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物探与化探  2025, Vol. 49 Issue (5): 1110-1117    DOI: 10.11720/wtyht.2025.2466
  方法研究信息处理仪器研制 本期目录 | 过刊浏览 | 高级检索 |
多属性融合技术预测薄互砂体储层厚度——以哈萨克斯坦W油田为例
依尔繁·阿西木江1, 卢志明1, 艾尼·买买提1, 米尔扎提·迪力木拉提2, 多力坤·买买提明1
1.中国石油新疆油田分公司 勘探开发研究院,新疆 克拉玛依 834000
2.中国石油新疆油田分公司 油气储运公司,新疆 克拉玛依 834000
Prediction of thin interbedded sandstone reservoir thickness using multi-attribute fusion technology:A case study from the W oilfield,Kazakhstan
Yierfan Aximujiang1, LU Zhi-Ming1, Aini Maimaiti1, Mierzhati Dilimulati2, Duolikun Maimaitiming1
1. Research Institute of Exploration and Development,Xinjiang Oilfield Company,PetroChina,Karamay 834000,China
2. Oil & Gas Storage and Transportation Company,Xinjiang Oilfield Company,PetroChina,Karamay 834000,China
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摘要 

哈萨克斯坦南图尔盖盆地W油田薄互砂体横向变化快且连通性差。多年来,常规储层预测手段应用效果不佳,有利储层横、纵向展布特征认识不清等问题,严重制约了该油田的勘探开发进程。本文针对储层预测难点问题,配套应用正演模拟、叠后资料处理、多属性融合等技术,集成一套适用于研究区地质条件的薄互砂体预测方法:在正演模拟构建储层变化与地震波形变化关系的基础上,通过经验模态反褶积与蓝色滤波处理提高地震资料主频及其分辨率,高分辨率资料波形指示反演结果与均方根振幅、瞬时频率的多属性融合有利于判别目标砂体的展布范围与厚度。研究结果表明:该方法有效预测了有利目标砂体的展布范围及厚度,预测砂体厚度与全区钻遇砂体厚度误差小于2 m,储层平面分布与地质认识一致,可为油田后续滚动评价与高效开发提供有效指导。

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依尔繁·阿西木江
卢志明
艾尼·买买提
米尔扎提·迪力木拉提
多力坤·买买提明
关键词 W油田薄互砂体正演模拟多属性融合储层预测    
Abstract

The thin interbedded sand bodies in the W oilfield of the South Turgay Basin,Kazakhstan,exhibit rapid lateral variation and poor connectivity.For many years,the application of conventional reservoir prediction methods has yielded unsatisfactory results,and unclear insights into the horizontal and vertical distribution characteristics of favorable reservoirs have severely constrained the oilfield's exploration and development.To address these challenges,this study adopted an integrated approach incorporating forward modeling,post-stack seismic processing,and multi-attribute fusion to develop a prediction methodology suitable for the geological conditions of the study area.Based on forward modeling that established the relationship between reservoir variation and seismic waveform changes,empirical mode decomposition and blue filtering were applied to enhance the dominant frequency and resolution of the seismic data.The multi-attribute fusion of waveform indication inversion results,root-mean-square amplitude,and instantaneous frequency ultimately delineated the distribution and thickness of the target sand bodies.The results demonstrate that this method effectively predicts the distribution and thickness of favorable sand bodies,with errors of less than 2 meters compared to drilled thicknesses across the field.The spatial distribution of reservoirs is consistent with geological understanding.This study provides valuable guidance for subsequent rolling evaluation and efficient development of the oilfield.

Key wordsW oilfield    thin interbedded sandbody    forward modeling    multi-attribute fusion    resvoir prediction
收稿日期: 2024-05-30      修回日期: 2025-02-10      出版日期: 2025-10-20
ZTFLH:  P631.4  
基金资助:中国石油科技重大专项(2011E-2506);中国石油哈萨克斯坦公司科研基金研究项目(577108/2021/2)
作者简介: 依尔繁·阿西木江(1993-),男,工程师,硕士研究生,2019年毕业于中国石油大学(华东)地质工程专业,主要从事油气田构造解释、储层预测及勘探部署工作。
引用本文:   
依尔繁·阿西木江, 卢志明, 艾尼·买买提, 米尔扎提·迪力木拉提, 多力坤·买买提明. 多属性融合技术预测薄互砂体储层厚度——以哈萨克斯坦W油田为例[J]. 物探与化探, 2025, 49(5): 1110-1117.
Yierfan Aximujiang, LU Zhi-Ming, Aini Maimaiti, Mierzhati Dilimulati, Duolikun Maimaitiming. Prediction of thin interbedded sandstone reservoir thickness using multi-attribute fusion technology:A case study from the W oilfield,Kazakhstan. Geophysical and Geochemical Exploration, 2025, 49(5): 1110-1117.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2025.2466      或      https://www.wutanyuhuatan.com/CN/Y2025/V49/I5/1110
Fig.1  W油田正演模拟
Fig.2  地震正演剖面属性特征
Fig.3  地震资料提频效果对比
Fig.4  波形指示反演剖面
Fig.5  地震属性与砂体厚度相关性分析
Fig.6  多属性融合结果与实钻井砂体厚度相关性分析
Fig.7  W油田M层属性平面
Fig.8  W油田M层多属性融合砂体厚度预测等值线
井名 钻遇厚度/m 预测厚度/m 误差/m
W1 5.6 6.2 0.6
W107 4.0 3.4 -0.6
W108 0 0.3 0.3
W111 2.3 3.5 1.2
W112 8.6 8.7 0.1
W13 14.5 12.4 -2.1
W130 10.6 9.7 -0.9
W15 12.1 10.2 -1.9
W16 13.1 14.1 1.0
W18 5.2 6.5 1.3
W19 11.5 10.4 -1.1
W205 3.5 5.1 1.6
W21 4.9 5.9 1.0
W216 8.6 9.6 1.0
W250 3.4 4.7 1.3
W26 8.1 9.9 1.8
W260 4.5 4.1 -0.4
W27 8.1 6.5 -1.6
W270 11.3 12.6 1.3
W271 16.1 14.3 -1.8
W272 11.1 12.9 1.8
W273 10.2 11.9 1.7
W275 13.1 11.4 -1.7
W28 6.2 6.6 0.4
W4 11.6 13.5 1.9
W41 5.5 7.1 1.6
W49 7.4 6.9 -0.5
W57 7.3 6.2 -1.1
W58 2.8 3.5 0.7
W6 5.5 5.0 -0.5
W90 13.8 13.6 -0.2
W96 13.2 11.8 -1.4
Table 1  多属性融合砂体厚度预测误差分析
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