不同边长及分辨率下陆相页岩微孔隙非均质特性分析——以鄂尔多斯盆地瑶科1井长7<sup>2</sup>页岩为例

尚彦军; 赵斌; 胡瑞林; 邵鹏

doi:10.11781/sysydz202001156

不同边长及分辨率下陆相页岩微孔隙非均质特性分析——以鄂尔多斯盆地瑶科1井长7²页岩为例

doi: 10.11781/sysydz202001156

尚彦军^{1, 2,},
赵斌³,
胡瑞林^{1, 2},
邵鹏^{1, 2}

1.
中国科学院地质与地球物理研究所, 中国科学院页岩气与地质工程重点实验室, 北京 100029
2.
中国科学院大学, 北京 100049
3.
中国石油塔里木油田分公司勘探开发研究院, 新疆库尔勒 841000

基金项目:

中国科学院战略先导专项 XDB10030103

详细信息

作者简介:
尚彦军(1967-), 男, 博士, 研究员, 从事水文工程地质科研教学工作。E-mail: jun94@mail.igcas.ac.cn

中图分类号: TE122.2
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- 被引次数: 0
出版历程
- 收稿日期: 2019-07-22
- 修回日期: 2019-12-01
- 刊出日期: 2020-01-28

Micropore inhomogeneity of continental shale under different side length and resolution: a case study of Chang 7² shale from well Yaoke 1 in Ordos Basin

SHANG Yanjun^{1, 2
,},
ZHAO Bin³,
HU Ruilin^{1, 2},
SHAO Peng^{1, 2}

1.
Key Laboratory of Shale Gas and Geological Engineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Exploration and Development Research Institute, PetroChina Tarim Oilfield Company, Korla, Xinjiang 841000, China

摘要

摘要: 陆相页岩的非均质性与海相页岩不同，其主要表现为孔隙结构的非均质性。以鄂尔多斯盆地瑶科1井采出的上三叠统长7²黑色页岩为例，利用微米CT在1 μm分辨率下对7个不同边长（100~700 μm）、纳米CT在65 nm分辨率下对4个不同边长（10~39 μm）的孔隙和裂缝进行了观测和分析。建立了3D图像重构基础上的不同边长及分辨率的孔隙指标非均质特性表征：孔隙数量和体积随边长增加而呈指数增大，面密度随边长增大而减小，长宽平均值及其比值基本不变。作为表征连通性指标的配位数与孔隙长度均值关系较为密切。
- 微观孔隙 /
- 边长 /
- 面密度 /
- 长宽比 /
- 延长组页岩 /
- 鄂尔多斯盆地
Abstract: Continental shale is different from marine shale due to its inhomogeneity, which is apparent mainly in the inhomogeneity of pore structure. The Upper Triassic Yanchang black shale (Chang 7²) samples were collected from the well Yaoke 1 in the Ordos Basin. Micro and nano CT were used to observe and analyze the pores and cracks of 7 different side lengths (100-700 μm) and 4 different side lengths (10-39 μm) at 1 μm and 65 nm resolutions, respectively. The spatial inhomogeneity index of different side lengths and resolutions based on 3D image reconstruction was established. It was found that the number and volume of pores increased exponentially with the increase of side lengths, while the plane density of the pores decreased with the increase of side lengths. The average length, width and their ratio remained basically unchanged. Coordination number, as an indicator of connectivity, is closely related to the average width of pores.
- micropore /
- block side length /
- plane density of pores /
- ratio of pore length with width /
- Yanchang shale /
- Ordos Basin

HTML全文

图 1 样品微米CT扫描重构图像

左为三维显示；中上为同一平面上向下切立体块；右为同一平面切割图像放大；数字表示边长, μm。

Figure 1. Micro CT images after reconstruction

下载: 全尺寸图片幻灯片

图 2 样品纳米CT扫描重构图像

左为三维显示；中为向下切立体块；右为切割面图像放大。数字表示边长, μm。

Figure 2. Nano CT images after reconstruction

下载: 全尺寸图片幻灯片

图 3 微米CT扫描重构边长700 μm的立方块体及微裂隙分布

Figure 3. Micro CT scanned image and micro-fissure distribution in a cubic block (side length 700 μm)

下载: 全尺寸图片幻灯片

图 4 应用Connected技术显示的截图区内的孔隙连通情况

Figure 4. Connectivity of pores shown by Connected technique

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图 5 CT扫描图像中不同边长立方块孔隙参量变化对比

Figure 5. Pore indices for description of cubic blocks from CT images

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图 6 不同观测尺度下长宽比值的孔隙数量变化曲线

Figure 6. Variation of pore quantity vs. different ratios of length with width

下载: 全尺寸图片幻灯片

表 1 微米—纳米CT扫描实验条件

Table 1. Micro CT and Nano CT scanning situations

检测类型	仪器型号	视域	像素	分辨率	样品规格	3D方块边长/μm	二维灰度图像
微米CT	Xradia micro CT VERSA-500	2 mm×2 mm	2 048×2 048	1 μm	圆柱, Φ2 mm, 高2 mm	100, 200, 300, 400, 500, 600, 700	1 984张
纳米CT	Xradia L-200 Nano CT ULTRAXRM	65 μm×65 μm	1 024×1 024	65 nm	圆柱, Φ65 μm, 高65μm	10, 20, 30, 39	1 021张

