应用遗传神经网络研究低渗透储层成岩储集相—以胜利渤南油田三区沙河街组为例

以渤南油田三区沙河街组为例,应用遗传人工神经网络模式识别方法,开展了低渗透储层成岩储集相的研究。该工作是在储集层沉积相、成岩作用研究的基础上,选用流动层带指标、孔隙度、渗透率、粒度中值、泥质含量、孔喉半径均值和变异系数等7项参数,采用神经网络模式识别方法,通过建立遗传神经网络的学习及预测模型,对渤南油田三区沙河街组进行了成岩储集相识别,识别出4类成岩储集相:不稳定组分强溶解次生孔隙成岩储集相、碳酸盐胶结物溶解次生孔隙成岩储集相、强压实强胶结残余粒间孔成岩储集相和极强压实强胶结致密成岩储集相。Ⅰ类储集相的储集性能最好,Ⅳ类最差,为非储层或差储层。     

Awards for Distinguished Contributions to Psychology in the Public Interest: 1986.

The awards for Distinguished Contributions to Psychology in the Public Interest recognize persons who, in the opinion of the Committee on Public Interest Awards, have advanced psychology as a science and/or profession by a single extraordinary achievement or a lifetime of outstanding contributions in the public interest. These contributions might include the identification or solution of significant social problems; unusual initiative or dedication to activity in the public interest; or the integration of the science and/or profession of psychology with social action in a manner beneficial to all. The Committee is authorized to present two awards per year, each with a prize of $2,000. The second award, for which recipients may not have held a Ph.D. for more than 15 years, was established to recognize the large number of excellent psychologists who have made significant contributions to the public interest during the early stages of their careers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

地震勘探技术在焉耆盆地勘探开发中的合理应用探讨

地震勘探技术应用可以分为以二维地震研究构造为主的地震勘探初级阶段、以地震地层学为主的地震勘探中级阶段、以三维地震油藏静态描述为主的地震勘探高级阶段、以地震储层研究为主的开发地震妆级阶段和以四维地震进行油藏监测为主的开发地震高级阶段。针对5个不同阶段的地质条件和地质任务，选择使用合理的地震勘探技术是有效提高勘探开发效益的重要途径。焉耆盆地的勘探开发体现了以地震勘探为主的思路，在勘探开发过程中重视了针对不同勘探开发阶段和不同的地质 地震技术，因此，在早期勘探开发中取得了很好的经济效益。     

神经网络在缺陷识别中的应用

为了准确、快速地进行缺陷识别，介绍了一种新型的前馈神经网络模型，即径向基概率神经网络。与以往的算法相比，该方法具有分类识别精度高且速度快的优点。仿真获得了很好的结果。     

面块切片解释方法应用实例探讨

面块切片是一种新的三维数据显示、解释方法，将它应用于安棚油田地震资料解释中和BBT油田识别小断层中。与常规解释方法相比，不仅大大提高了地震资料的解释效率，而且在识别小断层和小构造方面效果明显。     

池27井机抽排水采气效果分析

介绍了池27井实施机抽排水工艺取得累计排水13 334.4m3的明显效果.分析了五次检泵的原因.提出了对池27井机抽排水的四点认识.     

EXPERIMENTAL AND NUMERICAL INVESTIGATIONS ON HORIZONTAL OIL-GAS FLOW

Experiments were carried out to investigate the characteristics of oil-gas flow in a horizontal pipe on a large scale (with the inner diameter D = 125 mm). With the experimental data, the flow patterns were presented. Through the analyses for the flow regime transition, it was found that there was a critical superficial velocity of liquid phase for the flow regime transiting from stratified flow to slug flow. The slug flow could not occur until the superficial velocity of liquid phase was higher than the critical velocity. For the flow pattern transiting from stratified to slug flow, the transmitting velocity of gas phase decreases with the augmentation of superficial velocity of liquid phase. On the basis of the experiments, numerical simulations of different flow patterns and their transitions were performed with the use of the Volume Of Fluid (VOF) technique. The results of the computations are shown to match well with the measured data in the experiments.     

Solving the small sample size problem in face recognition using generalized discriminant analysis

The goal of face recognition is to distinguish persons via their facial images. Each person's images form a cluster, and a new image is recognized by assigning it to the correct cluster. Since the images are very high-dimensional, it is necessary to reduce their dimension. Linear discriminant analysis (LDA) has been shown to be effective at dimension reduction while preserving the cluster structure of the data. It is classically defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters. The requirement that one of these matrices be nonsingular restricts its application to datasets in which the dimension of the data does not exceed the sample size. For face recognition, however, the dimension typically exceeds the number of images in the database, resulting in what is referred to as the small sample size problem. Recently, the applicability of LDA has been extended by using the generalized singular value decomposition (GSVD) to circumvent the nonsingularity requirement, thus making LDA directly applicable to face recognition data. Our experiments confirm that LDA/GSVD solves the small sample size problem very effectively as compared with other current methods.     

Experience, Context, and the Visual Perception of Human Movement.

Why are human observers particularly sensitive to human movement? Seven experiments examined the roles of visual experience and motor processes in human movement perception by comparing visual sensitivities to point-light displays of familiar, unusual, and impossible gaits across gait-speed and identity discrimination tasks. In both tasks, visual sensitivity to physically possible gaits was superior to visual sensitivity to physically impossible gaits, supporting perception-action coupling theories of human movement perception. Visual experience influenced walker-identity perception but not gait-speed discrimination. Thus, both motor experience and visual experience define visual sensitivity to human movement. An ecological perspective can be used to define the conditions necessary for experience-dependent sensitivity to human movement. (PsycINFO Database Record (c) 2010 APA, all rights reserved)