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    COMPRESSIVE SENSING
    4.
    发明申请
    COMPRESSIVE SENSING 有权
    压缩感应

    公开(公告)号：US20150124560A1

    公开(公告)日：2015-05-07

    申请号：US14529690

    申请日：2014-10-31

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Chengbo LI ,  Sam T. KAPLAN ,  Charles C. MOSHER ,  Joel D. BREWER ,  Robert G. KEYS

    IPC: G01V1/30

    CPC classification number: G01V1/30 ,  G01V1/003 ,  G01V1/36 ,  G01V2210/169 ,  G01V2210/57 ,  G01V2210/60 ,  G01V2210/614

    Abstract: Computer-implemented method for determining optimal sampling grid during seismic data reconstruction includes: a) constructing an optimization model, via a computing processor, given by minu∥Su∥1 s.t. ∥Ru−b∥2≦σ wherein S is a discrete transform matrix, b is seismic data on an observed grid, u is seismic data on a reconstruction grid, and matrix R is a sampling operator; b) defining mutual coherence as μ ≤ C S  m ( log   n ) 6 , wherein C is a constant, S is a cardinality of Su, m is proportional to number of seismic traces on the observed grid, and n is proportional to number of seismic traces on the reconstruction grid; c) deriving a mutual coherence proxy, wherein the mutual coherence proxy is a proxy for mutual coherence when S is over-complete and wherein the mutual coherence proxy is exactly the mutual coherence when S is a Fourier transform; and d) determining a sample grid r*=arg minr μ(r).

    Abstract translation: 用于在地震数据重建期间确定最佳采样网格的计算机实现的方法包括：a）通过计算处理器构建优化模型，由minu|Su‖1s.t.t给出。 ∥Ru-b‖2＆nlE;＆sgr; 其中S是离散变换矩阵，b是观测网格上的地震数据，u是重建网格上的地震数据，矩阵R是采样算子; b）将相互相干定义为μ≤CCSm（对数n）6，其中C是常数，S是Su的基数，m与观察到的网格上的地震轨迹数成比例，并且n与 重建网格上的地震轨迹数; c）导出相互一致性代理，其中当S超过完成时，相互连贯代理是相互一致性的代理，并且其中当S是傅立叶变换时，相互连贯代理恰好是相互相干; 和d）确定样本网格r * = arg minrμ（r）。

    NON-UNIFORM OPTIMAL SURVEY DESIGN PRINCIPLES
    5.
    发明申请
    NON-UNIFORM OPTIMAL SURVEY DESIGN PRINCIPLES 审中-公开

    公开(公告)号：US20180335536A1

    公开(公告)日：2018-11-22

    申请号：US15641916

    申请日：2017-07-05

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Chengbo LI ,  Charles C. MOSHER ,  Frank D. JANISZEWSKI ,  Laurence S. WILLIAMS

    IPC: G01V1/36 ,  G01V1/38

    Abstract: Method for acquiring seismic data is described. The method includes determining a non-uniform optimal sampling design that includes a compressive sensing sampling grid. Placing a plurality of source lines or receiver lines at a non-uniform optimal line interval. Placing a plurality of receivers or nodes at a non-uniform optimal receiver interval. Towing a plurality of streamers attached to a vessel, wherein the plurality of streamers is spaced apart at non-uniform optimal intervals based on the compressive sensing sampling grid. Firing a plurality of shots from one or more seismic sources at non-uniform optimal shot intervals. Acquiring seismic data via the plurality of receivers or nodes.

    SEISMIC DENOISING
    6.
    发明申请
    SEISMIC DENOISING 有权

    公开(公告)号：US20220236436A1

    公开(公告)日：2022-07-28

    申请号：US17587765

    申请日：2022-01-28

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Chengbo LI ,  Yu ZHANG

    IPC: G01V1/36

    Abstract: Leveraging migration and demigration, here we propose a learning-based approach for fast denoising with applications to fast-track processing. The method is designed to directly work on raw data without separating each noise type and character. The automatic attenuation of noise is attained by performing migration/demigration guided sparse inversion. By discussing examples from a Permian Basin dataset with very challenging noise issues, we attest the feasibility of this learning-based approach as a fast turnaround alternative to conventional denoising methodology.

    NON-UNIFORM OPTIMAL SURVEY DESIGN PRINCIPLES
    8.
    发明申请
    NON-UNIFORM OPTIMAL SURVEY DESIGN PRINCIPLES 有权

    公开(公告)号：US20210033741A1

    公开(公告)日：2021-02-04

    申请号：US17073907

    申请日：2020-10-19

    Applicant: ConocoPhillips Company

    Inventor： Chengbo LI ,  Charles C. MOSHER ,  Frank D. JANISZEWSKI ,  Laurence S. WILLIAMS

    IPC: G01V1/36 ,  G01V1/38

    Abstract: Method for acquiring seismic data is described. The method includes determining a non-uniform optimal sampling design that includes a compressive sensing sampling grid. Placing a plurality of source lines or receiver lines at a non-uniform optimal line interval. Placing a plurality of receivers or nodes at a non-uniform optimal receiver interval. Towing a plurality of streamers attached to a vessel, wherein the plurality of streamers is spaced apart at non-uniform optimal intervals based on the compressive sensing sampling grid. Firing a plurality of shots from one or more seismic sources at non-uniform optimal shot intervals. Acquiring seismic data via the plurality of receivers or nodes.

    METHODS FOR SIMULTANEOUS SOURCE SEPARATION
    9.
    发明申请
    METHODS FOR SIMULTANEOUS SOURCE SEPARATION 审中-公开

    公开(公告)号：US20200225377A1

    公开(公告)日：2020-07-16

    申请号：US16833975

    申请日：2020-03-30

    Applicant: ConocoPhillips Company

    Inventor： Chengbo LI ,  Chuck MOSHER ,  Leo JI ,  Joel BREWER

    IPC: G01V1/36 ,  G01V1/28

    Abstract: A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

    METHODS FOR SIMULTANEOUS SOURCE SEPARATION
    10.
    发明申请
    METHODS FOR SIMULTANEOUS SOURCE SEPARATION 审中-公开

    公开(公告)号：US20170082761A1

    公开(公告)日：2017-03-23

    申请号：US14974060

    申请日：2015-12-18

    Applicant: CONOCOPHILLIPS COMPANY

    Inventor： Chengbo LI ,  Chuck MOSHER ,  Leo JI ,  Joel BREWER

    IPC: G01V1/36 ,  G01V1/28

    CPC classification number: G01V1/368 ,  G01V1/282 ,  G01V1/364 ,  G01V2210/127 ,  G01V2210/57

    Abstract: A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

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