{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T19:34:24Z","timestamp":1768073664013,"version":"3.49.0"},"reference-count":56,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T00:00:00Z","timestamp":1723248000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"publisher","award":["89233218CNA000001"],"award-info":[{"award-number":["89233218CNA000001"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006168","name":"National Nuclear Security Administration","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006168","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008902","name":"Los Alamos National Laboratory","doi-asserted-by":"publisher","award":["20220019DR"],"award-info":[{"award-number":["20220019DR"]}],"id":[{"id":"10.13039\/100008902","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Geosciences"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1016\/j.cageo.2024.105700","type":"journal-article","created":{"date-parts":[[2024,8,10]],"date-time":"2024-08-10T15:23:39Z","timestamp":1723303419000},"page":"105700","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Bayesian learning of gas transport in three-dimensional fracture networks"],"prefix":"10.1016","volume":"192","author":[{"given":"Yingqi","family":"Shi","sequence":"first","affiliation":[]},{"given":"Donald J.","family":"Berry","sequence":"additional","affiliation":[]},{"given":"John","family":"Kath","sequence":"additional","affiliation":[]},{"given":"Shams","family":"Lodhy","sequence":"additional","affiliation":[]},{"given":"An","family":"Ly","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0847-5284","authenticated-orcid":false,"given":"Allon G.","family":"Percus","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4224-2847","authenticated-orcid":false,"given":"Jeffrey D.","family":"Hyman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3551-2885","authenticated-orcid":false,"given":"Kelly","family":"Moran","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4356-9443","authenticated-orcid":false,"given":"Justin","family":"Strait","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5160-4176","authenticated-orcid":false,"given":"Matthew R.","family":"Sweeney","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1178-9647","authenticated-orcid":false,"given":"Hari S.","family":"Viswanathan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6976-221X","authenticated-orcid":false,"given":"Philip H.","family":"Stauffer","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.cageo.2024.105700_b1","doi-asserted-by":"crossref","first-page":"1896","DOI":"10.1109\/TVCG.2016.2582174","article-title":"Analysis and visualization of discrete fracture networks using a flow topology graph","volume":"23","author":"Aldrich","year":"2017","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"issue":"August","key":"10.1016\/j.cageo.2024.105700_b2","first-page":"1","article-title":"Topology of fracture networks","volume":"1","author":"Andresen","year":"2013","journal-title":"Front. Phys."},{"key":"10.1016\/j.cageo.2024.105700_b3","series-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"issue":"3","key":"10.1016\/j.cageo.2024.105700_b4","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1029\/1999RG000074","article-title":"Scaling of fracture systems in geological media","volume":"39","author":"Bonnet","year":"2001","journal-title":"Rev. Geophys."},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b5","doi-asserted-by":"crossref","DOI":"10.2136\/vzj2018.07.0134","article-title":"Evaluating the importance of barometric pumping for subsurface gas transport near an underground nuclear test site","volume":"18","author":"Bourret","year":"2019","journal-title":"Vadose Zone J."},{"key":"10.1016\/j.cageo.2024.105700_b6","series-title":"Machine learning on graphs: A model and comprehensive taxonomy","author":"Chami","year":"2021"},{"key":"10.1016\/j.cageo.2024.105700_b7","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1029\/2001WR001009","article-title":"Hydraulic properties of two-dimensional random fracture networks following power law distributions of length and aperture","volume":"38","author":"de Dreuzy","year":"2002","journal-title":"Water Resour. Res."},{"issue":"9","key":"10.1016\/j.cageo.2024.105700_b8","doi-asserted-by":"crossref","first-page":"2685","DOI":"10.1029\/1999WR900118","article-title":"Derivation of equivalent pipe network analogues for three-dimensional discrete fracture networks by the boundary element method","volume":"35","author":"Dershowitz","year":"1999","journal-title":"Water Resour. Res."},{"issue":"5","key":"10.1016\/j.cageo.2024.105700_b9","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.102.053312","article-title":"Graph-based flow modeling approach adapted to multiscale discrete-fracture-network models","volume":"102","author":"Doolaeghe","year":"2020","journal-title":"Phys. Rev. E"},{"key":"10.1016\/j.cageo.2024.105700_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2021.127173","article-title":"A meta-modeling approach for hydrological forecasting under uncertainty: Application to groundwater nitrate response to climate change","volume":"603","author":"Focaccia","year":"2021","journal-title":"J. Hydrol."