A Review of Metaheuristic Algorithms for Optimizing 3D Well-Path Designs

Biswas, Kallol; Vasant, Pandian; Vintaned, José Antonio Gámez; Watada, Junzo

doi:10.1007/s11831-020-09441-1

Cited by 22 publications

(10 citation statements)

References 64 publications

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“…Moreover, retention probability index HMCR has an important impact on optimality finding for HS algorithm. It has been observed that the higher number of HMCR leads to having a better probability for searching optimal solution [39]. The small value of HMCR tends to provide precise solutions, but it takes higher computational time to provide that solution.…”

Section: Harmony Search Algorithm (Hs)mentioning

confidence: 99%

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

et al. 2021

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Combinatorial optimization problems are often considered NP-hard problems in the field of decision science and the industrial revolution. As a successful transformation to tackle complex dimensional problems, metaheuristic algorithms have been implemented in a wide area of combinatorial optimization problems. Metaheuristic algorithms have been evolved and modified with respect to the problem nature since it was recommended for the first time. As there is a growing interest in incorporating necessary methods to develop metaheuristics, there is a need to rediscover the recent advancement of metaheuristics in combinatorial optimization. From the authors’ point of view, there is still a lack of comprehensive surveys on current research directions. Therefore, a substantial part of this paper is devoted to analyzing and discussing the modern age metaheuristic algorithms that gained popular use in mostly cited combinatorial optimization problems such as vehicle routing problems, traveling salesman problems, and supply chain network design problems. A survey of seven different metaheuristic algorithms (which are proposed after 2000) for combinatorial optimization problems is carried out in this study, apart from conventional metaheuristics like simulated annealing, particle swarm optimization, and tabu search. These metaheuristics have been filtered through some key factors like easy parameter handling, the scope of hybridization as well as performance efficiency. In this study, a concise description of the framework of the selected algorithm is included. Finally, a technical analysis of the recent trends of implementation is discussed, along with the impacts of algorithm modification on performance, constraint handling strategy, the handling of multi-objective situations using hybridization, and future research opportunities.

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Section: Harmony Search Algorithm (Hs)mentioning

confidence: 99%

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

et al. 2021

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“…Now, with the advancement of technologies, such as directional/horizontal drilling, the production from unconventional sources has become possible with some unwanted challenges [ 1 ]. One of the major challenges in directional / horizontal drilling is wellbore trajectory design, which is associated with cost and safety [ 2 ]. Sometimes, directional/horizontal drilling needs high expenditure, which tends to increase the oil and gas price at the consumer level.…”

Section: Introductionmentioning

confidence: 99%

“…The researchers focused on metaheuristic algorithms due to the weakness of the traditional algorithms in the large search region [ 14 , 15 ]. Among the metaheuristic algorithms, genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), artificial bee colony optimization (ABC), harmony search (HS) were utilized for well trajectory optimization [ 2 , 4 , 16 ]. To improve the issues faced by the metaheuristic algorithms and to improve the efficiency, some hybrid algorithms, for example, hybrid cuckoo search optimization (HCSO), hybrid bat flight optimization (HBFO) were introduced [ 17 – 19 ].…”

Section: Introductionmentioning

confidence: 99%

A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization

et al. 2022

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Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO’s exploration phase is enhanced, and the SHO’s hunting mechanisms are modified with PSO’s velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization.

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“…Due to the exceptional geophysical properties, the production of oil and gas from shale is not similar to that from conventional sources. Fortunately, with the advancement of technologies such as horizontal drilling and fracturing, the industry is shifting toward shale hydrocarbon production (Danso et al 2020(Danso et al , 2021Miah et al 2018;Fujian et al 2019;Biswas et al 2020Biswas et al , 2021.…”

Section: Introductionmentioning

confidence: 99%

Effects of imidazolium- and ammonium-based ionic liquids on clay swelling: experimental and simulation approach

Rahman

Negash

Danso

et al. 2021

J Petrol Explor Prod Technol

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Water-based fracturing fluids without an inhibitor promote clay swelling, which eventually creates wellbore instability. Several ionic liquids (ILs) have been studied as swelling inhibitors in recent years. The cations of the ILs are crucial to the inhibitory mechanisms that take place during hydraulic fracturing. Individual studies were carried out on several ILs with various cations, with the most frequently found being ammonium and imidazolium cations. As a result, the goal of this study is to compare these two cations to find an effective swelling inhibitor. A comparison and evaluation of the clay swelling inhibitory properties of tetramethylammonium chloride (TMACl) and 1-ethyl-3-methylimidazolium chloride (EMIMCl) were conducted in this work. Their results were also compared to a conventional inhibitor, potassium chloride (KCl), to see which performed better. The linear swelling test and the rheology test were used to determine the inhibitory performance of these compounds. Zeta potential measurements, Fourier-transform infrared spectroscopy, and contact angle measurements were carried out to experimentally explain the inhibitory mechanisms. In addition, the COSMO-RS simulation was conducted to explain the inhibitory processes and provide support for the experimental findings. The findings of the linear swelling test revealed that the swelling was reduced by 23.40% and 15.66%, respectively, after the application of TMACl and EMIMCl. The adsorption of ILs on the negatively charged clay surfaces, neutralizing the charges, as well as the lowering of the surface hydrophilicity, aided in the improvement of the swelling inhibition performance.

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A Review of Metaheuristic Algorithms for Optimizing 3D Well-Path Designs

Cited by 22 publications

References 64 publications

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization

Effects of imidazolium- and ammonium-based ionic liquids on clay swelling: experimental and simulation approach

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