公开(公告)号：US10684388B2

公开(公告)日：2020-06-16

申请号：US14360214

申请日：2013-06-07

Applicant: Halliburton Energy Services, Inc.

Inventor： David L. Perkins ,  Dingding Chen ,  Christopher Michael Jones ,  Jing Shen

IPC: G01V8/10 ,  G01N21/31

Abstract: Disclosed are systems and methods that use discriminant analysis techniques and processing in order to reduce the time required to determine chemical and/or physical properties of a substance. One method includes optically interacting a plurality of optical elements with one or more known substances, each optical element being configured to detect a particular characteristic of the one or more known substances, generating an optical response from each optical element corresponding to each known substance, wherein each known substance corresponds to a known spectrum stored in an optical database, and training a neural network to provide a discriminant analysis classification model for an unknown substance, the neural network using each optical response as inputs and one or more fluid types as outputs, and the outputs corresponding to the one or more known substances.

公开(公告)号：US10656634B2

公开(公告)日：2020-05-19

申请号：US14432336

申请日：2013-05-07

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  David L. Perkins ,  Christopher Michael Jones ,  Li Gao ,  Jing Shen

IPC: G05B19/418 ,  G06N3/02 ,  G02B27/00 ,  G06E3/00 ,  G01N21/31 ,  G06N3/12 ,  G01J3/28 ,  G02B5/28 ,  G01J3/12

Abstract: This disclosure includes methods for designing a simplified Integrated Computational Element (ICE) and for optimizing a selection of a combination of ICE designs. A method for fabricating a simplified ICE having one or more film layers includes predicting an optimal thickness of each of the one or more film layers of the simplified ICE using a neural network. A method for recalibrating the fabricated ICE elements for system implementation is also disclosed. The disclosure also includes the simplified ICE designed by and the ICE combination selected by the disclosed methods. The disclosure also includes an information handling system with machine-readable instructions to perform the methods disclosed herein.

公开(公告)号：US10400550B2

公开(公告)日：2019-09-03

申请号：US15505576

申请日：2015-09-02

Applicant: HALLIBURTON ENERGY SERVICES, INC.

Inventor： Ming Gu ,  Deepak Gokaraju ,  John Andrew Quirein ,  Dingding Chen

IPC: E21B41/00 ,  E21B43/26

Abstract: A method for shale fracturing includes determining dynamic-elastic properties of a shale deposit in a geological formation. A training database is generated by three-dimensional fracture modeling. A neural network is generated in response to output results of the training database. The shale fracturing may then be performed based on the neural network.

公开(公告)号：US20190120049A1

公开(公告)日：2019-04-25

申请号：US15559800

申请日：2016-11-04

Applicant: HALLIBURTON ENERGY SERVICES, INC.

Inventor： Dingding Chen ,  Bin Dai ,  Christopher M. Jones ,  Darren Gascooke

IPC: E21B49/08 ,  G01N33/28

Abstract: System and methods for downhole fluid analysis are provided. Measurements are obtained from one or more downhole sensors along a current section of wellbore within a subsurface formation. The measurements obtained from the one or more downhole sensors are transformed into principal spectroscopy component (PSC) data. At least one fluid composition or property is estimated for the current section of the wellbore, based on the PSC data and a fluid analysis model. The fluid analysis model is refined for one or more subsequent sections of the wellbore within the subsurface formation, based at least partly on the fluid composition or property estimated for the current section of the wellbore.

公开(公告)号：US20190107434A1

公开(公告)日：2019-04-11

申请号：US16213880

申请日：2018-12-07

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  David L. Perkins

IPC: G01J1/02 ,  E21B41/00 ,  E21B47/12 ,  G01D18/00

Abstract: 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.

公开(公告)号：US20170269260A1

公开(公告)日：2017-09-21

申请号：US15303299

申请日：2015-11-18

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  Bin Dai ,  Jing Shen ,  Ming Gu

IPC: G01V13/00 ,  E21B49/08 ,  E21B47/06 ,  G01V99/00

Abstract: A method may include collecting measurement data using a first operational sensor and a second operational sensor of a downhole tool, standardizing optical responses of each operational sensor to a master sensor in a tool parameter space to obtain a standardized master sensor response, transforming the standardized master sensor response to a synthetic parameter space response of the master sensor, applying a fluid model with the synthetic parameter space response of the master sensor to predict a fluid characteristic, comparing a first prediction obtained with the fluid model from the first operational sensor with a second prediction obtained with the fluid model from the second operational sensor, determining a fluid characteristic from the first prediction and the second prediction, and optimizing a well testing and sampling operation according to the fluid characteristic.

公开(公告)号：US20170261640A1

公开(公告)日：2017-09-14

申请号：US15124282

申请日：2015-11-19

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  Bin Dai ,  Christopher Michael Jones ,  Darren Gascooke ,  Tian He

IPC: G01V8/02 ,  G01N33/28 ,  G06F17/50 ,  G01N33/18 ,  G06N3/04 ,  G01N33/24 ,  G01N33/22

CPC classification number: G01V8/02 ,  E21B47/102 ,  E21B49/08 ,  G01N33/18 ,  G01N33/225 ,  G01N33/241 ,  G01N33/2823 ,  G06F17/5009 ,  G06N3/04

Abstract: 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.

