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针对现有浅地层剖面图像中层界人工划分方法效率低、准确度不高的缺陷,提出了基于图像处理技术的层界自动划分方法及层界提取流程.首先对浅地层剖面原始观测数据解码,并对每Ping的振幅数据转换,形成原始浅地层剖面图像;然后对原始图像进行Ping插补、异常Ping修复、消噪和多次波压制等处理,消除异常观测值的影响,提高图像质量;在此基础上,根据回波振幅与层界的响应机制以及回波强度时序的变化特点,提出了基于灰度突变的阈值法层界粗提取及实施原则,实现了概略层界位置的确定;最后,顾及浅地层底质变化的渐进性和连续性,提出了基于拓扑理论的层界追踪和精提取方法,实现了离散层界的滤除及连续层界的提取.该方法实现了层界的自动提取及与钻孔取芯相同的划分精度.
Aiming at the defect of low efficiency and low accuracy of the artificial boundary method in the existing shallow stratum profile images, this paper proposed a method of automatic boundary layer separation based on image processing technology.Firstly, the original observation data of shallow stratum section was decoded, And transform the amplitude data of each Ping to form the original shallow stratum profile image. Then the original image is processed by Ping interpolation, abnormal Ping repair, noise reduction and multiple suppression to eliminate the influence of abnormal observations and improve the image quality. On this basis, according to the echo amplitude and the response mechanism of the horizon and the characteristics of the timing of the echo intensity, a rough threshold extraction method based on the gray level mutation is proposed, and the principle of the horizon is realized. Finally, taking into account the graduality and continuity of sediment changes in shallow formations, a method based on topological theory is proposed to track and refine the layer boundaries, and the filtering of discrete layer boundaries and the continuous layer boundary extraction are realized. Automatic extraction and the same as the core drilling accuracy.