Method for predicting clay mineral development in lacustrine shale based on artificial intelligence learning of logging

Abstract

A method for predicting clay mineral development in lacustrine shale based on artificial intelligence is disclosed. The method comprises acquiring logging data of lacustrine shale, collecting rock samples of lacustrine shale, performing data preprocessing on the collected logging data, and acquiring types and contents of clay minerals in shale development a prediction model of clay mineral development is then developed based on an artificial intelligence. The artificial intelligence-based prediction model of clay mineral development is then optimized; and clay mineral development in lacustrine shale is predicted. In the present disclosure, the accuracy and efficiency of existing prediction methods are improved, allowing for the rapid acquisition of valuable information for the exploration and development of lacustrine shale.

Dependencies are inferred from the claim text.