DFIT测试在长庆气田开发中的应用

与常规的小型测试压裂不同，流体注入诊断测试（DFIT）是通过关井阶段出现的拟线性流或拟径向流阶段求取储层压力，采用改进的梅耶霍夫方法（M-method）解释储层渗透率。以长庆榆林气田一口开发井为例，依据DFIT的技术原理和测试步骤，对该井测试压降数据进行解释分析，结果可信度较高，证明了该项工艺在长庆低压低渗油气田的可行性。     

Best L1 Piecewise Monotonic Data Modelling

Let us consider n data measurements of a univariate process that have been altered by random errors. We assume that an underlying model function has a substantially smaller number of turning points than the observed ones. We propose algorithms that make least the sum of the moduli of the errors by requiring k monotonic sections, alternately increasing and decreasing, in the sequence of the smoothed values. The main difficulty in this calculation is that the optimal positions of the joins of the monotonic sections have to be found automatically among so many combinations that it is impossible to test each one separately. Moreover, the calculation seems to be very intractable to general optimization techniques because O(n^k) local minima can occur. It is shown that dynamic programming can be used for separating the data into optimal disjoint sections of adjacent data, where each section requires a single L₁ monotonic calculation. This procedure is highly efficient, requiring at most O(kn²) computer operations and O(n) best L₁ monotonic calculations to subranges of data for a global minimum.     

电致伸缩陶瓷微位移器非线性的数值方法补偿

本文通过对电致伸缩陶瓷材料的非线性进行分析。找到了补偿电致伸缩陶瓷非线性的数值方法，并对不同回程大小的电滞回线进行了分段处理，使补偿结果更为精确。     

连续流动分析仪应用于水中硫化物的测定

对连续流动法测定硫化物进行初步探讨和研究。同时与其他几种测定硫化物的方法进行了比较。实验结果表明，连续流动法对硫化物分析在线性、稳定性、最低检测限、准确性和精密度等方面均优于其他方法。     

布尔函数的对偶性和线性点

本文主要讨论了部分自对偶和部分反自对偶函数、部分线性函数以及具有线性点的函数的性质。     

Isometric Piecewise Polynomial Curves

The main preoccupations of research in computer-aided geometric design have been on shape-specification techniques for polynomial curves and surfaces, and on the continuity between segments or patches. When modelling with such techniques, curves and surfaces can be compressed or expanded arbitrarily. There has been relatively little work on interacting with direct spatial properties of curves and surfaces, such as their arc length or surface area. As a first step, we derive families of parametric piecewise polynomial curves that satisfy various positional and tangential constraints together with arc-length constraints. We call these curves isometric curves. A space curve is defined as a sequence of polynomial curve segments, each of which is defined by the familiar Hermite or Bézier constraints for cubic polynomials; as well, each segment is constrained to have a specified arc length. We demonstrate that this class of curves is attractive and stable. We also describe the numerical techniques used that are sufficient for achieving real time interaction with these curves on low-end workstations.     

Uniform modeling of parameter dependent nonlinear systems

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. Modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ’multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.     

一种基于高阶统计信息的信噪比估计改进算法

针对多进制正交幅度调制(Multiple quadrature amplitude modulation,MQAM)信号在低信噪比条件下估计精度不高的问题,提出了一种基于综合利用高阶统计信息的信噪比估计改进算法。根据所选高阶统计量最高阶数的不同,建立了3种信噪比与多种高阶统计量运算式之间的线性关系,利用全回归线性分析方法将3种线性关系转化为3种全回归模型,并求解模型系数。该算法充分利用了多种高阶统计量的有用信息,提高了信噪比估计精度。MQAM的仿真结果表明:在低信噪比条件下,该算法减小了信噪比估计误差,其估计性能明显优于传统的其他算法,且3种模型估计性能依次增加,可依据不同的信噪比要求对3种模型进行选取。     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.     

多交叉混沌选择反向小生境遗传算法

为提高小生境遗传算法的全局以及局部搜索能力,提出一种多交叉混沌选择反向小生境遗传算法。利用分段线性混沌映射函数生成一组混沌数序列,在每次进行交叉操作前,依据序列中对应元素的数值大小选择不同的交叉算子进行操作,通过小生境遗传算法产生较优的子代种群。针对子代种群,应用反向搜索策略获得反向种群,在子代种群和反向种群中进行精英选择得到最终新种群,以进一步加强算法的局部寻优能力。仿真实验结果表明,该算法在最优解及均值方面好于小生境遗传算法,从而证明其可行性和优越性。