基于分段快速模拟退火的零偏VSP全波形反演
|
摘要
基于常规模拟退火算法的零偏VSP全波形反演面临着计算量大和耗时长的问题。为此提出了一种不同阶段对应不同扰动模型和退火方式的分段快速模拟退火(segmented fast simulated annealing,SFSA)反演策略,以提高零偏VSP资料全波形反演的效率。在反演前期采用大模型扰动空间和较慢温度衰减速度,充分发挥全局搜索能力,而在后期引入限制因子产生扰动模型,在迭代不断增加的时候逐渐减小模型的扰动空间,同时采用较快的温度衰减速度,有效提高反演的速度,使反演快速收敛到最优解。基于相同的初始温度和马尔可夫链长度,分别利用基于SFSA和非常快速模拟退火(very fast simulated annealing,VFSA)方法进行零偏VSP纵波速度全波形反演测试。结果表明,基于SFSA的反演方法的反演效率提高约50%,在迭代次数更少的条件下能获得更好的反演效果。基于SFSA的零偏VSP全波形反演具有高效和高精度的特点,其反演结果为地震地质层位标定、成果解释及油气预测奠定了基础。
The application of the full-waveform inversion technique based on the conventional simulated annealing algorithm to zero-offset VSP data is time consuming and complex.This paper therefore proposes an efficient segmented fast simulated annealing(SFSA)strategy,which uses different disturbance models and annealing methods at different stages to improve the waveform inversion efficiency of zero-offset V S P data.In the early stage of inversion,large model perturbation space and slow decay rate of temperature were adopted to fully perform global search;in late stage,the perturbation model with restriction factor was adopted;the model perturbation space was gradually reduced as the iteration increased,with a faster decay rate of temperature,to improve the efficiency of the inversion and help the algorithm converge to the optimal solution quickly.Finally,SFSA and conventional very fast simulated annealing(VFSA)algorithms were compared for P-wave velocity inversion of zero-offset VSP.The test results showed that the SFSA algorithm can improve the inversion efficiency by50%,while a better inversion effect could be obtained using less iteration.The proposed method could lay the foundation for the calibration of seismic geological horizons,seismic interpretation,and reservoir prediction.
The application of the full-waveform inversion technique based on the conventional simulated annealing algorithm to zero-offset VSP data is time consuming and complex.This paper therefore proposes an efficient segmented fast simulated annealing(SFSA)strategy,which uses different disturbance models and annealing methods at different stages to improve the waveform inversion efficiency of zero-offset V S P data.In the early stage of inversion,large model perturbation space and slow decay rate of temperature were adopted to fully perform global search;in late stage,the perturbation model with restriction factor was adopted;the model perturbation space was gradually reduced as the iteration increased,with a faster decay rate of temperature,to improve the efficiency of the inversion and help the algorithm converge to the optimal solution quickly.Finally,SFSA and conventional very fast simulated annealing(VFSA)algorithms were compared for P-wave velocity inversion of zero-offset VSP.The test results showed that the SFSA algorithm can improve the inversion efficiency by50%,while a better inversion effect could be obtained using less iteration.The proposed method could lay the foundation for the calibration of seismic geological horizons,seismic interpretation,and reservoir prediction.
