Perm Journal of Petroleum and Mining Engineering

Publisher: Perm National Research Polytechnic University, Perm, Russian Federation

DOI: 10.15593/2712-8008/

Languages: Russian, English

Editor-in-Chief: Professor, Dr. Sci. Galkin V.I.

  • is a periodical published scientific peer-reviewed open access edition. The Journal is registered in Federal Service for Supervision of Communications, Information Technology and Communications (Roscomnadzor), certificate PI № FS77-78478 on 08 July 2020. Subscription index in the union catalog "The Russian Press" - 43440.
  • is published by the Federal State Autonomous Education Institution for Higher Education "Perm National Research Polytechnic University", Perm, Russian Federation.
  • is included in the List of peer-reviewed scientific publications, in which basic scientific results of dissertations for the degree of Candidate of Science, for the degree of Doctor of Science should be published in scientific specialties:
    25.00.12 – Geology, prospecting and exploration of oil and gas fields (technical sciences),
    25.00.12 – Geology, prospecting and exploration of oil and gas fields (geological and mineralogical sciences),
    25.00.15 – Technology of well drilling and completion (technical sciences),
    25.00.16 – Mining and oil and gas geology, geophysics, mine surveying and subsoil geometry (technical sciences),
    25.00.17 – Development and exploitation of oil and gas fields (technical sciences),
    25.00.20 – Geomechanics, rock destruction, mine aerogasdynamics and mining thermal physics (technical sciences).
  • is included in the project "Russian Science Citation Index".
  • highlights challenges of environmental management, questions of resource evaluation and forecasting of the lithosphere, environmentally safe field development and mining, power engineering and energy efficiency of oil and gas companies.
  • is intended for scientists, engineers, technicians, teachers and students of higher technical educational institutions with mining, oil and gas profiles.
  • does not charge any publication or submission fees.
  • is published 4 times a year.

Editorial board organizes the formation of full-text electronic versions of journal articles that are available on the websites

vestnik.pstu.ru/geo/ and www.elibrary.ru

In 2020, the average time of article publication, including article review - 175 days.

In 2019, the average time of article publication, including article review - 169 days.

In 2018, the average time of article publication, including article review - 125 days.

In 2017, the average time of article publication, including article review - 129 days.

In 2016, the average time of article publication, including article review - 141 days.

In 2015, the average time of article publication, including article review - 98 days.

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Current Issue

Vol 23, No 3 (2023)

ARTICLES
Reconstruction of Paleogeochemical Data from the Riphean-Vendian Sediments of the Vychegda Depression of the Volga-Ural Oil and Gas Province
Botalov A.N., Krivoschekov S.N.

Abstract

Reconstruction of paleogeochemical data is one of the important stages in the projection of oil and gas content and modeling of sedimentary basins. The present research is devoted to reconstruction of paleogeochemical data of the Riphean-Vendian source rocks of the Vychegda Depression, which occupies the territory of the northern Volga-Ural oil-and-gas province. Five oil-producing formations are traced in the studied area: Pez Formation RF2pz, composed of argillites, siltstones and sandstones, Omen RF3om and Nyafta RF3nf Formations, of predominantly carbonate composition with interlayers of terrigenous sediments (argillites, sandstones, and siltstones), as well as the Ust-Pinega Formation V2up and rocks of the Kudymkar Series V2kd consisting of interbedded argillites, siltstones, and sandstones. Based on the analysis of the results of pyrolytic studies, it was established that the organic matter of the source rocks at the present stage is characterized by predominantly low values of the main geochemical parameters and high catagenetic transformation. Reconstruction of the paleogeochemical data included determination of the degree of realization of the initial generative potential by the source rocks, reconstruction of the paleo values of the hydrogen index, total organic carbon and generative potential. According to the results obtained, the Riphean-Vendian source rocks of the Vychegda Depression are enriched in the sapropelic (I/II) type of organic matter. The Pez, Omen and Nyafta formations of the Riphean have predominantly good and very good initial generative potential, while the initial potential of the Vendian sediments: Ust-Pinega Formation and Kudymkar Series is estimated as fair to very good. Initial generative potential of Riphean rocks is realized by 50-100 %, and Vendian - up to 60 %. The greatest perspectives of oil-and-gas content are connected with Vendian sediments. Riphean source rocks also have the ability to generate hydrocarbons, but in small volumes.
Perm Journal of Petroleum and Mining Engineering. 2023;23(3):102-110
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Development of Geostatistical Models for Assessing the Confirmability of Geomorphological Characteristics of the Geological Structures (Bashkir Svod, Perm Krai)
Kolesnikov E.S.

