伊通盆地鹿乡断陷低渗储层敏感性机理分析及分布预测

单华生; 周锋德

doi:10.3799/dqkx.2012.080

伊通盆地鹿乡断陷低渗储层敏感性机理分析及分布预测

doi: 10.3799/dqkx.2012.080

单华生^{1, 2,},
周锋德¹

1.
中国地质大学资源学院，湖北武汉 430074
2.
中国地质大学生物地质与环境地质国家重点实验室，湖北武汉 430074

基金项目:

中国石油天然气股份有限公司吉林油田分公司重大项目“伊通盆地构造、沉积及油气成藏评价” 2006026157

详细信息

作者简介:
单华生(1978-)，男，讲师，博士在读，研究方向为油气储层地质及开发.E-mail: shanhuasheng@163.com

中图分类号: TE348
计量
- 文章访问数: 520
- HTML全文浏览量: 674
- PDF下载量: 10
- 被引次数: 0
出版历程
- 收稿日期: 2012-03-07
- 网络出版日期: 2021-10-13
- 刊出日期: 2012-07-15

Analysis of the Sensitivity Mechanism and Distribution in Low Permeability Reservoir in Luxiang Depression, Yitong Basin

SHAN Hua-sheng^{1, 2
,},
ZHOU Feng-de¹

1.
Faculty of Earth Resources, China University of Geosciences, Wuhan 430074, China
2.
State Key Laboratory of Biogeology and Environmental Geology, Wuhan 430074, China

摘要

摘要: 为了准确认识和预测伊通盆地鹿乡断陷储层敏感性的分布，从实验分析入手，测量不同样品的敏感性、物性和粘土矿物等参数，结合铸体薄片、压汞、扫描电镜等实验方法，从宏观和微观2个角度分析了储层敏感性与孔隙度、渗透率与各类粘土矿物相对含量之间的关系，分析了储层敏感性与储层的孔喉类型和粘土矿物产状之间的关系，建立了不同微相控制下的孔隙度、渗透率、粘土矿物含量、石英和长石含量的解释模型.最后，选取孔隙度、渗透率、石英含量、长石含量、伊利石含量、高岭石含量、绿泥石含量、伊/蒙混层含量8个参数，采用Elman神经网络方法分别建立了速敏、水敏、酸敏和碱敏的预测模型.结果表明：采用神经网络方法预测的储层敏感性指数与实验结果吻合；五星构造带具有强的速敏、酸敏、碱敏和盐敏，鹿乡断陷中部和西北部具有强的水敏性.
- 低渗储层 /
- 储层敏感性 /
- 影响因素 /
- 预测模型 /
- 沉积学 /
- 油气
Abstract: In order to determine the affecting factors and to build the predicating model of sensitivity in Luxiang depression, this paper firstly analyzes the sensitivity results and some parameters, including porosity, permeability, contents of different kinds of clay minerals tested in laboratory. Then it analyzes the relationship between sensitivity and porosity, permeability, contents of different kinds of clay minerals, throat type, and the distribution of clay minerals, integrated with the lab methods, such as core casting slices, microscope scanning, etc. Next, parameter prediction models are built by relating with sedimentary facies and depth. The porosity, permeability, contents of different clays, contents of quartz and feldspar were predicted based on these models which were used for sensitivity prediction. At last, sensitivity predicating models are built for speed sensitivity, water sensitivity, acid sensitivity and alkali sensitivity using Elman neural network. Results show that the Elman is efficient in sensitivity prediction; there are strong speed sensitivity, acid sensitivity, alkali sensitivity and salt sensitivity in Wuxing structural zone; whereas there is strong speed sensitivity in the center and northwest of Luxiang depression.
- low permeability reservoir /
- reservoir sensitivity /
- affecting factors /
- predicating model /
- sedimentoloy /
- hydrocarbon

