Patents by Inventor Dingding Chen

Dingding Chen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 8374974
    Abstract: A system and method for selecting a training data set from a set of multidimensional geophysical input data samples for training a model to predict target data. The input data may be data sets produced by a pulsed neutron logging tool at multiple depth points in a cases well. Target data may be responses of an open hole logging tool. The input data is divided into clusters. Actual target data from the training well is linked to the clusters. The linked clusters are analyzed for variance, etc. and fuzzy inference is used to select a portion of each cluster to include in a training set. The reduced set is used to train a model, such as an artificial neural network. The trained model may then be used to produce synthetic open hole logs in response to inputs of cased hole log data.
    Type: Grant
    Filed: March 21, 2003
    Date of Patent: February 12, 2013
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dingding Chen, John A. Quirein, Jacky M. Wiener, Jeffery L. Grable, Syed Hamid, Harry D. Smith, Jr.
  • Patent number: 8355873
    Abstract: Reservoir characterization based on observations of displacements at the earth's surface. One method of characterizing a reservoir includes the steps of: detecting a response of the reservoir to a stimulus, the stimulus causing a pressure change in the reservoir; and determining a characteristic of the reservoir from the response to the stimulus. The response may be the pressure change which varies periodically over time, or a set of displacements of a surface of the earth. In another example, a method includes the steps of: detecting a set of displacements of the earth's surface corresponding to a pressure change in the reservoir; and determining a characteristic of the reservoir from the surface displacements. In yet another example, a method includes the steps of: detecting a set of displacements of the earth's surface corresponding to a change in volume of the reservoir; and determining a characteristic of the reservoir from the surface displacements.
    Type: Grant
    Filed: November 29, 2005
    Date of Patent: January 15, 2013
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Ali Mese, Syed Hamid, Dingding Chen, Harry D. Smith, Jr., John Howard, Neal Skinner
  • Publication number: 20120109604
    Abstract: A model is disclosed that includes an intelligent ligent linear programming (“ILP”) member to produce a ILP result, a member selected from the group consisting of a feed-forward neural network (“FNN”) to produce a FNN result and a geochemical normative analysis (“GNA”) model to produce a GNA result. The model also includes a result generator to combine the ILP result with the result from the other member to produce the estimates of the mineral content of the sample.
    Type: Application
    Filed: August 27, 2009
    Publication date: May 3, 2012
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Dingding Chen, Syed Hamid, Michael Charles Dix
  • Patent number: 8065244
    Abstract: Various neural-network based surrogate model construction methods are disclosed herein, along with various applications of such models. Designed for use when only a sparse amount of data is available (a “sparse data condition”), some embodiments of the disclosed systems and methods: create a pool of neural networks trained on a first portion of a sparse data set; generate for each of various multi-objective functions a set of neural network ensembles that minimize the multi-objective function; select a local ensemble from each set of ensembles based on data not included in said first portion of said sparse data set; and combine a subset of the local ensembles to form a global ensemble. This approach enables usage of larger candidate pools, multi-stage validation, and a comprehensive performance measure that provides more robust predictions in the voids of parameter space.
    Type: Grant
    Filed: March 13, 2008
    Date of Patent: November 22, 2011
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dingding Chen, Allan Zhong, Syed Hamid, Stanley Stephenson
  • Publication number: 20110282818
    Abstract: 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.
    Type: Application
    Filed: April 21, 2009
    Publication date: November 17, 2011
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Dingding Chen, Weijun Guo, Larry A. Jacobson
  • Patent number: 8024936
    Abstract: 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.
    Type: Grant
    Filed: November 16, 2004
    Date of Patent: September 27, 2011
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Bruce H Storm, Dingding Chen, Haoshi Song
  • Publication number: 20110137566
    Abstract: Processing gamma count rate decay curves using neural networks. At least some of the illustrative embodiments are methods comprising 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 the gamma count rate decay curves to input nodes of a neural network, predicting by the neural network a geophysical parameter of the formation surrounding the borehole, repeating the obtaining, applying and predicting for a plurality of borehole depths, and producing a plot of the geophysical parameter of the formation as a function of borehole depth.
