Connectivity constrained segmentation of geologic features

Segmentation of geologic features plays a significant role in seismic interpretation. Based on the segmentation results, interpreters can readily recognize the shape and distribution of geologic features in three-dimensional space and conduct further quantitative analysis. Usually, there are mainly two steps for the segmentation of geologic features: the first step is to extract seismic attributes that can highlight the occurrence of geologic features, and the second step is to apply the segmentation algorithm on the seismic attribute volumes. However, the occurrence of geologic features is not always corresponding to the anomaly value on the seismic attribute volumes and vice versa because of several factors, such as noise in the seismic data, the limited resolution of seismic images and the limited effectiveness of the seismic attribute. Therefore, the segmentation results, which are generated solely based on seismic attributes, are not sufficient to give an accurate depiction of geologic features. Aiming at this problem, we introduce the connectivity constraint into the process of segmentation based the assumption that for one single geologic feature all of its components should be connected to each other. Benefiting from this global constraint, the segmentation results can precisely exclude the interference by false negatives on seismic attribute volumes. However, directly introducing the connectivity constraint into segmentation would face the risk that the segmentation results would deteriorate significantly because of false positives with relatively large area when the connectivity constraints are enforced. Therefore, based on the seismic attribute that highlights the boundary of geologic feature, we further propose a post-processing technique, called pruning, to refine the segmentation results. By taking the segmentation of the channel as an example, we demonstrate that the proposed method is able to preserve the connectivity in the process of segmentation and generate better segmentation results on the field data.     

Semi-automatic fault/fracture interpretation based on seismic geometry analysis

Fault and fracture interpretation is a fundamental but essential tool for subsurface structure mapping and modelling from 3D seismic data. The existing methods for semi-automatic/automatic fault picking are primarily based on seismic discontinuity analysis that evaluates the lateral changes in seismic waveform and/or amplitude, which is limited by its low resolution on subtle faults and fractures without apparent vertical displacements in seismic images. This study presents an innovative workflow for computer-aided fault/fracture interpretation based on seismic geometry analysis. First, the seismic curvature and flexure attributes are estimated for highlighting both the major faults and the subtle fractures in a seismic volume. Then, fault probability is estimated from the curvature and flexure volumes for differentiation between the potential faults and non-faulting features in the geometric attributes. Finally, the seeded fault picking is implemented for interpreting the target faults and fractures guided by the knowledge of interpreters to avoid misinterpretation and artefacts in the presence of faulting complexities as well as coherent seismic noises. Applications to two 3D seismic volumes from the Netherlands North Sea and the offshore New Zealand demonstrate the added values of the proposed method in imaging and picking the subtle faults and fractures that are often overlooked in the conventional seismic discontinuity analysis and the following fault-interpretation procedures.     

面向室内应急疏散标识的VR眼动感知实验与布局评估

在室内应急疏散的背景下,理解人们如何感知应急疏散标识以及他们的感知如何影响疏散行为十分重要。虚拟地理环境基于虚拟现实（VR）技术构建的沉浸式多维信息空间,是一个符合人类感知认知规律的三维、动态、可交互空间。而基于虚拟地理环境的虚拟地理感知/认知实验,则可以提供一个可定量观测的可控虚拟实验环境,通过设计多种实验方案,定量地获取与空间感知、认知行为相关的客观实验数据。本文将沉浸式虚拟环境与眼动追踪技术相结合,设计了VR眼动感知实验,以室内通道为例,采用定量观测、数据统计、可视化分析等方法,对不同虚拟火灾逃生场景下的疏散时间、眼动注视点、个体移动轨迹数据进行了处理与分析,最后对室内应急疏散标识布局进行评估并提出合理建议。实验结果表明：① 女性参与者比男性更容易被逃生起始位置干扰,拥有较差的虚拟空间感;② 3种场景类型（无标识无烟雾、有标识无烟雾、有标识有烟雾）在疏散时间之间存在明显差异,应急标识、烟雾与逃生起始位置对疏散时间有显著性影响;③ 通道墙贴标识的感知率最高为0.929,在火灾逃生中最容易被识别;④ 安全出口标识感知率最低为0.333,眼动注视点大多在安全门而非安全出口标识上,因此需要提升安全出口标识的视觉吸引力;⑤ 室内通道微观环境的不同（例如通道长度）对应急标识注视时长的变化有较大影响;⑥ 安全出口附近的标识布局、设计有待改进。虚拟眼动感知实验为评估室内应急疏散标识的合理性和布局优化提供了一个有效的科学途径。     

