KMS XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY，CAS
| 基于多时相 NDWI 里海油气平台识别 | |
| Alternative Title | Identification of Caspian Oil and Gas Platform Based on Multi-temporal NDWI |
| 朱惠 | |
| Subtype | 硕士 |
| Thesis Advisor | 张清凌 |
| 2020-06-30 | |
| Degree Grantor | 中国科学院大学 |
| Place of Conferral | 北京 |
| Degree Discipline | 理学硕士 |
| Keyword | 里海地区 社会经济 夜光遥感 Landsat-NDWI 油气平台 Caspian Sea Socioeconomic development nigtht-time light NDWI Oil and Gas Platform |
| Abstract | 里海地区是世界上最古老的产油区之一，也是全球能源生产中越来越重要的来源。随着海（水）上油气资源的开发，里海地区能源地位日益突出。目前关于里海被定义为“海洋”还是“湖泊”依旧缺乏共识，里海地区的法律地位十分复杂。在每种情况下都将适用不同的国际法。因此，不断变化的法律法规框架为外国公司投资自然资源带来了不确定性以及更加复杂的形势。出于商业机密等原因，可共享的关于海上油气平台的空间属性信息依旧缺乏，仅北海、墨西哥的油气平台对外公开，但依旧存在更新不及时不明确等问题。而海上油气平台的空间位置信息在当今时代的很多领域都具有非常重要的地位，如能源安全、资源管理、环境保护。油气开发平台的时空分布、状态属性等信息直观反映了油气资源的开发程度，而及时、准确、全面地把握里海油气资源开发的历史、现状与趋势，对进一步保证里海地区区域安全具有重要作用。但目前，已有的可共享的油气资源相关数据，主要是基于国家层面的统计数据，如 BP 世界能源统计、 EIA 国际能源统计、世界银行数据库等，数据受人为因素干扰比较大，且耗时耗力、时效性差、难以反映油气开采活动的时空分布以及精细的油气产能。哈萨克斯坦、土库曼斯坦作为里海周边国家之一，油气资源丰富。然而，自1991 年苏联解体从其体系中独立以来，短短二十多年经历了政治经济改革、俄罗斯金融危机、全球金融危机、国际原料价格浮动等多次重大事件，社会经济多次受阻。而作为资源出口型的国家，能源出口尤其是油气资源出口日渐成为哈萨克斯坦、土库曼斯坦换取大量外汇的主要方式。准确把握和理解两国社会经济发展的区域特征对中亚区域安全以及我国“一带一路”倡议的顺利实施具有重要的现实意义。随着遥感技术的发展，利用卫星遥感技术获取人类活动成为可能。较传统的人工手段而言，遥感具有重返周期短、时效性强、大面积同步观测等特点，为实现油气活动监测、社会经济的动态观测提供了可能。而地理信息系统强大的空间管理、空间分析功能等为其提供了有力的技术支撑。同时，随着云平台技术的发展，以谷歌地球引擎（Google Earth Engine,GEE）为代表的云计算遥感平台，为大尺度大范围的快速精确提取地理信息创造了可能。针对以上里海油气资源数据缺乏和海上钻井平台位置信息、 属性信息有待明确等问题，本研究在遥感、 GIS、谷歌云平台等技术的支持下，通过多时相 Landsat7/ETM+、 DMSP/OLS、 NPP/VIIRS 等遥感数据自动提取里海油气开采活动空间位置、时间等属性信息，并建立基于遥感的石油产能估算，探究以油气产业为主要支撑产业的哈萨克斯坦、土库曼斯坦的社会经济发展状况，为进一步保证区域安全及我国能源安全提供技术支持和相关的决策辅助信息。本文的研究结论主要有：（1）里海油气平台静态识别：油气平台作为油气开采的主要设备之一，其时空分布、状态属性等信息直观反映了油气资源的开发程度。本文基于 Landsat-7/ETM+ NDWI 影像提出了一种自动识别油气平台的方法。本文首先根据油气平台在最大 NDWI、最小 NDWI、均值 NDWI 影像上的影像特征，选取水体、油气平台、裸地样本并统计其 NDWI 值分布，然后根据水体、裸地、油气平台的NDWI 特征建立了一套以描绘水体（Max_NDWI>0.55），裸地（岛屿）（Min_NDWI<-0.05）和油气平台（0 |
| Other Abstract | The Caspian Sea region is one of the oldest oil-producing areas in the world andis an increasingly important source of global energy production. The legal status ofthe Caspian area is complicated due to lack of agreement on whether the body ofwater is defined as a 'sea' or 'lake'. Different international laws would apply in eachcase. Therefore, the ever-changing legal and regulatory framework brings uncertaintyand more complex situation for foreign companies to invest in natural resources.Due to trade secrets and other reasons, there is still a lack of information aboutthe spatial attributes of offshore oil and gas platforms that can be shared. Only the oiland gas platforms in the North Sea and Mexico are open to the public, but there arestill problems such as the update is not timely and clear. The spatial locationinformation of offshore oil and gas platforms plays an important role in many fields,such as energy security, resource management and environmental protection. Thetemporal and spatial distribution, state attribute and other information of oil and gasdevelopment platform directly reflect the development degree of oil and gas resources,and timely, accurate and comprehensive grasp of the history, current situation andtrend of the development of oil and gas resources in the Caspian Sea plays animportant role in further ensuring the regional security of the Caspian Sea. However,at present, the existing shareable data of oil and gas resources are mainly based onnational level statistics, such as BP world energy statistics, EIA international energystatistics, world bank database, etc. the data are greatly disturbed by human factors,and the data are time-consuming, time-consuming, poor timeliness, difficult to reflectthe temporal and spatial distribution of oil and gas exploitation activities and fine oiland gas production capacity.As one of the countries around the Caspian Sea, Kazakhstan and Turkmenistanare rich in oil and gas resources. However, since the collapse of the Soviet Union in1991 and its independence from its system, it has experienced many major events in the past 20 years, such as political and economic reform, Russian financial crisis,global financial crisis, international raw material price fluctuation, etc., and socialeconomy has been blocked for many times. As a resource export-oriented country,energy export, especially oil and gas export, is becoming the main way forKazakhstan and Turkmenistan