微CT扫描重建低渗气藏微观孔隙结构--以新场气田上沙溪庙组储层为例

doi:10.11743/ogg20110519

石油与天然气地质 ›› 2011, Vol. 32 ›› Issue (5): 792-796.doi: 10.11743/ogg20110519

微CT扫描重建低渗气藏微观孔隙结构--以新场气田上沙溪庙组储层为例

苏娜^1,2, 段永刚¹, 于春生^1,2

1. 中国石化河南油田分公司勘探开发研究院,河南南阳 473132;
2. 西南石油大学,四川成都 610500

收稿日期:2010-06-25 修回日期:2011-09-13 出版日期:2011-10-28 发布日期:2011-12-16
作者简介:苏娜(1981-),女,博士,油藏描述及数值模拟。
基金资助:
国家科技重大专项(2008ZX05022-001)。

Reconstruction of microscopic pore structure in low permeability gas reservoirs by micro-CT scanning: an example from the Upper Shaximiao Formation in Xinchang gas field

Su Na^1,2, Duan Yonggang¹, Yu Chunsheng^1,2

1. Exploration and Development Research Institute,SINOPEC Henan Oilfield Company,Nanyang,Henan 473132,China;
2. Southwest Petroleum University,Chengdu,Sichuan 610500, China

Received:2010-06-25 Revised:2011-09-13 Online:2011-10-28 Published:2011-12-16

摘要/Abstract

摘要：

为了提高气藏采收率,从微观孔隙结构出发,建立孔隙网络模型,定量描述孔隙微观尺度上的渗流机理。以川西新场气田上沙溪庙组岩心为例,开展孔隙结构三维重构研究。首先采用微CT技术对岩心进行扫描获得投影数据,采用FDK算法重建岩心灰度图像,然后以宏观孔隙度为基础利用二值分割法分割灰度图像,最后使用光线跟踪算法得到三维孔隙结构图像,即数字岩心。对数字岩心的相关性质进行统计分析,得到的数字岩心孔隙度与岩心实验孔隙度基本一致,相对误差约为0.1。这一数值与新场气田上沙溪庙组储层物性相吻合,说明微CT扫描法重构微观孔隙结构是可行的。该研究为建立孔隙网络模型及开展后续微观渗流模拟研究奠定了基础。

关键词: 分辨率, 二值分割, 光线跟踪, 微CT扫描, 微观孔隙结构, 低渗气藏, 新场气田

Abstract:

In order to enhance gas recovery,it is necessary to construct pore network model and quantitatively describe micro-pore-scale percolation mechanism based on micro-pore structure.Taking cores of the Upper Sha-ximiao Formation in the Xinchang gas field of western Sichuan Basin as an example,this paper studies 3D reconstruction of pore structure.First,using micro-CT to scan core to get projection data,and using the FDK algorithm for construction of grayscale images.Then based on experimental porosity,using 2-value segmentation to cut grayscale images and using ray tracing algorithm to get 3D pore structure image(digital core).Statistical analysis of the properties of digital core shows that the porosity of digital core is almost identical to the measured core porosity with a relative error of only 0.1,which is in coincide with the properties of Upper Shaximiao Formation in the Xinchang gas field.It shows that reconstruction of micro pore structure with micro-CT scanning is feasible.The study provides a solid foundation for pore network modeling and subsequent microscopic flow simulation study.

Key words: resolution, 2-value segmentation, ray tracing, micro-CT, microscopic pore structure, low permeability gas pool, Xinchang gas field

中图分类号:

TE122.2

苏娜,段永刚,于春生. 微CT扫描重建低渗气藏微观孔隙结构--以新场气田上沙溪庙组储层为例[J]. 石油与天然气地质, 2011, 32(5): 792-796. doi: 10.11743/ogg20110519 Su Na,Duan Yonggang,Yu Chunsheng. Reconstruction of microscopic pore structure in low permeability gas reservoirs by micro-CT scanning: an example from the Upper Shaximiao Formation in Xinchang gas field[J]. Oil & Gas Geology, 2011, 32(5): 792-796. doi: 10.11743/ogg20110519