探地雷达应用概述

以ASTM标准规范为基础对探地雷达（Ground Penetrating Radar 以下简称GPR）的地下探测方法的应用做了比较系统的概述,主要内容包括：部分专业术语的解释;测试过程中雷达探测深度及其中心频率、垂直分辨率、水平分辨率等的关系,测试过程中常见的天线移动方式,以及雷达波速的预测几种方法,数据显示方式;雷达数据解释和数据处理的一般过程及方法.目前我国尚没有关于GPR的国家规范或行业标准,文章对GPR的使用及规范的编制具有一定的参考意义.     

非纵观测系统地震测深资料分析处理的人机对话过程

本文在三维壳幔结构中两点射线追踪分步搜索算法的基础上,在物探中心地震方法研究室ＳＵＮ工作站上研究开发出可应用于非纵观测系统深地震测深资料人机对话三维分析处理的方法及软件。对研究区域的三角形剖分减少了人机对话过程中的工作量及人为干预,并用该方法以反演得到的华北块状模型作为初始模型,对该模型的剩余ＰｍＰ波残差进行了人机对话拟合。     

约束型贝叶斯网络在遥感图像解译中的应用方法研究

采用一种带有约束条件的贝叶斯网络来构造分类器,即特征节点被约束为类节点的子节点,子节点间允许有不同的连接关系,并将约束型贝叶斯网络的几种典型模型--NB、TAN、BAN用于遥感图像的解译中.通过评价结构的似然函数得到网络结构,综合特征节点和类别节点的拓扑和概率统计信息学习得到分类器.将这些模型用于多光谱和高光谱影像的分类,并就其性能进行探讨.     

黔南-桂北地区大地电磁测深法应用研究

结合黔南—桂北地区大地电磁测深(MT)区域大剖面资料的分析,划分了不同的地质构造单元,揭示了盆、台结构的存在并圈定了其范围。结果表明:在我国南方海相地区,不同相带沉积岩相电阻率总体特征存在明显的差异;利用大地电磁测深的电阻率总体特征可以进行相带划分;根据各自相带中不同的地电结构特征可以研究标志层及局部构造圈闭。     

湖南湘西金矿及外围石英脉包裹体特征与石英脉含金性研究

以湖南湘西金矿及其外围(东部)脉石英为例，研究了脉石英包裹体的气、液相成分特点，提出包裹体中的CO2、HCO3^-、CO2／H2O、HCO3^-／Cl^-及离子总浓度(∑1)可作为评价石英脉含金性的标志，并总结出石英脉含金性评价的矿物学特征，预测了湘西金矿外围四个工作区的成矿远景。     

石鸡坝一带金矿成矿地质特征及其找矿标志

石鸡坝一带金矿属阳山金矿田的西延部分,在西秦岭的金矿中占有重要地位,重新系统总结其成矿规律和找矿标志具有现实意义。研究表明,石鸡坝一带金矿的成矿规律主要体现在构造控矿、岩脉控矿和岩性控矿。不同类型矿石的物质成分基本相似,均为Fe、Cu、As、Sb等的化合物;差异主要表现在花岗斑岩型金矿石的化学成分富K2O,脉石中有含水的铁、镁硅酸盐矿物。矿床地质及稳定同位素资料证明,矿床成因属于多元热液复合形成的中低温热液金矿。Au、Hg、As、Sb等元素前缘晕异常、以褐铁矿化为主的构造蚀变带及中酸性岩脉分布区是该类型金矿的重要找矿标志。区域地质及地球化学资料显示自石鸡坝至阳山一带找矿前景良好,但具体的找矿突破区段尚待进一步的研究。     

地层切片技术在复杂勘探区储层预测与地质体识别中的应用

研究并讨论地层切片技术在复杂断陷盆地岩相识别中的应用及对策,以准确反映盆地中沉积体系的展布,精细刻画振幅型和结构异常型沉积体系.应用地层切片技术,结合三维精细解释结果及三维可视化方法,在海拉尔盆地贝西次凹霍1井区识别了下白垩统大磨拐河组河道的展布并刻画了下白垩统南屯组扇体发育的特征.