Sharp spatially constrained inversion with applications to transient electromagnetic data

Time‐domain electromagnetic data are conveniently inverted by using smoothly varying 1D models with fixed vertical discretization. The vertical smoothness of the obtained models stems from the application of Occam‐type regularization constraints, which are meant to address the ill‐posedness of the problem. An important side effect of such regularization, however, is that horizontal layer boundaries can no longer be accurately reproduced as the model is required to be smooth. This issue can be overcome by inverting for fewer layers with variable thicknesses; nevertheless, to decide on a particular and constant number of layers for the parameterization of a large survey inversion can be equally problematic. Here, we present a focusing regularization technique to obtain the best of both methodologies. The new focusing approach allows for accurate reconstruction of resistivity distributions using a fixed vertical discretization while preserving the capability to reproduce horizontal boundaries. The formulation is flexible and can be coupled with traditional lateral/spatial smoothness constraints in order to resolve interfaces in stratified soils with no additional hypothesis about the number of layers. The method relies on minimizing the number of layers of non‐vanishing resistivity gradient, instead of minimizing the norm of the model variation itself. This approach ensures that the results are consistent with the measured data while favouring, at the same time, the retrieval of horizontal abrupt changes. In addition, the focusing regularization can also be applied in the horizontal direction in order to promote the reconstruction of lateral boundaries such as faults. We present the theoretical framework of our regularization methodology and illustrate its capabilities by means of both synthetic and field data sets. We further demonstrate how the concept has been integrated in our existing spatially constrained inversion formalism and show its application to large‐scale time‐domain electromagnetic data inversions.     

接地导线源电磁场全域有效趋肤深度

为了更好地推进广域电磁法的发展和应用,本文以接地长导线源为例,研究了可控源电磁场全场域的有效趋肤深度.利用频域电偶极源在均匀半空间产生电磁场的闭合表达式,计算了不同电磁场分量定义的有效趋肤深度,并讨论了在不同频率、不同偏移距、不同电导率情况下,有效趋肤深度的变化特性.根据有效趋肤深度随偏移距的变化特征以及与平面波趋肤深度之间的关系,利用多项式拟合的办法在五个不同频率范围内给出了适用于全场域的有效趋肤深度快速估算公式.研究结果表明：不同分量定义的有效趋肤深度是不同的,但是它们随偏移距、频率、电导率等参数的变化趋势是类似的,而且在一定范围内都趋近于平面波趋肤深度.理论模型的研究表明,有效趋肤深度可以作为测量参数选取和数据解释工作的参考依据.     

磁源瞬变电磁法应用及其方法技术

归纳磁源瞬变电磁法在地质矿产、地质灾害和工程地质中的勘查应用,并对该方法的野外数据采集、资料处理等方法技术进行了探讨。     

雷琼地区晚新生代玄武岩地球化学：EM2成分来源及大陆岩石圈地幔的贡献

对雷琼地区21个晚新生代玄武岩样品的主量、微量元素和Sr、Nd、Pb同位素分别用湿化学法、ICP-MS和MC-ICPMS进行了测定.这些玄武岩主要为石英拉斑玄武岩,其次为橄榄拉斑玄武岩和碱性玄武岩.大多数样品的微量元素和同位素成分与洋岛玄武岩(OIBs)相似,而且随着SiO_2不饱和度增加,不相容元素含量也增加.除R4-1可能受到地壳混染外,其他样品相对均一的Nd同位素(ε_(Nd)=2.5-6.0)以及变化明显但范围有限的Sr同位素(0.703106～0.704481),可能继承了地幔源区的特征.~(87)Sr/~(86)Sr与~(206)Pb/~(204)Pb的正相关和~(143)Nd/~(144)Nd与~(206)Pb/~(204)Pb的负相关特征暗示DM(软流圈地幔)与EM2(岩石圈地幔)的混合.地幔捕虏体的同位素特征暗示EM2成分不可能存在于尖晶石橄榄岩地幔,而La/Yb和Sm/Yb系统表明岩浆由石榴石橄榄岩部分熔融产生,这意味着EM2成分可能存在于石榴石橄榄岩地幔.雷琼地区玄武岩的地球化学变化可以用软流圈地幔为主的熔体加入不同比例石榴石橄榄岩地幔不同程度熔融产生的熔体来解释:碱性玄武岩和橄榄拉斑玄武岩是软流圈熔体与石榴石橄榄岩地幔较低程度(7%～9%)熔融体混合,而石英拉斑玄武岩是软流圈熔体与石榴石橄榄岩地幔较高程度(10%～20%)熔融体的混合.     

基于自适应参数估计的多时相遥感图像变化检测

提出一种基于自适应参数估计实现多时相遥感图像的变化检测算法.首先应用分层Markov随机场模型建立多时相差分图像的统计模型;然后通过非监督的迭代自适应参数估计实现差分图像的分类,从而检测出变化的像元.在每次参数估计过程中,先将上次估计出的参数用于最大后验估计实现差分图像的分类,然后根据分类结果再对参数进行修正,并将修正后的参数用于下一次迭代分类,如此循环迭代,能够自适应地完成差分图像的参数估计与分类.     

