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井、震多尺度信息融合预测老油田浅层岩性气藏

Using well and seismic multi-scale information integration to predict shallow lithology gas reservoir in mature oilfield

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【作者】 张宪国林承焰张涛王永刚

【Author】 Zhang Xian-guo1,Lin Cheng-yan1,Zhang Tao1 and Wang Yong-gang1.1.Institute of the Earth Recourses and Information,China University of Petroleum(East China),Dongying City,Shandong Province,257061,China

【机构】 中国石油大学(华东)地球资源与信息学院

【摘要】 老油田浅层岩性气藏岩性分布复杂,利用地震属性分析、含气砂岩地震正演模拟及基于概率神经网络(PNN)的声波时差参数预测等方法对气藏分布进行描述,是寻找该类气藏的有效手段,其中建立符合研究区地质特征的地质模型,开展地震正演研究,总结含气砂体的地震反射特征,是利用地震反射资料进行含气目标检验的前提。在属性优选的基础上,利用PNN神经网络算法将多种地震属性与声波时差测井信息相结合,对三维空间的声波时差参数分布特征进行预测,一方面避免了单一地震属性信息的片面性,另一方面实现了气藏敏感测井参数的合理延伸,是一种快速有效的气藏检测方法。将井、震多尺度信息融合预测浅层岩性气藏方法应用于吉林红岗油气田,地震正演结果显示,气藏顶部为较强的波谷反射,底部为强波峰反射特征,地震属性异常区的特征在地震反射剖面上与正演的含气砂岩反射特征相近,从而查明了HI3气藏的主控因素,并获得高产气井。

【Abstract】 The lithology distribution for shallow gas reservoir in mature oilfield is quite complex,using seismic attribute analysis,gas-bearing sandstone forward modeling and sonic parameter prediction method which is based on Probability Neural Networks(PNN) to predict the distribution of the shallow gas reservoir are the effective tools for exploration of this kind of reservoir.Building geological model which is consistent with regional geology trends and applying the model in seismic forward modeling studies,summarizing the seismic reflection characteristics of the gas reservoirs,are the precondition for reservoir prediction in surface seismic exploration.Based on optimized attributes,PNN is used to integrate multi seismic attributes with well logging sonic data,then the distribution characteristics of the sonic parameters in 3d space can be predicted.On the one hand the workflow above avoid the information sidedness caused when only using single seismic attribute,on the other hand it realizes the reasonable extension of sonic parameters in the zone of interests over the 3d space,therefore the workflow provides a fast and effective tool for gas reservoir prediction.The workflow was applied in Honggang oilfield,Jilin,the seismic forward modeling results show that strong trough reflection from the top of the gas reservoir and strong peak reflection from the bottom of the reservoir can be seen,the anomalies of seismic attributes on seismic sections and the reflection characteristics from forward modeling gas-bearing sandstone are similar,thus major control factor for HI3 gas reservoir was identified,and the highly productive gas wells were the awards for the integrated studies.

【基金】 国家863重点项目(编号2007AA060501);国家自然科学基金(编号40872094)资助
  • 【文献出处】 石油地球物理勘探 ,Oil Geophysical Prospecting , 编辑部邮箱 ,2009年05期
  • 【分类号】P618.13
  • 【被引频次】8
  • 【下载频次】256
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