For geotechnical design in heterogeneous rock mass, such as flysch, the rock mass characterisation is important, as it describes engineering geological properties of the investigated area. The knowledge of geomechanical properties of intact rock and discontinuities is crucial for rock mass characterisation, because the geotechnical behaviour of the rock mass during the excavation depends on them. For heterogeneous rock mass characterisation, we need to determine the ratio between different lithological units, as well. Flysch of southwestern Slovenia and east Italy is represented by the cyclic alternation of thin-bedded marlstone and sandstone, with different percentage and different geomechanical properties. Layers are usually 2 cm to 60 cm thick, therefore it is difficult to determine individual lithological units in the field, only using manual data acquisition. This is especially apparent when logging distant and unstable outcrops and excavated faces. As a result, the geological face logs lack of measured data and are subjective. For my doctoral thesis I have therefore decided to test the possibility for integrating close-range photogrammetry and terrestrial laser scanning in the geological logging of excavations in thin-bedded flysch, as it is possible to extract geometrical properties of discontinuities and determine the lithology. Measurements have been performed in selected ground and underground excavations in flysch. The results showed, that in case the data acquisition using close-range photogrammetry and terrestrial laser scanning has been properly planned, it can be appropriate for geological logging of thin-bedded flysch. Due to some limitations, it is advisable to combine both methods. When characterizing flysch by using the RMR classification system, based on which we predict the geotechnical behaviour of the rock mass, the used technologies represent an important contribution towards the objective engineering-geological logging. It is possible to quickly and accurately acquire data of excavated faces. Design relating to measured field data is more realistic than predefined analytical solutions.