Identification of hard-thin layers on the seabed or shallow sediments using geophysical data: A case study in the Liwan pipeline route, northern South China Sea
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摘要: 由沉溺珊瑚礁、各类胶结砂以及胶结的珊瑚石或贝壳碎屑等组成的硬质薄层通常呈零散状分布,地质取样难以准确确定它们是如何分布的,这给海底管线施工带来极大的困难和风险。本文以南海北部为例,基于多种物探资料并结合正演模拟,分析、总结了海底以及海底之下硬质薄层的声学特征,在研究区综合识别出23个硬质薄层分布区。研究认为,硬质薄层与松散沉积物物理性质的差异可用于声学探测数据识别和定位。在浅地层剖面上,硬质薄层表现为强反射薄层,并对其下方地层的地震反射信号有一定的屏蔽作用,这一现象有助于确定硬质薄层是否存在以及其埋深和位置。在侧扫声呐影像和后向散射强度图上,硬质薄层通常表现为具有不规则形状的明暗变化阴影,阴影的边界指示了硬质薄层的分布范围。当硬质薄层出露于海底时,侧扫影像、反向散射强度结合浅地层剖面可以有效地识别并确定硬质薄层的范围;而当硬质薄层位于海床浅部(埋深数米到十几米)时,浅地层剖面可能是识别硬质薄层的唯一且最有效的方法。Abstract: The hard-thin layers (HTLs) are usually composed of submerged coral reefs, various cemented sands, cemented coral stones or shell fragments and their locations are difficult to be determined by geological sampling due to their sporadic distribution. They bring great challenges and risks to the construction of submarine pipelines. In this paper, taking the northern shelf of the South China Sea as an example, we summarized the acoustic characteristics of the HTLs on the seabed and in the shallow sediments based on a variety of high-resolution geophysical data combined with forward simulation analysis. Twenty-three areas with HTLs in the study area were determined. Our study suggests that differences in the physical properties of HTLs and loose sediments help identify and locate them using high-resolution geophysical data. On the sub-bottom profiles, the HTLs are characterized by reflective interfaces with high-amplitude, beneath of which the low-amplitude reflections usually occur. These reflection features help to determine the HTLs, their depths and locations. The HTLs usually display the alternating light and dark zones with irregular boundaries on the side scan sonar and backscatter intensity images. When the HTLs are located on the seafloor, the comprehensive interpretation of the side-scan images, backscatter intensity images and the sub-bottom profiles is effective to identify and locate them. For those THLs several meters to ten meters below the seafloor, high-resolution sub-bottom profiles may be the only and most effective way to identify and locate them.
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1. 引言
