A new Bayesian-based brittleness prediction method for the Pingdiquan formation in the Eastern Shiqiantan depression of the East Junggar Basin

This paper presents a novel Bayesian-based method for predicting brittleness. The involves synthesizing petrophysical data from multiple well cores to establish joint Gaussian distribution function shale facies and non-shale facies. Furthermore, Bayesian classification is applied seismic data. proposed combines with Rickman brittleness obtain new index. are utilized enhance the differentiation of among different geological bodies. Practical analysis demonstrates that index effectively increases contrast in values between various bodies, highlighting target areas interest. presented offers promising approach prediction, leveraging integration through techniques. results suggest its potential applicability enhancing characterization understanding formations.