IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v41y2014i5p1105-1121.html
   My bibliography  Save this article

Selection of the best well control system by using fuzzy multiple-attribute decision-making methods

Author

Listed:
  • S. Mostafa Mokhtari
  • Hamid Alinejad-Rokny
  • Hossein Jalalifar

Abstract

There are numerous difficulties involved in drilling operations of an oil well, one of the most important of them being well control. Well control systems are applied when we have irruption of liquids or unwanted intrusion of the reservoir's liquid (oil, gas or brine) into the well, during drilling when the pressure of well fluid column is less than formation pressure, and the permeability of the reservoir has a value that is able to pass the liquid through. For this purpose, a variety of methods including Driller, wait and weight, and the concurrent methods were used to control the well at different drilling sites. In this study, we investigate the optimum method for well control using a fussy method based on many parameters, including technical factors (mud weight, drilling rate, blockage of pipes, sensitivity to drilling network changes, etc.) and security factors (existence of effervescent mud, drilling circuit control, etc.), and cost of selection, which is one of the most important decisions that are made under critical conditions such as irruption. Till now, these methods were selected based on the experience of field personnel in drilling sites. The technical criteria and standards were influenced by experience, so the soft computerizing system (fuzzy method) was used. Thus, both these criteria and standards would be of greater importance and indicate whether the optimum numerical method is the same one that is expressed by human experience. The concurrent method was selected as the best for well control, using the fuzzy method at the end of the evaluation, while field personnel experience suggests the Driller method.

Suggested Citation

  • S. Mostafa Mokhtari & Hamid Alinejad-Rokny & Hossein Jalalifar, 2014. "Selection of the best well control system by using fuzzy multiple-attribute decision-making methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(5), pages 1105-1121, May.
  • Handle: RePEc:taf:japsta:v:41:y:2014:i:5:p:1105-1121
    DOI: 10.1080/02664763.2013.862218
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2013.862218
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2013.862218?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liang, Gin-Shuh, 1999. "Fuzzy MCDM based on ideal and anti-ideal concepts," European Journal of Operational Research, Elsevier, vol. 112(3), pages 682-691, February.
    2. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
    3. Tsung-Yu Chou & Gin-Shuh Liang, 2001. "Application of a fuzzy multi-criteria decision-making model for shipping company performance evaluation," Maritime Policy & Management, Taylor & Francis Journals, vol. 28(4), pages 375-392, October.
    4. Büyüközkan, Gülçin & Feyzioglu, Orhan & Nebol, Erdal, 2008. "Selection of the strategic alliance partner in logistics value chain," International Journal of Production Economics, Elsevier, vol. 113(1), pages 148-158, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Singh, Amritpal & Vats, Gaurav & Khanduja, Dinesh, 2016. "Exploring tapping potential of solar energy: Prioritization of Indian states," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 397-406.
    2. Tonghui Lian & Caihua Yu & Zhongqun Wang & Zhiping Hou, 2017. "The evaluation study on tourism websites: from the perspective of triangular intuitionistic fuzzy multiple attribute group decision making," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(16), pages 2877-2889, December.
    3. Oguzhan Ece & Ahmet Serhat Uludag, 2017. "Applicability of Fuzzy TOPSIS Method in Optimal Portfolio Selection and an Application in BIST," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(10), pages 107-127, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alaa Alden Al Mohamed & Sobhi Al Mohamed & Moustafa Zino, 2023. "Application of fuzzy multicriteria decision-making model in selecting pandemic hospital site," Future Business Journal, Springer, vol. 9(1), pages 1-22, December.
    2. Sanja Puzović & Jasmina Vesić Vasović & Dragan D. Milanović & Vladan Paunović, 2023. "A Hybrid Fuzzy MCDM Approach to Open Innovation Partner Evaluation," Mathematics, MDPI, vol. 11(14), pages 1-26, July.
    3. Awasthi, Anjali & Chauhan, Satyaveer S. & Goyal, S.K., 2010. "A fuzzy multicriteria approach for evaluating environmental performance of suppliers," International Journal of Production Economics, Elsevier, vol. 126(2), pages 370-378, August.
    4. Wei Zhang & Qingpu Zhang, 2014. "Multi-stage evaluation and selection in the formation process of complex creative solution," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2375-2404, September.
    5. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    6. Ajripour Iman, 2022. "Supplier Selection during the COVID-19 Pandemic Situation by Applying Fuzzy TOPSIS: A Case Study," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 10(1), pages 91-105, September.
    7. Rajak, Manindra & Shaw, Krishnendu, 2019. "Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS," Technology in Society, Elsevier, vol. 59(C).
    8. Bouzon, Marina & Govindan, Kannan & Rodriguez, Carlos M.Taboada & Campos, Lucila M.S., 2016. "Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 182-197.
    9. Pandey, Mukesh Mohan, 2020. "Evaluating the strategic design parameters of airports in Thailand to meet service expectations of Low-Cost Airlines using the Fuzzy-based QFD method," Journal of Air Transport Management, Elsevier, vol. 82(C).
    10. Shuang Yao & Donghua Yu & Yan Song & Hao Yao & Yuzhen Hu & Benhai Guo, 2018. "Dry Bulk Carrier Investment Selection through a Dual Group Decision Fusing Mechanism in the Green Supply Chain," Sustainability, MDPI, vol. 10(12), pages 1-19, November.
    11. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    12. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    13. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang & Chen-Ming Lu, 2021. "A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    14. V. Alpagut Yavuz, 2016. "An Analysis of Job Change Decision Using a Hybrid Mcdm Method: A Comparative Analysis," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 6(3), pages 60-75, March.
    15. Caetani, Alberto Pavlick & Ferreira, Luciano & Borenstein, Denis, 2016. "Development of an integrated decision-making method for an oil refinery restructuring in Brazil," Energy, Elsevier, vol. 111(C), pages 197-210.
    16. Ram Avtar & Netrananda Sahu & Ashwani Kumar Aggarwal & Shamik Chakraborty & Ali Kharrazi & Ali P. Yunus & Jie Dou & Tonni Agustiono Kurniawan, 2019. "Exploring Renewable Energy Resources Using Remote Sensing and GIS—A Review," Resources, MDPI, vol. 8(3), pages 1-23, August.
    17. Lupo, Toni, 2015. "Fuzzy ServPerf model combined with ELECTRE III to comparatively evaluate service quality of international airports in Sicily," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 249-259.
    18. Alaa Alden Al Mohamed & Sobhi Al Mohamed, 2023. "Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap," Future Business Journal, Springer, vol. 9(1), pages 1-20, December.
    19. Kannan, Devika & Jabbour, Ana Beatriz Lopes de Sousa & Jabbour, Charbel José Chiappetta, 2014. "Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company," European Journal of Operational Research, Elsevier, vol. 233(2), pages 432-447.
    20. Wang, Xiaojun & Chan, Hing Kai & Li, Dong, 2015. "A case study of an integrated fuzzy methodology for green product development," European Journal of Operational Research, Elsevier, vol. 241(1), pages 212-223.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:41:y:2014:i:5:p:1105-1121. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.