基于粒子群优化最小二乘支持向量机的非线性AVO反演
发布时间：2019-02-19 21:35
【摘要】：为了求解非线性AVO反演问题,本文提出基于粒子群算法和最小二乘支持向量机的非线性AVO反演方法,并用粒子群算法优化最小二乘支持向量机的参数。即首先通过精确Zoeppritz方程正演得到角道集,并进行动校正和部分角度叠加;然后运用最小二乘支持向量机方法建立反射振幅与弹性参数之间的非线性模型;最后以此非线性模型对地震道集数据进行反演。模型数据和实际资料的反演结果表明,该方法克服了常规广义线性AVO反演在远炮检距及弹性参数纵向变化大等情况下的缺陷,可直接从实际地震道集数据中提取较高精度的地层弹性参数,具有快速稳健、抗噪能力强的优点。
[Abstract]:In order to solve the nonlinear AVO inversion problem, a nonlinear AVO inversion method based on particle swarm optimization (PSO) and least square support vector machine (LS-SVM) is proposed in this paper. The parameters of LS-SVM are optimized by particle swarm optimization (PSO). First, the angular gathers are obtained by accurate Zoeppritz equation, then the nonlinear model between reflection amplitude and elastic parameters is established by using least square support vector machine (LS-SVM), and the NMO and partial angle superposition are carried out. Finally, the nonlinear model is used for inversion of seismic gather data. The inversion results of the model data and the actual data show that the method overcomes the defects of the conventional generalized linear AVO inversion under the condition of large longitudinal variation of the far offset and elastic parameters. The formation elastic parameters can be extracted directly from the actual seismic gather data, which has the advantages of fast stability and strong anti-noise ability.
【作者单位】： 中国地质大学(北京)地球物理与信息技术学院;中国石油华北油田公司勘探开发研究院;中国石化勘探分公司研究院;
【基金】：国家高技术研究发展计划项目(2013AA064201) 国家“十二五”油气田及煤层气科技重大专项专题(2011ZX05033-004)联合资助
【分类号】：P631.4
[Abstract]:In order to solve the nonlinear AVO inversion problem, a nonlinear AVO inversion method based on particle swarm optimization (PSO) and least square support vector machine (LS-SVM) is proposed in this paper. The parameters of LS-SVM are optimized by particle swarm optimization (PSO). First, the angular gathers are obtained by accurate Zoeppritz equation, then the nonlinear model between reflection amplitude and elastic parameters is established by using least square support vector machine (LS-SVM), and the NMO and partial angle superposition are carried out. Finally, the nonlinear model is used for inversion of seismic gather data. The inversion results of the model data and the actual data show that the method overcomes the defects of the conventional generalized linear AVO inversion under the condition of large longitudinal variation of the far offset and elastic parameters. The formation elastic parameters can be extracted directly from the actual seismic gather data, which has the advantages of fast stability and strong anti-noise ability.
【作者单位】： 中国地质大学(北京)地球物理与信息技术学院;中国石油华北油田公司勘探开发研究院;中国石化勘探分公司研究院;
【基金】：国家高技术研究发展计划项目(2013AA064201) 国家“十二五”油气田及煤层气科技重大专项专题(2011ZX05033-004)联合资助
【分类号】：P631.4
【相似文献】
相关期刊论文 前10条
1 傅文敏;AVO模拟分析泥盆系礁体勘探的困难和可能性[J];重庆石油高等专科学校学报;1997年01期
2 朱兆林,王永刚,曹丹平;裂缝性储层AVO检测方法综述[J];勘探地球物理进展;2004年02期
3 胡晓丽;谭大龙;;孔隙形状对AVO响应影响的研究[J];岩性油气藏;2010年03期
4 李中元;北极地区天然气水合物的AVO属性研究[J];石油物探;2004年S1期
5 何涛;史，
本文编号：2426899
本文链接：https://www.wllwen.com/kejilunwen/diqiudizhi/2426899.html