HTML全文

图 1 伊通盆地构造划分及研究区位置

1.梁家构造带；2.新安堡凹陷；3.万昌构造带；4.波太凹陷；5.孤店斜坡带；6.靠山凹陷；7.尖山隆起带；8.马鞍山断阶；9.大南凹陷；10.五星构造带

Fig. 1. Schematic diagram of the study area and structural zones in Yitong basin

下载: 全尺寸图片幻灯片

图 2 不同敏感性类型指数纵向分布关系

Fig. 2. Variations of experimental sensitivity index with depth

下载: 全尺寸图片幻灯片

图 3 鹿乡断陷不同粘土矿物类型分布形式

a.片状高岭石集合体(昌10井，1 883.76 m)；b.绒球状伊利石(昌10井，1 883.96 m)；c.片状绿泥石集合体(星2井，2 157.31 m)；d.蜂窝状伊/蒙混层(刘2井，2 666.00 m)；e.伊/蒙混层充填孔隙(刘2井)；f.书页状自生高岭石充填孔隙(星2井)；g.绒球状伊利石充填孔隙(昌10井)；h.片状高岭石分散式充填孔隙(昌10井)；i.高岭石片状分散在颗粒表面(昌10井)；j.弯曲状伊利石、蜂窝状伊/蒙混层分散在颗粒表面(星2井)；k、l.扫描电镜下观察到的伊利石搭桥状分布孔隙间(昌10井)

Fig. 3. Illustration of clay minerals by scanning electron microscope (SEM) pictures (samples from Luxiang depression)

下载: 全尺寸图片幻灯片

图 4 各样品的物性和粘土矿物相对含量随深度的变化

Fig. 4. Variations of samples' porosity, permeability and clay content with depth

下载: 全尺寸图片幻灯片

图 5 不同敏感性模型预测的敏感性指数与实验结果对比

Fig. 5. Relationship of the sensitivity index between the prediction by Elman neural network and the experimental test

下载: 全尺寸图片幻灯片

图 6 鹿乡断陷双二段敏感性预测结果平面分布

Fig. 6. Sensitivity distribution by Elman neural network in second section of Shuangyang Formation, Luxiang depression

下载: 全尺寸图片幻灯片

表 1 储层敏感性实验分析结果

Table 1. Experimental results of sensitivity

样号	速敏指数	盐敏指数	水敏指数	酸敏指数	碱敏指数
X2S2-1	0.00	0.48	0.59	0.16	0.29
L2S2-2	0.00	/	0.80	0.00	0.16
X14S1-3	/	/	/	0.55	0.43
X14S2-4	0.00	0.35	0.79	0.16	0.52
X8S2-5	0.00	0.69	/	/	/
X8S2-6	0.00	0.27	0.49	/	0.74
X8S2-7	0.00	0.43	0.84	/	/
注：“/”表示样品未作敏感性试验；敏感性指数的公式为D_i=(K_max-K_min)/K_min，式中：D_i为敏感性指数，K_max和K_min分别为实验测试过程中渗透率的最大值和最小值.

下载: 导出CSV

表 2 敏感性实验样品物性和粘土矿物参数

Table 2. Porosity, permeability and clay mineral content of the samples

样号	深度(m)	物性		粘土矿物相对含量(%)
样号	深度(m)	孔隙度(%)	气测渗透率(10^－3 μm²)	蒙皂石	伊利石	高岭石	绿泥石	伊/蒙混层
X2S2-1	2 157.31	11.6	1.8	0	13.46	74.73	8.79	3.02
L2S2-2	2 666.00	12.7	3.7	0	6.00	83.00	0.00	11.00
X14S1-3	2 522.20	2.1	1.2	0	18.60	11.50	57.10	12.80
X14S2-4	2 218.35	8.8	1.5	0	25.70	65.70	5.80	8.80
X8S2-5	2 310.50	8.9	0.5	0	2.00	74.00	8.00	16.00
X8S2-6	2 294.70	12.7	0.5	0	6.00	42.50	11.00	40.50
X8S2-7	2 284.44	13.2	1.8	0	10.00	11.00	14.00	65.00

