Well placement optimization subject to realistic field development constraints

Jesmani, Mansoureh; Bellout, Mathias C.; Hanea, R.G.; Foss, Bjarne A.

doi:10.1007/s10596-016-9584-1

Cited by 50 publications

(15 citation statements)

References 44 publications

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“…Nonlinear constraints, if any, can be handled by some constraint handling methods. In [34], two different constraint handling methods are coupled with the PSO algorithm. In addition, note that the optimality of the Pareto solutions can be checked by perturbing the optimization parameters and comparing the obtained objective function.…”

Section: Remarkmentioning

confidence: 99%

Locomotion Efficiency Optimization of Biologically Inspired Snake Robots

Kelasidi

Jesmani²,

Pettersen

et al. 2018

Applied Sciences

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Snake robots constitute bio-inspired solutions that have been studied due to their ability to move in challenging environments where other types of robots, such as wheeled or legged robots, usually fail. In this paper, we consider both land-based and swimming snake robots. One of the principal concerns of the bio-inspired snake robots is to increase the motion efficiency in terms of the forward speed by improving the locomotion methods. Furthermore, energy efficiency becomes a crucial challenge for this type of robots due to the importance of long-term autonomy of these systems. In this paper, we take into account both the minimization of the power consumption and the maximization of the achieved forward velocity in order to investigate the optimal gait parameters for bio-inspired snake robots using lateral undulation and eel-like motion patterns. We furthermore consider possible negative work effects in the calculation of average power consumption of underwater snake robots. To solve the multi-objective optimization problem, we propose transforming the two objective functions into a single one using a weighted-sum method. For different set of weight factors, Particle Swarm Optimization is applied and a set of optimal points is consequently obtained. Pareto fronts or trade-off curves are illustrated for both land-based and swimming snake robots with different numbers of links. Pareto fronts represent trade-offs between the objective functions. For example, how increasing the forward velocity results in increasing power consumption. Therefore, these curves are a very useful tool for the control and design of snake robots. The trade-off curve thus constitutes a very useful tool for both the control and design of bio-inspired snake robots. In particular, the operators or designers of bio-inspired snake robots can choose a Pareto optimal point based on the trade-off curve, given the preferred number of links on the robot. The optimal gait parameters for the robot control system design are then directly given both for land-based and underwater snake robots. Moreover, we are able to obtain some observations about the optimal values of the gait parameters, which provide very important insights for future control design of bio-inspired snake robots.

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Section: Remarkmentioning

confidence: 99%

Locomotion Efficiency Optimization of Biologically Inspired Snake Robots

Kelasidi

Jesmani²,

Pettersen

et al. 2018

Applied Sciences

Self Cite

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“…Although some of them are adjoint-based (Wang et al 2007;Zandvliet et al 2008a;Sarma and Chen 2008;Vlemmix et al 2009), the most effective techniques use 'non-classical' methods such as genetic algorithms, particle swarm optimization or evolutionary strategies (e.g. Güyagüler et al 2002;Yeten et al 2003;Bangerth, 2006;Owunalu and Durlofsky, 2010, Bouzarkouna et al 2012Forouzanfar et al 2013b, Jesmani et al 2016. There is also an increasing number of studies involving the joint optimization of well controls and locations (e.g.…”

Section: Application Case Reservoir Engineering -Long-term Reservoir mentioning

confidence: 99%

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

Benndorf

2017

Math Geosci

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Advanced data acquisition and process modelling technology provide 'real-time' data and decision support capacity for different aspects of the resource extraction process. Closed-loop approaches have recently been applied to utilize information extracted from these data in combination with advanced computing technology for improved production control in mineral resource extraction. Similar techniques have been developed in the petroleum industry combining computer-assisted model updating with model-based production optimization. This contribution reviews recent developments and methods applied, highlights differences and assesses the potential value added for both application domains. The focus here is on the two main constituents of closed-loop concepts, data assimilation and optimization. Technological readiness of the constituents is assessed, and gaps for further technology development are identified. The value added is illustrated by means of selected cases. Key Wordsclosed-loop reservoir management, real-time mining, data assimilation, optimization Published as Benndorf, J. and Jansen, J.D., 2017: Recent developments in closed-loop approaches for realtime mining and petroleum extraction. Mathematical Geosciences 49 (3) 277-306.

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“…Minimum inter-well distance constraint has been studied in many researches (Awotunde and Naranjo 2014;Jesmani et al 2016;Zhang et al 2017). According to the minimum distance between two line segments, the minimum interwell distance Dis well can be obtained.…”

Section: Optimization Model Based On Theil Indexmentioning

confidence: 99%

“…This method made sure that most regions of the reservoir could be swept. Jesmani et al (2016) analyzed the optimal well placement according to the time of flight. The optimal well locations in their research could obtain an even time of flight in each injection-production line.…”

Section: Introductionmentioning

confidence: 99%

Well placement optimization for offshore oilfield based on Theil index and differential evolution algorithm

Chen

Feng

Zhang

et al. 2017

J Petrol Explor Prod Technol

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Proper well placement should match the heterogeneity of reservoir and development schedule, in which case the displacement is balanced. A balanced displacement process can achieve a good development performance of reservoir. Present parameters to evaluate the displacement balanced degree are not fit for high water-cut oilfields and need a specific reservoir simulator. In this work, a well placement optimization method for offshore oilfield is established. A displacement balanced degree evaluation method is proposed based on Theil index. By using minimum Theil index as the objective function, well placement optimization model for offshore oilfield is built. In this model, constraints about the available infilling scope and minimum inter-well distance are considered to find the realizable optimal location. This optimization model is solved by a derivative-free optimization algorithm, differential evolution algorithm. This method is applied and validated in a semisynthetic offshore oilfield to find optimal well locations. Results demonstrate that this proposed method can find the optimal well placement for offshore oilfield to achieve a more balanced displacement and a higher oil recovery.

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Well placement optimization subject to realistic field development constraints

Cited by 50 publications

References 44 publications

Locomotion Efficiency Optimization of Biologically Inspired Snake Robots

Locomotion Efficiency Optimization of Biologically Inspired Snake Robots

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

Well placement optimization for offshore oilfield based on Theil index and differential evolution algorithm

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