High-frequency compensation in seismic data based on system identification of ARX model
HU Rui-Qing1,2, XIA Zhen-Hua1,3, GUI Zhi-Xian1,2, SUN Pu2,4
1. Key Laboratory of Exploration Technologies for Oil and Gas Resources;Ministry of Education, Yangtze University, Wuhan 430100, China; 2. School of Geophysics and Oil Resources, Yangtze University, Wuhan 430100, China; 3. School of Electronics and Information, Yangtze University, Jinzhou 434023, China; 4. Jiangsu Coal Geophysical Prospecting and Surveying Party, Nanjing 210000, China
Abstract：Absorptive attenuation has always been one of the reasons for the limited resolution of the seismic data.The mechanism of the absorption in strata,the evaluation of the attenuation quantity and the compensation of the high frequency components are essential in the seismic resolution improvement.Based on ARX model,the authors simulated the reversion of the absorption process in strata by establishing a numerical model with system identification technology.The low frequency data (the surface seismic data) and the high frequency data (the well log data or the cross-well seismic data) are respectively set as the input and the output of the model,and then the structure parameters of the model can be obtained.The model in this paper can establish an interconnection between the conventional seismic data and the well log data,the cross-well data or the VSP data.It is shown by processing the practical data that the main frequency can be increased by 10~15 Hz,and the frequency band width can be expanded by 8~10 Hz.
胡瑞卿, 夏振华, 桂志先, 孙璞. 基于ARX模型的地震资料提频方法[J]. 物探与化探, 2014, 38(6): 1270-1274.
HU Rui-Qing, XIA Zhen-Hua, GUI Zhi-Xian, SUN Pu. High-frequency compensation in seismic data based on system identification of ARX model. Geophysical and Geochemical Exploration, 2014, 38(6): 1270-1274.
[1] Chopra S,Alexeev V,Sudhakar V.High-frequency restoration of surface seismic data[J].The Leading Edge,2003,22(8):730-738. [2] 曾锐,刘洪.柯西约束盲反褶积技术在井间地震的应用[J].地球物理学进展,2004,19 (1):166-172. [3] 轩仁飞,曹俊兴.地震分倒频处理技术[J].地球物理学进展,2012,27(3):1183-1188. [4] 刘浩杰,王延光,韩文功.基于系统辨识提高地震资料分辨率研究[J].地球物理学进展,2010,25(3):1-5. [5] 李庆忠,王建花.井间地震勘探的误区及出路[J].石油地球物理勘探,2004,39(1):1-11. [6] Bouzrara K,Garna T,Ragot J,et al.Online identification of the ARX model expansion on Laguerre orthonormal based with filters on model input and output[J].International Journal of Control,2013,86(3):369-385. [7] 刘文岭,夏海英.同位协同克里金方法在储层横向预测中的应用[J].勘探地球物理进展,2004,27(5):367-370. [8] Gunnarsson S.Frequency domain accuracy of recursively identified ARX models[J].International Journal of Control,1991,54(2):465-480. [9] 周彤.面向控制的系统辨识导论[M].北京:清华大学出版社,2009. [10] Millnert M.Identification of ARX models with markovian parameters[J].International Journal of Control,1987,45(6):2045-2058. [11] Byehan S,Alci M.Fuzzy functions based ARX model and new fuzzy basis function models for nonlinear system identification[J]. Applied Soft Computing Journal,2009,10(2):439-444. [12] 靳国栋, 刘衍聪,牛文杰.距离加权反比插值法和克里金插值法的比较[J].长春工业大学学报:自然科学版,2003,31(3):46-48. [13] Nounou M N,Nounou H N.Improving the prediction and parsimony of ARX models using multiscale estimation[J].Applied Soft Computing Journal,2006,7(3):711-721. [14] Nicolao G D,Magni L,Scattolini R.Stabilizing predictive control of nonlinear ARX models[J].Automatica,1997,33(9):1691-1697. [15] Golob M,Tovornik B.Input-output modeling with decomposed neuro-fuzzy ARX model[J].Neurocomputing, 2007,71(4):875-884.
