摘要
体绘制技术是一种重要的科学计算可视化方法,它能够将体数据中所隐藏的信息,交互地以图形图像方式展示给用户。在医学、气象学和油气地震勘探等领域,体绘制技术被广泛应用,用于辅助用户分析数据、发现其中蕴含的科学规律。随着大量复杂油气勘查难题的出现,传统三维地震可视化解释技术面临着新的挑战。因此研究地震体数据可视化与分析技术,具有重要的理论意义和实用价值。
本文主要研究地震体数据可视化与分析中的关键技术。提出了三种地震体数据可视化与分析算法,集成这些算法并开发了地震体数据可视化与分析原型系统,大量实验结果验证了本文算法的有效性。
1.提出基于光线不透明度调整的区间体绘制算法,克服传输函数设置复杂、多特征相互遮挡和特征剥离依赖视点等现有体绘制算法的局限性。本文采用区间体定义体数据结构特征,区间体是三维空间中标量值属于特定范围的所有数据的集合,能够更准确描述视觉特征。本文提出的基于光线不透明度调整的区间体绘制算法,通过区间体的数值局部相关性计算,自动识别体数据的主要区间体,依据区间体识别结果自动设置传输函数；通过分析投射光线上区间体的不透明度分布,定义区间体绘制方程,保证所有区间体同时可见。应用本文提出的基于光线不透明度调整的区间体绘制算法,用户能够交互地剥离并绘制区间体,剥离结果不依赖视点。
2.提出保特征量化方法和特征增强体绘制算法,解决高动态范围地震体数据在采用传统量化方法时所带来的特征丢失问题。在普通显示器上绘制高动态范围地震体数据,需要对其进行量化预处理。通过对高动态范围地震体数据分段可视化分析,定义体数据的细节结构、局部相关结构和奇异点结构等特征。采用迭代保边滤波算法分离细节结构特征,根据局部相关性统计属性获得局部相关结构特征,然后分离奇异点结构特征。基于结构特征分类结果及它们对体绘制结果的影响,提出保特征量化准则和优化策略,实现高动态范围地震体数据量化。对于量化后地震体数据,为抑制噪声对体绘制结果的影响,提出了特征增强体绘制算法。
3.提出鲁棒多尺度地震层位识别与可视化方法,解决复杂层位识别和分类难题。地震层位能够揭示岩石属性变化,层位识别对地质构造解释非常重要。现有层位识别算法由于受噪声干扰往往无法有效工作,经过非连续点所识别的层位常常会产生歧义连接问题。为抑制噪声,增强层位连续性,本文提出了基于多属性滤波的地震体数据结构增强算法。该方法采用体数据强度、空间距离和局部结构定义滤波权值；根据倾角属性旋转滤波核窗口,保证滤波处理沿地震层位进行,增强层位连续性；基于相干体属性平移滤波核窗口,避免平滑非连续特征;参照紊乱度属性自适应调整滤波参数,调整不同噪声水平区域的滤波效果。对于滤波后的地震体数据,提出多尺度层位识别方法,根据层位平坦度,在层位识别过程中自动调整识别尺度实现层位自动分类。为观察所识别层位,还给出了多体可视化与层位识别过程可视化方法。
最后,本文介绍了集成上述特征增强体绘制技术与层位识别技术的地震体数据可视化与分析系统,该系统实现了地震属性计算与多属性体可视化、地震体数据剖面分析与处理等功能。
本文研究工作结合了地震属性分析、可视化算法和图形硬件技术,为解决复杂油气勘查难题,探索新的思路和技术手段。大量实验结果验证了本文所提方法的有效性。
Volume Rendering is one of the primary methods in scientific visualization field. The intrinsic information of volume dataset can be visualized interactively by this method. In medicine, meteorology and oil and gas seismic exploration application, volume rendering technology is widely used, and helps users to analyze the data and to find the rule or law concerning the data. With the emergence of various complex oil and gas discovering and forecasting problems, the traditional interpretation of seismic volume data visualization technology faces new challenges. Thus, it is vital important to study further the seismic volume data visualization in theory and practice.
This thesis focuses on the key technologies of seismic volume data visualization and analysis, and proposed three novel seismic volume data visualization and analysis algorithms. All three new algorithms are integrated into our developed seismic volume data visualization and analysis system. Some seismic exploration data are tested by our system and the experimental results demonstrate the efficiency of our new algorithms.
Firstly, we proposed an interval volume rendering algorithms by ray-opacity-modulation. Our algorithm can overcome complex specification of transfer function, feature occlusion, and view-dependent feature peeling which are the limitations of existing volume rendering algorithm. We adopted the interval volume to define the structures of volume data, in which the interval volume is defined by a sub-space with scalar values in a specific range and it can be used to describe visual feature with more accuracy. Transfer function can be automatically generated by the principle interval volume which is detected based on corresponding level of local data relevance. To assure the visibility of all interval volumes at once, we proposed a novel interval volume rendering equation based on ray interval profile analysis. By the application of our rendering equation, users can interactively achieve interval volume peeling rendering without view dependence.
Secondly, to solve the problem of features missing by traditional high dynamic range seismic volume data quantization method, we proposed a feature preserved seismic volume data quantization method, and introduced a feature enhanced volume rendering algorithm. The seismic volume data quantization is an important preprocessing step before rendering high dynamic range seismic volumes on regular display screen. Base on the sub-range visual analysis of the high dynamic range seismic volume data, a series of features such as the fine structures, the local relevant structures and singularities structures of volume data are defined. Fine structures can be isolated by series iteratively edge preserved filter algorithms, local relevant structures are obtained by local relevance statistics, and then singularities structures are departed from them. We proposed guidelines and an optimization strategy of feature preserved quantization by analyzing the classification of features and their effects on volume rendering. To suppress the noise which may affect the quality of volume rendering of the scaled seismic volume data, we introduced a feature enhanced volume rendering algorithm.
Thirdly, a method of robust multi-scale seismic horizon detection and visualization is introduced for more complex horizon detection and classification. Seismic horizons are the predominant geological features which indicate changes in rock properties, so horizon detection is more important to seismic interpretation. But many existing horizon detection algorithm cannot work well due to the high noise of seismic data, and discontinuity points often results in ambiguous horizons detected. To suppress the noise and enhance the continuity of horizon, we proposed a multi-attribute based filtering algorithm to enhance the structures of seismic volume data. Our multi-attribute based filtering algorithm defined the filter weight by the intensity, space distance and local structures of seismic volume data. The filter window of our multi-attribute based filtering algorithm can be rotated along dip to enhance the continuity of horizon, translated with coherence to keep the discontinuity features. The filter weight can be adaptively adjusted with chaos due to the noise level of region to achieve different filter effects. We proposed a flatness-based multi-scale horizon detection method for the enhanced seismic volume data by our multi-attribute based filtering algorithm. The method can adaptively adjust the scale of detection by local flatness and achieve horizon classification. To observe the detected horizons, we implemented the multi-volume visualization technique and proposed a method to visualize the processing of horizon detection.
Finally, we developed a seismic volume data visualization and analysis system that integrates the above feature enhanced visualization and horizon detection methods. The system also provides various functions, such as seismic attributes estimation, multi-attribute volume visualization and seismic slice processing, etc.
The research of this thesis explored seismic attributes calculation algorithms, volume rendering methods and graphics hardware techniques, and provides the new methods for complex seismic interpretation. A number of experimental results demonstrate the efficiency of our proposed methods.
引文
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