地球物理学进展 ›› 2018, Vol. 33 ›› Issue (5): 2148-2152.doi: 10.6038/pg2018BB0390

• 应用地球物理学Ⅱ(海洋、工程、环境、仪器等) • 上一篇    下一篇

扩展弹性阻抗在低孔、低渗砂砾岩储层物性预测中的应用

秦德海(),李德郁,蔡纪琰,戴建芳   

  1. 中海石油(中国)有限公司天津分公司渤海石油研究院,天津 300452
  • 收稿日期:2018-03-01 修回日期:2018-06-03 出版日期:2018-10-20 发布日期:2019-01-11
  • 作者简介:秦德海,男,1988年生,2013年毕业于中国石油大学(北京)获硕士学位,物探工程师,主要从事地球物理解释及储层预测等研究.

Application of extended elastic impedance for physical property prediction of low porosity and low permeability glutenite reservoirs

QIN De-hai(),LI De-yu,CAI Ji-yan,DAI Jian-fang   

  1. Bohai Oil Research Institute, Tianjin Branch, CNOOC Limited,Tianjin 300452, China
  • Received:2018-03-01 Revised:2018-06-03 Online:2018-10-20 Published:2019-01-11

摘要:

砂砾岩储层是渤海A构造区油气勘探的重要目标之一,近源、快速堆积的特征使得砂砾岩储层非均质性较强,物性变化快,寻找局部发育的优质储层成为后续勘探亟待解决的关键问题.为此,基于弹性阻抗理论,引入一种依赖梯度阻抗(GI)的物性预测方法,其核心是在常规声波阻抗(AI)和梯度阻抗(GI)空间中实现角度旋转,通过计算最佳旋转角度下的扩展弹性阻抗,获得和孔隙度直接相关的敏感弹性参数,通过有色反演将AVO截距-梯度属性转到阻抗域,进而得到相应的孔隙度敏感参数体.对研究区展开的实际应用表明:上述方法能够凸显砂砾岩体内部的物性变化,同时克服了常规物性预测步骤复杂、对井和地震资料要求苛刻的问题,获得的孔隙度敏感参数体与实钻井吻合率高,有效指示了优质储层平面展布,为后续勘探评价提供了支持.

关键词: 物性预测, 孔隙度, 梯度阻抗, 坐标旋转, 扩展弹性阻抗

Abstract:

The glutenite reservoirs are one of the important exploration targets in the Bohai A structural area. With the characteristics of near-source and rapid accumulation, the glutenite reservoir is very heterogeneous and its physical property variation is fast, searching the high quality reservoirs which are locally distributed becomes the key issues to be solved for the following exploration. Based on the theory of elastic impedance, a method of physical property prediction based on Gradient Impedance (GI) is introduced in this paper. The core is the angle rotation in the space of conventional Acoustic Impedance (AI) and Gradient Impedance (GI). By calculating the optimal rotation angle and the corresponding elastic impedance, the elastic parameters related to reservoir porosity are got directly.Then the AVO intercept-gradient attributes are transferred to impedance domain by the colored inversion, and the corresponding porosity-sensitive parameter body is obtained. The practical application in the research area shows that the above method can highlight the physical property variations inside the glutenite reservoirs, and also avoids the complexity steps of the conventional physical prediction. The obtained porosity sensitive parameter body fit the real drilling data well, which effectively indicates the distribution of high quality reservoirs, thus providing support for follow exploration evaluation.

Key words: physical property prediction, porosity, gradient impedance, coordinate rotation, extended elastic impedance

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