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We present a filtration tomography technique for isolating components of the gravity field anomalies generated by inhomogeneities of the horizontally layered density model. The filtration algorithm of field separation relies on the solution of the forward and inverse problems of analytical continuation of harmonic functions through the horizontal boundary plane. We applied the regularizing algorithms to analytical continuation of the gravity field "down" to its generating sources. The fields successively recalculated upward and downward relative to preset depths allowed us to partition the initial (total) field as the sum of the fields generated in the layers based on the properly selected adaptive regularization parameter α. For the sake of stability of the inverse problem solution in the analytical continuation of the observed gravity field to a certain depth, we used the Lavrentiev regularization scheme involving the L -curve method (for selecting the adaptive regularization parameter). The smoothing regularization parameter values obtained from the preset successive depth intervals and grid step for the observed field are shown to be optimal for dividing the observed field into components corresponding to different depths. The developed algorithms for massively parallel computing systems and their application to a group of different heights were numerically implemented on the Uran supercomputer.

The work is concerned with the theoretical substantiation of a new geophysical technology for studying a unique geologic object with unconventional hard-to-recover hydrocarbon reserves. The technology is based on transient electromagnetic sounding from a spatially distributed system of highly deviated wells drilled in target objects near the Bazhenov Formation. The results of computer modeling predetermine a new direction for the geological exploration of unconventional hydrocarbon deposits. We consider a numerical solution to the 3D direct problem of pulsed electromagnetic sounding and, on its basis, develop a computational scheme and a computer program. A mathematical model is constructed, which describes the sensing process through a pulsed source for electromagnetic-field excitation. The Fourier transform is used for time discretization, and the vector finite element method, for spatial discretization. This approach makes it possible to obtain many independent 3D problems and solve them in parallel by applying the modern multiprocessor technology. Using the KNL and Broadwell computing nodes of the Siberian Supercomputer Center SB RAS, we performed calculations of electromagnetic signals, which showed a high efficiency of the devised computing scheme and a high performance of the implemented algorithm. Despite the fact that the total peak performance of the KNL nodes is 2.5 times higher than that of the Broadwell nodes, their practical application for performing large-scale 3D modeling on the cluster shows a high efficiency of the latter. When choosing the most suitable computing architecture for the implementation of mass calculations, one should not rely on their formal characteristics only; significant performance is achieved when taking into account the peculiarities of the computational methods employed for solving a specific problem. The implemented more efficient ways of performing parallel matrix-vector operations did not significantly increase the performance for this computational scheme. The created computational tools form the basis for further design of the configuration of a pulsed electromagnetic sounding system and for identifying the capabilities of the new geophysical technology for examining complex geologic media.

The work deals with the development of methodological and algorithmic tools for the quantitative interpretation of oil well resistivity logs. We review the results of applying the neural-network-based approach to the inversion of resistivity logs measured in thinly bedded high-contrast environments. The capabilities of the proposed approach are demonstrated by the example of the algorithm for noninterative express-inversion of unfocused lateral logs (BKZ). BKZ is the unfocused array logging method widely used in the Commonwealth of Independent States for oil well studies. BKZ logs are known for their complexity: The signals of unfocused gradient probes are highly affected by the medium properties below and above the measuring point. The developed algorithm is based on the inversion of full logs into the parameters of a 2D axisymmetric model of the medium, which allows naturally taking into account the influence of surrounding rocks and borehole conditions. Transition from the «layered» parametrization conventional for BKZ logs interpretation to a quasi-continuous change of properties along the well axis allows extracting meaningful information at every measurement point and constructing high-resolution geoelectric models of the sediments. The noniterative nature of the algorithm provides a high computing efficiency. This opens up the possibility of using the 2D inversion advantages to increase the reliability of the initial express interpretation results. Testing the algorithm on the practical data from West Siberian oilfields has revealed the field of its maximum efficiency, namely, study of impermeable and low-permeability sediments, such as the complex shaly caprocks and bituminous deposits of the Bazhenov Formation. With high-quality input data, the approach is also efficient for studying permeable terrigenous sediments.

