阈值约束的加权K均值聚类自动速度拾取方法OA

In conventional K-means clustering,the number of clusters and the initial values need to be predeter-mined,and the picking result is the geometric center of the energy cluster and is greatly influenced by the initial values.This paper proposes an automatic velocity picking method based on weighted K-means clustering with threshold constraints.Multiple rectangles of appropriate length are obtained by applying a variable velocity point threshold.The number of clustering centers,initial time,and initial velocity are obtained with the rectangles and prior velocity.At the same time,the prior velocity is used to limit the velocity picking range,and then the con-stant threshold and adaptive threshold are used to eliminate the velocity points with small amplitudes,reduce the number of velocity points involved in the calculation,and improve calculation efficiency.The weighted K-means clustering algorithm uses the amplitude of velocity points to calculate the weights,and removes the points far away from the center step by step through the distance threshold,so that the cluster center overlaps with the energy cluster center.Finally,multiples are eliminated by comparing with the slope of the prior velocity to make the picking result more accurate.The processing of model and actual data shows that the method proposed in this paper can intelligently pick up seismic velocity under the premise of ensuring accuracy and has high effi-ciency.