标题:Determination of the effective reservoirs on carbon dioxide geological storage in petroleum industry
作者:Feng Qiao; Zhang Xiaoli; Wang Xiangzeng; Gao Ruimin; Ma Jinfeng; Wang Zhenliang; Huang Chunxia; Jiang Shaojing
通讯作者:Xiaoli, Zhang
作者机构:[Feng Qiao] Shandong Univ Sci & Technol, Coll Geol Sci & Engn, Qingdao 266510, Shandong, Peoples R China.; [Zhang Xiaoli; Ma Jinfeng; Wang Zhenliang 更多
会议名称:12th International Conference on Greenhouse Gas Control Technologies (GHGT)
会议日期:OCT 05-09, 2014
来源:12TH INTERNATIONAL CONFERENCE ON GREENHOUSE GAS CONTROL TECHNOLOGIES, GHGT-12
出版年:2014
卷:63
页码:5172-5177
DOI:10.1016/j.egypro.2014.11.547
关键词:Carbon dioxide geological storage; High gamma ray sandstone; Log; response; Provenance; Sedimentary process; Well log curve overlap graph
摘要:For the evaluation of the carbon dioxide geological storage, the projects must be carried out: lithology recognition and lithology prediction, reservoir parameter evaluation, temperature and pressure analysis, injection pressure and sealing analysis, rock physical simulation experiment, carbon dioxide flooding, actual performance feedback, etc. The lithology recognition and lithology prediction are the base of the above all. So, the problems about lithology identification and lithology prediction will be mainly discussed. Comparative analyzing the geological features and log responses of the high gamma ray sandstones in Ordos Basin, it is supposed that the origin peculiarities of the high gamma ray sandstones may have three kinds: first, it may be due to provenance; second, it may be caused by homochronous sedimentary volcano tuff ash or previous tuffs; third, it may consist of the above two factors. Four-property relationships of high gamma ray reservoirs and well logging data interpretation results can reveal that the high gamma ray sandstones and mudstones will be quickly identified by using the spontaneous potential logging curve and well log curve overlap graph of spontaneous potential and acoustic slowness. (C) 2014 The Authors. Published by Elsevier Ltd.
收录类别:CPCI-S;EI
资源类型:会议论文
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