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物探与化探  2021, Vol. 45 Issue (6): 1402-1408    DOI: 10.11720/wtyht.2021.1364
  地质调查·资源勘查 本期目录 | 过刊浏览 | 高级检索 |
压制孔隙影响的流体敏感因子优选及其在烃类检测中的应用
王迪1(), 张益明1, 牛聪1, 黄饶1, 韩利2
1.中海油研究总院有限责任公司,北京 100028
2.中国海洋石油国际有限公司,北京 100028
The optimization of sensitive fluid factor removing the effect of porosity and its application to hydrocarbon detection
WANG Di1(), ZHANG Yi-Ming1, NIU Cong1, HUANG Rao1, HAN Li2
1. CNOOC Research Institute Co.,Ltd.,Beijing 100028,China
2. CNOOC International Ltd.,Beijing 100028,China
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摘要 

尼日尔三角洲盆地S区块发育深水扇沉积,高孔含水砂岩表现为振幅“亮点”和远道增强的AVO异常,其特征与油层类似,基于常规方法开展烃类检测存在多解性。针对该问题,笔者提出一种新的流体因子敏感性定量分析和优选方法,能够压制孔隙度造成的流体识别假象,达到“突出流体、压制孔隙影响”的目的。分析结果表明,λ/μ具有对流体性质敏感性高、对孔隙度敏感性低的特征,是本区开展烃类检测的最佳敏感流体因子。实际应用结果表明,利用该方法能够有效区分真“亮点”油层和假“亮点”水层,预测结果与已钻井更加吻合,有效提升了烃类检测成功率。

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王迪
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韩利
关键词 尼日尔三角洲亮点流体因子定量分析烃类检测    
Abstract

The deep-water turbidite sandstone reservoirs in Niger Delta basin have great oil-gas exploration potential.Drilling results in S Block area indicate that high-porosity water sandstones show "bright spot" and class II-III AVO anomaly,which are similar to features of oil sandstones. It is critical to remove the effect of porosity while fluid detection is conducted.However,conventional analysis method seldom considers the effect of porosity,and the selected fluid factor is sensitive to both hydrocarbon and porosity,which leads to inaccurate detection result.Therefore,in this study,a new quantitative evaluation method based on fluid and porosity substitution is proposed to choose the most sensitive fluid factor,which can highlight hydrocarbon and suppress the effect of porosity.The analysis result shows that λ/μ is the most suitable elastic parameter in this area and can be used to detect hydrocarbon.The real data application result shows that λ/μ can effectively distinguish "bright spot" water sandstones from oil sandstones, and the predicted results are well consistent with the drilling data, which proves the feasibility of this method.

Key wordsNiger Delta basin    bright spot    fluid factor    quantitative evaluation    hydrocarbon detection
收稿日期: 2021-01-20      出版日期: 2021-12-21
ZTFLH:  P631.4  
基金资助:国家科技重大专项项目(2017ZX05032-003)
作者简介: 王迪(1988-),男,硕士研究生,主要从事储层预测和流体检测方面的研究工作。 Email: wangdi4@cnooc.com.cn
引用本文:   
王迪, 张益明, 牛聪, 黄饶, 韩利. 压制孔隙影响的流体敏感因子优选及其在烃类检测中的应用[J]. 物探与化探, 2021, 45(6): 1402-1408.
