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1. 发明申请

WO2020018069A1 OPTICAL SENSOR ADAPTIVE CALIBRATION 审中-公开
公开(公告)号：WO2020018069A1
公开(公告)日：2020-01-23
申请号：PCT/US2018/042336
申请日：2018-07-16
申请人： HALLIBURTON ENERGY SERVICES, INC.
发明人： CHEN, Dingding , JONES, Christopher Michael , DAI, Bin , PEARL, Megan , PRICE, James M.
IPC分类号： E21B49/08 , G01V13/00 , G01V8/00
摘要： The subject disclosure provides for a method of optical sensor calibration implemented with neural networks through machine learning to make real-time optical fluid answer product prediction adapt to optical signal variation of synthetic and actual sensor inputs integrated from multiple sources. Downhole real-time fluid analysis can be performed by monitoring the quality of the prediction with each type of input and determining which type of input generalizes better. The processor can bypass the less robust routine and deploy the more robust routine for remainder of the data prediction. Operational sensor data can be incorporated from a particular optical tool over multiple field jobs into an updated calibration when target fluid sample compositions and properties become available. Reconstructed fluid models adapted to prior field job data, in the same geological or geographical area, can maximize the likelihood of quality prediction on future jobs and optimize regional formation sampling and testing applications.

2. 发明申请

WO2017164854A1 CALIBRATION MODULE FOR POOLED OPTICAL SENSORS IN DOWNHOLE FLUID ANALYSIS 审中-公开
标题翻译：池内光学传感器在井下流体分析中的标定模块
公开(公告)号：WO2017164854A1
公开(公告)日：2017-09-28
申请号：PCT/US2016/023642
申请日：2016-03-22
申请人： HALLIBURTON ENERGY SERVICES, INC.
发明人： CHEN, Dingding , JONES, Christopher, M. , DAI, Bin , GASCOOKE, Darren
IPC分类号： E21B47/135 , E21B47/26 , G01N21/49
CPC分类号： E21B49/08 , E21B43/121 , E21B44/00 , E21B2049/085 , G01N21/274 , G01N21/85 , G01N2201/1293 , G06N3/086 , G06N3/10
摘要： A method including selecting candidate sensors for pooled calibration and determining a multivariate fluid characterization model with the pooled sensors is provided. The method includes determining a virtual master kernel standardization model with the pooled sensors, implementing a calibration result into a processor circuit and determining a value of a fluid characteristic by apply ing the multivariate fluid composition model to a plurality of responses obtained from a plurality of sensor responses to the fluid sample. The plurality of responses may be obtained from the plurality of sensor responses using the virtual master kernel standardization model. The method includes optimizing a wellbore operation based on the value of the fluid characteristic. A device for implementing the above method is also provided.
摘要翻译：提供了一种方法，该方法包括选择用于汇集校准的候选传感器并且利用汇集的传感器确定多变量流体表征模型。该方法包括利用合并的传感器确定虚拟主内核标准化模型，将校准结果实施到处理器电路中，并且通过将多元流体合成模型应用于从多个传感器获得的多个响应来确定流体特性的值对流体样本的响应。可以使用虚拟主内核标准化模型从多个传感器响应获得多个响应。该方法包括基于流体特性的值来优化井筒操作。还提供了实现上述方法的设备。

