CN108139498B - 具有振幅保持的fwi模型域角度叠加 - Google Patents

具有振幅保持的fwi模型域角度叠加 Download PDF

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CN108139498B
CN108139498B CN201680059382.2A CN201680059382A CN108139498B CN 108139498 B CN108139498 B CN 108139498B CN 201680059382 A CN201680059382 A CN 201680059382A CN 108139498 B CN108139498 B CN 108139498B
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杨迪
R·班赛尔
S·K·拉杂拉拖斯
燕佳
A·I·鲍姆斯坦
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Abstract

一种方法，包括：获得根据预定的地下反射角范围被分成子集的地震数据集；利用计算机分别对每个子集执行声波全波场反演过程以对密度进行反演并生成相应的密度模型；使用相应的密度模型，作为反射角的函数为每个子集生成声阻抗；以及使用计算机将每个子集的声阻抗变换成反射率剖面，其中所述变换包括通过它们相应的带宽对反射率剖面进行归一化。

Description

具有振幅保持的FWI模型域角度叠加
相关申请的交叉引用
本申请要求于2015年10月15日提交的标题为“FWI MODEL DOMAIN ANGLE STACKSWITH AMPLITUDE PRESERVATION”的美国临时专利申请62/241,780的权益，该申请的全部内容通过引用被结合于此。
技术领域
本文描述的示例性实施例涉及地球物理勘探领域，并且更特别地涉及地球物理数据处理。具体而言，本文描述的实施例涉及用于更高效地生成FWI模型域角度叠加(anglestack)的方法。
背景技术
本部分旨在介绍可以与本发明的示例性实施例相关联的现有技术的各个方面。这种讨论被认为有助于提供框架以便于更好地理解本发明的特定方面。因此，应当理解的是，本部分应该以此来阅读，而不必作为对现有技术的承认。
地震勘探的重要目标是准确地对通常称为反射体的地下结构进行成像。通过在地震勘测的执行期间获得原始地震数据有利于地震勘探。在地震勘测期间，地震能量通过例如受控***在地面生成，并传递到地球。地震波由地下结构反射，并被许多称为地震检波器的传感器接收。由地震检波器接收到的地震数据被处理以便创建地下环境的准确映射。处理后的数据然后被检查，以识别可能含有油气(hydrocarbon)的地质构造。
全波场反演(FWI)是用于估计地下属性(诸如速度或密度)的地球物理学方法。众所周知，与传统方法相比，它具有更高的分辨率和更准确的物理特性。FWI算法的基本组成部分可以被描述如下：使用起始地下物理属性模型，通过使用数值方案(例如，有限差分、有限元法等)求解波动方程来生成合成地震数据。将合成地震数据与现场地震数据进行比较，并使用两者之间的差计算目标函数的值。为了最小化目标函数，生成修改后的地下模型，其用于模拟一组新的合成地震数据。将这组新的合成地震数据与现场数据进行比较以重新计算目标函数的值。通过使用新的更新模型作为寻找另一个搜索方向的起始模型来迭代目标函数优化过程，然后将其用于干扰模型以便更好地解释观察到的数据。这个过程继续，一直到发现能够令人满意地解释观察到的数据的更新模型。可以使用全局或局部优化方法来最小化目标函数并更新地下模型。常用的局部目标函数优化方法包括但不限于梯度搜索法、共轭梯度法、准牛顿法、高斯牛顿法和牛顿法。常用的全局方法包括但不限于蒙特卡罗或网格搜索。