下载: 导出CSV

表 3 鹿乡断陷不同沉积微相间粘土矿物预测

Table 3. Predicting equations of clay mineral contents within different sedimentary facies

沉积微相	伊利石	高岭石	绿泥石	伊/蒙混层
重力流	I=0.000 6D+0.042 2	K=-0.006 0D+19.853 0	C= 0.001 7D-0.763 6	IS=0.003 0D-3.655 7
席状砂	I=0.000 6D+0.042 2	K=-0.006 0D+19.853 0	C=0.001 7 D-0.763 6	IS=0.003 0D-3.655 7
滩坝	I=0.000 6 D+ 0.042 2	K=-0.006 0D+19.853 0	C=0.001 7D-0.763 6	IS=0.003 0D-3.655 7
水下分流河道	I=0.000 2D+0.971 5	K=-0.002 2D+9.138 7	C= 0.000 7D-0.388 1	IS=0.001 5D-1.194 8
辫状分流河道	I=0.000 3D+1.492 2	K=-0.002 1D+10.170 0	C=0.001 4D-1.331 0	IS=0.002 1D-2.017 7
河口坝	I=0.008 2D-3.591 8	K=-0.003 1D+9.335 8	C=0.000 8D-0.675 3	IS=0.000 1D+0.375 9
注：D为深度，单位m；I为伊利石的含量(%)；K为高岭石的含量(%)；C为绿泥石的含量(%)；IS为伊/蒙混层的含量(%).

下载: 导出CSV

表 4 鹿乡断陷不同沉积微相间岩矿含量预测

Table 4. Predicting equations of quart and feldspar contents within different sedimentary facies

沉积微相	石英(Q)(%)	长石(F)(%)
辫状分流河道	Q=0.015 7D+32.389(＜2 350 m)	F=-0.005 4D+38.435(＜2 350 m)
辫状分流河道	Q=-0.026 3D+124.470(＞2 350 m)	F=0.023 5D-31.827(＞2 350 m)
辫状河道	Q=-0.002 7D+58.151	F=0.011 2D+12.431
心滩	Q=90	F=10
水下分流河道	Q=1.2D-1 914	F=-0.727 3D+1 218.4
滩坝	Q=-0.016 D+88.728(＞1 800 m)	F=0.004D+23.558(＞1 800 m)
滩坝	Q=62(＜1 800 m)	F=25(＜1 800 m)
席状砂	Q=35.7(＜1 200 m)	F=49.4(＜1 200 m)
	Q=0.028 2D+1.817 6(1 200~2 220 m)	F=-0.022 9D+76.929(1 200~2 220 m)
	Q=64.5(＞2 220 m)	F=26(＞2 220 m)
河口坝	Q=-0.003D+74.185	F=0.003 6D+17.596
重力流	Q=-0.016D+88.728	F=0.004D+23.558
注：D为深度，单位m；Q为石英的含量；F为长石的含量.

下载: 导出CSV

参考文献(35)

