侧扫声纳和浅地层剖面仪在海管断裂点定位中的应用

结合侧扫声纳和浅地层剖面仪能够探测出海底管道附近异常,路由区浅层地质灾害以及海底管道位置等特点,通过实例探讨了侧扫声纳和浅地层剖面仪在海底管道断裂位置定位中的应用。船锚、浅层气等外力作用,导致海底油气管道断裂,使用侧扫声纳和浅地层剖面仪探测的方法,综合分析海水中的气体屏蔽现象、海底面的地貌异常特征、海底管道的平面位置及埋深变化、地层剖面的反射空白等异常特征,快速准确定位海底油气管道断裂位置。     

上覆硬质保护层海底管道检测技术探讨

海底管道在油气工业中发挥着重要作用,为保障其安全运营必须定期进行检测掌握其在海底的状态。有的海底管道在铺设时为其安全考虑,在海底管道上方覆盖了抛石等硬质保护层,这样就导致在海底管道定期检测时一些检测仪器难以探测到硬质保护层下海底管道的位置和埋深,而浅地层剖面仪和磁力仪仍然可以不同程度地实现这种情况下的海底管道检测。文中对浅地层剖面仪和磁力仪的原理进行了介绍并对其在上覆抛石等硬质保护层海底管道检测中的应用进行了分析探讨。分析结果表明浅地层剖面仪和磁力仪组成的综合检测系统对上覆硬质保护层的海底管道探测有一定效果,可查明海硬质保护层下海底管道的位置和埋深,为海底管道的安全管理和维护提供数据支持,也可为其他类似海底管道检测提供参考。     

海底烃类渗漏的地球物理识别

海底烃类渗漏在向上运移过程中会改变深部地层和海底表层沉积物的声学性质,在地震和浅地层剖面上会形成各种可能指示烃类渗漏的地球物理标志。渗漏烃到达海底后会改变海底表面形态,形成与海底烃类渗漏有关的表面特征,如麻坑构造、海底凸起、海底古河道、碳酸盐丘、硬地面、泥火山以及表面断层等。渗漏烃进入海水后在继续上升过程中会形成气泡、渗漏羽,到达海面后会形成表面油膜。利用侧扫声纳、多波束测深和浅地层剖面可以探测到与海底烃类渗漏有关的表面特征。合成孔径雷达能够识别因海底烃类渗漏形成的海水表面油膜。海底烃类渗漏的地球物理标志是间接的,必须通过地球化学校验才能确定渗漏的存在。     

一种海底浅层声学探测数据综合可视化方法

提出了一种基于Open GL可编程管线的海底浅层声学探测数据三维综合可视化方法。通过处理,将侧扫声呐影像、多波束数据和浅地层剖面在同一视图下显示,可以方便的对海底地质环境多种信息进行综合判读并进行多维数据的交互式提取。利用纹理缓冲区处理侧扫声呐影像数据,具有数据加载量大的优点,避免了实际应用中纹理数据反复切换带来的延迟;并且探讨了侧扫声呐影像和多波束数据分辨率不一致引起的纹理贴图问题。该方法在南海海底峡谷区域的海底地质环境综合显示和分析中进行了应用,结果表明,该方法能处理多种格式的侧扫声呐影像,不受侧扫声呐影像和多波束测深数据分辨率不一致的限制,数据加载量大、绘制速度快。     

SES-2000浅地层剖面仪在福建LNG海底管道检测中的应用

利用声学浅地层剖面仪对海底管道在海底的赋存状态检测是确保海底输油气管道安全运行的重要措施之一。介绍了新型参量阵浅地层剖面仪SES-2000的基本原理及其特点,通过对福建湄洲湾LNG海底管道检测实际应用,有效识别出了埋藏、裸露和悬空等3类海底管道赋存状态,尤其对沙包回填治理后的管道埋深能有效探测识别。检测结果表明,该设备具有高分辨率和强穿透的特点,稳定性好,能获取高品质的管道检测数据,应用效果良好。获取的基础数据为海底管道日常维护提供了科学依据和技术支持。     