    Type: Application
    Filed: August 26, 2008
    Publication date: June 9, 2011
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Larry A. Jacobson, Dingding Chen, John A. Quirein
  • Patent number: 7814036
    Abstract: An artificial neural network, ANN, and method of training the ANN for inversion of logging tool signals into well logs of formation parameters is disclosed. Properly selected synthetic models of earth formations are used to train the ANN. The models include Oklahoma and chirp type of formations. In each model parameter contrasts of from 10 to 1 to about 100 to 1 are included. Models including maximum and minimum parameter values spanning the operating range of the selected logging tool are included. Parameter contrasts at interfaces are limited to realistic values found in earth formations. The selected models are used to generate synthetic tool signals, which are then used as inputs to the ANN for training. When the ANN coefficients are properly adjusted to produce an output matching the original models, the ANN can be used for inversion of any real signals from the selected logging tool.
    Type: Grant
    Filed: June 19, 2003
    Date of Patent: October 12, 2010
    Assignee: Haliburton Energy Services, Inc.
    Inventors: Dingding Chen, Luis E. San Martin, Gulamabbas A. Merchant, Robert W. Strickland, Martin T. Hagan
  • Publication number: 20100040281
    Abstract: 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.
    Type: Application
    Filed: August 12, 2008
    Publication date: February 18, 2010
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Dingding CHEN, Syed HAMID, Michael C. DIX
  • Patent number: 7613665
    Abstract: Methods of creating and using robust neural network ensembles are disclosed. Some embodiments take the form of computer-based methods that comprise receiving a set of available inputs; receiving training data; training at least one neural network for each of at least two different subsets of the set of available inputs; and providing at least two trained neural networks having different subsets of the available inputs as components of a neural network ensemble configured to transform the available inputs into at least one output. The neural network ensemble may be applied as a log synthesis method that comprises: receiving a set of downhole logs; applying a first subset of downhole logs to a first neural network to obtain an estimated log; applying a second, different subset of the downhole logs to a second neural network to obtain an estimated log; and combining the estimated logs to obtain a synthetic log.
    Type: Grant
    Filed: June 24, 2005
    Date of Patent: November 3, 2009
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dingding Chen, John A. Quirein, Harry D. Smith, Jr., Syed Hamid, Jeffery L. Grable
  • Patent number: 7610251
    Abstract: Well control systems and associated methods. A well control method includes the steps of drilling a wellbore and predicting a change in flow between the wellbore and a reservoir prior to the change occurring, the predicting step being performed, and the change in flow occurring while drilling. Another well control method includes the steps of: sensing at least one first drilling operation variable while drilling a wellbore, thereby generating first sensed variables; sensing at least one second drilling operation variable while drilling the wellbore, thereby generating second sensed variables; and training a predictive device, using the first and second sensed variables, to predict the second drilling operation variable at a selected time.
    Type: Grant
    Filed: January 17, 2006
    Date of Patent: October 27, 2009
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Sara Shayegi, Craig W. Godfrey, Dingding Chen, Roger L. Schultz
  • Patent number: 7587373
    Abstract: Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
    Type: Grant
    Filed: November 9, 2005
    Date of Patent: September 8, 2009
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Harry D. Smith, Jr., John A. Quirein, Jeffery L. Grable, Dingding Chen
  • Publication number: 20080228680
    Abstract: Various neural-network based surrogate model construction methods are disclosed herein, along with various applications of such models. Designed for use when only a sparse amount of data is available (a “sparse data condition”), some embodiments of the disclosed systems and methods: create a pool of neural networks trained on a first portion of a sparse data set; generate for each of various multi-objective functions a set of neural network ensembles that minimize the multi-objective function; select a local ensemble from each set of ensembles based on data not included in said first portion of said sparse data set; and combine a subset of the local ensembles to form a global ensemble. This approach enables usage of larger candidate pools, multi-stage validation, and a comprehensive performance measure that provides more robust predictions in the voids of parameter space.
    Type: Application
    Filed: March 13, 2008
    Publication date: September 18, 2008
    Applicant: Halliburton Energy Services Inc.
    Inventors: Dingding Chen, Allan Zhong, Syed Hamid, Stanley Stephenson
  • Patent number: 7280987
    Abstract: A system and method for generating a neural network ensemble. Conventional algorithms are used to train a number of neural networks having error diversity, for example by having a different number of hidden nodes in each network. A genetic algorithm having a multi-objective fitness function is used to select one or more ensembles. The fitness function includes a negative error correlation objective to insure diversity among the ensemble members. A genetic algorithm may be used to select weighting factors for the multi-objective function. In one application, a trained model may be used to produce synthetic open hole logs in response to inputs of cased hole log data.
