新疆石油地质

新疆石油地质 ›› 2006, Vol. 27 ›› Issue (6): 746-748.

• 应用技术 • 上一篇    下一篇

地震反演技术在火山岩储集层预测中的应用——以枣35块为例

郑亚斌1,2, 王延斌1, 韩德馨1   

  1. 1.中国矿业大学, 北京 100083;
    2.中国石油石油勘探开发科学研究院, 北京 100083
  • 收稿日期:2006-01-04 修回日期:2006-03-29 出版日期:2006-12-01 发布日期:2020-10-21
  • 作者简介:郑亚斌(1966-), 男, 河北晋州人, 在读博士研究生, 油藏描述与油气成藏,(Tel) 13683300395(E-mail) yabin.z@163.com.

Application of Seismic Inversion Technique to Prediction of Volcanic Reservoir —An example of Block Zao-35

ZHENG Ya-bin1,2, WANG Yan-bin1, HAN De-xin1   

  1. 1. China University of Mining and Technology, Beijing 100083, China;
    2. Research Institute of Petroleum Exploration and Development, PetroChina, Beijing 100083, China
  • Received:2006-01-04 Revised:2006-03-29 Online:2006-12-01 Published:2020-10-21

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摘要： 利用测井约束的波阻抗反演和基于神经网络的多属性反演技术, 研究了黄骅坳陷枣35 断块火山岩储集层波阻抗反演是基于模型的地震反演方法, 反演结果能比较清楚地反映火山岩体的结构, 对火山岩的横向预测和期次划分有很大帮助; 基于神经网络的多属性反演则把岩性参数、测井参数、地震参数联系起来, 反演出火山岩的厚度和物性参数分布。反演结果可以为储集层地质建模和储量计算提供地质依据。

关键词: 火山岩, 储集层, 波阻抗, 神经网络, 反演, 物性参数

Abstract: This paper presents two methods of seismic data inversion for study of volcanic reservoir of Block Zao-35 in Huanghua depression: the well log constrained wave impedance inversion and the neural network-based multi-attribute inversion. The former is one of model-based seismic inversion, helpful to recognize the structure of volcano, laterally predict the volcanic rock and classify the volcanic process stage; the latter provides the ranges of thickness and physical property of volcanic rocks by the inversion, combined with lithology, well logs and seismic parameters. The results of inversion could be as bases for geologic modeling and reserves calculation of volcanic reservoir.

Key words: volcanic rock, reservoir, wave impedance, neural network, inversion, petrophysical property, parameter

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