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物探与化探  2024, Vol. 48 Issue (1): 98-104    DOI: 10.11720/wtyht.2024.2567
  方法研究·信息处理·仪器研制 本期目录 | 过刊浏览 | 高级检索 |
考虑软矿物纵横比的页岩岩石物理建模及其应用
杨骐羽1,2(), 李景叶1,2, 吴凡1,2, 李文瑾1,2, 崔津铭1,2
1.油气资源与探测国家重点实验室,北京 102249
2.中国石油大学(北京) 地球物理学院,北京 102249
A petrophysical model of shales considering soft-mineral aspect ratios and its application
YANG Qi-Yu1,2(), LI Jing-Ye1,2, WU Fan1,2, LI Wen-Jin1,2, CUI Jin-Ming1,2
1. State Key Laboratory of Petroleum Resource and Prospecting,Beijing 102249,China
2. College of Geophysics,China University of Petroleum(Beijing),Beijing 102249,China
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摘要 

以往针对页岩储层的岩石物理建模常忽略孔隙类型与软矿物纵横比对弹性模量的影响。本文同时考虑孔隙类型、孔隙形状与软矿物纵横比,建立横向各向同性页岩岩石物理模型:将固体矿物分为硬矿物与软矿物两类,考虑软矿物的各向异性特征与形状变化;基于储层实际情况将孔隙分为粒内孔、有机孔与粒间孔三类,孔隙形状分为硬孔隙与软孔隙两种;最后,利用粒子群法反演输入参数,进一步计算纵横波速度、各向异性参数与岩石力学参数。结合实际资料应用,用已知测井横波速度与各向同性岩石力学计算结果进行对比,结果表明该模型的应用效果较好。

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杨骐羽
李景叶
吴凡
李文瑾
崔津铭
关键词 软矿物纵横比孔隙纵横比横向各向同性岩石物理模型页岩横波速度预测    
Abstract

Previous petrophysical modeling of shale reservoirs often ignored the influence of pore types and soft-mineral aspect ratios on the elastic modulus.This study built a petrophysical model for transversely isotropic shales considering pore types and shapes,and soft-mineral aspect ratios.In this study,solid minerals were divided into hard and soft minerals,and soft minerals'anisotropic characteristics and shape changes were considered.According to the actual conditions of reservoirs, pores were categorized into intragranular,organic,and intergranular pores,and they were classified into stiff and soft pores based on their shapes.Finally,the input parameters were inverted using the particle swarm optimization algorithm to further calculate compressional and shear wave velocities,anisotropy parameters,and rock mechanical parameters.Combined with the actual data application,the results of this study were compared with the known results of shear wave velocity and isotropic rock mechanical calculation,suggesting that the model in this study is effective.

Key wordssoft-mineral aspect ratio    pore aspect ratio    transverse isotropy    petrophysical model    shale    shear-wave velocity prediction
收稿日期: 2022-11-25      修回日期: 2023-09-08      出版日期: 2024-02-20
ZTFLH:  P631.4  
基金资助:国家自然科学基金项目(41774131);国家自然科学基金项目(41774129);国家重点研发计划项目(2019YFC0312000)
作者简介: 杨骐羽(1999-),博士在读,专业为地质资源与地质工程,研究重点为地震反演与储层预测、页岩气“甜点”预测。Email:2021310418@student.cup.edu.cn
引用本文:   
杨骐羽, 李景叶, 吴凡, 李文瑾, 崔津铭. 考虑软矿物纵横比的页岩岩石物理建模及其应用[J]. 物探与化探, 2024, 48(1): 98-104.
