Status quo and prospect in acoustic detection technology for submarine cobalt-rich crust exploration
-
摘要:
富钴结壳是深海固体矿产之一,其资源潜力巨大,已成为世界各国竞相调查的重要对象。声学探测技术作为一种海洋地球物理探测技术,因其在大面积调查和局部连续精细勘探方面的独特优势,在富钴结壳资源调查中得到了广泛应用。在搜集整理国内外相关文献的基础上,概述了富钴结壳的分布特征,分析传统勘探方法的不足,系统介绍多波束、侧扫声呐、浅地层剖面、原位高频测厚等声学探测技术在富钴结壳勘探中的应用现状。通过比较分析国内外声学探测技术发展现状以及未来富钴结壳勘探需求,提出3点未来发展趋势:开发一体化声学探测技术以实现海底特性的综合性测量;综合利用深海潜水器以实现近底高精度探测;深度融合大数据和人工智能技术以实现海量声学数据的智能化处理。
Abstract:Cobalt-rich crusts are one of the deep-sea mineral resources with great potential, and have become an important target of exploration in the world. Acoustic detection technology has been widely used to search for cobalt-rich crust resources due to its unique advantages in large-area survey and local continuous fine exploration. The distribution characteristics of cobalt-rich crusts are summarized, the traditional exploration methods are commented, the application status of acoustic detection technologies such as multi-beam system, side-scan sonar, sub-bottom profiler probe are reviewed, and in-situ high-frequency thickness measurement in the exploration of cobalt-rich crusts is introduced. In addition, the status quo in research and development in this regard in China and other countries of the world are compared, and three suggestions on future demand of cobalt-rich crusts exploration are proposed: to develop integrated acoustic detection technology to realize comprehensive measurement of seafloor characteristics, to make comprehensive use of deep-sea submersible to achieve high-precision near seabed exploration, and to deeply integrate the Big Data and artificial intelligence technology to obtain intelligent processing of massive acoustic data.
-
-
表 1 常用声学探测技术在富钴结壳探测中的应用
Table 1. The applications of common acoustic detection technologies in cobalt-rich crusts detection
技术名称 工作方式 获得声学参数 空间/地层分辨率/m 富钴结壳探测目标 优势与不足 参考文献 多波束系统 利用声学换能器向海底发射宽扇区覆盖声波,并进行窄波束接收,通过发射、接收形成的照射脚印,对所测区域进行条带式测量 声回波强度 0.10~0.40 海山地形、地貌特征;底质类型;空间分布 可实现全覆盖,工作高效;船载方式、分辨率较低 文献[10,
21, 30-31,
49-54]侧扫声呐 利用声学换能器向航迹两侧海底发射宽角度声波,对所测区域进行大规模扫测 声回波强度 0.05 海山地形、地貌特征;底质类型 深拖方式,分辨率较高;粗略空间定向 文献[34-35,55] 浅地层剖面 利用声学换能器垂直向海底发射低频声波,对所测区域进行连续走航式探测 反射波的波速、振幅和返回时间 0.10 沉积类型、特征;
结壳—沉积物分布界限;结壳厚度获取浅地层内部结构信息;分辨率较低 文献[12,
36-39,56]原位高频测厚 基于深海潜水器利用高频声学探头,对富钴结壳进行原位自动连续测厚 原频、差频反射波的时延差;富钴结壳的声速 0.01 结壳厚度;矿体分布 近底原位,分辨率高;工作效率较低 文献[40-45,
57-62] -
[1] HALBACH P. Processes controlling the heavy metal distribution in Pacific ferromanganese nodules and crusts[J]. Geologische Rundschau,1986,75(1):235-247. doi: 10.1007/BF01770191
[2] HEIN J R, KOSCHINSKY A, BAU M, et al. Cobalt-rich ferromanganese crusts in the Pacific[M]//Cronan D S. Handbook of Marine Mineral Deposits. Florida: CRC Press, 2000: 239-279.
