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水合物是在低温高压条件下由水分子组成的笼状构架将小型气体分子吸附其中而形成的似冰状固态物质，主要分布于陆地永久冻土带和大陆边缘水深超过300 m的陆坡带（Kvenvolden，1993）。水合物因能源资源潜力、环境效应问题和对地质灾害影响，受到了世界各国的广泛关注（Collett，2002; Chong Zhengrong et al.，2016）。神狐海域是南海北部陆坡水合物勘探程度最高的区域。自2007年，广州海洋地质调查局（GMGS）在神狐海域深水区进行多次水合物钻探，获得大量的水合物样品，呈结核状、脉状、厚层状、薄层状和分散状等多种赋存形式（Wu Nengyou et al.，2008; Yang Shengxiong et al.，2017a; 杨胜雄等，2017b）。目前许多学者通过钻井取芯（Liu Changling et al.，2012，2015; Su Ming et al.，2016; Yang Shengxiong et al.，2017a; 杨胜雄等，2017b）、化学检测（Pang Lei et al.，2022）、标型矿物（侯元立等，2020）、温度异常（Sun Jiaxin et al.，2017; Wan Zhifeng et al.，2017）、地球物理（Liang Jinqiang et al.，2017; 张伟等，2017，2018; Zhang Wei et al.，2019，2020a，2020b，2021; Zhang Xudong et al.，2021）和数值模拟（Su Pibo et al.，2018; Fang Yunxin et al.，2019）等手段描述神狐海域水合物的资源远景、水合物样品产出特征和成藏机制（Wu Nengyou et al.，2008; 吴能友等，2009; Yu Xinghe et al.，2014; 苏明等，2015; Zhang Guangxue et al.，2015; Su Ming et al.，2017; Fu Chao et al.，2019；Su Ming et al.，2021）。上述研究指出，神狐海域新生代以来构造运动活跃，沉积速率较大，油气资源丰富，是形成水合物的有利地区。
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基于已有的水合物钻探与测井资料，获得了含水合物地层的物理性质，预测稳定带厚度和水合物饱和度等（Wang Xiujuan et al.，2011a，2011b，2012，2014a，2014b; Qian Jin et al.，2018）。但由于钻探覆盖的区域与深度有限，不利于水合物分布范围和资源评价的进一步研究（Zhang Wei et al.，2020a）。神狐海域的地震勘探研究提供了水合物的空间分布信息，推测了水合物的饱和度与可能的天然气运移通道，在地震剖面上发现了大量的BSR甚至双BSR，指示了水合物稳定带的底界（徐华宁等，2014; Wang Xiujuan et al.，2014a，2014b，2016; Liu Jie et al.，2017; Su Ming et al.，2017; 张伟等，2017，2018; Wang Jiliang et al.，2018; Zhang Wei et al.，2020a，2020b；Wang Xiujuan et al.，2022）。地震AVO反演技术也用于预测神狐海域水合物和游离气体分布（Yang Rui et al.，2015; Zhang Wei et al.，2021; Qian Jin et al.，2022）。然而，仅利用BSR不能给出水合物的顶界信息，而地震勘探因横向分辨率较低且波速对游离气过度敏感的特征，不利于分析游离气运移通道。
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海洋可控源电磁方法（MCSEM）作为海洋电磁法的一个分支，具有浅层分辨率髙、高阻异常识别能力强的优势 （Schwalenberg et al.，2022），经过多年发展，已成为一种有效的地球物理探测手段。鉴于含水合物地层比围岩具有更高的电阻率，海洋可控源电磁法能够对水合物稳定带进行电性结构成像，尤其对高阻体的顶界埋深与横向边界刻画得尤为准确，是地震探测水合物的有效补充手段（Weitemeyer et al.，2006，2010，2011，2017; Constable et al.，2007; Goto et al.，2009; Hsu Shukun et al.，2014; Goswami et al.，2015，2016，2017；Attias et al.，2016，2018；Schwalenberg et al.，2017，2020；Gehrmann et al.，2019; Jing Jianen et al.，2019; Johansen et al.，2019）。因此，两者相结合可以有效地减少单一地球物理方法的多解性，从而显著提高勘探精度（MacGregor et al.，2012）。
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本文在神狐海域布设一条MCSEM测线，进行水合物调查研究，采集了15个测站的人工源电磁数据，对这批数据进行处理和反演，获得观测剖面的二维（2D）电阻率结构图像。结合SH-W07-2016钻孔测井资料和2D地震反射剖面，解释研究区水合物和游离气的分布及地质构造对气源运移的控制作用。
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1 地质与地球物理研究背景
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1.1 地质背景
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神狐海域位于南海北部陆坡区中段神狐暗沙东南海域（图1a），隶属于珠江口盆地珠二凹陷（Wan Zhifeng et al.，2017）。海底受浊积岩侵蚀作用影响，从西到东发育17条近南北向的海底峡谷（Ding Weiwei et al.，2013；图1c），形成一系列水道-堤坝系统（Qiao Shaohua et al.，2015; Li Xishuang et al.，2016）。
