珠江口盆地边缘洼陷油气勘探潜力以西江36洼为例

何金海, 彭光荣, 吴静, 李振升, 蔡国富, 汪晓萌, 杜晓东, 赵超, 石创, 朱定伟

何金海,彭光荣,吴静,等. 珠江口盆地边缘洼陷油气勘探潜力−以西江36洼为例[J]. 海洋地质与第四纪地质,2022,42(4): 146-158. DOI: 10.16562/j.cnki.0256-1492.2022041401
引用本文: 何金海,彭光荣,吴静,等. 珠江口盆地边缘洼陷油气勘探潜力−以西江36洼为例[J]. 海洋地质与第四纪地质,2022,42(4): 146-158. DOI: 10.16562/j.cnki.0256-1492.2022041401
HE Jinhai,PENG Guangrong,WU Jing,et al. Exploration potential of marginal sags in the Pearl River Mouth Basin: An example from the Xijiang 36 Sag[J]. Marine Geology & Quaternary Geology,2022,42(4):146-158. DOI: 10.16562/j.cnki.0256-1492.2022041401
Citation: HE Jinhai,PENG Guangrong,WU Jing,et al. Exploration potential of marginal sags in the Pearl River Mouth Basin: An example from the Xijiang 36 Sag[J]. Marine Geology & Quaternary Geology,2022,42(4):146-158. DOI: 10.16562/j.cnki.0256-1492.2022041401

珠江口盆地边缘洼陷油气勘探潜力——以西江36洼为例

基金项目: 中海油重大生产科研项目“珠江口盆地(东部)浅水区古近系油气成藏条件及勘探突破方向”(SCKY-2020-SZ-21)
详细信息
    作者简介:

    何金海(1984—),男,硕士,工程师,主要从事石油地质综合研究,E-mail:hejh15@cnooc.com.cn

  • 中图分类号: P736

Exploration potential of marginal sags in the Pearl River Mouth Basin: An example from the Xijiang 36 Sag

  • 摘要: 近几年的研究与勘探实践表明,部分边缘洼陷同样具备较好的油气成藏条件与勘探潜力。南海北部珠江口盆地发育大量低勘探程度的边缘洼陷,系统梳理这些洼陷的结构、构造演化和成藏条件具有重要实践意义。本文以珠江口盆地边缘洼陷西江36洼为例,基于重处理三维地震、测井和地球化学等资料,开展洼陷结构演化研究、原型盆地恢复、地震相对比和油气运移分析,系统梳理了西江36洼的洼陷结构、烃源潜力和成藏特征。研究表明:① 西江36洼受NE向断层控制,为“南断北超”的箕状断陷湖盆;② 西江36洼发育一定规模的中深湖相烃源岩且已经成熟,具备较好烃源条件;③ 受区域泥岩盖层和油源断层断距的影响,西江36洼具有深层古近系近源成藏的特征,宜围绕古近系构造、地层和岩性圈闭勘探。该研究认识有助于推动西江36洼的勘探进程,并为其他边缘洼陷的油气勘探提供借鉴。
    Abstract: Research and exploration in recent years show that some marginal sags also hold good hydrocarbon accumulation conditions and exploration potential. The Pearl River Mouth Basin, northern South China Sea, have many marginal sags in low exploration degree, and it is of great significance to systematically sort out the structure, tectonic evolution, and accumulation conditions of these marginal sags. Taking the Xijiang 36 Sag as an example, we analyzed the tectonic evolution, prototype basin restoration, seismic facies comparison, and oil and gas migration using 3D seismic, well logging, and geochemistry data, based on which the structure, hydrocarbon source potential, and accumulation characteristics of the Xijiang 36 Sag were systematically researched. Results show that (1) Xijiang 36 Sag was a half-graben rift lake basin controlled by an NE-striking fault in the south and structural overlapping in the north; (2) Xijiang 36 Sag holds a certain scale of medium-deep lacustrine facies source rock, and is mature with good hydrocarbon accumulation conditions; (3) affected by the regional mudstone caprock and the fault throw of the source fault, Xijiang 36 Sag was characterized by deep Paleogene near-source accumulation. Therefore, we suggest the Paleogene structure, stratigraphy, and lithologic trap are the main target for further exploration. This research helps to promote the exploration process of the Xijiang 36 Sag and provides a reference for oil and gas exploration in other marginal sags in the Pearl River Mouth Basin.
  • 地震绕射波是地下构造细节和异常的反映,地下构造的不连续点会产生绕射波,如裂缝、断层、溶洞和地层尖灭等。在原始地震勘探数据中,既存在绕射波也存在反射波,反射波是地质背景的综合反映,绕射波则是地质细节的小构造的反映。相对反射波而言,绕射波的能量往往很弱,甚至难以识别,导致绕射信息常常被高能量的反射信息所覆盖,而绕射波信息是提高地震勘探分辨率的重要信息载体。在地震资料处理解释中,正确识别断层、尖灭和小尺寸散射体等地质不连续性是一个重要问题,绕射波包含有关产生绕射波的介质结构和组成的有价值信息。然而,在标准地震资料处理中,绕射波常被视为噪声而被抑制[1-3]。把绕射波从原始地震勘探记录中分离出来进行单独成像,可以加强小型地震异常体的成像,从而提高复杂断块的地震成像精度。

