西湖凹陷古近系始新统平湖组低渗-致密背景下优质储层特征及分布预测

Characteristics and distribution prediction of high-quality reservoirs under the background of low permeability and tightness of Paleogene Eocene Pinghu Formation in Xihu Sag

通过岩石薄片、扫描电镜、粉末粒度、物性等实验测试资料,结合测井及地震数据,开展砂岩储层微观薄片-岩心-测井-地震尺度的研究,以解决西湖凹陷宝云亭区平湖组深层低渗-致密背景下储层有效性识别及预测难的问题。结果表明,宝云亭区平湖组下段优质储层刚性颗粒含量较高,泥质杂基含量低,砂岩较“洁净”;储集空间原生孔隙保存好,次生溶孔占比60%,受沉积物源控制形成的洁粗砂岩及后期溶蚀改造是平湖组埋深4.6 km依然发育优质储层的关键。在划分平湖组成岩相类型基础上,利用BP神经网络拟合技术建立取心段不同成岩相与测井参数的关系,结合地震敏感属性对成岩相进行预测,强物源供给能力形成的水下分流河道微相,叠合中强压实强溶蚀相是优质储层发育区,该地质认识及预测方法对平湖组深层勘探具有一定的指导意义。

Through the analyses of rock thin section,scanning electron microscope,powder particle size and physical properties,combined with the application of logging and seismic data,the study of sandstone reservoir in thin section-core-logging-seismic scale is carried out in order to resolve the difficulty of the validity of reservoir recognition and prediction on Pinghu Formation deep low permeable and tight reservoir in Baoyunting District of Xihu Sag.The results show that the high quality reservoir in the lower member of Pinghu Formation in Baoyunting area has a high content of rigid particles,a low content of argillous matrix,with the development of relatively clean sandstone.It shows that the primary pores in the reservoir are well preserved and the secondary dissolved pores account for 60%.The coarse sandstone formed under the control of sediment sources and the late dissolution transformation are the key to the development of high quality reservoir in Pinghu Formation with a depth of 4.6 km.Based on the lithofacies classification of Pinghu Formation,the relationship between different diagenetic facies and logging parameters in the core section is established by using BP neural network fitting technology,and the diagenetic facies is predicted by combining with seismic sensitive attributes.It is considered that the underwater distributary channel microfacies formed by strong provenance supply capacity and the superposed strong compaction and strong dissolution facies are high quality reservoir development areas.This geological recognition and prediction method has certain significance for deep exploration of Pinghu Formation.