引文
[1] CAO D P,YIN X Y,ZHANG F C.Joint inversion of 3D seismic,VSP and crosswell seismic data[J].Expanded Abstracts of 79th Annual Internat SEG Mtg,2009:2373-2377
[2]曹丹平.多尺度地震资料正反演方法研究[D].东营:中国石油大学(华东),2008CAO D P.Method research of multiscale seismic data modeling and inversion[D].Dongying:China University of Petroleum,2008
[3] STEWART R R.Vertical-seismic-profile(VSP)interval velocities from traveltime inversion[J].Geophysical Prospecting,1984,32(4):608-628
[4] LINES L,BOURGEOIS A,COVEY J.Traveltime inversion of vertical seismic profiles—a feasibility study[J].Geophysics,1984,49(3):250-264
[5]邹强,周熙襄,钟本善.旅行时与波阻抗联合反演求取层速度[J].石油地球物理勘探,2003,38(4):396-399ZOU Q,ZHOU X X,ZHONG B S.Acquiring interval velocity by joint inversion of travel-time and wave impedance[J].Oil Geophysical Prospecting,2003,38(4):396-399
[6]姚忠瑞,何惺华.利用零偏VSP资料求取横波速度—以七北101井VSP测井为例[J].勘探地球物理进展,2007,30(2):100-103YAO Z R,HE X H.Calculation of S-wave velocity from zero-offset VSP data:Taking the VSP data of well 101in Qibei survey area an example[J].Progress in Exploration Geophysics,2007,30(2):100-103
[7]张继国,牟风明.VSP横波速度反演实用性研究[J].石油地球物理勘探,2006,41(6):697-701ZHANG J G,MU F M.Study of practicality of VSP Swave velocity inversion[J].Oil Geophysical Prospecting,2006,41(6):697-701
[8]卞爱飞,於文辉,周华伟.频率域全波形反演方法研究进展[J].地球物理学进展,2010,25(3):982-993BIAN A F,YU W H,ZHOU W H.Progress in the frequency-domain full waveform inversion method[J].Progress in Geophysics,2010,25(3):982-993
[9]单蕊,卞爱飞,於文辉,等.利用叠前全波形反演进行储层预测[J].石油地球物理勘探,2011,46(4):629-633,667SHAN R,BIAN A F,YU W H,et al.Pre-stack full waveform inversion for reservoir prediction[J].Oil Geophysical Prospecting,2011,46(4):629-633,667
[10] OWUSU J C,PODGORNOVA O,CHARARA M,et al.Anisotropic elastic full-waveform inversion of walkaway vertical seismic profiling data from the Arabian Gulf[J].Geophysical Prospecting,2016,64(1):38-53
[11] EGOROV A,PEVZNER R,BóNA A,et al.Time-lapse full waveform inversion of vertical seismic profile data:workflow and application to the CO2CRC Otway project[J].Geophysical Research Letters,2017,44(14):7211-7218
[12]张繁昌,肖张波,印兴耀.地震数据约束下的贝叶斯随机反演[J].石油地球物理勘探,2014,49(1):176-182ZHANG F C,XIAO Z B,YIN X Y.Bayesian stochastic inversion constrained by seismic data[J].Oil Geophysical Prospecting,2014,49(1):176-182
[13]刘汉卿,张繁昌,代荣获.基于神经网络的井间地震数据外推及多尺度反演[J].物探化探计算技术,2015,37(3):348-354LIU H Q,ZHANG F C,DAI R H.Extrapolating of the cross-well seismic data based on the neural network and multi-scale seismic joint inversion[J].Computing Techniques for Geophysical and Geochemical Exploration,2015,37(3):348-354
[14]杨勤勇,胡光辉,王立歆.全波形反演研究现状及发展趋势[J].石油物探,2014,53(1):77-83YANG Q Y,HU G H,WANG L X.Research status and development trend of full waveform inversion[J].Geophysical Prospecting for Petroleum,2014,53(1):77-83
[15]张广智,姜岚杰,孙昌路,等.基于照明预处理的分步多参数时间域声波全波形反演方法研究[J].石油物探,2017,56(1):31-37,74ZHANG G Z,JIANG L J,SUN C L,et al.The stepped multi-parameter FWI of acoustic media in time-domain by L-BFGS method with illumination analysis[J].Geophysical Prospecting for Petroleum,2017,56(1):31-37,74
