Abstract: Mud logging information is important basis of oil and gas identification during petroleum exploration practice. At present, there are limitations in the traditional cross charting analysis method, and this method has low comparability in different areas. In order to make rational use of various mud logging data and achieve the quantitative identification of oil and gas potential in reservoirs during drilling process, grey correlation analysis is introduced to systematically analyse the mud logging data. Considering that the size of numerical value in the process of dimensionless grey correlation analysis is crucial information in logging, this paper aims at the limitation of measuring correlation degree based on single curve similarity, introduces the correlation degree of modulus size, establishes a more perfect evaluation system for spatial similarity of parameter sequences, and presents an effective evaluation index for logging information. Results show that optimized grey correlation analysis based on optimal logging parameters is effective in Penglai A structure and can realize rapid and accurate quantitative evaluation of oil and gas bearing property of reservoir.