{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T16:22:18Z","timestamp":1775665338849,"version":"3.50.1"},"reference-count":22,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Postdoctoral Program","doi-asserted-by":"publisher","award":["JWBH 2308"],"award-info":[{"award-number":["JWBH 2308"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Key Program of National Natural Science Foundation of China","award":["42030805"],"award-info":[{"award-number":["42030805"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Geosci. Remote Sensing Lett."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/lgrs.2024.3506017","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T13:56:38Z","timestamp":1732542998000},"page":"1-5","source":"Crossref","is-referenced-by-count":3,"title":["Shear-Wave Velocity Prediction by CNN-GRU Fusion Network Based on the Self-Attention Mechanism"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3577-5570","authenticated-orcid":false,"given":"Yahua","family":"Yang","sequence":"first","affiliation":[{"name":"SINOPEC Key Laboratory of Logging Well and the Geosteering and Logging Technology Research Institute, SINOPEC MATRIX Corporation, Qingdao, China"}]},{"given":"Junfeng","family":"Zhao","sequence":"additional","affiliation":[{"name":"SINOPEC Key Laboratory of Logging Well and the Processing and Interpretation Center, SINOPEC MATRIX Corporation, Qingdao, China"}]},{"given":"Huanfu","family":"Du","sequence":"additional","affiliation":[{"name":"SINOPEC Key Laboratory of Logging Well and the Geosteering and Logging Technology Research Institute, SINOPEC MATRIX Corporation, Qingdao, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2432-8548","authenticated-orcid":false,"given":"Xingyao","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao, China"}]},{"given":"Tengfei","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1190\/1.1441933"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2478.1992.tb00371.x"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1190\/1.1440450"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2478.1995.tb00126.x"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1093\/jge\/gxy009"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2785834"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.petsci.2021.09.046"},{"issue":"6","key":"ref10","first-page":"14","article-title":"Research on flow prediction of oil-gas-water multiphase pipe based on deep learning","volume":"42","author":"Li","year":"2023","journal-title":"Oil Gas Field Surf. Eng."},{"issue":"5","key":"ref11","first-page":"140","article-title":"Porosity prediction of tight sandstone reservoir based on deep feedforward neural network","volume":"42","author":"Li","year":"2023","journal-title":"Petroleum Geol. Oilfield Develop. Daqing"},{"issue":"4","key":"ref12","first-page":"111","article-title":"Shear wave velocity prediction based on one-dimensional convolutional neural network","volume":"33","author":"Ma","year":"2021","journal-title":"Lithologic Reservoirs"},{"issue":"1","key":"ref13","first-page":"93","article-title":"Logging curve prediction method based on GRU","volume":"30","author":"Teng","year":"2023","journal-title":"Petroleum Geol. Recovery Efficiency"},{"issue":"6","key":"ref14","first-page":"829","article-title":"Shear wave prediction method based on LSTM recurrent neural network","volume":"28","author":"Zhou","year":"2021","journal-title":"Fault-Block Oil Gas Field"},{"issue":"5","key":"ref15","first-page":"1993","article-title":"Research on reservoir porosity prediction method based on bidirectional longshort-term memory neural network","volume":"37","author":"Liu","year":"2022","journal-title":"Prog. Geophys."},{"issue":"3","key":"ref16","first-page":"484","article-title":"Prediction of S-wave velocity based on GRU neural network","volume":"55","author":"Sun","year":"2020","journal-title":"Oil Geophys. Prospecting"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/9974157"},{"issue":"5","key":"ref18","first-page":"73","article-title":"A method to predict reservoir parameters based on convolutional neural network-gated recurrent unit","volume":"26","author":"Song","year":"2019","journal-title":"Petroleum Geol. Recovery Efficiency"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1190\/geo2020-0886.1"},{"issue":"3","key":"ref20","first-page":"598","article-title":"Prestack seismic porosity prediction method based on bidirectional GRU and attention mechanism","volume":"63","author":"Yang","year":"2023","journal-title":"Geophys. Prospecting Petroleum"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2113\/2022\/4701851"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"}],"container-title":["IEEE Geoscience and Remote Sensing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8859\/10764750\/10767373.pdf?arnumber=10767373","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T19:02:00Z","timestamp":1764270120000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10767373\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/lgrs.2024.3506017","relation":{},"ISSN":["1545-598X","1558-0571"],"issn-type":[{"value":"1545-598X","type":"print"},{"value":"1558-0571","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}