在南海北部发育的海底地貌中,硬质海床是一种比较典型的地貌类型,主要包括珊瑚礁、各类胶结砂以及胶结的珊瑚石或贝壳碎屑等组成的厚度较薄的土层[1]。此外,在海底之下数米的土层中,也存在类似的以胶结的珊瑚碎片为主的薄层[2]。对于上述位于不同深度的各类胶结砂或胶结珊瑚碎片或贝壳等组成的硬质土层,本文统一称之为“硬质薄层(Hard-thin Layers, HTLs)”。在物理性质上,硬质薄层与其上下方的松散土层具有较大的差异,往往表现出硬度高、密度大等特点[3]。在南海北部,硬度大且分布极具不确定性的硬质薄层对海上工程施工,比如海底光缆、油气管道铺设等带来极大困难。硬质薄层可能导致海底挖沟二次作业,造成重大经济损失和工期延误,甚至可能导致相关设备的损害[4]。因此,如何快速而有效地识别并确定硬质薄层的位置、分析评估其危害性成为海上工程地质勘察中迫切需要解决的问题。然而,迄今有关讨论海床浅表层硬质层的文献不多。吴海京和年永吉[1]基于侧扫声呐影像讨论了不同类型硬质海底的声学特征;徐梓辰等[5]讨论了基于钻头振动数据识别硬质地层的方法。
本文以南海北部荔湾管线路由区为例,基于浅地层剖面、侧扫声呐影像以及多波束后向散射强度等声学资料,分析并讨论了海床浅表层硬质薄层的声学识别特征,总结了海底以及埋藏于海底之下硬质薄层的声学识别方法。研究结果对于利用工程物探资料快速而有效地识别硬质薄层有指导意义。
2. 荔湾管道路由区硬质薄层的物理特性
南海北部陆架区的海底重力取样与地质钻孔取样的土工测试数据显示,海底附近的硬质薄层主要由粉质黏土、砂质黏土/黏土质砂和砂粒、贝壳/珊瑚石碎屑等组成,厚度从几十厘米到数米不等。已有的研究显示,贝壳碎屑和珊瑚礁碎屑通常具有比正常陆架沉积物高的纵波声速和声衰减系数[6];而细颗粒的沉积物将贝壳以及大块珊瑚石“胶结”(图1),会增加沉积物的刚度,从而导致高的剪切波和压缩波速度,使得海床变硬,不利于挖沟作业。
3. 资料与方法
3.1 声学资料
研究中收集了南海北部荔湾管道路由区的工程物探资料,包括高分辨率浅地层剖面、侧扫声呐影像以及由多波束数据提取的后向散射数据,这些物探数据分布于宽度约为500 m的条带状区域(图2)。浅地层剖面的采集使用了KONGSBERG公司的TOPAS PS18浅地层剖面仪,采用CW模式发射脉冲信号。侧扫声呐资料采用Klein 3000侧扫声呐获得,数据采集过程中使用了双频率(100 kHz和500 kHz)。多波束后向散射数据由EM302获得的多波束原始数据中提取后经校正、网格化后生成,网格化间距为5 m×5 m。
图 2 研究中收集的工程物探资料分布a中灰色线表示侧扫声呐和多波束数据覆盖的条带状区域,黑色点表示有浅地层剖面数据的区域,其中一个区域进行了放大如bFigure 2. Track of geophysical data collected in the study areaGrey lines represent the narrow zone covered by side-scan sonar and multibeam data and black dots represent the areas with sub-bottom profiles in a. An area is enlarged as in b3.2 正演模拟
为更好地了解海底附近硬质薄层与正常沉积物在浅地层剖面上反射特征的差异,在研究中构建了两种简单的二维地层模型进行正演模拟。为方便计算,正演模型中地层/薄层厚度和子波频率做相应的缩放,薄层厚度/埋深放大20倍(放大后约为10 m),输入子波的频率则变为浅地层剖面主频的1/20,约为100 Hz。
4. 结果与讨论
4.1 硬质薄层的地震正演模拟
研究中使用两个二维平行介质模型来进行正演模拟,模型中的具体参数见表1,两组模型及正演结果分别如图3和图4所示。
表 1 地震正演模型参数Table 1. Parameters in seismic forward models模型 I 模型 II 硬质薄层宽度 400 m 400 m 硬质薄层厚度 10 m 10 m 硬质薄层位置 海底以下10 m 出露海底5 m 图 3 模型I(a)及地震正演结果(b)模型I中不同介质(硬质薄层、海水、地层1和地层2)的密度取值相同,仅考虑速度差异而引起的波阻抗变化,硬质薄层纵波波速取3 000 m/s,海水波纵波波速取1 500 m/s,地层1纵波波速取 2 000 m/s,地层2纵波波速取2 500 m/sFigure 3. Model I (a) and seismic forward result (b)In model I, the density of medias (hard-thin layer, seawater, formation 1 and formation 2) are assumed to be same; therefore, impedances of the medias are determined by their sound velocities. Here, the sound velocity is taken as 3 000 m/s for the hard-thin layer, 1 500 m/s for seawater, 2 000 m/s for formation 1 and 2 500 m/s for formation 2图 4 模型II(a)及地震正演结果(b)模型II中不同介质(硬质薄层、海水、地层1和地层2)的密度取值相同,仅考虑速度差异而引起的波阻抗变化,硬质薄层纵波波速取3 000 m/s,海水波纵波波速取1 500 m/s,地层1纵波波速取 2 000m/s,地层2纵波波速取2 500 m/sFigure 4. Model II (a) and seismic forward result (b)In model II, the density of medias (hard-thin layer, seawater, formation 1 and formation 2) are assumed to be same; therefore, impedances of the medias are determined by their sound velocities. Here, the sound velocity is taken as 3 000 m/s for the hard-thin layer 1 500 m/s for seawater, 2 000 m/s for formation 1 and 2 500 m/s for formation 2在模型I中,硬质薄层位于海底以下10 m。