The coral reef pores are the main reservoir space of oil and gas resources. Through determining the structural form and distribution characteristics of pores, it can be helpful for scientific and reasonable stratigraphic division and reservoir evaluation, and provide basic data for the efficient development of using coral reefs as oil and gas reservoir sites. The core difficulty of interpretation and evaluation of coral reef pore structure and distribution characteristics is the pore recognition and feature extraction. In view of problems of low accuracy and efficiency in the recognition and feature extraction of coral reef pore at present, this paper proposes a method of coral reef pore recognition and feature extraction based on borehole image data. First of all, based on the borehole image and combined with the pore characteristics in borehole image, this paper proposes the coral reef pore recognition method. By using the feature of color gradient difference between the pore and the non pore in the borehole image, it realizes the segmentation of coral reef pore with low noise and weak interference. On the basis of obvious coral reef pores, the contour tracking method and image filling system of coral reef pore are established. Then, on the basis of traditional eight connected region marking algorithm, a pore region feature extraction method is proposed. The equivalent relationship between the temporary mark and the final mark is established, and an evaluation criterion that can comprehensively reflect the pore region feature parameters in the borehole image is formed. Finally, a systematic analysis and a comparison of results are carried out based on the actual coral reef borehole images. The results are consistent with the real values, which verifies the correctness of method.

At present, very few drilling surveys have been conducted on coral reefs, and comprehensive geological info on coral reefs is difficult to obtain. However, research on coral reefs is of great importance to development and exploitation of maritime resources. In the survey of Chenhang Island in Paracel (Xisha) Islands, we applied the digital borehole camera technology the first time in China, which resulted in a large amount of first-hand geological data. We utilized the rock mass integrity index (RMDI) method in our analysis of coral reef integrity, and the value of coefficient α in the RMDI was determined to evaluate the size effect of cavities on coral reefs. We then developed the correlation between RMDI values and coral reef integrity with references to the rock mass classification standard, which enabled the engineering evaluation of coral reef integrity. By statistical analysis of camera data gathered along the CK2 borehole for approximately 1-km length, we performed an integrity evaluation of the entire borehole length using the RMDI classification and created a coral reef stratum development diagram that was consistent with the actual cores. The results indicated: (1) the RMDI is a feasible approach for the analysis of coral reef integrity, (2) the classification system based on RMDI is feasible in the integrity evaluation of coral reefs, (3) the values of coral reef integrity obtained using the RMDI method are accurate, and (4) borehole camera survey and statistical analysis are important in the study of coral reefs.

In order to more accurately realize the automatic identification and quantitative characterization of coral reef multi-scale pore structure, this paper has carried out such research. On the basis of using multiple information acquisition technology, it can effectively collect field measured data and indoor observation data to form a high-precision digital image of the development characteristics of multi-scale coral reef pore structure. By constructing the multi-scale structure information correlation and fusion function of coral reef pore structure, it can formulate the positioning and search strategy for the key areas of coral reef pore structure development characteristics. In this paper, a fine identification and quantitative characterization method suitable for the pore structure of “millimeter–micron–nanometer” is formed. At the same time, combined with the actual project requirements, the multi-scale pore structure feature area location method of coral reef is constructed, which combines the distribution characteristics, variation characteristics, fractal characteristics and shape characteristics in a certain range, and realizes the search of pore key areas between different scales and different regions of the same scale through the similarity matching algorithm, which can effectively realize the automatic search of key areas in the “millimeter–micron–nanometer”-scale image of coral reefs. Finally, the correctness and feasibility of this method are verified by multi-angle example data comparison. It shows that this method can effectively solve the productivity prediction and evaluation problem of coral reef oil and gas reservoirs.