碎裂煤二维显微裂隙自动识别及信息提取

发布时间：2019-05-12 04:27

【摘要】：碎裂煤二维裂隙定量分析对构造复杂区煤储层渗透性、煤体强度有效预测有重要意义。针对2张分别取自不同变形程度碎裂煤的二维显微裂隙位图,基于MATLAB图像处理平台,经二值化、降噪和修复,编程实现裂隙自动识别,成功消除擦痕及大小不等杂斑干扰,识别裂隙与原裂隙趋于一致;然后在裂隙分割的基础上,实现了裂隙面积、长度、平均宽度及面裂隙率等参数的自动提取,并对2张位图获得的裂隙信息进行对比,结果与直观反映的裂隙发育程度一致。
[Abstract]:The two-dimensional fracture quantitative analysis of broken coal is of great significance for the effective prediction of coal reservoir permeability and coal body strength in complex structural areas. Based on MATLAB image processing platform, based on two-dimensional micro-fracture bitmaps taken from different deformation degree fractured coal, through binarization, noise reduction and restoration, the automatic recognition of cracks is realized by programming, and the interference of scuffing and speckle of different sizes is eliminated successfully. The identification of cracks tends to be consistent with the original cracks. Then on the basis of fracture segmentation, the parameters such as fracture area, length, average width and surface fracture rate are automatically extracted, and the fracture information obtained from two bitmaps is compared. The results are in agreement with the direct reflection of fracture development degree.
【作者单位】：中国矿业大学资源与地球科学学院;煤层气资源与成藏过程教育部重点实验室;中国石油大学(北京)石油工程学院;
【基金】：国家自然科学基金重点项目(41430317);国家自然科学基金青年科学基金项目(41302130) 大学生创新创业计划(201410290034X)~~
【分类号】：P618.11

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