to exchange a large amount of foreign exchange. Onebelt, one road and one country, is the most important part of the regional economicdevelopment.With the development of remote sensing technology, it is possible to obtainhuman activities by using satellite remote sensing technology. Compared with thetraditional artificial means, remote sensing has the characteristics of short returnperiod, strong timeliness and large area synchronous observation, which provides thepossibility to realize the monitoring of oil and gas activities and the dynamicobservation of social economy. The powerful spatial management and spatial analysisfunctions of GIS provide strong technical support for it. At the same time, with thedevelopment of cloud platform technology, the cloud computing remote sensingplatform represented by Google Earth engine (GEE) makes it possible to extractgeographic information quickly and accurately on a large scale and in a large range.In view of the lack of oil and gas resources and the lack of location informationand attribute information of offshore drilling platforms in the Caspian Sea, this study,supported by remote sensing, GIS, google cloud platform and other technologies,adopts multi-temporal Landsat-7 / ETM +, DMSP / OLS, NPP / viirs and other remotesensing data automatically extract the spatial location, time and other attributeinformation of oil and gas exploitation activities in the Caspian Sea, establish the oilproduction capacity estimation based on remote sensing, explore the socio-economicdevelopment status of Kazakhstan and Turkmenistan with oil and gas industry as themain supporting industry, and finally form the data set of "oil and gas platform oil andgas production socio-economic" as one To provide technical support and relevantdecision-making information for further ensuring regional security and energy security in China. The main conclusions of this paper are as follows:(1) Static identification of Caspian Sea oil and gas platform: as one of the mainequipment of oil and gas exploitation, the information of space-time distribution andstate attribute of oil and gas platform directly reflects the development degree of oiland gas resources. Based on Landsat-7 / ETM + NDWI image, this paper presents amethod of automatic identification of oil and gas platform. Firstly, according to theimage characteristics of oil and gas platform on the Max_NDWI, Min_NDWI andmean_NDWI images, this paper selects water, oil and gas platform and bare landsamples and makes statistics of their NDWI value distribution. Then, according to theNDWI characteristics of water, bare land and oil and gas platform, a set is establishedto describe water (max_ NDWI > 0.55), bare land (Island) (min_ NDWI < - 0.05) andoil and gas platform (0 < mean_ According to the classification rule of NDWI < 0.4),the Landsat NDWI images of two consecutive years are used to synthesize the bestNDWI images. Through the verification of the location information of oil and gasplatforms in 2018 by high-resolution images such as Google Earth images andsentinel-2, we found that there are 526 oil and gas platforms in the Caspian Sea,including 497 oil and gas platforms automatically identified by the algorithm, 29 oiland gas platforms were missed (13 oil and gas platforms were covered by buffer zone),25 oil and gas platforms were mistakenly identified, the accuracy rate was 90.2%, theleakage rate was 5.3%, and the miscalculation rate was 4.5%. Among them, 13 oil andgas platforms are missed due to the setting of near shore buffer zone, and 14 oil andgas platforms are less than one pixel (30M) in size, At present, the remaining two oiland gas platforms cannot be verified; the main reason for the error recognition is thatthere is a small piece of bare land near the shore of the Caspian Sea area, whose widthis less than or nearly one pixel width (30M) and its length is generally greater than30m.