WANG Di, ZHANG Yi-Ming, NIU Cong, HUANG Rao, HAN Li. The optimization of sensitive fluid factor removing the effect of porosity and its application to hydrocarbon detection. Geophysical and Geochemical Exploration, 2021, 45(6): 1402-1408.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2021.1364      或      https://www.wutanyuhuatan.com/CN/Y2021/V45/I6/1402
Fig.1  研究区位置示意
井名 钻探结果 孔隙度/% 厚度/m 含油饱和度/%
W1 油层 26.0 18.0 90%
W2 油层 23.4 26.5 85%
W3 水层 29.7 24.0 8%
Table 1  研究区已钻井结果
Fig.2  过W1、W2和W3井的连井地震剖面
Fig.3  叠后振幅影响因素分析
Fig.4  W1、W2和W3井旁地震道集
Fig.5  油层(a)及水层(b)AVO特征随孔隙度变化
Fig.6  不同流体、孔隙度的截距—梯度交会
弹性参数 σ AI/
(106 m-2·kg·s-1)
SI/
(106 m-2·kg·s-1)
μρ/
(1012 m-4·kg2·s-2)
λρ/
(1012 m-4·kg2·s-2)
λ/μ 泊松阻抗PI/
(106 m-2·kg·s-1)
流体项f/
(1012 m-4·kg2·s-2)
原状地层 0.2293 5.6825 3.3678 11.3420 9.6063 0.8470 0.9675 16.4115
流体替代 0.2973 6.3717 3.4223 11.7126 17.1739 1.4463 1.5804 24.2015
孔隙度替代 0.2231 5.0941 3.0413 9.2494 7.4515 0.8056 0.8364 13.0011
系数A 0.1281 0.0571 0.0080 0.0161 0.2825 0.2677 0.2405 0.1918
系数B 0.0137 0.0546 0.0509 0.1016 0.1263 0.0250 0.0723 0.1159
评价因子C 0.7918 0.0232 -0.7274 -0.7268 0.3821 0.8391 0.5357 0.2465
Table 2  流体和孔隙度替代后弹性参数值及敏感系数计算结果
Fig.7  不同弹性参数的流体敏感系数A(a)、孔隙度敏感系数B(b)和评价因子C(c)
Fig.8  λρ (a)及λ/μ (b) 流体识别效果对比
Fig.9  过W1、W2、W3井的λρ反演剖面(a)和流体因子λ/μ反演剖面(b)
Fig.10  R1180层均方根振幅(a)和流体因子λ/μ反演结果(b)
[1] 吕福亮, 贺训云, 武金云, 等. 世界深水油气勘探现状、发展趋势及对我国深水勘探的启示[J]. 中国石油勘探, 2007, 12(6):28-31.
[1] Lyu F L, He X Y, Wu J Y, et al. Current situation and tendency of deepwater oil and gas exploration in the world[J]. China Petroleum Exploration, 2007, 12(6):28-31.
[2] 李大伟, 李德生, 陈长民, 等. 深海扇油气勘探综述[J]. 中国海上油气, 2007, 19(1):18-24.
[2] Li D W, Li D S, Chen C M, et al. An overview of hydrocarbon exploration in deep submarine fans[J]. China Offshore Oil and Gas, 2007, 19(1):18-24.
[3] 江怀友, 赵文智, 闫存章, 等. 世界海洋油气资源与勘探模式概述[J]. 海相油气地质, 2008, 13(3):5-10.
[3] Jiang H Y, Zhao W Z, Yan C Z, et al. Review on marine petroleum resources and exploration models in the globe[J]. Marine Origin Petroleum Geology, 2008, 13(3):5-10.
[4] 邓荣敬, 邓运华, 于水, 等. 尼日尔三角洲盆地油气地质与成藏特征[J]. 石油勘探与开发, 2008, 35(6):755-762.
[4] Deng R J, Deng Y H, Yu S, et al. Hydrocarbon geology and reservoir formation characteristics of Niger delta Basin[J]. Petroleum Exploration and Development, 2008, 35(6):755-762.
[5] Ostrander W J. Plane wave reflection coefficients for gas sands at non-normal incidence[J]. Geophysics, 1984, 49(10):1637-1648.
doi: 10.1190/1.1441571
[6] Smith G C, Gidlow P M. Weighted stacking for rock property estimation and detection of gas[J]. Geophysical Prospecting, 1987, 35(9):993-1014.
doi: 10.1111/gpr.1987.35.issue-9
[7] Goodway B, Chen T W, Downton J. Improved AVO fluid detection and lithology discrimination using Lamé petrophysical parameters;“λρ”, “μρ”,& “λ/μ fluid stack”,from P and S inversions[C]// SEG Technical Program Expanded Abstracts, 1997, 16:183-186.
[8] Russell B H, Hedlin K, Hilterman F J, et al. Fluid-property discrimination with AVO:A Biot-Gassmann perspective[J]. Geophysics, 2003, 68(1):29-39.
doi: 10.1190/1.1543192
[9] 张玉洁, 刘洪, 崔栋, 等. 基于挤喷流效应的Russell流体因子推广及应用[J]. 地球物理学报, 2016, 59(10):3901-3908.
[9] Zhang Y J, Liu H, Cui D, et al. Construction and application of the Russell fluid factor with squirt flow effect[J]. Chinese Journal of Geophysics, 2016, 59(10):3901-3908.
[10] 姜仁, 欧阳永林, 曾庆才, 等. Russell流体因子在致密砂岩气层检测中的应用[J]. 天然气工业, 2017, 37(1):76-81.
[10] Jiang R, Ouyang Y L, Zeng Q C, et al. Application of the Russell fluid factor in tight sandstone gas detection[J]. Natural Gas Industry, 2017, 37(1):76-81.