[16] METROPOLIS N,ROSENBLUTH A W,ROSENBLUTH M N,et al.Equation of state calculations by fast computing machines[J].The Journal of Chemical Physics,1953,21(6):1086-1092
[17] INGBER L.Very fast simulated re-annealing[J].Mathematical Computer Modeling,1989,12(8):967-973
[18]刘海飞,阮百尧,张赛民,等.基于模拟退火的全局混合反演方法及其应用[J].桂林工学院报,2008,28(3):312-318LIU H F,RUAN B Y,ZHANG S M,et al.Global hybrid inversion method and application based on simulated annealing[J].Journal of Guilin University of Technology,2008,28(3):312-318
[19]李亚楠,郭海湘,黎金玲,等.一种基于模拟退火的参数自适应差分演化算法及其应用[J].系统管理学报,2016,25(4):652-662LI Y N,GUO H X,LI J L,et al.A differential evolution algorithm with self-adaptive parameters based on simulated annealing and its applications[J].Journal of Systems&Management,2016,25(4):652-662
[20]陈可洋.标量声波波动方程高阶交错网格有限差分法[J].中国海上油气,2009,21(4):232-236CHEN K Y.High-order staggered-grid finite difference scheme for scalar acoustic wave equation[J].China Offshore Oil and Gas,2009,21(4):232-236
[21]陈华根,吴健生,王家林,等.模拟退火算法机理研究[J].同济大学学报(自然科学版),2004,32(6):802-805CHEN H G,WU J S,WANG J L,et al.Mechanism study of simulated annealing algorithm[J].Journal of Tongji University(Natural Science),2004,32(6):802-805
[22]李宁.基于模拟退火的地质统计学反演方法研究[D].东营:中国石油大学(华东),2013LI N.The Study of geostatistics inversion based on simulated annealing method[D].Dongying:China University of Petroleum,2013
[23]蒋龙聪,刘江平.模拟退火算法及其改进[J].工程地球物理学报,2007,4(2):135-140JIANG L C,LIU J P.Revised simulated annealing algorithm[J].Chinese Journal of Engineering Geophysics,2007,4(2):135-140
[2]曹丹平.多尺度地震资料正反演方法研究[D].东营:中国石油大学(华东),2008CAO D P.Method research of multiscale seismic data modeling and inversion[D].Dongying:China University of Petroleum,2008
[3] STEWART R R.Vertical-seismic-profile(VSP)interval velocities from traveltime inversion[J].Geophysical Prospecting,1984,32(4):608-628
[4] LINES L,BOURGEOIS A,COVEY J.Traveltime inversion of vertical seismic profiles—a feasibility study[J].Geophysics,1984,49(3):250-264
[5]邹强,周熙襄,钟本善.旅行时与波阻抗联合反演求取层速度[J].石油地球物理勘探,2003,38(4):396-399ZOU Q,ZHOU X X,ZHONG B S.Acquiring interval velocity by joint inversion of travel-time and wave impedance[J].Oil Geophysical Prospecting,2003,38(4):396-399
[6]姚忠瑞,何惺华.利用零偏VSP资料求取横波速度—以七北101井VSP测井为例[J].勘探地球物理进展,2007,30(2):100-103YAO Z R,HE X H.Calculation of S-wave velocity from zero-offset VSP data:Taking the VSP data of well 101in Qibei survey area an example[J].Progress in Exploration Geophysics,2007,30(2):100-103
[7]张继国,牟风明.VSP横波速度反演实用性研究[J].石油地球物理勘探,2006,41(6):697-701ZHANG J G,MU F M.Study of practicality of VSP Swave velocity inversion[J].Oil Geophysical Prospecting,2006,41(6):697-701
[8]卞爱飞,於文辉,周华伟.频率域全波形反演方法研究进展[J].地球物理学进展,2010,25(3):982-993BIAN A F,YU W H,ZHOU W H.Progress in the frequency-domain full waveform inversion method[J].Progress in Geophysics,2010,25(3):982-993
[9]单蕊,卞爱飞,於文辉,等.利用叠前全波形反演进行储层预测[J].石油地球物理勘探,2011,46(4):629-633,667SHAN R,BIAN A F,YU W H,et al.Pre-stack full waveform inversion for reservoir prediction[J].Oil Geophysical Prospecting,2011,46(4):629-633,667