    在过去的几十年,许多地球物理学者对地震绕射波分离方法做了相关研究。1988年Kanasewich和Phadke[4]提出了一种适用于共偏移距道集的绕射波走时曲线直接拾取绕射波的方法来分离绕射波。1992年Claerbout[5]首次提出了平面波预测滤波器的概念,并在信噪分离方面得到了很好的应用。Fomel[6]进一步完善了平面波预测滤波器,并提出了平面预测滤波器的残差可以作为绕射波的近似。Nowak等[7]根据反射波和绕射波同相轴的几何差异,采用加权双曲Radon滤波器分离地震绕射波。Berkovitch等[8]利用绕射波多次聚焦叠加剖面将绕射波聚焦到绕射点位置,同时将反射波反聚焦到整个道集记录,从而分离绕射波。Koren和Ravve[9]提出了方位相关反射波属性,通过构建加权叠加滤波器将绕射波和反射波分离。Klokov等[10]根据角度域共成像点道集中反射波和绕射波的差异,首先压制去除反射顶点附近反射能量,然后利用混合Radon变换去除剩余反射波能量,进而分离出绕射波。Moser和Howard[11]提出基于深度域的反射聚焦,从叠前数据中过滤反射进而对绕射波分离成像的方法。Decker等[12]使用人工模拟数据和从皮森盆地获得的野外实际数据进行绕射波分离,评估解决绕射特征的多种方法,证明平面波预测滤波器方法能使图像保存更多绕射能量和较少的迁移伪影,但不足是无法消除斜率不连续的反射变量。上述绕射波分离算法主要是利用了绕射波和反射波在不同地震数据道集中的差异,通过数学变换或者信号预测的方法将绕射波识别和分离出来。在国内研究方面,赵娟娟等[13]利用F-K滤波方法分离成像绕射波,通过F-K域斜率滤波去除反射波从而分离出绕射波信息。马永生[14]从油藏中具有代表性的地质模型出发,分析VSP中绕射波的基本特点,理论上总结了绕射波运动学的部分认识规律。黄建平等[15]着重介绍了平面波预测滤波器及其在叠前域、叠后域分离并成像绕射波的方法原理,探讨了绕射波分离成像方法的应用前景和改进方向。朱生旺[16]提出一种局部倾角滤波和预测反演联合起来分离绕射波的方法。蒋波等[17]提出一种基于反射波层拉平的绕射波分离与成像方法用于碳酸盐岩缝洞储集体地质目标,提高对溶洞、裂缝等特殊异常体的刻画精度。李正伟等[18]根据倾角域共成像点道集中菲涅耳带变化特点,通过倾角-偏移距道集中精确切除菲涅耳带的方法来分离绕射波。本文在平面波分解绕射波分离[6]基础上,分析了绕射波与反射波信号特征的差异,深入研究了平面波预测的绕射波分离方法的影响因素,并探讨了噪声和平面波预测滤波器平滑参数对地震绕射波分离结果的影响,为在实际地震数据处理中应用平面波分解方法进行绕射波分离提供了理论指导。