[3] OKAMOTO N,USUI A. Regional distribution of co-rich ferromanganese crusts and evolution of the seamounts in the Northwestern Pacific[J]. Marine Georesources and Geotechnology,2014,32(3):187-206.
[4] 韦振权,何高文,邓希光,等. 大洋富钴结壳资源调查与研究进展[J]. 中国地质,2017,44(3):460-472.
[5] HALBACH P, MARBLER H. Marine ferromanganese crusts: contents, distribution and enrichment of strategic minor and trace elements[M]//BGR-Report. Hannover: Bundesanstalt für Geowissenschaften und Rohstoffe, 2009: 1-73.
[6] HEIN J R,MIZELL K,KOSCHINSKY A,et al. Deep-ocean mineral deposits as a source of critical metals for high and green technology applications:comparison with land-based resources[J]. Ore Geology Reviews,2013,51:1-14. doi: 10.1016/j.oregeorev.2012.12.001
[7] 刘永刚,何高文,姚会强,等. 世界海底富钴结壳资源分布特征[J]. 矿床地质,2013,32(6):1275-1284.
[8] HEIN J R,KOSCHINSKY A. Deep-ocean ferromanganese crusts and nodules[J]. Treatise on Geochemistry,2014,13:273-291.
[9] 张富元, 章伟艳, 朱克超, 等. 太平洋海山钴结壳资源评价[M]. 北京: 海洋出版社, 2011: 143-160.
[10] 杨永,何高文,朱克超,等. 利用多波束回波强度进行中太平洋潜鱼海山底质分类[J]. 地球科学,2016,41(4):718-728.
[11] HALBACH P E, JAHN A, CHERKASHOV G. Marine co-rich ferromanganese crust deposits: description and formation, occurrences and distribution, estimated world-wide resources[M]//Deep-Sea Mining. Cham: Springer International Publishing, 2017: 65-141.
[12] 赵斌,吕文超,张向宇,等. 西太平洋维嘉平顶山沉积特征及富钴结壳资源意义[J]. 地质通报,2020,39(1):18-26.
[13] 何高文,杨永,韦振权,等. 西太平洋中国富钴结壳勘探合同区矿床地质[J]. 中国有色金属学报,2021,31(10):2649-2664.
[14] 张富元,章伟艳,任向文,等. 全球三大洋海山钴结壳资源量估算[J]. 海洋学报,2015,37(1):88-105.
[15] 矫东风,金翔龙,初凤友,等. 厚结壳的形成条件及控制因素分析[J]. 矿床地质,2007,26(3):296-306.
[16] USUI A,NISHI K,SATO H,et al. Continuous growth of hydrogenetic ferromanganese crusts since 17 Myr ago on Takuyo-Daigo Seamount,NW Pacific,at water depths of 800–5 500 m[J]. Ore Geology Reviews,2017,87:71-87. doi: 10.1016/j.oregeorev.2016.09.032
[17] 王淑玲,白凤龙,黄文星,等. 世界大洋金属矿产资源勘查开发现状及问题[J]. 海洋地质与第四纪地质,2020,40(3):160-170.
[18] YAMAZAKI T,TSURUSAKI K,CHUNG J S. A gravity coring technique applied to cobalt-rich manganese deposits in the Pacific Ocean[J]. Marine Georesources and Geotechnology,1996,14(4):315-334.
[19] ANDERSON J T,HOLLIDAY V,KLOSER R,et al. Acoustic seabed classification of marine physical and biological landscapes[J]. ICES Cooperative Research Report,2007,286:1-6.
[20] 耿雪樵,徐行,刘方兰,等. 我国海底取样设备的现状与发展趋势[J]. 地质装备,2009,10(4):11-16.
[21] USUI A,OKAMOTO T. Geophysical and geological exploration of cobalt-rich ferromanganese crusts:an attempt of small-scale mapping on a Micronesian seamount[J]. Marine Georesources and Geotechnology,2010,28(3):192-206.
[22] 何水原,罗伟东,于彦江,等. 动力定位系统在大洋富钴结壳调查中的应用[J]. 海洋地质前沿,2015,31(10):57-64.
