Seismic attenuation estimation using a complete ensemble empirical mode decomposition-based method

The frequency attenuation gradient method can provide important information for hydrocarbon detection. In this paper, a method using Complete Ensemble Empirical Mode Decomposition (CEEMD), Hilbert transform and the least-squares curve-fitting is proposed for seismic attenuation estimation as an effective frequency attenuation gradient estimation approach. We first use CEEMD to obtain the different Intrinsic Mode Functions (IMFs), which have a narrow band and can enhance the physical meaning of instantaneous attributes trace by trace. The time-frequency spectrum, which is computed using a Hilbert transform of each IMF, is represented as a spectrum with a single-peak that has narrow side lobes, which is conducive to frequency attenuation gradient estimation. Second, for each time sample, the frequency-amplitude spectrum of each IMF trace is extracted from the time-frequency spectrum to conduct the attenuation gradient computation. Then, the logarithm operation is performed for each IMF trace. Due to the very narrow bands of some IMFs in some seismic traces, a variable frequency window is adopted along the IMF trace according to the local data characteristics. Finally, the attenuation gradient for each IMF in a seismic trace can be computed using least-squares fitting. A different IMF reflects a seismic trace with a different spatiotemporal scale and can highlight different geologic and stratigraphic information. The correlation weighted average operation is used to highlight some useful details in seismic trace and obtains the attenuation gradient for each seismic trace. Field data examples demonstrate our method and its effectiveness. The proposed method can stably estimate the frequency attenuation gradient.     

Application of multi-seismic attributes analysis in the study of distributary channels

During the exploration of stratigraphic reservoirs, the key to locating these reservoirs is to identify the sandstone distribution. Seismic data can be used to recognize large-scale distributary-channel sedimentary bodies; however, depiction of sedimentary bodies in small distributary channels using traditional interpretation data from seismic profiles is extremely difficult. In the Upper Cretaceous first sandstone bed of the third member of the Nenjiang Formation (called the Nen 3 member for simplicity) in the XB area of the southern Songliao basin, distributary channels are the main sedimentary facies. The distributary channels migrate frequently; therefore, it is difficult to precisely depict the morphology of the channel and the distribution of sandstone. In this study, we investigated the deposition of distributary channels using equal-scale formation plane seismic attributes such as post-stack amplitude, instantaneous amplitude and seismic waveform classification, analyzed well logging data from target formations, and mapped the distribution of distributary channels. This study shows that seismic sedimentological study and stacking multiple attribute analysis can identify the distribution of distributary channels precisely and effectively. The attributes of equal-scale strata slices are evidently superior to those of time and horizon slices; Attribute extraction and selection of equal-scale formation slices is an essential step. The comprehensive selection of seismic attributes that show a good correlation to a single-well can be used to clearly depict channel bodies. The overlap of the 40-Hz single-frequency energy and the RMS amplitude depicts the sedimentary characteristics and shapes of sandstone bodies in main channels as well as small-scale distributary channels more clearly than a single attribute. These attributes show that the first sandstone bed of the Nen 3 member was from distributary channels with complex shapes. The distributary channels cut across each other vertically and laterally. It indicates that, during the deposition of the Nen 3 member in XB area, the direction of the main channel is from north to south, and the provenance could be from north and east. The method of this paper may provide some helpful suggestions to the geologist using seismic attributes to undertake research on sedimentary environment at other places in the world.     

