曹思远,,
徐彦凯,
孙晓明,
陈思远
中国石油大学(北京)油气资源与勘探国家重点实验室, 北京 102249
基金项目: 国家重点研发计划"面向E级计算的能源勘探高性能应用软件系统与示范-基于压缩感知的海量数据高效并行处理-提高海量地震数据分辨率的研究"（ZX20170131）和国家自然科学基金（41674128）联合资助
详细信息
作者简介: 潘晓, 女, 1991年生, 山西运城人, 博士研究生, 主要从事地震信号处理方面研究.E-mail:panx_data@163.com
通讯作者: 曹思远, 男, 1962年生, 江苏启东人, 教授, 主要从事地震数据高分辨率处理方面的研究.E-mail:csy@cup.edu.cn
中图分类号: P631收稿日期:2019-11-02
修回日期:2020-05-26
上线日期:2020-11-05
The hydrocarbon detection technology based on synchrosqueezing wavelet transform
PAN Xiao,CAO SiYuan,,
XU YanKai,
SUN XiaoMing,
CHEN SiYuan
State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, China
More Information
Corresponding author: CAO SiYuan,E-mail:csy@cup.edu.cn
MSC: P631--> Received Date: 02 November 2019
Revised Date: 26 May 2020
Available Online: 05 November 2020
摘要
摘要:利用频谱分解得到的频率能量数据体进行属性提取，是烃类检测的常用手段之一.同步挤压小波变换能够提供高分辨率的时频谱，具有较好的应用潜力.本文以同步挤压小波变换为基础，提出了一套烃类检测方法，包括低频阴影检测、流体流动性估计以及高频能量衰减等，通过自适应选取优势频段，实现了多属性联合高精度刻画烃类的分布范围.实际资料处理结果与现有钻井情况吻合，具有较好的实用性，实现了对储层位置的高精度描述，对指导油气田开发具有重要的理论意义和实用价值.
关键词: 烃类检测/
同步挤压小波变换/
能量衰减梯度/
流体流动性/
低频阴影
Abstract:Spectral decomposition has been widely used to extract attributes which is also one of the most popular hydrocarbon detection technology. Synchrosqueezing wavelet transform provides high resolution time-frequency map indicating its great potential in field application. This paper proposes a set of technology based on synchrosqueezing wavelet transform, including low frequency shadow, fluid mobility and high frequency energy absorption analysis, which can select optimal frequency band adaptively and realize multi-attribute detecting hydrocarbon and describe the location of reservoir accurately. The field result matches the drilling result which proves this technique has good practical values and it can realize the description of reservoir's location with high precision.
Key words:Hydrocarbon detection/
Synchrosqueezing wavelet transform/
Energy attenuation gradient/
Fluid mobility/
Low-frequency shadow
PDF全文下载地址:
http://www.geophy.cn/data/article/export-pdf?id=5fed3366bfedb50717e0ce47