[23] 罗伟东,何水原. 岩石拖网在富钴结壳调查中的应用[J]. 海洋地质前沿,2017,33(9):66-70.
[24] 朱维庆. 海洋声学技术和信息处理[J]. 世界科技研究与发展,2000,22(4):41-44.
[25] 何清华,袁碧华. 用声波检测大洋富钴结壳厚度的初步探讨[J]. 采矿技术,2003,3(2):93-95.
[26] 金翔龙. 海洋地球物理研究与海底探测声学技术的发展[J]. 地球物理学进展,2007,22(4):1243-1249.
[27] ANDERSON J T,VAN H D,KLOSER R,et al. Acoustic seabed classification:current practice and future directions[J]. ICES Journal of Marine Science,2008,65(6):1004-1011. doi: 10.1093/icesjms/fsn061
[28] 杨永,朱克超,邓希光,等. 声学勘探技术在大洋矿产资源勘查中的应用前景[J]. 地质论评,2013,59(1):947-948.
[29] 张国祯. 富钴结壳矿区申请需要解决的两个重要问题[J]. 海洋地质动态,2005,21(10):19-22.
[30] YEO I A,HOWARTH S A,SPEARMAN J,et al. Distribution of and hydrographic controls on ferromanganese crusts:Tropic Seamount,Atlantic[J]. Ore Geology Reviews,2019,114:103131. doi: 10.1016/j.oregeorev.2019.103131
[31] YANG Y,HE G W,LIU Y G,et al. Automated multi-scale classification of the terrain units of the Jiaxie Guyots and their mineral resource characteristics[J]. Acta Oceanologica Sinica,2022,41(7):129-139.
[32] JOHNSON H P,HELFERTY M. The geological interpretation of side-scan sonar[J]. Reviews of Geophysics,1990,28(4):357-380. doi: 10.1029/RG028i004p00357
[33] ATALLAH L,SMITH P P. Automatic seabed classification by the analysis of side-scan sonar and bathymetric imagery[J]. IEE Proceedings-Radar,Sonar and Navigation,2004,151(5):327-336. doi: 10.1049/ip-rsn:20040279
[34] 徐建,郑玉龙,包更生,等. 基于声学深拖调查的海山微地形地貌研究:以马尔库斯-威克海岭一带的海山为例[J]. 海洋学研究,2011,29(1):17-24.
[35] 冯强强,温明明,牟泽霖,等. 侧扫声呐在富钴结壳探测中的应用前景[J]. 地质学刊,2016,40(2):320-325.
[36] LEE T G,HEIN J R,LEE K,et al. Sub-seafloor acoustic characterization of seamounts near the Ogasawara Fracture Zone in the Western Pacific using chirp(3-7 kHz) sub-bottom profiles[J]. Deep-Sea Research 1,2005,52(10):1932-1956. doi: 10.1016/j.dsr.2005.04.009
[37] 李守军,陶春辉,初凤友,等. 浅地层剖面在富钴结壳调查研究中的应用[J]. 海洋技术,2007,26(1):54-57.
[38] MEL’ NIKOV M E,TUGOLESOV D D,PLETNEV S P. The structure of the incoherent sediments in the Ita Mai Tai Guyot(Pacific Ocean) based on geoacoustic profiling data[J]. Oceanology,2010,50(4):582-590. doi: 10.1134/S0001437010040144
[39] 何高文,梁东红,宋成兵,等. 浅地层剖面测量和海底摄像联合应用确定平顶海山富钴结壳分布界线[J]. 地球科学(中国地质大学学报),2005,35(4):509-512.
[40] THORNTON B, ASADA A, URA T, et al. The development of an acoustic probe to measure the thickness of ferromanganese crusts[C]//Oceans 2010 IEEE, Sydney: IEEE, 2010: 1- 9.
