摘要
四川盆地川中地区下二叠统栖霞组天然气勘探获得了重大突破。该区储层以薄层状白云岩为主,孔隙类型多样,孔隙结构复杂,溶蚀孔洞的大小、分布情况都表现出很强的非均质性,大大增加了测井储层综合评价的难度。由于成像测井具有较高纵向分辨率、直观反映井壁孔洞和裂缝等优点,故利用该区丰富的成像测井资料来计算栖霞组地层的孔隙度谱,并将孔隙结构分类,建立成像孔隙度谱图版,然后根据孔隙度谱开展基质孔和次生溶孔的定量计算,并结合常规测井计算的孔隙度,对储层类型进行了划分。结果表明:(1)成像孔隙度谱结构特征在一定程度上可反映孔径大小的分布情况,进而反映储层孔隙结构特征,不同的谱结构反映不同孔隙类型组合特征和原生孔隙与次生孔隙的搭配关系;(2)栖霞组孔隙度谱结构可分为无峰宽谱型、多峰中谱型、单峰中谱型和单峰窄谱型4种类型,有利储层的成像孔隙度谱以无峰宽谱型和多峰中谱型为主;(3)通过标定成像孔隙度谱可定量计算地层基质孔和溶蚀孔的孔隙度,进而划分储层类型。
Several great gas discoveries have been made recently in the Lower Permian Qixia Formation in the central Sichuan Basra. The reservoirs are mainly composed of laminated dolomite, and characterized by multiple types of pores and complex pore structures, with dissolved pores which are strongly heterogeneous in size and distribution, making the comprehensive logging reservoir evaluation much more difficult. Image logging is higher in vertical resolution and can depict intuitively the pores and fractures on the wellbore wall. In this paper, therefore, the porosity spectrum of Qixia Formation strata was calculated by using the abundant image logging data of this area. Furthermore, pore structures were divided and image porosity spectrum chart was prepared. Then, matrix porosity and secondary dissolved porosity were calculated quantitatively based on the porosity spectrum. Finally, combined with the porosity cal- culated from conventional logging, the reservoirs were classified. It is shown that the structure characteristics of image porosity spec- trum, to a certain extent, can reflect the distribution of the pore diameters, and even the structural characteristics of reservoir pores, and different spectrum structures can reflect the combination characteristics of different types of pores and the collocation relationship between primary pores and secondary pores. The porosity spectrum of Qixia Formation can be structurally divided into four types, i.e., no-peak wide spectrum, multi-peak medium spectrum, unimodal medium spectrum, and unimodal narrow spectrum. The image porosi- ty spectrum of favorable reservoirs is mainly in the form of no-peak wide spectrum and multi-peak medium spectrum. Matrix porosity and dissolved porosity can be quantitatively calculated by calibrating the image porosity spectrum, and ultimately reservoirs classifi- cation can be implemented.
出处
《天然气勘探与开发》
2017年第4期9-16,共8页
Natural Gas Exploration and Development
基金
中国石油天然气股份有限公司重大科技专项"西南油气田天然气上产300亿立方米关键技术研究与应用"(编号:2016E-0604)
关键词
四川盆地
早二叠世
栖霞组
成像孔隙度谱
孔隙结构
储层划分
Sichuan Basin
Early Permian
Qixia Formation
Image porosity spectrum
Pore structure
Reservoir classification
