加权MPFI方法及其在三维连片处理中的应用
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摘要
在对采集参数差异较大的多块三维区块开展连片处理时,传统的基于MPFI,ALFT,Low-Rank及MWNI等理论的规则化方法要么无法有效克服空间假频,要么无法满足其线性假设条件,不能真正实现保真规则化处理。针对这一问题,在传统MPFI算法的基础上,将不含假频的低频信息谱作为先验信息进行加权,实现了加权MPFI数据插值,并建立了规则化方法。实际测试结果表明,该方法与传统MPFI方法相比,一方面可以有效克服空间假频,实现多块三维区块的连片规则化处理;另一方面,该方法并未增加额外的地质信息,只是在一定程度上改变了观测系统的空间采样属性,具有比传统规则化方法更高的保真性。通过数据正演模型试算及野外地震数据实算,验证了该方法的准确性、有效性和对野外地震资料的适应性。
Conventional regularization methods based on the theories of MPFI,ALFT,Low-Rank and MWNI either cannot effectively overcome spatial aliasing,or cannot satisfy the linear assumption,therefore,they are not effective to achieve fidelity regularization in three-dimensional multi-block joint processing with different acquisition parameters. On the basis of conventional MPFI algorithm,the low-frequency spectrum without false frequency was weighted as prior information,the weighted MPFI data interpolation was realized,and the regularization method was established. The results show that compared with the conventional MPFI method,this method can effectively overcome the spatial aliasing and realize three-dimensional multi-block regularization joint processing. Moreover,it does not add additional geological information,but improves the spatial sampling properties of the observation system to some extent,and has a higher fidelity than the conventional regularizationmethod. The accuracy,validity and adaptability to field seismic data of this method were verified by trial calculation of forward model and field seismic data.
Conventional regularization methods based on the theories of MPFI,ALFT,Low-Rank and MWNI either cannot effectively overcome spatial aliasing,or cannot satisfy the linear assumption,therefore,they are not effective to achieve fidelity regularization in three-dimensional multi-block joint processing with different acquisition parameters. On the basis of conventional MPFI algorithm,the low-frequency spectrum without false frequency was weighted as prior information,the weighted MPFI data interpolation was realized,and the regularization method was established. The results show that compared with the conventional MPFI method,this method can effectively overcome the spatial aliasing and realize three-dimensional multi-block regularization joint processing. Moreover,it does not add additional geological information,but improves the spatial sampling properties of the observation system to some extent,and has a higher fidelity than the conventional regularizationmethod. The accuracy,validity and adaptability to field seismic data of this method were verified by trial calculation of forward model and field seismic data.
引文
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[22]刘俊田,张代生,黄卫东,等.三塘湖盆地马朗凹陷火山岩岩性测井识别技术及应用.岩性油气藏,2009,21(4):87-91.LIU J T,ZHANG D S,HUANG W D,et al.Volcanic rock lithology recognition technique and its application in Malang Depression,Santanghu Basin.Lithologic Reservoirs,2009,21(4):87-91.
[23]杨占龙,肖冬生,周隶华,等.高分辨率层序格架下的陆相湖盆精细沉积体系研究:以吐哈盆地西缘侏罗系-古近系为例.岩性油气藏,2017,29(5):1-10.YANG Z L,XIAO D S,ZHOU L H,et al.Depositional system of lacustrine basins within high-resolution sequence framework:a case of Jurassic to Paleogene in western Turpan-Kumul Basin.Lithologic Reservoirs,2017,29(5):1-10.
[2]杜金虎,熊金良,王喜双,等.世界物探技术现状及中国石油物探技术发展的思考.岩性油气藏,2011,23(4):1-8.DU J H,XIONG J L,WANG X S,et al.Status quo of international geophysical exploration technologies and thinking about the development of PetroChina geophysical exploration Technologies.Lithologic Reservoirs,2011,23(4):1-8.
[3]王靖,孙赞东,吴杰,等.地震资料处理方法的叠前保幅性研究.岩性油气藏,2016,28(3):105-112.WANG J,SUN Z D,WU J,et al.Pre-stack amplitude-preserved ability about several seismic data processing methods.Lithologic Reservoirs,2016,28(3):105-112.
[4]石颖,张振,王建民,等.地震数据反假频规则化方法研究.地球物理学进展,2013,28(1):250-256.SHI Y,ZHANG Z,WANG J M,et al.Investigation on anti-aliasing regularization approach for seismic data.Progress in Geophysics,2013,28(1):250-256.
