Patents by Inventor David Potter

David Potter 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: 20240067603
    Abstract: Biguanide compounds of formula where R1 comprises a cubanyl-substituted alkyl and R2 comprises a substituted or unsubstituted alkyl, and their use in the treatment of cancers and viral infections are described.
    Type: Application
    Filed: December 16, 2021
    Publication date: February 29, 2024
    Inventors: David A. POTTER, Zhijun GUO, Gunda GEORG, Kwon Ho HONG, Jianxun LEI, Elizabeth AMBROSE, Kris WHITE
  • Patent number: 11808906
    Abstract: A method for training a backpropagation-enabled segmentation process is used for identifying an occurrence of a sub-surface feature. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A prediction of the occurrence of the subsurface feature has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.
    Type: Grant
    Filed: September 10, 2019
    Date of Patent: November 7, 2023
    Assignee: SHELL USA, INC.
    Inventors: Donald Paul Griffith, Sam Ahmad Zamanian, Russell David Potter
  • Patent number: 11802984
    Abstract: A method for improving a backpropagation-enabled process for identifying subsurface features from seismic data involves a model that has been trained with an initial set of training data. A target data set is used to compute a set of initial inferences on the target data set that are combined with the initial training data to define updated training data. The model is trained with the updated training data. Updated inferences on the target data set are then computed. A set of further-updated training data is defined by combining at least a portion of the initial set of training data and at least a portion of the target data and associated updated inferences. The set of further-updated training data is used to train the model. Further-updated inferences on the target data set are then computed and used to identify the occurrence of a user-selected subsurface feature in the target data set.
    Type: Grant
    Filed: October 26, 2021
    Date of Patent: October 31, 2023
    Assignee: SHELL USA, INC.
    Inventors: Satyakee Sen, Russell David Potter, Donald Paul Griffith, Sam Ahmad Zamanian, Sergey Frolov
  • Patent number: 11698471
    Abstract: A method for training a backpropagation-enabled regression process is used for predicting values of an attribute of subsurface data. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A predicted value of the attribute has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.
    Type: Grant
    Filed: September 10, 2019
    Date of Patent: July 11, 2023
    Assignee: SHELL USA, INC.
    Inventors: Donald Paul Griffith, Sam Ahmad Zamanian, Russell David Potter
  • Patent number: 11525934
    Abstract: A method for a method for identifying a subsurface pore-filling fluid and/or lithology. A training set of field-acquired geophysical data and/or simulated geophysical data is provided to train a backpropagation-enabled process. The trained process is used on a field-acquired data set that is not part of the training set to infer presence of a subsurface pore-filling fluid and/or lithology.
    Type: Grant
    Filed: May 14, 2020
    Date of Patent: December 13, 2022
    Assignee: SHELL USA, INC.
    Inventors: Donald Paul Griffith, Sam Ahmad Zamanian, Russell David Potter, Stéphane Youri Richard Michael Joachim Gesbert, Thomas Peter Merrifield
  • Publication number: 20220128724
    Abstract: A method for improving a backpropagation-enabled process for identifying subsurface features from seismic data involves a model that has been trained with an initial set of training data. A target data set is used to compute a set of initial inferences on the target data set that are combined with the initial training data to define updated training data. The model is trained with the updated training data. Updated inferences on the target data set are then computed. A set of further-updated training data is defined by combining at least a portion of the initial set of training data and at least a portion of the target data and associated updated inferences. The set of further-updated training data is used to train the model. Further-updated inferences on the target data set are then computed and used to identify the occurrence of a user-selected subsurface feature in the target data set.
    Type: Application
    Filed: October 26, 2021
    Publication date: April 28, 2022
    Inventors: Satyakee SEN, Russell David Potter, Donald Paul Griffith, Sam Ahmad Zamanian, Sergey Frolov
  • Publication number: 20220113441
    Abstract: A method for training a backpropagation-enabled regression process is used for predicting values of an attribute of subsurface data. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A predicted value of the attribute has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.
    Type: Application
    Filed: September 10, 2019
    Publication date: April 14, 2022
    Inventors: Donald Paul GRIFFITH, Sam Ahmad ZAMANIAN, Russell David POTTER
  • Publication number: 20220113440
    Abstract: A method for training a backpropagation-enabled segmentation process is used for identifying an occurrence of a sub-surface feature. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A prediction of the occurrence of the subsurface feature has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.
