Coral reef pore recognition and feature extraction based on borehole image
文献类型：期刊论文
| 作者 | Wang, Jinchao3,4; Chen, Wei2,3; Wang, Yiteng4; Zou, Junpeng1 |
| 刊名 | MARINE GEORESOURCES & GEOTECHNOLOGY
 |
| 出版日期 | 2021-01-12 |
| 页码 | 12 |
| 关键词 | Coral reef borehole image pore region automatic recognition feature extraction |
| ISSN号 | 1064-119X |
| DOI | 10.1080/1064119X.2021.1874576 |
| 英文摘要 | 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. |
| 资助项目 | National Natural Science Foundation for the Youth of China[41902294] ; Opening Foundation of Key Laboratory of Carbonate Reservoir of CNPC[RIPED-2020-JS-51018] |
| WOS研究方向 | Engineering ; Oceanography ; Mining & Mineral Processing |
| 语种 | 英语 |
| WOS记录号 | WOS:000609531800001 |
| 出版者 | TAYLOR & FRANCIS INC |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/25692]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Wang, Jinchao |
| 作者单位 | 1.China Univ Geosci, Fac Engn, Wuhan, Hubei, Peoples R China 2.PetroChina Hangzhou Res Inst Geol, Hangzhou, Peoples R China 3.CNPC, Key Lab Carbonate Reservoirs, Hangzhou, Peoples R China 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan, Hubei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Jinchao,Chen, Wei,Wang, Yiteng,et al. Coral reef pore recognition and feature extraction based on borehole image[J]. MARINE GEORESOURCES & GEOTECHNOLOGY,2021:12. |
| APA | Wang, Jinchao,Chen, Wei,Wang, Yiteng,&Zou, Junpeng.(2021).Coral reef pore recognition and feature extraction based on borehole image.MARINE GEORESOURCES & GEOTECHNOLOGY,12. |
| MLA | Wang, Jinchao,et al."Coral reef pore recognition and feature extraction based on borehole image".MARINE GEORESOURCES & GEOTECHNOLOGY (2021):12. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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