    地震记录既含有反射波同相轴也含有绕射波同相轴,在点震源激发时,反射波和绕射波波形在炮记录中都是双曲线,不易于分离反射波和绕射波。在平面波震源激发时,来自反射界面的反射波是平面波,而来自绕射体的绕射波是双曲线。因此,在平面波震源条件下反射波和绕射波具有明显的几何差异,更有利于绕射波分离。在实际地震勘探中大都是点源激发,反射波和绕射波的同相轴不易区分,但我们根据爆炸反射面理论将共偏移距剖面近似为平面波震源获得的地震记录,这样绕射波和反射波有较好的几何差异,根据其几何差异进行绕射波分离。

    平面波预测滤波器利用未知的局部倾角构造最优非稳态预测误差滤波器,根据相邻地震道的数据,在局部倾角平滑变化约束下,使预测误差最小化以此预测目标道数据。通过最优化方法不断迭代可获得局部倾角场,倾角场能够反映反射波场几何信息。

    局部平面波的微分方程表示为[6]

    $$\frac{{\partial P}}{{\partial {{x}}}} + \sigma \frac{{\partial P}}{{\partial t}} = 0$$ (1)

    其中,$P\left( {t,x} \right)$是波场,$x$$t$分别是炮检距和旅行时,$\sigma $是局部倾角,是$x$$t$的函数,局部倾角是旅行时对炮检距的导数。

    Fomel给出了Z变换域平面波预测的形式[6]

    $${\hat P_{x + 1}}\left( {{Z_t}} \right) = {\hat P_x}\left( {{Z_t}} \right)\frac{{B\left( {{Z_t}} \right)}}{{B\left( {{\rm{1/}}{Z_t}} \right)}}$$ (2)

    式中,${{\hat P}_x}\left( {{Z_t}} \right)$是相应记录道的Z变换形式,$B\left( {{Z_t}} \right){\rm{/}}B\left( {{\rm{1/}}{Z_t}} \right)$等价于全通数字滤波器。用Taylor级数展开拟合得到${B\left( {{Z_t}} \right)}$五阶中心滤波器:

    $$ \begin{split} {B_5}\left( {{Z_t}} \right) =& \frac{{(1 - \sigma )(2 - \sigma )(3 - \sigma )(4 - \sigma )}}{{1\;680}}Z_t^{ - 2} + \\ &{\frac{{(4 - \sigma )(2 - \sigma )(3 - \sigma )(4 + \sigma )}}{{420}}Z_t^{ - 1} + }\\ &{\frac{{(4 - \sigma )(3 - \sigma )(3 + \sigma )(4 + \sigma )}}{{280}} + }\\ &{\frac{{(4 - \sigma )(2 + \sigma )(3 + \sigma )(4 + \sigma )}}{{420}}{Z_t} + }\\ &{\frac{{(1 + \sigma )(2 + \sigma )(3 + \sigma )(4 + \sigma )}}{{1\;680}}Z_t^2} \end{split} $$ (3)

    利用平面波预测滤波器预测分离绕射波的过程中,关键一步是反射波同相轴局部倾角的估计。如果局部倾角已知的情况下,可以用$C\left( \sigma \right)$表示地震数据与二维滤波器的褶积算子。因此,在最小平方意义下,可通过求解如下最小二乘目标函数估计局部倾角:

    $$C\left( \sigma \right)d \approx 0$$ (4)

    其中,$d$为已知的地震数据。优化问题(3)可以利用高斯—牛顿线性化迭代的方法求解:

    $$C'\left( {{\sigma _0}} \right)\Delta \sigma d + C\left( {{\sigma _0}} \right)d \approx 0$$ (5)

    式中,$\Delta \sigma $为倾角增量,${{\sigma _0}}$为初始倾角,$C\left( {{\sigma _0}} \right)$为对应初始倾角${{\sigma _0}}$估计的褶积算子。$C'\left( {{\sigma _0}} \right)$$C\left( {{\sigma _0}} \right)$的导数值。为了保证倾角场稳定可靠,在反演求解过程中引入正则化约束项,控制倾角场沿着空间和时间两个方向平滑。由于平面预测是针对平面波形的预测,而绕射波难于满足其预测方程,因此一旦估计出了倾角场,将倾角参数代入预测方程(4),预测的残差就是绕射波的近似。