正演得到的地震记录(图3)显示,硬质薄层处反射振幅较两侧沉积物强,硬质薄层两侧可见绕射现象,并且硬质薄层下方反射的受到“屏蔽”而变弱。上述地震反射特征出现的主要原因是,相对于周边的松散沉积物,硬质薄层具有较高的波阻抗(硬质薄层具有更大的密度和纵波波速),较多的反射波能量会在硬质薄层的上界面反射回去,只有部分能量能继续向下传播。在硬质薄层两侧与沉积物接触的边缘,可以视为弹性不连续的间断点,当地震波通过时会产生绕射现象[7]。
在模型II中,硬质薄层位于海床表面。正演得到的地震记录(图4)显示,较之两侧沉积物,硬质薄层具有较强的振幅,薄层两端仍可见绕射现象,但不如模型I中明显。薄层下方地层的反射振幅相对于模型I中更弱,表明当硬质薄层位于海床表面时对下方地层反射振幅影响更大。
4.2 浅地层剖面
荔湾浅水路由区的浅地层剖面上,海底之下数米至十几米范围内可以识别出4种典型的声学反射相(图5a至图5d):振幅较强的平行反射相、振幅较弱的平行反射相、无反射以及绕射。结合路由区已有的地质取样,上述反射相中平行反射通常代表了软质松散沉积物,无反射则通常与砂质沉积物相关;海底管线表现出明显的绕射。有一种反射特征值得注意,即强反射界面之下出现弱振幅平行反射,且弱反射的边界是直立的(图5d),这一反射特征可以与正演模型II得到的地震记录相对比,推测是位于海底且厚度不大的硬质薄层引起的。在陆架外缘(水深约为200 m)的部分浅地层剖面上(图5e),海底或者海底之下数米可见典型的绕射现象,绕射弧之间表现为强反射界面下紧跟着空白反射或弱反射,这种反射特征也与正演模型得到的结果相似。据文献[2]的研究,这种反射特征被解释为埋藏的薄层珊瑚礁,强反射指示了位于海底附近硬质薄层的位置和分布。
图 5 路由区典型声学反射相(a−d)以及陆架外缘的埋藏硬质薄层反射特征(e)a. 振幅较强的平行反射;b. 振幅较弱的平行反射及管线引起的绕射;c. 海底下方的无反射;d. 强反射海底下反射突然变弱现象Figure 5. Typical acoustic reflection facies (a−d) in the study area and the reflection configuration of the buried hard-thin layers at the outer edge of the shelf (e)a. Parallel reflections with high amplitude; b. parallel reflections with low amplitude and diffractions caused by the pipeline; c. no reflections beneath the seafloor; d. the phenomenon that amplitude of the reflections are abruptly lower beneath the seafloor which has high-amplitude reflections从硬质薄层物理性质和模拟结果来看,由胶结的珊瑚礁石组成的硬质薄层相对于松散沉积物而言波阻抗差异大,硬质薄层边界处绕射现象明显,这种类型的硬质薄层多出现于陆架外缘[2]。当硬质薄层是细颗粒沉积物和贝壳胶结而成时,其与正常沉积物的接触边界不像珊瑚礁那样明显,导致其边缘绕射现象不明显,但其相对较高的波阻抗仍然能够形成强反射界面并能够“阻挡”部分反射波能量向下透射,从而造成薄层下方反射振幅变弱。这种硬质薄层多见于陆架浅水区。
4.3 侧扫声呐影像
侧扫声呐技术在水下目标探测以及海底底质分类中有着广泛的应用[8-15]。侧扫声呐影像图可以清楚地显示出不同海底地貌类型的声学特征[10, 16-19]。浅水路由区发育的麻坑、沙波、沙纹等地貌在侧扫声呐影响上很容易识别出来(图6a,图6c):麻坑在平面上呈近圆形,内部为暗色阴影,边缘较亮;沙波和沙纹呈明显的明暗阴影交替;已铺设的海底管线在侧扫声呐影像上呈线状阴影(图6a至图6d)。此外,侧扫声呐影像图上还可以识别出边界呈不规则状、内部呈现明暗快速变化的区域,其特征与典型礁石的侧扫影像相似[20],分布呈零散状,面积大小不一(图6b,图6d)。考虑到沿路由区的取样以及浅地层剖面并未揭示基岩存在,上述影像特征可能指示了出露海底的硬质薄层。
4.4 多波束后向散射强度
多波束水深测量时记录的后向散射强度反映了海底的粗糙程度,其大小依赖于声波入射角、海底粗糙程度、沉积物类型、声学性质以及声波在水体中的传播状况,在海底沉积物类型分类中应用广泛[21-27]。由后向散射强度转化得到的灰度图可以较为直观地反映海底的粗糙程度,其灰度纹理以及其几何形态可以反映出海底底质类型的变化和地貌分区。当由细颗粒沉积物和贝壳/珊瑚礁碎块构成的硬质薄层出露海底时,由于硬质海底力学强度大,其形态受海流冲刷影响小,粗糙的表面通常表现出较大的后向散射强度。在路由浅水区,后向散射强度灰度图上至少显示出4种典型的影像特征(图7)。在这些影像特征中,有一种表现为颜色较深(灰度值较大,对应于后向散射强度大)且呈不规则几何形态,其形成与海底处的硬质薄层密切相关(图7c)。已铺设的海底管线则表现出与侧扫声呐影像图上类似的线性阴影特征(图7a,图7c和图7d)。
4.5 硬质薄层的综合物探数据验证及分布
