首页 | 官方网站   微博 | 高级检索  
     


Automatic stacking‐velocity estimation using similarity‐weighted clustering
Authors:Guochang Liu  Chao Li  Xingye Liu  Qiang Ge  Xiaohong Chen
Affiliation:1. China University of Petroleum (Beijing), State Key Laboratory of Petroleum Resource and Prospecting, and National Engineering Laboratory for Offshore Oil Exploration, Beijing, China;2. PetroChina Research Institute of Petroleum Exploration & Development‐Langfang Branch, Langfang, China
Abstract:Local seismic event slopes contain subsurface velocity information and can be used to estimate seismic stacking velocity. In this paper, we propose a novel approach to estimate the stacking velocity automatically from seismic reflection data using similarity‐weighted k‐means clustering, in which the weights are local similarity between each trace in common midpoint gather and a reference trace. Local similarity reflects the local signal‐to‐noise ratio in common midpoint gather. We select the data points with high signal‐to‐noise ratio to be used in the velocity estimation with large weights in mapped traveltime and velocity domain by similarity‐weighted k‐means clustering with thresholding. By using weighted k‐means clustering, we make clustering centroids closer to those data points with large weights, which are more reliable and have higher signal‐to‐noise ratio. The interpolation is used to obtain the whole velocity volume after we have got velocity points calculated by weighted k‐means clustering. Using the proposed method, one obtains a more accurate estimate of the stacking velocity because the similarity‐based weighting in clustering takes into account the signal‐to‐noise ratio and reliability of different data points in mapped traveltime and velocity domain. In order to demonstrate that, we apply the proposed method to synthetic and field data examples, and the resulting images are of higher quality when compared with the ones obtained using existing methods.
Keywords:Automatic velocity estimation  Local similarity  Weighted clustering  Local seismic event slopes
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号