抄録
Oilfield reservoir characterization and resource evaluation are critical processes in oil and gas exploration and development, directly influencing the assessment of resource potential, optimization of development plans, and accuracy of production forecasting. In recent years, with the deep integration of multi-source geological data and the extensive application of artificial intelligence and big data technologies, significant advances have been achieved in theoretical methods, technical systems, and engineering practices. This paper systematically reviews the core technological progress in reservoir characterization, including core experimental analysis, fine well-logging interpretation, seismic inversion, and digital rock modeling, and summarizes the main technical systems of resource evaluation along with their practical applications and effectiveness in both conventional and unconventional oil and gas development. Moreover, it emphasizes the integrated application of big data and artificial intelligence in reservoir characterization and resource evaluation, provides an in-depth analysis of the major technical challenges under complex reservoir conditions, and discusses future development directions and research frontiers. The findings of this paper can offer theoretical support and technical guidance for efficient oil and gas exploration, development, and intelligent geological modeling.