Prediction of the open porosity factor below boreholes and in the interwell space, from electromagnetic sounding and electrical logging data, has been studied. Modeling porosity data are synthesized from laboratory studies on the samples of two boreholes drilled in the Bishkek geodynamic site. The porosity prediction is carried out using specific electrical resistivity data obtained from 1D inversion of magnetotelluric sounding data collected in the vicinities of these wells. A new approach to predict porosity is suggested, based on the constructing of electromagnetic resistivity pseudologs at the target location. The comparison of this technique with other options indicates that its application results in substantial improvement of the predicted accuracy (in particular, relative errors of prediction in double depth of the borehole and in the interwell space could be 2 and 8 %, respectively). In general, the porosity predictions, based on Archie formula, give worse results.

The Albian carbonates of the Quissama Formation in the Campos Basin, southeastern Brazil, are important oil reservoirs. They make part of a carbonate platform that formed along the eastern coast of Brazil and the western coast of Africa during the Albian, which resulted in the opening of the South Atlantic Ocean. Subsequently, this reservoir was subjected to different postdepositional diagenetic processes. The present study utilized geophysical well logs to estimate the porosity of this reservoir, based on density, neutron porosity, and sonic logs. The estimates do not show good results when compared with the laboratory measurements. Then, exploring the fact that these logs are obtained with different physical principles, a multiple linear regression and an artificial neural network with Bayesian stochastic approach were applied, which resulted in a better porosity estimate. As porosity is a petrophysical parameter considered significant in the characterization of reservoirs, it was used, hereafter, to estimate permeability and water saturation of the reservoir, applying empirical equations. From there, it was not enough just to estimate the porosity, but was necessary to know what type it is. For this purpose, the concepts of the electrical formation factor, cementation coefficient, tortuosity, and anisotropy were used. With them, the zones with primary intergranular and interparticle porosity as well as secondary porosity, such as fractures, fissures, and vugs, were mapped. It was concluded that, with studies of this type, it is also possible to identify the connected and nonconnected porosities, which permits estimation of the effective porosity along the well.

The results of a numerical study of the equilibrium parameters of a one-dimensional chain consisting of three dust particles levitating in the electric fields of a gas-discharge plasma are presented. A numerical model is considered in which the motion of dust particles is simulated taking into account the action of the Coulomb repulsion force, external electric field, gravity, electrostatic force induced by the space charge of the plasma, as well as the ion drag force described analytically. A comparison has been made of the spatial distributions of the plasma space charge and potential around dust particles, as well as the equilibrium structural parameters of a chain of dust particles, depending on whether the ion drag force is taken into account analytically or not. It is shown that when the force of ion drag is taken into account analytically, the chain of dust particles as a whole is displaced in the direction of the ion flow. In this case, the distances between dust particles turn out to be smaller than in the case of neglecting the force of ion drag.

The paper described further development of a gas-jet method of synthesizing diamond coatings with the use of a high-velocity jet for transporting the gas mixture (hydrogen, methane, and argon) activated in a microwave discharge to a silicon substrate. A substrate holder is developed, which ensures substrate integrity under thermal loading under conditions of chemical vapor deposition. The diamond synthesis rate in the present experiments is higher than that obtained previously in microwave plasma-assisted chemical vapor deposition experiments without addition of argon.

The generation of a low-frequency low-pressure inductive discharge with ferromagnetic enhancement of the magnetic coupling between the inductor and plasma is investigated. The main features and advantages of this plasma generation method for surface ion-plasma treatment technologies are considered. New experimental data on electrophysical and dynamic characteristics of ferromagnetic-enhanced low-pressure inductive discharge in argon with the addition of oxygen are presented. It is shown that the radial distribution of plasma parameters in a gas-discharge chamber can be controlled using distributed discharge generation. Significant fluctuations in the electron temperature during the period of oscillations of the discharge electric field are found, and the mechanism of their occurrence is analyzed.

A method for measuring the temperature of the silicon melt during plasma-chemical electron-beam refining is proposed. The method is based on measuring the radiation intensity from the melt in the infrared range and comparing it with the temperature. It is established that the refined silicon temperature can be varied from 1500 K to 2600 K by changing the refining conditions, in particular, the electron beam current.

This study demonstrates that the surface roughness of a copper sample can be controlled by treating it with glow discharge plasma. It is established that the main process affecting the morphology and composition of the surface is oxidation. Treatment causes various copper oxide nano- and microstructures on the surface of a copper sample. It is shown that, in the parameter range studied, the working gas pressure has a more significant effect on the formation of various structures than the glow discharge current density. As a result of the treatment, various stages of the surface oxidation are observed, caused by differences in the surface temperature.