(2) Temporal and spatial dynamic monitoring of Caspian oil and gas platforms: inorder to monitor the temporal and spatial dynamic changes of oil and gas platforms,this study uses the rolling continuous method to synthesize the Landsat images of2011-2018 into 7 long-term series NDWI images, and then generates 8 dynamicchange templates of oil and gas platforms, 8 dynamic change templates of bare landand 1 continuous water template through Gauss random function. Finally, through Theminimum distance classification method and uses Euclidean distance to classify thepixels, so as to monitor the spatiotemporal dynamic information of oil and gasplatform. Through the verification of time accuracy of dynamic monitoring of oil andgas platforms by Google Earth image, sentinel-2, PALSAR and other high-resolutionimages, we found that 390 oil and gas platforms out of 497 oil and gas platforms hadtheir starting time correctly classified, 107 were misclassified, and the accuracy ratewas 78.5%. The above research shows that the optimal NDWI method based on multitemporal Landsat Image synthesis is very effective for the automatic identificationand dynamic monitoring of the Caspian oil and gas platform.(3) Production estimation of offshore oil platforms: in view of the difficulty inobtaining the production information of offshore oil and gas resources, according tothe image characteristics of NPP / viirs night light image of natural gas productionplatforms and different production modes of oil production, the total amount of nightlight is used to quantify the intensity of offshore oil production, and then the oilproduction estimation based on night light remote sensing in Kazakhstan andTurkmenistan is established. The results show that the estimated oil production ofKazakhstan and Turkmenistan is consistent in the order of magnitude, and theestimation effect is good. The ratio of Kazakhstan's oil estimation to EIA's oilproduction ranges from 0.97 to 1.07, and the ratio to BP's oil production ranges from0.93 to 0.98. The ratio of Turkmenistan's estimated oil output to EIA's is between0.85-1.02, and that to BP's is between 0.83-0.98.(4) Research on Socioeconomic Development in Kazakhstan and Turkmenistan:In order to study the socio-economic development and changes of Kazakhstan andTurkmenistan in the past 30 years from 1992 to 2017, this paper analyzes the spatiotemporal dynamic development process and driving factors of social andeconomic development with the indexes of total night-time light (SNL) andnight-time light growth (PNLG), based on DMSP/OLS, NPP/VIIRS and yearbookdata. The results show that: 1) Night-time light can better characterize thespatiotemporal changes of the socio-economic development in Kazakhstan andTurkmenistan, and Night-time light remote sensing data is more intuitive andsensitive than socio-economic statistic data such as GDP; 2) The socio-economicreforms in the early period after independence had a large and wide impact onKazakhstan and Turkmenistan. The SNL of Kazakhstan declined largely, while TheSNL of Turkmenistan increased by 4.5%; 3) Due to differences in basic conditionsand resource endowments, the gap of social economic development in Kazakhstanand Turkmenistan has gradually widened, and the ability to resist risks has greatlyvaried, such as Global financial crisis of 2008. 4) Kazakhstan and Turkmenistan aresusceptible to the impact of international energy market prices, especially those of oiland gas.In conclusion, the method based on the best NDWI to automatically identify theCaspian oil and gas platform solves the problems of the lack of remote sensing images,low quality, large amount of calculation, false alarm, etc. in particular, in the aspect ofeliminating the influence of ships, it establishes the spatial-temporal dynamic data setof oil and gas exploitation activities in the Caspian Sea in the past seven years, andtimely, accurately and comprehensively grasps the oil and gas in the Caspian SeaMining situation. At the same time, it also studies the long-term socio-economicdevelopment of Kazakhstan and Turkmenistan around the Caspian Sea from differentspatial scales, solving the situation that there is no spatial information in previousstudies, and the research scale is limited to the state without further detailed scale, andthe time span is small and the continuity is weak, mainly focusing on a certain timenode. |
| Subject Area | 地图学与地理信息系统 |
| Language | 中文 |
| Document Type | 学位论文 |
| Identifier | http://ir.xjlas.org/handle/365004/15478 |
| Collection | 中国科学院新疆生态与地理研究所 研究系统 |
| Affiliation | 中国科学院新疆生态与地理研究所 |
| First Author Affilication | 中国科学院新疆生态与地理研究所 |
| Recommended Citation GB/T 7714 | 朱惠. 基于多时相 NDWI 里海油气平台识别[D]. 北京. 中国科学院大学,2020. |
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