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    • 3. 发明申请
    • SYSTEM AND METHOD OF PREDICTING GAS SATURATION OF A FORMATION USING NEURAL NETWORKS
    • 使用神经网络预测气体饱和度的系统和方法
    • US20110282818A1
    • 2011-11-17
    • US13146437
    • 2009-04-21
    • Dingding ChenWeijun GuoLarry A. Jacobson
    • Dingding ChenWeijun GuoLarry A. Jacobson
    • G06N3/02
    • G01V5/125
    • Predicting gas saturation of a formation using neural networks. At least some of the illustrative embodiments include obtaining a gamma count rate decay curve one each for a plurality of gamma detectors of a nuclear logging tool (the gamma count rate decay curves recorded at a particular borehole depth), applying at least a portion of each gamma count rate decay curve to input nodes of a neural network, predicting a value indicative of gas saturation of a formation (the predicting by the neural network in the absence of a formation porosity value supplied to the neural network), and producing a plot of the value indicative of gas saturation of the formation as a function of borehole depth.
    • 使用神经网络预测地层的气体饱和度。 至少一些示例性实施例包括获得针对核测井工具的多个伽马检测器(在特定钻孔深度处记录的伽马计数速率衰减曲线)中的伽马计数率衰减曲线,每个伽马计数率衰减曲线应用至少一部分每个 伽马计数速率衰减曲线到神经网络的输入节点,预测指示地层的气体饱和度的值(在没有提供给神经网络的地层孔隙度值的情况下由神经网络预测),并且产生 表示地层气体饱和度的值作为钻孔深度的函数。
    • 4. 发明申请
    • SYSTEMS AND METHODS FOR DOWNHOLE FLUID TYPING WITH PULSED NEUTRON LOGGING
    • 具有脉冲中子记录的井下流体类型的系统和方法
    • US20110202276A1
    • 2011-08-18
    • US13124930
    • 2009-09-28
    • Jerome TruaxSteve ZannoniDaniel DorfferWeijun Guo
    • Jerome TruaxSteve ZannoniDaniel DorfferWeijun Guo
    • G06F19/00
    • G01V5/104
    • Downhole fluid typing with pulsed neutron logging. A method comprises obtaining gamma count rates at a particular borehole depth; calculating a fluid type indicative response value for the borehole depth; determining at least one fluid type based on the response value for the particular borehole depth; and producing a display of the at least one fluid type corresponding to the borehole depth. A system comprises a downhole tool comprising a neutron source and at least one gamma detector; gamma count rates produced due to gamma arrivals at the gamma detector(s); and a processor coupled to a memory, wherein the memory stores a program that, when executed by the processor, causes the processor to: calculate a fluid type indicative response value for a particular borehole depth based on the gamma count rates; and determine at least one fluid type based on the response value for the particular borehole depth.
    • 井下流体分类与脉冲中子测井。 一种方法包括在特定钻孔深度获得伽马计数率; 计算井眼深度的流体类型指示响应值; 基于特定钻孔深度的响应值确定至少一种流体类型; 以及产生对应于钻孔深度的至少一种流体类型的显示。 一种系统包括井下工具,其包括中子源和至少一个伽马检测器; 由于γ检测器处的​​伽马到达而产生的伽马计数率; 以及处理器,其耦合到存储器,其中所述存储器存储程序,所述程序在由所述处理器执行时使所述处理器基于所述伽马计数率来计算特定钻孔深度的流体类型指示响应值; 并且基于特定钻孔深度的响应值来确定至少一种流体类型。
    • 6. 发明授权
    • System and method of predicting gas saturation of a formation using neural networks
    • 使用神经网络预测地层气饱和度的系统和方法
    • US08898045B2
    • 2014-11-25
    • US13146437
    • 2009-04-21
    • Dingding ChenWeijun GuoLarry A. Jacobson
    • Dingding ChenWeijun GuoLarry A. Jacobson
    • G06E1/00G01V5/12
    • G01V5/125
    • Predicting gas saturation of a formation using neural networks. At least some of the illustrative embodiments include obtaining a gamma count rate decay curve one each for a plurality of gamma detectors of a nuclear logging tool (the gamma count rate decay curves recorded at a particular borehole depth), applying at least a portion of each gamma count rate decay curve to input nodes of a neural network, predicting a value indicative of gas saturation of a formation (the predicting by the neural network in the absence of a formation porosity value supplied to the neural network), and producing a plot of the value indicative of gas saturation of the formation as a function of borehole depth.
    • 使用神经网络预测地层的气体饱和度。 至少一些示例性实施例包括获得针对核测井工具的多个伽马检测器(在特定钻孔深度处记录的伽马计数速率衰减曲线)中的伽马计数率衰减曲线,每个伽马计数率衰减曲线应用至少一部分每个 伽马计数速率衰减曲线到神经网络的输入节点,预测指示地层的气体饱和度的值(在没有提供给神经网络的地层孔隙度值的情况下由神经网络预测),并且产生 表示地层气体饱和度的值作为钻孔深度的函数。
    • 9. 发明授权
    • Systems and methods for downhole fluid typing with pulsed neutron logging
    • 用脉冲中子测井技术进行井下流体分类的系统和方法
    • US08510050B2
    • 2013-08-13
    • US13124930
    • 2009-09-28
    • Jerome TruaxSteve ZannoniDaniel DorfferWeijun Guo
    • Jerome TruaxSteve ZannoniDaniel DorfferWeijun Guo
    • G01V1/40
    • G01V5/104
    • Downhole fluid typing with pulsed neutron logging. A method comprises obtaining at least one capture gamma count rate at a particular borehole depth, calculating a fluid type indicative response value for the borehole depth, and determining at least one fluid type based on the response value. A system comprises a downhole tool, including a neutron source, at least one gamma detector, and a processor coupled to a memory. The memory stores a program that, when executed by the processor, causes the processor to obtain at least one capture gamma count rate for a particular borehole depth. The processor calculates a fluid type indicative response value for the borehole depth and determines at least one fluid type based on the response value.
    • 井下流体分类与脉冲中子测井。 一种方法包括在特定钻孔深度获得至少一个捕获伽马计数率,计算钻孔深度的流体类型指示响应值,以及基于响应值确定至少一种流体类型。 系统包括井下工具,其包括中子源,至少一个伽马检测器和耦合到存储器的处理器。 存储器存储程序,当由处理器执行时,处理器获得针对特定钻孔深度的至少一个捕获伽马计数率的程序。 处理器计算钻孔深度的流体类型指示响应值,并且基于响应值确定至少一种流体类型。