海底管道测量声学剖面特征分析

海底管道的位置与埋深测量通常采用浅地层剖面仪等声学手段来实现,由于海管与地层之间的声阻抗差异,会以绕射弧的形态出现在声学剖面中。但当海管埋设于管沟中时,管沟中断棱的绕射与海管绕射易于混淆,给声学剖面图的解译和识别带来困难。基于地震勘探原理,结合浅地层剖面仪的性能、挖沟作业对地层的扰动等,分析了管沟绕射弧的类型与特点、挖沟作业扰动的声学特征等,提出了管沟中海管绕射弧的识别方法。结果表明,正确认识不同类型管沟的绕射、施工扰动产生的绕射等声学特征,才能辨识出海管的绕射现象。实际工作中应根据测量海区的水深、土质、海管属性等多种要素,选用适宜的仪器类型及测量参数。     

浅地层剖面仪和侧扫声呐仪器检测与评价方法研究

针对浅地层剖面仪和侧扫声呐这2种声呐系统探讨性地提出了"两步法"的性能检测和评价方法:1)声学物理参数检测:分析了与浅地层剖面仪和侧扫声呐系统性能相关的关键声学物理参数(声源级、频率/频谱、脉冲长度、波束角或开角),并提出了在消声水池中测定这些参数的方法;2)实际探测性能评价:分析了与浅地层剖面仪和侧扫声呐系统性能相关的实际探测效果评价指标,并提出了通过海上试验来检测和评价这些指标的方法。最后对建设具备高效消声性能的大型试验水池,建设海底标准地层检测场和海底标准目标物检测场以真正实现设备性能的检定应做的后续工作进行了讨论。     

一种新型浅地层剖面仪试验平台的设计与应用

为探讨浅地层剖面声学影像形成原理,探索不同类型沉积物声学影像特征,厘清不同沉积物厚度的识别算法,采用模块化设计理念研发一套新型浅地层剖面仪室内试验平台。综合室内定位技术、浅剖试验平台尺寸合理性分析技术、直线轨道与换能器之间的固定连接技术和海底声学参数反演技术,形成一个试验高效的新型平台。通过铺设沉积物和布设障碍物,利用浅地层剖面仪进行走航测试,精确识别了沉积物的厚度和障碍物的位置。该平台可为开展理想环境下沉积物厚度和障碍物识别提供较好的测试环境,为声学海洋设备性能检测提供测试平台,也为高校学生和技术人员提供设备使用培训场所。     

参量阵浅剖探测技术在海底管线探测中的应用

以航道、港口海底管线为探测目标,以浅地层剖面(sub-bottom profile)探测技术为主要技术手段,结合SES2000系列浅地层剖面探测系统在近海航道、港口海底管线探测中的应用案例,探讨SBP探测技术在管线探测中的应用。就浅剖图像中的航道、港口海底埋深管线识别定位中存在的技术难题,提出了基于波路径的偏移处理定性分析法和基于信号分析的管道反射弧识别定量计算法进行管道埋深的分析与计算,结合DGPS导航系统可准确获取管线所在平面位置与埋深深度。对于航道适航安全、港口安全建设具有积极意义。     

DTA-6000声学深拖系统在富钴结壳探测中的应用

富钴结壳作为一种潜在的海洋矿产资源逐渐引起人们的关注,研究发现海山微地形是影响富钴结壳分布的重要因素。DTA-6000声学深拖系统是我国具有自主知识产权的第一套深海拖曳观测系统,其最大工作深度6 000m,该设备上安装的高分辨率测深侧扫声纳和浅地层剖面仪能够分别获得高分辨率的海底地形地貌和浅地层剖面。它的测深覆盖范围600m,侧扫覆盖范围800m。声学深拖系统因其高效和价格优势,被列为富钴结壳资源调查的常规设备。大洋29航次中,DTA-6000声学深拖系统在采薇海山完成2条测线共约50km海山斜坡的探测,获得了高分辨率的地形地貌数据和浅地层剖面数据。介绍DTA-6000声学深拖系统及其在富钴结壳探测中的应用,并对探测结果进行了分析。     

