Abstract
The study is focused on the problem of using geophysical data to estimate brittleness of rock masses for the needs of petroleum industry. Three main developed ways to estimate brittleness—mineral-based, log-based, and elastic-based brittleness indices—are discussed from the perspective of scaling factor. The study highlights the contradictions between brittleness indices calculated from the same data using various ways of introducing brittleness. These contradictions are explained by scaling factor, as geophysical data used for brittleness estimation are typically obtained at different spatial and temporal scales. A model based on the effective medium theory is used to understand the relationships between inner structure of inhomogeneous rocks and their brittleness indices estimated from laboratory tests on core samples as well as log data analysis.
Highlights
Exploration and development of hydrocarbon reservoirs are related to many fields of applied sciences and mechanics in particular
Before applying the constructed rock-physics model for the log-based brittleness indices (LBI) analysis of carbonate rocks we test it on available log data on elastic wave velocities, porosity, and density
Recall that LBI6 was proposed with energy concept kept in mind: critical energy release rate was considered as a factor con
Summary
Exploration and development of hydrocarbon reservoirs are related to many fields of applied sciences and mechanics in particular. Filtration processes, well drilling, well log data obtaining and assessment, and hydraulic fracturing are all closely related to hydrodynamics and rock mechanics [1]. It is natural that methods used in these fields are being developed to answer industrial needs: for example, failure mechanics has been developed a lot to understand and optimize hydraulic fracturing procedures. Consideration of hydrocarbon fields’ exploration and development makes emergence of specific problems evident. Some of these problems have their analogs in the other fields, so ideas regarding the ways to solve them are available. The current study is aimed at one of such problem—rock brittleness estimation
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