Natural Gas Hydrate CT Image Threshold Segmentation Based on Time Evolution

Micro-scale X-ray computed tomography (CT) has been widely used to study the occurrence forms of gas hydrate-bearing sediments. However, the similarity between the X-ray attenuation coefficient of hydrate and that of water leads to a strong non-uniqueness in their phase differentiation in CT images. To improve threshold segmentation accuracy between hydrate and water in CT images, this study proposes a CT image and histogram normalized method by analyzing the histogram characteristics of CT images at different times during the growth process of natural gas hydrate. First, the peak gray value baseline of methane gas and quartz sand was selected. Then, a Gaussian function was used to fit the curves corresponding to methane gas and quartz sand in the current CT image histogram to obtain the peak gray values. In addition, the peak gray values of methane gas and quartz sand in the current CT image histogram were normalized to the chosen peak gray baseline. Subsequently, the normalized histogram was used to normalize the corresponding CT images. Finally, according to the changing trend of normalized gray histogram curves, the increasing gray ranges of hydrate and decreasing gray ranges of gas-water in CT images were obtained quantitatively, which guided threshold segmentation of CT images. Experimental results show that the proposed threshold segmentation method can provide a basis for phase differentiation between hydrate and water in CT images, improving the threshold segmentation accuracy.