地质矿产部海洋沉积开放研究实验室举行揭牌暨第一届学术委员会第一次会议

地质矿产部海洋沉积开放研究实验室举行揭牌暨第一届学术委员会第一次会议ＴＨＥＵＮＶＥＩＬＩＮＧＣＥＲＥＭＯＮＹＡＮＤＴＨＥ１ＳＴＭＥＥＴＩＮＧＯＦＴＨＥＡＣＡＤＥＭＩＣＣＯＭＭＩＴＴＥＥＯＦＴＨＥＯＰＥＮＬＡＢＯＲＡＴＯＲＹＦＯＲＭＡＲＩＮＥＳＥＤＩＭ...     

缺少密度或孔隙度测定数据的块体堆积速率的计算

缺少密度或孔隙度测定数据的块体堆积速率的计算Ｔ．Ｊ．Ｓ．Ｓｙｋｅｓ等块体堆积速率（ＭＡＲ）计算已被应用于深海钻探计划（ＤＳＤＰ）和大洋钻探计划（ＯＤＰ）岩心，以研究大洋盆地的沉积物演化，或把ＭＡＲ数据分离成岩石学成分以决定方解石补偿深度（ＣＣＤ）的历...     

经略２１世纪海上丝路之海洋环境特征：极值风速和极值波高

极值风速和极值波高是海洋工程、海洋能开发、防灾减灾等极为关注要素。文章基于来自欧洲中期天气预报中心（ＥＣＭＷＦ）的ＥＲＡ－ｉｎｔｅｒｉｍ 海浪再分析资料、ＥＲＡ 阵风资料,计算了“２１世纪海上丝绸之路”涉及海域的年极值风速、极值波高,并首次计算了不同季节的极值。结果表明：①南海的５０年一遇年极值风速大于孟加拉湾,孟加拉湾大于阿拉伯海;极值波高的分布特征与极值风速大体一致。②南海的极值风速在各个季节都大于孟加拉湾,孟加拉湾大于阿拉伯海;南海－ 北印度洋的极值风速在ＪＪＡ 和ＳＯＮ 期间明显大于ＭＡＭ 期间,ＤＪＦ期间最小。③南海各个季节的极值波高都大于北印度洋,阿拉伯海的极值波高在ＭＡＭ和ＪＪＡ 期间明显大于孟加拉湾;南海的极值波高在ＪＪＡ 和ＳＯＮ 期间明显大于ＭＡＭ 和ＤＪＦ期间;北印度洋的极值波高在ＪＪＡ 期间最大,ＭＡＭ 次之,ＤＪＦ最小。     

矿产地质学家谭启新研究员简介

矿产地质学家谭启新研究员简介ＢＲＩＥＦＩＮＴＲＯＤＵＣＴＩＯＮＯＦＰＲＯＦ．ＴＡＮＱＩＸＩＮ，ＡＭＩＮＥＲＡＬＲＥＳＯＵＲＣＥＧＥＯＬＯＧＩＳＴ谭启新研究员，１９６０—１９６５年就读于长春地质学院地质系，毕业后，就职于陕西省地矿局、山东省地矿局，１９...     

珠江（广州河段）沉积物中砷形态的存在及迁移特征

根据珠江（广州河段）沉积物中Ａｓ（Ｔ），Ａｓ（Ⅲ），Ａｓ（Ⅴ），ＭＭＡ，ＤＭＡ含量与Ｆｅ，Ａｌ，Ｋ，Ｃａ，Ｍｇ及有机碳含量，研究了南亚热带近河口区沉积物中Ａｓ形态的存在特征，并计算ＡＳ形态间及与其它元素间的相关性，从而说明ＡＳ形态在河口区的存在及迁移特征。     

