{"title":"基于水平井随钻高分辨率测井图像的碳酸盐岩储层类型与填图","authors":"S. Yang, R. Lawatia","doi":"10.3997/2214-4609.201903318","DOIUrl":null,"url":null,"abstract":"Summary To better provide rock typing in carbonate reservoir more efficient, we propose a solution for the rock typing from Log While Drilling (LWD) high resolution images. The porosity in carbonate is controlled by the secondary porosity and can be computed from borehole images with integration with traditional total porosity measurement; and pores connectedness is a good indicator for the formation permeability. The fracture evaluation is another key element for reservoir permeability computation; and we can identify, classify and compute fracture parameters from borehole image confidently. Based on the secondary porosity and fracture evaluation result, we can classify the reservoir rock typing with Heterogenous Rock Analysis (HRA) clustering by integrating the principle components analysis (PCA) and K-means clustering algorithm. And then the reservoir mapping can be achieved by combining the structure and rock typing.","PeriodicalId":427666,"journal":{"name":"Third EAGE Borehole Geology Workshop","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Carbonate Reservoir Rock Typing and Mapping from the Horizontal Well High Resolution Logging While Drilling Images\",\"authors\":\"S. Yang, R. Lawatia\",\"doi\":\"10.3997/2214-4609.201903318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary To better provide rock typing in carbonate reservoir more efficient, we propose a solution for the rock typing from Log While Drilling (LWD) high resolution images. The porosity in carbonate is controlled by the secondary porosity and can be computed from borehole images with integration with traditional total porosity measurement; and pores connectedness is a good indicator for the formation permeability. The fracture evaluation is another key element for reservoir permeability computation; and we can identify, classify and compute fracture parameters from borehole image confidently. Based on the secondary porosity and fracture evaluation result, we can classify the reservoir rock typing with Heterogenous Rock Analysis (HRA) clustering by integrating the principle components analysis (PCA) and K-means clustering algorithm. And then the reservoir mapping can be achieved by combining the structure and rock typing.\",\"PeriodicalId\":427666,\"journal\":{\"name\":\"Third EAGE Borehole Geology Workshop\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third EAGE Borehole Geology Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201903318\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third EAGE Borehole Geology Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201903318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Carbonate Reservoir Rock Typing and Mapping from the Horizontal Well High Resolution Logging While Drilling Images
Summary To better provide rock typing in carbonate reservoir more efficient, we propose a solution for the rock typing from Log While Drilling (LWD) high resolution images. The porosity in carbonate is controlled by the secondary porosity and can be computed from borehole images with integration with traditional total porosity measurement; and pores connectedness is a good indicator for the formation permeability. The fracture evaluation is another key element for reservoir permeability computation; and we can identify, classify and compute fracture parameters from borehole image confidently. Based on the secondary porosity and fracture evaluation result, we can classify the reservoir rock typing with Heterogenous Rock Analysis (HRA) clustering by integrating the principle components analysis (PCA) and K-means clustering algorithm. And then the reservoir mapping can be achieved by combining the structure and rock typing.