WTK油田白垩系低阻油层成因及流体识别方法

针对南图尔盖盆地WTK油田白垩系油藏低阻油层发育广泛、识别难度大的现状,利用岩心分析与测井资料,对该区低阻油层成因机理开展研究,并结合试油等资料,探索油、水层识别方法。根据研究区地质特征,从沉积过程储集层岩性与黏土矿物含量、成岩作用中孔隙结构特征与流体分布、成藏过程中油水分异等内因及钻探过程中测量方法精度等外因开展综合研究。研究区油层低阻主控因素为黏土矿物阳离子附加导电性与高束缚水饱和度和矿化度引起的导电性,构造幅度低与油层厚度薄为次要因素。通过对储集层导电模型分析,基于地层水与束缚水饱和度计算模型,构建电性特征与流体饱和度对应关系,分层系建立低阻油层定量评价模型,划分各流体类型下限标准,实现流体精确识别。在生产实践应用中,测井解释与实际生产匹配程度88.2%,应用效果较好。

Genesis and Fluid Identification Method of Cretaceous Low-Resistivity Oil Layers in WTK Oilfield

The Cretaceous low-resistivity oil layers in WTK oilfield, South Turgay basin are widely developed and difficult to identify. In this paper, the genetic mechanism of these low-resistivity oil layers was analyzed using core analysis and logging data, and the method for identifying oil/water layers was stuided by combining formation testing data. According to the geological features of the study area, comprehensive research was carried out on internal factors and external factors. The internal factors include the reservoir lithology and clay mineral content during the deposition process, the pore structure characteristics and fluid distribution during diagenesis, and the oil-water differentiation during hydrocarbon accumulation, and the external factors include the accuracy of measurement methods during drilling, etc. The main controlling factors for the low resistivity of the oil layers in the study area are the additional conductivity of clay mineral cations and the conductivity caused by high irreducible water saturation and salinity, and the secondary controlling factors are low structural amplitude and thin oil layers. By analyzing the reservoir conductivity model and based on the model for calculating formation water and irreducible water saturations, the relationship between electrical characteristics and fluid saturation was established, the quantitative evaluation model of low-conductivity oil layers was constructed by stratification, and the lower limit standard for dividing each fluid type was made to realize accurate fluid identification. The practical application shows that the matching degree between the results of logging interpretation and actual production reaches 88.2%, suggesting a good application effect.