Patents by Inventor Dwight David Fulton

Dwight David Fulton 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).

  • Publication number: 20210087925
    Abstract: Disclosed are systems and methods for receiving historical production data associated with at least one hydraulic fracturing well, receiving time-series data associated with the at least one hydraulic fracturing well, the time-series data representing at least one type of data, receiving non-temporal data associated with the at least one hydraulic fracturing well, generating a machine learning model based on the historical production data, the time-series data associated with the at least one hydraulic fracturing well and based on an original job design during a first stage of the job at a particular hydraulic fracturing well, and the non-temporal data, determining an optimized job design for the particular hydraulic fracturing well having an objective function using a prediction based on the machine learning model, and implementing the optimized job design for the particular hydraulic fracturing well.
    Type: Application
    Filed: September 25, 2019
    Publication date: March 25, 2021
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Peyman HEIDARI, Harold Grayson WALTERS, Dwight David FULTON, Manisha BHARDWAJ
  • Publication number: 20210018655
    Abstract: Disclosed are systems and methods for obtaining input data comprising properties associated with at least one parent well and a child well associated with the at least one parent well, dividing the input data into a training data subset, a validation data subset, and a test data subset, selecting at least one machine learning model using the training data subset, the validation data subset, and the test data subset based on k-fold cross validation, tuning hyper parameters for each of the at least one machine learning model, and generating a learning output using the at least one machine learning model and the hyper parameters for each of the at least one machine learning model, the learning output indicating a test root-mean-square error (RMSE) and a training RMSE.
    Type: Application
    Filed: July 18, 2019
    Publication date: January 21, 2021
    Applicant: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Jianlei Sun, Jianfu Ma, Dwight David Fulton, Ajish Sreeni Radhakrishnan Potty
  • Publication number: 20200319368
    Abstract: A wellbore trajectory survey, having an ordered plurality of survey points, is acquired. Each of the plurality of survey points has a measured depth, an inclination, and a geographic location of the point in the wellbore corresponding to the survey point. The wellbore trajectory survey is ordered on measured depth. The processor identifies a minimum lateral measured depth (min_LMD), a maximum lateral measured depth (max_LMD). The processor identifies a mid-lateral point (mid_LMP) in the plurality of survey points whose measured depth (mid_LMD) is greater than min_LMD and less than max_LMD.
    Type: Application
    Filed: December 28, 2017
    Publication date: October 8, 2020
    Applicant: Halliburton Energy Services, Inc.
    Inventors: Manisha Bhardwaj, Dwight David Fulton
  • Patent number: 10087746
    Abstract: One example of well treatment design based on three-dimensional wellbore shape can be implemented as a computer-implemented method. Wellbore data including acoustic logging data that defines an internal shape of a wall of the wellbore at multiple locations around the perimeter of the wellbore can be received. A volume of an open hole portion of the wellbore that includes the multiple locations can be determined using the wellbore data. Using the volume of the open hole portion of the wellbore, a volume of a fluid loss treatment to treat the portion of the wellbore for well fluid loss can be determined.
    Type: Grant
    Filed: February 28, 2014
    Date of Patent: October 2, 2018
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dwight David Fulton, Julio Vasquez
  • Publication number: 20170030187
    Abstract: One example of well treatment design based on three-dimensional wellbore shape can be implemented as a computer-implemented method. Wellbore data including acoustic logging data that defines an internal shape of a wall of the wellbore at multiple locations around the perimeter of the wellbore can be received. A volume of an open hole portion of the wellbore that includes the multiple locations can be determined using the wellbore data. Using the volume of the open hole portion of the wellbore, a volume of a fluid loss treatment to treat the portion of the wellbore for well fluid loss can be determined.
    Type: Application
    Filed: February 28, 2014
    Publication date: February 2, 2017
    Inventors: Dwight David Fulton, Julio Vasquez
  • Patent number: 9417970
    Abstract: A method, system, and apparatus, including a program encoded on computer-readable medium, for detecting duplicate data files to be stored in a well job data archive includes identifying a well job data file for storage in a well job data archive and performing an initial duplicate check and a secondary duplicate check to determine if the well job data file is a duplicate of a data file stored in the well job data archive, as well as a quality assurance test of the file data. At least one of the well job data file or one or more of the data files stored in the well job data archive is identified as a duplicate data file based on the initial and secondary duplicate checks, and the well job data file is stored in the well job data archive in accordance with the initial and secondary duplicate checks and the identification of a duplicate data file.
    Type: Grant
    Filed: February 27, 2014
    Date of Patent: August 16, 2016
    Assignee: Halliburton Energy Services, Inc.
    Inventors: Dwight David Fulton, Jon Matthew Orth, Pooja Nitin Khanapurkar, Venu Madhav Reddy Amudala
  • Publication number: 20150286954
    Abstract: A data mining and analysis system which analyzes a database of wellbore-related data in order to determine those predictor variables which influence or predict well performance.
    Type: Application
    Filed: October 31, 2012
    Publication date: October 8, 2015
    Inventors: Marko Maucec, Srimoyee Bhattacharya, Jeffrey Marc Yarus, Dwight David Fulton, Ajay Pratap Singh
  • Publication number: 20150242411
    Abstract: A method, system, and apparatus, including a program encoded on computer-readable medium, for detecting duplicate data files to be stored in a well job data archive includes identifying a well job data file for storage in a well job data archive and performing an initial duplicate check and a secondary duplicate check to determine if the well job data file is a duplicate of a data file stored in the well job data archive, as well as a quality assurance test of the file data. At least one of the well job data file or one or more of the data files stored in the well job data archive is identified as a duplicate data file based on the initial and secondary duplicate checks, and the well job data file is stored in the well job data archive in accordance with the initial and secondary duplicate checks and the identification of a duplicate data file.
    Type: Application
    Filed: February 27, 2014
    Publication date: August 27, 2015
    Applicant: Halliburton Energy Services, Inc.
    Inventors: Dwight David Fulton, Jon Matthew Orth, Pooja Nitin Khanapurkar, Venu Madhav Reddy Amudala
  • Publication number: 20090182693
    Abstract: A method for generating an artificial neural network ensemble for determining stimulation design parameters. A population of artificial neural networks is trained to produce one or more output values in response to a plurality of input values. The population of artificial neural networks is optimized to create an optimized population of artificial neural networks. A plurality of ensembles of artificial neural networks is selected from the optimized population of artificial neural networks and optimized using a genetic algorithm having a multi-objective fitness function. The ensemble with the desired prediction accuracy based on the multi-objective fitness function is then selected.
    Type: Application
    Filed: January 14, 2008
    Publication date: July 16, 2009
    Inventors: Dwight David Fulton, Stanley V. Stephenson