摘要：

泥灰岩储层是页岩油勘探开发的关键目标层，含油饱和度作为表征油气富集程度与评估储层开发潜力的核心参数，其预测精度直接决定“甜点”区筛选效率与开发策略制定的科学性。传统Archie模型建立于均质砂岩储层的理想化假设，在沉积环境复杂、非均质性强的泥灰岩储层中应用时，存在饱和度预测精度不足的缺陷。为解决这一问题，以束鹿凹陷沙三下段泥灰岩储层为研究对象，提出一种基于有机孔隙校正的Archie模型改进方法。首先使用基于流体与有机质联合校正的HERRON模型预测总孔隙度，将元素测井中矿物的质量含量转化为体积含量，根据总有机碳含量、有机质密度及岩石体积密度建立有机质体积分数模型，将转换后的矿物与骨架密度建立线性公式，校正密度孔隙度和中子孔隙度，优化后得到总孔隙度；然后根据总有机碳含量和有机质转化率计算有机质孔隙度，总孔隙度与之相减得到无机孔隙度值；最后使用有机孔隙校正的Archie模型预测研究区饱和度。结果表明，有机孔隙校正的Archie模型增强了孔隙度与饱和度关联的物理合理性，大幅提高预测精度，能够适配研究区复杂的地质背景和较强的非均质性，为泥灰岩储层“甜点区”识别、产能潜力评估以及开发方案优化提供技术支撑。

关键词: 束鹿凹陷, 泥灰岩, 页岩油, 饱和度, 孔隙度, 测井

Abstract:

Marlstone reservoirs stand as the pivotal and primary target formations throughout the entire process of shale oil exploration and development. Oil saturation functions as the fundamental core parameter utilized for characterizing the degree of hydrocarbon enrichment within reservoir rocks and assessing the inherent development potential of subsurface reservoir systems, and its corresponding prediction accuracy exerts a decisive influence on both the screening efficiency of favorable sweet-spot zones and the scientific rigor and rationality in the formulation of practical development strategies for shale oil reservoirs. The conventional Archie model was initially formulated and established on the basis of a set of idealized assumptions that are exclusively applicable to relatively homogeneous sandstone reservoirs. When this classical model is implemented and utilized in marlstone reservoirs characterized by highly complex sedimentary environments and significant reservoir heterogeneity, it is confronted with prominent defects such as insufficient accuracy in the prediction of oil saturation. To address the inherent applicability limitations of conventional methodologies, the present study has conducted systematic petrophysical investigations targeting the Es_3x marlstone reservoir intervals within the Shulu Sag, culminating in the development of an advanced Archie model modification methodology incorporating organic porosity corrections. Initially, compute total porosity utilizing an enhanced Herron petrophysical model incorporating joint corrections for pore fluids and organic constituents, subsequently transform mineral mass fractions derived from elemental spectroscopy logging into mineralogical volume fractions. Establish a volumetric quantification model for organic matter fraction through integration of total organic carbon concentration, kerogen-bitumen density characteristics, and formation bulk density measurements, subsequently formulating a multivariate linear regression relationship between transformed mineralogical volume constituents and dry matrix grain density parameters. Calibrate and correct density-derived porosity and neutron-derived porosity measurements, then optimize these values to obtain total porosity. Subsequently, computationally derive organic-hosted porosity through petrophysical integration of total organic carbon concentration and kerogen transformation ratio parameters, then arithmetically isolate inorganic porosity by subtracting this quantitatively determined organic-hosted porosity component from the pre-established total porosity value. Ultimately, apply the Archie formation resistivity relationship, calibrated specifically for organic porosity systems, to predict hydrocarbon saturation distributions throughout the study area’s reservoir interval. The results indicate that the organic porosity-corrected Archie model enhances the physical plausibility of the relationship between porosity and saturation, significantly improves prediction accuracy, and demonstrates strong adaptability to the complex geological settings and pronounced heterogeneity of the study area. This model provides technical support for the identification of “sweet spot” zones, productivity potential evaluation, and development plan optimization in marlstone reservoirs.

Key words: Shulu Sag, marl, shale oil, saturation, porosity, well logging

中图分类号: 

• TE19

• P618.13