新疆石油地质 ›› 2011, Vol. 32 ›› Issue (4): 385-386.

• 油藏工程 • 上一篇    下一篇

基于地震多属性的孔隙度预测——以川东A气田为例

张新亮1, 何丽箐2, 吴俊1   

  1. 1.中国地质大学能源学院,北京 100083;
    2.中国石油冀东油田分公司勘探开发研究院,河北唐山 063004
  • 收稿日期:2010-12-06 出版日期:2011-08-01 发布日期:2020-08-19
  • 作者简介:张新亮(1979-),男,新疆阿克苏人,在读博士研究生,工程师,矿产勘探,(Tel)15810633183(E-mail)zxlmm2000@163.com.

Application of Porosity Prediction Based on Seismic Multiattributes to Eastern Sichuan A Gas Field

ZHANG Xin-liang1, HE Li-qing2, WU Jun1   

  1. 1. Institute of Energy Resources, China University of Geosciences, Beijing 100083, China;
    2. Research Institute of Exploration and Development, Jidong Oilfield Company, PetroChina, Tangshan, Hebei 063004, China
  • Received:2010-12-06 Online:2011-08-01 Published:2020-08-19

摘要: 利用基于地震多属性的孔隙度预测方法,可综合权衡各属性参数,更客观、有效地反映孔隙度的变化。建立测井孔隙度同地震属性联系,运用多元回归、误差分析、交叉验证等技术来确定最优的属性类型及数量;结合人工神经网络方法建立这些属性与测井孔隙度之间的映射关系,预测孔隙度在平面、垂向上的分布特征。首次将地震多属性孔隙度预测方法运用于川东A 气田超致密砂岩储集层孔隙度的预测研究,取得了良好的效果。

关键词: 孔隙度, 预测, 地震多属性, 神经网络, 多元回归, 交叉验证

Abstract: Using porosity prediction method based on seismic multiattributes can comprehensively balance individual attribute parameters so that more objectively and effectively reflect the variation of porosity, develop the relationship between the well log porosity and the seismic attribute and determine the optimal type and amount of attribute by means of multielement regression, error analysis and cross-validation techniques, and finally establish the mapping relations between the attributes and well log porosity and predict the lateral and vertical distributions of porosity. This paper first applies this method to the eastern Sichuan A gas field and predicts the porosity distribution of its super-dense sandstone reservoir. And good result is gained.

Key words: porosity, prediction, multiattribute, neural network, multielement regression, cross validation

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