Gas seepage, pockmarks and mud volcanoes in the near shore of SW Taiwan

In order to understand gas hydrate related seafloor features in the near shore area off SW Taiwan, a deep-towed sidescan sonar and sub-bottom profiler survey was conducted in 2007. Three profiles of high-resolution sub-bottom profiler reveal the existence of five gas seeps (G96, GS1, GS2, GS3 and GS4) and one pockmark (PM) in the study area. Gas seeps and pockmark PM are shown in lines A and C, while no gas venting feature is observed along line B. This is the first time that a gas-hydrate related pockmark structure has been imaged off SW Taiwan. The relatively high backscatter intensity in our sidescan sonar images indicates the existence of authigenic carbonates or chemosynthetic communities on the seafloor. More than 2,000 seafloor photos obtained by a deep-towed camera (TowCam) system confirm the relatively high backscatter intensity of sidescan sonar images related to bacteria mats and authigenic carbonates formation at gas seep G96 and pockmark PM areas. Water column gas flares are observed in sidescan sonar images along lines A and C. Likewise, EK500 echo sounder images display the gas plumes above gas seep G96, pockmark PM and gas seep GS1; the gas plumes heights reach about 150, 100 and 20 m from seafloor, respectively. Based on multichannel seismic reflection (MCS) profiles, an anticline structure trending NNE-SSW is found beneath gas seep G96, pockmark PM and gas seep GS2. It implies that the gas venting features are related to the anticline structure. A thermal fluid may migrate from the anticline structure to the ridge crest, then rises up to the seafloor along faults or fissures. The seafloor characteristics indicate that the gas seep G96 area may be in a transitional stage from the first to second stage of a gas seep self-sealing process, while the pockmark PM area is from the second to final stage. In the pockmark PM area, gas venting is observed at eastern flank but not at the bottom while authigenic carbonates are present underneath the pockmark. It implies that the fluid migration pathways could have been clogged by carbonates at the bottom and the current pathway has shifted to the eastern flank of the pockmark during the gas seep self-sealing process.     

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.     

Improved detection and mapping of deepwater hydrocarbon seeps: optimizing multibeam echosounder seafloor backscatter acquisition and processing techniques

Marine seep hunting surveys are a current focus of hydrocarbon exploration surveys due to recent advances in offshore geophysical surveying, geochemical sampling, and analytical technologies. Hydrocarbon seeps are ephemeral, small, discrete, and therefore difficult to sample on the deep seafloor. Multibeam echosounders are an efficient seafloor exploration tool to remotely locate and map seep features. Geophysical signatures from hydrocarbon seeps are acoustically-evident in bathymetric, seafloor backscatter, midwater backscatter datasets. Interpretation of these signatures in backscatter datasets is a fundamental component of commercial seep hunting campaigns. Degradation of backscatter datasets resulting from environmental, geometric, and system noise can interfere with the detection and delineation of seeps. We present a relative backscatter intensity normalization method and an oversampling acquisition technique that can improve the geological resolvability of hydrocarbon seeps. We use Green Canyon (GC) Block 600 in the Northern Gulf of Mexico as a seep calibration site for a Kongsberg EM302 30 kHz MBES prior to the start of the Gigante seep hunting program to analyze these techniques. At GC600, we evaluate the results of a backscatter intensity normalization, assess the effectiveness of 2X seafloor coverage in resolving seep-related features in backscatter data, and determine the off-nadir detection limits of bubble plumes using the EM302. Incorporating these techniques into seep hunting surveys can improve the detectability and sampling of seafloor seeps.     

An insight into shallow gas hydrates in the Dongsha area,South China Sea

Previous studies of gas hydrate in the Dongsha area mainly focused on the deep-seated gas hydrates that have a high energy potential, but cared little about the shallow gas hydrates occurrences. Shallow gas hydrates have been confirmed by drill cores at three sites(GMGS2 08, GMGS2 09 and GMGS2 16) during the GMGS2 cruise, which occur as veins, blocky nodules or massive layers, at 8–30 m below the seafloor. Gas chimneys and faults observed on the seismic sections are the two main fluid migration pathways. The deep-seated gas hydrate and the shallow hydrate-bearing sediments are two main seals for the migrating gas. The occurrences of shallow gas hydrates are mainly controlled by the migration of fluid along shallow faults and the presence of deep-seated gas hydrates.Active gas leakage is taking place at a relatively high-flux state through the vent structures identified on the geophysical data at the seafloor, although without resulting in gas plumes easily detectable by acoustic methods.The presence of strong reflections on the high-resolution seismic profiles and dim or chaotic layers in the subbottom profiles are most likely good indicators of shallow gas hydrates in the Dongsha area. Active cold seeps,indicated by either gas plume or seepage vent, can also be used as indicators for neighboring shallow gas hydrates and the gas hydrate system that is highly dynamic in the Dongsha area.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.     

