Frequency-space wavefield extrapolation using infinite impulse response digital filters: is it feasible?

被引:2
作者
Mousa, Wail A. [1 ]
机构
[1] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
关键词
IIR fx filters; Model reduction theory; Seismic imaging; Wavefield extrapolation; EXPLICIT DEPTH EXTRAPOLATION; LEAST-SQUARES APPROXIMATION; FIR; DESIGN;
D O I
10.1111/j.1365-2478.2012.01058.x
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The purpose of this paper is to study the possibility of performing practically stable and efficient frequency-space (fx) wavefield extrapolation for the application of seismic imaging and datuming via infinite impulse response (IIR) filters. The model reduction control theory was adopted to design such IIR fx extrapolation filters. The model reduction theory reduces the order of a given order system which, in this case, involves reducing a finite impulse response (FIR) fx extrapolation filter system into an IIR fx extrapolation filter system. This theory relies on decomposing the states of the given filter system into strong and weakly coupled sub-systems, and then eliminating the weakly coupled states via singular value decomposition of the Hankel and the impulse response Gramian matrices. Simulation results indicate that IIR fx filters can be obtained, which are stable from an IIR filter design point of view. Simulations also indicate that stable seismic impulse responses and synthetics can be obtained with a reduced system model order and, hence, less computational efforts with respect to the number of complex multiplications and additions per output sample. It is hoped that this study will open new possibilities for researchers to reconsider designing IIR fx explicit depth extrapolation filters due to their expected computational savings and wavenumber response accuracy, when compared to the FIR fx explicit depth extrapolation filters.
引用
收藏
页码:504 / 515
页数:12
相关论文
共 20 条
[1]   Design of linear-phase IIR digital filters using singular perturbational model reduction [J].
Aldhaheri, RW .
IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 2000, 147 (05) :409-414
[2]  
[Anonymous], 1997, NUMERICAL LINEAR ALG
[3]  
[Anonymous], THESIS U LEEDS
[4]  
[Anonymous], SEG 2002
[5]  
[Anonymous], EAGE 2007
[6]   APPROXIMATION OF FIR BY IIR DIGITAL-FILTERS - AN ALGORITHM BASED ON BALANCED MODEL-REDUCTION [J].
BELICZYNSKI, B ;
KALE, I ;
CAIN, GD .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1992, 40 (03) :532-542
[7]   Least-squares approximation of FIR by IIR digital filters [J].
Brandenstein, H ;
Unbehauen, R .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1998, 46 (01) :21-30
[8]   Weighted least-squares approximation of FIR by IIR digital filters [J].
Brandenstein, H ;
Unbehauen, R .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (03) :558-568
[9]   IIR FILTER DESIGN VIA OPTIMAL HANKEL-NORM APPROXIMATION [J].
CHEN, BS ;
PENG, SC ;
CHIOU, BW .
IEE PROCEEDINGS-G CIRCUITS DEVICES AND SYSTEMS, 1992, 139 (05) :586-590
[10]  
Chen C.-T., 1999, LINEAR SYSTEM THEORY