南海海底地形可视化分析及其地质意义

海底地形是海洋地质学、海洋地球物理学、物理海洋学和海洋生物学等研究的基础资料,是影响海洋要素分布的重要因素之一。可视化是地形数据解译的关键,它为揭示海底地形与其他海洋要素之间所蕴含的关系和规律提供了独到的方法。基于可视化工具Vertical Mapper,在MapInfo Professional中对南海海底地形信息进行了渲染图与三维可视化实现,并对地形进行了剖面分析,进而将可视化的南海海底地形信息与表层沉积物类型、流场等其他海洋要素信息进行叠加分析,由此探讨了表层沉积物类型的分布与地形、海洋动力条件等的空间相关性,说明海底地形的可视化对于海洋地质现象的解释具有重要的意义。     

浅层地震声学剖面的声地层学解释

浅层地震声学剖面测量是用声波探测水深和海底沉积物分层结构的技术方法,并采用声地层学方法来进行浅层地震声学剖面解释.通过对东海某区的剖面海底浅层沉积物有效地解释和研究,具有良好的应用前景.     

海底三维可视化技术及应用

海底地形地貌能表现海洋世界重要的空间信息,也是常规光学和电磁手段难以探测的水下区域。应用侧扫声纳技术可以反演海底地貌,同时多波束测深技术得到的水深数据重建数字水深模型,二者结合创建三维海底空间景观。利用海洋探测技术和三维可视化技术进行海底地形地貌三维仿真和分析,并对其应用进行探讨。     

渤海海底地貌特征和控制因素浅析

基于我国近海地形地貌调查项目获取的水深、侧扫声纳及浅层剖面数据,结合渤海海域历史资料和前人相关工作、研究成果,对渤海地貌类型和分布特征进行了描述。在一些重点区域通过最新调查资料和历史资料的对比,描述了地貌的变化趋势,在此基础上编绘了渤海海底地貌类型图,并从地质构造、海平面变化、河流和海流等水动力作用以及人类活动几个方面对影响渤海海底地貌发育的因素进行了讨论。     

台湾岛西南海域福尔摩沙海脊冷泉区地形地貌特征分析

利用水深数据和ROV近海底影像资料,对福尔摩沙海脊冷泉区的海底地形地貌和冷泉系统的海底表征进行了描述和分析,并讨论了二者之间的响应关系。结果表明,相对于船载多波束数据而言,近海底多波束测深系统所获得的数据能更高精度地反映冷泉区海底地形地貌特征,是研究冷泉系统不可或缺的基础资料。基于ROV近海底观测影像资料,福尔摩沙海脊冷泉系统整体表现为局部被化能自养生物群落覆盖并有流体喷口零星分布的巨大自生碳酸盐岩岩丘,海底表征主要包括形态各异的自生碳酸盐岩结壳或岩体、化能自养生物群落、流体喷口、还原性沉积物等几种形式。研究表明,福尔摩沙海脊冷泉区的地形地貌特征与冷泉系统海底表征具有良好的响应关系,并且该区的地形地貌特征主要受控于出露于海底的自生碳酸盐岩的形态特征及规模。首次揭示了福尔摩沙海脊冷泉区地形地貌特征与其海底表征之间的响应关系,以期为后续的冷泉研究提供必要的背景资料支持。     

基于浅地层剖面的海底浅表层沉积物物理性质参数反演技术研究

海底浅表层（小于1 m）沉积物的物理性质,如粒度、孔隙度、密度等是海洋沉积学研究和海洋工程地质分析的重要内容,目前主要基于有限的海底取样或原位测试获取这些沉积物的物理性质。浅地层剖面是基于声学信号（频率几千赫兹）在沉积物中的传播得到可反映沉积地层结构的数据,其中的一些声学参数,如海底反射系数、波阻抗等与沉积物物理性质密切相关。如何充分而有效地利用浅地层剖面资料,反演得到剖面覆盖区海底浅表层沉积物的物理性质参数,极具科学意义和应用价值,且基于声学属性反演沉积物物理性质是当前研究的热点。为此,本文基于渤海LD16-3CEPA至LD10-1PAPD路由段的浅地层剖面数据和海底表层沉积物的实测物理参数,利用Biot-Stoll模型建立研究区海底反射系数和沉积物物理性质之间的关系,并基于浅地层剖面数据计算得到的海底反射系数,反演了研究区海底浅表层沉积物的孔隙度、密度、平均粒径等物理性质参数。其中反演的孔隙度、密度、平均粒径与实测孔隙度、密度、平均粒径基本相符,偏差度基本都在20%的偏差范围内,表明该反演方法在该区的应用是可行的。     

