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反演技术和频谱成像技术在储层预测中的综合应用
引用本文:冯凯,查朝阳,钟德盈. 反演技术和频谱成像技术在储层预测中的综合应用[J]. 石油物探, 2006, 45(3): 262-266
作者姓名:冯凯  查朝阳  钟德盈
作者单位:1. 成都理工大学,四川,成都,610059
2. 北京艾普斯特能源技术有限公司,北京,100085
基金项目:特别感谢美国EPT公司提供的波阻抗反演软件EPS^T Mreservoir和频谱成像软件EPS^TM image及其详细的技术支持.
摘    要:井约束地震反演技术县有很好的垂向分辨能力,在储层横向变化不大时反演效果很好,但如果储层的横向变化十分复杂,反演技术的局限性就非常突出,要获得好的反常效果很困难。基于薄层反射调谐原理的频谱成像技术不依赖于井资料,只与地震资料的品质有关,对于储层边界,非均质及厚度的成像,分辨率尤其是横向分辨率要高于传统的宽带地震分辨率。中国东部H区块S构造带,主要目标地层厚度变化大,构造复杂,目标储层主要由砂岩、砾岩、凝灰质砾岩和火山碎屑岩组成,非均质性强。综合应用反演技术和频谱成像技术对其含油气储层的分布范围进行了预测,预测结果与验证井吻合很好。

关 键 词:储层预测  井约束地震反演  波阻抗  频谱成像  属性累积厚度
文章编号:1000-1441(2006)03-0262-05
收稿时间:2005-12-13
修稿时间:2005-12-132006-01-25

Integrated application between inversion and spectral image technology in the reservoir prediction.
Feng Kai,Zha Zhaoyang,Zhong Deying. Integrated application between inversion and spectral image technology in the reservoir prediction.[J]. Geophysical Prospecting For Petroleum, 2006, 45(3): 262-266
Authors:Feng Kai  Zha Zhaoyang  Zhong Deying
Affiliation:Chengdu University of Technology, Chengdu 610059, China
Abstract:We can get high vertical resolution by using well constraint inversion based on well datum, especially under the constraint of suitable geologic condition like little lateral variation of reservoir. The inversion effect is not satisfied when lateral variation of the reservoir is complicated. Spectral image technique based on bed tuning theory has higher resolution while imaging for reservoir boundary, heterogeneous medium and thickness than traditional wideband seismic display, especially its lateral resolution. Spectral image technique mainly depends on the quality of seismic data rather than well data. Well data constraint will impose less on the lateral variation of reservoir. Integrating the well constraint inversion with spectral image technologies, we have implemented reservoir prediction for S structure of H Block in eastern China; the prediction result is well consistent with the real data.
Keywords:reservoir prediction  well constraint inversion  impedance  spectral image  accumulation thickness of attributes
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