首页 | 本学科首页   官方微博 | 高级检索  
     

频谱分解及地质模型反演新方法在滩坝砂沉积特征及发育模式研究中的应用
引用本文:郭建卿,林承焰. 频谱分解及地质模型反演新方法在滩坝砂沉积特征及发育模式研究中的应用[J]. 中国石油大学学报(自然科学版), 2013, 37(3): 37-43
作者姓名:郭建卿  林承焰
作者单位:中国石油大学地球科学与技术学院,山东青岛,266580
摘    要:基于研究区三维高精度地震资料,根据地震沉积学原理,利用频谱分解、地震反演等岩性地球物理技术,并结合地质、测井、录井资料,对博兴油田沙四上亚段滩坝砂储层进行有效预测。结果表明:30 Hz为最佳调谐频率值;沙四上中部砂体最发育,沉积特征较为显著;滩坝砂经历了一次明显"湖退砂进"的沉积演化过程;研究区滩坝砂沉积模式呈湖退进积"坝"砂沉积为主,湖进退积"滩"砂、浅湖泥沉积为主的特征;滩坝砂沉积主要控制因素为水动力作用和古地形条件等。

关 键 词:滩坝砂  频谱分解  地震反演  单频切片  储层预测
收稿时间:2012-11-12

Application of new method of spectrum decomposition and seismic inversion in research of beach-bar sand sedimentary characteristics and development model
GUO Jian-qing and LIN Cheng-yan. Application of new method of spectrum decomposition and seismic inversion in research of beach-bar sand sedimentary characteristics and development model[J]. Journal of China University of Petroleum (Edition of Natural Sciences), 2013, 37(3): 37-43
Authors:GUO Jian-qing and LIN Cheng-yan
Affiliation:(School of Geosciences in China University of Petroleum,Qingdao 266580,China)
Abstract:Based on 3D high-precision seismic information and seismic sedimentology principle, beach-bar facies reservoir of Upper Es4 formation of Boxing Oilfield were predicted by using spectrum decomposition,seismic inversion of seismic sedimentology and geology, logging, borehole logging information. The results show that 30 Hz is the optimum tuning frequency. Sandstone is the most development in the middle part of Upper Es4 formation and its sedimentary characteristic is remarkble. Beach-bar sand boby undergoes obvious "sandstone sedimentation under the water regression period" evolution process. Beach-bar sedimentary model shows its giving priority to "bar" sand sedimentation under the water regression period, while "beach" sand and shallow lake mud sedimentation under the water transgression period. Hydrodynamism and palaeotopography condition are the main control factors of beach-bar sedimentation.
Keywords:beach-bar sand  spectrum decomposition  seismic inversion  monochromatic slice  reservoir prediction
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《中国石油大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《中国石油大学学报(自然科学版)》下载全文
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