由于物探资料解译具有多解性,不同物探资料的相互验证尤为必要,这种验证在物探资料的信噪比较低时更是必须的。很多研究案例显示,综合利用物探资料识别并确定海底目标是一个有效的手段[28-30]。我们将工程物探资料确定的硬质薄层区域与已通过地质取样确认或其他方式(如现场施工)确定的硬质薄层区域进行对比,其中位于管线附近的8个硬质薄层区高度吻合,这表明通过综合利用不同物探方法和资料可以较准确地确定硬质薄层是否存在以及其分布范围。图8展示了其中一个硬质薄层分布区的验证情况。在侧扫声呐影像图上,硬质薄层对应的位置表现为边界不清楚的亮斑(图8a);而在后向散射强度灰度图上(图8b),硬质薄层表现出较大的后向散射强度值,其不规则的边界比较清晰;而浅地层剖面上(图8c)硬质薄层处海底表现为强反射特征,海底下方沉积层的反射变弱至近乎空白,两侧具有直立边界,与周边松散沉积物展示的中等强度的平行反射相形成明显对比。
图 8 多种物探资料解释的硬质薄层a 为侧扫声呐影像,b 为后向散射强度,c 为浅地层剖面。a 和 b 中红色虚线圈定的区域为硬质薄层分布区;c 中带双箭头的白线为硬质薄层的分布区Figure 8. Comprehensive interpretation of hard-thin layers by geophysical dataa is sde-scan sonar image, b is backscattering intensity and c is sub-bottom profile. The area delineated by the red dotted lines is the distribution area of the hard-thin layers in a and b. The white lines with double arrows indicate the distribution of the hard-thin layers in c综合利用侧扫影像、多波束后向散射强度以及浅地层剖面,沿荔湾管线路由区共确定出23个规模较大的硬质薄层分布区(图9)。在这些区域中,大部分区域已得到证实(地质取样或现场工程施工的确认)。对上述23个区域的统计显示,路由区(500 m宽的条带)硬质薄层的分布面积约为5.6×105 m2,其中最小区域的面积约为600 m2,最大面积超过7×104 m2。
图 9 研究区内识别的硬质薄层的分布(埋藏深度小于5 m)b的位置见右上角a;c是b的局部放大,黑色区域为识别的硬质薄层分布区Figure 9. The location of hard-thin layers (buried depth is less than 5 m) identified in the study areaThe location of b is shown in a, and c is a partial enlargement of b. Black areas denote the distribution area of hard-thin layers identified by geophysical data5. 总结
本文以南海北部荔湾管线路由区为例,基于硬质薄层的物理性质开展了地震正演模拟以及工程物探资料的综合分析,得到了如下认识:
(1)硬质薄层的物理性质显示它们与周边沉积物相比具有较高波阻抗和强度,且容易形成粗糙的海底,因此可以基于声学探测数据(如浅地层剖面、侧扫声呐影像和后向散射强度)识别并确定它们的位置。
(2)在浅地层剖面上,平直的强反射界面及其对下方地层反射信号的“削弱”甚至屏蔽现象可以作为硬质薄层存在的指示,强反射的位置指示硬质薄层的埋深和分布。
(3)侧扫声呐影像和后向散射强度均能够很好地显示位于或出露于海底面的硬质薄层,都表现为具不规则形状的明暗阴影变化的特征,但后向散射强度图能更清楚地揭示硬质的分布边界。
(4)当硬质薄层位于海底时,综合侧扫影像、反向散射强度结合浅地层剖面可以有效地确定硬质层的存在及其分布范围;而当硬质层位于海床浅层部位(数米至十几米)时,浅地层剖面可能是目前唯一且有效方法。
致谢:感谢刘洋廷博士在正演方面给予的大力支持,也感谢审稿人在提高本文质量方面提出的富有建设性的建议和意见!
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图 2 研究中收集的工程物探资料分布
a中灰色线表示侧扫声呐和多波束数据覆盖的条带状区域,黑色点表示有浅地层剖面数据的区域,其中一个区域进行了放大如b
Fig. 2 Track of geophysical data collected in the study area
Grey lines represent the narrow zone covered by side-scan sonar and multibeam data and black dots represent the areas with sub-bottom profiles in a. An area is enlarged as in b
图 3 模型I(a)及地震正演结果(b)
模型I中不同介质(硬质薄层、海水、地层1和地层2)的密度取值相同,仅考虑速度差异而引起的波阻抗变化,硬质薄层纵波波速取3 000 m/s,海水波纵波波速取1 500 m/s,地层1纵波波速取 2 000 m/s,地层2纵波波速取2 500 m/s
Fig. 3 Model I (a) and seismic forward result (b)
