煤系地层中薄砂岩储层预测

Thin-sandstone reservoir prediction in coal-bearing strata

K区块沉积环境以三角洲和滨湖沼泽为主,主要沉积为灰色砂岩、粉砂岩、泥岩和煤系地层,储层薄、横向变化快,且煤层对地震勘探的影响较大。地震资料常规反演方法及流程难以对薄砂岩储层实现有效预测。针对这种情况,文中提出了一套针对该区薄砂岩储层预测流程,有效实现了对薄砂岩储层分布范围及储层物性特征的预测。首先,通过对钻井、测井和地震等资料的综合分析,确定解释岩性的敏感参数,建立岩性解释模板;其次,利用地震波阻抗贝叶斯反演遗传算法以及云变换伽马属性预测技术,得到波阻抗及伽马数据体;最后,综合利用波阻抗和伽马数据体,结合岩性解释模板,实现对储层物性的预测。

Targets in Block K in Turgai Basin are sets of coal-bearing layers composed of sandstones and mudstones(lakeshore and swamp facies).They are characterized by thin beds and thickness quick changes,and seismic data quality is rather poor due to coal bed influence.It is very difficult to predict thin reservoirs on seismic data processed by conventional inversion methods.We propose here an approach to predict this kind of thin reservoirs based on multi-discipline data.Based on analysis of drilling,logging,and seismic data,we find out a few parameters sensitive to lithological interpretation and build a lithological interpretation template.Then with a wave impedance inversion genetic algorithm and cloud-transform gamma-ray attribute prediction,we derive the impedance and gamma attribute volumes.Finally,with the lithological interpretation template we predict thin-sandstone reservoirs in coal-bearing strata on the impedance and gamma attribute volumes.