[10] OWUSU J C,PODGORNOVA O,CHARARA M,et al.Anisotropic elastic full-waveform inversion of walkaway vertical seismic profiling data from the Arabian Gulf[J].Geophysical Prospecting,2016,64(1):38-53
[11] EGOROV A,PEVZNER R,BóNA A,et al.Time-lapse full waveform inversion of vertical seismic profile data:workflow and application to the CO2CRC Otway project[J].Geophysical Research Letters,2017,44(14):7211-7218
[12]张繁昌,肖张波,印兴耀.地震数据约束下的贝叶斯随机反演[J].石油地球物理勘探,2014,49(1):176-182ZHANG F C,XIAO Z B,YIN X Y.Bayesian stochastic inversion constrained by seismic data[J].Oil Geophysical Prospecting,2014,49(1):176-182
[13]刘汉卿,张繁昌,代荣获.基于神经网络的井间地震数据外推及多尺度反演[J].物探化探计算技术,2015,37(3):348-354LIU H Q,ZHANG F C,DAI R H.Extrapolating of the cross-well seismic data based on the neural network and multi-scale seismic joint inversion[J].Computing Techniques for Geophysical and Geochemical Exploration,2015,37(3):348-354
[14]杨勤勇,胡光辉,王立歆.全波形反演研究现状及发展趋势[J].石油物探,2014,53(1):77-83YANG Q Y,HU G H,WANG L X.Research status and development trend of full waveform inversion[J].Geophysical Prospecting for Petroleum,2014,53(1):77-83
[15]张广智,姜岚杰,孙昌路,等.基于照明预处理的分步多参数时间域声波全波形反演方法研究[J].石油物探,2017,56(1):31-37,74ZHANG G Z,JIANG L J,SUN C L,et al.The stepped multi-parameter FWI of acoustic media in time-domain by L-BFGS method with illumination analysis[J].Geophysical Prospecting for Petroleum,2017,56(1):31-37,74
[16] METROPOLIS N,ROSENBLUTH A W,ROSENBLUTH M N,et al.Equation of state calculations by fast computing machines[J].The Journal of Chemical Physics,1953,21(6):1086-1092
[17] INGBER L.Very fast simulated re-annealing[J].Mathematical Computer Modeling,1989,12(8):967-973
[18]刘海飞,阮百尧,张赛民,等.基于模拟退火的全局混合反演方法及其应用[J].桂林工学院报,2008,28(3):312-318LIU H F,RUAN B Y,ZHANG S M,et al.Global hybrid inversion method and application based on simulated annealing[J].Journal of Guilin University of Technology,2008,28(3):312-318
[19]李亚楠,郭海湘,黎金玲,等.一种基于模拟退火的参数自适应差分演化算法及其应用[J].系统管理学报,2016,25(4):652-662LI Y N,GUO H X,LI J L,et al.A differential evolution algorithm with self-adaptive parameters based on simulated annealing and its applications[J].Journal of Systems&Management,2016,25(4):652-662
[20]陈可洋.标量声波波动方程高阶交错网格有限差分法[J].中国海上油气,2009,21(4):232-236CHEN K Y.High-order staggered-grid finite difference scheme for scalar acoustic wave equation[J].China Offshore Oil and Gas,2009,21(4):232-236
[21]陈华根,吴健生,王家林,等.模拟退火算法机理研究[J].同济大学学报(自然科学版),2004,32(6):802-805CHEN H G,WU J S,WANG J L,et al.Mechanism study of simulated annealing algorithm[J].Journal of Tongji University(Natural Science),2004,32(6):802-805
[22]李宁.基于模拟退火的地质统计学反演方法研究[D].东营:中国石油大学(华东),2013LI N.The Study of geostatistics inversion based on simulated annealing method[D].Dongying:China University of Petroleum,2013
[23]蒋龙聪,刘江平.模拟退火算法及其改进[J].工程地球物理学报,2007,4(2):135-140JIANG L C,LIU J P.Revised simulated annealing algorithm[J].Chinese Journal of Engineering Geophysics,2007,4(2):135-140