Pattern recognition in electrical images - digital image analysis with special focus on Gas Hydrate Leg 204

电图像中的模式识别 - 数字图像分析，特别关注天然气水合物 Leg 204

• 批准号: 5434755
• 负责人: Professor Dr. Christoph Clauser
• 金额: --
• 依托单位: Informatik 5 - Lehr- und Forschungsgebiet Life Science Informatik
• 依托单位国家: 德国
• 项目类别: Infrastructure Priority Programmes
• 财政年份: 2004
• 资助国家: 德国
• 起止时间: 2003-12-31 至 2005-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5434755?language=en
• 关键词: Pattern; recognition; electrical; images; digital

Electrical images are widely used in oil industry for borehole inspection and reservoir characterisation. They consist of artifically colour-coded micro-resistivity measurements on the borehole wall. In ODP these are commonly used to study the internal structure of the oceanic crust. At present, the reconstruction of lithology from electrical images is purely based on visual inspection and subjective interpretation. Our objectives are to (1) develop methods for an object- and texture-based pattern recognition of electrical images; (2) develop methods for an automatic classification of rocks; (3) apply this methodology to study the occurrence and characteristics of gas hydrates at ODP Leg 204. Avaible methods from seismic data interpretation and biomedical imaging will be adapted for use with resistive images. In particular, we will implement an algorithm for automatic object identification for a study of the internal rock morphology with respect to sediments drilled at ODP Leg 204. This way, resistivity anomalies caused by gas hydrates will localised them in electrical images. Their proportion, size, and shape will be quantified in order to analyse anisotropy and spatial heterogeneity of identified gas hydrates. Finally, we will correlate the 1D information from all available boreholes and interpolate them into a 2D map of the gas hydrates distribution at Leg 204.

电成像在石油工业中广泛用于井眼检查和储层表征。它们包括对井壁进行的人工彩色编码微电阻率测量。在ODP中，这些通常用于研究洋壳的内部结构。目前，从电成像资料中进行岩性重建，主要是依靠肉眼观察和主观解释。我们的目标是（1）开发基于对象和纹理的电图像模式识别方法;（2）开发岩石自动分类方法;（3）应用该方法研究ODP Leg 204天然气水合物的产状和特征。地震数据解释和生物医学成像的现有方法将适用于电阻率图像。特别是，我们将实施一个算法，自动识别对象的内部岩石形态的研究，相对于在ODP的腿204钻探沉积物。这样，由天然气水合物引起的电阻率异常将在电图像中定位它们。它们的比例，大小和形状将被量化，以分析已识别的天然气水合物的各向异性和空间异质性。最后，我们将把所有可用钻孔的一维信息关联起来，并将其插入204航次天然气水合物分布的二维地图中。