Chen, Z., Zhang, S.N., Shen, M.D., 1996. Potential damages of clay minerals in oil-field protection. Journal of Chengdu Institute of Technology, 23(2): 80-87 (in Chinese with English abstract). http://www.researchgate.net/publication/294762544_Potential_damages_of_clay_minerals_in_oil-field_protection
Civan, F., 2007. Formation damage mechanisms and their phenomenological modeling—an overview. SPE European Formation Damage Conference, Scheveningen, The Netherlands, 1-12.
Elman, J.L., 1990. Finding structure in time. Cognitiv. Sci. , 14(2): 179-211. doi: 10.1016/0364-0213(90)90002-E
Huang, X.T., Fang, S., Xu, H.H., 2002. Reservoir sensibility research on Shuangyang Formation in Moliqing basin of Yitong graben. World Geology, 21(4): 372-352 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-SJDZ200204006.htm
Hassan, B., Reza, R.M., Nazhat, D., et al., 2011. Evaluation of damage mechanisms and skin factor in tight gas reservoirs. SPE European Formation Damage Conference, Noordwijk, The Netherlands, 1-13.
Jiang, T., Xie, X.N., 2005. Effects of high temperature and overpressure on reservoir quality in the Yinggehai basin, South China Sea. Earth Science—Journal of China University of Geosciences, 30(2): 215-220 (in Chinese with English abstract). http://www.researchgate.net/publication/290056087_Effects_of_high_temperature_and_overpressure_on_reservoir_quality_in_the_Yinggehai_basin_South_China_Sea
Kang, Y.L., Luo, P.Y., 2000. Influence of clay minerals on formation damage in sandstone reservoir: a review and prospect in it. Drilling Fluid & Completion Fluid, 17(5): 36-40 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZJYW200005009.htm
Li, Y.L., Yang, D.Q., Tian, N.X., et al., 2003. The sensitivity evaluation of low permeability reservoir of Jurassic in Yanqi basin. Mineral Petrol. , 23(1): 77-80 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-KWYS200301016.htm
Palmer, Ⅰ., Mansoori, J., 1998. How permeability depends on stress and pore pressure in coal beds: a new model. SPE Reservoir Evaluation & Engineering, 1(6): 539-544. http://www.researchgate.net/publication/250089489_How_Permeability_Depends_on_Stress_and_Pore_Pressure_in_Coalbeds_A_New_Model
Peng, C.Y., Yan, J.N., Li, Y.F., 1999. New ways of predicting reservoir damage of potential sensitivity. Drilling Fluid & Completion Fluid, 16(2): 1-7 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZJYW199902000.htm
Shi, J.Q., Durucan, S., 2004. Drawdown induced changes in permeability of coal beds: a new interpretation of the reservoir response to primary recovery. Transport in Porous Media, 56(1): 1-16. doi: 10.1023/B:TIPM.00000.18398.19928.5a
Sun, J.M., Li, Z.C., Guan, X., 1999. Reservoir sensitivity determination by well logging. ACTA, 20(4): 34-38 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-SYXB904.008.htm
Wang, J., Zhao, Y.C., Liu, K., et al., 2006. Superimposing controls of acidic and alkaline dissolutions on sandstone reservoir quality of the Paleozoic Xiashihezi and Shanxi Formations in Tabamiao area, Ordos basin. Earth Science—Journal of China University of Geosciences, 31(2): 221-228 (in Chinese with English abstract). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dqkx200602012
Wei, Z.Y., Yao, G.Q., He, S., et al., 2008. Diagenetic evolution and mode in the Chaluhe faulted depression reservoir, Yitong graben. Earth Science—Journal of China University of Geosciences, 33(2): 227-234 (in Chinese with English abstract). doi: 10.3799/dqkx.2008.030