频谱分解技术在泥页岩储层含气性预测中的应用——以柴达木盆地鱼卡凹陷为例

针对柴达木盆地北缘鱼卡凹陷中侏罗统大煤沟组泥页岩,利用地震频谱曲线在不同流体介质储层中的形态、斜率、主频与中心频率的差值等属性参数特征,识别陆相泥页岩层系的地震频谱属性特征,预测含气性。研究结果表明,中侏罗统大煤沟组上部能量系数较低,平均为0.6719,下部能量系数较高,平均为0.7521,结合现场含气量和全烃特征认为,可以以能量系数0.7为界线,作为识别下部和上部含气性的标志,下部明显比上部含气性好。平面上进一步圈定了2个有利目标区,得到柴页1井勘探验证。因此,频谱分解技术可应用于中国陆相页岩气的勘查开发。     

微波消解-电感耦合等离子体质谱法测定海泡石中的稀土元素

海泡石是一种纤维状含水的富镁硅酸盐黏土矿,其中的稀土元素含量在1×10~(-7)～1×10~(-5)之间,目前还没有建立海泡石中稀土元素的国家标准分析方法。测定岩石中的稀土元素主要是采用电感耦合等离子体质谱法(ICP-MS),样品前处理一般采用封闭溶矿和碱熔,但这两种处理方法耗时较长,效率不高。本文通过比较硝酸-氢氟酸-过氧化氢、硝酸-氢氟酸、硝酸-过氧化氢三种样品前处理方法,确定使用硝酸-氢氟酸溶矿,然后进行微波消解同时赶去氢氟酸,避免氢氟酸与稀土元素生成难溶的氟化物,再采用ICP-MS法测定15种稀土元素的含量。由于海泡石中的镁含量较高,为降低基体效应,以~(103)Rh和~(185)Re作内标补偿基体效应和校正灵敏度漂移,各元素测定值的准确性显著提高,回收率为91. 2%～110. 9%,检出限为0. 002～0. 011μg/L,精密度≤2. 79%。本方法与封闭酸溶ICP-MS法的分析结果吻合较好,且用酸量少(7 mL),溶矿效率高(1 h),检出限更低。     

2000-2014年西藏雅鲁藏布江流域积雪时空变化分析及对气候的响应研究

利用2000-2014年MODIS逐日无云积雪产品对雅鲁藏布江流域积雪特征的空间分布及变化、积雪随高程变化的规律进行了分析,并采用被动微波数据SMMR （1979-1987年）和SSM/I （1988-2008年）以及中国地面降水和气温0.5°×0.5°日值格点数据集,研究了雅鲁藏布江流域关键积雪参数对气候要素的响应等。结果表明：流域下游积雪日较大且变化剧烈;流域整体上呈显著减少的趋势;积雪日随高程的上升而增加;流域内降水呈不显著的增加趋势,而气温呈显著的增加趋势,最高气温对积雪变化影响最大;气温对积雪终日的影响明显高于积雪初日;在积雪消融期降水的增多促进了积雪的消融。     

微波辐射计在对流天气预报中的应用

选取2016—2018年每年4—9月份RPG-HATPRO型42通道微波辐射计观测的不稳定指数参数(K、SI、CAPE、LI)及水汽参数(IWV、LWP),研究得出各参数触发雷雨大风、短时强降水的阈值条件为K>37℃、SI<-1℃、IWV>60 kg/m~2、LWP>400 g/m~2,而LI、CAPE无法对3种天气类型进行区分。利用费舍判别分析方法,将不稳定指数参数及水汽参数作为预报因子,建立预报方程并进行检验,结果表明:二级判别方程预测对流天气的准确率为76%,可以作为预报对流天气的辅助工具;多级判别方程不能很好地区分3种天气类型,但将其作为修正后的二级判别方程使用,能提高对流天气的测中概率。     

磁法三维建模在龙王沟磁铁矿勘探中的应用

以龙王沟磁铁矿高精度磁测数据为基础,采用小波多尺度分解方法,对化极后的磁法数据进行多尺度分解,通过功率谱法计算小波多尺度分解后的各阶细节异常的场源深度。结合地形、地质及钻孔资料,采用2.5D人机交互反演对磁测剖面上的磁铁矿体进行拟合,利用Golden Software公司开发的Voxler软件,在虚拟三维环境下实现二维小波多尺度分解数据的可视化,建立三维地质体模型,直观的预测磁铁矿体的空间范围和分布形态,实现地质、物探和地上、地下信息一体化集成展示,进行专业分析评价和辅助决策,可以有效的提高地质找矿效果。     