3. 发明申请

WO2015094303A1 CROSS-SENSOR STANDARDIZATION 审中-公开
标题翻译：交叉传感器标准化
公开(公告)号：WO2015094303A1
公开(公告)日：2015-06-25
申请号：PCT/US2013/076660
申请日：2013-12-19
申请人： HALLIBURTON ENERGY SERVICES, INC.
发明人： CHEN, Dingding , PERKINS, David L.
IPC分类号： G06F19/00
CPC分类号： G01J1/0295 , E21B41/00 , E21B47/123 , G01D18/002
摘要： The disclosed embodiments include a method, apparatus, and computer program product for generating a cross-sensor standardization model. For example, one disclosed embodiment includes a system that includes at least one processor; at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations comprising selecting a representative sensor from a group of sensors comprising at least one of same primary optical elements and similar synthetic optical responses and calibrating a cross-sensor standardization model based on a matched data pair for each sensor in the group of sensors and for the representative sensor. In one embodiment, the at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations further comprises generating the matched data pair, wherein the matched data pair comprises calibration input data and calibration output data.
摘要翻译：所公开的实施例包括用于产生交叉传感器标准化模型的方法，装置和计算机程序产品。例如，一个公开的实施例包括一个包括至少一个处理器的系统; 至少一个存储器，其耦合到所述至少一个处理器并且存储当所述至少一个处理器执行时执行操作的指令，所述指令包括从包括相同主要光学元件和类似合成光学响应中的至少一个的一组传感器中选择代表性传感器，以及基于传感器组中的每个传感器和代表性传感器的匹配数据对，校准交叉传感器标准化模型。在一个实施例中，所述至少一个存储器耦合到所述至少一个处理器并且存储当所述至少一个处理器执行的操作执行操作时的指令还包括生成所述匹配数据对，其中所述匹配数据对包括校准输入数据和校准输出数据。

4. 发明申请

WO2015069249A1 APPARATUS AND METHODS OF DATA ANALYSIS 审中-公开
标题翻译：数据分析的装置和方法
公开(公告)号：WO2015069249A1
公开(公告)日：2015-05-14
申请号：PCT/US2013/068868
申请日：2013-11-07
申请人： HALLIBURTON ENERGY SERVICES, INC.
发明人： PERKINS, David L , GAO, Li , JONES, Christopher Michael , CHEN, Dingding , PELLETIER, Michael T
IPC分类号： G06F19/00
CPC分类号： G01V99/00 , E21B47/00 , G01V13/00
摘要： Various embodiments include apparatus and methods to perform a correlation of data and/or a statistical analysis of data. A correlation of data can include generating a scalar product of measured responses with known responses and using a threshold to determine a correlation of the data. Statistical analysis of data can include generating a statistical measure of measurement data, comparing the statistical measure to a threshold value, and determining phase status of a fluid. Additional apparatus, systems, and methods are disclosed.
摘要翻译：各种实施例包括执行数据相关性和/或数据统计分析的装置和方法。数据的相关性可以包括生成具有已知响应的测量响应的标量积，并且使用阈值来确定数据的相关性。数据的统计分析可以包括生成测量数据的统计量度，将统计量度与阈值进行比较，以及确定流体的相位状态。公开了附加装置，系统和方法。

5. 发明申请

WO2014074108A1 INTEGRATED COMPUTATIONAL ELEMENT DESIGN OPTIMIZATION AND PERFORMANCE EVALUATION 审中-公开
标题翻译：综合计算元素设计优化与性能评估
公开(公告)号：WO2014074108A1
公开(公告)日：2014-05-15
申请号：PCT/US2012/064346
申请日：2012-11-09
申请人： HALLIBURTON ENERGY SERVICES, INC. , CHEN, Dingding , JONES, Christopher Michael , PERKINS, David L. , GAO, Li
发明人： CHEN, Dingding , JONES, Christopher Michael , PERKINS, David L. , GAO, Li
IPC分类号： G01B11/02
CPC分类号： G06N3/126
摘要： A system for integrated computational element ("ICE") design optimization and analysis utilizes a genetic algorithm to evolve layer thickness of each fixed ICE structure using a constrained multi-objective merit function. The system outputs a ranked representative group of ICE design candidates that may be used for further fabricability study, ICE combination selection, efficient statistical analysis and/or feature characterization.
摘要翻译：用于集成计算元件（“ICE”）设计优化和分析的系统利用遗传算法来利用约束多目标优值函数来演化每个固定ICE结构的层厚度。该系统输出可用于进一步可行性研究，ICE组合选择，有效统计分析和/或特征表征的ICE设计候选者的排名代表性组。

