A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Borehole image-based evaluation of coral reef porosity distribution characteristics
In this study, we used digital borehole image camera to obtain images of porosity distribution in coral reefs in South China Sea, and developed an effective evaluation system for such distributions. First, the original images are preprocessed, allowing the pore regions to be automatically detected. The depth and sectional functions are established to measure five parameters: pore count, pore radius, radius concentration rate, total pore area ratio, and fractal dimension count. These are used to calculate the characteristic values of porosity distributions, and their fuzzy relationships are used to build the evaluation model, determine the Hamming distances between distributions, and establish the relationships between the characteristics and coral rock classifications. Test results from applying the method on a deep borehole image segment show the results to be consistent with other methods, and the following conclusions can be reached: (1) the porosity evaluation model is a viable way to analyze porosity distribution characteristics; (2) the resulting classification method is viable; and (3) porosity distribution analysis on coral reefs has important implications.
Borehole image-based evaluation of coral reef porosity distribution characteristics
In this study, we used digital borehole image camera to obtain images of porosity distribution in coral reefs in South China Sea, and developed an effective evaluation system for such distributions. First, the original images are preprocessed, allowing the pore regions to be automatically detected. The depth and sectional functions are established to measure five parameters: pore count, pore radius, radius concentration rate, total pore area ratio, and fractal dimension count. These are used to calculate the characteristic values of porosity distributions, and their fuzzy relationships are used to build the evaluation model, determine the Hamming distances between distributions, and establish the relationships between the characteristics and coral rock classifications. Test results from applying the method on a deep borehole image segment show the results to be consistent with other methods, and the following conclusions can be reached: (1) the porosity evaluation model is a viable way to analyze porosity distribution characteristics; (2) the resulting classification method is viable; and (3) porosity distribution analysis on coral reefs has important implications.
Borehole image-based evaluation of coral reef porosity distribution characteristics
Wang, Jin-chao (author) / Wang, Chuan-ying / Zhu, Chang-qi / Hu, Sheng
2017
Article (Journal)
English
Borehole image-based evaluation of coral reef porosity distribution characteristics
| Taylor & Francis Verlag | 2017
Borehole image-based evaluation of coral reef porosity distribution characteristics
| Online Contents | 2016
Coral reef pore recognition and feature extraction based on borehole image
| Taylor & Francis Verlag | 2022
Analysis and evaluation of coral reef integrity based on borehole camera technology
| Online Contents | 2017
Analysis and evaluation of coral reef integrity based on borehole camera technology
| Taylor & Francis Verlag | 2017