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Reflections on sedimentology in the digital-intelligent era
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Xinghe YU, Shengli LI, Shunli LI, Chengpeng TAN, Chao FU
Journal of Palaeogeography (Chinese Edition) | 2026, 28(2) : 429 - 446
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Journal of Palaeogeography (Chinese Edition) | 2026, 28(2): 429-446
• SPECIAL TOPIC ON THE 100TH ANNIVERSARY OF PROFESSOR FENG ZENGZHAO •
Reflections on sedimentology in the digital-intelligent era
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Xinghe YU, Shengli LI, Shunli LI, Chengpeng TAN, Chao FU
Affiliations
  • China University of Geosciences(Beijing),Beijing 100083, China
  • YU Xinghe,born in 1958,is a professor and doctoral supervisor. He is mainly engaged in research and teaching in the field of sedimentology. E-mail: .

About Author:

YU Xinghe,born in 1958,is a professor and doctoral supervisor. He is mainly engaged in research and teaching in the field of sedimentology. E-mail: .

Published: 2026-04-01 doi: 10.7605/gdlxb.2026.015
Outline
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In the digital-intelligent era,disruptive technologies such as artificial intelligence and big data are driving sedimentology into its fourth research paradigm shift. This transformation profoundly reshapes its research philosophy and methodological system,which is critical not only for the disciplinary innovation of sedimentology itself but also for national strategic demands including energy security and ecological governance. To clarify the disciplinary evolution,core challenges,and proactive response strategies,this paper systematically reviews the intelligent development,problem typology,technological innovation,and application expansion of sedimentology. Results show that the intelligent evolution of sedimentology can be divided into four stages,with a fundamental shift from experience driven to data and knowledge dual driven mode. Based on the four major question types in natural science,sedimentology is confronted with a series of core propositions including the Soul Question,Mystery Question,Century Question,and Epochal Question,among which the mass slope coupling and heterogeneity of terrestrial reservoirs represent key breakthroughs. Currently,the application of AI in sedimentology is constrained by methodological conflicts,data fragmentation,and lagging theoretical development. To meet these challenges,sedimentology must break traditional mindsets,reject imitative research and empty conceptual innovation,and establish a new logic integrating theory,technology,and data. The deployment and optimization of AI models constitute the cornerstone of intelligent transformation,emphasizing fullcycle implementation: application deployment,realtime monitoring,and continuous iteration. Only by rooting in the disciplinary essence of sedimentology,deeply integrating AI with sedimentary dynamics,forming a closed loop of “data-simulation-verification”,strengthening interdisciplinary integration,and expanding frontier fields such as deep Earth,deep sea,and carbon neutrality,can sedimentology accomplish the leap from interpretive science to predictive and generative science and provide solid scientific support for national energy security and ecological civilization.

sedimentology  /  digital-intelligent era  /  research paradigm shift  /  artificial intelligence(AI)  /  data fragmentation  /  interdisciplinary
于兴河, 李胜利, 李顺利, 谭程鹏, 付超. 数智时代沉积学问题之思考*. 古地理学报, 2026 , 28 (2) : 429 -446 . DOI: 10.7605/gdlxb.2026.015
Xinghe YU, Shengli LI, Shunli LI, Chengpeng TAN, Chao FU. Reflections on sedimentology in the digital-intelligent era[J]. Journal of Palaeogeography (Chinese Edition), 2026 , 28 (2) : 429 -446 . DOI: 10.7605/gdlxb.2026.015
  • National Natural Science Foundation of China(42272124)
  • National Natural Science Foundation of China(42272121)
  • National Natural Science Foundation of China(42402150)
Year 2026 volume 28 Issue 2
147
61
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Article Info
doi: 10.7605/gdlxb.2026.015
  • Receive Date:2026-01-14
  • Online Date:2026-09-24
  • Published:2026-04-01
Article Data
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History
  • Received:2026-01-14
  • Revised:2026-02-23
Funding
National Natural Science Foundation of China(42272124)
National Natural Science Foundation of China(42272121)
National Natural Science Foundation of China(42402150)
Affiliations
    China University of Geosciences(Beijing),Beijing 100083, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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