Patents by Inventor Rayan Kanfar

Rayan Kanfar 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).

  • Determination of mechanical properties of a geological formation using deep learning applied to data acquired while drilling
    Patent number: 11796714
    Abstract: Methods for determination of mechanical properties of geological formations using deep learning include receiving, by a computer system, data acquired during drilling a geological formation. The computer system generates features of the data acquired during drilling. The features are indicative of mechanical properties of the geological formation. The computer system segments the features of the data acquired during drilling into sequences readable by a trained temporal convolutional network (TCN). The computer system determines the mechanical properties of the geological formation using the TCN based on the sequences obtained from the features of the data. A display device of the computer system generates a graphical representation of the mechanical properties of the geological formation.
    Type: Grant
    Filed: December 9, 2021
    Date of Patent: October 24, 2023
    Assignee: Saudi Arabian Oil Company
    Inventors: Robert Smith, Rayan Kanfar, Andrey Bakulin, Nasher Muqbel AlbinHassan, Philippe Nivlet
  • DETERMINATION OF MECHANICAL PROPERTIES OF A GEOLOGICAL FORMATION USING DEEP LEARNING APPLIED TO DATA ACQUIRED WHILE DRILLING
    Publication number: 20220187493
    Abstract: Methods for determination of mechanical properties of geological formations using deep learning include receiving, by a computer system, data acquired during drilling a geological formation. The computer system generates features of the data acquired during drilling. The features are indicative of mechanical properties of the geological formation. The computer system segments the features of the data acquired during drilling into sequences readable by a trained temporal convolutional network (TCN). The computer system determines the mechanical properties of the geological formation using the TCN based on the sequences obtained from the features of the data. A display device of the computer system generates a graphical representation of the mechanical properties of the geological formation.
    Type: Application
    Filed: December 9, 2021
    Publication date: June 16, 2022
    Inventors: Robert Smith, Rayan Kanfar, Andrey Bakulin, Nasher Muqbel AlbinHassan, Philippe Nivlet