    图1给出了平面波预测绕射波分离算法的流程图。在平面波预测绕射波分离方法中,倾角场估计的正则化平滑参数是一个重要的参数,它控制着倾角的空间平滑性,从而约束着预测的范围。同时,实际地震勘探中噪声的存在也会影响倾角的估计和绕射波的分离,因此需要对噪声和正则化参数进行深入的分析讨论。

    图  1  绕射波分离算法流程图
    Figure  1.  A flowchart for separation of diffraction wave

    以地震勘探中被广泛采用的Sigsbee 2A模型为例对绕射波分离算法的影响因素进行分析。在绕射波分离的过程中,倾角场预测结果对绕射波分解效果影响较大,而噪声和平面波预测平滑参数均对倾角场的估计产生影响。图2-4中,在目标数据中增添了不同方差的均值为0的正态分布随机噪音,给出了不同噪声水平下的倾角场估计结果和绕射波分离结果。随着噪音水平的增大,原始数据共偏移距地震数据变得复杂,估计的倾角场准确性降低,尤其在低信噪比情况下倾角场估计的误差变大,但是高信噪情况下倾角场估计的结果较好,尽管在原始数据中可以观察到噪声,但估计的倾角几乎和没有噪声数据估计的倾角一致,其主要原因是正则化平滑技术约束了倾角场的平滑性,提高估计的稳定性和可靠性。在高信噪比情况下,尽管倾角场估计比较准确,但是绕射波的分离仍然受到了噪声影响,其原因为在平面波预测中我们只把可预测的平面波提取出来,而噪声也被留在了残差中,而残差正是绕射波的估计,因此在分离的绕射波中含有噪声。噪声水平越强,分离的绕射波效果越差,在低信噪比条件下,倾角场的估计也变差,绕射波分离结果几乎被淹没在噪声和假象下,无法得到较好的绕射波信息。由于噪声会降低倾角场估计的精度,同时噪声也会影响分离算法的效果,因此,在利用平面波预测法进行绕射波分离时,必须要先压制随机噪音,从而提高分离结果的精度。

    图  2  不含噪声地震数据的倾角场估计和绕射波分离
    a. 原始含有绕射波的数据,b. 估计的倾角场,c. 分离的绕射波。
    Figure  2.  The dip field estimation and diffraction separation of seismic data without noise
    a. The original data containing diffraction wave, b. estimated dip field, c. separated diffraction wave.
    图  3  高信噪比地震数据的倾角场估计和绕射波分离(噪声方差为0.001)
    a.原始含有绕射波的数据,b.估计的倾角场,c.分离的绕射波。
    Figure  3.  The dip field estimation and diffraction separation of high SNR seismic data(noise variance is 0.001)
    a. The original data containing diffraction wave, b. estimated dip field, c. separated diffraction wave.
    图  4  低信噪比地震数据的倾角估计和绕射波分离(噪声方差为0.025)
    a.原始含有绕射波的数据,b.估计的倾角场,c.分离的绕射波。
    Figure  4.  The dip estimation and diffraction separation of low SNR seismic data(noise variance is 0.025)
    a. The original data containing diffraction wave, b. estimated dip field, c. separated diffraction wave.

    倾角估计问题属于反问题范畴,存在多解性和不适定性,为了解决这一问题,需要采用正则化技术对估计的局部倾角场进行约束。在反问题正则化中光滑半径参数控制着正则化程度,下面讨论在倾角估计过程中,沿着水平方向平滑和沿垂直方向平滑半径大小对倾角预测和绕射波分离结果的影响。图5显示了不同平滑半径下倾角估计和绕射波分离的结果。随着水平或垂直方向光滑半径的不断增大,倾角估计值的范围越来越小,倾角估计的结果在水平或垂直方向上越来越平滑,随着光滑半径的进一步增大,理论上当光滑半径趋于无穷大时,倾角估计结果也会趋于与坐标轴平行。从对应的绕射波分离结果来看,随着光滑半径的增大,倾角估计值变小,绕射波分离结果显得越来越干净,信噪比明显提高。具体原因有两方面:一是大的光滑半径将部分噪音平滑掉了,减少了噪音对分离结果的干扰;二是大的光滑半径将小的绕射波忽略了,这样大尺度的绕射波就显得很干净。光滑半径太小会使倾角估计的范围大于理论值,使绕射波分离结果中出现许多全波场中没有的小尺度绕射波,使得绕射波分离结果信噪比降低,利用这些小尺度绕射波偏移成像后可能出现许多小尺度地质构造体假象,即造成偏移噪音和偏移假象[19]

