An insightful multicriteria model for the selection of drilling technique for heat extraction from geothermal reservoirs using a fuzzy-rough approach

被引:0
|
作者
Sandra, Michael [1 ]
Narayanamoorthy, Samayan [1 ]
Suvitha, Krishnan [1 ]
Pamucar, Dragan [2 ,3 ,4 ]
Simic, Vladimir [5 ,6 ]
Kang, Daekook [7 ]
机构
[1] Bharathiar Univ, Dept Math, Coimbatore 641046, India
[2] Szecheny Istvan Univ, Gyor, Hungary
[3] Univ Belgrade, Fac Org Sci, Dept Operat Res & Stat, Belgrade, Serbia
[4] Western Caspian Univ, Dept Mech & Math, Baku, Azerbaijan
[5] Univ Belgrade, Fac Transport & Traff Engn, Vojvode Stepe 305, Belgrade 11010, Serbia
[6] Korea Univ, Coll Informat, Dept Comp Sci & Engn, 145 Anam Ro, Seoul 02841, South Korea
[7] Inje Univ, Inst Digital Antiaging Hlth care, Dept Ind & Management Engn, 197 Inje Ro, Gimhae 50834, Gyeongsangnam, South Korea
基金
新加坡国家研究基金会;
关键词
Decision making; Fuzzy rough sets; Drilling techniques; Geothermal energy; Ranking alternatives with weights of criterion; ENERGY; MCDM; RESOURCES;
D O I
10.1016/j.ins.2024.121353
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Geothermal energy stands out as an exceptional renewable resource for power generation, offering a consistent power production without the intermittency issues. Despite its potential to deliver a consistent supply of electricity on demand, geothermal adoption is hindered due to substantial costs. Utilising the most effective drilling method can alleviate this challenge by boosting efficiency and reducing operational costs. The primary goal of this study is to identify the best drilling method for extracting heat from geothermal reservoirs. This optimised approach facilitates better access to geothermal reservoirs, leading to increased heat recovery rates and improved project viability. Traditional methods often fall short in evaluating optimal drilling alternatives due to uncertainties. To address this, our research introduces an innovative paradigm that integrates novel T-Spherical Hesitant Fuzzy Rough (T - SHFR) set, method for the removal effects of criteria with a geometric mean and ranking alternatives with weights of criterion hybrid Multiple Criteria Decision-Making (MCDM) techniques. By leveraging the novel T - SHFR concept, our approach allows for a comprehensive assessment of various factors. This holistic evaluation ensures an exhaustive comprehension of the decision-making environment. The study reveals that reservoir characteristics play a significant role in selecting a sustainable drilling alternative. Furthermore, directional drilling appears as the most promising method with higher energy yields followed by slim hole drilling. The robustness and credibility of these findings are established through sensitivity and comparative analyses, indicating the potential applicability of this MCDM method to analogous challenges in different contexts. The findings of the ranking techniques were validated using Spearman's rank correlation coefficient, which revealed a positive and notable correlation. This research will empower stakeholders to make informed decisions, thereby enhancing the overall efficiency and sustainability of geothermal energy projects.
引用
下载
收藏
页数:18
相关论文
共 14 条
  • [1] Optimal selection of healthcare waste treatment devices using fuzzy-rough approach
    Puska, Adis
    Stilic, Andelka
    Pamucar, Dragan
    Simic, Vladimir
    Petrovic, Natasa
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2024,
  • [2] Simultaneous feature extraction and selection of microarray data using fuzzy-rough based multiobjective nonnegative matrix factorization
    Abd Elaziz, Mohamed E.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 33 (06) : 4043 - 4053
  • [3] A novel radial jet drilling stimulation technique for enhancing heat recovery from fractured geothermal reservoirs
    Salimzadeh, S.
    Grandahl, M.
    Medetbekova, M.
    Nick, H. M.
    RENEWABLE ENERGY, 2019, 139 : 395 - 409
  • [4] Feature Selection from Protein Primary Sequence Database using Enhanced QuickReduct Fuzzy-Rough Set
    Chandran, C. P.
    2008 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, VOLS 1 AND 2, 2008, : 111 - 114
  • [5] Enhanced Prediction for Piezophilic Protein by Incorporating Reduced Set of Amino Acids Using Fuzzy-Rough Feature Selection Technique Followed by SMOTE
    Tiwari, Anoop Kumar
    Shreevastava, Shivam
    Subbiah, Karthikeyan
    Som, Tanmoy
    MATHEMATICS AND COMPUTING (ICMC 2018), 2018, 253 : 185 - 196
  • [6] PHOTOVOLTAICS TYPE SELECTION USING A PROJECTION MODEL-BASED APPROACH TO INTUITIONISTIC FUZZY MULTICRITERIA DECISION MAKING
    Kahraman, Cengiz
    Oztaysi, Basar
    Onar, Sezi Cevik
    UNCERTAINTY MODELLING IN KNOWLEDGE ENGINEERING AND DECISION MAKING, 2016, 10 : 924 - 929
  • [7] A novel entropy-based weighted attribute selection in enhanced multicriteria decision-making using fuzzy TOPSIS model for hesitant fuzzy rough environment
    Archana Dikshit-Ratnaparkhi
    Dattatraya Bormane
    Rajesh Ghongade
    Complex & Intelligent Systems, 2021, 7 : 1785 - 1796
  • [8] A novel entropy-based weighted attribute selection in enhanced multicriteria decision-making using fuzzy TOPSIS model for hesitant fuzzy rough environment
    Dikshit-Ratnaparkhi, Archana
    Bormane, Dattatraya
    Ghongade, Rajesh
    COMPLEX & INTELLIGENT SYSTEMS, 2021, 7 (04) : 1785 - 1796
  • [9] Effects of pore water-rock reaction on heat extraction from the karst geothermal reservoirs: Based on the dual media model
    Ji, Jiayan
    Song, Xianzhi
    Yi, Junlin
    Song, Guofeng
    Wang, Gaosheng
    ENERGY, 2024, 293
  • [10] Enhanced prediction of anti-tubercular peptides from sequence information using divergence measure-based intuitionistic fuzzy-rough feature selection
    Pankhuri Jain
    Anoop Kumar Tiwari
    Tanmoy Som
    Soft Computing, 2021, 25 : 3065 - 3086