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.     

Statistical analyses of Global U-Pb Database 2017

The method of obtaining zircon samples affects estimation of the global U-Pb age distribution.Researchers typically collect zircons via convenience sampling and cluster sampling.When using these techniques,weight adjustments proportional to the areas of the sampled regions improve upon unweighted estimates.Here,grid-area and modern sediment methods are used to weight the samples from a new database of 418,967 U-Pb ages.Preliminary tests involve two age models.Model-1 uses the most precise U-Pb ages as the best ages.Model-2 uses the~(206)Pb/~(238)U age as the best age if it is less than a1000 Ma cutoff,otherwise it uses the~(207)Pb/~(206)Pb age as the best age.A correlation analysis between the Model-1 and Model-2 ages indicates nearly identical distributions for both models.However,after applying acceptance criteria to include only the most precise analyses with minimal discordance,a histogram of the rejected samples shows excessive rejection of the Model-2 analyses around the1000 Ma cutoff point.Because of the excessive rejection rate for Model-2,we select Model-1 as the preferred model.After eliminating all rejected samples,the remaining analyses use only Model-1 ages for five rock-type subsets of the database:igneous,meta-igneous,sedimentary,meta-sedimentary,and modern sediments.Next,time-series plots,cross-correlation analyses,and spectral analyses determine the degree of alignment among the time-series and their periodicity.For all rock types,the U-Pb age distributions are similar for ages older than 500 Ma,but align poorly for ages younger than 500 Ma.The similarities(500 Ma)and differences(500 Ma)highlight how reductionism from a detailed database enhances understanding of time-dependent sequences,such as erosion,detrital transport mechanisms,lithification,and metamorphism.Time-series analyses and spectral analyses of the age distributions predominantly indicate a synchronous period-tripling sequence of~91-Myr,~273-Myr,and~819-Myr among the various rock types.     

基于Hyperion高光谱数据和随机森林方法的岩性分类与分析

探索利用高光谱数据的岩性填图新方法是遥感地质应用领域的重要需求之一。本文运用随机森林方法和EO-1Hyperion高光谱数据,对新疆塔里木西北部柯坪地区的局部区域进行岩性分类,并对相关问题进行分析。分别利用光谱特征以及加入光谱一阶导数特征进行岩性分类,并对不同特征对岩性分类的重要性进行分析,同时与现有的基于光谱角制图方法(SAM)进行比较。结果表明,与SAM方法相比,随机森林方法得到了更高精度的岩性分类结果,是一种有效可行的岩性分类方法。根据特征重要性的排序,蓝绿光波段、短波红外波段以及相应的一阶导数特征对研究区Hyperion数据的沉积岩岩性分类贡献更大。     

Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery

Coffee berry necrosis is a fungal disease that, at a high level, significantly affects coffee productivity. With the advent of surface mapping satellites, it was possible to obtain information about the spectral signature of the crop on a time scale pertinent to the monitoring and detection of plant phenological changes. The objective of this paper was to define the best machine learning algorithm that is able to classify the incidence CBN as a function of Landsat 8 OLI images in different atmospheric correction methods. Landsat 8 OLI images were acquired at the dates closest to sampling anthracnose field data at three times corresponding to grain filling period and were submitted to atmospheric corrections by DOS, ATCOR, and 6SV methods. The images classified by the algorithms of machine learning, Random Forest, Multilayer Perceptron and Naive Bayes were tested 30 times in random sampling. Given the overall accuracy of each test, the algorithms were evaluated using the Friedman and Nemenyi tests to identify the statistical difference in the treatments. The obtained results indicated that the overall accuracy and the balanced accuracy index were on an average around 0.55 and 0.45, respectively, for the Naive Bayes and Multilayer Perceptron algorithms in the ATCOR atmospheric correction. According to the Friedman and Nemenyi tests, both algorithms were defined as the best classifiers. These results demonstrate that Landsat 8 OLI images were able to identify an incidence of the coffee berry necrosis by means of machine learning techniques, a fact that cannot be observed by the Pearson correlation.     