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珠江口盆地（PRMB）位于南海北部大陆架，是在中生代活动大陆边缘基底构造基础上发育的中、新生代盆地（Li Pinglu et al.，1994）。PRMB的结构演化可分为两个阶段:始新世—渐新世裂谷和新近纪—第四纪裂谷后热沉降阶段（Ru Ke et al.，1986; Sun Zhen et al.，2009）。古新世—早渐新世形成箕状或地堑状断陷，沉积了古新统神狐组、始新统文昌组及下渐新统恩平组陆相地层（米立军等，2008）。自晚渐新世以来，PRMB逐渐过渡到凹陷阶段，沉积了上渐新统珠海组、中中新统珠江组、韩江组、上中新统粤海组、万山组和第四纪地层（图2；Li Pinglu et al.，1994; Xie Hui et al.，2014）。已发现的水合物大多储集在晚中新世—第四纪地层中（Liang Jin et al.，2022）。
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始新统文昌组中深层湖泊泥岩和下渐新统恩平组煤层（图2）和海洋-大陆过渡泥岩已被证实是主要的成熟—高成熟烃源岩，上渐新统珠海组深埋的泥岩是该地区另一组成熟的烃源岩（Gao Gang et al.，2015; Li Yajun et al.，2016）。浅部地层如中新统粤海组、上新统万山组，具有厚度大、有机质丰富的特点，有利于产生大量的微生物气（He Min et al.，2017）。构造运动诱发古近系厚层超压泥页岩塑性流动，形成了规模巨大的底辟活动带，造成泥底辟和气烟囱异常发育（Sun Yunbao et al.，2012; Cheng Cong et al.，2020），为神狐海域水合物的形成提供了气源运移通道（吴能友等，2009; Chen Duanxin et al.，2013; Yang Rui et al.，2015; Su Ming et al.，2017; 张伟等，2017，2018; Zhang Wei et al.，2020a，2020b）。此外，神狐海域海底温度2~4℃，地温梯度44~67℃/km，海底承受的水深压力大于10 MPa，满足水合物成藏的有利温度及压力条件（张伟等，2018）。
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1.2 地球物理研究与水合物稳定带
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2016年，中国地质调查局广州海洋地质调查局（GMGS）在南海神狐海域进行了2D地震勘探与第四次水合物钻探（GMGS4）（图1b、d；Yang Shengxiong et al.，2017a; Zhang Wei et al.，2020a）。根据获取的高分辨率地震资料（图3a）、SH-W07-2016站点的深钻取芯资料和随钻测井数据（Yang Shengxiong et al.，2017a），Zhang Wei et al.（2020a）对水道-堤防系统的地质地球物理特征进行了研究，并表征了沉积物的岩性和物理性质及其与水合物储层关系。SH-W07-2016站点位于海底山脊的高点，水深为914 m，实际钻探的海底深度为188 mbsf（meter of bottom of seafloor）。随钻测井数据在122~153 mbsf之间存在明显的电阻率、波速和密度异常，基于压力岩芯脱气计算的水合物饱和度在39%~62%（Yang Shengxiong et al.，2017a）。
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图1 珠江口盆地海底地形与海洋可控源电磁剖面位置
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Fig.1 Geographical map of the Pearl River Mouth basin (PRMB) and MCSEM sites
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（a）—珠江口盆地中北部神狐海域位置（据Su Ming et al.，2018修改）;（b）—白云凹陷构造简图;（c）—神狐海域海底地形图（据Ding Weiwei et al.，2013修改）;（d）—海洋可控源电磁测点、地震测线与SH-W07-2016钻探井位位置（据 Zhang Wei et al.，2020a修改）
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(a) —the location of the Shenhu area in the northern central PRMB (after Su Ming et al., 2018) ; (b) —schematic tectonic structure of the Baiyun sag; (c) —the seafloor topography of the Shenhu area (after Ding Weiwei et al., 2013) ; (d) —the location of the MCSEM sites (red dots) , seismic lines and the SH-W07-2016 drilling (modified after Zhang Wei et al., 2020a)
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在SH-W07-2016站点附近，地震剖面显示了两个明显的似海底反射（BSR）。上部BSR1深度为154 mbsf（以下均为距离海底的深度），下部的BSR2深度为259 mbsf （图3b；Zhang Wei et al.，2020a）。BSR1与海底山脊地形近似平行，呈现“背斜”特征，它的上方存在一个凸起的强振幅反射，可能代表了水合物顶界面分布。在BSR1和BSR2之间存在地震空白反射，并且在空白反射两侧出现强振幅反射（ERs）。这些强反射下方出现了大范围的明显弱反射异常，这可能与深部天然气沿着泥底辟或气烟囱向浅层的运移与聚集有关（Zhang Wei et al.，2020a）。
