Title

Frequency-dependent AVO inversion based on Gray reflection coefficient formula

单位

(1.成都理工大学油气藏地质及开发工程国家重点实验室,四川成都610059;2.成都理工大学地球勘探与信息技术教育部重点实验室,四川成都610059)

Organization

(1.State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation,Chengdu University of Technology,Chengdu 610059,China;2.Key Laboratory of Earth Exploration and Information Techniques of Ministry of Education,Chengdu University of Technology,Chengdu 610059,China)

摘要

地震波传播过程中的频散现象对于流体识别至关重要,而常规的AVO反演技术没有考虑地震波在传播过程中的能量衰减和速度频散,忽略了频率因素,影响流体识别效果。基于Gray的λ-μ-ρ反射系数公式,通过依赖频率的AVO反演,构建了新的频散属性Iλ和Iμ,将其作为新的流体识别因子可以识别出含流体介质所引起的频散现象。模型试算和实际数据处理结果表明,该频散属性可以较好地识别出含流体储层,并且对不同流体的敏感性存在差异,频散属性Iλ可以更加准确地识别出含气储层,且受背景干扰很小。因此,基于Gray反射系数公式的频变AVO反演方法得到的频散因子对于有效储层的识别具有重要意义,为利用频散属性进行流体识别提供了一条有效途径。

Abstract

The dispersion phenomenon is highly relevant for the identification of different fluids.Conventional AVO technology does not take into account attenuation and velocity dispersion in seismic wave propagation,and it also ignores the frequency factor.New dispersion attributes related to Lame coefficient and shear modulus are constructed via frequency-dependent AVO inversion based on the Gray reflection coefficient formula.The new dispersion attributes can be used as new fluid identification factors to identify the dispersion phenomenon caused by a fluid-saturated medium.Synthetic data and field data tests demonstrated that the dispersion attributes can identify the fluid-saturated reservoir effectively,and its sensitivity is different for each different fluid.The Lame coefficient dispersion attribute can indicate the gas reservoir more accurately and is less affected by the background value.The proposed method is effective for reservoir and fluid identification.

关键词：

依赖频率的AVO; 速度频散; 时频分析; 流体识别; 频散属性;

Keywords:

frequency-dependent AVO,; velocity dispersion,; time-frequency analysis,; fluid identification,; dispersion attribute;

基金项目

国家自然科学基金项目(41374134、41574130)、国家科技重大专项(2016ZX05014-001-009)、四川省青年科技创新研究团队项目(2016TD0023)和成都理工大学优秀科研创新团队培育计划(KYTD201410)联合资助。

DOI

10.3969/j.issn.1000-1441.2018.02.015

基于Gray反射系数的频变AVO反演