积雪变化对中国森林凋落物分解影响研究进展

森林凋落物的分解对于维持生态系统物质循环和养分平衡具有重要意义,并受到不同积雪厚度下冻融格局的影响。冻融期（包括冻结过程期、完全冻结期、融化过程期）是冻土区凋落物分解的重要时期,该时期分解的凋落物量约占全年分解总量的一半。积雪减少通常会导致土壤温度降低、冻融循环次数增加,进而影响凋落物分解。通过综述近10年来积雪变化对我国森林凋落物分解影响的研究成果发现,积雪厚度减少在冻融期通常会抑制凋落物质量损失、碳元素释放和纤维素降解,生长季则起到促进作用,从全年来看多数表现为抑制作用。因此,冻融作用造成凋落物的物理破坏,对其分解的促进作用主要发生在后续生长季。积雪厚度减少在冻融期通常抑制氮元素释放,生长季和全年则无明显规律;磷元素和木质素目前研究还存在很大差异。最后,进一步阐述了积雪变化对凋落物分解影响研究存在的问题及未来研究发展方向。     

基于优化经验模态分解和聚类分析的滑坡位移智能预测研究

针对三峡库区"阶跃式"滑坡的变形特征,提出了一种新的滑坡位移预测方法。以白水河滑坡ZG118和XD-01监测点位移数据为例,采用基于软筛分停止准则的经验模态分解(SSSC-EMD)将累计位移-时间曲线和影响因子时间序列自适应地分解为多个固有模态函数(IMF),并采用K均值(K-Means)聚类法对其进行聚类累加,得到有物理含义的位移分量(趋势性位移、周期性位移以及随机性位移)和影响因子分量(高频影响因子和低频影响因子)。使用最小二乘法对趋势性位移进行拟合预测;采用果蝇优化-最小二乘支持向量机(FOA-LSSVM)模型对周期性位移和随机性位移进行预测。将各位移分量预测值进行叠加处理,实现滑坡累计位移的预测。研究结果表明,所提出的(SSSC-EMD)-K-Means-(FOA-LSSVM)模型能够预测"阶跃式"滑坡的位移变化规律,且预测精度高于传统的支持向量机回归(SVR)、最小二乘支持向量机(LSSVM)模型;并通过改变训练集长度,进行单因素分析,发现其与预测精度之间呈正相关关系。     

Latitudinal and Scan-dependent Biases of Microwave Humidity Sounder Measurements and Their Dependences on Cloud Ice Water Path

The relationship between differences in microwave humidity sounder(MHS)–channel biases which represent measured brightness temperatures and model-simulated brightness temperatures, and cloud ice water path(IWP) as well as the influence of the cloud liquid water path(LWP) on the relationship is examined. Seven years(2011–17) of NOAA-18 MHS-derived measured brightness temperatures and IWP/LWP data generated by the NOAA Comprehensive Large Array-data Stewardship System Microwave Surface and Precipitation Products System are used. The Community Radiative Transfer Model, version2.2.4, is used to simulate model-simulated brightness temperatures using European Center for Medium-Range Weather Forecasts reanalysis data as background fields. Scan-angle deviations of the MHS window channel biases range from-1.7 K to1.0 K. The relationships between channels 2, 4, and 5 biases and scan angle are symmetrical about the nadir. The latitudedependent deviations of MHS window channel biases are positive and range from 0–7 K. For MHS non-window channels,the latitudinal deviations between measured brightness temperatures and model-simulated brightness temperatures are larger when the detection height is higher. No systematic warm or cold deviations are found in the global spatial distribution of difference between measured brightness temperatures and model-simulated brightness temperatures over oceans after removing scan-angle and latitudinal deviations. The corrected biases of five different MHS channels decrease differently with respect to the increase in IWP. This decrease is stronger when LWP values are higher.