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
计量
- 文章访问数: 907
- HTML全文浏览量: 126
- PDF下载量: 194
- 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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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：$\frac{{最小值 \sim 最大值}}{{平均值}}$。

下载: 导出CSV

参考文献(17)

[1]	王香增, 张金川, 曹金舟, 等. 陆相页岩气资源评价初探: 以延长直罗-下寺湾区中生界长7段为例[J]. 地学前缘, 2012, 19(2): 192-197. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY201202029.htm WANG Xiangzeng, ZHANG Jinchuan, CAO Jinzhou, et al. A preliminary discussion on evaluation of continental shale gas resources: a case study of Chang 7 of Mesozoic Yanchang Formation in Zhiluo-Xiasiwan area of Yanchang[J]. Earth Science Frontiers, 2012, 19(2): 192-197. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY201202029.htm
[2]	李成成, 周世新, 李靖, 等. 鄂尔多斯盆地南部延长组泥页岩孔隙特征及其控制因素[J]. 沉积学报, 2017, 35(2): 315-329. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB201702010.htm LI Chengcheng, ZHOU Shixin, LI Jing, et al. Pore characteristics and controlling factors of the Yanchang Formation mudstone and shale in the south of Ordos Basin[J]. Acta Sedimentologica Sinica, 2017, 35(2): 315-329. https://www.cnki.com.cn/Article/CJFDTOTAL-CJXB201702010.htm
[3]	赵帮胜, 李荣西, 覃小丽, 等. 鄂尔多斯盆地中部上古生界山西组页岩储层特征[J]. 沉积学报, 2019, doi: 10.14027/j.issn.1000-0550.2019.054. ZHAO Bangsheng, LI Rongxi, QIN Xiaoli, et al. Characteristics of shale reservoirs in the Upper Paleozoic Shanxi Formation in the central Ordos Basin[J]. Acta Sedimentologica Sinica, 2019, doi: 10.14027/j.issn.1000-0550.2019.054.
[4]	李丽慧, 黄北秀, 李严严, 等. 考虑页岩纹层与裂缝网络的延长组页岩多尺度三维地质结构模型[J]. 工程地质学报, 2019, 27(1): 69-79. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201901008.htm LI Lihui, HUANG Beixiu, LI Yanyan, et al. Multi-scale 3-D modeling of Yanchang shale geological strucutre considering laminas and fracture networks[J]. Journal of Engineering Geo-logy, 2019, 27(1): 69-79. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201901008.htm
[5]	赵斌, 尚彦军. 基于复杂网络理论的页岩纳米孔隙连通性表征[J]. 工程地质学报, 2018, 26(2): 504-509. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201802028.htm ZHAO Bin, SHANG Yanjun. Characterizing connectivity of nano-sized pores of shale based on complex network theory[J]. Journal of Engineering Geology, 2018, 26(2): 504-509. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201802028.htm
[6]	支东明, 唐勇, 杨智峰, 等. 准噶尔盆地吉木萨尔凹陷陆相页岩油地质特征与聚集机理[J]. 石油与天然气地质, 2019, 40(3): 524-434. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201903009.htm ZHI Dongming, TANG Yong, YANG Zhifeng, et al. Geological chara-cteristics and accumulation mechanism of continental shale oil in Jimusaer sag, Junggar Basin[J]. Oil & Gas Geology, 2019, 40(3): 524-534. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201903009.htm
[7]	赵静. 陆相页岩气成藏条件分析: 以松辽盆地南部S洼槽为例[J]. 断块油气田, 2019, 26(3): 290-293, 313. https://www.cnki.com.cn/Article/CJFDTOTAL-DKYT201903005.htm ZHAO Jing. Accumulation conditions of shale gas in continental facies: taking S Depression of Songliao Basin as an example[J]. Fault-Block Oil and Gas Field, 2019, 26(3): 290-293, 313. https://www.cnki.com.cn/Article/CJFDTOTAL-DKYT201903005.htm
[8]	马晓潇, 黎茂稳, 蒋启贵, 等. 陆相页岩含油性的化学动力学定量评价方法[J]. 油气地质与采收率, 2019, 26(1): 137-152. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201901015.htm MA Xiaoxiao, LI Maowen, JIANG Qigui, et al. Chemical kinetic model for quantitative evaluation on oil-bearing property of lacustrine shale[J]. Petroleum Geology and Recovery Efficiency, 2019, 26(1): 137-152. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201901015.htm
