CN103460074B - 全波场反演中小波估计和多次波预测的方法 - Google Patents
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Abstract
本发明涉及一种小波估计方法，其利用数据中的一次和多次反射波，对地震数据的全波场反演（“FWI”）是尤其有利的。本发明方法使用FWI算法以在多次反射波第一次到达之前（101）从浅层的一次反射波产生地下模型(101)。然后该模型用于模拟多次波（102）。所述小波随后经修改（104）以便模拟的多次波接近匹配真实的记录多次波（103）。然后可从测量的数据中减去该模拟的多次波（105）由此创造基本上没有多次波的更深顶层的数据，且然后可重复所述方法以拓展所述地下模型至更大的深度（106）。
Description
相关申请的交叉参考
本申请要求2011年3月31日提交的美国临时专利申请号61/470,237的优先权，该申请名称为Method of Wavelet Estimation and MultiplePrediction in Full Wavefield Inversion(全波场反演中小波估计和多次波预测的方法)，其通过引用包括在此。
技术领域
本发明一般涉及地球物理勘探领域，更具体地涉及地震数据处理。特别地，本发明是一种地震数据的全波场反演中小波估计和多次波预测的方法。
背景技术
全波场反演(full waveform inversion,“FWI”)是将地震数据反演来推导影响地震波传播的地球地表下/次地表性质的方法。它的正演建模引擎(forward modeling engine)利用有限差或其他的计算方法来建模通过地球次地表模型的声音或弹性地震波的传播。FWI寻求最优的次地表模型以便所模拟的地震波形匹配在接收器位置处现场记录的地震波形。FWI理论最初是由Tarantola(1989)开发的。在过去的十年里在勘探地球物理中对FWI的研究和应用十分活跃，这得益于计算能力的大幅提升。
众所周知，当线性的声波或弹性波等式被用于建模地震波传播时，模拟的波形线性地依赖于输入源小波。实际上，源小波的精确估计在FWI中起着关键的作用。Delprat-Jannaud和Lailly(2005)指出精确的小波测量对于FWI中阻抗坡面的声音重塑似乎是一个重要挑战。他们认为震源小波中的小误差导致已反演模型(inverted model)更深部分中的强干扰，这是由于多次反射的不匹配。他们得出如下结论：“通过最小化一次反射波形的能量来估计小波的经典方法不可能提供所要求的精度，除非是非常特殊的情形。”
事实上，在没有井控(well control)的情况下的一次反射波的反演在估计小波时面临着基本非唯一性。例如，较大的反射事件可由较大的阻抗对比或较强的震源引起。对于小波相位和功率谱而言没有相似的模糊性。井数据通常用于限制小波强度和相位。但是井日志不是总能获得的，特别是在早期勘探设置中或浅次地表情形下。
在地球物理著作中已对小波估计有广泛的研究。特别地，Wang等人(2009)讨论了关于FWI的小波特征的反演且参考书目在此。然而，这些方法都隐含依赖直达波或折射波用于小波估计。因为这些传输的模式沿着几乎水平的射线路径传播，所以会受到不影响几乎垂直的反射射线路径的效应(例如辐射型、与自由面的复杂相互作用)的影响。这样的效应常常难于精确地描述和模拟。因此，需要为垂直传播的能量估计小波，且这对于反射主导的应用(例如深水获取、更深目标的成像)是特别相关的。
在传统的地震处理中多次波被认为是噪声，因为它们常常污染一次反射波且使解译更困难。另一方面，已知多次波可以对于限制次地表性质和地震源小波也有用。Verschuur等人(1989、1992)提出地表相关多次波消除(SRME)的方法，通过该方法在多次波消除的同时可实施小波估计。SRME的主要原理已被G.J.A van Groenestijn等人(2009)拓展到反演机制中以重塑失去的近偏移一次波和小波。但是不清楚对于SRME最优的小波是否对于FWI也是最优的。诸如vanGroenestijn和Verschuur的论文在时域中实施多次波建模和小波估计，即没有次地表模型的数据驱动。
