The Ocean-Bottom Nodes (OBN) seismic exploration technique can not only obtain all-dimensional fidelity data, but also improve the repeatability of 4D exploration and the reservoir monitoring results. The multi-component seismic data acquired by OBN seismic exploration contains P- and S-wave information of marine sediments, which provides abundant data for offshore oil and gas exploration and reservoir monitoring. In this paper, in order to obtain the velocity distribution of sediments and provide a basis for migration velocity modeling and oil and gas identification, based on OBN seismic data, linear traveltime interpolation ray tracing forward algorithm and particle swarm optimization nonlinear inversion algorithm are comprehensively adopted to perform joint inversion of P- and S-waves. A theoretical model is first created to verify the validity and adaptability of the inversion algorithm, and then the joint inversion of actual OBN data is carried out to determine the P- and S-wave velocities. The experimental results of theoretical model and actual OBN data test show that the method is feasible, and the joint inversion of P- and S-wave velocity using the method has high accuracy.

海洋底节点（OBN）地震勘探技术不仅可以获取全方位的保真度数据，而且还可以提高4D勘探的可重复性和储层监测结果。OBN地震勘探获得的多分量地震数据包含海洋沉积物的P波和S波信息，为海上油气勘探和储层监测提供了丰富的数据。为了获得沉积物的速度分布，为运移速度建模和油气识别提供依据，在OBN地震资料的基础上，综合采用线性行进时间插值射线追踪正演算法和粒子群优化非线性反演算法。进行P波和S波的联合反演。首先创建一个理论模型以验证反演算法的有效性和适应性，然后对实际OBN数据进行联合反演以确定P波和S波速度。理论模型和实际OBN数据试验的实验结果表明，该方法是可行的，并且利用该方法联合反演P波和S波速度具有较高的精度。