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水合物稳定带（GHSZ）是由天然气水合物、水和气体组成的三相热力学平衡区。水合物相平衡曲线计算结果表明结构I（SI）型（100%CH4）水合物稳定带底部为154 mbsf，这与从地震剖面解释的BSR1非常吻合（Zhang Wei et al.，2020a）。因此，BSR1代表了SH-W07-2016站点GHSZ的底界。Zhang Wei et al.（2020a）使用99%C1+0.5%C2+0.5%C3和98%C1+1%C2+1%C3计算了结构II（SII）型水合物的GHSZ分别为199 mbsf和231 mbsf，这与BSR2深度不匹配，表明BSR2的成因可能与含C2+烃的热成因气无关。
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图2 珠江口盆地白云凹陷地层与构造框架（据Zhang Wei et al.，2019）
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Fig.2 Stratigraphic and tectonic framework of the Baiyun sag in the PRMB (after Zhang Wei et al., 2019)
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2 电磁数据采集与反演
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2.1 数据采集
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海底介质的电性参数（如电阻率等）较之其他物性参数能更好地反映岩性、组分、孔隙度、水合物饱和度的横向变化。为了进一步提高神狐海域水合物的勘探精度，研究团队搭乘海洋四号调查船完成了一条NW-SE向的海洋可控源电磁剖面（图1d）。该剖面长7.0 km，设计15个接收站位，站间距平均为500 m。本研究中使用的电磁发射机和接收机由中国地质大学（北京）研制 （Chen Kai et al.，2015; Wang Meng et al.，2015）。电磁接收机按照设定的坐标进行投放，当沉至海底后利用多点声学斜距测量技术确定水下接收机的相对位置，并参考调查船的GPS坐标得到了每台接收机在海底的实际地理坐标。拖曳发射结束后，所投放的电磁接收机100%回收，获得了15个测站的人工源电磁场时间序列数据。
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图4为MCSEM观测剖面（图1d）中部RH测站采集的电磁场数据时频谱图。可以看到，在4∶48前后 RH测站接收到了人工激发的8 Hz电磁场信号。从原始数据中抽取一段电场的时间序列数据，绘制了电场时间序列曲线图（图5），由图可以看到，人工源电场呈光滑的正弦曲线，数据质量较高。
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2.2 数据处理
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在海洋可控源电磁数据预处理中，Myer et al.（2011）介绍了基于快速傅里叶变换（FFT）的数据处理方法，笔者据此建立了海洋可控源电磁数据处理流程（图6），并编写了数据处理可视化软件（王铭等，2016；赵文强等，2021）。
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首先通过FFT计算电磁场时间序列的傅立叶谱，以获得电磁场的振幅和相位。在频率域中，通过标定获得了采集电路的频率响应函数，利用这个标定信息对经过FFT后的电场幅值与相位进行校正，得到实际的电场数据。利用相同的方法计算电流数据的幅度和相位，然后对电磁场数据进行电偶矩的归一化处理，最后得到电场的MVO（振幅随偏移距变化）与PVO（相位随偏移距变化）曲线。图7给出了RH站位电场的MVO曲线，可以看到，电场归一化曲线的最小值可达到10-15 V/Am2。
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图3 神狐海域过水合物钻探井SH-W07-2016的地震剖面（据Zhang Wei et al.2020a修改）
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Fig.3 Seismic data crossing gas hydrate site SH-W07-2016 in Shenhu area (modified from Zhang Wei et al., 2020a)
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地震剖面位置见图1d；ERs—增强地震反射
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Location of the seismic profile is shown in Fig.1d; ERs—enhanced reflections
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图4 RH测站电场时间序列的时频图
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Fig.4 Time frequency variation diagram of electric field time series at RH site
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（a）—Ex分量时频谱;（b）—Ey分量时频谱
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(a) —Ex component; (b) —Ey component
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图5 RH测点电场时间序列片段
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Fig.5 Time series section of electrical field at RH site
