储层微观孔喉网络图形识别方法

Identification Method of Reservoir Microscopic Pore-Throat Network

通过对大量岩样铸体薄片的图形特征反复观察与实验,设计了一种储层微观孔喉网络图形识别方法。该方法的关键是将原图片由RGB彩色空间转换到受亮度影响很小的YUV空间下,使待识别岩样孔喉网络产生很好的类聚,然后采用形态学分水岭分割方法识别出岩样铸体薄片图片中的孔隙与喉道。将该方法识别出的孔喉网络与RGB空间下一般图像分割技术识别出的孔喉网络对比,结果表明该方法识别出的孔喉网络比较完整与清晰;同时使用德国蔡司公司图像处理系统中的Axiovision4.0软件对待识别岩样薄片进行面孔率测算,结果表明该方法识别效果明显,相对误差降低了0.425%,大大提高了储层微观孔喉网络图形识别的准确度。

A micro-reservoir pore network pattern recognition method is designed by the repeated observation and experiments of a large number of the casting thin section of the rock sample.The key point of this method is that the transform from the RGB（red,green,blue） space into the YUV（Y-brightness,U,V-Color） space make the pore throat network be identified into good clusterings,and then by use of the morphological watershed segmentation method,segment the pore and throat of the casting thin sections of rock samples.The identified pore-throat networks by this method and the general image segmentation techniques are comparative studied.The comparison results show that the pore-throat networks are more complete and clear by this method identifies.The surface porosity of casting thin section of the rock sample to be identified is calculated by use of Axiovision4.0 software belongs to the German Zeiss image processing system at the same time.Calculation results show that the recognition effect is obvious,relative error is smaller;the micro-pore network of reservoirs accuracy of pattern recognition is improved.