地球物理学进展 ›› 2019, Vol. 34 ›› Issue (1): 401-405.doi: 10.6038/pg2019BB0520

• 应用地球物理学Ⅱ(海洋、工程、环境、仪器等) • 上一篇    下一篇

基于地震属性的中深层薄砂层厚度定量预测——以渤海A油田为例

严皓,李宾,李久   

  1. 中海石油(中国)有限公司天津分公司,天津 300452
  • 收稿日期:2018-04-15 修回日期:2018-10-16 出版日期:2019-02-20 发布日期:2019-04-15
  • 作者简介:严皓,男,1990年生,汉族,湖北武汉人,毕业于中国地质大学(武汉),硕士学位,工程师,主要从事地震资料解释及油气田生产等相关研究工作.(E-mail: yanhao8@cnooc.com.cn)

Quantitative prediction of mid-deep thin sand thickness with seismic attributes: a case study of Bohai A oilfield

YAN Hao,LI Bin,LI Jiu   

  1. Tianjin Branch of CNOOC Limited, Tianjin 300452, China
  • Received:2018-04-15 Revised:2018-10-16 Online:2019-02-20 Published:2019-04-15

摘要:

渤海广泛分布着油气资源,其中一部分目的层为古近系东营组和沙河街组的中深层油气藏,地震分辨率一般较低,利用常规手段难以准确预测薄层发育情况.本文以渤海中深层的A油田为例研究薄层厚度分布规律,首先利用谱反演技术提高地震资料的分辨率,并详细地分析不同厚度对最大振幅的影响.然后提取不同地震属性,与开发井厚度建立拟合关系,通过优选属性认识到最大振幅属性能够较好刻画薄油层厚度分布规律.最后利用测试探井验证研究结果,吻合较好,证明了地震属性定量预测中深层薄砂体厚度的可行性,发现油田边部潜力储量,为油田挖潜提供了基础.

关键词: 中深层, 谱反演, 薄层厚度, 地震属性, 定量预测

Abstract:

The oil and gas resources in Bohai sea are widely distributed. Some of them are middle and deep reservoirs of the Paleogene Dongying Formation and Shahejie Formation. The seismic resolution is generally low, and it is difficult to predict the thin layer development accurately by conventional means. In this paper, the thin layer thickness distribution is studied by taking A oilfield in Bohai Bay as an example. Firstly, seismic resolution is improved by spectral inversion technique, and the effects of different thickness on maximum amplitude are analyzed. And then different seismic attributes are extracted to establish the fitting relationship with the thickness of development wells. It is concluded that the maximum amplitude property can be used to describe the thickness distribution of the thin oil layer. At last, the results are verified by the test well. It proves that it is feasible to predict the deep sand body thickness quantitatively by the seismic attributes in mid-deep layer. The potential reserves are discovered at the edge of the oil field, which provides the basis for oil potential exploration.

Key words: Mid-deep layer, Spectral inversion, Thin layer thickness, Seismic attribute, Quantitative prediction

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