The thickness imaging of channels using multiple-frequency components analysis

被引:10
作者
Ye, Yan [1 ,2 ]
Zhang, Bo [2 ]
Niu, Cong [3 ]
Qi, Jie [4 ]
Zhou, Huailai [1 ]
机构
[1] Chengdu Univ Technol, Coll Geophys, Chengdu, Sichuan, Peoples R China
[2] Univ Alabama, Dept Geol Sci, 2003 Bevill Bldg, Tuscaloosa, AL 35401 USA
[3] CNOOC Res Inst, Beijing, Peoples R China
[4] Univ Oklahoma, ConocoPhillips Sch Geol & Geophys, Norman, OK 73019 USA
来源
INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION | 2019年 / 7卷 / 01期
关键词
90-DEGREES-PHASE WAVELETS; INTERPRETIVE ADVANTAGES; COLOR; RESOLUTION; ATTRIBUTES; THIN;
D O I
10.1190/INT-2018-0064.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Blending of different frequency components of seismic traces is a common way to estimate the relative time thickness of the formation. Red, blue, and green (RGB) color blending is one of the most popular blending models in analyzing multiple seismic attributes. Geologists and geophysicist interpreters typically associate low-frequency components (formations with the largest thickness value) with a red color, medium-frequency components (formations with a medium thickness value) with a green color, and high-frequency components (formations with the smallest thickness value) with a blue color for the thickness estimation of thin beds using frequency components. However, we found that the same result of RGB blending may come from different sets of three frequency components. As a result, the same blended color may correspond to several different time thicknesses. It is also very difficult to interpret the corresponding thickness of the blended colors such as white and yellow. To avoid the ambiguity of time-thickness estimation using RGB blending, we have estimated the time thickness of the thin beds using all of the frequency components in a user-defined frequency band instead of only three frequency components. Our workflow begins with the normal seismic spectral decomposition. Considering that the different reflectivity pairs with a different time thickness have a different amplitude spectrum, we then use the self-organizing map to cluster the decomposed amplitude spectra of seismic traces. We finally assign each cluster with a relative thickness by comparing the clustered results with well logs.
引用
收藏
页码:B1 / B8
页数:8
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