| 本文已被：浏览次 下载次 |
码上扫一扫！ |
|
|
| 测井成岩相自动识别及其在鄂尔多斯盆地苏里格地区的应用 |
|
白烨1,薛林福1,石玉江2,潘保芝3,张海涛2,王建强1
|
|
(1.吉林大学 地球科学学院,吉林 长春 130026;2.中国石油长庆油田分公司 勘探开发研究院,陕西 西安 710018;3.吉林大学 地球探测科学与技术学院,吉林 长春 130026)
|
|
| 摘要: |
| 以岩性作为测井特征提取及成岩相识别单元,排除岩性差异对测井信息影响,控制识别单元发育成岩相类型。利用黏土矿物含量比值反映孔隙流体酸碱性,提高判别结果的准确性。根据成岩相对孔缝演化作用的最终影响,定义测井成岩相,并利用基于贝叶斯最佳分类的概率神经网络,对比不同测井组合下神经网络对测井成岩相的识别能力。利用所提方法对鄂尔多斯盆地苏里格地区进行成岩相识别。结果表明,测井成岩相识别结果与实际取心鉴别结果的符合率为81％,且识别的溶蚀相发育区域在实际试气中基本为气层及气水同层,无差气层存在。 |
| 关键词: 油气储层 岩性 测井 成岩相 成岩作用 概率神经网络 黏土矿物 |
| DOI：10.3969/j.issn.1673-5005.2013.01.006 |
| 分类号::P 618.13 |
| 基金项目:国家科技重大专项(2011ZX05044) |
|
| An automatic identification method of log diagenetic facies and its application in Sulige area, Ordos Basin |
|
BAI Ye1, XUE Lin-fu1, SHI Yu-jiang2, PAN Bao-zhi3, ZHANG Hai-tao2, WANG Jian-qiang1
|
|
(1.College of Earth Science, Jilin University, Changchun 130026, China;2.Research Institute of Exploration & Development, Changqing Oilfield Company, PetroChina, Xi 'an 710018, China;3.College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China)
|
| Abstract: |
| Lithology was used as a unit to extracting log feature and identifying diagenetic facies, which could remove the lithology influence on the well-logging informations and control the development types of diagenetic facies in the identification unit.The clay content ratio was used to reflect acidic or alkaline of pore fluid, and the identification accuracy of diagenetic facies was improved. Based on the final effect of diagenetic facies on the development of pore, the conception of log diagenetic facies was given. By using probabilistic neural network based on Bayes optimal classification, the identification ability of diagenetic facies with different logs was compared. The identification coincidence rate of log diagenetic facies is 81％ by this method in He 8 section of Sulige area, Ordos Basin. And the gas test results are general gas reservoirs or gas and water reservoirs.The poor gas reservoirs barely exist in the area where corrosion facies develop widely. |
| Key words: petroleum reservoirs lithology well logging diagenetic facies diagenesis probabilistic neural network clay mineral |
