基于PCAS软件对孔隙结构的定量表征——以川北地区广元千佛崖组砂岩为例  

Quantitative characterization of pore structure based on PCAS:A case study on Qianfoya sandstone in Guangyuan,Sichuan,China

作　　者：郝嘉欣 向芳[2] 施紫越 文耀羚 赵希 王建平 HAO Jiaxin;XIANG Fang;SHI Ziyue;WEN Yaoling;ZHAO Xi;WANG Jianping(College of Earth and Planetary Science,Chengdu University of Technology,Chengdu 610059,China;Institute of Sedimentary Geology,Chengdu University of Technology,Chengdu 610059,China;Guangyuan Grottoes Research Institute,Guangyuan 628000,China)

机构地区：[1]成都理工大学地球与行星科学学院,成都610059 [2]成都理工大学沉积地质研究院,成都610059 [3]广元石窟研究所,四川广元628000

出　　处：《成都理工大学学报（自然科学版）》2024年第3期439-448,共10页Journal of Chengdu University of Technology: Science & Technology Edition

基　　金：广元市科技计划项目(重点研发项目)(22ZDYF0002)。

摘　　要：使用川北地区广元千佛崖组砂岩薄片图像样品,开展基于孔、裂隙分析系统(PCAS)定量表征孔隙结构的研究,并探讨如何提升PCAS识别孔隙度的精度。研究表明:使用PCAS默认的单阈值分割法,识别的孔隙与人工圈定的孔隙范围不一致,并且孔隙度偏高,为31.21%。为了提高软件的识别效果,使用Adobe Photoshop对图像进行初步优化,然后采用多阈值分割法,根据孔隙的颜色差异设置各阈值的容差,最终得出孔隙度为14.18%,孔隙识别正确且内部结构更加完整,说明以上操作能够显著提升软件的识别效果。将优化后的孔隙度与默认的单阈值分割法识别的孔隙度、薄片估算的面孔率进行对比,发现优化后的孔隙度与薄片估算的孔隙度接近,仅相差1%~2%,并且参考邻区储层物性测试所得孔隙度,可确定该结果具有一定准确性。此外,PCAS还能快速、准确地提取各种孔隙特征参数,对于孔隙成因、孔隙评价、赋孔特征、赋气机制、渗流网络等研究具有重要意义。这些结果证实了PCAS软件在定量表征孔隙方面的潜力。In this study,we analyze thin slices of images of sandstone in the Qianfoya Formation in the Guangyuan area to quantitatively characterize its pore structure by using pores/particles and cracks analysis system(PCAS),and discuss measures to improve the accuracy of porosity identification by using this software.The results showed that the pores identified by the default single-threshold method of segmentation of PCAS were inconsistent with manually identified pores.The porosity of the sandstone calculated by PCAS was also too high,at 31.21%.To improve the identification of pores by the software,we preliminarily optimized the images in Adobe Photoshop,and then used a multi-threshold method of segmentation to set the tolerance of each threshold according to the difference in color between pores in the image slices.The resulting calculated porosity of sandstone was 14.18%,the pores were correctly identified,and the software was able to accurately represent the internal structure of sandstone.A comparison was made between the porosity after optimization,the porosity identified by the default single-threshold method of segmentation,and the face ratio estimated using the thin slices of images,revealed that the optimized porosity was close to that estimated by using the thin image slices,with a difference of only 1%~2%.And refer to the porosity which was obtained from previous tests on the physical properties of reservoirs in adjacent areas,it can be confirmed that the result has a certain accuracy.Moreover,PCAS was able to quickly and accurately extract various characteristic parameters of the pores.This is important for the study of pore genesis,pore evaluation,pore characteristics,gas injection mechanism and seepage network.These results confirm the potential of using PCAS for the quantitative characterization of pores.

关 键 词：千佛崖组 砂岩孔隙度 孔、裂隙分析系统 孔隙特征参数 软件应用效果 

分 类 号：P642.25[天文地球—工程地质学]