Yin, X., 2005. Experimental research on sensitive it of sandstone reservoir in Daniudi Ga field in E'erduosi basin. Natural Gas Industry, 25(8): 31-34 (in Chinese with English abstract). http://www.trqgy.cn/EN/abstract/abstract10740.shtml
Zhang, G.L., Chen, S.Y., Yan, J.H., 2006. Characteristics of clay minerals and their effects on formation sensitivity in Sha-1 member in Zhengjia-Wangzhuang area. Acta Mineralogica Sinica, 26(1): 99-106 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-KWXB200601017.htm
Zhao, D.H., Li, B.M., Zhao, H.T., 2002. Evaluating Upper Palaeozoic sand-stone reservoir sensitivity by use of log data. Natural Gas Industry, 22(6): 42-44 (in Chinese with English abstract). http://www.researchgate.net/publication/291825778_Evaluating_upper_Palaeozoic_sandstone_reservoir_sensitivity_by_use_of_log_data
Zhao, X.Y., Luo, J.C., Yang, F., 2005. Application of clay mineral study results to hydrocarbon prospecting in Tarim basin. Xinjiang Petroleum Geology, 26(5): 570-576 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-XJSD200505030.htm
Zhou, F.D., Yao, G.Q., Chen, J.X., et al., 2007a. Analysis of affecting factors and predication of sensitivity for low permeability reservoir: a case study of Liangjia-xin'anpu district in Chaluhe depression. J. Mineral. Petrol. , 27(3): 101-105 (in Chinese with English abstract).
Zhou, F.D., Yang, G.Q., Wang, G.C., et al., 2007b. Elman neural networks applied in the low permeability reservoir sensitivity prediction. Geological Science and Technology Information, 26(6): 91-94 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DZKQ200706017.htm
陈忠, 张哨楠, 沈明道, 1996. 粘土矿物在油田保护中的潜在危害. 成都理工学院学报, 23(2): 80-87. https://www.cnki.com.cn/Article/CJFDTOTAL-CDLG602.012.htm
黄湘通, 方石, 许海华, 2002. 伊通地堑莫里青盆地双阳组储层敏感性研究. 世界地质, 21(4): 347-352. doi: 10.3969/j.issn.1004-5589.2002.04.006
姜涛, 解习农, 2005. 莺歌海盆地高温超压环境下储层物性影响因素. 地球科学——中国地质大学学报, 30(2): 215-220. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX20050200E.htm
康毅力, 罗平亚, 2000. 粘土矿物对砂岩储层损害的影响——回顾与展望. 钻井液与完井液, 17(5): 36-40. doi: 10.3969/j.issn.1001-5620.2000.05.009
李永林, 杨道庆, 田纳新, 等, 2003. 焉耆盆地侏罗系低渗透储层敏感性评价. 矿物岩石, 23(1): 77-80. doi: 10.3969/j.issn.1001-6872.2003.01.016
彭春耀, 鄢捷年, 李玉凤, 1999. 预测储层潜在敏感性损害的新方法. 钻井液与完井液, 16(2): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-ZJYW199902000.htm
孙建孟, 李召成, 关雎, 1999. 用测井确定储层敏感性. 石油学报, 20(4): 34-38. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB904.008.htm
王京, 赵彦超, 刘琨, 等, 2006. 鄂尔多斯盆地塔巴庙地区上古生界砂岩储层"酸性+碱性"叠加溶蚀作用与储层质量主控因素. 地球科学——中国地质大学学报, 31(2): 221-228. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200602011.htm
魏忠元, 姚光庆, 何生, 等, 2008. 伊通地堑岔路河断陷储层成岩演化史与成岩模式. 地球科学——中国地质大学学报, 33(2): 227-234. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200802011.htm
尹昕, 2005. 大牛地气田砂岩储层敏感性实验研究. 天然气工业, 25(8): 31-34. doi: 10.3321/j.issn:1000-0976.2005.08.010
张关龙, 陈世悦, 鄢继华, 2006. 郑家－王庄地区沙一段粘土矿物特征及对储层敏感性影响. 矿物学报, 26(1): 99-106. doi: 10.3321/j.issn:1000-4734.2006.01.018
赵大华, 李保民, 赵会涛, 2002. 用测井资料评价上古生界砂岩储层敏感性. 天然气工业, 22(6): 42-44. doi: 10.3321/j.issn:1000-0976.2002.06.011
赵杏媛, 罗俊成, 杨帆, 2005. 粘土矿物研究成果在塔里木盆地油气勘探中的应用. 新疆石油地质, 26(5): 570-576. doi: 10.3969/j.issn.1001-3873.2005.05.026
周锋德, 姚光庆, 陈金霞, 等, 2007a. 岔路河断陷梁家-新安堡地区低渗储层敏感性影响因素分析及预测. 矿物岩石, 27(3): 101-105. https://www.cnki.com.cn/Article/CJFDTOTAL-KWYS200703016.htm
周锋德, 姚光庆, 王国昌, 等, 2007b. Elman神经网络在低渗储层敏感性预测中的应用. 地质科技情报, 26(6): 91-94. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ200706017.htm