In model I, the density of medias (hard-thin layer, seawater, formation 1 and formation 2) are assumed to be same; therefore, impedances of the medias are determined by their sound velocities. Here, the sound velocity is taken as 3 000 m/s for the hard-thin layer, 1 500 m/s for seawater, 2 000 m/s for formation 1 and 2 500 m/s for formation 2
图 4 模型II(a)及地震正演结果(b)
模型II中不同介质(硬质薄层、海水、地层1和地层2)的密度取值相同,仅考虑速度差异而引起的波阻抗变化,硬质薄层纵波波速取3 000 m/s,海水波纵波波速取1 500 m/s,地层1纵波波速取 2 000m/s,地层2纵波波速取2 500 m/s
Fig. 4 Model II (a) and seismic forward result (b)
In model II, the density of medias (hard-thin layer, seawater, formation 1 and formation 2) are assumed to be same; therefore, impedances of the medias are determined by their sound velocities. Here, the sound velocity is taken as 3 000 m/s for the hard-thin layer 1 500 m/s for seawater, 2 000 m/s for formation 1 and 2 500 m/s for formation 2
图 5 路由区典型声学反射相(a−d)以及陆架外缘的埋藏硬质薄层反射特征(e)
a. 振幅较强的平行反射;b. 振幅较弱的平行反射及管线引起的绕射;c. 海底下方的无反射;d. 强反射海底下反射突然变弱现象
Fig. 5 Typical acoustic reflection facies (a−d) in the study area and the reflection configuration of the buried hard-thin layers at the outer edge of the shelf (e)
a. Parallel reflections with high amplitude; b. parallel reflections with low amplitude and diffractions caused by the pipeline; c. no reflections beneath the seafloor; d. the phenomenon that amplitude of the reflections are abruptly lower beneath the seafloor which has high-amplitude reflections
图 8 多种物探资料解释的硬质薄层
a 为侧扫声呐影像,b 为后向散射强度,c 为浅地层剖面。a 和 b 中红色虚线圈定的区域为硬质薄层分布区;c 中带双箭头的白线为硬质薄层的分布区
Fig. 8 Comprehensive interpretation of hard-thin layers by geophysical data
a is sde-scan sonar image, b is backscattering intensity and c is sub-bottom profile. The area delineated by the red dotted lines is the distribution area of the hard-thin layers in a and b. The white lines with double arrows indicate the distribution of the hard-thin layers in c
图 9 研究区内识别的硬质薄层的分布(埋藏深度小于5 m)
b的位置见右上角a;c是b的局部放大,黑色区域为识别的硬质薄层分布区
Fig. 9 The location of hard-thin layers (buried depth is less than 5 m) identified in the study area
The location of b is shown in a, and c is a partial enlargement of b. Black areas denote the distribution area of hard-thin layers identified by geophysical data
表 1 地震正演模型参数
Tab. 1 Parameters in seismic forward models
模型 I 模型 II 硬质薄层宽度 400 m 400 m 硬质薄层厚度 10 m 10 m 硬质薄层位置 海底以下10 m 出露海底5 m -