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（a）—Ex分量;（b）—Ey分量
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(a) —Ex component; (b) —Ey component
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在计算得到两个水平电场分量Ex、Ey后，又对极化椭圆参数进行了分析，得到了电场极化椭圆的主轴分量（Pmax）。这个分量是最大的电场幅值分量，它受随机噪声的影响小，且对几何位置和发射方位变化不敏感（景建恩等，2018; Jing Jianen et al.，2019; Liu Chenggong et al.，2023）。
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本文采用上述方法对15个站位的可控源电磁数据进行处理，获得8 Hz的Pmax分量的MVO数据（图8），并利用这些数据进行后续的反演研究。
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图6 海洋可控源电磁数据处理流程图
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Fig.6 Flow chart of data processing for marine controlled-source electromagnetic method
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图7 RH测站电场的MVO曲线
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Fig.7 MVO curve of electric field at RH site
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2.3 二维反演
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最初，MCSEM数据以视电阻率拟断面的形式显示电阻率的横向变化（Weitemeyer et al.，2006）。二维MCSEM正反演建模程序（MARE2DEM）使我们能够详细查看MCSEM剖面的二维电阻率结构（Key，2016）。为了对电阻率结构进行成像，利用MARE2DEM对上述Pmax分量的MVO数据进行反演，获得各向同性电阻率模型。
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MARE2DEM的反演基于Occam算法（Constable et al.，1987）。它通过寻找将数据拟合到给定容差的最简单或最平滑的模型来解决正则化反演问题。利用Occam算法对实测海洋可控源电磁数据进行2D反演，能够得到光滑的地电模型并保留模型的主要特征，避免产生虚假电阻率异常。
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为了进行反演，首先需要建立海底电阻率初始模型。根据工区海水深度、海底地形和海水电阻率分层结构，建立图9所示的电阻率初始模型。在海平面以上，设置一个厚度为100 km的空气层，并设定了1012Ω·m的恒定电阻率。为了获得海底电阻率的最佳分辨率，在反演中需要确定海水电阻率分层结构（Key，2009）。这里，海水层电阻率分层数据根据电导率-温度-盐度（CTD）测量确定，并在后期反演中设定为固定参数。
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在海底以下，根据海底地形变化建立带地形的初始电阻率模型。海床的初始电阻率为1.0 Ω·m。为了减少网格数量和节省计算时间，每个子区域填充不同边长的三角形网格。紧邻海底的浅层区域三角形边长为30 m，较深区域的三角形边长分别为60 m和100 m。
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反演中，为8 Hz的观测电场Pmax数据设置10%的噪声基底。经过13次迭代后，最终电阻率模型趋于稳定，均方根误差（root mean square，RMS）为1.96。图8a、b 显示了最后的拟合结果和归一化残差，可以看到，模型响应与实际数据拟合较好。由图10可以看到， RMS已经基本稳定，表明反演收敛。
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2.4 灵敏度分析
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灵敏度分析是检查反演模型可靠性有效手段之一。灵敏度或雅可比矩阵是数据相对于模型参数的偏导数（Farquharson et al.，1996），可用于确定模型参数对数据是否敏感（Schwalenberg et al.，2002; Goswami et al.，2016; Weitemeyer et al.，2017）。这里给出了对应于发射机剖面的较大区域的反演模型（图11），图中叠加了观测数据对模型参数的敏感性等值线（白色实线与数字）。在海底，根据发射机覆盖区域所对应的灵敏度值为0.6，确定在接收机剖面正下方灵敏度大于0.6的区域为可有效探测的区域。
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3 反演结果
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电阻率模型的灵敏度分析表明，MCSEM反演结果的探测深度可以达到600 mbsf。根据钻孔和地震BSR的结果，神狐海域水合物大多储存在100~300 mbsf深度（吴能友等，2009; Su Ming et al.，2016）。这里给出了0.8~2.25 km深度的电阻率图像（图12）。为了更好地解释电阻率模型，本文搜集了SH-W07-2016水合物钻井数据以及过井的反射地震剖面（Yang Shengxiong et al.，2017a; Zhang Wei et al.，2020a）。其中，SH-W07-2016井位对应MCSEM的RM测点位置。将电阻率剖面和地震剖面叠加（图13），有助于更好地理解电阻率异常与BSR以及地震空白反射的关系。
