Patents by Inventor Lingyun Qiu

Lingyun Qiu 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).

  • Inversion with exponentially encoded seismic data
    Patent number: 11215726
    Abstract: Inversion with exponentially encoded seismic data can include exponentially encoding acquired seismic data and associated synthetic seismic data, storing the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data, determining a one-dimensional (1D) Wasserstein distance between the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data, and generating an adjoint source based on the 1D Wasserstein distance. The example method also includes adapting a dynamic weight implementation of a sensitivity kernel to the adjoint source to build a gradient associated with the acquired seismic data and the associated synthetic seismic data, and iteratively inverting a waveform associated with the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data based on the gradient. An image of a subsurface location can be generated based on results of the iterative inversions.
    Type: Grant
    Filed: March 29, 2018
    Date of Patent: January 4, 2022
    Assignee: PGS GEOPHYSICAL AS
    Inventors: Lingyun Qiu, Jaime Ramos-Martinez, Alejandro A. Valenciano Mavilio
  • Inversion with Exponentially Encoded Seismic Data
    Publication number: 20190257968
    Abstract: Inversion with exponentially encoded seismic data can include exponentially encoding acquired seismic data and associated synthetic seismic data, storing the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data, determining a one-dimensional (1D) Wasserstein distance between the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data, and generating an adjoint source based on the 1D Wasserstein distance. The example method also includes adapting a dynamic weight implementation of a sensitivity kernel to the adjoint source to build a gradient associated with the acquired seismic data and the associated synthetic seismic data, and iteratively inverting a waveform associated with the exponentially encoded acquired seismic data and the exponentially encoded associated synthetic seismic data based on the gradient. An image of a subsurface location can be generated based on results of the iterative inversions.
    Type: Application
    Filed: March 29, 2018
    Publication date: August 22, 2019
    Applicant: PGS Geophysical AS
    Inventors: Lingyun Qiu, Jaime Ramos-Martinez, Alejandro A. Valenciano Mavilio