Estimating the starting time and identifying the type of urbanization based on dense time series of landsat-derived Vegetation-Impervious-Soil (V-I-S) maps – A case study of North Taiwan from 1990 to 2015

Land cover and land use change (LCLUC) is a global phenomenon, and LCLUC in urbanizing regions has substantial impacts on humans and their environments. In this paper, a semi-automatic approach to identifying the type and starting time of urbanization was developed and tested based on dense time series of Vegetation-Impervious-Soil (V-I-S) maps derived from Landsat surface reflectance imagery. The accuracy of modeled V-I-S fractions and the estimated time of initial change in impervious cover were assessed. North Taiwan, one of the regions of the island of Taiwan that experienced the greatest urban LCLUC, was chosen as a test area, and the study period is 1990 to 2015, a period of substantial urbanization. In total, 295 dates of Landsat imagery were used to create 295 V-I-S fraction maps that were used to construct fractional cover time series for each pixel. Root Mean Square Error (RMSE)s for the modeled Vegetation, Impervious, and Soil were 25 %, 22 %, 24 % respectively. The time of Urban Expansion is estimated by logistic regression applied to Impervious cover time series, while the time of change for Urban Renewal is determined by the period of brief Soil exposure. The identified location and estimated time for newly urbanized lands were generally accurate, with 80% of Urban Expansion estimated within ±2.4 years. However, the accuracy of identified Urban Renewal was relatively low. Our approach to identifying Urban Expansion with dense time series of Landsat imagery is shown to be reliable, while Urban Renewal identification is not.     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.     

Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design

In this paper, we present and evaluate three long-term wave models for application in simulation-based design of ships and marine structures. Designers and researchers often rely on historical weather data as a source for ocean area characteristics based on hindcast datasets or in-situ measurements. The limited access and size of historical datasets reduces repeatability of simulations and analyses, making it difficult to assess the sampling variability of performance and loads on marine vessels and structures. Markov, VAR and VARMA wave models, producing independent long-term time series of significant wave height (H_s) and spectral peak period (T_p), is presented as possible solutions to this problem. The models are tested and compared by addressing how the models affect interpretation of design concepts and the ability to replicate statistical and physical characteristics of the wave process. Our results show that the VAR and VARMA models perform sufficiently in describing design performance, but does not capture the physical process fully. The Markov model is found to perform worst of the tested models in the applied tests, especially for measures covering several consecutive sea states.     

Study of irregular wave run-up over fringing reefs based on a shock-capturing Boussinesq model

This paper presents the results of a parametric study of irregular wave run-up over fringing reefs using the shock-capturing Boussinesq wave model Funwave-TVD to better understand the role of fringing reefs in the mitigation of wave-driven flooding. Laboratory experiments were newly performed with a typical fringing reef profile and typical hydrodynamic conditions to validate the model. Experimental data shows irregular wave run-ups are dominated by the low-frequency motions and confirms the run-up resonant phenomenon over the back-reef slope, which has been revealed in previous numerical studies. It is demonstrated that irregular wave evolution and run-up over fringing reefs are reasonably reproduced by the present model with a proper grid size. However, the infragravity run-up height and highest 2% run-up height over the back-reef slope are under-predicted due to the underestimation of the infragravity wave height over the reef flat. The validated model was then utilized to model irregular wave transformations and run-ups under different conditions. Through a series of numerical experiments, the effects of key hydrodynamic and reef geometry parameters, including the reef flat width, water depth over the reef flat, fore-reef slope angle and back-reef slope angle, on the irregular wave run-up were investigated. Variations of spectral components of irregular wave run-ups were examined to better understand the physical process underlying the effect of each parameter.     

月地岩矿光谱特征对比及月表信息提取方法简介

分析了月、地同类岩石矿物的光谱特征差异,对比了遥感地质信息提取方法和模型的适用性。利用Clemen-tine UV-VIS（紫外—可见光）数据,以月表典型撞击坑Aristillus（阿里斯基尔）和典型月海Humorum（湿海）为研究区,对月球表面岩矿信息提取方法进行了初步实践。     

短脉冲激光在实验室天体物理方面的研究进展

随着啁啾脉冲放大技术(Chirped Pulse Amplification,CPA)的飞速发展,激光功率密度实现了飞跃式的提升,利用短脉冲激光开展实验室天体物理研究的条件日趋成熟.短脉冲激光与靶相互作用可以产生相对论粒子(正负电子、质子、中子等)和高能电磁辐射(X射线、γ射线),这些粒子和辐射的产生过程与天体中的某些...