珠江（广州河段）沉积物中砷形态的存在及迁移特征

根据珠江（广州河段）沉积物中Ａｓ（Ｔ），Ａｓ（Ｖ），ＭＭＡ，ＤＭＡ含量与Ｆｅ，Ａｌ，Ｋ，Ｃａ，Ｍｇ及有机碳含量，研究了南亚热带近河口区沉积物中Ａｓ形态的存在特征，并计算Ａｓ形态间及与其它元素间的相关性，从而说明Ａｓ形态河口区的存在及迁移特征。     

关于龙门山区二叠纪灰岩飞来峰成因与时代的讨论

关于龙门山区二叠纪灰岩飞来峰成因与时代的讨论ＤＩＳＣＵＳＳＩＯＮＳＯＮＯＲＩＧＩＮＡＮＤＴＩＭＥＯＦＰＥＲＭＩＡＮＬＩＭＥＳＴＯＮＥＫＬＩＰＰＥＩＮＬＯＮＧＭＥＮＭＯＵＮＴＡＩＮＡＲＥＡ四川龙门山地区二叠纪灰岩超覆在中晚侏罗世地层之上的事实，早在我国...     

JB—1型交流磁场退磁仪的研制

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珍惜自然资源 保护地球环境——纪念世界地球日28周年

珍惜自然资源保护地球环境——纪念世界地球日２８周年ＣＨＥＲＩＳＨＮＡＴＵＲＡＬＲＥＳＯＵＲＣＥＳＡＮＤＰＲＯＴＥＣＴＴＨＥＥＡＲＴＨＥＮＶＩＲＯＮＭＥＮＴ——ＤＥＤＩＣＡＴＥＤＴＯＴＨＥ２８ＴＨＡＮＮＩＶＥＲＳＡＲＹＯＦＴＨＥＷＯＲＬＤＥＡＲＴＨＤＡ...     

青年海洋地质学家姚德副研究员简介

青年海洋地质学家姚德副研究员简介ＢＲＩＥＦＩＮＴＲＯＤＵＣＴＩＯＮＯＦＤＲ．ＹＡＯＤＥ，ＭＡＲＩＮＥＧＥＯＬＯＧＩＳＴ姚德副研究员，１９８４年毕业于长春地质学院地球化学专业，１９８７年在长地院获硕士学位，１９９３年在中国科学院海洋研究所获博士学位。现...     

基于ARMA模型的海浪功率谱估计方法研究

针对经典功率谱估计方法的一些缺点,对随即海浪过程进行了ARMA谱估计的仿真研究,仿真的结果表明ARMA功率谱估计方法在分辨率、平滑和偏差等方面更加有效。     

关于海浪ARMA模型的研究

本文研究了用ＡＲＭＡ模型描述海浪运动的数学模型。通过ＡＲＭＡ模型的参数估计，给出了描述海浪运动的ＡＲＭＡ模型，利用仿真数据进行了拟合检验。结果表明：本文提出的海浪ＡＲＭＡ模型是一种非常理想的数学模型，且适于在线递推运算，便于工程应用。     

有ARMA噪声的一种参数估计的优效性

对于有ARMA噪声的线性回归模型,本文给出了只用递推进行模型辨识和参数估计的线性方法。若用所计算得到的回归残差作为数据,采用Hannan-Rissanen的线性估计法求ARMA噪声的参数估计,则本文证明了估计是强相容的,且对正态序列,估计具有渐近正态优效性。     

浒苔水体光谱特征参量时间序列数据拟合研究

开展时间序列浒苔水体光谱特征参量的拟合研究可为寻求最佳拟合方法,从而对进一步开展大尺度的高光谱高空间高时间分辨率遥感动态实时监测具有重要的参考价值。在实验室培养3种不同浓度的浒苔水体,用ASD光谱仪测定并获取浒苔水体的时间序列反射光谱,基于反射光谱定量提取光谱特征参量,构建时间序列数据;应用曲线拟合和时间序列ARMA模型开展浒苔水体光谱特征参量的时间序列拟合研究。结果表明:应用二阶或三阶多项式和ARMA模型可较高精度地拟合浒苔水体的光谱特征参量;但时间序列ARMA模型比多项式拟合模型更能反映浒苔水体光谱特征参量的时间序列数据的分布和变动特性。该研究可为浒苔灾害动态监测业务化运行部门提供浒苔光谱数据,同时也为光谱数据的处理和分析提供一种新的方法。     

