Patents by Inventor Jacky M. Wiener

Jacky M. Wiener 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).

  • Permeability prediction systems and methods using quadratic discriminant analysis
    Patent number: 9176255
    Abstract: Permeability prediction systems and methods using quadratic discriminant analysis are presented. At least one disclosed method embodiment includes: acquiring formation property measurements at a plurality of positions along at least one borehole in a study area; identifying clusters in a plurality of points representing the formation property measurements at the plurality of postions; and determining a system permeability value for each cluster. Quadratic Discriminant Analysis (“QDA”) is used to associate one the clusters with each position along the one or more boreholes, thereby determining a system permeability prediction for each position. The total system permeability can then be predicted by aggregating the system permeability predictions.
    Type: Grant
    Filed: December 8, 2011
    Date of Patent: November 3, 2015
    Assignee: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Jacky M. Wiener, Muthukumarappan Ramurthy
  • PERMEABILITY PREDICTION SYSTEMS AND METHODS USING QUADRATIC DISCRIMINANT ANALYSIS
    Publication number: 20150039235
    Abstract: Permeability prediction systems and methods using quadratic discriminant analysis are presented. At least one disclosed method embodiment includes: acquiring formation property measurements at a plurality of positions along at least one borehole in a study area; identifying clusters in a plurality of points representing the formation property measurements at the plurality of postions; and determining a system permeability value for each cluster. Quadratic Discriminant Analysis (“QDA”) is used to associate one the clusters with each position along the one or more boreholes, thereby determining a system permeability prediction for each position. The total system permeability can then be predicted by aggregating the system permeability predictions.
    Type: Application
    Filed: December 8, 2011
    Publication date: February 5, 2015
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Jacky M. Wiener, Muthukumarappan Ramurthy
  • Neural network training data selection using memory reduced cluster analysis for field model development
    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.
  • Neural network training data selection using memory reduced cluster analysis for field model development
    Publication number: 20040133531
    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: Application
    Filed: March 21, 2003
    Publication date: July 8, 2004
    Inventors: Dingding Chen, John A. Quirein, Jacky M. Wiener, Jeffery L. Grable, Syed Hamid, Harry D. Smith
  • Neural network interpretation of aeromagnetic data
    Patent number: 5355313
    Abstract: A method for determining depth to basement from aeromagnetic data utilizes neural networks to automate the laborious process of profile interpretation. The neural networks provide consistency, accuracy and overall quality without bias of interpretation.
    Type: Grant
    Filed: October 25, 1991
    Date of Patent: October 11, 1994
    Assignee: Texaco Inc.
    Inventors: Robert F. Moll, William C. Pearson, John R. Rogers, Jacky M. Wiener
  • Method for estimating formation permeability from wireline logs using neural networks
    Patent number: 5251286
    Abstract: A method for determining rock formation permeability from wireline well logs utilizes neural networks. The neural networks provide consistency, accuracy and overall quality without bias to the calculations.
    Type: Grant
    Filed: March 16, 1992
    Date of Patent: October 5, 1993
    Assignee: Texaco, Inc.
    Inventors: Jacky M. Wiener, Robert F. Moll, John A. Rogers