    Type: Application
    Filed: September 10, 2019
    Publication date: April 14, 2022
    Inventors: Donald Paul GRIFFITH, Sam Ahmad ZAMANIAN, Russell David POTTER
  • Publication number: 20210406512
    Abstract: A method for assessing risk to a marine hydrocarbon recovery operation involves collecting a set of training images and labeling sea surface anomalies on the set of training images. The set of training images and associated labels are used to train a model via backpropagation. A set of non-training images is collected and the trained model is applied to identify a potentially disruptive sea surface anomaly on the set of non-training images. Any risk to the marine hydrocarbon recovery operation by the potentially disruptive sea surface anomaly is then assessed.
    Type: Application
    Filed: June 24, 2020
    Publication date: December 30, 2021
    Inventors: David A. LAVALLEE, Russell David POTTER, Oliver MUELLENHOFF, Benjamin Thomas KING, Stephen Edward KEEDWELL, Jason Dane MCCONOCHIE, Paul Henry GARDNER
  • Publication number: 20210390343
    Abstract: A backpropagation-enabled method for identifying a sea surface anomaly involves collecting an initial set of images and labeling the anomaly on the initial set of images. The initial set of images are selected from satellite-acquired images and/or simulated satellite images. The labels are used to train a model via backpropagation. A subsequent set of images, including satellite-acquired, airborne-acquired images, and combinations thereof, is collected and the trained model is applied to identify a sea surface anomaly on the subsequent set of images.
    Type: Application
    Filed: October 23, 2019
    Publication date: December 16, 2021
    Inventors: David A. LAVALLEE, Russell David POTTER, Stephen Edward KEEDWELL, Oliver MUELLENHOFF, Benjamin Thomas KING
  • Patent number: 11163093
    Abstract: A distribution of sand sediment class in a subsurface of the Earth is identified. Three-dimensional stratigraphic images of sediment distribution in a subsurface of the Earth are constructed, including at least two depositional domains, by simulating sediment transport and deposition over a selected time interval of sediments originating from one or more clastic sediment input sources. The simulation uses at least two equilibrium surfaces bounding the at least two depositional domains and at least two sediment classes, and updates the equilibrium surfaces in a sequence of timesteps, by accounting for sediment feed from the one or more clastic sediment input sources, erosion and deposition in accordance with mass-balance equality constraints. The images are used to identify a distribution of sand sediment class in the subsurface of the Earth suitable for acquiring hydrocarbons or fresh water, or for storing gas or liquids.
    Type: Grant
    Filed: May 14, 2018
    Date of Patent: November 2, 2021
    Assignee: SHELL OIL COMPANY
    Inventors: Oriol Falivene Aldea, Alessandro Frascati, Michele Bolla Pittaluga, Russell David Potter, Thomas Patrick Etienne Krayenbuehl
  • Publication number: 20210223422
    Abstract: A method for producing a synthetic model for training a backpropagation-enabled process for identifying subsurface features, includes generating synthetic subsurface models with realizations of subsurface features. The synthetic subsurface models are generated by introducing at least three distinct model variations selected from geologically realistic features simulating the outcome of a geologic process, simulations of geologic processes, simulations of noise sources, and combinations thereof. Labels are applied to one or more of the subsurface features in one or more of the synthetic subsurface models. The labels and the corresponding synthetic subsurface models are imported into the backpropagation-enabled process for training.
    Type: Application
    Filed: April 16, 2019
    Publication date: July 22, 2021
    Inventors: Donald Paul GRIFFITH, Sam Ahmad ZAMANIAN, Russell David POTTER, Antoine Victor Applolinaire VIAL-AUSSAVY
  • Publication number: 20210223423
    Abstract: A method for producing a synthetic model for training a backpropagation-enabled process for identifying subsurface features, includes generating noise-free synthetic subsurface models with realizations of subsurface features. The noise-free synthetic subsurface models are generated by introducing a model variation selected from geologically realistic features simulating the outcome of a geologic process, simulations of geologic processes, and combinations thereof. Labels are applied to one or more of the subsurface features in one or more of the synthetic subsurface models. A simulation of a noise source is applied to a copy of one or more of the noise-free synthetic subsurface models to produce a noise-augmented copy. The labels and the corresponding synthetic subsurface models are imported into the backpropagation-enabled process for training.