冷泉气体渗漏过程海洋多电极电阻率法探测效果模拟分析

为分析评价一种新型海洋多电极电阻率法对海底沉积物中冷泉气体渗漏过程的探测能力,根据前人理论研究,结合具体实例构建沉积物中快速及慢速冷泉气体汇聚、渗漏、喷发阶段地电模型,模拟采用海洋多电极电阻率法进行探测,利用数值计算方法得到理论剖面图像,并和室内实验实测剖面图像进行对比分析。研究结果表明,在快速冷泉探测剖面图像中,含气层和渗漏通道会因冷泉气体扩散状态不同表现为不同的电阻率异常特征,但易于识别。在慢速冷泉探测剖面图像中,浅层沉积物中气体富集区呈明显的高阻异常区,随着气体渗漏异常区逐步消失。两种喷发过程形成的微地貌特征也可在探测图像中得到反映。海洋多电极电阻率法是一种可以图化描述沉积物中含气层、渗漏通道及气液界面空间分布位置的有效方法。     

菲律宾海深水环境下浅地层沉积特征分析

本文依托菲律宾海浅地层剖面资料,结合前人已发表的该区域样品资料和钻孔资料,对九州-帕劳海脊以及与海脊相邻的西菲律宾海盆和帕里西维拉海盆浅层沉积物特征进行了初步研究.研究认为海底以下浅层沉积物一般存在3个波阻抗界面,根据其反射特征划分为4个基本类型,并对剖面特征的成因进行了初步探讨,认为在沉积物的沉积过程中,沉积物供给、...     

海底松散沉积物声学性质原位测量实验研究

分析研究了国内外海底松散泥沙的声速和声衰减系数测量的研究现状,并据此研制了海底表层沉积物声速声衰减系数原位测量系统。利用原位测量系统分别在实验室和海滩对不同粒度的沉积物进行了测量分析,得到了不同粒度沉积物的声速和声衰减系数。数据分析表明,沉积物的声速和声衰减系数与沉积物的粒径有密切的关系,粒径越粗,声速越高,声衰减系数越大。通过沉积物声学性质研究,可以开发海底浅层沉积物声学性质原位测量技术,提高相关海洋调查的速度和效率。     

南海浅海海底沉积物的声衰减

报道了南海浅海海底沉积物的声衰减性质。给出了测量和计算海底沉积物声衰减的方法。分析讨论了不同频率下的声衰减以及与若干个海底沉积物物理参数的关系,结果表明,同一类型沉积物在高频段时的声衰减要比低频段的声衰减大;同一频段下粗颗粒沉积物的声衰减要比细颗粒的声衰减大;北部湾海底浅层沉积物声衰减在低频100kHz下为80~150dB/m,在高频1MHz下为150~360dB/m;海南岛南部外海海底浅层沉积物声衰减在低频下为66~160dB/m,在高频1MHz下为190~350dB/m;高频段的数据与台湾海峡北部海底表层沉积物声衰减测量分析数据比较接近,而低频段的数据与台湾海峡北部海底表层沉积物声衰减测量分析数据有较大的差别。     

基于水下自主航行器(AUV)的神狐峡谷谷底块体搬运沉积特征及其对深水峡谷物质输运过程的指示

海底峡谷是陆源物质向深海运移的重要通道。对于远离陆地的海底峡谷,通常认为浊流是物质搬运的主要营力。受限于探测精度和复杂作业环境影响,使用常规地球物理资料对深水海底峡谷尤其是对谷底沉积体的形态和结构特征的刻画不够精细。基于水下自主航行器(AUV,Autonomous Underwater Vehicle)采集的高分辨率多波束、旁扫声呐和浅地层剖面资料,对神狐峡谷群中的一条峡谷的谷底表面及部分浅部地层的沉积特征进行了分析。结果表明,峡谷谷底浅部地层并不像它平滑的表面那么简单,而是由大量内部杂乱弱反射、厚度在8.4 m及以下的块体搬运沉积体组成。峡谷中下游块体搬运沉积体大都沿峡谷走向整体呈条带状展布,不是直接来源于相邻的峡谷脊部。研究认为在特定沉积环境下(例如高海平面时期),陆坡限定性峡谷谷底的块体搬运沉积过程的重复进行是峡谷谷底物质输运的重要途径,与浊流共同雕刻了峡谷的地形地貌。基于AUV的地球物理探测技术将是研究海底浅表层沉积过程和保障海底工程施工的重要手段。     

