Patents by Inventor Nicolas CHAZALNOEL

Nicolas CHAZALNOEL 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).

  • Reflection full waveform inversion methods with density and velocity models updated separately
    Patent number: 11487036
    Abstract: A reflection full waveform inversion method updates separately a density model and a velocity model of a surveyed subsurface formation. The method includes generating a model-based dataset corresponding to the seismic dataset using a velocity model and a density model to calculate an objective function measuring the difference between the seismic dataset and the model-based dataset. A high-wavenumber component of the objective function's gradient is used to update the density model of the surveyed subsurface formation. The model-based dataset is then regenerated using the velocity model and the updated density model, to calculate an updated objective function. The velocity model of the surveyed subsurface formation is then updated using a low-wavenumber component of the updated objective function's gradient. A structural image of the subsurface formation is generated using the updated velocity model.
    Type: Grant
    Filed: January 9, 2018
    Date of Patent: November 1, 2022
    Assignee: CGG SERVICES SAS
    Inventors: Adriano Gomes, Nicolas Chazalnoel
  • REFLECTION FULL WAVEFORM INVERSION METHODS WITH DENSITY AND VELOCITY MODELS UPDATED SEPARATELY
    Publication number: 20180196154
    Abstract: A reflection full waveform inversion method updates separately a density model and a velocity model of a surveyed subsurface formation. The method includes generating a model-based dataset corresponding to the seismic dataset using a velocity model and a density model to calculate an objective function measuring the difference between the seismic dataset and the model-based dataset. A high-wavenumber component of the objective function's gradient is used to update the density model of the surveyed subsurface formation. The model-based dataset is then regenerated using the velocity model and the updated density model, to calculate an updated objective function. The velocity model of the surveyed subsurface formation is then updated using a low-wavenumber component of the updated objective function's gradient. A structural image of the subsurface formation is generated using the updated velocity model.
    Type: Application
    Filed: January 9, 2018
    Publication date: July 12, 2018
    Inventors: Adriano GOMES, Nicolas CHAZALNOEL