数智时代沉积学问题之思考OA

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 sedi-mentology 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 chal-lenges,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.