Fully connected deep network: An improved method to predict TOC of shale reservoirs from well logs D Zheng, S Wu, M Hou Marine and Petroleum Geology 132, 105205, 2021 | 24 | 2021 |
Application of machine learning in the identification of fluvial-lacustrine lithofacies from well logs: A case study from Sichuan Basin, China D Zheng, M Hou, A Chen, H Zhong, Z Qi, Q Ren, J You, H Wang, C Ma Journal of Petroleum Science and Engineering 215, 110610, 2022 | 19 | 2022 |
Zircon classification from cathodoluminescence images using deep learning D Zheng, S Wu, C Ma, L Xiang, L Hou, A Chen, M Hou Geoscience Frontiers 13 (6), 101436, 2022 | 14 | 2022 |
Jurassic paleomagnetism of the Lhasa terrane—implications for Tethys evolution and true polar wander Y Ma, Q Wang, H Wang, B Wan, S Zhang, C Deng, D Zheng, Q Ren, ... Journal of Geophysical Research: Solid Earth 127 (12), e2022JB025577, 2022 | 9 | 2022 |
Provenance of upper Permian-lowermost Triassic sandstones, Wutonggou low-order cycle, Bogda Mountains, NW China: implications on the unroofing history of the Eastern North … DY Zheng, W Yang Journal of Palaeogeography 9 (1), 19, 2020 | 7 | 2020 |
A knowledge graph for standard carbonate microfacies and its application in the automatical reconstruction of the relative sea-level curve H Wang, H Zhong, A Chen, K Li, H He, Z Qi, D Zheng, H Zhao, M Hou Geoscience Frontiers 14 (5), 101535, 2023 | 5 | 2023 |
Construction of a fluvial facies knowledge graph and its application in sedimentary facies identification L Zhang, M Hou, A Chen, H Zhong, JG Ogg, D Zheng Geoscience Frontiers 14 (2), 101521, 2023 | 4 | 2023 |
Principal component analysis of textural characteristics of fluvio-lacustrine sandstones and controlling factors of sandstone textures DY Zheng, SX Wu Geological Magazine 158 (10), 1847-1861, 2021 | 3 | 2021 |
Marine aragonite evolution in the oxygen-decreasing interval before the Cenomanian-Turonian Ocean anoxic event (OAE2) in the southeastern Neo-Tethys Y Ge, H Wang, Z Tian, D Zheng, L Yi, H Han Sedimentary Geology 429, 106078, 2022 | 1 | 2022 |
Provenance and depositional environments of the upper Permian-lowermost Triassic fluvial and lacustrine sandstones, Wutonggou low-order cycle, Bogda Mountains, NW China D Zheng Missouri University of Science and Technology, 2019 | 1 | 2019 |
PBDB 数据库在古地理重建中的重要应用进展 王晓楠, 任强, 侯明才, 董俊玲, 陈安清, 马超, 钟瀚霆, 郑栋宇 沉积与特提斯地质 44 (1), 34-44, 2024 | | 2024 |
Continuous 3D modelling over deep time–the SCION Earth Evolution Model B Mills, D Zheng, K Gurung, A Merdith, A Krause, Z Xu, F Bowyer, ... EGU24, 2024 | | 2024 |
DDViT: Advancing lithology identification on FMI image logs through a dual modal transformer model with less information drop L Hou, C Ma, W Tang, Y Zhou, S Ye, X Chen, X Zhang, C Yu, A Chen, ... Geoenergy Science and Engineering 234, 212662, 2024 | | 2024 |
Using Deep Learning to integrate paleoclimate and global biogeochemistry over Phanerozoic time D Zheng, A Merdith, Y Goddéris, Y Donnadieu, K Gurung, BJW Mills Geoscientific Model Development Discussions 2024, 1-20, 2024 | | 2024 |
Explainable deep learning for automatic rock classification D Zheng, H Zhong, G Camps-Valls, Z Cao, X Ma, B Mills, X Hu, M Hou, ... Computers & Geosciences 184, 105511, 2024 | | 2024 |
岩相古地理知识图谱构建及应用 张佳佳, 张蕾, 钟瀚霆, 王瀚, 陈安清, 李凤杰, 任强, 郑栋宇, 赵洪祎, ... 高校地质学报 29 (3), 345, 2023 | | 2023 |
High accuracy doesn't prove that a deep learning model is accurate: a case study from automatic rock classification of thin section photomicrographs D Zheng, Z Cao, L Hou, C Ma, M Hou EGU General Assembly Conference Abstracts, EGU-244, 2023 | | 2023 |
福建中新世中期三宝木属 (大戟科) 一新种及其古气候与古生态学意义 郑清丹, 董俊玲, 郑栋宇, 孙柏年 | | 2023 |
基于 APSO-MCMC 的叠前三参数同步随机反演方法研究 向坤, 陈科, 段心标, 郑栋宇 石油物探 61 (4), 673-682, 2022 | | 2022 |
A New Stochastic Process of Prestack Inversion for Rock Property Estimation L Yin, S Zhang, K Xiang, Y Ma, Y Ji, K Chen, D Zheng Applied Sciences 12 (5), 2392, 2022 | | 2022 |