Using the example of a Geophysical field, the work examines the history of the formation of anticlinal trap structures in the Gydan oil and gas area. It is noted that in the Gydan oil and gas region, unlike the Nadym–Taz interfluve, the main gas accumulations are concentrated not in the Cenomanian, but in the Aptian sand layers of the TP group. It is concluded that such a redistribution of reserves across complexes is associated with a different history of the formation of trap structures. Unlike the Nadym–Taz region, where the formation of contrasting uplifts occurred in the post-Turonian period, the uplifts of the Gydan oil and gas region were formed at all stages of the Mesozoic–Cenozoic history, and the high potential of the Aptian deposits of this region is associated with an increase in the amplitudes of structures down the section and with the presence of Yarong cap-rock in the roof of the apt and a series of zonally developed clay bundles – tires.

Numerical inversion of borehole electrometry signals in vertical wells was performed for Middle Jurassic deposits of the central part of Western Siberia, and a priori geological information was analyzed. Typical geoelectric models of J₂ reservoirs have been constructed. According to the results of joint inversion of galvanic and induction probe signals, the deposits in the reservoir interval and the host rocks are distinguished by a strong resistivity contrast. The thickness of the formations is small compared to the electric logging probes. The clayey intervals are also characterized by electrical anisotropy. Numerical modeling of electromagnetic logging signals was performed for these models. The article demonstrates the main changes in the synthesized signals with an increase in the zenith angle of inclination of the well.

In the Vibroseis method, along with the main sweep signal, its harmonics, which are usually considered as noise, travel into the Earth's crust. The natural information that can be extracted from the harmonics is the high-frequency component that is absent in the signal. However, even within the frequency range of the main sweep, it is possible to utilize the energy of the harmonics to improve the signal-to-noise ratio. It is shown that the conventional signature deterministic deconvolution loses the energy of the harmonics. At the same time, the optimal statistical focusing filter that accounts for the additive noise factor, successfully utilizes the energy of the harmonics.

The principles of machine learning and its use in solving seismic facies analysis problems are considered. The issues of the efficiency of the obtained solutions at a qualitative level, as well as significant aspects influencing their efficiency are discussed. The latter include: data quality, groups of attributes used, features of clustering algorithms. As an example, the results obtained for horizons related to the Bobrikovian–Tournasian strata of the Lower Carboniferous age in the southwestern part of the Orenburg region are given.

A new approach to solving the direct problem of non-stationary electrodynamics in a complete formulation for a heterogeneous geological environment is proposed. The new formulation of Maxwell's equations makes it possible to write down the equations of the electromagnetic field for potentials in the form of a system of first-order hyperbolic type equations. Information about the spatial distribution of specific electrical conductivity in the geological environment is contained in the electromagnetic response – the reaction of the medium to external electromagnetic influence.

The article presents the results of Prony decomposition using real and synthetic data as an example. This decomposition allows us to obtain the following parameters of a seismic record: attenuation, amplitude, frequency, and phase. The attenuation parameter is associated with the characteristics of the rocks in the geological section, in particular, the compaction of the rocks. The results of the study demonstrate a high correlation between the quality factor, which is the inverse of the obtained attenuation value, and the density of the rocks in the section.