石油学报 ›› 2012, Vol. 33 ›› Issue (S2): 154-159.DOI: 10.7623/syxb2012S2015

• 地质勘探 • 上一篇    下一篇

高清晰岩石结构图像处理方法及其在碳酸盐岩储层评价中的应用

柴 华 1  李 宁 1,2  夏守姬 1  武宏亮 1  郭宏伟 1  王克文 1  冯 周 1  梁明星 3   

  1. 1.  中国石油勘探开发研究院 北京 100083; 2. 长江大学地球物理与石油资源学院 湖北荆州 434023; 3.  东北石油大学地球科学学院 黑龙江大庆 163318
  • 收稿日期:2012-07-04 修回日期:2012-10-31 出版日期:2012-12-25 发布日期:2013-03-01
  • 通讯作者: 柴华
  • 作者简介:柴华,男,1981年11月生,2009年毕业于北京大学,现为中国石油勘探开发研究院工程师,主要从事成像测井处理解释方法研究。
  • 基金资助:

    国家重大科技专项(2008ZX05020-001)资助。

High-resolution rock structure image processing method and its applications in carbonate reservoir evaluation

CHAI Hua 1  LI Ning 1, 2  XIA Shouji 1 WU Hongliang 1  GUO Hongwei 1  WANG Kewen 1  FENG Zhou 1  LIANG Mingxing 3   

  • Received:2012-07-04 Revised:2012-10-31 Online:2012-12-25 Published:2013-03-01

摘要:

电阻率成像测井已经成为解决非均质复杂碎屑岩储层、缝洞型碳酸盐岩储层、火山岩储层问题不可或缺的关键手段之一,而且正在逐渐从高端测井技术走进常规系列。目前主流的成像处理方法中,普遍采用了基于像素分布特征统计的图像增强方法。该方法相对于最初的线性图像增强方法,效果明显改善,然而在处理中未能考虑岩石结构特征的分布规律,经常导致重要的地质特征被湮没在次要特征和噪声中。笔者在传统图像增强方法的基础上,进一步以结构信息为核心要素,提出了基于岩石结构的图像增强方法。该方法以岩石结构特征判别为基础,有针对性地提高图像中关键信息的权重,弱化背景和噪声,并针对结构特征分布规律进行成像色标动态优化,从而显著提高了图像的有效信息量和清晰度,为进一步的精细解释工作提供了先决条件。

关键词: 成像测井, 特征识别, 图像增强, 岩石结构, 碳酸盐岩储层

Abstract:

The resistivity imaging logging is known as one of the indispensable means for solving problems of heterogeneous complex clastic reservoirs fractured-vuggy carbonate reservoirs, and volcanic reservoirs. The previous high-end logging technology is gradually considered to be a routine method. At present, the mainstream image processing approaches commonly employ the image enhancement methods based on the pixel distribution characteristics. Despite substantial improvement compared to the original linear image enhancement method, the distribution-based image enhancement methods do not take into account the distributions of rock structural features, commonly leading to the submergence of major geological features in minor features and noises. On the basis of conventional image enhancement methods, this study focused on rock structure information and proposed a new rock structure-based image enhancement method. Based on the identification of rock structural features, the proposed method was shown to increase the weight of targeted key information in the images, weaken the background and noises, and optimize the dynamic imaging color according to the distributions of rock structural features. These would significantly increase the effective information and improve the image resolution, providing a prerequisite for further precise interpretation.

Key words: image logging, feature recognization, image enhancement, rock structure, carbonate reservoir