 16–34.

15.

Nam

. Automatic interior space arrangement of mid-sized superyachts using a constraint-based genetic algorithm. J Mar Sci Technol 2012; 17: 481–492.

16.

Gutin

Yeo

Zverovich

. Traveling salesman should not be greedy: domination analysis of greedy-type heuristics for the TSP. Discrete Appl Math 2002; 117: 81–86.

17.

Dorigo

Gambardella

. Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE T Evolut Comput 1997; 1: 53–66.

18.

Kaveh

Sharafi

. Ant colony optimization for finding medians of weighted graphs. Eng Computation 2008; 25: 102–120.

19.

Fereidoonian

Mirzazadeh

. A genetic algorithm for the integrated scheduling model of a container-handling system in a maritime terminal. Proc IMechE, Part M: J Engineering for the Maritime Environment 2012; 226: 62–77.

20.

Naeem

Sutton

Chudley

. A genetic algorithm-based model predictive control autopilot design and its implementation in an autonomous underwater vehicle. Proc IMechE, Part M: J Engineering for the Maritime Environment 2004; 218: 175–188.

21.

Cooper

. Location-allocation problems. Oper Res 1963; 11: 331–343.

22.

Nocedal

Wright

. Numerical optimization. 2nd ed. New York: Springer Verlag, 1999.