Blind Submarine Seismic Deconvolution for Long Source Wavelets

In seismic deconvolution, blind approaches must be considered in situations where reflectivity sequence, source wavelet signal, and noise power level are unknown. In the presence of long source wavelets, strong interference among the reflectors contributions makes the wavelet estimation and deconvolution more complicated. In this paper, we solve this problem in a two-step approach. First, we estimate a moving average (MA) truncated version of the wavelet by means of a stochastic expectation-maximization (SEM) algorithm. Then, we use Prony's method to improve the wavelet estimation accuracy by fitting an autoregressive moving average (ARMA) model with the initial truncated wavelet. Moreover, a solution to the wavelet initialization problem in the SEM algorithm is also proposed. Simulation and real-data experiment results show the significant improvement brought by this approach.     

伪近邻方法在ARMA系统阶数判别中的应用

从相空间重构的角度,提出利用伪近邻方法判别ＡＲＭＡ 系统的总阶数。该方法可在数据量较小和阈值固定的情况下判别ＡＲＭＡ 系统总阶数。数值计算表明,使用该方法判别线性ＡＲＭＡ系统总阶数,取得了比较满意的结果。     

Refined autoregressive moving average modeling of underwater heaveprocess

Earlier treatments of the underwater dynamic motion effects including the heave, or vertical dynamic motion, phenomenon relied on frequency response methods and Kalman filtering for the compensation task. An alternative model of the heave process is proposed. The model is based on transforming the underlying time series using exponential operations and then finding autoregressive integrated moving-average (ARIMA) representations of the time series. A refined ARMA model based on modeling of a series of innovations is also proposed. A computational comparison of the performance of two estimators is conducted using a real heave record as a base case. The refined ARMA model gives better results than the other alternative models investigated     

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.     

Processing irregular wave measurements to enhance point absorber power capture performance

The paper aims at introducing practical methods for power capture performance enhancement of a heaving wave energy converter in irregular seas. The optimum control solution requires tuning to wave frequency based on wave force information. However, identification of the wave frequency in irregular seas is considered to be a complex and difficult task. This is partly due to technical difficulties in determination of the wave force. Besides, there are no clear guidelines for identification of wave frequency from an irregular sea state based wave force information. In a typical application, one of the available sources of information about the wave properties is the wave elevation record. The proposed approach presents a method for estimation of the wave frequency information from the wave elevation data by using signal processing and filtering techniques. The proposed method uses filters to generate an estimation of wave force information, which is used to identify the local wave frequency by method of a time-series analysis of the data. This wave frequency information is then used in tuning the device. The details of the proposed techniques, the model of the wave energy converter, the simulated sea states and the related simulation results are also presented.     

Correlation between individual waves in a real sea state

The correlation between individual waves in a real sea state has a central role in existing theories of wave grouping. The attractive Kimura (1980) theory has two critical assumptions, that the sequence of individual wave heights follows a Markov process and that the joint distribution of consecutive wave heights follows a bivariate Rayleigh form. Analysis of measured water surface records suggests that sequences of individual waves can reasonably be described as a first order mixed autoregressive, moving-average or ARMA process, though a distinction among ARMA (1,0), ARMA (0,1) and ARMA (1,1) models was beyond the resolution of the data. These include the Markov or ARMA (1,0) model. The decisive detail, the joint distribution of consecutive wave heights in the sea state, was evaluated by a simulation methodology that is consistent with the Gaussian random wave model. The estimates are dependent on spectral shape and are consistently narrower and more sharply focussed at the peak than the corresponding bivariate Rayleigh estimate. The resulting predictions of run and group length statistics differ from the Kimura theory, though not by a sufficient margin to displace the Kimura theory as a pragmatic choice for wave grouping.