Please wait a minute...
E-mail Alert Rss
 
物探与化探  2020, Vol. 44 Issue (6): 1329-1335    DOI: 10.11720/wtyht.2020.1427
  地质调查·资源勘查 本期目录 | 过刊浏览 | 高级检索 |
基追踪弹性阻抗反演识别含气砂岩
郝亚炬1(), 高君2
1.东华理工大学 地球物理与测控技术学院,江西 南昌 330013
2.中国石油化工有限公司 勘探开发研究院,北京 100083
Gas sand prediction using basis pursuit elastic impedance inversion
HAO Ya-Ju1(), GAO Jun2
1. School of Geophysics and Measurement-Control Technology,East China University of Technology,Nanchang 330013,China
2. Petroleum Exploration and Production Research Institute,SINOPEC,Beijing 100083,China
全文: PDF(6904 KB)   HTML
输出: BibTeX | EndNote (RIS)      
摘要 

砂岩储层含气后地震波阻抗会显著降低,因此阻抗反演是对含气砂岩储层进行预测的常用方法。但砂岩储层的波阻抗值不仅取决于含流体性质,还与岩石的孔隙度、矿物结构组分等多种因素有关,即使砂岩储层含气,其波阻抗也可能高于高孔含水砂岩,因此,叠后地震阻抗反演结果在含气砂岩储层预测中存在较强的多解性。由于利用了含气砂岩的AVO异常特性,叠前弹性阻抗在含气砂岩储层预测中比叠后地震阻抗具有更高的可靠性。为了提高弹性反演结果的精度,将基追踪反演(basis pursuit inversion,BPI)算法引入叠前弹性阻抗反演。该方法是将地震信号投影到奇、偶子波库上,通过投影值求得每道的相对反射系数,然后进行道积分得到相对弹性波阻抗。相比于传统的稀疏脉冲反演(sparse spike inversion,SSI)算法,基追踪弹性反演算法不需要建立初始低频模型,可显著提高薄层分辨能力和反演精度。通过合成信号的试算和实际地震数据的反演表明,基追踪叠前弹性反演可有效地对砂岩储层的含气异常进行检测,并且相比于传统SSI算法具有更高的反演精度。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
郝亚炬
高君
关键词 基追踪反演弹性阻抗角道集含气砂岩预测    
Abstract

The impedance of sand reservoir will become lower if the pores are filled with natural gas,so the gas reservoir can be detected by using impedance inversion,which is a common used method.However,the impedance of sand reservoir can be influenced by many kinds of factors such as porosity and mineral composition.As a consequence,the impedance of gas sand may be higher than that of high porosity brine sandstone.In this case,mistake would be caused if post-stack impedance is only used to predict gas sand.Elastic impedance is more reliable than acoustic impedance,because gas sand reservoir can induce AVO anomaly.Simultaneously,in order to improve inversion resolution and accuracy,the authors introduce BP (Basis Pursuit) algorithm to complete elastic inversion.This algorithm is used to decompose seismic signal to even and odd wavelet dictionaries and then reflection coefficient can be obtained by the decomposition coefficients.The method proposed by the authors doesn't need initial low frequency model that traditional inversion method SSI (Sparse Spike Inversion) has to know beforehand. In this case,resolution and accuracy can be improved.The application to synthetic data and field data indicates that this method is more accurate than SSI.