下载: 导出CSV

表 2 不同边长立方块的孔隙特征

Table 2. Pore features of cubic blocks at 11 different side lengths

边长/μm	孔隙数/个	裂隙数/个	(孔隙+裂隙)数/个	(孔隙+裂隙)体积/μm³	总体积/μm³	孔隙度/%	(孔隙+裂隙)总长/μm	面密度/(μm·μm^-2)	长/μm	宽/μm	长/宽	喉道与孔隙半径比	配位数
10	210	150	360	20.35	906.28	2.245	142.281	1.423	$\frac{{0.092 \sim 10.022}}{{0.395}}$	$\frac{{0.065 \sim 3.775}}{{0.214}}$	$\frac{{0.96 \sim 4.00}}{{1.86}}$		$\frac{{0 \sim 9}}{{1.66}}$
20	1 268	854	2 122	111.88	7 301.73	1.532	895.622	2.239	$\frac{{0.092 \sim 11.866}}{{0.422}}$	$\frac{{0.065 \sim 5.196}}{{0.230}}$	$\frac{{0.96 \sim 6.00}}{{1.83}}$		$\frac{{1 \sim 10}}{{1.71}}$
30	3 894	550	4 444	406.00	2.63×10⁴	1.542	1 779.817	1.978	$\frac{{0.092 \sim 14.149}}{{0.401}}$	$\frac{{0.065 \sim 9.463}}{{0.221}}$	$\frac{{0.96 \sim 5.40}}{{1.83}}$		$\frac{{0 \sim 9}}{{1.64}}$
39	2 307	1578	3 885	539.06	5.88×10⁴	0.917	1 654.060	1.087	$\frac{{0.092 \sim 15.255}}{{0.426}}$	$\frac{{0.065 \sim 8.227}}{{0.223}}$	$\frac{{1.00 \sim 10.00}}{{1.93}}$	$\frac{{0.04 \sim 0.96}}{{0.33}}$	$\frac{{1 \sim 12}}{{1.68}}$
100	253	190	443	3.49×10⁴	9.64×10⁵	3.620	3 204.079	0.320	$\frac{{1.414 \sim 72.717}}{{7.233}}$	$\frac{{1.000 \sim 21.920}}{{3.383}}$	$\frac{{1.00 \sim 9.00}}{{2.00}}$	$\frac{{0.29 \sim 1.09}}{{0.63}}$	$\frac{{0 \sim 4}}{{1.44}}$
200	1 632	735	2 367	2.51×10⁵	7.74×10⁶	3.248	1.877×10⁴	0.469	$\frac{{1.414 \sim 66.468}}{{7.929}}$	$\frac{{1.000 \sim 26.839}}{{3.757}}$	$\frac{{1.00 \sim 8.01}}{{2.04}}$	$\frac{{0.17 \sim 1.30}}{{0.52}}$	$\frac{{0 \sim 6}}{{1.58}}$
300	4 444	1 458	5 902	1.06×10⁶	2.59×10⁷	4.073	3.330×10⁴	0.370	$\frac{{1.414 \sim 89.239}}{{7.493}}$	$\frac{{1.000 \sim 41.754}}{{3.662}}$	$\frac{{0.96 \sim 9.19}}{{1.95}}$
400	4 785	6 464	1.12×10⁴	2.39×10⁶	6.16×10⁷	3.882	3.927×10⁴	0.245	$\frac{{1.414 \sim 106.000}}{{8.836}}$	$\frac{{1.000 \sim 36.338}}{{4.038}}$	$\frac{{1.00 \sim 10.00}}{{2.11}}$	$\frac{{0.09 \sim 2.18}}{{0.48}}$	$\frac{{0 \sim 11}}{{1.86}}$
500	4 444	1.67×10⁴	2.11×10⁴	4.29×10⁶	1.21×10⁸	3.554	4.038×10⁴	0.162	$\frac{{1.414 \sim 94.173}}{{9.087}}$	$\frac{{1.000 \sim 39.294}}{{4.126}}$	$\frac{{0.96 \sim 12.00}}{{2.11}}$
600	1.71×10⁴	2.07×10⁴	3.78×10⁴	8.22×10⁶	2.08×10⁸	3.959	4.044×10⁴	0.112	$\frac{{1.414 \sim 84.247}}{{9.100}}$	$\frac{{1.000 \sim 30.249}}{{4.054}}$	$\frac{{0.92 \sim 9.00}}{{2.16}}$	$\frac{{0.09 \sim 2.18}}{{0.49}}$	$\frac{{0 \sim 12}}{{1.81}}$
700	4.44×10⁴	1.96×10⁴	6.41×10⁴	1.43×10⁷	3.28×10⁸	4.364	4.118×10⁴	0.084	$\frac{{1.414 \sim 106.177}}{{9.266}}$	$\frac{{1.000 \sim 40.213}}{{4.163}}$	$\frac{{0.96 \sim 9.42}}{{2.13}}$
注：表中分式的意义为：$\frac{{最小值 \sim 最大值}}{{平均值}}$。

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