Nonlinear structure-enhancing filtering using plane-wave prediction |
Yang Liu, Sergey Fomel, Guochang Liu
College of Geo-Exploration Science and Technology,
Jilin University
No.6 Xi minzhu street,
Changchun, China, 130026
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
State Key Laboratory of Petroleum Resource and Prospecting,
China University of Petroleum-Beijing
18 Fuxue road, Changping,
Beijing, China, 102249
Attenuation of random noise and enhancement of structural continuity can significantly improve the quality of seismic interpretation. We present a new technique, which aims at reducing random noise while protecting structural information. The technique is based on combining structure prediction with either similarity-mean filtering or lower-upper-middle (LUM) filtering. We use structure prediction to form a structural prediction of seismic traces from neighboring traces. We apply a nonlinear similarity-mean filter or an LUM filter to select best samples from different predictions. In comparison with other common filters, such as mean or median, the additional parameters of the nonlinear filters allow us to better control the balance between eliminating random noise and protecting structural information. Numerical tests using synthetic and field data show the effectiveness of the proposed structure-enhancing filters.
Nonlinear structure-enhancing filtering using plane-wave prediction |