多波束反向散射强度数据处理研究

在探讨多波束测深系统反向散射强度与海底底质类型的关系基础上,研究影响反向散射强度的各种因素,主要分析了海底地形起伏、中央波束区反射信号对反向散射强度的影响,并给出了消除这些影响的方法;将处理后的“纯”反向散射强度数据镶嵌生成海底声像图,为海底底质类型划分以及地貌解译提供了基础数据和辅助判读依据.     

Processing Multibeam Backscatter Data

A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research.     

Discovery of the southwest Dongsha Island mud volcanoes amid the northern margin of the South China Sea

The Dongsha Basin, circling Dongsha Island that is amid the northern margin of the South China Sea, is characterized by thin (∼0.5 km) Cenozoic sediments veneering on thick (up to 5 km) Mesozoic strata. Recently, several geophysical and geological surveys, including multiple channel reflection seismic, sub-bottom profiling and benthic dredging, have been conducted on the slope southwest to the Dongsha Island, where the water depth varies from 400 m to 2000 m. A novel discovery is numerous submarine mud volcanoes of various sizes over there, typically 50–200 m high and 0.5–5 km wide. Geophysical profiles document their unusual features, e.g., roughly undulating seafloor, high-amplitude seabed reflectivity, foggy hyperbolic diffractions up to 50 m in water column above seabed, and internal reflection chaos and wipe-out down to 2–3 km level or deeper below the seabed. Benthic dredging from the mud volcanoes gives abundant faunas of high diversity, e.g., scleractinian (stony coral), gorgonian, black coral, thiophil tubeworm, glass sponge, bryozoan etc., indicating booming chemosynthetic community, among which the Lophelia pertusa-like coral and the Euretidae-like glass sponges are the first reports in the South China Sea. Concomitantly with them, there are also abundant authigenic carbonate nodules and slabs, raw, brecciated and breccias with bio-clasts congregation. Besides, there coexist massive mudflows and allogenic coarse-grained quartz, feldspar and tourmaline most likely brought out by mud volcanism. Geochemical analysis of the bottom water samples give dissolved methane concentration up to 4 times higher than the background average. These results lend comprehensive evidences for the ongoing and historical mud volcanism. The escaping methane gas is inferred to source mainly from the Mesozoic strata. Occupying a large province of the deep water slope, ca. 1000 km² or more, the mud volcanoes is prospective for gas hydrate and natural gas for the Dongsha Basin.     

Acoustic evidence of a submarine slide in the deepest part of the Arctic,the Molloy Hole

The western Svalbard continental margin contains thick sediment sequences with areas known to contain gas hydrates. Together with a dynamic tectonic environment, this makes the region prone to submarine slides. This paper presents results from geophysical mapping of the deepest part of the high Arctic environment, the Molloy Hole. The mapping includes multibeam bathymetry, acoustic backscatter and sub-bottom profiling. The geophysical data reveal seabed features indicative of sediment transport and larger-scale mass wasting. The large slide scar is here referred to as the Molloy Slide. It is located adjacent to the prominent Molloy Hole and Ridge system. The slide is estimated to have transported >65 km³ of sediments over the deep axial valley of the Molloy Ridge, and further into the Molloy Hole. A unique feature of this slide is that, although its run-out distance is relatively short (<5 km), it extends over an enormous vertical depth (>2,000 m) as a result of its position in a complex bathymetric setting. The slide was most likely triggered by seismic activity caused by seafloor spreading processes along the adjacent Molloy Ridge. However, gas-hydrate destabilization may also have played a role in the ensuing slide event.     

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.