<Emphasis Type="Italic">Q</Emphasis> value structure of geoscience transect from Korla to Jimsar and its geodynamic implication

In this paper, the methods for Q value inversion in 2-D lateral inhomogeneous medium have been introduced. The 2-D Q value inversion has been conducted using seismic wide-angle reflection/refraction data of the profile from Korla to Jimsar. The result shows that the 2-D Q value structure of the transect from Korla to Jimsar is characterized by vertical stratifying and lateral zoning. Vertically, the crust can be divided into upper crust, middle crust and lower crust with the Q value increasing downwards. Horizontally, the total transect can be classified as three regions— the northern margin of the Tarim Basin, the Tianshan orogenic belt (TOB) and the southern margin of the Junggar Basin. At the northern margin of the Tarim Basin the Q value increases northwards, indicating a northward subduction of the Tarim Basin into the The Q value within the TOB jumps near Kumux, making a stage-like difference in Q value. The Q value distribution at the southern margin of the JB suggests a southward subduction of the Junggar Basin (JB) into the The double subduction pattern of the and JB into the TOB revealed by the transect from Korla to Jimsar has a big difference from the model “lithospheric subduction with intrusion of the layers into the crust” developed according to the results of the geoscience transect from Xayar to Burjing. The differences between the two provide some dynamic evidence at lithospheric scale for the segmentation of the Zhang Xiankang, Zhang Chengke, Jia Shixu et al., A summary report on exploration and research on GGT (in Chinese), 1999 Xu Xinzhong, A summary report on the results of seismic exploration on the comprehensive geophysical profile from Kktuohai to Aksai (in Chinese), 1990     

Polar Sea Ice Identification and Classification Based on HY-2A/SCAT Data

In this paper,a Bayesian sea ice detection algorithm is first used based on the HY-2A/SCAT data,and a backpropagation(BP)neural network is used to classify the Arctic sea ice type.During the implementation of the Bayesian sea ice detection algorithm,linear sea ice model parameters and the backscatter variance suitable for HY-2A/SCAT were proposed.The sea ice extent obtained by the Bayesian sea ice detection algorithm was projected on a 12.5 km grid sea ice map and validated by the Advanced Microwave Scanning Radiometer 2(AMSR2)15%sea ice concentration data.The sea ice extent obtained by the Bayesian sea ice detection al-gorithm was found to be in good agreement with that of the AMSR2 during the ice growth season.Meanwhile,the Bayesian sea ice detection algorithm gave a wider ice edge than the AMSR2 during the ice melting season.For the sea ice type classification,the BP neural network was used to classify the Arctic sea ice type(multi-year and first-year ice)from January to May and October to De-cember in 2014.Comparison results between the HY-2A/SCAT sea ice type and Equal-Area Scalable Earth Grid(EASE-Grid)sea ice age data showed that the HY-2A/SCAT multi-year ice extent variation had the same trend as the EASE-Grid data.Classification errors,defined as the ratio of the mismatched sea ice type points between HY-2A/SCAT and EASE-Grid to the total sea ice points,were less than 12%,and the average classification error was 8.6%for the study period,which indicated that the BP neural network classification was a feasible algorithm for HY-2A/SCAT sea ice type classification.     

咸化湖盆细粒重力流沉积特征及其页岩油勘探意义——以准噶尔盆地玛湖凹陷风城组为例

细粒重力流沉积作用是咸水深湖环境重要的沉积作用过程之一,它能把浅水细粒碎屑和有机质搬运到深湖,形成页岩油的甜点储层和优质源岩。开展咸化湖盆细粒重力流沉积特征的研究对陆相盆地页岩油评价具有重要的意义。准噶尔盆地玛湖凹陷风城组(P₁f)沉积时期发育了一套咸水湖泊环境下的湖底扇沉积体系,研究表明该体系扇缘可发育8类细粒重力流岩相组合：(1)细粒浓缩密度流-细粒过渡流-细粒碎屑流岩相组合;(2)细粒异重流岩相组合;(3)细粒浓缩密度流-细粒碎屑流岩相组合;(4)细粒浓缩密度流-泥流-安静水体空落岩相组合;(5)细粒过渡流-细粒碎屑流岩相组合;(6)细粒碎屑流-泥流岩相组合;(7)细粒碎屑流-湍流尾流岩相组合;(8)细粒下部过渡塞流-细粒上部过渡塞流-准层状泥(塞)流岩相组合。这8种岩相组合是细粒重力流沉积作用相互转化的结果,它们属于不完整的混合事件层,可构成一个完整的混合事件层。咸化湖盆、深层热卤水和凝灰质的加入使该湖底扇沉积体系的沉积物普遍含白云石、碳酸钠钙石、苏打石和硅硼钠石等矿物。其中,白云石为化学沉淀的方解石在准同生期和浅埋期形成的准同生白云石,碳酸钠钙石、苏打石...     

一次典型CINRAD/SA接收机动态范围异常分析与处理

从一次典型的CINRAD/SA雷达数字化接收机动态范围异常故障人手,分析了影响接收机动态范围和动态极限性能扩展的主要因素,重点对动态异常进行了翔实分析.通过分步、分模块的动态范围调整与故障排查等一系列过程,详细诊断了导致接收机动态范围异常的故障原因,并迅速、准确的定位了故障单元,为数字中频接收机故障维修提供方法与借鉴.