Sergo Ordzhonikidze Russian State University for Geological Prospecting (Russian: Российский государственный геологоразведочный университет, МГРИ), or the Russian State University for Geological Prospecting is named after Sergo Ordzhonikidze and previously known as the Moscow Geological Prospecting Institute, is a public university based in Moscow, Russia, specialising in geology, geophysics, gemmology, ecology and other earth-science disciplines.There was a task in the USSR to prepare 435.000 engineers and technicians in five years (1930-1935) during the USSR industrialization period, while their number in 1929 was 66.000.In 1930 the Moscow Mining Academy was divided into six independent institutes by the order of Supreme Soviet of the National Economy. Among the new colleges which grew out of the Academy's departments was Moscow Geological Prospecting Institute (Russian: Московский геологоразведочный институт).Over the entire history of MGRI, the university raised more than 30.000 specialists, 1.500 candidates and 400 doctors of sciences. More than 1.300 foreigners from over 78 countries of the world are among the graduates of Russian State University of Geological Prospecting.University graduates are the discoverers of more than two hundred large mineral deposits both in the Russian Federation and abroad. There is one mineral named after university as Mgriite (Cu3AsSe3). Lots of other minerals as well as geographic and geological objects and about 280 species of fossils of flora and fauna are named after graduates(professors and geologists) of MGRI. About 15 graduates of MGRI were elected academicians of the USSR Academy of Sciences(now the Russian Academy of Sciences) and 12 people were elected as corresponding members. Professors have been working on the set of "Construction Norms and Regulations" for engineering and geological spheres in Commonwealth of Independent States(CIS) and in Latin America. For more than 100 years of history, the university has developed scientific and pedagogical schools in almost all areas of the Earth Sciences. Graduates of MGRI have made a significant contribution to the development of the geological prospecting and mining industries internationally..
The numerical challenges of Tikhonov’s regularization method in solving general nonlinear problems are well known: non-uniqueness of the global extremum of the objective functional, high dimensionality and the need for extensive a priori information, the need to specify an initial approximation, determining the regularization parameter, etc. The use of neural network methods, in particular physics informed neural networks (PINNs), largely allows us to resolve these problems due to the ability to calculate a training sample of reference solutions (of virtually any desired dimensionality), decompose the original problem being solved, and apply special training methods adapted to the physics of the problem being solved. This paper provides a review and analyzes the experience of applying PINNs to solving nonlinear inverse problems of geoelectrics. It is noted that the first examples of constructing PINNs for solving inverse problems of geoelectrics were presented in a publication by the authors of this paper M.I. Shimelevich and E.A. Obornev in 2009. The problem of estimating the nonuniqueness (ambiguity) of the obtained solutions of inverse problems, which is insufficiently covered in the literature on geoelectrics, is considered separately.
This study introduces a novel integrated approach to modeling crude oil in situ combustion by incorporating free radical chain reaction kinetics to address the critical limitation of conventional models: their inability to accurately predict ignition behavior. Current Arrhenius-based models fail to capture the transient ignition phase, a critical element for field implementation safety and efficiency. We developed a hybrid modeling framework combining conventional combustion kinetics with chain reaction mechanisms for the initial oxidation stages (150-250 degrees C). The methodology was validated using pressurized differential scanning calorimetry (PDSC) experiments at 5 MPa with heating rates of 2-10 degrees C/min on light and middle crude oils, combined with SARA compositional analysis. Two-reaction and four-reaction Arrhenius schemes were systematically evaluated and matched to experimental data. The chain reaction approach achieved 14% relative error in predicting lowtemperature oxidation heat release, representing more than 50% improvement over conventional models (30% error). This physics-based framework enables accurate ignition timing prediction - a critical capability previously unattainable through traditional hydrodynamic modeling. The validated methodology demonstrates broad applicability across different crude oil types and provides a practical pathway for integrating advanced kinetic mechanisms into commercial reservoir simulators for enhanced in situ combustion project design.
We consider the Cauchy problem for the nonstationary discrete p-Laplacian with absorption term on infinite graph which supports the Sobolev inequality. We established the precise conditions on parameters which guarantee the decay in time of the total mass for nonnegative solutions. Our technique relies on suitable energy inequalities.
The Laptev Sea is an area of active exploration for hydrocarbons; however, estimations of its hydrocarbon potential vary significantly, both in terms of total hydrocarbon quantities and their phase composition. This variability is due to the absence of a unified geological framework and, consequently, the use of different analogous basins in calculations. Based on a comprehensive interpretation of geological and geophysical data, as well as seismic facies analysis, a reliable geological model was created. Paleogeographic conditions for the formation of major sedimentary cover complexes were reconstructed, including the Aptian-Upper Cretaceous, Paleocene-Eocene, Oligocene, and Miocene-Quaternary periods. It was shown that, within the modern shelf of the Laptev Sea, a marine basin existed since the second half of the Cretaceous, the boundaries of which are determined based on outcrop data from adjacent islands and onshore, wells, and seismic patterns. The main factors controlling the formation of the sedimentary cover and the change of paleogeographic conditions along the modern Laptev Sea continental margin were global tectonic events, including the opening of the Makarov-Podvodnikov Basin, rifting, and post-rift subsidence in the Eurasian Basin.
The phenomenon of metal concentration by plants is discussed. The metal content in plants can be tens or hundreds of times higher than the metal content in the soil. A kinetic model of phytomining is developed. The model is verified based on experimental data, the two-chamber nature of the process is demonstrated, a parametric analysis of the model is performed elucidating the role of the metal transfer rate from the geological substrate and metal translocation in the plant, and the dynamics of metal bioaccumulation is described. Natural coals are characterized by exceptionally high ash content (metal content up to 50