Key wordsbasis pursuit inversion    elastic impedance    angle seismic gather    gas sand prediction
收稿日期: 2019-11-10      出版日期: 2020-12-29
:  P631.4  
基金资助:国家重大专项子课题(2016ZX05033-02);中国石油天然气集团公司科学研究与技术开发项目“大型地震处理解释软件平台开发与集成”(2016E-1004)
作者简介: 郝亚炬(1990-),男,讲师,博士,主要从事地震反演理论与算法等方面的研究工作。Email:haoyj_13@163.com
引用本文:   
郝亚炬, 高君. 基追踪弹性阻抗反演识别含气砂岩[J]. 物探与化探, 2020, 44(6): 1329-1335.
HAO Ya-Ju, GAO Jun. Gas sand prediction using basis pursuit elastic impedance inversion. Geophysical and Geochemical Exploration, 2020, 44(6): 1329-1335.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2020.1427      或      https://www.wutanyuhuatan.com/CN/Y2020/V44/I6/1329
Fig.1  任意反射系数脉冲对的奇偶分解
Fig.2  模型及叠前正演道集
Fig.3  对应图2中叠前道集的基追踪弹性反演
Fig.4  基追踪反演与稀疏脉冲反演结果比较
Fig.5  实际井的叠前正演
Fig.6  对应图5中合成道集的基追踪弹性反演
a—基追踪EI反演结果;b—0°EI与30°EI交会图
Fig.7  30°入射角时基追踪反演与稀疏脉冲反演结果比较
Fig.8  野外地震数据
a—叠后地震资料;b—基于CDP点处的叠前角道集
Fig.9  叠后基追踪反演结果
a—叠后基追踪反演反射系数剖面;b—叠后基追踪反演阻抗剖面
Fig.10  基追踪弹性反演结果
a—基追踪弹性反演反射系数剖面;b—基追踪弹性阻抗剖面
Fig.11  不同入射角井旁弹性阻抗反演结果
Fig.12  不同入射角的弹性阻抗剖面
a—3°弹性阻抗剖面;b—16°弹性阻抗剖面;c—26°弹性阻抗剖面
[1] Connolly P, Amoco B P. Elastic impedance[J]. The Leading Edge, 1999,18(4):438-452.
[2] He F B, You J, Chen K Y. Gas sand distribution prediction by prestack elastic inversion based on rock physics modeling and analysis[J]. Applied Geophysics, 2011,8(3):197-205.
[3] Hampson D, Schuelke J S, Quirein J A. Use of multi-attribute transforms to predict log properties from seismic data[J]. Exploration Geophysics, 2001,66(1):220-236.
[4] 郝亚炬, 文晓涛, 李忠, 等. 基于基追踪分解算法的薄层波阻抗反演[J]. 科学技术与工程, 2015,15(33):10-17.
[4] Hao Y J, Wen X T, Li Z, et al. Impedance inversion of thin-bed based on basis pursuit[J]. Science Technology and Engineering, 2015,15(33):10-17.
[5] 栾颖, 冯晅, 刘财, 等. 波阻抗反演技术的研究现状及发展[J]. 吉林大学学报:地球科学版, 2008,38(s1):94-98.
[5] Luan Y, Feng X, Liu C, et al. The research present and future of wave impedance inversion technique[J]. Journal of Jilin University:Earth Science Edition, 2008,38(s1):94-98.
[6] 芮国胜, 王林, 田文飚. 一种基于基追踪压缩感知信号重构的改进算法[J]. 电子测量技术, 2010,33(4):38-41.
[6] Rui G S, Wang L, Tian W B. Improved algorithm based basis pursuit for compressive sensing reconstruction[J]. Electronic Measurement Technology, 2010,33(4):38-41.
[7] 汪雄良, 王正明. 基于快速基追踪算法的图像去噪[J]. 计算机应用, 2005,25(10):2356-2358.
[7] Wang X L, Wang Z M. Image de-noising based on fast basis pursuit algorithm[J]. Computer Application, 2005,25(10):2356-2358.
[8] 孙干超, 王吉林. 基于ARM的说话人识别系统的研究与实现[J]. 电子器件, 2014,37(6):1151-1154.
[8] Sun G C, Wang J L. Speaker recognition based on ARM[J]. Chinese Journal of Electron Devices, 2014,37(6):1151-1154.
[9] Zhang R, Castagna J. Seismic sparse-layer reflectivity inversion using basis pursuit decomposition[J]. Geophysics, 2011,76(6):R147-R158.
[10] Zhang R, Sen M K, Srinivasan S. A prestack basis pursuit seismic inversion[J]. Geophysics, 2013,78(1):R1-R11.
doi: 10.1190/geo2011-0502.1
[11] Zoeppritz K. Ber reflexion und durchgang seismischer wellen durch unstetigkeitsflchen[J]. Nachrichten von der Kniglichen Gesellschaft der Wissenschaften zu Gttingen, 1919: 66-84.
[12] Aki K, Richards P G. Quantitative seismology:Theory and methods[M]. W. H. Freeman, 1980.
[13] Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit[J]. Society for Industrial and Applied Mathematics Review, 2001,43(1):129-159.
[14] Hao Y, Huang H, Luo Y, et al. Nonstationary acoustic-impedance inversion algorithm via a novel equivalent Q-value estimation scheme and sparse regularizations[J]. Geophysics, 2018,83(6):R681-R698.
[15] 石战战, 夏艳晴, 周怀来, 等. 一种基于L1-L1范数稀疏表示的地震反演方法[J]. 物探与化探, 2019,43(4):851-858.
[15] Shi Z Z, Xia Y Q, Zhou H L, et al. Seismic reflectivity inversion based on L1-L1-norm sparse representation[J]. Geophysical and Geochemical Exploration, 2019,43(4):851-858.
[1] 梁立锋, 刘秀娟, 张宏兵, 陈程浩, 陈锦华. 超参数对GRU-CNN混合深度学习弹性阻抗反演影响研究[J]. 物探与化探, 2021, 45(1): 133-139.
[2] 张红文, 刘喜恒, 周兴海, 李六五, 杜喜善, 王成泉. 全方位偏移成像技术在南马庄潜山构造带的应用[J]. 物探与化探, 2020, 44(1): 25-33.
[3] 陈飞旭, 李振春, 张凯, 孙琦, 尚江伟. 基于波动方程偏移的宽方位三维角道集提取[J]. 物探与化探, 2015, 39(4): 797-804.
[4] 时磊, 刘俊州, 董宁, 王箭波, 夏红敏, 王震宇. 扩展弹性阻抗反演技术在致密砂岩薄储层含气性预测中的应用[J]. 物探与化探, 2015, 39(2): 346-351.
[5] 孙瑞莹, 印兴耀, 王保丽, 张广智. 基于Metropolis抽样的弹性阻抗随机反演[J]. 物探与化探, 2015, 39(1): 203-210.
[6] 苏世龙, 贺振华, 戴晓云, 王九拴, 张辉, 辛华刚, 刘艳娜. 岩性油气藏地震保幅处理技术及其应用——以东部某油田岩性气藏为例[J]. 物探与化探, 2015, 39(1): 54-59.
[7] 杨孛, 李瑞, 杨滔. 测井曲线构建技术在BMM地区的应用[J]. 物探与化探, 2013, 37(2): 333-337.
[8] 杨海长, 李智, 徐建永, 周玉. 叠前反演在LHK地区烃类检测中的应用[J]. 物探与化探, 2011, 35(5): 666-670,688.
[9] 孙歧峰, 白清云. 转换横波阻抗的求取[J]. 物探与化探, 2011, 35(1): 93-96.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-3
版权所有 © 2021《物探与化探》编辑部
通讯地址:北京市学院路29号航遥中心 邮编:100083
电话:010-62060192;62060193 E-mail:whtbjb@sina.com