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图8 神狐海域MCSEM各测点8 Hz的电场Pmax拟合曲线和拟合残差
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Fig.8 Pmax fitting curve and residual of electric field at 8 Hz for each MCSEM measurement point in Shenhu area
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（a）—观测电场 Pmax 数据（开环）和最终反演模型响应（实线）;（b）—归一化残差
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(a) —observation of electric field Pmax data (open loop) and final inversion model response (solid line) ; (b) —normalized residual
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图9 MCSEM二维反演的电阻率R初始模型
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Fig.9 Initial resistivity (R) model for two-dimensional inversion of MCSEM
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图10 二维反演的均方根误差曲线
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Fig.10 RMS misfit distribution of the 2D inversion
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如图13所示，在海底150 mbsf之上，地层电阻率主要表现为低阻特征，电阻率为1~2 Ω·m。在RA—RB、RC、RH—RI、RK、RL、RM等电磁测站下方存在多个高阻异常体（H1~H6），电阻率值约为2~5 Ω·m。SH-W07-2016井的LWD数据显示在122~153 mbsf之间存在明显的电阻率和声波波速异常（图14；Yang Shengxiong et al.，2017a；Zhang Wei et al.，2020a）。横跨水合物钻探点地震剖面（图3）在海底以下约150 mbsf深度附近存在明显的BSR（图3b中BSR1）。BSR1具有强振幅、连续性好、振幅空白带较明显、近似平行海底特征（Zhang Wei et al.，2020a）。在BSR1之上，GHSZ中的高电阻率异常体（图13中H5、H6尤为明显）都对应了明显的地震空白带，并且其下方均存在弱反射和不连续的地震反射事件。
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在海底150~260 mbsf（主要位于地震剖面的T1之上，T1为晚中新世与上新世的界面），地层以中—低电阻率特征为主，局部出现带状高阻异常体C1~C4，电阻率值为3~5 Ω·m。通过这些高阻异常带，浅层BSR1（海底150 mbsf）之上的高阻体（H1~H4）与下方地层中的高电阻率异常体（G1~G4）相连通。此外，在BSR1正下方观察到地震模糊反射，并且在该模糊区的两侧出现高振幅反射，表明BSR1下方地层中存在游离气的聚集（Zhang Wei et al.，2020a）。
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在海底BSR2之下的260~600 mbsf深度，海底地层主要表现为中—高电阻率特征，电阻率为3~10 Ω·m。在此层中，研究区主要存在5处高电阻率异常体G1~G5，电阻率异常体在横向上呈不连续的分块特征，并对应着地震反射剖面的同相轴错断（主要位于T1分界面下方），表明相应地层中裂隙或断层较为发育（图13中黑色虚线）。另外，G1~G5在整个剖面上电阻率较高，其顶界面恰好位于增强地震反射（ERs）之下，显示电阻率反演结果与地震剖面具有较好的对应关系。
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图11 电场Pmax数据二维反演的电阻率模型和灵敏度（蓝色方框为核心研究区）
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Fig.11 Sensitivity of resistivity model and model parameters for two-dimensional inversion of electric field Pmax data (blue box for core research area)
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图12 神狐海域海洋可控源电磁二维反演电阻率模型
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Fig.12 Two-dimensional resistivity model by electromagnetic inversion in the Shenhu area
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图13 神狐海域海洋可控源电磁二维电阻率与地震叠加剖面
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Fig.13 Electromagnetic 2D resistivity and seismic stacking profile in the Shenhu area
