用环境同位素论区域地下水资源属性

从可持续角度提出了区域地下水资源属性的概念; 分析了含水层系统中地下水质点的时间效应; 利用大量同位素资料分析了不同区域含水层系统中的地下水资源属性和人类活动对地下水资源属性的影响.指出利用环境同位素是研究区域地下水资源属性最直接、有效的方法; 正确认识评价区域地下水资源属性对实现地下水资源可持续性具有重要意义.      

瞬时地壳运动与地震短临预报

本文在利用卫星红外扫描仪观测资料的基础上，探讨地震前低空大气的增温是地壳瞬时运动的表现，也是地球－大气耦合现象。通过分析，给出瞬时地壳运动引起增温的三种可能机制：岩石的辐射能量增加；岩层中ＣＨ＿４、ＣＯ＿２等气体溢出和太阳辐射导致增温；ＣＨ＿４、ＣＯ＿２含量增高和低空电场异常激发。并通过某些震例的增温展布形态及规律，恢复震前应力场和热增温演化特征：我国大陆东部ＮＮＥ方向为主压应力方向，大陆东南沿海主压应力方向ＳＮ向，而我国大陆西部地区主压应力方向为ＳＮ向，在青藏高原的东北部派生主压应力为ＮＥ向。最后，介绍了这几年试验性预报效果检验：４年多总共预报３２次，其中虚报２次，７次较准，１７次较好，６次较差，漏报强震８次。最后涉及到地震孕育、发生过程中的机理的初步研究结果。     

瑞雷波勘探在地下洞穴探测中的应用

利用瑞雷波勘探方法进行地下洞穴探测，在实际处理过程中，对场地所测得的面波频散曲线进行分类、归纳，并利用动力触探曲线对各种特征曲线所反映的地下洞穴情况进行标定，从而确定整个测区洞穴的空间分布规律。     

辽河坳陷大民屯凹陷三台子地区下第三系碎屑岩储层预测研究

针对目标区下第三系储层横向变化快,沉积特征不明显等特点,为提高滚动探井、开发井的钻探成功率,本文研制形成一套具有针对性的油气藏勘探预测研究方法.即运用多井约束波阻抗地震反演方法来预测砂体展布,同时对生成的地震波阻抗反演数据体中的振幅、厚度等暗含的有效信息进行提取,对砂体的分布范围及厚度变化进行准确而精细的描述和预测,最终依据此法优选有利相带,部署井位,取得了很好的勘探开发效果.     

不同培养条件下多刺裸腹溞的生殖和种群增长参数

于 １９９６年在实验室对多刺探腹溞（Ｍｂｉｎａ　ｍａｃｒｏｃｏｐａ）种群的增长率及相关生态学参数进行了研究．结果表明,３个温度梯度（２４、２８和３２℃）和３个面包酵母（Ｓａｃｃｈａｒｏｍｙｃｅｓ　ｃｅｒｅｖｉｓｉ－ａｅ）密度（０．２５、２ ５和２５ ｘ １０_６ｃｅｌｌ．ｍＬ~（－１）下,以２８℃时内禀增长力（ｒ_ｍ）最高;２８℃时,面包酵母的投喂密度为２５×１０_６ｃｅｌｌ．ｍＬ_（－１）时,其ｒ_ｍ最大．温度２８℃,面包酵母密度为２５×１０_６ｃｅｌｌ．ｍＬ~（－１）时,该溞的繁殖前期最短,繁殖期和寿命均最长,并且怀卵量（每窝产仔数）最大．该溞的种群密度和瞬时增长率分别在接种后第７ｄ和第３－４ｄ达高峰．该搔批量培养时采收时间以第５ｄ为宜．     