南海北部陆坡东沙海域海底丘状体气体与水合物分布

海底丘状体在天然气水合物发育区是一种常见的微地貌,对丘状体的研究有助于理解海底流体渗漏模式以及水合物的赋存规律。本文研究南海北部陆坡东沙海域天然气水合物发育区海底丘状体的特征及其与水合物的关系。研究所用的数据包括准三维多道地震数据、多波束数据以及浅地层剖面数据。在多波束海底地形图上,丘状体表现为局部的正地形,直径大约为300 m,高出周围海底约50 m。浅地层剖面上存在明显的声空白以及同相轴下拉现象,指示了海底丘状体气体的分布以及流体运移的路径。丘状体周围明显的BSR表明局部区域可能发育有水合物,水合物钻探结果也证实了这一推测。三维多道地震剖面上,丘状体正下方存在空白反射区域,这与泥火山的地震反射特征类似。但空白反射区域内存在强振幅能量,而且丘状体正下方存在连续的反射层,这表明该丘状体并非泥火山成因。综合钻探结果以及三维地震成像结果,认为水合物形成过程引起的沉积物膨胀以及海底碳酸盐岩的沉淀是形成该丘状体的主要原因。     

Multi-angle backscatter classification and sub-bottom profiling for improved seafloor characterization

This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r²?>?0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.     

A framework to quantify uncertainties of seafloor backscatter from swath mapping echosounders

Multibeam echosounders (MBES) have become a widely used acoustic remote sensing tool to map and study the seafloor, providing co-located bathymetry and seafloor backscatter. Although the uncertainty associated with MBES-derived bathymetric data has been studied extensively, the question of backscatter uncertainty has been addressed only minimally and hinders the quantitative use of MBES seafloor backscatter. This paper explores approaches to identifying uncertainty sources associated with MBES-derived backscatter measurements. The major sources of uncertainty are catalogued and the magnitudes of their relative contributions to the backscatter uncertainty budget are evaluated. These major uncertainty sources include seafloor insonified area (1–3 dB), absorption coefficient (up to >?6 dB), random fluctuations in echo level (5.5 dB for a Rayleigh distribution), and sonar calibration (device dependent). The magnitudes of these uncertainty sources vary based on how these effects are compensated for during data acquisition and processing. Various cases (no compensation, partial compensation and full compensation) for seafloor insonified area, transmission losses and random fluctuations were modeled to estimate their uncertainties in different scenarios. Uncertainty related to the seafloor insonified area can be reduced significantly by accounting for seafloor slope during backscatter processing while transmission losses can be constrained by collecting full water column absorption coefficient profiles (temperature and salinity profiles). To reduce random fluctuations to below 1 dB, at least 20 samples are recommended to be used while computing mean values. The estimation of uncertainty in backscatter measurements is constrained by the fact that not all instrumental components are characterized and documented sufficiently for commercially available MBES. Further involvement from manufacturers in providing this essential information is critically required.     

海床浅表层硬质薄层的声学识别

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。     

Validation of automated supervised segmentation of multibeam backscatter data from the Chatham Rise,New Zealand

Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation.     

Seafloor acoustic remote sensing with multibeam echo-sounders and bathymetric sidescan sonar systems

This paper examines the potential for remote classification of seafloor terrains using a combination of quantitative acoustic backscatter measurements and high resolution bathymetry derived from two classes of sonar systems currently used by the marine research community: multibeam echo-sounders and bathymetric sidescans sonar systems. The high-resolution bathymetry is important, not only to determine the topography of the area surveyed, but to provide accurate bottom slope corrections needed to convert the arrival angles of the seafloor echoes received by the sonars into true angles of incidence. An angular dependence of seafloor acoustic backscatter can then be derived for each region surveyed, making it possible to construct maps of acoustic backscattering strength in geographic coordinates over the areas of interest. Such maps, when combined with the high-resolution bathymetric maps normally compiled from the data output by the above sonar systems, could be very effective tools to quantify bottom types on a regional basis, and to develop automatic seafloor classification routines.     

Multi-stage formation of La Fossa Caldera (Vulcano Island,Italy) from an integrated subaerial and submarine analysis

Marine Geophysical Research - The analysis of multibeam bathymetry, seismic profiles, ROV dive and seafloor sampling, integrated with stratigraphic and geological data derived from subaerial field...     

Automatic Registration of TOBI Side-Scan Sonar and Multi-Beam Bathymetry Images for Improved Data Fusion

Deep towed side-scan sonar vehicles such as TOBI acquire high quality imagery of the seafloor with very high spatial resolution but poor locational accuracy. Fusion of the side-scan sonar data with bathymetry data from an independent source is often desirable to reduce ambiguity in geological interpretations, to aid in slant-range correction and to enhance seafloor representation. The main obstacle to fusion is accurate registration of the two datasets.The application of hierarchical chamfer matching to the registration of TOBI side-scan sonar images and multi-beam swath bathymetry is described. This matches low level features such as edges in the TOBI image, with corresponding features in a synthetic TOBI image created by simulating the flight of the TOBI vehicle through the bathymetry. The method is completely automatic, relatively fast and robust, and much easier than manual registration. It allows accurate positioning of the TOBI vehicle, enhancing its usefulness as a research tool. The method is illustrated by automatic registration of TOBI and multi-beam bathymetry data from the Mid-Atlantic Ridge.