虽然FWI被期望提供地下属性，但是难以直接用FWI从地震数据中提取正确的粘弹性属性。由于FWI通过将数据与合成波形进行拟合来估计属性，因此它依赖于波动方程可以如何准确地解释实际物理特性，以及优化方法可以多好地将影响与不同的属性分开。当使用声波方程时，FWI可以基于数据集中的行进时间信息来生成P-波速度模型。但是，由于真实的地球是粘弹性的，因此振幅信息没有得到充分利用，并且声学模型无法解释所获取的数据中的所有振幅。如果FWI被期望提供可解释的产品，比如弹性阻抗，那么通常需要弹性模拟，但非常昂贵；一般而言，它是声学FWI计算的6到10倍。此外，由于有限的剪切波运动学信息以及采集中常常较差的信噪比，因此难以获得剪切波速度的初始模型。
使用弹性振幅信息的替代方法是形成角度叠加。可以对角度叠加执行振幅与角度(AVA)分析[5]以提取弹性属性。用Kirchhoff迁移生成的传统AVA叠加需要几何扩展校正来解决传播期间的振幅损失。但是，不能保证校正后的振幅将反映数据的真实振幅。此外，Kirchhoff迁移基于有利于平滑速度模型并可能在高对比度的介质中失败的射线追踪。角度计算是在一维(1D)假设下进行的，当地下结构复杂时，这种假设不够准确。基于逆时间迁移(RTM)的角度叠加[1,2]对于利用高分辨率速度模型更为先进。尽管如此，振幅保持仍然困难。Yu Zhang等人(2014)[3]报告了平衡图像振幅的最小二乘RTM；但是，它尚未被证明能够生成角度叠加。
发明内容
一种方法，包括：获得根据预定的地下反射角范围被分成子集的地震数据集；利用计算机分别对每个子集执行声波全波场反演过程以对密度进行反演并生成相应的密度模型；使用相应的密度模型，作为反射角的函数为每个子集生成声阻抗；以及使用计算机将每个子集的声阻抗变换成反射率剖面(reflectivity section)，其中所述变换包括通过它们相应的带宽对反射率剖面进行归一化。
在该方法中，每个全波场反演过程从相同的速度模型开始。
在该方法中，每个全波场反演过程被独立地应用到子集。
在该方法中，所述获得包括通过使用包括反射体倾斜角和P-波速度的信息的数据屏蔽(data mask)将炮集(shot gather)划分为子集。
该方法还可以包括对于每个反射率剖面使用傅里叶变换、离散傅里叶变换或快速傅立叶变换以计算在相同位置处应用于全部反射率剖面的至少一个局部窗口内的平均频谱，并确定每个平均频谱的带宽。
在该方法中，所述确定带宽是基于10-dB点之间的距离。
在该方法中，所述确定带宽是基于具有最陡斜率的点之间的距离。
在该方法中，平均频谱在多个局部窗口内被计算，并且被平均。
该方法还可以包括确定多个角度的反射率值并通过内插构建角度与振幅的曲线。
该方法还可以包括使用反射率剖面管理油气生产。
在该方法中，管理油气生产包括在至少部分地由反射率剖面确定的位置处钻井。
一种利用指令编码的非瞬态计算机可读存储介质，当所述指令由计算机执行时使所述计算机实现一种方法，所述方法包括：获得根据预定的地下反射角范围被分成子集的地震数据集；利用计算机分别对每个子集执行声波全波场反演过程以对密度进行反演并生成相应的密度模型；使用相应的密度模型，作为反射角的函数为每个子集生成声阻抗；以及使用计算机将每个子集的声阻抗变换成反射率剖面，其中所述变换包括通过它们相应的带宽对反射率剖面进行归一化。
附图说明
虽然本公开容许各种修改和替代形式，但是其具体示例实施例已经在附图中示出并且在本文中进行了详细描述。但是，应当理解的是，本文对具体示例实施例的描述不旨在将本公开限制于本文所公开的特定形式，而是相反，本公开要涵盖由所附权利要求限定的所有修改和等同物。还应当理解的是，附图不一定按比例绘制，而是将重点放在清楚地图示本发明的示例性实施例的原理上。此外，某些维度可能被夸大以帮助在视觉上传达这些原理。
图1图示了用于生成FWI AVA叠加的示例性方法。
图2图示了由于散射角度引起的频谱扩展效应。
图3A图示了单炮集。
图3B图示了被静音成五个不同角度范围的单炮集。
图4A图示了具有声学FWI的角度叠加。
图4B图示了具有卷积的角度叠加。
图5图示了来自图4A和图4B中的每个角度叠加的垂直线，其被重叠以显示一致性。
具体实施方式
本文描述了示例性实施例。但是，就以下描述特定于特定实施例而言，这仅仅是出于示例性目的，并且只是提供示例性实施例的描述。因此，本发明不限于下面描述的具体实施例，而是，它包括落入所附权利要求的真实精神和范围内的所有替代、修改和等同物。
