致密地层岩石脆性指数的测井优化建模

脆性评价是页岩油气、致密油气等非常规油气藏的大型压裂、开发等储层改造工程中的关键工作。根据岩石力学、动态弹性参数和岩石物理、X-射线衍射、地球化学等资料,分析了国内外几种常用脆性指数之间的相互关系,研究了弹性参数法脆性指数与岩石矿物组分及含量的关系,明确了矿物及组分对脆性的影响并应用多元回归法建立了基于权重矿物组分的脆性指数模型。构建新的岩石物理体积模型,应用最优化测井方法得到岩石的矿物和孔隙含量,实现了基于常规测井资料的脆性指数精确计算。研究表明:岩石脆性指数与矿物组分及含量有关,不同区块、不同地层的矿物具有不同的脆性特征;该工区方解石是使岩石脆性增强和裂缝产生的主要矿物,有机碳、黏土、石英和斜长石是降低脆性的重要矿物;基于常规测井资料的优化计算所得岩石组分及含量与实验数据一致性高;将处理结果与矿物组分模型相结合得到的脆性指数与弹性参数法脆性指数基本一致,为无横波资料井的岩石脆性评价奠定了基础。

Logging optimization modeling on brittleness index of tight formation rocks

Brittleness evaluation is a key parameter for massive fracturing, development and other reconstruction engineering of unconventional hydrocarbon reservoirs such as shale and tight oil and gas. Based on rock mechanics, dynamic elastic parameters, rock physics, X-ray diffraction and geochemical data, this study analyzes the correlations among several brittle indices at home and abroad, carries out researches on the relationship between the brittleness index obtained by elastic parameter method and rock mineral components as well as contents, and clarifies the influences of minerals and components on brittleness. Meanwhile, the brittleness index model based on weighted mineral components is built using multiple regression method. A new rock physics volume model was established to obtain rock mineral and pore contents with the use of optimization logging method, based on which brittleness index can be precisely calculated based on conventional logging data. The results show that rock brittleness index is related to mineral components and contents. The minerals in different formations of various blocks had diversified brittle characteristics. Calcites in this work area are the main mineral produced through enhancement of rock brittleness and fissure generation, while the important minerals such as organic carbon, clay, quartz and plagioclase are formed due to brittleness reduction. Rock components and contents obtained by optimization calculation based on conventional logging data are highly consistent with experimental data. The brittleness index obtained through combination of processing results and mineral component model was basically consistent with that obtained by elastic parameter method, laying a foundation for evaluating rock brittleness of wells in lack of shear wave data.