岩性识别的英文

• lithologic discrimination
• lithologic identification
• lithological discrimination

• "岩"英文翻译    rock
• "性"英文翻译    nature; character; dispositi ...
• "识别"英文翻译    discriminate; distinguish; d ...
• "性识别" 英文翻译 :    gender recognition; sex recognition
• "操纵性识别" 英文翻译 :    maneuverability identification
• "磁性识别卡" 英文翻译 :    identity cards magnetic
• "属性识别" 英文翻译 :    attribute identification
• "特异性识别" 英文翻译 :    specific recognition
• "限制性识别" 英文翻译 :    restrictive recognition
• "整体性识别" 英文翻译 :    holistic recognition
• "安全性识别项" 英文翻译 :    sid
• "安全性识别元" 英文翻译 :    sid
• "三点手性识别模型" 英文翻译 :    three-point chiral recognition model
• "肿瘤源性识别因子" 英文翻译 :    tumor-derived recognition factor
• "岩性" 英文翻译 :    litho-porosity crossplot; lithostratigraphic; lithologic characters; lithological characters; lithologicalcharacter; lithology
• "理解性识记" 英文翻译 :    intelligent memory
• "岩性窗" 英文翻译 :    lithology window
• "岩性带" 英文翻译 :    lithizone; lithozone
• "岩性的" 英文翻译 :    lithic
• "岩性对" 英文翻译 :    lithology pair
• "岩性体" 英文翻译 :    lithosome; lithostrome
• "岩性图" 英文翻译 :    lithologic map; lithological map; lithologicalmap
• "岩性土" 英文翻译 :    endodynamorphic soil
• "岩性线" 英文翻译 :    lithology line
• "岩性型" 英文翻译 :    lithotype

• A study on lithology identification methods for volcanic rocks
  火山岩岩性识别方法研究
• Application of rprop algorithm to well logging lithologic identification
  算法在测井岩性识别中的应用
• Lithologic identification of xing anling group in sudeerte oilfield
  苏德尔特油田兴安岭群岩性识别方法
• It is indicated that cap layers classifying and lithological distinguishing in single well profile can be reached through well - logging facies analysis
  研究认为，从测井相分析的角度可以解决单井剖面地层中盖层划分与岩性识别的问题。
• The research on logging lithology identification suggests that svm can overcome the fundamental disadvantages of neural network , and it is a new method to identify lithology
  在测井岩性识别方面研究发现，支持向量机方法克服了神经网络的固有缺陷，提供了一种识别岩性的新方法。
• The experiment shows that self - organized characteristic map neural network is feasible for lithologic identification of logging data and has a high rate of identification
  实验结果表明：自组织特征映射神经网络对测井数据进行岩性识别是可行的，而且识别率较高，是一种行之有效的岩性识别的好方法。
• Identifying lithology according to logging data by self - organized neural network not only has stronger self - organizability , adaptability and fault - tolerance , but also has small calculation and gets quick returns compared with other methods of netural network
  摘要利用自组织神经网络对测井数据进行岩性识别，具有较强的自组织性、适应性和较高的容错能力，与其他神经网络算法相比，计算量小、收效速度快。
• The paper consist of three parts as follows : 1 . the method to calculate formation pressure : the method to calculate formation pressure in this paper is based on the equivalent depth technique , and it extract log characteristic parameters based on log ' s auto - separating and the lithology recognition . the automatization and precision of formation pressure calculation are upgraded
  地层压力计算技术：以等效深度法为基本原理，辅以测井曲线自动分段和岩性识别基础上的测井特征参数提取，建立了本论文所采用的地层压力计算技术，提高了地层压力计算的自动化程度和计算精度。
• This study made a conclusion ? amely in order to realize following the geological target while drilling , on the basis of making a better geological and drilling design for horizontal well , we must make full use of mwd , lwd and integrate logging to carry out lithfacy identifying in real time , the lwd interpretation and formation evaluation , to set up geological model of target formation , to select geosteering marked formation and compare simulative curves with lwd curves f to fix on the drilling direction of bit upper and declination , the position in target oil - gas layer , to revise borehole track in real time , to make it extend in reservoir better interval as possible
  研究认为，在做好水平井地质设计和钻井设计的基础上，要实现随钻跟踪地质目标钻井，必须充分利用随钻测量、随钻测井和录井等资料，从实时岩性识别、随钻测井解释和地层评价、目标层地质模型建立、导向标志层的选取及模拟曲线对比等方面入手，确定钻头上下倾钻进方向及在目标层中的位置，以实时调整井眼轨迹，使其尽可能在储层物性较好的部位延伸。
• By the practical studying , the author has a issue , in terms of well logging - facy identifying , on the basis of curve automatic classifying and reading , extract some reflecting lith parameter from the data and information while drilling to establish logfacy - lithfacy pattern , adopt gray conjunction method to recognize the rock type of drilling geological profile in real time
  研究认为，从测井相识别的角度出发，在曲线自动分层取值的基础上，从随钻资料中提取与岩性密切相关的参数建立测井相-岩相模式，采用灰色关联判别法实时识别钻井地质剖面的岩性是可行的。本研究所提出的随钻岩性识别方法具有推广使用价值。