    Type: Grant
    Filed: March 26, 2004
    Date of Patent: October 9, 2007
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dingding Chen, Syed Hamid, Harry D. Smith, Jr.
  • Publication number: 20070219128
    Abstract: The present invention relates to the use of pufferfish type I collagen extract as effective ingredient in the manufacture of medicaments and health-care foods for prevention and treatment of the following diseases, wherein the main chemical components and active components of the pufferfish type I collagen extract are natural pufferfish type I collagen or denatured pufferfish type I collagen extract and partial hydrolysates thereof. The present invention further relates to processes for the production of said pufferfish type I collagen extract, immunological assay methods of said extract, and uses of said extract as effective ingredient in treatment and health-care.
    Type: Application
    Filed: August 27, 2004
    Publication date: September 20, 2007
    Applicant: NANJING BESSON PHARMACY CO., LTD
    Inventors: Dingding Chen, Lizhong Gao
  • Publication number: 20070168056
    Abstract: Well control systems and associated methods. A well control method includes the steps of drilling a wellbore and predicting a change in flow between the wellbore and a reservoir prior to the change occurring, the predicting step being performed, and the change in flow occurring while drilling. Another well control method includes the steps of: sensing at least one first drilling operation variable while drilling a wellbore, thereby generating first sensed variables; sensing at least one second drilling operation variable while drilling the wellbore, thereby generating second sensed variables; and training a predictive device, using the first and second sensed variables, to predict the second drilling operation variable at a selected time.
    Type: Application
    Filed: January 17, 2006
    Publication date: July 19, 2007
    Inventors: Sara Shayegi, Craig Godfrey, Dingding Chen, Roger Schultz
  • Publication number: 20070124079
    Abstract: Reservoir characterization based on observations of displacements at the earth's surface. One method of characterizing a reservoir includes the steps of: detecting a response of the reservoir to a stimulus, the stimulus causing a pressure change in the reservoir; and determining a characteristic of the reservoir from the response to the stimulus. The response may be the pressure change which varies periodically over time, or a set of displacements of a surface of the earth. In another example, a method includes the steps of: detecting a set of displacements of the earth's surface corresponding to a pressure change in the reservoir; and determining a characteristic of the reservoir from the surface displacements. In yet another example, a method includes the steps of: detecting a set of displacements of the earth's surface corresponding to a change in volume of the reservoir; and determining a characteristic of the reservoir from the surface displacements.
    Type: Application
    Filed: November 29, 2005
    Publication date: May 31, 2007
    Inventors: Ali Mese, Syed Hamid, Dingding Chen, Harry Smith, John Howard, Neal Skinner
  • Publication number: 20070011114
    Abstract: Methods of creating and using robust neural network ensembles are disclosed. Some embodiments take the form of computer-based methods that comprise receiving a set of available inputs; receiving training data; training at least one neural network for each of at least two different subsets of the set of available inputs; and providing at least two trained neural networks having different subsets of the available inputs as components of a neural network ensemble configured to transform the available inputs into at least one output. The neural network ensemble may be applied as a log synthesis method that comprises: receiving a set of downhole logs; applying a first subset of downhole logs to a first neural network to obtain an estimated log; applying a second, different subset of the downhole logs to a second neural network to obtain an estimated log; and combining the estimated logs to obtain a synthetic log.
    Type: Application
    Filed: June 24, 2005
    Publication date: January 11, 2007
    Applicant: Halliburton Energy Services, Inc.
    Inventors: Dingding Chen, John Quirein, Harry Smith, Syed Hamid, Jeffery Grable
  • Publication number: 20070011115
    Abstract: Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
    Type: Application
    Filed: November 9, 2005
    Publication date: January 11, 2007
    Applicant: Halliburton Energy Services, Inc.
    Inventors: Harry Smith, John Quirein, Jeffery Grable, Dingding Chen
  • Patent number: 7053787
    Abstract: A signal filtering apparatus and associated methods enable noise to be significantly reduced or eliminated from a signal. In a described embodiment, the signal is indicative of tension in a slickline. An adaptive filter is used to effectively cancel the noise from the signal, using an input signal characteristic of a noise source.
    Type: Grant
    Filed: July 2, 2002
    Date of Patent: May 30, 2006
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Roger L. Schultz, Dingding Chen, Orlando DeJesús