Robust prediction for CH4/CO2 competitive adsorption by genetic algorithm pruned neural network

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Published inGeoenergy Science and Engineering Vol. 234; p. 212618
Main Authors Wang, Hai, Pang, Yu, Chen, Shengnan, Wang, Muming, Hui, Gang
Format Journal Article
LanguageEnglish
Published 01.03.2024
Online AccessGet full text
ISSN2949-8910
2949-8910
DOI10.1016/j.geoen.2023.212618

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ArticleNumber 212618
Author Wang, Hai
Hui, Gang
Chen, Shengnan
Pang, Yu
Wang, Muming
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10.3390/s21196410
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10.1016/j.jngse.2021.104045
10.1016/0893-6080(89)90020-8
10.1023/A:1010933404324
10.1016/j.juogr.2016.02.003
10.1016/j.petrol.2017.03.017
10.3390/en15072548
10.1016/j.fuel.2020.118358
10.1088/0957-0233/15/5/010
10.1016/j.eml.2016.05.014
10.1007/s11222-016-9646-1
10.1038/35065725
10.1016/j.coal.2017.06.006
10.1021/acs.energyfuels.5b02088
10.1016/j.jngse.2018.02.034
10.1007/s11042-020-10139-6
10.1016/j.jngse.2016.03.097
10.1039/C6RA05083B
10.1016/j.petrol.2021.108899
10.1038/s41598-021-92278-w
10.1016/j.apt.2021.09.015
10.1016/j.coal.2015.09.004
10.1016/j.cej.2021.133151
10.1016/j.petrol.2017.09.038
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References Guo (10.1016/j.geoen.2023.212618_bib12) 2018; 31
Fisher (10.1016/j.geoen.2023.212618_bib10) 2019; 20
Cancino (10.1016/j.geoen.2023.212618_bib5) 2017; 159
Lu (10.1016/j.geoen.2023.212618_bib26) 2022; 440
Huang (10.1016/j.geoen.2023.212618_bib18) 2022
Hong (10.1016/j.geoen.2023.212618_bib15) 2016; 14
Sui (10.1016/j.geoen.2023.212618_bib34) 2016; 31
Kundu (10.1016/j.geoen.2023.212618_bib21) 2021
Desai (10.1016/j.geoen.2023.212618_bib7) 2021; 11
Sun (10.1016/j.geoen.2023.212618_bib35) 2016; 6
Zeng (10.1016/j.geoen.2023.212618_bib39) 2022; 430
Wang (10.1016/j.geoen.2023.212618_bib37) 2021; 203
Dang (10.1016/j.geoen.2023.212618_bib6) 2017; 152
Hornik (10.1016/j.geoen.2023.212618_bib16) 1989; 2
Katoch (10.1016/j.geoen.2023.212618_bib20) 2021; 80
Liu (10.1016/j.geoen.2023.212618_bib23) 2017; 179
Zang (10.1016/j.geoen.2023.212618_bib38) 2021; 21
Duan (10.1016/j.geoen.2023.212618_bib9) 2016; 30
Liu (10.1016/j.geoen.2023.212618_bib24) 2018; 53
Murray-Smith (10.1016/j.geoen.2023.212618_bib29) 2012
Sankararaman (10.1016/j.geoen.2023.212618_bib32) 2020
Szegedy (10.1016/j.geoen.2023.212618_bib36) 2013
Archer (10.1016/j.geoen.2023.212618_bib1) 2008; 52
Breiman (10.1016/j.geoen.2023.212618_bib3) 2001; 45
Hoefler (10.1016/j.geoen.2023.212618_bib14) 2021; 22
Lin (10.1016/j.geoen.2023.212618_bib22) 2016; 9
Pessoa (10.1016/j.geoen.2023.212618_bib31) 2014; 11
Hamdia (10.1016/j.geoen.2023.212618_bib13) 2021; 33
Hu (10.1016/j.geoen.2023.212618_bib17) 2021; 32
Strogatz (10.1016/j.geoen.2023.212618_bib33) 2001; 410
Luo (10.1016/j.geoen.2023.212618_bib27) 2015; 150
Buitinck (10.1016/j.geoen.2023.212618_bib4) 2013
10.1016/j.geoen.2023.212618_bib8
Hui (10.1016/j.geoen.2023.212618_bib19) 2021; 94
Lu (10.1016/j.geoen.2023.212618_bib25) 2011
Gregorutti (10.1016/j.geoen.2023.212618_bib11) 2017; 27
Belmabkhout (10.1016/j.geoen.2023.212618_bib2) 2004; 15
Meng (10.1016/j.geoen.2023.212618_bib28) 2020; 278
Pang (10.1016/j.geoen.2023.212618_bib30) 2022; 15
References_xml – volume: 11
  start-page: 400
  year: 2014
  ident: 10.1016/j.geoen.2023.212618_bib31
  article-title: Understanding brain networks and brain organization
  publication-title: Phys. Life Rev.
