东营凹陷红层地球物理特征分析及有利储层预测

doi:10.13278/j.cnki.jjuese.20200127

摘要/Abstract

摘要： 东营凹陷深部储层是干燥沉积环境下的一套红层，其中的孔一中储层厚度大、钻遇井少，具有较大勘探潜力。但目标区地层结构复杂，埋深从南到北逐渐变大，井震关系一致性不好，储层预测有很大难度。通过综合分析井震特征、优选地震属性、建立井震厚度关系，使用单一最佳属性法、多元线性回归法、基于学习型的非线性储层预测法，得出以下认识与结论：1）研究区红层具有薄互层典型特征，频率较上覆和下伏地层高，地震反射具有中振、低连、低信噪比特征；2）新研发的基于优势频率的流度因子具有最好的厚度相关性，最大振幅、均方根振幅、过零点数、能量半时也较好；3）无论是多元线性回归还是非线性支持向量机，优化的五属性储层预测效果要好于七属性；4）基于交叉验证的支持向量机方法十分适合深部储层小样本储层厚度预测，效果好于单一最佳属性法和多元线性回归法。

关键词: 东营凹陷, 红层, 井震关系, 流度因子, 多元线性回归, 交叉验证SVM, 储层预测

Abstract: The deep reservoir of Dongying sag is a set of red beds under dry sedimentary environment. The reservoir of Ek₁^z has a great exploration potential with large thickness and less drilling. However, the reservoir prediction is very difficult,as the layer structure in the target area is complex, the burial depth becomes deeper from south to north gradually, and the consistency of well-to-seismic relationship is not good. Through a comprehensive analysis of well-to-seismic characteristics, the seismic attributes were optimized and the relationship of well-to-seismic thickness was established. Using the single best attribute method, multiple linear regression method, and learning-type nonlinear reservoir prediction method, the understandings and conclusions are drawn as follows:1) The red bed in the study area has the typical characteristics of thin inter-beds, with higher frequency than the overlying and underlying strata, medium amplitude seismic reflection, low continuity, and low signal-to-noise ratio; 2) Based on the dominant frequency, the newly developed mobility attribute has the best thickness correlation and the maximum amplitude, the root mean square amplitude, zero crossing count,and the energy half-time attribute is also better; 3) Whether it is linear regression or nonlinear support vector machine (SVM) method, the optimized five attributes reservoir prediction effect is better than that of seven attributes; 4) The cross-validation based SVM method is the most suitable one for the thickness prediction of small sample wells in deep reservoirs, and its effect is better than the single best attribute method and the multiple regression method.

Key words: Dongying sag, red beds, well-to-seismic relationship, mobility, multiple linear regression, cross validation SVM, reservoir prediction

中图分类号:

P631.4

张军华, 刘震, 李琴, 任雄风, 赵杰. 东营凹陷红层地球物理特征分析及有利储层预测[J]. 吉林大学学报(地球科学版), 2021, 51(4): 1256-1267.

Zhang Junhua, Liu Zhen, Li Qin, Ren Xiongfeng, Zhao Jie. Analysis of Geophysical Characteristics and Favorable Reservoir Prediction of Red Beds in Dongying Sag[J]. Journal of Jilin University(Earth Science Edition), 2021, 51(4): 1256-1267.

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