Igneous lithology identification and lithofacies classification in the basin using logging data: Taking Junggar Basin as an example

Taking the Junggar Basin as an example, this paper proposed a method for logging lithology identification and logging facies classification of igneous rock. Using the theory of igneous rocks and the technique of rock physics, we have set up the logging classification standard for igneous rock lithology and lithofacies, and revealed that the natural gamma ray logging, density logging, and ECS logging are the most sensitive logging methods to the variety of chemical components of igneous rock. We have observed that, from basic to acid igneous rock, the intensity of natural radioactivity is gradually growing, the density is reducing, the content of metal elements is reducing, and the silica content is growing. The structural change is partly reflected by natural radioactivity, density, resistivity of igneous rock. Compared with the homogeneous lava and pyroclastic rock, the intensity of radioactivity, the value of density, and the resistivity are degraded in magnitude. The most sensitive logging for igneous rock alteration degree is the compensated neutron logging, while the density and the resistivity also partly reflected the alteration degree. With the increase of the alteration degree, both the density value and the resistivity appear a tendency of declining. We have utilized the logging curves which are sensitive to lithology to make multidimensional igneous lithology identification chart. By using imaging logging, the texture and structure of igneous rock identification chart was made; the ECS logging was applied to distinguish the rock composition; and the methods were validated through the core data. A technique for igneous rock lithology recognition mode was proposed based on the conventional logging, imaging logging, ECS logging, and core calibration. Thus a way for comprehensive assessment of the type, composition, texture and structure of igneous rock has been built up; this method greatly enhances the identification accuracy for complicated igneous lithology. ©, 2015, The Editorial Office of Earth Science Frontiers. All right reserved.