本文描述的示例性实施例提供了一种方法，该方法可以：1)对于复杂的地质情况是稳健的；2)保持振幅与角度信息；以及3)比弹性FWI更便宜。所提出的FWI模型域角度叠加可以通过对不同声学模型的不同角度范围的数据集进行反演来生成。通过数据拟合过程可以实现振幅保持，并且使用坡印廷(Poynting)向量角度计算更准确。坡印廷向量描述了在各向同性和各向异性介质中体波、界面波、导波和非均匀波的能量流。坡印廷向量自然地利用了高分辨率FWI速度模型。当作为FWI工作流程的组成部分实现时，目前的技术优势可以在不改变平台的情况下利用FWI产品角度叠加。更重要的是，示例性方法不限于建模引擎中的不完整物理特性。
本技术进步的示例性实施例使用FWI生成模型域振幅保持的角度叠加。有利地，目前的技术进步可以仅使用声学模拟，但是可以应用于所获取的地震数据的完整偏移。使用一个声学模型来拟合包含各种物理特性的所有数据是不可能的。但是，如果数据集通过反射角度分开，那么对于每个角度，都存在可以解释数据的声学模型。在所有模型组合的情况下，阻抗模型被形成为反射角的函数：I(θ)。声阻抗是地震能量穿过地下环境的特定部分的容易程度的量度。本领域的普通技术人员将认识到的是，声阻抗可以被定义为密度和地震速度的乘积。根据阻抗，反射率可以作为角度的函数被推导出来：R(θ)，其正好是AVA的定义。
实际上，没有必要找到R(θ)的连续形式。相反，R(θ)可以在多个角度被确定，并且AVA曲线可以通过内插重建。
图1图示了用于生成FWI AVA叠加的示例性方法。在步骤101中，获得处理后的数据，其可以是从收集到的地震数据中生成的单炮集。这种处理后的数据是根据本领域普通技术人员已知的常规技术调整的地震数据。在步骤102中，炮集被划分成若干子集。每个子集都在相对小的反射角范围内。这可以通过使用精心设计的数据屏蔽来实现，这些数据屏蔽包括反射器倾角和P-波速度的信息。利用倾角和P-波速度，可以使用射线追踪方法来寻找在来自每个反射角的每个地下点的数据中的反射波的时间和偏移。数据屏蔽是隐藏原始数据的一部分使得只有期望的部分(即，期望角度范围)可用于后续处理的过程。附图中示出的角度范围仅仅是示例性的，并且可以使用其它角度范围。此外，角度范围的数量也是示例性的，因为炮集可以被划分成更多或更少的剖面。
在步骤103中，在步骤102中生成的每个数据子集上，应用声学FWI以独立地获得声阻抗。本领域的普通技术人员熟悉声学FWI，并且该过程的进一步细节被省略。所有的反演可以从相同的速度模型开始，并且假定速度模型建立已经完成并且足够准确，因此运动学在这个过程中不会被更新。模型更新仅用于解释数据振幅。在反演之后，用这些阻抗模拟的合成波形很好地拟合了真实数据，使得振幅信息被保持在模型域中。每个阻抗模型只能解释由数据屏蔽约束的一定范围的反射角的数据。在一个角度范围内，可以选择中间角度作为反射率的标称角度。在反演中形成梯度时，通过使用坡印廷向量[2]，可以附加地保证这一点，因此梯度对标称角度的反射最为敏感。在有限差分模拟和梯度计算的过程中，使用坡印廷向量来分离波传播方向。数据分离可以基于射线理论进行。由于坡印廷向量基于波动理论，因此它可以帮助检查数据分离的准确性。
如本文使用的术语速度模型、密度模型或物理属性模型是指数字的数组，通常是3-D数组，其中可以被称为模型参数的每个数字是速度、密度或小区中其它物理属性的值，其中地下区域在概念上被划分为离散的小区以用于计算目的。
在反演之后，密度和速度两者都是已知的，并且步骤104可以根据声学FWI的结果来确定阻抗，因为阻抗是密度和速度的函数。
在声学FWI中，两个参数可以被反演以拟合数据振幅：P-波速度和密度。当使用L-2标准类型的目标函数时，通常选择P-波速度来拟合振幅和行进时间。但是，密度可能是用于反射率反演的更好的参数。密度具有比P-波速度简单得多的AVA响应。如在Aki-Richards方程中所描述的：
其中Δρ是密度扰动并且Δα是P-波速度扰动，密度具有不随角度变化的恒定AVA响应[6]。这表明，当密度扰动被反演以在某个角度θ拟合数据振幅时，扰动的值直接表示在该角度θ的反射率，而不管实际θ的值如何。相反，如果使用P-波速度扰动，那么为了获得R(θ)，我们需要应用的校正。此外，方程[1]仅在扰动弱时是有效的，并且当扰动强时，校正不具有明确的形式。对于密度，恒定的AVA响应对于所有情况都是有效的。