河流相储层构型研究新理论、新方法——海上油田河流相复合砂体构型概念、内容及表征方法

基于陆上油田密井网的河流相储层构型研究,经过数十年积累,理论基础及表征方法已比较成熟,然而,将其应用于海上油田稀疏井网条件时,依然面临较大的挑战。笔者团队经过多年探索,基于海上油田开发地质研究方法,形成了井震结合、以"复合砂体"为核心的海上河流相复合砂体构型理论与表征方法,其特点在于运用三维原型建模、地震构型相预测及地震驱动确定性建模等技术,重点表征影响海上油田开发的五、六、七级构型单元(复合河道带、单一河道带、复合点坝),针对开发阶段的小层细分对比及不连续渗流屏障刻画等方面具有明显的优势。目前,应用这套理论及方法开展精细地质建模和数值模拟依然存在挑战,需要进一步发挥地震资料作用并探索人工智能的地震解释新途径。     

遥感多维空间数据场特征的角度分析与应用

科学计算的可视化是空间数据场的可视化。标题、矢量、张量是线性电磁系统中定义多维数据的基本参数。从瞬变电磁系统的因果律出发，可以将遥感传感器对电磁波的响应看作是地表电磁场量的映射，像元是记录电磁场量的一种方式。由于电磁场量的线性关联，多波段遥感数字图像可以表示为多维空间数据场量。在多维向量空间中可以对数据场量进行度量、分解和构造向量角度函数。遥感多维空间数据场有效弱信息提取方法则是基于多维空间数据场角度分析展开的。     

Estimation of reservoir porosity using probabilistic neural network and seismic attributes

Porosity is one of the most important properties of oil and gas reservoirs. The porosity data that come from well log are only available at well points. It is necessary to use other method to estimate reservoir porosity.Seismic data contain abundant lithological information. Because there are inherent correlations between reservoir property and seismic data,it is possible to estimate reservoir porosity by using seismic data and attributes.Probabilistic neural network is a powerful tool to extract mathematical relation between two data sets. It has been used to extract the mathematical relation between porosity and seismic attributes. Firstly,a seismic impedance volume is calculated by seismic inversion. Secondly,several appropriate seismic attributes are extracted by using multi-regression analysis. Then a probabilistic neural network model is trained to obtain a mathematical relation between porosity and seismic attributes. Finally,this trained probabilistic neural network model is implemented to calculate a porosity data volume. This methodology could be utilized to find advantageous areas at the early stage of exploration. It is also helpful for the establishment of a reservoir model at the stage of reservoir development.     

Defining the 3D geometry of thin shale units in the Sleipner reservoir using seismic attributes

Defining the 3D geometry and internal architecture of reservoirs is important for prediction of hydrocarbon volumes, petroleum production and storage potential. Many reservoirs contain thin shale layers that are below seismic resolution, which act as impermeable and semi-permeable layers within a reservoir. Predicting the storage volume of a reservoir with thin shale layers from conventional seismic data is an issue due to limited seismic resolution. Further, gas chimneys indicative of gas migration pathways through thin shale layers, are not easily defined by conventional seismic data. Additional information, such as borehole data, can be used to aid mapping of shale layers, but making lateral predictions from 1D borehole data has high uncertainty. This paper presents an integrated workflow for quantitative seismic interpretation of thin shale layers and gas chimneys in the Utsira Formation of the Sleipner reservoir. The workflow combines the use of attribute and spectral analysis to add resolution to conventional seismic amplitude data. Detailed interpretation of these analyses reveals the reservoirs internal thin shale architecture, and the presence of gas chimneys. The comprehensive interpretation of the reservoirs internal structure is used to calculate a new reservoir storage volume. This is done based on the distribution of sand and interpreted shale layers within the study area, for this active CO₂ storage site.     

东太平洋海盆多金属结核生长历史的重建

依据多金属结核ＣＣＣ１４剖面上Ｍｎ、Ｆｅ、Ｎｉ、Ｃｕ的含量和有关的公式，本文计算该结核生长过程中瞬时生长速率和Ｍｎ、Ｆｅ、Ｎｉ、Ｃｕ的瞬时通量，并在结核中建立时间标尺，划分和对比结核生长阶段，重建结核ＣＣＣ１４８．７９３Ｍａ，Ｂ．Ｐ．以来的生长历史。研究结果表明，采用由铁、锰含量计算结核生长速率的公式，可详细了解结核生长过程，并能识别与提取强核中古海洋信息记录。