海洋三维地震资料处理中的静校正方法
|
摘要
在海上油气勘探中,三维地震资料的采集通常会持续半年甚至一年。在如此长的时间中,海洋的物理条件,如水温、含盐度等都会发生很大的变化,而这些变化会改变地震波的传播速度。因此,在相同位置不同时间采集的地震资料会有不同的旅行时,从而产生了静校正问题。在三维地震资料处理中,这是一个长期存在而未解决的问题,为此提出了解决方法。该方法包括相邻测线段相对时差自动拾取和全局非线性反演,并在反演中引入先验知识加以约束。另外通过引入混合的l~1和l~2范数使反演对相对大的残差不敏感,以消除自动拾取产生的误差。数值模拟和实际资料处理结果证明了方法的有效性。
In offshore exploration activities,3D seismic data acquisition always lasts for half to one year.During this long period,the off- shore physical conditions have big changes,including water tem- perature and saline concentration,making the propagation velocity of seismic wave change.Therefore,the seismic data acquired at the same position but in different time has different travel time,giving rise to the static correction problem.In 3D seismic data processing, the problem exists for a long time and cannot be solved.So we have developed a novel procedure to solve the problem.The proce- dure consists of automatic pick of the relative static shift between the sail lines and the global nonlinear inversion.Meanwhile,some prior knowledge is inducted in the inversion as constraints.Fur- thermore,the mixed l~1 and l~2 norm is used to make the inversion in- sensitive to large residuals,which can remove the error from auto- matic pick.Numerical simulation and actual date processing results show the method is effective.
In offshore exploration activities,3D seismic data acquisition always lasts for half to one year.During this long period,the off- shore physical conditions have big changes,including water tem- perature and saline concentration,making the propagation velocity of seismic wave change.Therefore,the seismic data acquired at the same position but in different time has different travel time,giving rise to the static correction problem.In 3D seismic data processing, the problem exists for a long time and cannot be solved.So we have developed a novel procedure to solve the problem.The proce- dure consists of automatic pick of the relative static shift between the sail lines and the global nonlinear inversion.Meanwhile,some prior knowledge is inducted in the inversion as constraints.Fur- thermore,the mixed l~1 and l~2 norm is used to make the inversion in- sensitive to large residuals,which can remove the error from auto- matic pick.Numerical simulation and actual date processing results show the method is effective.
引文
1 Barley B.Deep-water problems around the world[J]. The Leading Edge,1999,18(4),488～494
2 Bertrand A,MacBeth C.Seawater velocity variations and real time reservoir monitoring[J].The Leading Edge,2003,22(4),351～355
3 MacKay S,Fried J,Carvill C.The impact of water-ve- locity variations on deepwater seismic data[J].The Leading Edge,2003,22(4),344～350
4 Bube K P,Langan R T.Hybridλ~1/λ~2 minimization with application to tomography[J].Geophysics,1997, 62(4):1183～1195
5 Chapman,Barrodale I.Deconvolution of marine seis- mic data using theλ~1 norm[J].Geophysical Journal of the Royal Astronomical Society,1983,72(1):93～100
6 Claerbout J F,Muir F.Robust modeling with erratic data[J].Geophysics,1973,38(5):826～844
7 Scales J A,Gersztenkorn A,Treitel S,et al.Robust optimization methods in geophysical inverse theory [J].Expanded Abstracts of 58~(th) Annual Internat SEG Mtg,1998,827～830
8 Guitton A,Symes W W.Robust inversion of seismic data using the Huber norm[EB/OL].http://www. geo-online.org/manuscripts/guitton00139.pdf
9 Huber P J.Robust regression:asymptotics,conjec- tures,and Monte Carlo[J].Annals of Statistics,1973, 1(5):799～821
10 Tarantola A.Inverse problem theory and methods for model parameter estimation[M].Elsevier:SIAM, 1987.81～100
11 Wombell R.Water velocity variations and static cor- rections in 3D data processing[J].Expanded Abstracts of EAGE 59~(th)Annual Conference,1997,A029
2 Bertrand A,MacBeth C.Seawater velocity variations and real time reservoir monitoring[J].The Leading Edge,2003,22(4),351～355
3 MacKay S,Fried J,Carvill C.The impact of water-ve- locity variations on deepwater seismic data[J].The Leading Edge,2003,22(4),344～350
4 Bube K P,Langan R T.Hybridλ~1/λ~2 minimization with application to tomography[J].Geophysics,1997, 62(4):1183～1195
5 Chapman,Barrodale I.Deconvolution of marine seis- mic data using theλ~1 norm[J].Geophysical Journal of the Royal Astronomical Society,1983,72(1):93～100
6 Claerbout J F,Muir F.Robust modeling with erratic data[J].Geophysics,1973,38(5):826～844
7 Scales J A,Gersztenkorn A,Treitel S,et al.Robust optimization methods in geophysical inverse theory [J].Expanded Abstracts of 58~(th) Annual Internat SEG Mtg,1998,827～830
8 Guitton A,Symes W W.Robust inversion of seismic data using the Huber norm[EB/OL].http://www. geo-online.org/manuscripts/guitton00139.pdf
9 Huber P J.Robust regression:asymptotics,conjec- tures,and Monte Carlo[J].Annals of Statistics,1973, 1(5):799～821
10 Tarantola A.Inverse problem theory and methods for model parameter estimation[M].Elsevier:SIAM, 1987.81～100
11 Wombell R.Water velocity variations and static cor- rections in 3D data processing[J].Expanded Abstracts of EAGE 59~(th)Annual Conference,1997,A029
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心