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T1和T2为地震推断的地层界面（详见图2）；黑色虚线为地震数据推断的断层
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T1 and T2 are the stratigraphic interfaces inferred from seismic data (see Fig.2 for details) , and the black dashed lines represent the faults inferred from seismic data
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4 讨论
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4.1 水合物与游离气分布
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水合物的形成改变了沉积物的物理性质，最容易观察到的变化是电阻率的增加（Wang Xiujuan et al.，2011a）。来自SH-W07-2016站点的测井数据表明电阻率在122~153 mbsf之间有非常明显的高阻异常（图14），实际的水合物取芯证实研究区含水合物储层厚度约为31 m（Yang Shengxiong et al.，2017a；Zhang Wei et al.，2020a）。对应SH-W07-2016井的MCSEM反演结果见图14中的电阻率-MCSEM曲线。在120 mbsf之下，电阻率由2 Ω·m逐渐升高到4 Ω·m，指示了水合物的存在；另外，在SH-W07-2016井的水合物层之下MCSEM反演的电阻率随深度进一步升高（图13中C1、G1），表明水合物层之下可能还存在高阻含气层。然而，受分辨率的限制，MCSEM数据无法准确分辨出含气与含水合物地层的界限，需结合地震剖面的BSR进行讨论。
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图14 SH-W07-2016井随钻测井曲线与MCSEM反演的电阻率曲线
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Fig.14 Gas hydrate drilling area logging while drilling (LWD) of site SH-W07-2016 and resistivity curve obtained from MCSEM inversion
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地震相表明，研究区GHSZ具有明显的双BSR特征（Zhang Wei et al.，2020a）。 BSR2具有横向不连续分布的特征，深度为260 mbsf，且在BSR2下方也存在类似BSR1下方的模糊反射。Song Yingrui et al.（2022）利用天然气水合物的温度和压力相平衡方程计算GHSZ，并重建神狐海域8.2 Ma以来GHSZ的演变，结果表明SH-W07-2016站点BSR2是GHSZ的早期水合物分解后的残余古BSR。另外，增强地震反射（ERs）是解释游离气运移与水合物形成的主要指示之一（Zhang Wei et al.，2020a）。高阻异常G1~G3的顶界对应着地震剖面的ERs，并在其上方残存了BSR2，推测高电阻率异常体G1~G4是BSR2之下的含气储层，而结合地震剖面，推断高电阻率异常体G5为BSR1下部的游离气储层。
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结合地震剖面的BSR位置和电阻率反演结果推断，图13 中高电阻率异常体H1~H6位于BSR1之上的水合物稳定带内，推测它们与地层含水合物有关。高电阻率异常体G1~G5位于水合物稳定带之下，对应的地层中断层、裂隙发育，可能为上部水合物的形成提供了天然气源与运移通道。而C1~C4位于BSR1与BSR2之间，可能为BSR1之上水合物的形成提供了天然气运移通道。
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4.2 水合物储层结构
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基于对二维、三维地震资料的解释，科学家利用多种气体运移通道来解释神狐海域水合物分布的不均匀性，例如垂向运移（包括大型断层、气烟囱和泥底辟；Zhang Wei et al.，2020a，2020b）、水平扩散（Su Ming et al.，2017）。这些气体运移途径的不同，导致神狐海域水合物分布的差异。就本文研究的电磁剖面，根据地震结果（图13），游离气主要以断层、气烟囱的垂向运移为主。
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根据地震与电阻率模型特征，将电磁剖面划分为两个主要区段（图13）。第一个区段位于RO—RF测点之间，海底存在双BSR结构，储层呈三层结构形式。双BSR可能是由于峡谷脊部沉积和局部强流体渗漏导致的BSR上移形成的，气源分析水合物为I型水合物（周吉林等，2022）。早期游离气沿裂隙与断裂向上运移形成BSR2；随着峡谷脊部沉积的加厚和含气热液流体的活动，改变了早期的温压条件，引起BSR向上迁移，形成BSR1。BSR2之上的水合物部分分解与深部气一起向上运移，最后在BSR1之上重新形成水合物（Zhang Wei et al.，2020a）。BSR2之下的增强地震反射，对深部天然气起到圈闭作用，形成高阻异常G1~G4所对应的含气构造。BSR1与BSR2之间的地层中可能为水合物与游离气共存状态，形成了C1~C4异常。地层中水合物与游离气共存现象在琼东南盆地的水合物钻探中得到了证实（Ye Jianliang et al.，2019）。
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第二个区段位于RD与RA测点之间。与第一区段不同，这里为一明显的海底滑坡带，形成多条滑动断层（图13）。海底滑坡、侵蚀作用在一定程度上破坏了BSR2，使早期形成的水合物分解并向海底逃逸。随着后期沉积加厚，水合物稳定带底界向下调整，在深处气源供给的条件下，重新形成水合物。储层呈两层结构形式，上层是H5、H6所对应的水合物层，下层是G5对应的含游离气圈闭构造。