在获得声阻抗之后，它们可以在步骤105中被成形或转换为反射率剖面(P-P反射率)。可以根据声阻抗相对于空间的导数(或者更一般地，垂直导数，其在一些情况下可能是时间)近似地确定反射率剖面。但是，还有一个更多的步骤来平衡跨不同角度的反射率谱，即，“拉伸”。虽然图1示出了在同一步骤中的“成形”和“拉伸”，但这些不一定被同时执行。
类似于迁移中的小波拉伸效应，从不同反射角的数据获得的反射率具有不同的分辨率。由于只有带限数据(ω0～ωf)，其中ω0和ωf是在数据中存在的最小和最大频率，因此在每个角度θ，反射率谱仅在如图2所示的波数域中从到进行采样。波数域中的不同带宽导致空间域中的不同振幅。假定真实的反射率值R(θ1)和R(θ2)是相同的，那么反演的反射率之间的关系将是因此，为了在模型域中保持数据AVO，需要通过除以cosθ的因子来补偿频谱拉伸。实际上，使用单个反射角的数据是困难的。因此，获得补偿因子的替代方法是测量反射率的带宽。对于所有反射率剖面，可以使用傅里叶变换来计算在相同位置处应用到所有剖面的局部窗口内的平均频谱。只要位置在所有剖面中都是相同的，这就可以在多个位置处执行并求平均。傅立叶变换可以是优选的，但也可以使用其它变换，诸如FFT或DFT。带宽可以被定义为例如10-dB点之间的距离。但是，可以使用带宽的其它测量(即，3-dB点、半极大值全宽、最陡斜率点等)，但是10-dB点之间的距离可能是优选的。然后，为了完成步骤105并补偿“拉伸”，每个反射率剖面通过其自己的带宽被归一化，使得对反射率振幅的频谱拉伸效应被校正。
图1中的方法(步骤106)的最终输出是不同角度的反射率叠加。
本技术进步应用于用从SEG SEAM阶段I模型提取的2-D切片生成的合成数据集。压力数据是用4公里最大偏移量的拖缆(streamer)模拟的。在水面上使用了吸收边界条件。因此，数据中不存在与自由表面相关的倍数。如图3A所示，通过与以下角度范围0-10；10-20；20-30；30-40；以及40-50度对应的虚线301、302、303、304和305将单个炮集划分成五个剖面。角度范围不一定需要重叠。基于这些线301-305设计五个数据屏蔽，每个屏蔽覆盖10度的反射角。因此，如图3B所示，生成了五个数据子集(参见步骤102)。从相同的速度模型开始，分别使用每个子集来执行声学FWI(参见步骤103)。在反演之后结果得到的声学阻抗(参见步骤104)被“成形”和“拉伸”(参见步骤105)成反射率剖面(参见步骤106)，并且在图4A的面板中示出。最后面板中的间隙区域401是因为来自深部的大角度反射在采集偏移的外部。为了验证结果的质量，通过地震子波与反射率序列之间的卷积生成真实的反射率剖面，并且在图4B中示出。反射率序列使用Zoeppritz方程[4]和真实的合成模型进行计算。图4A和图4B中的AVA看起来是一致的。为了更仔细地研究，来自模型域叠加的五条垂直线402a、403a、404a、405a和406a以及来自卷积剖面402b、403b、404b、405b和406b的五条垂直线在图5中被重叠以示出一致性。很清楚，在所有角度和所有深度下，与卷积叠加相比，FWI模型域叠加具有非常相似的振幅。它表明工作流程在地质情况复杂的情况下是可靠且准确的。
最终反射率是可用于地下的解释和/或油气勘探的管理的地下图像的示例。如本文所使用的，油气管理包括油气提取、油气生产、油气勘探、识别潜在的油气资源、识别井的位置、确定井注入和/或提取率、识别储层连接性、获取、处置和/放弃油气资源、回顾先前的油气管理决策、以及其它与油气有关的行为或活动。
在所有实际应用中，本技术进步必须与根据本文公开内容编程的计算机结合使用。优选地，为了高效地执行FWI，计算机是如本领域技术人员已知的高性能计算机(HPC)。这种高性能计算机通常涉及节点集群，每个节点具有多个CPU和允许并行计算的计算机存储器。可以使用任何交互式可视化程序和相关联硬件(诸如显示器和投影机)对模型进行可视化和编辑。***的体系架构可以变化，并且可以由能够执行逻辑操作并根据本技术进步显示输出的任何数量的合适的硬件结构组成。本领域普通技术人员知道可从Cray或IBM获得的合适的超级计算机。
