多尺度联合反演及其应用
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摘要
随着油气勘探开发形势的发展,油气勘探正逐渐由构造油气藏转向岩性油气藏。而作为最有效的一种油气勘探地球物理方法,地震技术的应用也越来越广泛,已经从构造解释逐渐深入到储层评价、岩性解释和油藏描述等方面。地震反演技术能够从地震资料中提取出丰富的岩性、物性以及流体信息,为油藏描述提供各种有效的信息。然而,随着勘探开发难度的加大,常规的地震波阻抗反演已经无法满足油气勘探开发的需求。为了实现高精度的勘探,在波阻抗反演中联合利用了地面地震数据、井间地震数据和VSP地震数据,充分利用地面地震数据在横向上的高分辨率、井间地震数据的宽频带信息和VSP数据精确的时深关系,来提高反演的精度,以更好的为油气勘探开发服务。
常规的波阻抗反演方法只利用了地面地震数据,而地面地震数据虽然具有较高的横向分辨率,在垂向上的分辨能力却比较低,这样导致得到的反演结果往往精度不够高。地面地震数据、井间地震数据和VSP数据虽然具有采集方式不同、波场信息丰富程度不同、分辨率尺度不同,但是它们却是地下相同的地质体的地震波响应。利用贝叶斯理论可以将这三者联系起来,建立起这三种资料的联合概率密度函数。
论文中首先讨论了贝叶斯反演理论,研究了基于贝叶斯理论的多尺度地震资料联合反演方法。然后研究了不同的先验分布函数对于反演结果的影响,采用了符合实际井数据统计特征的柯西分布;同时研究了不同的参数对于反演结果的影响,为反演方程中参数的选取指明了方向。在求解反演方程时,通过对目标函数的分析,采用了改进的PRP共轭梯度法,加快了方程收敛的速率,确保了反演的稳定性。研究了序贯高斯模拟建模方法,避免了确定性建模方法的平滑效应,同时能够对模拟结果进行优选和不确定性评价。最后针对实际的地震资料量纲差别大的情况,对实际地震资料进行了预处理,方便了反演参数的选取。
对多尺度地震资料联合反演方法进行模型测试,通过与常规反演结果的对比可知,多尺度地震资料联合反演得到的结果不仅保持了很好的横向连续性,而且具有更高的分辨率,能够识别常规反演方法无法识别的薄层。在实际地震资料的反演试算中,多尺度地震资料联合反演也体现更高的分辨率,整体效果优于常规反演方法。
With the development of oil and gas exploration situation, hydrocarbon exploration is gradually shifted from structural reservoir to lithologic reservoirs. As a most effective geophysics method for reservoir exploration, seismic technology has been shifted from structure characterization to reservoir evaluation, lithologic interpretation and reservoir characterization and so on. Seismic inversion can extract various information about lithology, physical properties and fluid from seismic data, to help provide rich information for reservoir description. However, with increasing difficulty of exploration, conventional seismic inversion has failed to provide enough useful information. In order to perform high-precision exploration, I integrate the surface seismic data, crosswell and VSP data in the inversion method, making full use of the high lateral resolution of surface seismic data, wide-band information of crosswell data and accurate time-depth relationship of VSP data, to improve the accuracy of seismic inversion, and provide better service for exploration.
Conventional impedance inversion only uses the surface seismic data. Although surface seismic data has high lateral resolution, its vertical resolution is low. Surface seismic data, crosswell seismic data, and VSP data, although acquired in different means, of different resolution, are the corresponding seismic wave responses of the same geologic body. With the help of the Bayesian theory, we can link these three data together, and set up the joint probability density function of them.
In this thesis, I first discussed the Bayesian Theory, and studied multiscale seismic data joint inversion method. Then, I studied the influence of different prior distribution on the inversion results, and finally chose the Cauchy distribution, which fits the real well data well. Besides, I studied the influence of different parameters on the inversion results. In solving the inversion equation, I used the modified PRP conjugate gradient method, accelerating the convergence rate and increasing the robustness of the method. I also studied the sequential Gaussian simulation method for modeling. This method avoids the smoothing effect of the determinable modeling, and can help optimize the best results, as well as assessing the uncertainty. Finally, considering that real data has giant difference in value, I preprocessed the real data, making the choice of inversion parameters easier.