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5 结论
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在南海神狐海域进行了天然气水合物的海洋可控源电磁调查，采集了15个海底站位的人工源电磁场数据。通过数据处理与反演，获得了高质量的海底电阻率二维结构图像。灵敏度分析表明8 Hz的海洋可控源电磁数据的探测深度可达到600 mbsf。SH-W07-2016水合物钻井数据验证了高电阻率异常H1的可靠性。尽管电阻率模型的纵向分辨率较地震剖面低，但是电阻率异常与地震反射异常特征较为吻合，进一步表明电阻率反演结果是可靠的，能为研究区水合物与游离气分布研究提供重要的电性信息。
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结合地震解释结果，将电阻率模型分为两个主要区段。两个区段的电性特征存在一定的差异，可能代表两个区段的储层结构存在差异。第一区段高阻体G1~G4较第二区段G5的顶界面埋深大，推断第一区段以BSR1和BSR2为界，海底储层为三层结构，自上而下分别为含水合物层、水合物与游离气共存层和含气构造层；第二区段海底储层为两层结构，以G5的顶为界线分为上部含水合物层和下部的含气构造层。研究表明，断层、裂隙为游离气向上运移提供了通道，峡谷脊部沉积、海底滑坡侵蚀作用影响了海底水合物的储层结构。
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摘要
地震剖面的似海底反射（BSR）指示了天然气水合物的底边界，并已得到钻探的验证。南海神狐海域是天然气水合物（简称水合物）研究的热点区域。然而，由于地质构造的复杂性且钻井数量有限，仅仅依靠地震与钻探研究不能完全描述区内天然气水合物及气源通道的分布。含水合物地层比围岩具有更高的电阻率，海洋可控源电磁（MCSEM）数据获得的电阻率能为水合物和气源通道检测提供重要依据。本文在神狐海域开展MCSEM探测研究，沿一条测线采集了15个站位的海洋可控源电磁场数据，通过数据处理与二维反演，实现了研究区海底二维电阻率成像。然后，通过灵敏度分析，检验了MCSEM反演结果的可靠性。结合SH-W07-2016随钻测井（LWD）和地震数据，对二维电阻率剖面进行解释，推断了剖面上水合物和游离气分布，划分了两种形式的水合物储层结构，分析了其构造成因。
Abstract
The presence of a bottom simulating reflector (BSR) on seismic profiles serves as a reliable indicator of the lower boundary of natural gas hydrate accumulations, a phenomenon that has been confirmed by drilling data. The Shenhu area in the South China Sea is a prominent region for natural gas hydrate (referred to as “hydrates”) research. However, the complex geological structures andlimited spatial coverage of drilling sites pose significant challenges to comprehensively characterizing hydrate distribution and associated gas source channels through seismic and drilling data alone.The distinct electrical resistivity contrast between hydrate-bearing formations and surrounding rocks presents a unique opportunity for geophysical exploration. Marine controlled-source electromagnetic (MCSEM) data,which effectively captures this resistivity contrast, provides a valuable toolfor detecting both hydrates and gas source channels.This study presents the findings of MCSEM exploration research conducted in the Shenhu area. Electromagnetic field data were collected at 15 discrete sites along a designated survey line. Subsequent data processing and two-dimensional inversion yielded two-dimensional resistivity images of the seabed. The reliability of the MCSEM inversion results was rigorously evaluated through sensitivity analysis. By integrating logging-while-drilling (LWD) data from the SH-W07-2016 well and seismic data, the two-dimensional resistivity profile was interpreted to infer the distribution of hydrates and free gas along the profile. Two distinct forms of hydrate reservoir structures were identified, and their structural origins were subsequently analyzed.
