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复杂介质高斯束偏移成像方法研究
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摘要
作为对地下介质进行精确成像的重要手段,叠前深度偏移自上世纪90年代兴起以来,在油气勘探的过程中发挥着越来越重要的作用。然而,对于一般的叠前深度偏移方法而言,成像精度和计算效率往往难以兼得的,例如,逆时偏移虽然具有很高的成像精度,但是计算效率低下,而计算效率很高的Kirchhoff偏移成像精度则较差。高斯束叠前深度偏移是一种兼具计算效率、成像精度以及灵活性的成像方法,其独特的优势使之具有很高的应用前景和研究价值。本文之所以进行复杂介质高斯束偏移成像方法的研究,一方面为了扩展其应用范围,使之更好的应用于当前地震勘探的成像处理之中,另一方面为了突出其优势,使之更加的实用化。
     本文进一步发展了现有的高斯束偏移方法。主要包括以下几个方面:(1)依据统一的理论思路,推导了适用于不同道集叠前数据的高斯束偏移公式,并通过数值试算对公式的正确性进行验证;(2)提出了一种适用于复杂地表条件的保幅高斯束偏移方法,该方法直接在起伏地表进行局部平面波的分解,不但具有更高的近地表成像精度,还可以得到近似反映地下反射系数随角度变化的保幅的成像结果;(3)提出了一种多分量叠前地震资料成像方法—弹性波高斯束偏移,该方法利用纵、横波的速度,将多分量地震记录分解为不同波型、不同方向的局部平面波,并且利用弹性动力学高斯束进行延拓成像。该方法可以直接在波场延拓的过程中对耦合的矢量波场进行解耦,无需波场分离便可以得到纵、横波的成像结果。
     共成像点道集是叠前偏移过程中重要的输出结果,其对速度模型修正更新以及AVO/AVA岩性分析都有着重要的意义。本文对高斯束偏移过程中不同类型共成像点道集的提取进行研究,给出了ODCIGs、ADCIGs以及PWDCIGs的提取方法,并以ADCIGs为重点进行了讨论。由于高斯束偏移的过程中包含了传播角度的信息,因而可以直接利用此信息进行ADCIGs的提取,无需复杂的映射转换过程。本文给出了三维方位角/反射角域,以及多分量反射角域共成像点道集的提取方法,并通过ADCIGs的提取试验对上述方法正确性和有效性进行了验证。
     在提高程序计算效率方面,本文给出了Hill所提出的高效算法,对其基本原理和应用效果进行了详细的分析,并在编程计算过程中设计使用的一系列优化算法,例如偏移孔径的选取,最近点的优化搜索以及粗网格递归算法的应用等。初始宽度、参考频率以及成像角度范围等参数是决定高斯束偏移成像效果以及计算效率的重要因素,本文对上述参数的作用及特点进行分析,并给出了优化的参数选取准则。
As an important approach to accurately image the subsurface, pre-stack depth migration(PSDM) is playing a more and more important role during the process of oil and gas exploration since 90th last centry. However, the conventional PSDM can’t compromise imaging accuracy and computational efficiency. For example, reverse-time migration is very accurate but with low efficiency, on the contrary, Kirchhoff migration is very efficient but with low accuracy. Gaussian beam migration(GBM) is an imaging method with computational efficiency, imaging accuracy and flexibility, this unique advantage offer it high research value and broad applicate prospect. In this doctoral dissertation, i take a study on GBM methods in complex medium with two purpose, one is to intensify its advantage in order to make it more practical, the other is to extend its range of application so as to be well applied in oil and gas exploration.
     In this dissertation, i futherly develop the existing GBM methods, including the following several aspects: (1). With an unique approach, i derive GBM formulas suitable for different seismic data gather, and verify those validitiy with numerical tests. (2). I present an amplitude-preserved GBM method which can be used in complex surface conditions. By decompose seismic data into local plane-waves directly from the rugged surface, this method not only have better imaging quality especially the near surface part, but also get an amplitude preserved image which could measure angle-dependent reflection coefficients. (3). I present pre-stack elastic GBM which images the multi-component seismic data. With the P and S wave velocity, this method decompose multi-component data into local plane-waves with different initial wavemode and different direction, and downward-continue and image local plane-waves using elastic Gaussian beams. Due to decoupling the coupled elastic wavefield during the downward-continuation process ,this method can get P and S wave image without wavefield separation.
     Common Image Gathers(CIGs) are important outputs during the process of PSDM, it can be used to refine velocity field and provide AVO/AVA informations. In this dissertation, i study CIGs of GBM, and present ways to extract ODCIGs, ADCIGs and PWDCIGs. Because GBM naturely have ray angle imformations, it can directly extract ADCIGs without complicate mapping process. I present methods to calculate 2D/3D reflection angle, 3D reflction azimuth angle and reflection angle of converted wave, then verify the exactness of those method with extraction tests of ADCIGs.
     Parameters such as initial half-width, reference frequency and imaging angle range are important factors which control the imaging quality and computational efficiency of GBM. I analysis the effects and characters of those parameters, and give optimized seletion criterions. Concerning the aspects of efficiency enhancement, i give high effiective algorithm presented by Hill(1990), analysis its fundamental principle and use a series of optimized algorithms during programming.
引文
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