{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T20:26:09Z","timestamp":1783110369647,"version":"3.54.6"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005046","name":"Heilongjiang Province Natural Science Foundation","doi-asserted-by":"publisher","award":["ZD2023D002"],"award-info":[{"award-number":["ZD2023D002"]}],"id":[{"id":"10.13039\/501100005046","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":[[2026,8]]},"DOI":"10.1016\/j.cageo.2026.106198","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T16:12:31Z","timestamp":1779466351000},"page":"106198","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Reservoir facies modeling under multiple depositional conditions using latent diffusion models"],"prefix":"10.1016","volume":"214","author":[{"given":"Zhenghao","family":"Tang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baiquan","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1304-5692","authenticated-orcid":false,"given":"Yu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suibao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daming","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuli","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cageo.2026.106198_bib1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10994-025-06772-7","article-title":"An in-depth review and analysis of mode collapse in generative adversarial networks","volume":"114","author":"Barsha","year":"2025","journal-title":"Mach. Learn."},{"key":"10.1016\/j.cageo.2026.106198_bib2","article-title":"Ten years of generative adversarial nets (GANs): a survey of the state-of-the-art","volume":"5","author":"Chakraborty","year":"2024","journal-title":"Mach. Learn.: Sci. Technol."},{"key":"10.1016\/j.cageo.2026.106198_bib3","author":"Chan"},{"key":"10.1016\/j.cageo.2026.106198_bib4","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111934","article-title":"On the design fundamentals of diffusion models: a survey","volume":"169","author":"Chang","year":"2026","journal-title":"Pattern Recogn."},{"key":"10.1016\/j.cageo.2026.106198_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2024.105755","article-title":"Latent diffusion models for parameterization of facies-based geomodels and their use in data assimilation","volume":"194","author":"Di Federico","year":"2025","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib6","author":"Dupont"},{"key":"10.1016\/j.cageo.2026.106198_bib7","series-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems","first-page":"2672","article-title":"Generative adversarial nets","author":"Goodfellow","year":"2014"},{"key":"10.1016\/j.cageo.2026.106198_bib8","first-page":"1","article-title":"Sedimentary provenance studies","volume":"57","author":"Haughton","year":"1991","journal-title":"SP (Sci. Prog.)"},{"key":"10.1016\/j.cageo.2026.106198_bib9","series-title":"Proceedings of the 34th Conference on Neural Information Processing Systems","first-page":"6840","article-title":"Denoising diffusion probabilistic models","author":"Ho","year":"2020"},{"key":"10.1016\/j.cageo.2026.106198_bib10","series-title":"Auto-Encoding Variational Bayes","author":"Kingma","year":"2022"},{"key":"10.1016\/j.cageo.2026.106198_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2024.105750","article-title":"Latent diffusion model for conditional reservoir facies generation","volume":"194","author":"Lee","year":"2025","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib12","doi-asserted-by":"crossref","first-page":"7506","DOI":"10.1109\/TPAMI.2025.3569700","article-title":"Efficient Diffusion Models: a Comprehensive Survey from principles to practices","volume":"47","author":"Ma","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.cageo.2026.106198_bib13","author":"Merzoug"},{"key":"10.1016\/j.cageo.2026.106198_bib14","doi-asserted-by":"crossref","DOI":"10.1029\/2019WR025787","article-title":"Simulation of fluvial patterns with GANs trained on a data set of satellite imagery","volume":"57","author":"Nesvold","year":"2021","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.cageo.2026.106198_bib15","series-title":"Proceedings of the 38th International Conference on Machine Learning","first-page":"8162","article-title":"Improved denoising diffusion probabilistic models","author":"Nichol","year":"2021"},{"key":"10.1016\/j.cageo.2026.106198_bib16","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10674","article-title":"High-Resolution image synthesis with latent diffusion models","author":"Rombach","year":"2022"},{"key":"10.1016\/j.cageo.2026.106198_bib17","series-title":"Proceedings of the 32nd International Conference on Machine Learning","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","author":"Sohl-Dickstein","year":"2015"},{"key":"10.1016\/j.cageo.2026.106198_bib19","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s10596-021-10059-w","article-title":"Geological Facies modeling based on progressive growing of generative adversarial networks (GANs)","volume":"25","author":"Song","year":"2021","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib18","first-page":"1","article-title":"Bridging the gap between geophysics and geology with generative adversarial networks","volume":"60","author":"Song","year":"2022","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.cageo.2026.106198_bib20","series-title":"Advances in Neural Information Processing Systems","article-title":"Generative modeling by estimating gradients of the data distribution","author":"Song","year":"2019"},{"key":"10.1016\/j.cageo.2026.106198_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.dib.2022.108785","article-title":"GAN River-I: a process-based low NTG meandering reservoir model dataset for machine learning studies","volume":"46","author":"Sun","year":"2023","journal-title":"Data Brief"},{"key":"10.1016\/j.cageo.2026.106198_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2023.105460","article-title":"A conditional GAN-based approach to build 3D facies models sequentially upwards","volume":"181","author":"Sun","year":"2023","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib23","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s10596-023-10190-w","article-title":"Geological realism in Fluvial facies modelling with GAN under variable depositional conditions","volume":"27","author":"Sun","year":"2023","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib24","author":"Weltje"},{"key":"10.1016\/j.cageo.2026.106198_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128373","article-title":"Generative diffusion models: a survey of current theoretical developments","volume":"608","author":"Ye\u011fin","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.cageo.2026.106198_bib26","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1007\/s10596-021-10086-7","article-title":"Reconstruction of fluvial reservoirs using multiple-stage concurrent generative adversarial networks","volume":"25","author":"Zhang","year":"2021","journal-title":"Comput. Geosci."},{"key":"10.1016\/j.cageo.2026.106198_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2022.127493","article-title":"Stochastic simulation of deltas based on a concurrent multi-stage VAE-GAN model","volume":"607","author":"Zhang","year":"2022","journal-title":"J. Hydrol."},{"key":"10.1016\/j.cageo.2026.106198_bib28","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1007\/s12182-019-0328-4","article-title":"Generating geologically realistic 3D reservoir facies models using deep learning of sedimentary architecture with generative adversarial networks","volume":"16","author":"Zhang","year":"2019","journal-title":"Pet. Sci."},{"key":"10.1016\/j.cageo.2026.106198_bib29","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1111\/j.1365-2117.2009.00445.x","article-title":"Tectonostratigraphic units and stratigraphic sequences of the nonmarine Songliao basin, northeast China","volume":"22","author":"Zhi\u2010qiang","year":"2010","journal-title":"Basin Res."}],"container-title":["Computers &amp; Geosciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426000956?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300426000956?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:57:31Z","timestamp":1783108651000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098300426000956"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":29,"alternative-id":["S0098300426000956"],"URL":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106198","relation":{},"ISSN":["0098-3004"],"issn-type":[{"value":"0098-3004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Reservoir facies modeling under multiple depositional conditions using latent diffusion models","name":"articletitle","label":"Article Title"},{"value":"Computers & Geosciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cageo.2026.106198","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106198"}}