Multiscale seismic data joint inversion method is tested with theoretical model, by comparing the results with the conventional inversion, it shows that the result of joint inversion not only has better lateral continuity, but also has higher resolution. Through the test of real survey data, multiscale seismic data joint inversion reflects higher resolution, and its overall performance is better than the conventional inversion method.
常规的波阻抗反演方法只利用了地面地震数据,而地面地震数据虽然具有较高的横向分辨率,在垂向上的分辨能力却比较低,这样导致得到的反演结果往往精度不够高。地面地震数据、井间地震数据和VSP数据虽然具有采集方式不同、波场信息丰富程度不同、分辨率尺度不同,但是它们却是地下相同的地质体的地震波响应。利用贝叶斯理论可以将这三者联系起来,建立起这三种资料的联合概率密度函数。
论文中首先讨论了贝叶斯反演理论,研究了基于贝叶斯理论的多尺度地震资料联合反演方法。然后研究了不同的先验分布函数对于反演结果的影响,采用了符合实际井数据统计特征的柯西分布;同时研究了不同的参数对于反演结果的影响,为反演方程中参数的选取指明了方向。在求解反演方程时,通过对目标函数的分析,采用了改进的PRP共轭梯度法,加快了方程收敛的速率,确保了反演的稳定性。研究了序贯高斯模拟建模方法,避免了确定性建模方法的平滑效应,同时能够对模拟结果进行优选和不确定性评价。最后针对实际的地震资料量纲差别大的情况,对实际地震资料进行了预处理,方便了反演参数的选取。
对多尺度地震资料联合反演方法进行模型测试,通过与常规反演结果的对比可知,多尺度地震资料联合反演得到的结果不仅保持了很好的横向连续性,而且具有更高的分辨率,能够识别常规反演方法无法识别的薄层。在实际地震资料的反演试算中,多尺度地震资料联合反演也体现更高的分辨率,整体效果优于常规反演方法。
With the development of oil and gas exploration situation, hydrocarbon exploration is gradually shifted from structural reservoir to lithologic reservoirs. As a most effective geophysics method for reservoir exploration, seismic technology has been shifted from structure characterization to reservoir evaluation, lithologic interpretation and reservoir characterization and so on. Seismic inversion can extract various information about lithology, physical properties and fluid from seismic data, to help provide rich information for reservoir description. However, with increasing difficulty of exploration, conventional seismic inversion has failed to provide enough useful information. In order to perform high-precision exploration, I integrate the surface seismic data, crosswell and VSP data in the inversion method, making full use of the high lateral resolution of surface seismic data, wide-band information of crosswell data and accurate time-depth relationship of VSP data, to improve the accuracy of seismic inversion, and provide better service for exploration.
Conventional impedance inversion only uses the surface seismic data. Although surface seismic data has high lateral resolution, its vertical resolution is low. Surface seismic data, crosswell seismic data, and VSP data, although acquired in different means, of different resolution, are the corresponding seismic wave responses of the same geologic body. With the help of the Bayesian theory, we can link these three data together, and set up the joint probability density function of them.
In this thesis, I first discussed the Bayesian Theory, and studied multiscale seismic data joint inversion method. Then, I studied the influence of different prior distribution on the inversion results, and finally chose the Cauchy distribution, which fits the real well data well. Besides, I studied the influence of different parameters on the inversion results. In solving the inversion equation, I used the modified PRP conjugate gradient method, accelerating the convergence rate and increasing the robustness of the method. I also studied the sequential Gaussian simulation method for modeling. This method avoids the smoothing effect of the determinable modeling, and can help optimize the best results, as well as assessing the uncertainty. Finally, considering that real data has giant difference in value, I preprocessed the real data, making the choice of inversion parameters easier.
Multiscale seismic data joint inversion method is tested with theoretical model, by comparing the results with the conventional inversion, it shows that the result of joint inversion not only has better lateral continuity, but also has higher resolution. Through the test of real survey data, multiscale seismic data joint inversion reflects higher resolution, and its overall performance is better than the conventional inversion method.