参考文献：
以下参考文献通过引用被整体地结合于此：
[1]Xu,S.,Y.Zhang和B.Tang,2011年,3D angle gathers from reverse timemigration:Geophysics,76:2,S77–S92.doi:10.1190/1.3536527；
[2]Thomas A.Dickens和Graham A.Winbow(2011)RTM angle gathers usingPoynting vectors.SEG Technical Program Expanded Abstracts 2011:pp.3109-3113；
[3]Yu Zhang,Lian Duan和Yi Xie(2013)A stable and practicalimplementation of least-squares reverse time migration.SEG Technical ProgramExpanded Abstracts 2013:pp.3716-3720；
[4]Encyclopedic Dictionary of Applied Geophysics,R.E.Sheriff,4thedition.,SEG,2002,p.400；
[5]Encyclopedic Dictionary of Applied Geophysics,R.E.Sheriff,4thedition.,SEG,2002,p.12；以及
[6]Aki,K和Richards,P(2002)Quantitative seismology,2nd edition,University Science Books,p.148.

Claims (11)

1.一种用于生成全波场反演模型域角度叠加的方法，包括：
获得根据预定的地下反射角范围被分成子集的地震数据集；
利用计算机分别对每个子集执行声波全波场反演过程以对密度进行反演并生成相应的密度模型；
使用相应的密度模型为每个子集生成作为反射角的函数的声阻抗；
使用计算机将每个子集的声阻抗变换成反射率剖面，其中所述变换包括通过每个子集的相应的带宽对反射率剖面进行归一化；以及
对于每个反射率剖面使用傅里叶变换、离散傅立叶变换或快速傅立叶变换以计算在相同位置处应用于全部反射率剖面的至少一个局部窗口内的平均频谱，并确定每个平均频谱的带宽。
2.如权利要求1所述的方法，其中每个声波全波场反演过程从相同的速度模型开始。
3.如权利要求1所述的方法，其中每个声波全波场反演过程被独立地应用到子集。
4.如权利要求1所述的方法，其中获得所述地震数据集包括通过使用数据屏蔽将炮集划分为子集，所述数据屏蔽包括反射体倾斜角和P-波速度的信息。
5.如权利要求1所述的方法，其中确定带宽是基于10-dB点之间的距离。
6.如权利要求1所述的方法，其中确定带宽是基于具有最陡斜率的点之间的距离。
7.如权利要求1所述的方法，其中所述平均频谱在多个局部窗口内被计算并且被平均。
8.如权利要求1所述的方法，还包括确定多个角度的反射率值并通过内插构建角度与振幅的曲线。
9.如权利要求1所述的方法，还包括使用反射率剖面管理油气生产。
10.如权利要求9所述的方法，其中管理油气生产包括在至少部分地由反射率剖面确定的位置处钻井。
11.一种利用指令编码的非瞬态计算机可读存储介质，当所述指令由计算机执行时使所述计算机实现一种用于生成全波场反演模型域角度叠加的方法，所述方法包括：
获得根据预定的地下反射角范围被分成子集的地震数据集；
利用计算机分别对每个子集执行声波全波场反演过程以对密度进行反演并生成相应的密度模型；
使用相应的密度模型为每个子集生成作为反射角的函数的声阻抗；
使用计算机将每个子集的声阻抗变换成反射率剖面，其中所述变换包括通过每个子集的相应的带宽对反射率剖面进行归一化；以及
对于每个反射率剖面使用傅里叶变换、离散傅立叶变换或快速傅立叶变换以计算在相同位置处应用于全部反射率剖面的至少一个局部窗口内的平均频谱，并确定每个平均频谱的带宽。
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