Fine reservoir description，with rich content and massive accumulated data，provides a solid foundation for the application of big data technology. Meanwhile，the transformation and rapid development of fine reservoir description from digital to intelligent need support from big data technology. The characteristics of big data in fine reservoir description are expounded from aspects of basic statistical data and comprehensive data on research results. In addition to the above data tables，the big data in fine reservoir description also includes logging interpretation charts，seismic interpretation data volumes，geological models，and other data volumes，as well as various result maps. In light of scientific research practices，the application of big data technology in fine reservoir description is discussed from the perspectives of automatic fine stratigraphic division and correlation，automatic bulk discriminant classification of reservoir sedimentary microfacies（or reservoir architecture），bulk fine logging reinterpretation，comprehensive quantitative reservoir evaluation by cluster analysis，and multipoint geostatistical 3D geological modeling. The problems with the application of the big data technology in fine reservoir description include the database construction for big data technology，information mining for the big data technology，representativeness of big data，fusion of various types of big data，security of big data application，and expansion of big data application fields. Future development mainly involves the construction of the big data application platforms，optimization of information mining methods oriented towards big data technology，quality control of big data，innovation of visualization technology in the big data，standardized management of massive big data on oilfield development，and exploratory application of the big data technology in fine reservoir description of the unconventional oil and gas.