YANG Qi-Yu, LI Jing-Ye, WU Fan, LI Wen-Jin, CUI Jin-Ming. A petrophysical model of shales considering soft-mineral aspect ratios and its application. Geophysical and Geochemical Exploration, 2024, 48(1): 98-104.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2024.2567      或      https://www.wutanyuhuatan.com/CN/Y2024/V48/I1/98
Fig.1  测井曲线
Fig.2  岩石物理建模流程
组分 体积模量/GPa 剪切模量/GPa
矿物 石英 37 44
长石 37.5 15
黏土 2.9 2.7
干酪根 21 7
流体 天然气 0.01 0
2.2 0
Table 1  各组分弹性模量[21-22]
Fig.3  单一孔与三类孔对速度的影响
Fig.4  不同孔隙占比对速度的影响
Fig.5  软孔隙占比对速度的影响
Fig.6  软孔隙占比对Thomsen各向异性参数的影响
Fig.7  软矿物纵横比对速度的影响
Fig.8  软矿物纵横比对Thomsen各向异性参数的影响
Fig.9  岩石物理参数反演流程
Fig.10  反演曲线与模型得到的速度曲线
Fig.11  各向异性参数与岩石力学参数计算结果
[1] Jones L E A, Wang H F. Ultrasonic velocities in Cretaceous shales from the Williston Basin[J]. Geophysics, 1981, 46(3):288-297.
doi: 10.1190/1.1441199
[2] Hornby B E, Schwartz L M, Hudson J A. Anisotropic effective-medium modeling of the elastic properties of shales[J]. Geophysics, 1994, 59(10):1570-1583.
doi: 10.1190/1.1443546
[3] 原宏壮. 各向异性介质岩石物理模型及应用研究[D]. 北京: 中国石油大学(北京), 2007.
[3] Yuan H Z. Study of anisotropic rock physics model and application[D]. Beijing: China University of Petroleum, 2007.
[4] Bandyopadhyay K. Seismic anisotropy-geological causes and its implications to reservior geophysics[D]. Stanford University, 2009.
[5] Wu X, Chapman M, Li X Y, et al. Anisotropic elastic modeling for organic shales[C]// 74th Conference and Exhibition,EAGE,Extended Abstracts, 2012.
[6] 胡起, 陈小宏, 李景叶. 基于单孔隙纵横比模型的有机页岩横波速度预测方法[J]. 地球物理学进展, 2014, 29(5):2388-2394.
[6] Hu Q, Chen X H, Li J Y. Shear velocity prediction for organic shales based on the single aspect ratio model[J]. Progress in Geophysics, 2014, 29(5):2388-2394.
[7] 胡起. 页岩气储层岩石物理模型的构建及其应用[D]. 北京: 中国石油大学(北京), 2014.
[7] Hu Q. Construction and application of the rock physics model for shale gas reservoirs[D]. Beijing: China University of Petroleum, 2014.
[8] 王璞, 吴国忱. 基于自相容近似的致密储层岩石物理建模[J]. 地球物理学进展, 2015, 30(5):2233-2238.
[8] Wang P, Wu G C. The rock physics modeling for tight reservoir based on the self-consistent approximation[J]. Progress in Geophysics, 2015, 30(5):2233-2238.
[9] 张琦斌, 郭智奇, 刘财, 等. 针对有机质微观特性的页岩储层岩石物理建模及应用[J]. 地球物理学进展, 2018, 33(5):2083-2091.
[9] Zhang Q B, Guo Z Q, Liu C, et al. Rock physics model and its applications in the Longmaxi shale based on the quantification of microstructural properties of organic matter[J]. Progress in Geophysics, 2018, 33(5):2083-2091.
[10] Ruiz F, Azizov I. Tight shale elastic properties using the soft-porosity and single aspect ratio models[C]// SEG Technical Program Expanded Abstracts 2011,Society of Exploration Geophysicists, 2011:2241-2245.
[11] Ruiz F, Cheng A. A rock physics model for tight gas sand[J]. The Leading Edge, 2010, 29(12):1484-1489.
doi: 10.1190/1.3525364
[12] 桂俊川, 马天寿, 陈平. 横观各向同性页岩岩石物理模型建立——以龙马溪组页岩为例[J]. 地球物理学报, 2020, 63(11):4188-4204.
doi: 10.6038/cjg2020N0294
[12] Gui J C, Ma T S, Chen P. Rock physics modeling of transversely isotropic shale:an example of the Longmaxi formation in the Sichuan basin Chinese[J]. Chinese Journal of Geophysics, 2020, 63(11):4188-4204.