[41] THORNTON B,ASADA A,BODENMANN A,et al. Instruments and methods for acoustic and visual survey of manganese crusts[J]. IEEE Journal of Oceanic Engineering,2013,38(1):186-203. doi: 10.1109/JOE.2012.2218892
[42] NEETTIYATH U, THORNTON B, SANGEKAR M, et al. Automatic extraction of thickness information from sub-surface acoustic measurements of manganese crusts[C]//Oceans 2017 - Aberdeen, Aberdeen: IEEE, 2017: 1-7.
[43] NEETTIYATH U, THORNTON B, SUGIMATSU H, et al. Automatic detection of buried Mn-crust layers using a sub-bottom acoustic probe from AUV based surveys[C]//Oceans 2022 - Chennai, Chennai: IEEE, 2022: 1-7.
[44] 冯海泓,任晓寰,黄敏燕,等. 探测深海富钴结壳厚度的参量阵声呐系统关键技术研究[J]. 声学技术,2020,39(3):267-271.
[45] HONG F,FENG H H,HUANG M Y,et al. China’s first demonstration of cobalt-rich manganese crust thickness measurement in the Western Pacific with a parametric acoustic probe[J]. Sensors,2019,19(19):4300. doi: 10.3390/s19194300
[46] 黄威,路晶芳,龚建明,等. 北极海域铁锰结核和结壳的分布与成因[J]. 海洋地质前沿,2020,36(7):11-16.
[47] 中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. GB/T 35572—2017, 大洋富钴结壳资源勘查规范[S]. 北京: 中国标准出版社.
[48] HEIN J R. Cobalt-rich ferromanganese crusts: global distribution, composition, origin and research activities[M]//Minerals Other than Polymetallic Nodules of the International Seabed Area. Jamaica: International Seabed Authority, 2004: 188-256.
[49] 张同伟,秦升杰,唐嘉陵,等. 深水多波束测深系统现状及展望[J]. 测绘通报,2018,5:82-85.
[50] HUGHES CLARKE J E. Multibeam echosounders[M]//Submarine Geomorphology. Cham: Springer International Publishing, 2018: 25-41.
[51] KODAMA T,MAEDA K. Interpretation of a backscattering image for the prospecting of cobalt-rich manganese crust[J]. The Journal of the Acoustical Society of America,1996,100(4):2667.
[52] JOO J,KIM J,KO Y,et al. Characterizing geomorphological properties of Western Pacific seamounts for cobalt-rich ferromanganese crust resource assessment[J]. Economic and Environmental Geology,2016,49(2):121-134. doi: 10.9719/EEG.2016.49.2.121
[53] JOO J,KIM S S,CHOI J W,et al. Seabed mapping using shipboard multibeam acoustic data for assessing the spatial distribution of ferromanganese crusts on seamounts in the Western Pacific[J]. Minerals,2020,10(2):155. doi: 10.3390/min10020155
[54] YAO H Q,LIU Y G,YANG Y,et al. Assessment of acoustic backscatter intensity surveying on deep-sea ferromanganese crust:constraints from Weijia Guyot,Western Pacific Ocean[J]. China Geology,2021,4(2):288-298.
[55] 曹金亮,刘晓东,张方生,等. DTA-6000声学深拖系统在富钴结壳探测中的应用[J]. 海洋地质与第四纪地质,2016,36(4):173-181.
[56] MEREDYK S P,EDINGER E,PIPER D J W,et al. Enigmatic deep-water mounds on the Orphan Knoll,Labrador Sea[J]. Frontiers in Marine Science,2020,6:2296-7745.
[57] 王斌贤,冯海泓,黄敏燕,等. 基于参量阵双通道信息的富钴结壳高精度测厚算法[J]. 声学技术,2021,40(4):464-469.
[58] THORNTON B, BODENMANN A, ASADA A, et al. Acoustic and visual instrumentation for survey of manganese crusts using an underwater vehicle[C]//2012 Oceans, Hampton Roads: IEEE, 2012: 1-10.
[59] NEETTIYATH U, THORNTON B, SANGEKAR M, et al. An AUV based method for estimating hectare-scale distributions of deep sea cobalt-rich manganese crust deposits[C]//Oceans 2019-Marseille, Marseille: IEEE, 2019: 1-6.
