波形差异反演方法及其在气藏描述中的应用

在油气藏开发中后期,如何利用的已有的勘探成果和丰富的油气藏知识,加深对勘探区域油气开发潜力的认识,为油气田的稳产高产服务,是摆在油气田中后期开发人员面前的难题.油气田开发的研究人员,利用现有的资料,开发出了很多方法,结合地震测井等资料为油气田的稳产高产做出了巨大的贡献.本文在分析了地震波在地质体中传播过程中能量变化,相应的产生了振幅变化的理论,利用三维地震数据,通过对三维地震数据解释层位对应的波形差异的分析,结合工区内的生产井和开发井的对应地层中的油气信息,进行反演得到地层的波形差异数据体,利用相应的绘图软件绘制二维平面图形,结合工区内的沉积相等地质信息对其数据体进行油藏解释,最终得到波形差异反演数据体,利用波形差异反演数据体进行油气藏的识别、描述和预测,为油气田的中后期开发服务.     

利用零偏移VSP资料估计介质品质因子方法研究

利用峰值频率移动法估算零偏VSP资料的品质因子Q．该方法用Ricker子波和匹配地震子波分别逼近零相位和混合相位的震源子波,得到了峰值频率移动法估计Q值的公式．进而针对常规方法估计的地震子波峰值频率精度不高的问题,提出了估计地震子波峰值频率的特征结构法．通过合成零偏VSP资料的仿真试验,验证了峰值频率移动法估计Q值的正确性．仿真结果表明,与快速Fourier变换和Burg最大熵方法相比较,特征结构法得到的峰值频率和Q值精度高一些．仿真结果也表明,用峰值频率移动法估计Q值时需要选取恰当的子波参数,否则影响Q值估计的精度．     

天体运行轨道的背景介质理论导引与自相似分形测度计算的分维微积分基础

通过讨论天体运行背景介质理论的连续轨道及离散轨道这二个研究方向的基础假设,介绍了天体运行轨道的具体方程形式及理论框架概要;进一步地通过讨论天体运行轨道Binet方程的一般形式及其行星近日点进动角的解,给出了连续轨道理论与Newton理论及Einstein广义相对论的联系与区别;通过讨论天体运行轨道的分维扩展方程,给出了包括太阳系行星、天王星卫星、地球卫星、绕月航天器等在内的离散轨道（稳定性轨道）方程及其预言数据.特别地,作为对天体在较为广泛区域作用曲线的初步探讨推论,指出仅由天体引力难以形成质量密度趋于无穷大的理想黑洞.通过讨论一般函数的分维导数的位置假设及幂函数的分维导数的形式假设,进一步明晰了幂函数的分维导数、分维微分及分维积分的具体方程形式,给出分维导数与分数阶导数的区别,随后讨论了基于一般分形测度的分维微积分形式定义导出的自相似分形的测度计算方程具体形式,给出了其与目前Hausdorff测度方法（覆盖方法）的区别,并对包括三分Cantor集合、Koch曲线、Sierpinski垫片及正交十字星形等自相似分形在内的测度进行了计算分析.     

小波变换应用于日长变化的研究进展

随着空间测地技术的发展,日长变化的观测资料已经达到了空前高的程度,迫切需要合适的数学工具和方法从这些高精度的观测资料中提取有价值的信息.近些年,小波变换被应用于天文学和地球科学的资料分析中,它通过伸缩和平移等运算对时间信号进行多尺度的细化分析,从中提取有效的信息.本文主要介绍了小波变换应用于日长变化的研究进展,并初步探讨该领域以后的研究方向.     

塔里木河流域径流变化趋势及其对气候变化的响应

This paper has studied the change of streamflow and the impact of climatic variability conditions on regional hydrological cycle in the headwater of the Tarim River Basin. This study investigates possible causes of observed trends in streamflow in an environment which is highly variable in terms of atmospheric conditions, and where snow and ice melt play an important role in the natural hydrological regime. The discharge trends of three head streams have a significant increase trend from 1957 to 2002 with the Mann-Kendall test. Complex time-frequency distributions in the streamflow regime are demonstrated especially by Morlet wavelet analysis over 40 years. The purpose is to ascertain the nature of climatic factors spatial and temporal distribution, involved the use of EOF （Empirical Orthogonal Function） to compare the dominant temperature, precipitation and evaporation patterns from normally climatic records over the Tarim＇s headwater basin. It shows that the first principal component was dominated since the 1990s for temperature and precipitation, which identifies the significant ascending trend of spatial and temporal pattern characteristics under the condition of the global warming. An exponential correlation is highlighted between surface air temperature and mean river discharge monthly, so the regional runoff increases by 10%-16% when surface air temperature rises by 1 ℃. Results suggest that headwater basins are the most vulnerable environments from the point of view of climate change, because their watershed properties promote runoff feeding by glacier and snow melt water and their fundamental vulnerability to temperature changes affects rainfall, snowfall, and glacier and ice melt.     

球面退化四叉树格网的剖分及变形分析

为有效解决经纬度格网与四元三角网(QTM)在全球空间数据管理与操作中存在的不足,提出一种新的全球离散格网剖分方法——球面退化四叉树格网(DQG),给出该格网的剖分原理与编码规则,并对其进行几何变形计算与分析。结果表明:DQG既具有经纬度格网结构简单的特征,又具有QTM几何变形稳定等优点。     

A coupled discrete element model for the simulation of soil and water flow through an orifice

Soil erosion around defective underground pipes can cause ground collapses and sinkholes in urban areas. Most of these soil erosion events are caused by fluidization of the surrounding soil with subsequent washing into defective sewer pipes. In this study, this soil erosion process is simplified as the gradual washout of sand particles mixed with water through an orifice. The discrete element method is used to simulate the large deformation behavior of the sand particles, and the Darcy fluid model is coupled with this approach to simulate fluid flow through porous sand media. A coupled 3D discrete element model is developed and implemented based on this scheme. To simulate previous experiments using this coupled model considering the current computing capacity, we incorporated a ‘supply layer’ to study the continuous erosion process. The coupled model can predict the erosion flow rates of sand and water and the shape of erosion void. Thus, the model can be used as an effective and efficient tool to investigate the soil erosion process around defective pipes. Copyright © 2017 John Wiley & Sons, Ltd.     

Stage level,volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods

Lake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.     

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.     

Discrete wavelet‐based trend identification in hydrologic time series

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.