公开(公告)号：US09702248B2

公开(公告)日：2017-07-11

申请号：US14436017

申请日：2014-01-27

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  Christopher Michael Jones ,  David L. Perkins ,  Jing Shen ,  Li Gao ,  Michael T. Pelletier

IPC: G01N31/00 ,  E21B49/08 ,  E21B47/10 ,  G06F17/50 ,  G06N3/04 ,  G06N3/08 ,  G06N3/12 ,  E21B49/00

CPC classification number: E21B49/08 ,  E21B47/102 ,  E21B49/003 ,  E21B2049/085 ,  G06F17/5009 ,  G06N3/0481 ,  G06N3/08 ,  G06N3/126

Abstract: Apparatus, systems, and methods may operate to select a subset of sensor responses as inputs to each of a plurality of pre-calibrated models in predicting each of a plurality of formation fluid properties. The sensor responses are obtained and pre-processed from a downhole measurement tool. Each of the plurality of predicted formation fluid properties are evaluated by applying constraints in hydrocarbon concentrations, geo-physics, and/or petro-physics. The selection of sensor responses and the associated models from a pre-constructed model base or a candidate pool are adjusted and reprocessed to validate model selection.

公开(公告)号：US20160327684A1

公开(公告)日：2016-11-10

申请号：US14780780

申请日：2014-12-12

Applicant: Halliburton Energy Services, Inc.

Inventor： Dingding Chen ,  David L. Perkins ,  William Soltmann ,  Darren Gascooke ,  Jing Shen

IPC: G01V13/00 ,  E21B47/06 ,  E21B49/08 ,  G01V8/02 ,  G01N21/27

CPC classification number: G01V13/00 ,  E21B47/06 ,  E21B47/065 ,  E21B47/102 ,  E21B49/082 ,  G01N21/274 ,  G01V8/02

Abstract: An example method includes performing validation testing on a tool using a plurality of reference fluids, the tool having a calibrated optical sensor installed therein that includes one or more optical elements. One or more tool sensor responses from the calibrated optical sensor may be obtained and pre-processed, and the one or more tool sensor responses may be compared with calibrated optical sensor responses derived from the calibrated optical sensor during calibration and thereby detecting one or more optical sensor anomalies. The one or more optical sensor anomalies may be evaluated through performance analysis with one or more candidate models, and an alternative candidate model may be selected to mitigate the one or more optical sensor anomalies. One or more remedial options may be pursued when the alternative candidate model fails to mitigate the one or more optical sensor anomalies.

Abstract translation: 示例性方法包括使用多个参考流体对工具执行验证测试，该工具具有安装在其中的校准光学传感器，其包括一个或多个光学元件。 来自校准的光学传感器的一个或多个刀具传感器响应可以被获得并被预处理，并且一个或多个刀具传感器响应可以与在校准期间从校准的光学传感器导出的校准的光学传感器响应进行比较，从而检测一个或多个光学 传感器异常。 一个或多个光学传感器异常可以通过具有一个或多个候选模型的性能分析来评估，并且可以选择替代候选模型来减轻一个或多个光学传感器异常。 当替代候选模型不能减轻一个或多个光学传感器异常时，可以追求一个或多个补救选项。

公开(公告)号：US20160283615A1

公开(公告)日：2016-09-29

申请号：US14650820

申请日：2013-12-27

Applicant: HALLIBURTON ENERGY SERVICES, INC.

Inventor： Dingding Chen ,  David L. Perkins ,  Christopher Michael Jones ,  Jing Shen ,  Michael T. Pelletier ,  Robert Atkinson

IPC: G06F17/50 ,  G06N3/12 ,  G06N3/04 ,  G06F17/11

CPC classification number: G06F17/5009 ,  E21B49/10 ,  E21B2049/085 ,  G01N33/2823 ,  G06F17/11 ,  G06F19/704 ,  G06F19/707 ,  G06F2217/16 ,  G06N3/0481 ,  G06N3/126

Abstract: The disclosed embodiments include a method, apparatus, and computer program product for determining a synthetic gas-oil-ratio for a gas dominant fluid. For example, one disclosed embodiment includes a system that includes at least one processor, and 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 that include optimizing a gas-oil-ratio database using a genetic algorithm and a multivariate regression simulator and generating a synthetic gas-oil-ratio for a gas dominant fluid. In one embodiment, optimizing a gas-oil-ratio database using a genetic algorithm and a multivariate regression simulator comprises defining gas-oil-ratio searching boundaries gas-oil-ratio for each gas dominant fluid; assigning randomly a synthetic gas-oil-ratio for each gas dominant fluid in a set of gas dominant fluids in the initial population of gas-oil-ratio data, wherein the gas-oil-ratio for each gas dominant fluid is within the searching boundaries; generating an initial population of gas-oil-ratio data for a set of gas dominant fluids; and evaluating synthetic gas-oil-ratio assignments for the initial population using the multivariate regression simulator.

Abstract translation: 所公开的实施例包括用于确定气体优先流体的合成瓦斯油比的方法，装置和计算机程序产品。 例如，一个公开的实施例包括一个系统，该系统包括至少一个处理器，以及耦合到该至少一个处理器的至少一个存储器，并且存储当由至少一个处理器执行时执行包括优化气 - 油 - 比例数据库，使用遗传算法和多元回归模拟器，并为气体主导流体产生合成瓦斯油比。 在一个实施例中，使用遗传算法和多元回归模拟器来优化瓦斯油比数据库包括为每个气体主导流体定义瓦斯油比搜索边界瓦斯油比; 在原始油气比数据的初始群体中随机分配一组气体主导流体中的每种气体主导流体的合成瓦斯油比，其中每个气体主导流体的瓦斯 - 油比在搜索边界内 ; 产生一组气体主导流体的初始油气比数据; 并使用多元回归模拟器评估初始种群的合成瓦斯油比分配。