• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Sensing and imaging >Intelligent Integration of Neutron, Density and Gamma Ray Data for Subsurface Characterization
【24h】

Intelligent Integration of Neutron, Density and Gamma Ray Data for Subsurface Characterization

机译：智能集成中子，密度和伽马射线数据进行地下表征

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Earth subsurface recognition through describing the underground layers can be carried out using physical measurements to obtain clearer and more accurate subsurface model. This can be conducted applying well logging method. Among various information that can be provided by different well logging sensors, neutron, density and gamma-ray data are the most considerable in subsurface type determination. However, current analysis of these data stills a subjective task which adds a variable confidence interval to the obtained results. In this study, a real time decision level fusion system uses fuzzy logic approach is introduced to incorporate neutron, density, and gamma-ray information in order to provide more specific interpretation of the subsurface structures. Results of the proposed approach agreed well with the results of an offline subsurface determination program, with an average ratio of about 89.75%. The suggested approach was evaluated against real data from eight wells, and the results were promising to yield more objective interpretation.
机译：通过描述地下层可以使用物理测量来进行地下地下识别，以获得更清晰和更准确的地下模型。这可以进行应用良好的测井方法。在可以由不同井测井传感器提供的各种信息中，中子，密度和伽马射线数据在地下型确定中最相当相当相当相当。但是，对这些数据的当前分析仍然是一个主观任务，它为获得的结果增加了可变置信区间。在该研究中，将判定级别融合系统使用模糊逻辑方法来结合中子，密度和伽马射线信息，以便提供更具体的地下结构的解释。拟议方法的结果符合离线地下确定计划的结果，平均比例约为89.75％。建议的方法是针对八个井的真实数据评估的，结果是有希望产生更多客观的解释。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号