发明内容
在一个实施例中，本发明是由计算机实施的地震处理方法，其包括产生且同时优化震源小波和次地表模型到可延伸的深度，其中一次反射波和多次反射波的模拟波形是从深度域中的震源小波和次地表模型产生的且然后进行比较，用于匹配在地震接收器位置记录的波形。
附图说明
参考下面的详细描述和附图将更好地理解本发明和它的优势，其中：
图1是示出本发明方法的基本步骤的流程图；
图2示出在利用源S1和接收器/检波点R1的震波采集中的多次反射波的图解描述；
图3示出深水地震数据的炮点道集，其示出在感兴趣的多次波之前到达的浅一次波，这些多次波是水面相关的多次波；
图4示出来自图3中的浅一次波的反演浅次地表(inverted shallowsubsurface model)模型；
图5示出记录的炮点道集、基于图4中反演浅地下/次地表模型的模拟炮点道集和它们的数据残留；
图6示出具有深一次波和多次波、基于图4中浅次地表模型的模拟多次波和从记录数据中减去模拟多次波的记录数据；
图7示出图6(3.8s到4.5s)的放大以清楚地展示多次波预测的质量，其中帧示出被选择以执行小波估计的数据；
图8示出多次波建模，其中将30度相位旋转应用到最优小波：(从左边起)记录数据、基于已旋转小波和反演次地表模型的模拟多次波以及它们的数据残留；
图9示出基于具有不正确功率谱(与最优小波相比，在低频中丰富)的小波的多次波建模的结果：(从左边起)记录数据、基于低频小波的模拟多次波和它们的数据残留；
图10示出记录多次波的功率谱和模拟多次波的功率谱，其用于设计本发明的整形滤波器；
图11示出记录多次波的功率谱和在应用所述整形滤波器到图9和10中所用的小波后模拟多次波的功率谱；
图12示出图1的步骤103中所作的决定在步骤106中是怎样有可能改变的；以及
图13示出本发明方法从浅到深的递归。
将结合示例实施例描述本发明。但是，就下面的详细描述专用于特定实施例或本发明的特殊使用来说，这意图仅仅是示例性的，并且不解释为限制本发明的范围。相反，意图覆盖所有的替代、修改和等同情况，它们可包括在权利要求限定的本发明范围内。本领域技术人员将容易认识到在本发明方法的实际应用中，必须在合适编程的计算机上执行它。
具体实施方式
本发明是针对FWI应用的小波估计方法，其利用数据中的一次反射波和多次反射波。本发明方法使用FWI算法以从一次反射波产生次地表模型。该模型然后用于模拟多次反射波。所述小波后来经修正以便模拟的多次波接近匹配真实的记录多次波。
除了提供精确的小波估计外，这个方法提供一些好处作为多次波消除策略。具体地，它不需要使用密集的交叉线抽样来在3D中建模多次波：一旦使用FWI建立了浅次地表模型，则对于任何采集配置建模多次波是简单的。还有，因为该方法是基于模型的且不依赖于一次波/多次波时差分离性(primary/multiple moveout separability)，所以它自然提供对一次波的好的保护。
遵循示出本发明的一个实施例中基本步骤的图1流程图，使用深水地震数据作为例子来展示本发明方法。首先注意小波估计和水面相关的多次波的建模，但是本领域的技术人员将容易理解相似的方法可应用于其他类型多次波，其中的一个实例在图2中示出。
图2示出在利用源S1和检波点R1的地震采集中多次反射波的图解描述。在该图中，多次波可被认为是在任何次地表边界Ai和任何次地表边界Bi之间被不止一次反射的信号。事实上，存在至少一个强反射器来制造感兴趣的场景。假设图中A1是强反射器，其可是海洋数据中的水空气界面或陆地采集中空气地球界面或盐边界或任何高对比度次地表。现在将感兴趣的多次波定义为在A1和Bi的任何一个之间被不止一次反射的信号。术语浅一次波意味着在感兴趣的多次波第一次到达之前到达的信号。因此，深一次波被定义成在感兴趣的多次波第一次到达之后到达的一次反射波。
在图1的步骤101中，从浅一次波反演浅次地表模型。图3示出该深水地震数据集的一个炮点道集。在该情形下，浅一次波7指代在3.7s之前的到达波，因为水面相关的多次波是在3.7s之后到达的。我们能够识别水面相关的多次波，因为根据定义这些多次波的最早到达时间是水底反射时间的两倍。那约为3.7s。(在图3纵坐标上显示时间，时间向下增加。)感兴趣的多次波是水面相关的多次波。回来参考图2，A1现在是水空气界面且B1表示水底。用于反演浅次地表模型的“浅一次波”是在帧7内，其在水底多次波8之前到达。