},{"issue":"2","key":"10.1016\/j.cageo.2024.105700_b11","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s10040-013-1080-2","article-title":"A methodology to constrain the parameters of a hydrogeological discrete fracture network model for sparsely fractured crystalline rock, exemplified by data from the proposed high-level nuclear waste repository site at Forsmark, Sweden","volume":"22","author":"Follin","year":"2014","journal-title":"Hydrogeol. J."},{"issue":"W11502","key":"10.1016\/j.cageo.2024.105700_b12","article-title":"Inference of field-scale fracture transmissivities in crystalline rock using flow log measurements","volume":"46","author":"Frampton","year":"2010","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.cageo.2024.105700_b13","doi-asserted-by":"crossref","first-page":"75","DOI":"10.3389\/fphy.2015.00075","article-title":"Topological impact of constrained fracture growth","volume":"3","author":"Hope","year":"2015","journal-title":"Front. Phys."},{"issue":"5","key":"10.1016\/j.cageo.2024.105700_b14","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1088\/0305-4470\/30\/5\/012","article-title":"Geometry and topology of fracture systems","volume":"30","author":"Huseby","year":"1997","journal-title":"J. Phys. A: Math. Gen."},{"key":"10.1016\/j.cageo.2024.105700_b15","doi-asserted-by":"crossref","first-page":"6472","DOI":"10.1002\/2016WR018806","article-title":"Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size","volume":"52","author":"Hyman","year":"2016","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.cageo.2024.105700_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.advwatres.2021.103994","article-title":"Transport upscaling under flow heterogeneity and matrix-diffusion in three-dimensional discrete fracture networks","volume":"155","author":"Hyman","year":"2021","journal-title":"Adv. Water Resour."},{"issue":"24","key":"10.1016\/j.cageo.2024.105700_b17","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevLett.123.248501","article-title":"Emergence of stable laws for first passage times in three-dimensional random fracture networks","volume":"123","author":"Hyman","year":"2019","journal-title":"Phys. Rev. Lett."},{"key":"10.1016\/j.cageo.2024.105700_b18","doi-asserted-by":"crossref","DOI":"10.1029\/2018JB016553","article-title":"Linking structural and transport properties in three-dimensional fracture networks","author":"Hyman","year":"2019","journal-title":"J. Geophys. Res. Solid. Earth"},{"issue":"4","key":"10.1016\/j.cageo.2024.105700_b19","doi-asserted-by":"crossref","first-page":"A1871","DOI":"10.1137\/130942541","article-title":"Conforming delaunay triangulation of stochastically generated three dimensional discrete fracture networks: A feature rejection algorithm for meshing strategy","volume":"36","author":"Hyman","year":"2014","journal-title":"SIAM J. Sci. Comput."},{"key":"10.1016\/j.cageo.2024.105700_b20","doi-asserted-by":"crossref","first-page":"1948","DOI":"10.1137\/18M1180207","article-title":"Identifying backbones in three-dimensional discrete fracture networks: A bipartite graph-based approach","volume":"16","author":"Hyman","year":"2018","journal-title":"Multisc. Model. Simul."},{"key":"10.1016\/j.cageo.2024.105700_b21","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.96.013304","article-title":"Predictions of first passage times in sparse discrete fracture networks using graph-based reductions","volume":"96","author":"Hyman","year":"2017","journal-title":"Phys. Rev. E"},{"issue":"5","key":"10.1016\/j.cageo.2024.105700_b22","doi-asserted-by":"crossref","first-page":"3243","DOI":"10.1029\/2018WR022585","article-title":"Dispersion and mixing in three-dimensional discrete fracture networks: Nonlinear interplay between structural and hydraulic heterogeneity","volume":"54","author":"Hyman","year":"2017","journal-title":"Water Resour. Res."},{"issue":"3","key":"10.1016\/j.cageo.2024.105700_b23","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1007\/s11242-019-01372-1","article-title":"Characterizing the impact of fractured caprock heterogeneity on supercritical CO2 injection","volume":"131","author":"Hyman","year":"2020","journal-title":"Transp. Porous Media"},{"issue":"2078","key":"10.1016\/j.cageo.2024.105700_b24","doi-asserted-by":"crossref","DOI":"10.1098\/rsta.2015.0426","article-title":"Understanding hydraulic fracturing: a multi-scale problem","volume":"374","author":"Hyman","year":"2016","journal-title":"Phil. Trans. R. Soc. A"},{"key":"10.1016\/j.cageo.2024.105700_b25","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.cageo.2015.08.001","article-title":"dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport","volume":"84","author":"Hyman","year":"2015","journal-title":"Comput. Geosci."