Research on Intelligence Logging Interpretation Technology and System Based on Standard Big Data Platform

“Massive” logging data assets, due to their insufficient storage methods and normalization, cannot be quickly and accurately called up, become a “data island”, so that their value has not been fully explored. The current application scope of artificial intelligence is focused on single method research, with few system applications. However, intelligent interpretation requires the use of a large amount of logging data and related standard data. Based on a large number of documents related to large logging database and logging artificial intelligence, starting with supervised, unsupervised and semi-supervised intelligent algorithms, this paper expounds the application status quo and applicability of intelligent logging interpretation technology through machine learning for conventional logging lithology identification, automatic layering, sedimentary microfacies identification and reservoir identification. This paper briefly introduces the application status quo of logging data governance and mining technology. This paper summarizes the process of intelligent interpretation method, as well as the intelligent logging interpretation method and system based on a physical model under a standard big data platform. This paper discusses the existing problems in intelligent logging interpretation and evaluation and the feasible development direction of future research.