  doi: 10.1016/j.plrev.2014.03.005
– volume: 33
  start-page: 1923
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib13
  article-title: An efficient optimization approach for designing machine learning models based on genetic algorithm
  publication-title: Neural Comput. Appl.
  doi: 10.1007/s00521-020-05035-x
– volume: 440
  year: 2022
  ident: 10.1016/j.geoen.2023.212618_bib26
  article-title: Competitive adsorption in CO2 enhancing shale gas: low-field NMR measurement combined with molecular simulation for selectivity and displacement efficiency model
  publication-title: Chem. Eng. J.
  doi: 10.1016/j.cej.2022.135865
– volume: 21
  start-page: 6410
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib38
  article-title: Deep sparse learning for automatic modulation classification using Recurrent Neural Networks
  publication-title: Sensors
  doi: 10.3390/s21196410
– volume: 52
  start-page: 2249
  year: 2008
  ident: 10.1016/j.geoen.2023.212618_bib1
  article-title: Empirical characterization of random forest variable importance measures
  publication-title: Comput. Stat. Data Anal.
  doi: 10.1016/j.csda.2007.08.015
– volume: 94
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib19
  article-title: Machine learning-based production forecast for shale gas in unconventional reservoirs via integration of geological and operational factors
  publication-title: J. Nat. Gas Sci. Eng.
  doi: 10.1016/j.jngse.2021.104045
– year: 2013
  ident: 10.1016/j.geoen.2023.212618_bib36
– volume: 2
  start-page: 359
  year: 1989
  ident: 10.1016/j.geoen.2023.212618_bib16
  article-title: Multilayer feedforward networks are universal approximators
  publication-title: Neural Network.
  doi: 10.1016/0893-6080(89)90020-8
– start-page: 8469
  year: 2020
  ident: 10.1016/j.geoen.2023.212618_bib32
  article-title: The impact of neural network overparameterization on gradient confusion and stochastic gradient descent
– volume: 45
  start-page: 5
  year: 2001
  ident: 10.1016/j.geoen.2023.212618_bib3
  article-title: Random forests
  publication-title: Mach. Learn.
  doi: 10.1023/A:1010933404324
– year: 2011
  ident: 10.1016/j.geoen.2023.212618_bib25
– volume: 14
  start-page: 99
  year: 2016
  ident: 10.1016/j.geoen.2023.212618_bib15
  article-title: An investigation of factors affecting the interaction of CO2 and CH4 on shale in Appalachian Basin
  publication-title: Journal of Unconventional Oil and Gas Resources
  doi: 10.1016/j.juogr.2016.02.003
– volume: 152
  start-page: 456
  year: 2017
  ident: 10.1016/j.geoen.2023.212618_bib6
  article-title: Geological controls on methane adsorption capacity of Lower Permian transitional black shales in the Southern North China Basin, Central China: experimental results and geological implications
  publication-title: J. Petrol. Sci. Eng.
  doi: 10.1016/j.petrol.2017.03.017
– year: 2012
  ident: 10.1016/j.geoen.2023.212618_bib29
– volume: 15
  start-page: 2548
  year: 2022
  ident: 10.1016/j.geoen.2023.212618_bib30
  article-title: Predicting adsorption of methane and carbon dioxide mixture in shale using simplified local-density model: implications for enhanced gas recovery and carbon dioxide sequestration
  publication-title: Energies
  doi: 10.3390/en15072548
– volume: 278
  year: 2020
  ident: 10.1016/j.geoen.2023.212618_bib28
  article-title: Prediction of methane adsorption in shale: classical models and machine learning based models
  publication-title: Fuel
  doi: 10.1016/j.fuel.2020.118358
– volume: 15
  start-page: 848
  year: 2004
  ident: 10.1016/j.geoen.2023.212618_bib2
  article-title: High-pressure adsorption measurements. A comparative study of the volumetric and gravimetric methods
  publication-title: Meas. Sci. Technol.
  doi: 10.1088/0957-0233/15/5/010
– volume: 9
  start-page: 127
  year: 2016
  ident: 10.1016/j.geoen.2023.212618_bib22
  article-title: Which is the most efficient candidate for the recovery of confined methane: water, carbon dioxide or nitrogen?
  publication-title: Extreme Mechanics Letters
  doi: 10.1016/j.eml.2016.05.014
– volume: 27
  start-page: 659
  year: 2017
  ident: 10.1016/j.geoen.2023.212618_bib11
  article-title: Correlation and variable importance in random forests
  publication-title: Stat. Comput.
