The GEOLAB Company is developing technology and software for geophysical oil and gas exploration dataprocessing.

The staff of the company is involved in developing its own algorithmic framework and software products designed for high-precision interpretive seismic data processing. Among the original developments are the methods for velocity-depth model constructing: from kinematical inversion to full waveform inversion.

The use of such procedures can significantly improve the reliability of the obtained depth images.


Besides, the original seismic migration approaches have been implemented based on the ideas of the company's team experts.

Such methods allow high quality depth seismic imaging. Among the original data processing methods the package GEOLAB is equipped with, are various tools for attenuation of multiple reflections.

Their use always causes the customer's approval and allows processing of data acquired in different seismic and geological conditions (including the complex cases) and from different regions of the world.


All the procedures implemented in our software allow for efficient processing and interpretation of both 2D and 3D seismic data, including processing in real time.

This is facilitated by a high level of programming of the algorithms: using high-performance parallelization and cloud computing.


Currently, our subsidiary "GEOLAB-IT", resident of the "Skolkovo" Fund, is implementing a project to create a radically new software package for high-precision velocity-depth model building and seismic depth imaging,

which will considerably reduce the risks of exploration, prospecting and mineral mining.

The project is being funded by "Skolkovo".



Input data

Traveltime tomography


Migration velocity analysis


Full-waveform inversion



The unique elements of the technology include:


  • A three-stage method for seismic velocity model building including both the kinematical and dynamical wavefield inversion,


  • Accurate depth imaging tools, with the algorithms based on the theoretical background, confirmed by 
    scientific publications of the members of the project team,


  • Efficient software implementation of the algorithms for present-day parallel (supercomputers) and distributed ("cloud") computing platforms.


The new software package will significantly improve the accuracy of model building in comparison with the standard