特种油气藏2023，Vol.30Issue(6)：40-47,8.DOI:10.3969/j.issn.1006-6535.2023.06.006
基于三维地震数据的短期旋回内薄层砂体的预测
Application in the Prediction of Thin Sand Body Within Short-term Sequence Cycle Based on 3D Seismic Data
摘要
Abstract
Thin sand bodies are widely developed in the Cretaceous Qingshuihe Formation in the hinterland of Jung-gar Basin,and the thickness of the reservoir is about 10-20 m.The prediction of thin sand bodies is difficult due to the lack of discernible seismic data.With the data from logging curves and well drilling,and under the guidance of the principle of high-resolution sequence stratigraphy,the first member of the Cretaceous Qingshuihe Formation was divided into 1 long-term cycle,2 medium-term cycles,and 6 short-term cycles.Within each short-term cy-cle,6 seismic inversion slices were preferentially selected through the seismic slicing technique.By this method,the sedimentary evolution characteristics of sand bodies in six different periods,namely,low level period,lake in-trusion period,high level period,lake recession period,lake intrusion period,and lake flooding period,within the first member of the Qingshuihe Formation(about 140 m thick)in the hinterland of the Junggar Basin,were identi-fied,thus reducing the multiplicity of interpretations of the seismic data.This paper combines seismic slicing and high-resolution sequence stratigraphy,plays the role of lateral resolution of seismic data and high-resolution of wells,overcomes the lack of seismic resolution,deepens the research on the identification of thin sand body and depositional law in short-term cycle,achieves a good exploration effect,guides the deployment of wells in the field,and serves as a reference for the identification of thin bed in other areas.关键词
薄层/砂体预测/短期旋回/高分辨率层序地层学/地震切片/准噶尔盆地Key words
thin bed/sand body prediction/short-term cycle/high-resolution sequence stratigraphy/seismic sli-cing/Junggar Basin分类
石油、天然气工程引用本文复制引用
赵长永,陈希光,李俊飞,宋志华,常少英,单祥,郭华军,厚刚福..基于三维地震数据的短期旋回内薄层砂体的预测[J].特种油气藏,2023,30(6):40-47,8.基金项目
中国石油"十四五"前瞻性基础性重大科技项目"深层超深层有效储层形成主控因素与预测技术研究"(2021DJ0202) （2021DJ0202）
2022年新疆维吾尔自治区"天山英才"培养计划 （）
