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引用本文:刘德长,邱骏挺,童勤龙,谢涛,杨燕杰,王子涛. 新疆吉木萨尔地区油气渗漏与盐碱化相关性的航空高光谱遥感探测研究[J]. 中国地质, 2018, 45(5): 1062-1073.
LIU Dechang,QIU Junting,TONG Qinlong,XIE Tao,YANG Yanjie,WANG Zitao. Airborne hyperspectral study of spatial relationship between oil and gas leakage and salinization in Jimusar area[J]. Geology in China, 2018, 45(5): 1062-1073(in Chinese with English abstract).
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新疆吉木萨尔地区油气渗漏与盐碱化相关性的航空高光谱遥感探测研究
刘德长1, 邱骏挺1, 童勤龙1, 谢涛2, 杨燕杰1, 王子涛1
1.遥感信息与图像分析技术国家级重点实验室, 核工业北京地质研究院, 北京 100029;2.中国煤炭地质总局航测遥感局, 陕西 西安 710054
摘要:
笔者在新疆吉木萨尔地区开展航空高光谱遥感油气探测示范研究的过程中,发现油气渗漏地区往往有盐碱化现象。据此,利用航空高光谱成像系统在该区取得的可见光-近红外和短波红外遥感数据,采用自主开发的波段分类填图方法,对吉木萨尔农田、荒地和戈壁地区的油气渗漏异常信息进行了提取,经野外验证和化学分析,圈定了7处油气渗漏异常区。同时,构建了盐碱化的高光谱识别模型,利用该模型进行了盐碱化信息填图,并对吉木萨尔同一覆盖区的盐碱化异常进行了提取,圈定了盐碱化异常区。通过对油气渗漏异常区与盐碱化异常区的叠置聚焦分析,发现二者空间位置有高度的重合性。笔者认为这一高光谱遥感探测发现,不仅具有探索的理论意义,而且具有实用价值。其实用价值主要体现在高光谱遥感油气探测中,通过烃碱信息的相互印证,可以减少油气信息的漏判,提高油气渗漏信息识别的准确性。同时,在缺少航空高光谱遥感数据的情况下,还可以利用卫星多光谱遥感数据源,通过提取盐碱化异常和圈定盐碱化异常区的途径,帮助缩小找油气的目标区,为油气资源的调查、评价和选区提供新的信息和依据。上述研究同时表明,自然界的盐碱化可能并非全是由"干旱蒸发"形成,很可能还存在与油气有关的盐碱化,在油气勘查中如何区分这两种类型的盐碱化,特别是应用高光谱遥感技术将二者区分开来,是值得深入探讨的科学问题。
关键词:  航空高光谱遥感  CASI/SASI/TASI  油气渗漏异常  盐碱化异常  烃碱聚焦
DOI:10.12029/gc20180513
分类号:P631.3+4
基金项目:中国地质调查局油气资源调查中心工作项目(1211302108019-1)资助。
Airborne hyperspectral study of spatial relationship between oil and gas leakage and salinization in Jimusar area
LIU Dechang1, QIU Junting1, TONG Qinlong1, XIE Tao2, YANG Yanjie1, WANG Zitao1
1.National Key Laboratory of Science and Technology on Remote Sensing Information and Image analysis, Beijing Research Institute of Uranium Geology, Beijing 100029, China;2.Aerial Photogrammerty and Remote Sensing Bureau, China National Administration of Coal Geology, Xi'an 710054, Shaanxi China
Abstract:
Oil and gas leakages in the Jimusar area are spatially associated with salinization. In this study, the airborne hyperspectral image of the Jimusar region with a total area of 2500 km2 in Xinjiang was obtained by using CASI/SASI imagery of the National Key Laboratory of Science and Technology on Remote Sensing Information and Image analysis. The dataset was used to extract oil leakage information by using newly developed classification method. Seven oil leakage areas were detected. In addition, the extraction model for soil salt was also developed and applied to study the distribution of soil salt in the Jimasar region. Based on the superposition analysis of oil and gas anomaly area and salinization anomaly area, the authors detected a high degree of coincidence in the spatial location of the two ares. The authors believe that this hyperspectral remote sensing detection not only has theoretical significance but also has practical value. Its practical value is mainly reflected in the hyperspectral remote sensing oil and gas exploration. Through the mutual confirmation of hydrocarbon information, one can reduce redundant information of oil and gas leakage and improve the accuracy of oil and gas leakage identification. Additionally, in the absence of aerospace hyperspectral remote sensing data sources, satellite multispectral remote sensing data can also be used to extract the salinization anomalies and delineate the anomalous areas of salinization and alkalinization, thereby helping to narrow the target areas for oil and gas exploration. The results obtained by the authors indicate that the salinization of nature may not be wholly attributed to "dry evaporation", and there may be oil and gas related salinization. The distinguishing between these two kinds of salinization is a scientific problem worthy of in-depth discussion, especially in the field of hyperspectral remote sensing.
Key words:  airborne hyper-spectral image  CASI/SASI/  oil leakage information  soil salt anomalies  combination of oil and soil salt information