[1] 吴海京, 年永吉. 南海东部几种典型海底地貌特征的研究与认识[J]. 地球物理学进展, 2017, 32(2): 919−926. doi: 10.6038/pg20170264Wu Haijing, Nian Yongji. Research and cognition for several typical seabed features in the eastern of the South China Sea[J]. Progress in Geophysics, 2017, 32(2): 919−926. doi: 10.6038/pg20170264 [2] Li Xishuang, Li Xinzhong, Zhao Qiang, et al. The occurrence, acoustic characteristics, and significance of submerged reefs on the continental shelf edge and upper slope, northern South China Sea[J]. Continental Shelf Research, 2015, 100: 11−24. doi: 10.1016/j.csr.2015.03.006 [3] 王琳. 乐东22-1/15-1油气管线路由区工程地质灾害研究[D]. 青岛: 中国海洋大学, 2007, 17-19.Wang Lin. Research on the hazards of engineering geology about the route of Ledong 22-1/15-1 proposed pipeline[D]. Qingdao: Ocean University of China, 2007: 17−19. [4] 陈岱新, 郝高建, 王涛, 等. 莺歌海中部区域硬质海底特征及其工程影响[J]. 海洋地质前沿, 2016, 32(9): 47−52, 63. doi: 10.16028/j.1009-2722.2016.09007Chen Daixin, Hao Gaojian, Wang Tao, et al. Characteristics of hard seafloor in central Yinggehai and its engineering significance[J]. Marine Geology Frontiers, 2016, 32(9): 47−52, 63. doi: 10.16028/j.1009-2722.2016.09007 [5] 徐梓辰, 金衍, 洪国斌, 等. 基于近钻头振动数据的海底硬质地层探测方法[J]. 船海工程, 2019, 48(4): 112−116. doi: 10.3963/j.issn.1671-7953.2019.04.025Xu Zichen, Jin Yan, Hong Guobin, et al. Detection method of seabed hard strata based on near-bit vibration data[J]. Ship & Ocean Engineering, 2019, 48(4): 112−116. doi: 10.3963/j.issn.1671-7953.2019.04.025 [6] Jackson D R, Richardson M D. High-Frequency Seafloor Acoustics[M]. New York: Springer, 2007: 131−142. [7] Berkovitch A, Belfer I, Hassin Y, et al. Diffraction imaging by multifocusing[J]. Geophysics, 2009, 74(6): WCA75−WCA81. doi: 10.1190/1.3198210 [8] Lee S H, Kim K H. Side-scan sonar characteristics and manganese nodule abundance in the clarion-clipperton fracture zones, NE equatorial Pacific[J]. Marine Georesources & Geotechnology, 2004, 22(1/2): 103−114. [9] 潘国富, 付晓明, 荀诤慷, 等. 侧扫声纳在海底光缆维护工程中的应用[J]. 工程地球物理学报, 2004, 1(5): 389−394. doi: 10.3969/j.issn.1672-7940.2004.05.001Pan Guofu, Fu Xiaoming, Xu Zhengkang, et al. Side scan sonar applications in undersea fiber-optic cable maintenance projects[J]. Chinese Journal of Engineering Geophysics, 2004, 1(5): 389−394. doi: 10.3969/j.issn.1672-7940.2004.05.001 [10] Collier J S, Humber S R. Time-lapse side-scan sonar imaging of bleached coral reefs: a case study from the Seychelles[J]. Remote Sensing of Environment, 2007, 108(4): 339−356. doi: 10.1016/j.rse.2006.11.029 [11] Kumagai H, Tsukioka S, Yamamoto H, et al. Hydrothermal plumes imaged by high-resolution side-scan sonar on a cruising AUV, Urashima[J]. Geochemistry, Geophysics, Geosystems, 2010, 11(12): Q12013. [12] Hogan K A, Dowdeswell J A, Mienert J, et al. New insights into slide