现在，使用标准速率建模工具，从上面提到的浅一次波构建深度域内的P波速率模型。应用声波FWI到浅一次波给出图4中的浅声波阻抗，其是在深度-公共深度点域(depth-cdp domain)中。由此，图4示出来自图3中“浅一次波”的反演浅次地表模型。用9表示水面位置且用10表示水底。注意，可在该步骤中可应用弹性FWI或更复杂的物理学以更精确地捕获达到更长偏移的波形。
图5示出记录的炮点道集11(其仅仅是来自图3的区域7，按时间轴放大)，基于图4的次地表模型的模拟炮点道集12以及在13中示出11和12之差。图4中的反演浅地球模型很好地解释了测量的数据，如通过小数据残留13明显看出的。注意，通过在模型中具有空气水界面来模拟表面相关的多次波，尽管在3.7s之前不存在表面相关的多次波，且因此不在图5中示出。
在步骤102中，使用通过步骤101中的反演获得的浅次地表速率模型和假设的地震小波模拟，即建模多次反射波。通过将模拟时间延长到5.5s，我们能够基于图4中的次地表模型模拟水面相关的多次波。在图6中，14示出在1km公共偏移域内的记录的地震数据，其包括深一次波和从浅次地表产生的水面相关的多次波；15示出基于图4中的浅次地表模型的模拟水面相关的多次波；以及16是从14中减去15，且因此16是所估计的深一次波。
在步骤103中，在所选的窗口中将模拟的多次波和记录的数据相比较以确定不匹配度。图7示出图6(3.8s到4.5s)的放大以清晰展示多次波预测的质量。在记录的数据中选择窗口17，尝试最小化多次和一次反射波之间的重叠。在模拟的多次波中用18表示相应的窗口。窗口17和18中的数据被选择以执行小波估计。小波估计的目标是最小化记录的数据17和模拟的多次波18之间的差，因为选择窗口是为了避免在数据中包含强的深一次波。19中示出从最优小波所得的差。
如果在步骤103中模拟的多次波和记录的数据之间的匹配不是令人满意的，那么可在步骤104中通过改正用于估计小波的3个小波性质，即小波振幅、相位和功率谱的任何一个或更多个，可对用于模拟多次波的小波进行调整。18中模拟的多次波将不匹配17中记录的多次波，除非实现最优小波估计。当最优小波估计被用于产生图4中的次地表模型时，19示出17和18之间的差。在下面更详细讨论该3个小波调整。
小波振幅。一次反射波p的振幅是由源小波S、源(检波点)虚反射Gsrc(Gsrc)、次地表反射系数Ri和几何扩散因子(geometric spreadingfactor)Lp决定:
p＝(S*Gsrc*Grec)·Ri/Lp (1)
类似地，多次反射波m的振幅由自由面反射系数Rfs和多次反射波位置的反射系数决定。例如“假肢”多次波通过下面等式与水底反射系数Rwb关联：
m＝(S*Gsrc*Grec)·Ri·Rwb·Rfs/Lm。 (2)
(2)除以(1)产生相对的多次波/一次波波振幅比和小波振幅之间的以下关系，假设在水面是全反射(Rfs＝1)：
其中Lp和Lm相对Rwb固定且因此作为比例常量。(3)中的第二比例来自等式(1)，其中次地表反射器是水底，该第二比例可写成
其中来自等式(1)的剩余项组成独立于S的比例常量。假定现场数据中的一次反射波与步骤101中使用小波强度S的反演模型匹配，然后等式(3)指示
由此，如果相比于记录的数据中的多次波，模拟的多次波太大或太小，那么可通过按比例增加或降低源小波的强度来调整该模拟的多次波。换句话说，等式(3)的地球物理学意义在于相对的水底多次波/一次波振幅比约束了水底反射系数。然后水底反射系数的知识允许我们通过匹配水底一次反射波的振幅来估计小波振幅。