[60] NEETTIYATH U,THORNTON B,SANGEKAR M,et al. Deep-Sea robotic survey and data processing methods for regional-scale estimation of manganese crust distribution[J]. IEEE Journal of Oceanic Engineering,2021,46(1):102-114. doi: 10.1109/JOE.2020.2978967
[61] 张旭. 结壳矿层声学测厚仪在大洋富钴结壳资源勘察中的应用[J]. 机电工程技术,2018,47(5):157-159.
[62] HONG F,HUANG M Y,FENG H H,et al. First demonstration of recognition of manganese crust by deep-learning networks with a parametric acoustic probe[J]. Minerals,2022,12(2):249. doi: 10.3390/min12020249
[63] 程永寿. 西北太平洋海山富钴结壳资源评价和矿区圈定[D]. 青岛: 中国海洋大学, 2014.
[64] 吴自银,郑玉龙,初凤友,等. 海底浅表层信息声探测技术研究现状及发展[J]. 地球科学进展,2005,20(11):58-65.
[65] 温志坚,何志敏. 应用侧扫声呐的海底目标探测技术研究[J]. 科技创新导报,2017,14(22):28-29.
[66] 郑晖. 多波束与侧扫声呐在水下探测中的应用[J]. 中国新技术新产品,2020,10:34-36.
[67] STEEPLES D W,GREEN A G,MCEVILLY T V,et al. A workshop examination of shallow seismic reflection surveying[J]. The Leading Edge,1997,16(11):1641-1647. doi: 10.1190/1.1437543
[68] 杨国明,朱俊江,赵冬冬,等. 浅地层剖面探测技术及应用[J]. 海洋科学,2021,45(6):147-162.
[69] RIOBLANC M. High productivity multi-sensor seabed mapping sonar for marine mineral resources exploration[C]//2013 IEEE/OES Acoustics in Underwater Geosciences Symposium, Rio de Janeiro: IEEE, 2013: 1-6.
[70] FEZZANI R,ZERR B,MANSOUR A,et al. Fusion of swath bathymetric data:application to AUV rapid environment assessment[J]. IEEE Journal of Oceanic Engineering,2019,44(1):111-120. doi: 10.1109/JOE.2017.2773139
[71] 马晶鑫. 海底地形地貌与浅地层剖面一体化声学探测关键技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2021.
[72] 刘经南,赵建虎. 多波束测深系统的现状和发展趋势[J]. 海洋测绘,2002,22(5):3-6.
[73] SPIESS F N. Seafloor research and ocean technology[J]. Marine Technology Society Journal,1987,21(2):5-17.
[74] 何林帮. 基于多波束和浅剖的海底浅表层沉积物分类关键问题研究[J]. 测绘学报,2016,45(12):1498-1512.
[75] DEROOS B G, WILSON G, LYON F, et al. Technical survey and evaluation of underwater sensors and remotely operated vehicles[R]. Battelle Columbus: U.S. Coast Guard Research and Development Center, 1993.
[76] 朱大奇,胡震. 深海潜水器研究现状与展望[J]. 安徽师范大学学报(自然科学版),2018,41(3):205-216.
[77] 徐伟哲,张庆勇. 全海深潜水器的技术现状和发展综述[J]. 中国造船,2016,57(2):206-221.
[78] 刘永刚,姚会强,邓希光. 蛟龙号HOV在海山结壳资源勘查中的应用[J]. 地质论评,2017,63(1):231-232.
[79] 徐行. 我国海洋地球物理探测技术发展现状及展望[J]. 华南地震,2021,41(2):1-12.
[80] LI S,CHEN J P,LIU C. Overview on the development of intelligent methods for mineral resource prediction under the background of geological big data[J]. Minerals,2022,12:616.
[81] 刘智慧,张泉灵. 大数据技术研究综述[J]. 浙江大学学报(工学版),2014,48(6):957-972.
[82] 张雪薇,韩震,周玮辰,等. 智慧海洋技术研究综述[J]. 遥感信息,2020,35(4):1-7.
-