Structure- and Texture-Based Fullbore Image Reconstruction
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- 作者：Tuanfeng Zhang ; Andriy Gelman ; Robert Laronga
- 关键词：Wireline borehole images ; Image gaps ; Fullbore images ; Structures ; Textures ; Kernel regression ; Inpainting ; Multipoint statistics ; FilterSim
- 刊名：Mathematical Geosciences
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：49
- 期：2
- 页码：195-215
- 全文大小：
- 刊物类别：Earth and Environmental Science
- 刊物主题：Earth Sciences, general; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology;
- 出版者：Springer Berlin Heidelberg
- ISSN：1874-8953
- 卷排序：49
文摘
Borehole image logs are produced by tools lowered into a well. Such logs provide oriented electrical and acoustic maps of rocks and fluids encountered in the borehole. Electrical borehole images, acquired in either water-based (conductive) or oil-based (nonconductive) muds, are generated from electrodes arranged in fixed patterns on pads pressed against the borehole wall. Depending on borehole diameter, gaps nearly always occur between pads. Because of these gaps, it is common to have nonimaged parts of the borehole wall. The existence of gaps in pad-based borehole images hinders efficient geological interpretation and accurate formation evaluation. A novel method to generate fullbore images combines an inpainting technique with FilterSim: a continuous-variable multipoint statistical approach. The inpainting algorithm detects dips and captures the trend of borehole image logs. The extracted smooth trend maps are fed into FilterSim to guide the construction of high-resolution textures that honor the original borehole image data, leading to seamless reconstruction of 360\(^{\circ }\) fullbore images. The proposed method has been tested using various borehole image patterns and proves to be a reliable and robust way to perform fullbore image reconstruction. The reconstructed fullbore images facilitate improved visualization and interpretation of borehole image logs in various ways, including automated dip picking for fractures and bedding planes, thin-bed analysis in deepwater formations, complex heterogeneity analysis, and accurate porosity estimation in carbonates.