[13] 张益明, 秦小英, 郭智奇, 等. 针对致密砂岩气储层复杂孔隙结构的岩石物理模型及其应用[J]. 吉林大学学报:地球科学版, 2021, 51(3):927-939.
[13] Zhang Y M, Qin X Y, Guo Z Q, et al. Petrophysical model for complex pore structure and its applications in tight sand gas reservoirs[J]. Journal of Jilin University:Earth Science Edition, 2021, 51(3):927-939.
[14] 刘致水, 包乾宗, 刘俊州, 等. 一种简化的二维规则多边形孔隙岩石物理模型[J]. 石油地球物理勘探, 2022, 57(1):140-148.
[14] Liu Z S, Bao Q Z, Liu J Z, et al. A simplified 2D petrophysical model for regular polygon pores[J]. Oil Geophysical Prospecting, 2022, 57(1):140-148.
[15] 梁晓伟, 关梓轩, 牛小兵, 等. 鄂尔多斯盆地延长组7段页岩油储层储集性特征[J]. 天然气地球科学, 2020, 31(10):1489-1500.
[15] Liang X W, Guan Z X, Niu X B, et al. Reservoir characteristics of shale oil in Chang 7 Member of Yanchang Formation,Ordos Basin[J]. Natural Gas Geoscience, 2020, 31(10):1489-1500.
[16] 曹尚, 李树同, 党海龙, 等. 鄂尔多斯盆地东南部长7段页岩孔隙特征及其控制因素[J]. 新疆石油地质, 2022, 43(1):11-17.
[16] Cao S, Li S T, Dang H L, et al. Pore characteristics and controlling factors of Chang 7 shale in Southeastern Ordos Basin[J]. Xinjiang Petroleum Geology, 2022, 43(1):11-17.
[17] Voigt W. Lehrbuch der Kristallphysik:Teubner[M]. Leipzig, 1928:1-20.
[18] Reuss A. Berechnung der flieβgrenze von mischkristallen auf grund der plastizitätsbedingung für einkristalle[J]. ZAMM-Journal of Applied Mathematics and Mechanics, 1929, 9(1):49-58.
doi: 10.1002/zamm.v9:1
[19] Berryman J G. Single-scattering approximations for coefficients in Biot's equations of poroelasticity[J]. The Journal of the Acoustical Society of America, 1992, 91(2):551-571.
doi: 10.1121/1.402518
[20] Brown R J S, Korringa J. On the dependence of the elastic properties of a porous rock on the compressibility of the pore fluid[J]. Geophysics, 1975, 40(4):608-616.
doi: 10.1190/1.1440551
[21] Blangy,Jean-Pierre Dominique. Integrated seismic lithologic interpretation:The petrophysical basis.(Volumes I and II)[D]. Stanford University,1992.
[22] Carmichael R S. Practical handbook of physical properties of rocks and minerals(1988)[M]. CRC Press, 2017.
[23] Thomsen L. Weak elastic anisotropy[J]. Geophyscis, 1986, 51(10):1954-1966.
[24] 桂俊川, 陈平, 马天寿. 正交各向异性岩石弹性参数的空间展布[J]. 西南石油大学学报:自然科学版, 2019, 41(3):13-28.
[24] Gui J C, Chen P, Ma T S. The spatial distribution of elastic parameters of Orthotropic Rocks[J]. Journal of Southwest Petroleum University:Science & Technology Edition, 2019, 41(3):13-28.
[25] Guo Z Q, Chapman M, Li X Y. A shale rock physics model and its application in the prediction of brittleness index,mineralogy,and porosity of the Barnet Shale[C]// SEG Technical Program Expanded Abstracts 2012,Society of Exploration Geophysicists, 2012:1-5.
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