基于模型正演的深层砂泥岩薄互层地震分辨率研究

2014年 21卷 第05期
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Study on seismic resolution of deep thin sand and shale interbedded based on seismic forward modeling
黄诚 桂红兵 杨飞 韩福民 邓明霞 朱伟
油气资源与勘探技术教育部重点实验室(长江大学),湖北 武汉 430100 中海油田服务股份有限公司物探事业部,天津 300452 中国石化中原油田分公司物探研究院,河南 濮阳 457001
MOE Key Laboratory of Exploration Technologies for Oil and Gas Resources, Yangtze University, Wuhan 434000, China Geophysical Department, Oilfiled Services Limited, CNOOC Ltd., Tianjin 300452, China Geophysical Research Institute, Zhongyuan Oilfield Company, SINOPEC, Puyang 457001, China
东濮凹陷前梨园洼陷及周边地区有丰富的剩余石油和天然气资源,这些剩余的资源量绝大部分分布在埋深大于3 500 m的古近系—新近系及以下层系的深层隐蔽油气藏中,主要为砂泥岩薄互层沉积。但是受地震资料分辨率的影响,识别这类深层砂泥岩薄互层的隐蔽性油气藏具有一定的难度,使得油田深层的地层分布情况并不为研究人员所了解。正演模拟作为一种技术方法,是地震应用技术的基础,将其与反演方法进行有效地结合一定程度上能提高地震解释的精度。文中以此为依据,建立与实际情况相对应的地质模型,同时对正演模拟结果进行波阻抗反演,定性并定量地分析基于模型正演的地震预测所能识别的最小单砂体厚度,为东濮凹陷地区的深层储层预测精度提供参考依据。
Qianliyuan Sag in Dongpu Depression and its surrounding areas are rich in oil and gas resources. The vast majority of these remaining resources are located in Tertiary and the following strata below 3,500 m of deep subtle reservoirs and the reservoir is mainly thin sand and shale interbed deposition. However, affected by the resolution of seismic data, the identification of such subtle reservoir in deep sand and mudstone has a certain degree of difficulty, which makes the deep stratigraphic distribution of oilfled not be understood by researchers. Forward modeling as a method of technology is the foundation of seismic technology. Combining it with inversion method effectively can improve the precision of seismic interpretation. On this basis, the paper will establish geological model which is corresponding to actual situation. And it uses the forward modeling results for impedance inversion, then qualitatively and quantitatively analyzes the smallest single sand based on seismic prediction of forward modeling, which provides references for the prediction accuracy of deep reservoir in Dongpu Depression.
深层隐蔽油气藏; 砂泥岩薄互层; 正演模拟; 储层预测精度;
deep subtle reservoirs; thin sand and shale interbed; forward modeling; reservoir prediction accuracy;
10.6056/dkyqt201405012