[5]GUO J,ZHENG Y,LIAO W Y.High fidelity seismic trace interpolation.SEG Technical Program Expanded Abstracts,2015:3915-3919.
[6]POOLE G,HERMAN P.Multi-dimensional data regularization for modern acquisition geometries.Expanded abstracts of 69th EAGE annual conference,2007:70-75.
[7]XU S,ZHANG Y,LAMBARE G.Anti-leakage Fourier transform for seismic data regularization in higher dimensions.Geophysics,2010,70(4):87-95.
[8]SCHONEWILLE M,KLAEDTKE A,VIGNER A.seismic data regularization with the anti-alias anti-leakage Fourier transform.First Break,2009,27(9):85-92.
[9]LIU B,SACCHI M D.Minimum weighted norm interpolation of seismic records.Geophysics,2004,69(6):1560-1568.
[10]NG M,WANG X S,NEGUT D.6D interpolation by incorporating angular weight constraints into 5D MWNI.SEG Technical Program Expanded Abstracts,2015:3809-3813.
[11]ZHANG W,CHEN H L,ZHAO B,et al.5D seismic data interpolation using low-rank radial function interpolation.SEG Technical Program Expanded Abstracts,2016:4118-4122.
[12]LI W C,ZHAO Y.An imaging perspective of low-rank seismic data interpolation and denoising.SEG Technical Program Expanded Abstracts,2015:4106-4110.
[13]SHAO J,WANG Y B,XUE Q F,et al.Radon-domain interferometric interpolation of sparse seismic data.SEG Technical Program Expanded Abstracts,2017:4343-4347.
[14]NIMSAILA K,WANG P.Fast progressives parse Tau-p transform for regularization of spatially aliased seismic data.Expanded Abstracts of 76th EAGE Annul conference,2014:230-234.
[15]杨敬磊,余建鹏,于建华,等.基于压缩感知的数据规则化方法在三维数据重建中的应用.北京:SPG/SEG北京2016国际地球物理会议,2016.YANG J L,YU J P,YU J H,et al.Application of data regularization techniques based on compressive sensing in 3D seismic data reconstruction.Beijing:SPG/SEG 2016 International Geophysical Conference,2016.
[16]宋维琪,张宇.基于压缩感知理论的微地震资料噪声压制.地球物理学展,2017,32(4):1636-1642.SONG W Q,ZHANG Y.Noise suppression of the micro-seismic data based on the compressive sampling theory.Progress in Geophysics(in Chinese),2017,32(4):1636-1642.
[17]WANG B F.Comparison of the POCS and IHT methods for seismic data interpolation and denoising.SEG Technical Program Expanded Abstracts,2016:4845-4849.
[18]MALLAT S G,ZHANG Z F.Matching pursuits with time-frequency dictionaries.IEEE Transactions on Signal Processing,1993,41(12):3394-3415.
[19]段文胜,王鹏,党青宁.应用匹配追踪傅里叶插值技术实现OVT域连片处理.石油地球物理勘探,2017,52(4):669-677.DUAN W S,WANG P,DANG Q N.5D data regularization based on matching pursuit Fourier Interpolation for the OVTdomain data merging processing.Oil Geophysical prospecting.2017,52(4):669-677.
[20]NGUYEN T,WINNETT R.Seismic interpolation by optimally matched Fourier components.SEG Technical Program Expanded Abstracts,2011,30:3085-3089.
[21]TANG J,YAN Z M,DUHOON N,et al.5D matching pursuit Fourier interpolation and its application in surface-related multiple elimination for large offset coil data.SEG Technical Program Expanded Abstracts,2017:4758-4762.
[22]刘俊田,张代生,黄卫东,等.三塘湖盆地马朗凹陷火山岩岩性测井识别技术及应用.岩性油气藏,2009,21(4):87-91.LIU J T,ZHANG D S,HUANG W D,et al.Volcanic rock lithology recognition technique and its application in Malang Depression,Santanghu Basin.Lithologic Reservoirs,2009,21(4):87-91.
[23]杨占龙,肖冬生,周隶华,等.高分辨率层序格架下的陆相湖盆精细沉积体系研究:以吐哈盆地西缘侏罗系-古近系为例.岩性油气藏,2017,29(5):1-10.YANG Z L,XIAO D S,ZHOU L H,et al.Depositional system of lacustrine basins within high-resolution sequence framework:a case of Jurassic to Paleogene in western Turpan-Kumul Basin.Lithologic Reservoirs,2017,29(5):1-10.