致密砂岩气藏水平井测井评价——以鄂尔多斯盆地大牛地气田X井区为例

致密气藏中有相当一部分水平井测井系列少、评价难度大,如何利用有限的测井资料有效开展水平井测井评价,对气藏高效开发具有重要意义。以鄂尔多斯盆地大牛地气田X井区为例,结合地质和生产动态等资料,利用水平井仅有的随钻伽马测井和气测录井资料开展测井评价研究,形成了基于伽马峰值和全烃有效指示因子的双参数水平井产能评价方法,有效提高了水平井产能评价精度,为同类气藏水平井测井评价提供了借鉴。研究认为,基于随钻伽马峰值分析能够有效对储层进行评价,大牛地X井区山西组和下石盒子组高产井目的层段随钻伽马值的分布均表现出了明显的单峰特征,而低产井则表现为双峰或不具有明显的峰值特征,主要与水平井钻遇砂体的稳定性有关。利用X井区气测录井资料,构建了基于全烃有效指示因子用于评价单井产能,并建立了山西组和下石盒子组水平井经济产能的气测录井指标。综合上述两种方法,形成双参数水平井产能评价方法,准确评价了X井区水平井单井产能。     

网格长度对FDTD计算的影响

基于平面波传播的物理性质，提出一种FDTD改进方法——在研究稳态问题时，为保证数字波前与入射方向垂直，网格划分不能是固定的，其长度之比应随人射方向变化。研究了改进方法对数值色散的影响，并与传统方法作了比较。在三维Yee网格中对平面波的模拟结果表明，改进方法的收敛性能大为提高，对远场散射的误差影响小。     

模场直径对单模光纤接续损耗的影响

模场直径描述了单模光纤所传输的光能在光纤中的分布情况,对于单模光纤耦合和接续是一个很重要的参数。光纤中光能分布情况可用高斯公式描述。在这种情况下,我们可算出两根待接光纤的模场直径不同所引起的接续损耗。通过试验数据的分析,可以看出试验结果和理论计算较为接近。本文仅涉及模场直径对单模光纤接续损耗的影响。     

风场下自然地表红外辐射统计特性

考虑风场存在时热对流的作用,并根据自然地表的热平衡方程分析了自然地表红外辐射的统计特性,分析中采用一级近似,结果表明,风场的存在将使地表温度的概率分布产生明显改变,峰值及平均温度趋近地表附近空气的稳定温度,并导致地表热辐射图像对比度的显著降低,文中还提出了热对流效应的饱和现象。     

CdS半导体非线性吸收中的电场作用

在CdS的室温光学非线性吸收过程中,再外加直流电场,观察到光学非线性吸收随外场增大而增大,非线性出现的光强阈值随外场增大而减小.通过实验判断这一现象来源于电子激子散射.     

COMPARISON BETWEEN FEL AND CYCLOTRON RADIATION

In general,in free electron lasers there are two kinds of stimulated radiations:FELradiation and cyclotron radiation.This paper chows theoretically that if the initial transversevelocity of electron beam is large and the selected parameters for FEL are not suitable,thecyclotron radiation will be dominant,especially when the energy of electron beam is low.But thecyclotron radiation does not have double Doppler frequency upshift effect,its frequency is limitedby axial megnetic field,and when the energy of electron beam is high,the cyclotron radiationfrequency will be much lower than FEL radiation frequency.Therefore,in FEL experimentshow to distinguish these two kinds of radiations and to suppress the cyclotron radiation are veryimportant.     

同步辐射光刻技术

同步辐射光刻有希望代替传统光刻技术,用于0.25μm以下图形的超精细加工。本文叙述了它的原理、相关技术的开发现状和工艺应用。     

Cascade synthesis of 2-D dissipative reactance networks

In this paper, a new result, new formulas of transfer function and input impedance, for 2-D dissipative reactance network cascade synthesis is given in terms of simplified formulas to realize doubly terminated resistively 1-D dissipative reactance networks. The new result includes the more general cases, e.g. the both can be dissipative or one is dissipative and the another is a lossless reactance subnetwork and so on. Two calculation examples are given in the paper to illustrate the above realizations. Besides, considering some problems of the direct connection between two subnetworks, we also introduce one-way lines to discuss the cascade synthesis of nonreciprocal 2-D dissipative reactance networks.     

An implementation for a fast public-key cryptosystem

In this paper we examine the development of a high-speed implementation of a system to perform exponentiation in fields of the form GF(2 ⁿ ). For sufficiently large n, this device has applications in public-key cryptography. The selection of representation and observations on the structure of multiplication have led to the development of an architecture which is of low complexity and high speed. A VLSI implementation has being fabricated with measured throughput for exponentiation for cryptographic purposes of approximately 300 kilobits per second.     

Toward prediction of surface tension of branched n-alkanes using ANN technique

This study features the application of artificial neural network for prediction of surface tension of branched alkanes. Surface and interfacial tensions of alkanes show a specific interaction between adjacent molecules of the higher n-alkanes which results in an anisotropic dispersion force component of the surface energy. The surface tension of branched alkanes was studied for temperatures between 283.15 and 448.15 K. Two intelligent models named multilayer perceptron model (MLP) and radial basis function (RBF) model were developed and the accuracy of two models was examined by different graphical and statistical methods. Results showed that the both models are accurate and effective in prediction of surface tension of branched alkanes. However, the results were compared with experimental data and it was found that the estimated surface tension by multi-layer perceptron neural network is more accurate than radial basis function network.