小波相位。为了展示在本发明方法中小波相位是怎样被修正的，我们应用30度相位旋转到最优小波上，且重复图1中步骤101的FWI处理以建立不用于图4中的模型的新浅地球模型。然而，在2个模型中模拟的一次波都同样很好匹配测量的一次波。(未在附图中示出。)当反演不能仅基于一次反射波来检测小波相位旋转时，多次波用于获取小波相位旋转。图8示出模拟的水底多次波21不能匹配记录的水底多次波20，如22中的数据残留明显指示的。(这可与示出最优小波的相应结果的图6比较。)如果我们应用相位旋转算子Φ到21中模拟的水底多次波上，直到实现与20中测量的水底多次波的最好匹配，那么我们能够通过应用Φ到该小波来获取小波的相位旋转(在这个例子中是30度旋转)。在该步骤中，我们已选择水底多次波作为设计相位旋转算子Φ的事件。通常，我们可选取具有多次波和一次波的好分离度的任何局部事件。
小波功率谱。为了展示小波功率谱，即小波波形的傅里叶展开系数的绝对值是如何影响模拟和测量的多次波之间的一致性，应用0相位整形滤波器到最优小波以抑制它的高频能量。然后通过实施图1中的步骤101和102，如图10中所示，结果是具有与记录的多次波的功率谱26相比的功率谱27的模拟多次波。清楚的是模拟多次波具有比记录的多次波丰富的高频能量。这是预期的，和通过以下所见的相同。反演的地球功率谱E＝P/S，其中P和S分别是一次波和小波的功率谱。因为一阶多次波是再次被地球发射的一次波，所以多次波的功率谱是M＝E*P＝P2/S。因为P总是通过一次波上的FWI被匹配，所以S中更丰富的低频导致M中更丰富的高频。正如进一步证据显示模拟多次波具有比记录的多次波丰富的高频能量，图9示出模拟多次波24的多次波残留25且记录的多次波23包含高频能量。如果这是在应用本发明方法的过程中在步骤103的情况，那么我们可在步骤104中设计将功率谱26转变成27的0相位整形滤波器H。然后相同的整形滤波器被应用到所述小波上以获得最优小波。结果是，在应用H到图9和图10中使用的小波后，模拟多次波29的功率谱更接近于图11中记录的多次波28的功率谱。(如果在每个情形中选择相同的轨迹来计算功率谱那么曲线28和曲线26一样。)
一旦结束步骤104且从步骤101开始循环第二次，我们现在有了最优小波和在步骤102中预测感兴趣的多次波的浅次地表模型。通过在步骤105中从记录的数据中减去模拟多次波，我们将一次反射波从“浅”到“深”拓展。在具有最优小波的深一次波上执行FWI产生深次地表模型来匹配深一次波。
在步骤106中，重复步骤103中的比较。换句话说，多次反射波再次被模拟，但是现在使用从步骤105所得的模型，且在所选的窗口中将这些多次波预测与记录的数据比较。图12示出在步骤105中使深一次波反演后，步骤103中的决定是如何被改变的。如果在步骤103期间没有强的一次波出现在记录的数据中，那么无深一次波反演的估计的小波将是最终的小波。这是在现场数据研究中的情形，用此为实例来描述这里的方法。在强的深一次波与所选窗口内的多次波交叉或重叠的情形下，现将有可能在步骤105之后从多次波分离一次波。因此，为了使模拟多次波匹配和深一次波分离的多次波，在步骤104以及步骤101到106中需要重复小波估计。
如果有必要，通过重复上面的处理，本发明方法将产生最优小波和次地表模型，使得模拟的一次波(浅和深)和多次波匹配记录的数据。注意，概念“浅/深一次波”和“感兴趣的多次波”是递归定义的，即在“感兴趣的多次波”被建模和分离后，“深一次波”将变成“浅一次波”，且“感兴趣的”多次波将是在深度层中的强多次波，所述模型在递归数列中要延伸到该深度层。图13示出该递归。131示出被多次波(实线)掩盖的深一次波(下部---曲线)，该多次波是从浅一次波(上部---线)产生的。由于因此显示多次波，它可如132中所示被消除，其中出现在更大深度的多次波当前可被建模，且以此类推直到所有的一次波被反演(133)。由此，可重复整个处理直到获得最终的小波和次地表模型(107)。
为了描述本发明的目的，先前的权利申请针对本发明的特定实施例。然而对于本领域的技术人员明显的是，对这里描述的实施例做出许多改变和变形是可能的。所有这些改变和变形意在处于本发明的范围内，如所附的权利要求所定义的。
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Claims (9)
1.一种计算机可实施的用于反演从次地表区域测量的地震数据的方法，其包括：
(a)从所述地震数据选择浅层，其中确定所述浅层的深度以包括一次反射波即浅一次波，但是不包括感兴趣的多次反射波即多次波的第一次到达；