    Type: Application
    Filed: April 16, 2019
    Publication date: July 22, 2021
    Inventors: Donald Paul GRIFFITH, Sam Ahmad ZAMANIAN, Russell David POTTER, Antoine Victor Applolinaire VIAL-AUSSAVY
  • Publication number: 20200363546
    Abstract: A method for a method for identifying a subsurface pore-filling fluid and/or lithology. A training set of field-acquired geophysical data and/or simulated geophysical data is provided to train a backpropagation-enabled process. The trained process is used on a field-acquired data set that is not part of the training set to infer presence of a subsurface pore-filling fluid and/or lithology.
    Type: Application
    Filed: May 14, 2020
    Publication date: November 19, 2020
    Inventors: Donald Paul GRIFFITH, Sam Ahmad ZAMANIAN, Russell David POTTER, Stéphane Youri Richard Michael Joachim GESBERT, Thomas Peter MERRIFIELD
  • Patent number: 10545251
    Abstract: The computer system and computer-implemented method allow a user to position an interactive cursor my interaction with a user-input device, to select a point anywhere within a 3D seismic data volume that is visible on a display. In response, the computer dynamically calculates a horizon-based stratal slice that includes the user-selected point. A selected attribute rendering from seismic data that is contained within the horizon-based stratal slice is automatically calculated and dynamically shown on a second display.
    Type: Grant
    Filed: October 27, 2016
    Date of Patent: January 28, 2020
    Assignee: SHELL OIL COMPANY
    Inventors: Stéphane Youri Richard Michael Joachim Gesbert, Russell David Potter, Tjipto Santoso
  • Patent number: 10484723
    Abstract: There is provided a content automation system and a method for use by the content automation system for issuing a content management message for use in a program stream. In one implementation, such a content automation system comprises a processor and a memory, and a stream messaging module residing in the memory. The stream messaging module is configured to issue the content management message by embedding a command sequence as metadata in a container data structure, and inserting the container data structure into the program stream. The command sequence authorizes a replacement of program stream content.
    Type: Grant
    Filed: October 3, 2017
    Date of Patent: November 19, 2019
    Assignee: Disney Enterprises, Inc.
    Inventors: Michael Martin, Daniel Siewers, William Hooper, David Potter, Richard Hill, Michael Strein, Kenneth Michel, Alfredo Vincenty, James Casabella, David Converse, Guy Beverlin
  • Publication number: 20190298666
    Abstract: Certain embodiments of the invention provide a method of promoting T lymphocyte proliferation, comprising contacting in vitro, ex vivo or in vivo a population of cells comprising T lymphocytes with an effective amount of N1-hexyl-N5-benzyl biguanide (HBB), or a pharmaceutically acceptable salt thereof, wherein contact with HBB, or a pharmaceutically acceptable salt thereof, causes proliferation of the T lymphocytes.
    Type: Application
    Filed: February 21, 2019
    Publication date: October 3, 2019
    Inventors: David A. Potter, Michael Farrar, Zhijun Guo
  • Patent number: 10272055
    Abstract: Biguanide compounds and salts thereof are disclosed. Also disclosed are pharmaceutical compositions and therapeutic methods for treating certain diseases including cancer such as breast cancer.
    Type: Grant
    Filed: March 6, 2015
    Date of Patent: April 30, 2019
    Assignees: Regents of the University of Minnesota, The Regents of the University of California
    Inventors: David A. Potter, Zhijun Guo, Elizabeth Amin, Gunda Georg, Tom Poulos, Irina Sevrioukova
  • Publication number: 20180333415
    Abstract: Disclosed are therapeutic methods for treating cancer such as breast cancer.
    Type: Application
    Filed: May 18, 2018
    Publication date: November 22, 2018
    Inventors: David A. Potter, Zhijun Guo
  • Patent number: D874838
    Type: Grant
    Filed: June 30, 2016
    Date of Patent: February 11, 2020
    Assignee: HUMAN TOUCH, LLC
    Inventor: David Potter