6. 发明申请

WO2014035374A1 SENSOR CHARACTERIZATION APPARATUS, METHODS, AND SYSTEMS 审中-公开
标题翻译：传感器特征装置，方法和系统
公开(公告)号：WO2014035374A1
公开(公告)日：2014-03-06
申请号：PCT/US2012/052666
申请日：2012-08-28
申请人： HALLIBURTON ENERGY SERVICES, INC. , CHEN, Dingding , GAO, Li , PELLETIER, Michael T. , RODRIGUEZ, Nestor Javier
发明人： CHEN, Dingding , GAO, Li , PELLETIER, Michael T. , RODRIGUEZ, Nestor Javier
IPC分类号： G01N9/00
CPC分类号： G01N9/002 , E21B47/10 , E21B49/08
摘要： In some embodiments, an apparatus and a system, as well as a method and an article, may operate to receive a vibration signal having a frequency and a characteristic (e.g., voltage) proportional to the vibration amplitude of a tube in a vibrating tube density sensor. Further activity may include transmitting the density of a fluid flowing through the tube based on the frequency and an elastic modulus of the tube determined by the value of the characteristic. Additional apparatus, systems, and methods are described.
摘要翻译：在一些实施例中，设备和系统以及方法和物品可以操作以接收振动信号，该振动信号具有与振动管密度中的管的振动幅度成比例的频率和特性（例如，电压）传感器。进一步的活动可以包括基于由特征值确定的管的频率和管的弹性模量来传输流过管的流体的密度。描述了附加装置，系统和方法。

7. 发明申请

WO2010123494A1 SYSTEM AND METHOD OF PREDICTING GAS SATURATION OF A FORMATION USING NEURAL NETWORKS 审中-公开
标题翻译：使用神经网络预测气体饱和度的系统和方法
公开(公告)号：WO2010123494A1
公开(公告)日：2010-10-28
申请号：PCT/US2009/041222
申请日：2009-04-21
申请人： HALLIBURTON ENERGY SERVICES, INC. , CHEN, Dingding , GUO, Weijun , JACOBSON, Larry, A.
发明人： CHEN, Dingding , GUO, Weijun , JACOBSON, Larry, A.
IPC分类号： G01V5/12 , G01V5/04 , E21B47/00 , G01N23/06
CPC分类号： G01V5/125
摘要： 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.
摘要翻译：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。

8. 发明申请

WO2010017300A1 SYSTEMS AND METHODS EMPLOYING COOPERATIVE OPTIMIZATION-BASED DIMENSIONALITY REDUCTION 审中-公开
标题翻译：基于合作优化的尺寸减少的系统和方法
公开(公告)号：WO2010017300A1
公开(公告)日：2010-02-11
申请号：PCT/US2009/052860
申请日：2009-08-05
申请人： HALLIBURTON ENERGY SERVICES, INC. , CHEN, Dingding , HAMID, Syed , DIX, Michael, C.
发明人： CHEN, Dingding , HAMID, Syed , DIX, Michael, C.
IPC分类号： G01V1/40
CPC分类号： G01V1/34 , G06N3/126 , G06T11/206
摘要： Dimensionality reduction systems and methods facilitate visualization, understanding, and interpretation of high-dimensionality data sets, so long as the essential information of the data set is preserved during the dimensionality reduction process. In some of the disclosed embodiments, dimensionality reduction is accomplished using clustering, evolutionary computation of low-dimensionality coordinates for cluster kernels, particle swarm optimization of kernel positions, and training of neural networks based on the kernel mapping. The fitness function chosen for the evolutionary computation and particle swarm optimization is designed to preserve kernel distances and any other information deemed useful to the current application of the disclosed techniques, such as linear correlation with a variable that is to be predicted from future measurements. Various error measures are suitable and can be used.
摘要翻译：只要在维度降低过程中保留数据集的基本信息，尺寸减小系统和方法便于高维数据集的可视化，理解和解释。在一些所公开的实施例中，使用聚类，集群内核的低维度坐标的进化计算，核心位置的粒子群优化以及基于内核映射的神经网络的训练来实现维数降低。为进化计算和粒子群优化选择的适应度函数被设计为保留核心距离以及被认为对所公开技术的当前应用有用的任何其它信息，例如与将来的测量将要预测的变量的线性相关。各种错误措施是合适的，可以使用。