[9]	胡文瑄, 姚素平, 陆现彩, 等. 典型陆相页岩油层系成岩过程中有机质演化对储集性的影响[J]. 石油与天然气地质, 2019, 40(5): 947-956. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201905001.htm HU Wenxuan, YAO Suping, LU Xiancai, et al. Effects of organic matter evolution on oil reservoir property during diagenesis of typical continental shale sequences[J]. Oil & Gas Geology, 2019, 40(5): 947-956. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201905001.htm
[10]	高辉, 何梦卿, 赵鹏云, 等. 鄂尔多斯盆地长7页岩油与北美地区典型页岩油地质特征对比[J]. 石油实验地质, 2018, 40(2): 133-140. doi: 10.11781/sysydz201802133 GAO Hui, HE Mengqing, ZHAO Pengyun, et al. Comparison of geological characteristics of Chang 7 shale oil in Ordos Basin and typical shale oil in North America[J]. Petroleum Geology & Experiment, 2018, 40(2): 133-140. doi: 10.11781/sysydz201802133
[11]	刘国恒, 黄志龙, 姜振学, 等. 湖相页岩液态烃对页岩吸附气实验的影响: 以鄂尔多斯盆地延长组页岩为例[J]. 石油实验地质, 2015, 37(5): 648-653. doi: 10.11781/sysydz201505648 LIU Guoheng, HUANG Zhilong, JIANG Zhenxue, et al. Effect of liquid hydrocarbons on gas adsorption in a lacustrine shale: a case study of the Yanchang Formation, Ordos Basin[J]. Petro-leum Geology & Experiment, 2015, 37(5): 648-653. doi: 10.11781/sysydz201505648
[12]	赵立鹏. 江西省富有机质页岩孔裂隙结构特征及其对页岩气富集的影响[D]. 北京: 中国矿业大学, 2015. ZHAO Lipeng. Pore-fissures characteristics of the shale/mudstone reservoirs and their influence on shale gas enrichment in Jiangxi Province[D]. Beijing: China University of Mining & Technology, 2015.
[13]	鲍云杰, 李志明, 杨振恒, 等. 孔隙度测定误差及其控制方法研究[J]. 石油实验地质, 2019, 41(4): 593-597. doi: 10.11781/sysydz201904593 BAO Yunjie, LI Zhiming, YANG Zhenheng, et al. Porosity mea-surement error and its control method[J]. Petroleum Geology & Experiment, 2019, 41(4): 593-597. doi: 10.11781/sysydz201904593
[14]	郭彤楼. 页岩气勘探开发中的几个地质问题[J]. 油气藏评价与开发, 2019, 9(5): 14-19. https://www.cnki.com.cn/Article/CJFDTOTAL-KTDQ201905002.htm GUO Tonglou. A few geological issues in shale gas exploration and development[J]. Reservoir Evaluation and Development, 2019, 9(5): 14-19. https://www.cnki.com.cn/Article/CJFDTOTAL-KTDQ201905002.htm
[15]	邹才能, 董大忠, 杨桦, 等. 中国页岩气形成条件及勘探实践[J]. 天然气工业, 2011, 31(12): 26-39. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201112007.htm ZOU Caineng, DONG Dazhong, YANG Hua, et al. Conditions of shale gas accumulation and exploration practices in China[J]. Natural Gas Industry, 2011, 31(12): 26-39. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201112007.htm
[16]	黎茂稳, 马晓潇, 蒋启贵, 等. 北美海相页岩油形成条件、富集特征与启示[J]. 油气地质与采收率, 2019, 26(1): 13-28. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201901002.htm LI Maowen, MA Xiaoxiao, JIANG Qigui, et al. Enligh tenment from formation conditions and enrichment characteristics of marine shale oil in North America[J]. Petroleum Geology and Recovery Efficiency, 2019, 26(1): 13-28. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201901002.htm
[17]	王濡岳, 胡宗全, 刘敬寿, 等. 中国南方海相与陆相页岩裂缝发育特征及主控因素对比: 以黔北岑巩地区下寒武统为例[J]. 石油与天然气地质, 2018, 39(4): 631-640. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201804002.htm WANG Ruyue, HU Zongquan, LIU Jingshou, et al. Comparative analysis of characteristics and controlling factors of fractures in marine and continental shale: a case study of the Lower Cambrian in Cengongarea, northern Guizhou Province[J]. Oil & Gas Geo-logy, 2018, 39(4): 631-640. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT201804002.htm