Electromagnetic induction prediction of soil salinity and groundwater properties in a Tunisian Saharan oasis

Abstract

Electromagnetic induction measurements (EM) were taken in a saline gypsiferous soil of the Saharan-climate Fatnassa oasis (Tunisia) to predict the electrical conductivity of saturated soil extract (ECe) and shallow groundwater properties (depth, Dgw, and electrical conductivity, ECgw) using various models. The soil profile was sampled at 0.2 m depth intervals to 1.2 m for physical and chemical analysis. The best input to predict the log-transformed soil salinity (lnECe) in surface (0–0.2 m) soil was the EMh/EMv ratio. For the 0–0.6 m soil depth interval, the performance of multiple linear regression (MLR) models to predict lnECe was weaker using data collected over various seasons and years (R _a ² = 0.66 and MSE = 0.083 dS m^-1) as compared to those collected during the same period (R _a ² = 0.97, MSE = 0.007 dS m^-1). For similar seasonal conditions, for the Dgw–EMv relationship, R ² was 0.88 and the MSE was 0.02 m for Dgw prediction. For a validation subset, the R ² was 0.85 and the MSE was 0.03 m. Soil salinity was predicted more accurately when groundwater properties were used instead of soil moisture with EM variables as input in the MLR.

Editor D. Koutsoyiannis; Associate editor K. Heal

Citation Bouksila, F., Persson, M., Bahri, A., and Berndtsson, R., 2012. Electromagnetic induction predictions of soil salinity and groundwater properties in a Tunisian Saharan oasis. Hydrological Sciences Journal, 57 (7), 1473–1486.     

基于Landsat数据的2种地表温度空间降尺度算法比较研究

以2003年5月29日福州市LandsmETM＋影像为数据源,对2种地表温度空间降尺度算法——EM算法和HUTS算法进行实验、比较与分析,EM算法是利用高空间分辨率的地表比辐射率对低空间分辨率的亮度温度影像进行调节,从而达到提高热红外影像空间分辨率的目的;HUTS算法则是引入了归一化差异植被指数NDVI和地表反照率d,通过在低空间分辨率拟合二者与地表温度LST之间的关系,然后根据其尺度不变性,将该关系应用到高空间分辨率的影像上,从而达到提高热红外影像空间分辨率的目的．研究结果表明：1）2种算法所得结果影像都能在有效提高空间分辨率的同时较好地保持了原始地表温度影像的空间分布特征,达到了较好的降尺度效果;2）以RMSE为定量评价指标,HUTS算法要略优于EM算法,其中,EM算法的RMSE为1．2494,而HUTS算法仅为0．9869．     

Electromagnetic anomaly before earthquakes measured by electromagnetic experiments

Three experiments are carried out for earthquake monitoring using electromagnetic (EM) methods in recent years. Some earthquakes occurred in chance of the measurement time period for each experiment and the anomalies were recorded before the shocks. The observation at a site 20 km away from the epicenter of Zhangbei MS6.2 earthquake in 1998 shows that the apparent resistivity decreases in the strike direction before and/or during the earthquake and the resistivity increases in the de-cline direction. This a...     

生成模型学习的遥感影像半监督分类

以生成模型最大似然估计为例,引入结合已标记样本和未标记样本的半监督分类方法来解决遥感影像分类中的小样本问题,应用已有的少量已标记样本初始化一个分类器,结合大量未标记样本,通过递归计算的方式对分类器进行优化,直到包含所有样本的似然函数收敛到局部极大值。通过分析遥感影像待分类类别与影像中地物类型固有特征之间的关系,设计两个在不同生成模型假设下的分类实验。结果表明,未标记样本的参与可在很大程度上提高小样本条件下的影像分类精度,但两种样本的数量应保持一个适当的比例。最后通过与在解决小样本分类问题方面有独特优势的SVM方法的分类比较,发现在小样本情况下,本文方法具有更好的应用潜力。     

基于非结构有限元的时间域海洋电磁三维反演

海洋电磁法是一种有效的钻前储层评价手段,可识别出海底构造是否储油气,从而减少干井率降低勘探成本.近年来,频率域三维海洋电磁反演得到了快速发展,但受到空气波的影响,其在浅海环境中无法取得很好的效果.为解决这一问题,本文研究时间域海洋电磁数据三维正反演.正演模拟和计算中,我们选择基于非结构网格的矢量有限元方法.该算法中空间离散采用非结构四面体网格,可很好地拟合复杂海底地形条件和地下复杂结构;而对于时间离散,我们采用无条件稳定的后推欧拉方法,以确保任意时间步长数值计算的稳定性.反演计算中,灵敏度信息采用伴随正演隐式进行计算;同时,依据时间域反演方法的特点采用L-BFGS方法计算模型修正量.通过利用合成数据反演结果证明了本文提出的三维时间域反演方法可用于复杂海底环境,特别是在浅海环境下的有效性.