},{"issue":"9","key":"10.1016\/j.cageo.2024.105700_b26","doi-asserted-by":"crossref","first-page":"7289","DOI":"10.1002\/2015WR017151","article-title":"Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks","volume":"51","author":"Hyman","year":"2015","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.cageo.2024.105700_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.jcp.2022.111396","article-title":"Flow and transport in three-dimensional discrete fracture matrix models using mimetic finite difference on a conforming multi-dimensional mesh","volume":"466","author":"Hyman","year":"2022","journal-title":"J. Comput. Phys."},{"key":"10.1016\/j.cageo.2024.105700_b28","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.ijggc.2015.05.009","article-title":"The state of the art in monitoring and verification\u2014ten years on","volume":"40","author":"Jenkins","year":"2015","journal-title":"Int. J. Greenh. Gas Control"},{"key":"10.1016\/j.cageo.2024.105700_b29","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1007\/s10040-014-1165-6","article-title":"Multi-scale groundwater flow modeling during temperate climate conditions for the safety assessment of the proposed high-level nuclear waste repository site at Forsmark, Sweden","volume":"22","author":"Joyce","year":"2014","journal-title":"Hydrogeol. J."},{"key":"10.1016\/j.cageo.2024.105700_b30","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.advwatres.2017.03.024","article-title":"Anomalous transport in disordered fracture networks: spatial Markov model for dispersion with variable injection modes","volume":"106","author":"Kang","year":"2017","journal-title":"Adv. Water Resources"},{"issue":"11","key":"10.1016\/j.cageo.2024.105700_b31","doi-asserted-by":"crossref","DOI":"10.1029\/2020WR027378","article-title":"Anomalous transport in three-dimensional discrete fracture networks: Interplay between aperture heterogeneity and injection modes","volume":"56","author":"Kang","year":"2020","journal-title":"Water Resour. Res."},{"issue":"033304","key":"10.1016\/j.cageo.2024.105700_b32","article-title":"Modeling flow and transport in fracture networks using graphs","volume":"97","author":"Karra","year":"2018","journal-title":"Phys. Rev."},{"issue":"11","key":"10.1016\/j.cageo.2024.105700_b33","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1016\/0009-2509(78)85196-3","article-title":"On the physical meaning of the dispersion equation and its solutions for different initial and boundary conditions","volume":"33","author":"Kreft","year":"1978","journal-title":"Chem. Eng. Sci."},{"key":"10.1016\/j.cageo.2024.105700_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.cam.2022.114094","article-title":"Variable resolution Poisson-disk sampling for meshing discrete fracture networks","volume":"407","author":"Krotz","year":"2022","journal-title":"J. Comput. Appl. Math."},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b35","first-page":"13","article-title":"An artificial-neural-network-based surrogate modeling workflow for reactive transport modeling","volume":"7","author":"Li","year":"2022","journal-title":"Pet. Res."},{"key":"10.1016\/j.cageo.2024.105700_b36","unstructured":"Lichtner, P.C., Hammond, G.E., Lu, C., Karra, S., Bisht, G., Andre, B., Mills, R.T., Kumar, J., Frederick, J.M., 2020. PFLOTRAN User Manual. Technical Report,."},{"issue":"11","key":"10.1016\/j.cageo.2024.105700_b37","doi-asserted-by":"crossref","first-page":"8526","DOI":"10.1002\/2016WR018973","article-title":"Connectivity, permeability, and channeling in randomly distributed and kinematically defined discrete fracture network models","volume":"52","author":"Maillot","year":"2016","journal-title":"Water Resour. Res."},{"issue":"5","key":"10.1016\/j.cageo.2024.105700_b38","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1007\/s10596-015-9525-4","article-title":"Particle tracking approach for transport in three-dimensional discrete fracture networks","volume":"19","author":"Makedonska","year":"2015","journal-title":"Computat. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b39","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.apenergy.2015.03.023","article-title":"Shale gas and non-aqueous fracturing fluids: Opportunities and challenges for supercritical CO2","volume":"147","author":"Middleton","year":"2015","journal-title":"Appl. Energy"},{"key":"10.1016\/j.cageo.2024.105700_b40","series-title":"Characterization, Modeling, Monitoring, and Remediation of Fractured Rock","author":"National Academies of Sciences, Engineering, and Medicine","year":"2020"},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b41","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1007\/s10040-004-0397-2","article-title":"Trends, prospects and challenges in quantifying flow and transport through fractured rocks","volume":"13","author":"Neuman","year":"2005","journal-title":"Hydrogeol. J."