![[pdf]](icons/pdf.png){kind=icon}
|
|
|
|
| Time-frequency analysis of seismic data using local attributes | |
|
Guochang Liu
, Sergey Fomel
, Xiaohong Chen
State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Beijing, China
Bureau of Economic Geology,
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX, USA, 78713-8924
Time-frequency analysis is an important technology in seismic data processing and interpretation. To localize frequency content in time, we have developed a novel method for computing a time-frequency map for nonstationary signals using an iterative inversion framework. We calculated time-varying Fourier coefficients by solving a least-squares problem that uses regularized nonstationary regression. We defined the time-frequency map as the norm of time-varying coefficients. Time-varying average frequency of the seismic data can also be estimated from the time-frequency map calculated by our method. We tested the method on benchmark synthetic signals and compared it with the well-known Stransform. Two field data examples showed applications of the proposed method for delineation of sand channels and for detection of low-frequency anomalies.
|
|
|
|
| Time-frequency analysis of seismic data using local attributes | |
|