CFP技术层间多次波预测及Curvelet域相减方法

J4 ›› 2011, Vol. 41 ›› Issue (3): 907-914.

CFP技术层间多次波预测及Curvelet域相减方法

王德利¹|党丹¹|刘伟明²|张亚红³

1.吉林大学地球探测科学与技术学院|长春130026;
2.中石油勘探开发研究院西北分院|兰州730020;
3.中国石化石油物探技术研究院|南京210014

收稿日期:2010-06-10 出版日期:2011-05-26 发布日期:2011-05-26
作者简介:王德利(1973-)|男|山东莒南人|教授|博士生导师|主要从事各向异性介质波场正、反演理论和高精度地震勘探研究|E-mail:wangdeli@jlu.edu.cn
基金资助:
国家科技重大专项（2008ZX05023-05-013）

Internal Multiples Prediction Based on CFP Approach and Curvelet Domain Subtraction

WANG De-li¹, DANG Dan¹|LIU Wei-ming², ZHANG Ya-hong³

1.College of GeoExploration Science and Technology|Jilin University|Changchun130026, China;
2.Research Institute of Petroleum Exploration and Development-Northwest Petrochina|Lanzhou730020, China;
3.SINOPEC Geophysical Research Institute|Nanjing210014, China

Received:2010-06-10 Online:2011-05-26 Published:2011-05-26

摘要/Abstract

摘要：

在常规表面有关多次波压制（SRME）方法的基础上，利用共聚焦点（CFP）道集代替SRME方法中的炮集记录，对基于CFP技术的层间多次波压制方法进行了研究。通过在理论数据中加入噪声，验证了该方法具有一定的抗噪能力。利用切除处理后的CFP道集代替炮记录，能够很好地预测出与目标界面相关的层间多次波。在匹配相减的处理过程中，分别采用常规的相减法和Curvelet阈值减去法。通过2种方法的相减效果对比可以看出，在Curvelet域实现多次波的减去较常规减去法能够取得更好的效果。

关键词: 噪声压制, CFP道集, 层间多次波压制, Curvelet阈值法

Abstract:

Internal multiple elimination method has been studied based on the conventional surface related multiple elimination (SRME) using Common-Focus-Point (CFP)gathers instead of shots gathers. Noisy data results prove the ability of the method. We use muted CFP gather instead of common shot gather in the traditional surface related multiple elimination approach to predict internal multiples related to a target layer. At the matching and subtraction step, the curvelet based on thresholding algorithm is applied. The comparison of the results from curvelet thresholding and direct subtraction shows that the former method provides a better result.

Key words: noise abatement, CFP gathers, internal multiple elimination, Curvelet threshold

中图分类号:

P631.4

王德利, 党丹, 刘伟明, 张亚红. CFP技术层间多次波预测及Curvelet域相减方法[J]. J4, 2011, 41(3): 907-914.

WANG De-li, DANG Dan, LIU Wei-ming, ZHANG Ya-hong. Internal Multiples Prediction Based on CFP Approach and Curvelet Domain Subtraction[J]. J4, 2011, 41(3): 907-914.

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