石油与天然气地质 ›› 2014, Vol. 35 ›› Issue (4): 556-561.doi: 10.11743/ogg20140416

• 油气开发 • 上一篇    下一篇

冲积扇低孔、低渗砂砾岩油藏产能指标预测——以准噶尔盆地西北缘Y地区三叠系百口泉组油藏为例

任涛, 王彦春, 王仁冲   

  1. 1. 中国地质大学 地球物理与信息技术学院, 北京 100083;
    2. 中国石油 海外勘探开发公司, 北京 100034
  • 收稿日期:2014-02-20 修回日期:2014-06-20 出版日期:2014-08-08 发布日期:2014-08-28
  • 作者简介:任涛(1975-),男,博士研究生,构造解释与储层预测。E-mail:121885020@qq.com。

Productivity index prediction of alluvial fan coarse-grained clastic reservoirs with low porosity and low permeability:a case from Triassic Baikouquan Formation reservoir in Y-region at northwestern margin of Junggar Basin

Ren Tao, Wang Yanchun, Wang Renchong   

  1. 1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China;
    2. Chian National Offshore Development Company, Beijing 100034, China
  • Received:2014-02-20 Revised:2014-06-20 Online:2014-08-08 Published:2014-08-28

摘要:

为了利用三维地震资料开展冲积扇低孔、低渗砂砾岩油藏产能指标预测研究,选取准噶尔盆地西北缘Y地区三叠系百口泉组油藏为靶区,在砂砾岩厚度与孔隙度等常规储层预测基础上,精细剖析影响油藏产能的渗透性和含油性等因素,将老区初期平均月产量数据引入三维地震反演过程中,采用层层深入、逐步逼近的思路开展油藏产能指标预测研究,总结形成了“特征曲线反演找准砂砾岩、孔隙度反演找准高物性砂砾岩、自然电位反演找准渗透性砂砾岩、电阻率反演找准含油砂砾岩、多体融合预测油藏产能指标”的研究流程。最终以月产能指标为硬数据,以波阻抗、孔隙度、电阻率和自然电位反演数据体及时间域构造为训练样本,利用神经网络模拟得到油藏产能指标数据体。研究结果表明,预测月产能指标与油井初期平均月产油量为正相关,相关系数R2=0.948 7,老井初期平均月产量大于300 t的预测误差小于10%。产能指标数据体蕴含岩性、物性、含油性和渗透性等控制油气分布的多种信息,依据Y地区相应研究成果建议部署的3口评价井试油产量均在5 t/d以上,验证了该产能指标预测技术的准确性与实用性。

关键词: 三维地震反演, 产能指标预测, 砂砾岩油藏, 准噶尔盆地西北缘

Abstract:

In order to use 3D seismic data for productivity index prediction of alluvial fan coarse-grained clastic reservoirs with low porosity and low permeability,we chose the Triassic Baikouquan Formation reservoir in Y-region at the northwestern margin of Junggar Basin as a case.Based on traditional reservoir prediction such as thickness and porosity of coarse-grained clastic reservoirs,we analyzed in detail factors influencing permeability and oil-bearing properties,and introduced the average monthly production data at the early stage of development into 3D seismic inversion to predict the productivity index.The following work flow was established:‘finding coarse-grained clastic reservoirs through typical curve inversion,finding high quality coarse-grained clastic reservoirs through porosity inversion,finding permeable coarse-grained clastic reservoirs through spontaneous potential inversion,finding oil-bearing coarse-grained clastic reservoirs through resistivity inversion,and predicting reservoir productivity index with the combination of several methods’.A productivity index cube was finally generated through Neural Network modeling by using the monthly productivity as hard data and wave impedance,porosity,resistivity,spontaneous potential inversion data cube and time domain structure as trai-ning samples.The result shows that there is a positive correlation(R2=0.948 7)between the predicted monthly productivity and initial average monthly production.For wells with an initial monthly average production more than 300 ton,the error of prediction is less than 10%.The data cube contains various information controlling hydrocarbon distribution,such as lithology,reservoir property,oil-bearing property and permeability.The oil production of three appraisal wells deployed based on this research in Y-region reached more than 5 ton per day,which verified the accuracy and practicability of this productivity index prediction technology.

Key words: 3D seismic inversion, productivity index prediction, coarse-grained clastic reservoir, northwestern margin of Junggar Basin

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