引文
[1]张永刚.地震波阻抗反演技术的现状和发展[J].石油物探. 2002, 41(4): 385-390
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[2]杨谦,李正文.地震资料带宽约束反演方法及应用[J].石油物探. 1996, 35(4): 37-42
[3]孟宪民,蒋维平.波阻抗反演技术及其应用效果[J].中国煤炭地质. 2009, 21(1): 21-24
[4]印兴耀,韩文功,李振春.地震技术新进展[M].东营:中国石油大学出版社, 2006,341(5): 606-613
[5] Fu L Y. Joint inversion of seismic data for acoustic impedance[J]. Geophysics. 2004, 69(4): 994-1004
[6]曹丹平,印兴耀,张繁昌,等.多尺度地震资料联合反演方法研究[J].地球物理学报.2009,11(4): 1059-1067
[7] Danilo R.Velis. Stochastic sparse-spike deconvolution[J]. Geophysics. 2008, 73(1): 1021-1030
[8] Youzwishen C F. Non-linear sparse and blocky constraint for seismic inverse problems[D]. University of Alberta, 2001
[9] Paul Gelderblom, Jaap Leguijt. Geological constraints in model-based seismic inversion[J]. SEG Expanded Abstracts. 2010, 29(1): 2825-2829
[10]卢占武,韩立国.波阻抗反演技术研究进展[J].世界地质. 2002, 21(4): 28-34
[11]王西文,石兰亭,雍学善,等.地震波阻抗反演方法研究[J].岩性油气藏. 2007, 19(3): 144-151
[12]吕铁良,王永刚,谢万学,等.稀疏脉冲反演技术在井间地震反演中的应用[J].石油物探. 2007, 46(1): 58-63
[13]张宏兵,方前发.波阻抗约束反演的几种方法[J].水文地质工程. 2005, 9(5): 38-42
[14]张江华,林承焰,惠俊刚,等.影响约束地震反演品质的因素分析[J].西北大学学报. 2008, 38(4): 101-105
[15]彭传平.宽带约束反演方法实现及应用研究[D].西安:长安大学, 2008
[16] Carcione J M, Herman G C, Ten K A. Seismic modeling[J]. Geophysics. 2002, 67(4): 1304-1325
[17] Ulrych T J, Sacchi M D, Woodbury A. A Bayes tour of inversion: A tutorial[J]. Geophysics. 2001, 66(1): 55-69
[18] Laurence R L. Cooperative inversion of geophysical data[J]. Geophysics. 1988, 53(1): 1745-1749
[19] Bosch M, Mcgaughey J. Joint inversion of gravity and magnetic data under lithologic constraints[J]. The Leading Edge. 2001, 20(8): 877-881
[20] Tarantola A. Inverse Problem Theory and Methods for Model Parameter Estimation[M]. philadephia: Society for Industrial and Applied Mathematics, 2005
[21] Mackie R, Watts M D, Rodi W. Joint 3D inversion of marine CSEM and MT data[J]. SEG Technical Program Expanded Abstracts. 2007, 26(1): 574-578
[22]张繁昌,刘杰,印兴耀,等.修正柯西约束地震盲反褶积方法[J].石油地球物理勘探. 2008, 43(4): 391-396
[23]刘百红,李建华.测井和地震资料宽带约束反演的应用[J].石油物探. 2004, 13(1): 140-144
[24]黄文松,年静波,刘喜武.地震波阻抗反演的预条件共轭梯度法[J].新疆石油地质. 2006, 27(4): 15-19
[25]朱向阳,熊有伦.一种改进的Powell共轭方向算法[J].控制与决策,1996,11(2):304-308
[26] Vozoff K, Jupp D L B. Effective search for a buried layer: An approach to experimental design in geophysics[J]. Exploration Geophysics. 1977, 8(1): 6-15.
[27]孙英君,王劲峰,柏延臣.地质统计学方法进展研究[J].地球科学进展. 2004, 19(2): 35～42
[28] Dennis van der Burg, Arie Verdel, Kees Wapenaar. Ray-based stochastic inversion of prestack seismic data for improved reservoir characterization[J]. Geophysics. 2009, 74(5): 85-97
[29] R.P.Srivastava, M.K.Sen. Stochastic inversion of prestack seismic data using fractal-based initial models[J]. Geophysics. 2010, 75(3): 47-59
[30]秦月霜,郭海晓,陈友福.变差函数对地震反演精度的影响[J].大庆石油学院学报. 2009, 33(4): 62-67
[31]刘兴冬.随机反演变差函数适用性研究[J].石油天然气学报. 2010, 32(2):42-47
[32]刘永社,印兴耀,贺维胜.空间相关分析因素对储层建模中克里金估计结果的影响[J].石油大学学报. 2004, 28(2): 32-37
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