},{"issue":"4","key":"10.1016\/j.cageo.2024.105700_b42","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1007\/s10596-012-9307-1","article-title":"Pathline tracing on fully unstructured control-volume grids","volume":"16","author":"Painter","year":"2012","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b43","series-title":"Gaussian Processes for Machine Learning","author":"Rasmussen","year":"2006"},{"issue":"1\u20134","key":"10.1016\/j.cageo.2024.105700_b44","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/S0022-1694(01)00551-0","article-title":"Comparison of alternative modelling approaches for groundwater flow in fractured rock","volume":"257","author":"Selroos","year":"2002","journal-title":"J. Hydrol."},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b45","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.99.013110","article-title":"Characterizing the impact of particle behavior at fracture intersections in three-dimensional discrete fracture networks","volume":"99","author":"Sherman","year":"2019","journal-title":"Phys. Rev. E"},{"key":"10.1016\/j.cageo.2024.105700_b46","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1007\/s10596-020-09962-5","article-title":"Physics-informed machine learning for backbone identification in discrete fracture networks","volume":"24","author":"Srinivasan","year":"2020","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b47","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1007\/s10596-019-9811-7","article-title":"Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways","volume":"23","author":"Srinivasan","year":"2019","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b48","series-title":"Graph Machine Learning","author":"Stamile","year":"2021"},{"issue":"3","key":"10.1016\/j.cageo.2024.105700_b49","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1007\/s00024-012-0514-4","article-title":"Modeling noble gas transport and detection for the comprehensive nuclear-test-ban treaty","volume":"171","author":"Sun","year":"2014","journal-title":"Pure Appl. Geophys."},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b50","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1007\/s10596-019-09921-9","article-title":"Upscaled discrete fracture matrix model (UDFM): an octree-refined continuum representation of fractured porous media","volume":"24","author":"Sweeney","year":"2020","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b51","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1007\/s10596-016-9587-y","article-title":"Multi-fidelity meta-modeling for reservoir engineering \u2014 application to history matching","volume":"20","author":"Thenon","year":"2016","journal-title":"Comput. Geosci."},{"issue":"11","key":"10.1016\/j.cageo.2024.105700_b52","doi-asserted-by":"crossref","DOI":"10.1002\/hyp.14743","article-title":"Quantifying subsurface parameter and transport uncertainty using surrogate modelling and environmental tracers","volume":"36","author":"Thiros","year":"2022","journal-title":"Hydrol. Process."},{"key":"10.1016\/j.cageo.2024.105700_b53","first-page":"1","article-title":"Multilevel graph partitioning for three-dimensional discrete fracture network flow simulations","author":"Ushijima-Mwesigwa","year":"2021","journal-title":"Math. Geosci."},{"key":"10.1016\/j.cageo.2024.105700_b54","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1007\/s10596-018-9720-1","article-title":"Machine learning techniques for graph-based representations of three-dimensional discrete fracture networks","volume":"22","author":"Valera","year":"2018","journal-title":"Comput. Geosci."},{"issue":"1","key":"10.1016\/j.cageo.2024.105700_b55","doi-asserted-by":"crossref","DOI":"10.1029\/2021RG000744","article-title":"From fluid flow to coupled processes in fractured rock: Recent advances and new frontiers","volume":"60","author":"Viswanathan","year":"2022","journal-title":"Rev. Geophys."},{"key":"10.1016\/j.cageo.2024.105700_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2020.103848","article-title":"Meta-modelling of coupled thermo-hydro-mechanical behaviour of hydrate reservoir","volume":"128","author":"Zhou","year":"2020","journal-title":"Comput. Geotech."}],"container-title":["Computers &amp; Geosciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300424001833?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300424001833?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T23:53:17Z","timestamp":1726271597000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098300424001833"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":56,"alternative-id":["S0098300424001833"],"URL":"https:\/\/doi.org\/10.1016\/j.cageo.2024.105700","relation":{},"ISSN":["0098-3004"],"issn-type":[{"value":"0098-3004","type":"print"}],"subject":[],"published":{"date-parts":[[2024,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Bayesian learning of gas transport in three-dimensional fracture networks","name":"articletitle","label":"Article Title"},{"value":"Computers & Geosciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cageo.2024.105700","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"105700"}}