    图  5  不同平滑半径对倾角估计及绕射分离结果的影响
    a-b是光滑半径为3的结果,c-d是光滑半径为10的结果,e-f是光滑半径为50的结果。
    Figure  5.  Influence of different smoothing radius on dip angle estimation and diffraction separation results.
    a-b is the result of smooth radius of 3, c-d is the result of smooth radius of 10, e-f is the result of smooth radius of 50.

    因此,在应用平面波预测进行倾角估计和绕射波分离时应选择合适的光滑半径。光滑半径较小时,算法对小型地质体的绕射波识别更敏感。光滑半径较大时,小尺度绕射波没有很好地分离出来,不利于小尺度地质体的识别与成像。但较大的光滑半径对大型的绕射波聚焦顶点的识别非常清晰。在处理实际数据时,应根据具体的研究目的对平滑参数做适当的调整。例如,识别的目标是地下小尺度构造体、小型缝洞时,可以选择较小的光滑半径;若研究的目标是大型裂缝、断层、不整合面以及地层缺失时,应当选择较大的光滑半径。

    为了说明平面波预测地震绕射波分离的效果,我们将其应用于一个模拟数据和两个实际数据绕射波分离中。图6a是一个模拟的共偏移距道集,可以清楚地看到绕射波和反射波互相干扰。图6b是预测出的倾角场,这里的光滑半径为5。图6c是经过分离后的结果,可以看出分离的绕射波中反射波同相轴几乎不存在,绕射波信息明显,该算例表明平面波预测滤波器可以很好地预测出反射波信息并对其进行压制。

    图  6  模拟的具有绕射波的共偏移距道集
    a.原始数据,b.预测倾角场,c.分离的绕射波。
    Figure  6.  The synthetic common offset gather with diffracted waves
    a. original data, b. prediction of dip field, c. separated diffracted waves.

    然后,我们将其应用于实际海洋地震勘探的共偏移距叠前道集(图7a),可以发现该数据绕射波非常发育,从叠前共偏移距道集上可以清楚看到一些绕射波,尤其是对于3.5 s处复杂断块引起的绕射波非常清楚,我们首先估计其局部倾角场(图7b),光滑半径确定为5。在反射波发育的地方,倾角场比较平滑且数值较小,而在绕射波发育的地方倾角较大,从分离的绕射波结果(图7c)可以看出平面波预测方法可以很好地分离绕射波,这些被分离出的绕射波可以很好地进行断块构造的成像[20]及储层表征[21]

    图  7  实际海洋地震数据的共偏移距道集
    a.原始数据,b.估计的倾角场,c.分离的绕射波。
    Figure  7.  The common offset gather of real marine seismic data
    a. original data, b. estimated dip field, c. separated diffracted waves.

    最后,我们对叠后的实际地震数据进行绕射波分离(图8a),由于叠加会破坏一些绕射波的信息,因此在叠后的剖面上绕射波能量较弱,但是叠后的剖面信噪比较高,对估计倾角场比较有利。图8b为估计的局部倾角场信息,由于叠加对绕射波的压制,同时因为该数据剖面上的绕射波分布散乱,为了得到正确的倾角,此处的横向光滑半径为50,纵向光滑半径为20,图8c显示了叠后地震数据绕射波分离后的结果,可以发现绕射波很好地被分离出来。模拟和实际数据表明平面波预测方法可以有效分离绕射波。

    图  8  实际地震数据叠加剖面
    a.原始数据,b.估计的局部倾角,c.分离的绕射波。
    Figure  8.  The field poststack seismic section
    a. original data, b. estimated local dip field, c. separated diffraction wave.