[11] 郑静静, 印兴耀, 张广智. 流体因子关系分析以及新流体因子的构建[J]. 地球物理学进展, 2011, 26(2):579-587.
[11] Zheng J J, Yin X Y, Zhang G Z. Fluid factor analysis and the construction of the new fluid factor[J]. Progress in Geophysics, 2011, 26(2):579-587.
[12] 张广智, 郑静静, 印兴耀, 等. 基于Curvelet变换的角度流体因子提取技术[J]. 物探与化探, 2011, 35(4):505-510.
[12] Zhang G Z, Zheng J J, Yin X Y, et al. The technique for extracting angle fluid factor based on curvelet transform[J]. Geophysical and Geochemical Exploration, 2011, 35(4):505-510.
[13] 谢玉洪, 邓勇, 李芳, 等. 莺歌海盆地“暗点”型油气藏指示因子构建及应用[J]. 石油地球物理勘探, 2019, 54(6):1302-1309.
[13] Xie Y H, Deng Y, Li F, et al. A dim-spot reservoir indicative factor in the Yinggehai Basin[J]. OGP, 2019, 54(6):1302-1309.
[14] 宗兆云, 印兴耀, 张繁昌. 基于弹性阻抗贝叶斯反演的拉梅参数提取方法研究[J]. 石油地球物理勘探, 2011, 46(4):598-604.
[14] Zong Z Y, Yin X Y, Zhang F C. Elastic impedance Bayesian inversion for lame parameters extracting[J]. OGP, 2011, 46(4):598-604.
[15] 印兴耀, 张世鑫, 张繁昌, 等. 利用基于Russell近似的弹性波阻抗反演进行储层描述和流体识别[J]. 石油地球物理勘探, 2010, 45(3):373-380.
[15] Yin X Y, Zhang S X, Zhang F C, et al. Utilizing Russell Approximation-based elastic wave impedance inversion to conduct reservoir description and fluid identification[J]. OGP, 2010, 45(3):373-380.
[16] 李红梅. 弹性参数直接反演技术在储层流体识别中的应用[J]. 物探与化探, 2014, 38(5):970-975.
[16] Li H M. The application of elastic parameters direct inversion to reservoir fluid identification[J]. Geophysical and Geochemical Exploration, 2014, 38(5):970-975.
[17] 杨培杰, 董兆丽, 刘昌毅, 等. 敏感流体因子定量分析与直接提取[J]. 石油地球物理勘探, 2016, 51(1):158-164.
[17] Yang P J, Dong Z L, Liu C Y, et al. Sensitive fluid factor extraction and analysis[J]. OGP, 2016, 51(1):158-164.
[18] 桂金咏, 高建虎, 李胜军, 等. 面向实际储层的流体因子优选方法[J]. 石油地球物理勘探, 2015, 50(1):129-135.
[18] Gui J Y, Gao J H, Li S J, et al. Reservoir oriented fluid factor optimization method[J]. OGP, 2015, 50(1):129-135.
[19] 张世鑫. 基于地震信息的流体识别方法研究与应用[D]. 东营:中国石油大学(华东), 2012.
[19] Zhang S X. Methodology and application of fluid identification with seismic information[D]. Dongying:China University of Petroleum, 2012.
[20] 李英, 秦德海. 基于流体替代的敏感弹性参数优选及流体识别在渤海B 油田的应用[J]. 物探与化探, 2018, 42(4):662-667.
[20] Li Y, Qin D H. The optimization of sensitive elastic parameters based on fluid substitution and the application of fluid identification to Bohai B Oilfield[J]. Geophysical and Geochemical Exploration, 2018, 42(4):662-667.
[21] Yin X Y, Zhang S X. Bayesian inversion for effective pore-fluid bulk modulus based on fluid-matrix decoupled amplitude variation with offset approximation[J]. Geophysics, 2014, 79(5):R221-R232.
doi: 10.1190/geo2013-0372.1
[22] 冉然, 宋建国. 基于Zoeppritz方程的纵横波模量反演[J]. 物探与化探, 2017, 41(4):707-714.
[22] Ran R, Song J G. Compressional and shear modulus inversion based on Zoeppritz equation[J]. Geophysical and Geochemical Exploration, 2017, 41(4):707-714.
[23] 邓炜, 印兴耀, 宗兆云. 等效流体体积模量直接反演的流体识别方法[J]. 石油地球物理勘探, 2017, 52(2):315-325.
[23] Deng W, Yin X Y, Zong Z Y. Fluid identification based on direct inversion of equivalent fluid bulk modulus[J]. OGP, 2017, 52(2):315-325.
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