大民屯凹陷地层水水文地质特征与油气聚集关系

对大民屯凹陷前第三系潜山、下第三系沙河街组地层水化学场研究发现，本区油田水总矿化度及二价阳离子浓度偏低，地层水总矿化度具有明显的垂向分带性，水体主要为陆相成因并受地表水渗入的影响较大，变质程度高，油田水的演化与盐类的溶解有关。该区地层水的流动受断裂和沉积砂体的控制，在水头压力、浮力动力场控制下其流动样式和分布规律反映了凹陷内油气的运聚规律，可为本区自生自储、新生古储式油气藏的判别提供有利证据。     

Filters for linear sea-wave prediction

Deterministic sea-wave prediction (DSWP) models are appearing in the literature designed for quiescent interval prediction in marine applications dominated by large swell seas. The approach has focused upon spectral methods which are straightforward and intuitively attractive. However, such methods have the disadvantage that while the sea is aperiodic in nature, the standard discrete spectral processing techniques force an absolutely periodic structure onto the resulting sea surface prediction models. As it is the shape of the sea surface that is important in such applications, particularly near the end of the domain which is important, the standard windowing techniques used in signal processing work to reduce leakage artifacts cannot be employed. This has necessitated the use of end matching methods that can be both inconvenient and may reduce the fraction of the time for which legitimate predictions are available. As a result, an investigation has been undertaken of the use of finite impulse response prediction filters to provide the necessary dispersive phase shifting required in DSWP systems. The present work examines the theoretical basis for such filters and explores their properties together with their application to both long and short crested swell seas. It is shown that wide band forms of such filters are only convergent in the sense of distributions having both infinite duration impulse responses and asymptotically divergent first derivatives. However, appropriate band limitation can produce useful finite impulse responses allowing implementation via standard discrete convolution methods. It is demonstrated that despite the prediction filters having a non-causal impulse response such filters can be used in practice due to a combination of the asymmetric nature of the impulse response and the fundamental nature of the prediction process. The findings are confirmed against actual sea-wave data.     

基于神经网络的平底结构砰击压力预报

对利用神经网络预报平底结构入水砰击压力的方法进行了探讨。首先利用仿真软件计算各种情况下平底结构入水所产生的砰击压力，以此形成训练神经网络的数据集。其次利用数据集对三层反馈式网络进行了训练，讨论了不同隐含层节点数对该非线性系统的拟合能力，并且对梯度下降法、动量修正法和基于优化的LM算法的有效性和精度进行了比较，最后得出了适合平底结构入水砰击系统的网络结构。     

1999年以来台湾及邻近海域7.5级以上强震前的条带现象

中国台湾地区地处欧亚板块与菲律宾海板块之间,地震活动频繁．本文报道了 我国台湾地区及其邻近海域1985～2002年间5．5级以上地震的条带内外频度比分 布,并着重研究了1999—2002年中发生的3次7．5级以上地震前的条带现象．其结 果表明:台湾地区近期发生的3次7．5级以上大地震前,5．5级以上地震呈条带分 布．这些条带符合条带内地震个数Nin≥6的条件,符合条带内、外频度比Nin／(Nin Nout)≥75％的条件,也符合条带长宽比大于5的要求,只是与板内地震条带相比,条 带的长度较短．     

利用归一化层速度预测和研究储层物性的方法

归一化层速度是对任意深度处的层速度进行归一化处理的一种速度形式，归一化处理的目的是把任意深度处的层速度转换为与深度无关的格式，归一化后层速度的横向变化主要取决于地层岩性，孔隙度等物性的变化，利用这一特点可以方便地利用已知钻井资料对其进行标定，比较简单地进行地层岩性，孔隙度等特性的预测。实际应用表明，其预测结果与钻井揭示吻合较好，预测效果令人满意。     

辽东湾地区下第三系地震速度—岩性预测模型研究

地震速度－岩性预测模型由四个子模型组成：即（１）砂泥岩压实模型；（２）地震层速度转换模型；（３）速度校正模型；（４）砂岩指数转换模型。辽东湾地区的实际资料证明，上述四个子模型不但决定了岩性预测的具体方法，而且严格控制岩性预测的精度。     

黄渤海底层盐度预报方法的研究

根据二维流体动力学方程和深度平均盐度扩散方程在河口径流量以及蒸发和降水之差为已知情况下构成的闭合方程组,预报出深度平均盐度,然后利用底层盐度与深度平均盐度、水深和时间(月)之间的经验关系,给出底层盐度的二维预报。为了检验试报结果的可靠性,文中将黄渤海底层盐度的试报结果(1979年7月11日,时效为3d)与标准断面观测资料(7月4—14日观测,124.5°E以西,共104站)作一粗略比较。比较表明,试报结果与实测值的相关系数为0.96,均方误差为α=0.26,绝对误差小于0.2和0.3的站数分别占总站数的63.5％和77.0％,而总均绝差为0.19。由此可见,试报的效果是令人满意的。     

Grey Prediction of Siltation in North Channel of Yangtze Estuary

-The North Channel in the Yangtze Estuary is one of sea-leading waterways of Shanghai Harbour, in which yearly dredging volume reaches over ten million cubic meters, and it tends to increase year by year. Based on the channel regime similarity and through the relational grade, a GM (2, 1) is set up. It reveals the course of development of channel regime similarity under the action of various factors, and predicts the siltation volume in the nearest future which is the basis of dredging planning for relevant dredging departments.     

Prediction of Load Carrying Capacity of Corroded Reinforced Concrete Beam

A novel method for prediction of the load carrying capacity of a corroded reinforced concrete beam (CRCB) is presented in the paper. Nine reinforced concrete beams, which had been working in an aggressive environment for more than 10 years, were tested in the laboratory. Comprehensive tests, including flexural test, strength test for corroded concrete and rusty rebar, and pullout test for bond strength between concrete and rebar, were condueted. The flexural test results of CRCBs reveal that the distribution of surface cracks on the beams shows a fractal behavior. The relationship between the fractal dimensions and mechanical properties of CRCBs is then studied. A prediction model based on artificial neural network (ANN) is established by the use of the fractal dimension as the corrosion index, together with the basic intbrmation of the beam. The validity of the prediction model is demonstrated through the experimental data, and satisfactory resuits are achieved.