9. 发明申请

WO2006055467A1 COOLING APPARATUS, SYSTEMS, AND METHODS 审中-公开
标题翻译：冷却装置，系统和方法
公开(公告)号：WO2006055467A1
公开(公告)日：2006-05-26
申请号：PCT/US2005/041105
申请日：2005-11-15
申请人： HALLIBURTON ENERGY SERVICES, INC. , STORM, Bruce, H. , CHEN, Dingding , SONG, Haoshi
发明人： STORM, Bruce, H. , CHEN, Dingding , SONG, Haoshi
IPC分类号： H05K7/20 , E21B36/00
CPC分类号： H05K7/20336 , F28D15/06 , F28F13/14
摘要： Apparatus and systems, as well as methods and articles, may operate to actively cool an electronic device using a first heat removing cooling element, and to induce a thermal gradient in a heat pipe by conducting heat from a hot side of the first heat removing cooling element to a cold side of a second heat removing cooling element using the heat pipe. The heat pipe may comprise a variable conductance heat pipe. The apparatus and system may operate in a downhole environment, including logging and drilling operations.
摘要翻译：设备和系统以及方法和制品可以操作以使用第一除热冷却元件主动冷却电子设备，并且通过从第一除热冷却的热侧传导热量来引导热管中的热梯度元件到使用热管的第二除热冷却元件的冷侧。热管可以包括可变电导热管。设备和系统可以在井下环境中操作，包括测井和钻井操作。

10. 发明申请

WO2017086961A1 SYSTEM AND METHODS FOR CROSS-TOOL OPTICAL FLUID MODEL VALIDATION AND REAL-TIME APPLICATION 审中-公开
标题翻译：用于跨工具光学流体模型验证和实时应用的系统和方法
公开(公告)号：WO2017086961A1
公开(公告)日：2017-05-26
申请号：PCT/US2015/061487
申请日：2015-11-19
申请人： HALLIBURTON ENERGY SERVICES, INC.
发明人： CHEN, Dingding , DAI, Bin , JONES, Christopher Michael , GASCOOKE, Darren , HE, Tian
IPC分类号： E21B49/08 , E21B47/00 , G01V8/02
CPC分类号： G01V8/02 , E21B47/102 , E21B49/08 , G01N33/18 , G01N33/225 , G01N33/241 , G01N33/2823 , G06F17/5009 , G06N3/04
摘要： A method of cross-tool optical fluid model validation includes selecting verified field data measured with a first sensor of an existing tool as validation fluids and selecting a second sensor for a new tool or on a different existing tool. The method may also include applying cross-tool optical data transformation to the validation fluids in a tool parameter space from the first sensor to the second sensor, and calculating the synthetic optical responses of the second sensor on the validation fluids through cross-space data transformation. The method may further include determining a new or adjusting an existing operational fluid model of the second sensor in a synthetic parameter space according to the candidate model performance evaluated on the validation fluids, and optimizing well testing and sampling operation based on real-time estimated formation fluid characteristics using the validated fluid models of the second sensor in an operating tool.
摘要翻译：横向工具光学流体模型验证的方法包括选择用现有工具的第一传感器测量的经验证的现场数据作为验证流体并选择用于新工具或不同现有工具的第二传感器。该方法还可以包括将交叉工具光学数据变换应用于工具参数空间中的验证流体从第一传感器到第二传感器，并且通过跨空间数据变换计算第二传感器对验证流体的合成光学响应。该方法可以进一步包括根据在验证流体上评估的候选模型性能确定合成参数空间中的新的或调整第二传感器的现有操作流体模型，并且基于实时估计形成来优化试井和采样操作使用操作工具中第二传感器的经验证流体模型的流体特性。

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