processes and seafloor geology revealed by side-scan imagery of the massive Hinlopen slide, Arctic Ocean margin[J]. Geo-Marine Letters, 2013, 33(5): 325−343. doi: 10.1007/s00367-013-0330-6 [13] Bryant R S. Side scan sonar for hydrography-an evaluation by the Canadian hydrographic service[J]. The International Hydrographic Review, 2015, 52(1): 43−56. [14] Powers J, Brewer S K, Long J M, et al. Evaluating the use of side-scan sonar for detecting freshwater mussel beds in turbid river environments[J]. Hydrobiologia, 2015, 743(1): 127−137. doi: 10.1007/s10750-014-2017-z [15] 王晓, 王爱学, 蒋廷臣, 等. 侧扫声呐图像应用领域综述[J]. 测绘通报, 2019(1): 1−4. doi: 10.13474/j.cnki.11-2246.2019.0001Wang Xiao, Wang Aixue, Jiang Tingchen, et al. Review of application areas for side scan sonar image[J]. Bulletin of Surveying and Mapping, 2019(1): 1−4. doi: 10.13474/j.cnki.11-2246.2019.0001 [16] 周兴华, 姜小俊, 史永忠. 侧扫声纳和浅地层剖面仪在杭州湾海底管线检测中的应用[J]. 海洋测绘, 2007, 27(4): 64−67. doi: 10.3969/j.issn.1671-3044.2007.04.019Zhou Xinghua, Jiang Xiaojun, Shi Yongzhong. Application of side scan sonar and sub-bottom profile in the checking of submerged pipeline in Hangzhou Bay[J]. Hydrographic Surveying and Charting, 2007, 27(4): 64−67. doi: 10.3969/j.issn.1671-3044.2007.04.019 [17] 董庆亮, 欧阳永忠, 陈岳英, 等. 侧扫声纳和多波束测深系统组合探测海底目标[J]. 海洋测绘, 2009, 29(5): 51−53. doi: 10.3969/j.issn.1671-3044.2009.05.015Dong Qingliang, Ouyang Yongzhong, Chen Yueying, et al. Measuring bottom of sea target with side scan sonar and multibeam sounding system[J]. Hydrographic Surveying and Charting, 2009, 29(5): 51−53. doi: 10.3969/j.issn.1671-3044.2009.05.015 [18] 年永吉, 朱友生, 陈强, 等. 流花深水区块典型滑坡特征的研究与认识[J]. 地球物理学进展, 2014, 29(3): 1412−1417. doi: 10.6038/pg20140357Nian Yongji, Zhu Yousheng, Chen Qiang, et al. The research and cognition of typical submarine landslide characteristics of Liuhua deepwater block[J]. Progress in Geophysics, 2014, 29(3): 1412−1417. doi: 10.6038/pg20140357 [19] 卢胜周, 彭华, 马秀敏, 等. 侧扫声呐在琼州海峡跨海通道工程物探中的应用[J]. 地质论评, 2015, 61(S1): 89−90.Lu Shengzhou, Peng Hua, Ma Xiumin, et al. Application of side-scan sonar in geophysical prospecting of Qiongzhou Strait cross-sea channel engineering[J]. Geological Review, 2015, 61(S1): 89−90. [20] Degraer S, Moerkerke G, Rabaut M, et al. Very-high resolution side-scan sonar mapping of biogenic reefs of the tube-worm Lanice conchilega[J]. Remote Sensing of Environment, 2008, 112(8): 3323−3328. doi: 10.1016/j.rse.2007.12.012 [21] Clarke J E H, Mayer L A, Wells D E. Shallow-water imaging multibeam