A bilevel decomposition technique for the optimal planning of offshore platforms

Carvalho, M.C.A.; Pinto, José M.

doi:10.1590/s0104-66322006000100008

Cited by 20 publications

(8 citation statements)

References 9 publications

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“…Ramazan (2007) aggregate blocks, in a long-term production scheduling problem, to form 'fundamental trees' -minimal collections of blocks that have a positive total economic value, and can be extracted without violating slope constraints -significantly reducing the number of integer variables required in MIP formulations of such problems. Boland et al (2009) For pooling problems involving time, such as the scheduling of crude oil refineries (Shah 1996, Wenkai et al 2002, Màs and Pinto 2003, Reddy et al 2004, Bengtsson et al 2013 and the planning or design of oilfield infrastructure (Iyer and Grossmann 1998, van den Heever and Grossmann 2000, Carvalho and Pinto 2006, solution techniques are commonly hierarchical or decomposition-based in nature. Shah (1996) consider a crude oil scheduling problem in which oil arriving on ships is allocated into port tanks, piped into storage tanks at a refinery, and allocated to crude distillation units (CDUs) for processing.…”

Section: Related Workmentioning

confidence: 99%

A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

2016

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We consider the multiple time period short-term production scheduling problem for a network of multiple open-pit mines and ports. Ore produced at each mine, in each period, is transported by rail to a set of ports and blended into products for shipping. Each port forms these blends to a specification, as stipulated in contracts with downstream customers. This problem belongs to a class of multiple producer/consumer scheduling problems in which producers are able to generate a range of products, a combination of which are required by consumers to meet specified demands. In practice, short-term schedules are formed independently at each mine, tasked with achieving a grade and quality target outlined in a medium-term plan. Due to uncertainty in the data available to a medium-term planner, and the dynamics of the mining environment, such targets may not be feasible in the short-term. We present, in this paper, an algorithm in which the grade and quality targets assigned to each mine are iteratively adapted, ensuring the satisfaction of blending constraints at each port, while generating schedules for each mine that maximise resource utilisation. : 2 Management Science 00(0), pp. 000-000, c ⃝ 0000 INFORMS mine. Moreover, we describe a general class of multiple producer/consumer problems to which our solving approach can be applied, instances of which appear in a wide range of domains.The MTP-MMPP is significantly more complex than the single period MMPP solved by Blom et al. (2014). This is primarily due to the combinatorial complexity of selecting regions of material to extract across multiple time periods, and several mines -where many extraction schedules are possible -to optimise an objective that is dependent on the activity at each mine, in each period.A solution to the short-term MTP-MMPP schedules the movement of material, from available sources of ore and waste at each mine, to appropriate destinations, and the transport of ore between each mine and port, in each time period of a scheduling horizon. In the short-term, for the case study we consider in this paper, this horizon is 13 weeks long, split into weekly periods. During each time period, at each mine, ore from a variety of sources is processed and blended in a stockyard, producing ore of a specific grade and quality. Ore is reclaimed from this stockyard onto trains, railed to a port, and blended with ore from other mines to form desired products. An optimal solution to the MTP-MMPP requires coordination across mines. The grade and quality of production at each mine, in each period, must support the formation of correctly blended products at each port.In practice, short-term planning in a network of open-pit mines proceeds with the independent construction of block extraction schedules at each mine, by individual short-term planners. In this process, the short-term planner at each mine is guided by a five year, or medium-term, plan. This plan sets monthly grade and quality targets on mine production -assumed to be both achievable given the estimated com...

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Section: Related Workmentioning

confidence: 99%

A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

2016

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“…After that, several studies attempted to achieve a decrease in solution time by reformulating previous models and upgrading the solving techniques. 11,12 After some time, two studies formulated the nonlinear behavior of reservoirs in their models that was not surveyed seriously until that time. 13,14 They also attempted to improve solving techniques.…”

Section: Introductionmentioning

confidence: 99%

“…They linearized the nonlinear reservoir performance equations by piecewise linear approximations. After that, several studies attempted to achieve a decrease in solution time by reformulating previous models and upgrading the solving techniques. , After some time, two studies formulated the nonlinear behavior of reservoirs in their models that was not surveyed seriously until that time. , They also attempted to improve solving techniques. Later, uncertainty features were considered in the model by various researchers. ,,,− Uncertainty parameters that they considered in their models were demand, crude oil recoverable amounts, crude oil price, and well productivity indices and reservoirs quality.…”

Section: Introductionmentioning

confidence: 99%

Optimum Integrated Design of Crude Oil Supply Chain by a Unique Mixed Integer Nonlinear Programming Model

Azadeh

Shafiee

Yazdanparast

et al. 2017

Ind. Eng. Chem. Res.

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In this paper, a mixed integer nonlinear programming model is proposed to concurrently design two segments (i.e., upstream and midstream) of crude1 oil supply chain. The network includes all entities and their connections from oil wells to product depots. Furthermore, a real world example is applied to show the improved model application. Furthermore, a sensitivity analysis in which ±20% deviations at a time were placed on two parameters is presented. Also, model performance is analyzed with GAMS 22.6. The proposed multiperiod and multiproduct model consists of several decisions (i.e., oil field development, transformation, transportation, and distribution). The main contributions of this work are inclusion of all entities related to upstream and midstream segments and both oil field development and transformation planning, simultaneously. Finally, it is shown that a decrease in production cost of refinery products will lead to more net profit given all refinery production capacity are used. Also, increase in refinery production capacity will improve network net profit given new fixed cost investment is not applied (e.g., refineries and transportation modes). This is the first study that simultaneously considers and optimizes upstream and midstream of crude oil supply chain. Second, it presents a unique mathematical model. Third, all features and parameters are included. Fourth, it is practical and may be used for other crude oil supply chain.

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“…Ortiz-Gomez et al (2002) presented three mixed-integer multiperiod optimization models of varying complexity for the oil production planning. Carvalho and Pinto (2006a) considered an MILP formulation for oilfield planning based on the model developed by Tsarbopoulou (2000), and proposed a bilevel decomposition algorithm for solving large-scale problems where the master problem determines the assignment of platforms to wells and a planning subproblem calculates the timing for the fixed assignments. The work was further extended by Carvalho and Pinto (2006b) to consider multiple reservoirs within the model.…”

Section: Introductionmentioning

confidence: 99%

Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties

Gupta

Grossmann

2014

Journal of Petroleum Science and Engineering

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The paper presents a new optimization model and solution approach for the investment and operations planning of offshore oil and gas field infrastructure. As compared to previous models where fiscal rules and uncertainty in the field parameters are considered separately, the proposed model is the first one in the literature that includes both of these complexities in an efficient manner. In particular, a tighter formulation for the production sharing agreements is used based on our recent work, and correlation among the endogenous uncertain parameters (field size, oil deliverability, water-oil ratio and gas-oil ratio) is considered to reduce the total number of scenarios in the resulting multistage stochastic formulation. To solve large instances, a Lagangean decomposition approach allowing parallel solution of the scenario subproblems is implemented in the GAMS grid computing environment. Computational results on a variety of oilfield development planning examples are presented to illustrate the efficiency of the model and the proposed solution approach.

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A bilevel decomposition technique for the optimal planning of offshore platforms

Cited by 20 publications

References 9 publications

A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

Optimum Integrated Design of Crude Oil Supply Chain by a Unique Mixed Integer Nonlinear Programming Model

Multistage stochastic programming approach for offshore oilfield infrastructure planning under production sharing agreements and endogenous uncertainties

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