The seismic response of the carboniferous ultra-deep thin sand layer in Tahe Oilfield is complex. The interval transit time and density logging curve are less sensitive to reservoirs，and the seismic attribute and the existing inversion methods cannot meet the requirements of fine development of oil and gas reservoirs in terms of reservoir prediction accuracy. Therefore，this paper proposes a pseudo-acoustic wave log constraint inversion method with seismic bipolarity transform based on bio-inspired algorithm. Specifically，the paper uses the bio-inspired algorithm to perform bipolarity transform on seismic data with different phases to make the date bipolar，which enhances the visual resolution of the data. In addition，most of the thin sand layers have corresponding seismic reflection events，which improves the relationships between thin sand layers and seismic responses. Then，the paper reconstructs pseudo-acoustic wave by self potential and natural gamma log curves to strengthen the reservoir sensitivity of inversion parameters. As a result，the inversion process only requires low-level log constraint，and the inversion results have a positive correlation with seismic data，which decreases the ambiguity and increases the reliability of reservoir prediction. The carboniferous ultra-deep thin sand layer，with a depth of 5 000 m and a thickness of more than 3 meters of Well S9702 area in Tahe Oilfield，can be identified by the proposed method and the error is small. The narrow channel morphology is relatively clear，with the distribution of sand bodies in line with the geological law.