Abstract: Well logging data is the basic data for pore pressure evaluation. The well logging data from an area in Junggar basin was used to study the pore pressure. Through regional study of the pore pressure, abnormal high pressure distribution was recognized. After analyzing the limitation of the traditional pore pressure prediction methods, a new method based on the effective pressure theorem and the acoustic velocity model was proposed. The clay content, permeability and acoustic velocity were calculated from related well logging data and the vertical effective stress was computed from sonic velocity model. In addition, the overburden pressure was also calculated from density logging data. Finally, the pore pressure was calculated according to the effective pressure theorem. The acoustic velocity model was built by regression support vector machine through nonlinear regression of the related logging data and the pressure data. The actual application indicates that the method can predict abnormal pore pressure accurately, which provides foundations for drilling engineering design and improves the level of drilling technology. What is more, it has a significant application value in preventing engineering accidents, decreasing stratum pollution, and saving drilling cost.