Based on lithologic logging interpretation, the authors identified typical fracture sections according to their logging response calibrated by core data integrating drilling mud leakage, drilling break and production data. Then the typical logging response of fracture section was employed as training samples for Artificial Neural Network Pattern Recognition (NNPR). All the 76 wells in the Qijia buried hill were processed by applying the ability of NNPR including paralleling process, distribution information storage, powerful self-study and automatic weight value adjustment. Finally, a new fracture prediction method integrating core, conventional logging, test and production data was formulated, which has been proved to be effective by drilling.