(b)使用估计的地震源小波反演所述浅一次波以产生影响地震波的传播的物理性质浅模型，然后在(c)-(e)中同时优化所述浅模型和所述估计的地震源小波；
(c)利用所反演的浅模型和所述估计的地震源小波，计算机模拟所述多次波；
(d)比较所模拟的多次波和所述地震数据中的对应多次波，并且调整所述估计的地震源小波来降低失配；
(e)重复(b)-(d)至少一次，或者直到所述失配降低到低于预定水平或满足其他停止条件；以及
(f)输出同时优化的地震源小波和浅模型。
2.根据权利要求1所述的方法，还包括通过在(e)之后并且在(f)之前***以下步骤来将所述浅模型和所述地震源小波的可应用性延伸到更大的深度：
(e1)从所述地震数据减去所模拟的多次波，然后将所述浅层延伸到更大的深度，然后为所延伸的浅层重复(b)-(e)。
3.根据权利要求2所述的方法，其中所述感兴趣的多次反射波是强多次波，“强”是基于预先选定的反射系数阈值确定的；
所述浅一次波的反演包括产生预测数据且在深度域中优化所述浅模型以匹配所述浅层中的测量的数据；以及
比较所模拟的多次波和所述地震数据中的对应多次波是在窗口内执行的，所述窗口被选择而包含多次波并且最小化在多次波和一次波之间的重叠。
4.根据权利要求3所述的方法，还包括通过重复(e1)至少一次进一步延伸所述浅模型的深度范围。
5.根据权利要求3所述的方法，其中调整所述估计的地震源小波包括以下中的至少一个：
应用相位旋转到所述估计的地震源小波；
应用振幅改正因子到所述估计的地震源小波；
应用频谱整形滤波器到所述估计的地震源小波。
6.根据权利要求5所述的方法，其中所述振幅改正因子是所述模拟多次反射波数据的振幅除以在窗口内的所述测量的地震数据的振幅，所述窗口被选择而包含多次波并且最小化在多次波和一次波之间的重叠。
7.根据权利要求5所述的方法，其中通过改变所述源小波的相位以及重复(b)-(d)以及为水底多次反射波事件或基于多次和一次反射波的分离而选择的另一个地震反射波事件检查改变的相位在(d)中的比较上的影响来确定所述相位旋转。
8.根据权利要求5所述的方法，其中至少部分基于(d)中关于频率内容的不匹配的分析设计所述频谱整形滤波器。
9.一种用于利用地震数据中的多次反射波优化源小波以及来自地震数据的次地表区域的物理性质模型的***，所述***包括：
(a)从所述地震数据选择浅层的装置，其中确定所述浅层的深度以包括一次反射波即浅一次波，但是不包括感兴趣的多次反射波即多次波的第一次到达；
(b)使用估计的地震源小波反演所述浅一次波以产生影响地震波的传播的物理性质浅模型，然后利用(c)-(e)中的装置同时优化所述浅模型和所述估计的地震源小波的装置；
(c)利用所反演的浅模型和所述估计的地震源小波，计算机模拟所述多次波的装置；
(d)比较所模拟的多次波和所述地震数据中的对应多次波并且调整所述估计的地震源小波来降低失配的装置；
(e)重复(b)-(d)中装置的功能至少一次，或者直到所述失配降低到低于预定水平或满足其他停止条件的装置；以及
(f)输出同时优化的地震源小波和浅模型的装置。
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| EP2691794A4 (en) | 2015-12-23 |
| SG193233A1 (en) | 2013-10-30 |
| CN103460074A (zh) | 2013-12-18 |
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| US8990053B2 (en) | 2015-03-24 |
| CA2825469A1 (en) | 2012-10-04 |
| CA2825469C (en) | 2017-06-13 |
| WO2012134609A1 (en) | 2012-10-04 |
| US20120253758A1 (en) | 2012-10-04 |
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