参考文献

[1] 姚军, 赵秀才, 衣艳静, 等. 数字岩心技术的发展及展望[J]. 油气地质与采收率, 2005, 12(6): 52-54. Yao Jun, Zhao Xiucai, Yi Yanjing, et al. The current situation and prospect on digital core technology[J]. Petroleum Geology and Recovery Efficiency, 2005, 12(6): 52-54. [2] Dunsmuir J H, Ferguson S R, D'Amico K L, et al. X-ray micro-tomography: a new tool for the characterization of porous media. SPE Annual Technical Conference, Dallas, Texas: Journal of Petroleum Science and Engineering, 1991: 423-430. [3] Hazlett R D. Statistical characterization and stochastic modeling of pore networks in relation to fluid flow[J]. Mathematical Geology, 1997, 29(4): 801-822. [4] Bakke S, ren P E. 3-D pore-scale modeling of sandstones and flow simulations in the pore networks[J]. Journal of Petroleum Science and Engineering, 1997, 2(2): 136-149. [5] Okabe H, Blunt M J. Prediction of permeability for porous media reconstructed using multiple-Point statistics[J]. Physical Review E, 2004, 70, 066135. [6] Kak A C. Slaney M. Principles of computerized tomographic imaging[M]. New York: IEEE Press, 1988. [7] Feldkamp L A, Davis L C, Kress J W. Practical cone-beam algorithm[J]. Journal of the Optical Society of America, 1984, 1(6): 612-619. [8] Wang G, Liu Y, Lin T H, et al. Half-scan cone-beam x-ray micro tomography formula[J]. Scanning, 1994, 16(4): 216-220. [9] Grass M, Köhler T, Proksa R. 3-D Cone-beam CT reconstruction for circular trajectories[J]. Physics in Medicine and Biology, 2000, 45(2): 329-347. [10] Liu Y, Liu H, Wang G. Half-scan Cone-beam CT fluoroscopy with multiple X-ray source. [J], Medical Physics, 2001, 28(7): 1466-1471. [11] 翟静. 三维锥束CT中滤波反投影算法的研究. 太原: 中北大学, 2008. Zhai jing. Research on filtered back projection algorithm in 3D cone-beam CT. Taiyuan: North University of China, 2008. [12] 王培珍. 基于二维阈值化与FCM相混合的图像迅速分割方法[J]. 中国图像图形学报, 1998, 3(9): 735-738. Wang Peizhen. Image segmentation based on fuzzy clustering and Two-dimensional Thresholding[J]. Journal of Image and Graphics, 1998: 3(9): 735-738. [13] Whitted T. An Improved illumination model for shaded display[J]. Communications of the ACM, 1980, 23(6): 343-349. [14] 叶泰然, 付顺, 吕其彪, 等. 多波地震联合反演预测相对优质储层--以川西深层致密碎屑砂岩为例[J]. 石油与天然气地质, 2009, 30(3): 357-362, 369. Ye Tairan, Fu Shun, Lü Qibiao, et al. Application of multiwave joint inversion to the prediction of relatively high-quality reservoirs-an example from the prediction of deep tight clastic sandstone reservoirs in the western Sichuan Basin[J]. Oil & Gas Geology, 2009, 30(3): 357-362, 369. [15] 张大伟. 加速我国页岩气资源调查和勘探开发战略构想[J]. 石油与天然气地质, 2010, 31(2): 135-139, 150. Zhang Dawei. Strategic concepts of accelerating the survey, exploration and exploitation of shale gas resources in China[J]. Oil & Gas Geology, 2010, 31(2): 135-139, 150. [16] 戴金星, 黄士鹏, 刘岩,等. 中国天然气勘探开发60年的重大进展[J]. 石油与天然气地质, 2010, 31(6): 689-698. Dai Jinxing, Huang Shipeng, Liu Yan et al. Significant advancement in natural gas exploration and development in China during the past sixty years[J]. Oil & Gas Geology, 2010, 31(6): 689-698. [17] 孙家广. 计算机图形学[M]. 第三版. 北京: 清华大学出版社, 2003. Sun Jiaguang. Computer graphics[M]. Third Edition. Beijing: Tsinghua University Press, 2003.

微CT扫描重建低渗气藏微观孔隙结构--以新场气田上沙溪庙组储层为例

Reconstruction of microscopic pore structure in low permeability gas reservoirs by micro-CT scanning: an example from the Upper Shaximiao Formation in Xinchang gas field

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