sonars: A new tool for investigating seafloor processes in the coastal zone and on the continental shelf[J]. Marine Geophysical Researches, 1996, 18(6): 607−629. doi: 10.1007/BF00313877 [22] Hewitt A, Salisbury R, Wilson J. Using multibeam echosounder backscatter to characterize seafloor features[J]. Sea Technology, 2010, 51(9): 10−13. [23] Brown C J, Todd B J, Kostylev V E, et al. Image-based classification of multibeam sonar backscatter data for objective surficial sediment mapping of Georges Bank, Canada[J]. Continental Shelf Research, 2011, 31(2): S110−S119. doi: 10.1016/j.csr.2010.02.009 [24] Hamilton L J, Parnum I. Acoustic seabed segmentation from direct statistical clustering of entire multibeam sonar backscatter curves[J]. Continental Shelf Research, 2011, 31(2): 138−148. doi: 10.1016/j.csr.2010.12.002 [25] Micallef A, Le Bas T P, Huvenne V A I, et al. A multi-method approach for benthic habitat mapping of shallow coastal areas with high-resolution multibeam data[J]. Continental Shelf Research, 2012, 39−40: 14−26. doi: 10.1016/j.csr.2012.03.008 [26] McGonigle C, Grabowski J H, Brown C J, et al. Detection of deep water benthic macroalgae using image-based classification techniques on multibeam backscatter at Cashes Ledge, Gulf of Maine, USA[J]. Estuarine, Coastal and Shelf Science, 2011, 91(1): 87−101. doi: 10.1016/j.ecss.2010.10.016 [27] Yang Yong, He Gaowen, Ma Jinfeng, et al. Acoustic quantitative analysis of ferromanganese nodules and cobalt-rich crusts distribution areas using EM122 multibeam backscatter data from deep-sea basin to seamount in western Pacific Ocean[J]. Deep-Sea Research Part I: Oceanographic Research Papers, 2020, 161: 103281. doi: 10.1016/j.dsr.2020.103281 [28] De Beukelaer S M, MacDonald I R, Guinnasso Jr N L, et al. Distinct side-scan sonar, RADARSAT SAR, and acoustic profiler signatures of gas and oil seeps on the Gulf of Mexico slope[J]. Geo-Marine Letters, 2003, 23(3/4): 177−186. [29] Lafferty B, Quinn R, Breen C. A side-scan sonar and high-resolution chirp sub-bottom profile study of the natural and anthropogenic sedimentary record of lower lough erne, northwestern Ireland[J]. Journal of Archaeological Science, 2006, 33(6): 756−766. doi: 10.1016/j.jas.2005.10.007 [30] Nakamura K, Toki T, Mochizuki N, et al. Discovery of a new hydrothermal vent based on an underwater, high-resolution geophysical survey[J]. Deep-Sea Research Part I: Oceanographic Research Papers, 2013, 74: 1−10. doi: 10.1016/j.dsr.2012.12.003 -