    平面波预测滤波器在反射波同相轴光滑连续的条件下,可以有效地估计地震数据的局部倾角场,进而分离出绕射波,该方法对隐藏在强反射能量下的小型绕射波信息起到很好的分离效果,为后期绕射波单独成像提供绕射波信息。通过对噪声和平滑参数对地震绕射波分离结果的影响分析,发现噪声水平严重影响绕射波分离效果,噪音过大分离结果会不准确;平面波预测滤波器光滑半径偏小会引入噪音和假象,光滑半径偏大会导致绕射波分离不彻底,小断块地震绕射波响应难以分离。在绕射波分离算法中,振幅保真性也是一个重要问题,因此提高算法的抗噪性和保真性是今后研究的重要方向。

  • 图  1   西江36洼位置图(a)和基底地形图(b)[14]

    Figure  1.   Tectonic sitting (a) of the Xijiang 36 Sag and the submarine geomorphology of the sediment basement (b)

    图  2   珠一坳陷综合柱状图[12]

    Figure  2.   Comprehensive geological column of the Zhu Ⅰ Depression

    图  3   过番禺4洼–西江36洼地震剖面

    剖面位置见图1。

    Figure  3.   An arbitrary seismic line along the Panyu 4–Xijiang 36 Sag

    See Figure 1 for the cross-sectional location.

    图  4   番禺4–西江36洼T80(文昌组顶面)沿层相干切片(a)与断层平面展布对比图(b)

    Figure  4.   Coherent slice along the T80 (top of Wenchang Formation) horizon (a) and the plane distribution of faults (b)

    图  5   过番禺4和西江36洼地震剖面

    剖面位置见图4b。

    Figure  5.   Seismic sections across the Panyu 4 and Xijiang 36 Sag

    See Figure 4b for the cross-sectional location.

    图  6   番禺4洼–西江36洼古近系构造恢复剖面

    剖面位置见图1b。

    Figure  6.   The Paleogene structure restoration of the Panyu 4–Xijiang 36 Sag

    See Figure 1b for the cross-sectional location.

    图  7   番禺4洼–西江36洼古近纪断层活动特征

    取样点位置见图4b。a. F1断层下文昌组(Tg-T83)沉积期断距-距离曲线图,b. F1断层上文昌组(T83-T80)沉积期断距-距离曲线图,c. F4断层古近纪活动速率,d. F5断层古近纪活动速率。

    Figure  7.   Characteristics of the Paleogene fault activity in the Panyu 4-Xijiang 36 Sag

    See Figure 4b for the location of the sampling point. a. the fault-distance curve of the Wenchang Formation (Tg-T83) of the F1 fault during the depositional period, b. the fault distance-distance curve of the F1 fault Wenchang Formation (T83-T80) during the depositional period, c. the Paleogene activity rate of the F4 fault, d. the Paleogene activity rate of the F5 fault.

    图  8   番禺4洼–西江36洼文昌组沉积厚度

    Figure  8.   Sedimentary thickness of the Panyu 4–Xijiang 36 Sag

    图  9   地球化学指标对比

    a. J31井地球化学指标,b. P48井地球化学指标。

    Figure  9.   Comparison of geochemical indices

    a. geochemical indices of Well J31, b. geochemical indices of Well P48.

    图  10   番禺4洼–西江36洼T80(文昌组顶面)构造叠合油气运移流线图

    Figure  10.   Migration streamline and T80 (Top of Wenchang Formation) structure of the Panyu 4–Xijiang 36 Sag

    图  11   烃源岩地震相对比

    剖面位置见图1。

    Figure  11.   Comparison in seismic facies of source rocks

    See Figure 1 for the cross-sectional location.

    图  12   西江36洼文四段沉积相

    Figure  12.   Sedimentary facies in the Wen 4 Member of the Xijiang 36 Sag

    图  13   西江36洼烃源岩成熟度(约10 Ma)

    Figure  13.   The maturity of source rocks of the Xijiang 36 Sag (about 10 Ma)

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  • 期刊类型引用(2)

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    2. 彭光荣,郭婧,姜福杰,姜大朋,吴宇琦,陈兆明,宋泽章,高中亮,张宇琦. 珠江口盆地开平凹陷烃源岩地球化学特征与油源对比. 石油学报. 2023(10): 1624-1636 . 百度学术

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出版历程
  • 收稿日期:  2022-04-13
  • 修回日期:  2022-06-27
  • 录用日期:  2022-06-27
  • 网络出版日期:  2022-08-08
  • 刊出日期:  2022-08-27

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