Patents by Inventor Stephen KamLing CHIU

Stephen KamLing CHIU 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).

  • Multi-dimensional data reconstruction constrained by a regularly interpolated model
    Patent number: 9158016
    Abstract: A process for overcoming aliasing using a minimum weighted norm interpolation (MWNI) technique may include computing an initial, regularly interpolated model with no data gaps and computing a plurality of initial spectral weights using the initial, regularly interpolated model. The initial, regularly interpolated model is used to compute the spectral weights as initial constraints in a least-squares solution methodology. The initial spectral weights are used as initial constraints in a constrained minimum weighted norm interpolation data reconstruction. The process may further include converting the initial, regularly interpolated model into a frequency domain and computing unknown spectral weights from frequency data at each frequency slice of the initial, regularly interpolated model using Fourier transform. The process results in reducing aliasing artifacts and improving data regularization.
    Type: Grant
    Filed: August 1, 2012
    Date of Patent: October 13, 2015
    Assignee: ConocoPhillips Company
    Inventors: Stephen KamLing Chiu, Phil Dean Anno
  • MULTI-DIMENSIONAL DATA RECONSTRUCTION CONSTRAINED BY A REGULARLY INTERPOLATED MODEL
    Publication number: 20130286041
    Abstract: A process for overcoming aliasing using a minimum weighted norm interpolation (MWNI) technique may include computing an initial, regularly interpolated model with no data gaps and computing a plurality of initial spectral weights using the initial, regularly interpolated model. The initial, regularly interpolated model is used to compute the spectral weights as initial constraints in a least-squares solution methodology. The initial spectral weights are used as initial constraints in a constrained minimum weighted norm interpolation data reconstruction. The process may further include converting the initial, regularly interpolated model into a frequency domain and computing unknown spectral weights from frequency data at each frequency slice of the initial, regularly interpolated model using Fourier transform. The process results in reducing aliasing artifacts and improving data regularization.
    Type: Application
    Filed: August 1, 2012
    Publication date: October 31, 2013
    Applicant: CONOCOPHILLIPS COMPANY
    Inventors: Stephen KamLing CHIU, Phil Dean ANNO