Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms
Field experience shows that the cutting transportation and hole-cleaning phenomena are essential during the drilling phase. Particularly in directional drilling, when the accumulation of cutting has caused some drilling problems such as drill string sticking, formation failure, slow rate of penetrat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Reaserch Institute of Petroleum Industry
2022-02-01
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| Series: | Journal of Petroleum Science and Technology |
| Subjects: | |
| Online Access: | https://jpst.ripi.ir/article_1269_90ab9105c76b3cc649124a390f044201.pdf |
| _version_ | 1797893071118008320 |
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| author | Mahdi Nazari Sarem Arash Ebrahimabadi |
| author_facet | Mahdi Nazari Sarem Arash Ebrahimabadi |
| author_sort | Mahdi Nazari Sarem |
| collection | DOAJ |
| description | Field experience shows that the cutting transportation and hole-cleaning phenomena are essential during the drilling phase. Particularly in directional drilling, when the accumulation of cutting has caused some drilling problems such as drill string sticking, formation failure, slow rate of penetration, drill bit abrasion, and the like. Through the study, a novel method for efficient hole cleaning, considering different parameters such as flow rate, the drill bit nozzles’ flow area, the consistency and flow behavior indices in the same time using PSO and ACO algorithms were implemented. Moreover, Power Law has been considered for the fluid rheology model. Based on this, the research parameter shows that the PSO algorithm is much more accurate than the ACO algorithm, improving objective function by 50% and 4%, respectively. The performance of each algorithm was evaluated, and the results show that hole cleaning has been significantly improved. The flow rate and the bit nozzle size, which play key roles, were selected as optimization variables. Effective parameters on hole cleaning were evaluated, and the results before and after optimization showed a significant improvement in the model. The PSO and ACO algorithms have been coded in MATLAB software, and the results are compared to the results of the ant colony. The amount of PV and YP has an inverse effect on the increment of minimum velocity required for cutting transport. Various model analyses reveal that the PSO algorithm is more accurate and robust than the Ant colony algorithm. |
| first_indexed | 2024-04-10T06:47:04Z |
| format | Article |
| id | doaj.art-3bfc5f4ea8a34e32bda581e9aa9a6e0b |
| institution | Directory Open Access Journal |
| issn | 2251-659X 2645-3312 |
| language | English |
| last_indexed | 2024-04-10T06:47:04Z |
| publishDate | 2022-02-01 |
| publisher | Reaserch Institute of Petroleum Industry |
| record_format | Article |
| series | Journal of Petroleum Science and Technology |
| spelling | doaj.art-3bfc5f4ea8a34e32bda581e9aa9a6e0b2023-02-28T11:58:42ZengReaserch Institute of Petroleum IndustryJournal of Petroleum Science and Technology2251-659X2645-33122022-02-01121213510.22078/jpst.2022.4869.18141269Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic AlgorithmsMahdi Nazari Sarem0Arash Ebrahimabadi1Department of Petroleum, Mining and Material Engineering, Central Tehran Branch, Islamic Azad University, Tehran, IranDepartment of Petroleum, Mining and Material Engineering, Central Tehran Branch, Islamic Azad University, Tehran, IranField experience shows that the cutting transportation and hole-cleaning phenomena are essential during the drilling phase. Particularly in directional drilling, when the accumulation of cutting has caused some drilling problems such as drill string sticking, formation failure, slow rate of penetration, drill bit abrasion, and the like. Through the study, a novel method for efficient hole cleaning, considering different parameters such as flow rate, the drill bit nozzles’ flow area, the consistency and flow behavior indices in the same time using PSO and ACO algorithms were implemented. Moreover, Power Law has been considered for the fluid rheology model. Based on this, the research parameter shows that the PSO algorithm is much more accurate than the ACO algorithm, improving objective function by 50% and 4%, respectively. The performance of each algorithm was evaluated, and the results show that hole cleaning has been significantly improved. The flow rate and the bit nozzle size, which play key roles, were selected as optimization variables. Effective parameters on hole cleaning were evaluated, and the results before and after optimization showed a significant improvement in the model. The PSO and ACO algorithms have been coded in MATLAB software, and the results are compared to the results of the ant colony. The amount of PV and YP has an inverse effect on the increment of minimum velocity required for cutting transport. Various model analyses reveal that the PSO algorithm is more accurate and robust than the Ant colony algorithm.https://jpst.ripi.ir/article_1269_90ab9105c76b3cc649124a390f044201.pdfoptimizationhole cleaningcutting bed heightpso algorithmant colony algorithm |
| spellingShingle | Mahdi Nazari Sarem Arash Ebrahimabadi Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms Journal of Petroleum Science and Technology optimization hole cleaning cutting bed height pso algorithm ant colony algorithm |
| title | Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms |
| title_full | Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms |
| title_fullStr | Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms |
| title_full_unstemmed | Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms |
| title_short | Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms |
| title_sort | optimization of hole cleaning in deviated wells using metaheuristic algorithms |
| topic | optimization hole cleaning cutting bed height pso algorithm ant colony algorithm |
| url | https://jpst.ripi.ir/article_1269_90ab9105c76b3cc649124a390f044201.pdf |
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