  doi: 10.1007/s11222-016-9646-1
– volume: 410
  start-page: 268
  year: 2001
  ident: 10.1016/j.geoen.2023.212618_bib33
  article-title: Exploring complex networks
  publication-title: Nature
  doi: 10.1038/35065725
– start-page: 344
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib21
  article-title: Dnr: a tunable robust pruning framework through dynamic network rewiring of dnns
– volume: 179
  start-page: 211
  year: 2017
  ident: 10.1016/j.geoen.2023.212618_bib23
  article-title: Experimental evaluation of CO2 enhanced recovery of adsorbed-gas from shale
  publication-title: Int. J. Coal Geol.
  doi: 10.1016/j.coal.2017.06.006
– volume: 30
  start-page: 2248
  year: 2016
  ident: 10.1016/j.geoen.2023.212618_bib9
  article-title: Adsorption equilibrium of CO2 and CH4 and their mixture on Sichuan Basin shale
  publication-title: Energy Fuels
  doi: 10.1021/acs.energyfuels.5b02088
– volume: 53
  start-page: 329
  year: 2018
  ident: 10.1016/j.geoen.2023.212618_bib24
  article-title: Competitive adsorption and diffusion of CH4/CO2 binary mixture within shale organic nanochannels
  publication-title: J. Nat. Gas Sci. Eng.
  doi: 10.1016/j.jngse.2018.02.034
– ident: 10.1016/j.geoen.2023.212618_bib8
– year: 2013
  ident: 10.1016/j.geoen.2023.212618_bib4
– volume: 80
  start-page: 8091
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib20
  article-title: A review on genetic algorithm: past, present, and future
  publication-title: Multimed. Tool. Appl.
  doi: 10.1007/s11042-020-10139-6
– volume: 31
  start-page: 738
  year: 2016
  ident: 10.1016/j.geoen.2023.212618_bib34
  article-title: Effect of surface chemistry for CH4/CO2 adsorption in kerogen: a molecular simulation study
  publication-title: J. Nat. Gas Sci. Eng.
  doi: 10.1016/j.jngse.2016.03.097
– volume: 22
  start-page: 1
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib14
  article-title: Sparsity in Deep Learning: pruning and growth for efficient inference and training in neural networks
  publication-title: J. Mach. Learn. Res.
– volume: 20
  start-page: 1
  year: 2019
  ident: 10.1016/j.geoen.2023.212618_bib10
  article-title: All models are wrong, but many are useful: learning a variable's importance by studying an entire class of prediction models simultaneously
  publication-title: J. Mach. Learn. Res.
– volume: 6
  start-page: 32770
  year: 2016
  ident: 10.1016/j.geoen.2023.212618_bib35
  article-title: Adsorption properties of CH 4 and CO 2 in quartz nanopores studied by molecular simulation
  publication-title: RSC Adv.
  doi: 10.1039/C6RA05083B
– volume: 203
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib37
  article-title: Production forecast and optimization for parent-child well pattern in unconventional reservoirs
  publication-title: J. Petrol. Sci. Eng.
  doi: 10.1016/j.petrol.2021.108899
– volume: 11
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib7
  article-title: Parsimonious neural networks learn interpretable physical laws
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-021-92278-w
– volume: 31
  year: 2018
  ident: 10.1016/j.geoen.2023.212618_bib12
  article-title: Sparse dnns with improved adversarial robustness
  publication-title: Adv. Neural Inf. Process. Syst.
– volume: 32
  start-page: 4110
  year: 2021
  ident: 10.1016/j.geoen.2023.212618_bib17
  article-title: Experimental study on influence of adsorption equilibrium time on methane adsorption isotherm and Langmuir parameter
  publication-title: Adv. Powder Technol.
  doi: 10.1016/j.apt.2021.09.015
– year: 2022
  ident: 10.1016/j.geoen.2023.212618_bib18
  article-title: Fast prediction of methane adsorption in shale nanopores using kinetic theory and machine learning algorithm
  publication-title: Chem. Eng. J.
– volume: 150
  start-page: 210
  year: 2015
  ident: 10.1016/j.geoen.2023.212618_bib27
  article-title: Adsorption of methane, carbon dioxide and their binary mixtures on Jurassic shale from the Qaidam Basin in China
  publication-title: Int. J. Coal Geol.
  doi: 10.1016/j.coal.2015.09.004
– volume: 430
  year: 2022
  ident: 10.1016/j.geoen.2023.212618_bib39
  article-title: Methane adsorption capacity measurement in shale matrix nanopores at high pressure by low-field NMR and molecular simulation
  publication-title: Chem. Eng. J.
  doi: 10.1016/j.cej.2021.133151
– volume: 159
  start-page: 307
  year: 2017
  ident: 10.1016/j.geoen.2023.212618_bib5
  article-title: Adsorption of pure CO2 and a CO2/CH4 mixture on a black shale sample: Manometry and microcalorimetry measurements
  publication-title: J. Petrol. Sci. Eng.
  doi: 10.1016/j.petrol.2017.09.038
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