Abstract

Today, despite the relatively high accuracy of preparing geological structures for deep drilling in the Perm Krai using 3D seismic, there is a discrepancy between the geological and morphological characteristics of structures before drilling and according to drilling results, which makes it necessary to develop a geological and statistical approach that makes it possible to more accurately assess the risks of non-confirmation of the geological and morphological characteristics of structures prepared for deep drilling, as well as to determine the priority of objects for further geological exploration work. This work describes one of the options for developing a geological and statistical approach for rank differentiation of 25 structures of the IIК seismic reflector and 21 structures of the IIП seismic reflector, prepared by 3D seismic exploration. These structures has been already drilled by prospecting and appraisal wells within the Bashkir arch (Perm Krai). The initial data for the analysis were from the passport of structures prepared for deep drilling: the amplitude of the structure, the structure area according to the corresponding reflecting horizon, the ratio of the structure length to its width, the angle between the long axis of the structure and the axis of the nearest tectonic second order element, the distance from the structure to the edge of the nearest second order tectonic element and the distance from the structure to the center of the nearest second order tectonic element. For each model, the nature and degree of influence of the studied indicators on the confirmability of the amplitude by drilling was determined and described. The assessment of differentiation of structures by class and the accuracy of determining class boundaries were confirmed when classifying the structures of the test sample using discriminant analysis. This geological and statistical approach can be used for a more accurate assessment of the risks associated with the problem of the unconfirmability of the geological and morphological characteristics of structures prepared for deep drilling, as well as for identifying priority objects for geological exploration work, regardless of their geographical location and belonging to tectonic elements.
Perm Journal of Petroleum and Mining Engineering. 2023;23(3):111-121
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Perspective Directions for Improving Acid Compositions and Methods of Influence on the Bottomhole Formation Zone
Glushchenko V.N., Khizhnyak G.P., Melekhin A.A.

Abstract

The development of the acid treatment method of bottomhole formation zone (BFZ) has gone from understanding the physics and chemistry of the acid compositions (AC) reactions with rocks through the expansion of the acid components range, AC modification by foaming, emulsification, generation to modern acid treatment methods with a wide range of scientifically based ACs. Through trial and error, we came to understanding the importance of maintaining high relative phase permeability of oil and gas in the BFZ with the negativity of its water saturation, imparting a hydrophilic state to the reservoir surface, preventing and eliminating the formation of clogging sedimentation as a result of corrosion during injection along the wellbore, neutralization rocks, mixing with oil, formation waters, hydrogen sulfide. As a result, the AC must additionally include ion stabilizers, steel corrosion inhibitors, demulsifying agents for the prevention and destruction of water-oil emulsions, hydrophilizers and a number of optional additives if necessary: nonionic surfactants, alcohols, polymers, antifiltrates, solvents for asphaltene-resin-paraffin deposits and a number of others. It is not always possible to combine them in one AC, which implies a complex effect on the BFZ with a number of compositions. The article discusses the conditions for effective acid treatment, which presupposes its facilitated removal of solid impurities, water-oil emulsions, hydrophilization of the reservoir surface and minimal water saturation. Options for improving known acid compositions using nonionic surfactants, polar nonelectrolytes, technical lignosulfonates, including direct and reverse acid-containing emulsions were proposed. Technological approaches to heating the BFZ with heat-generating inorganic compositions were outlined to transfer the hydrochloric acid dissolution of dolomite into the diffusion region for the purpose of easy formation of acid dissolution channels.
Perm Journal of Petroleum and Mining Engineering. 2023;23(3):122-132
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Material Structure Parameters Influence on Oil and Gas Field Equipment Corrosion Resistance
Apakashev R.A., Khazin M.L.

Abstract

To improve the reliability and durability of oil and gas equipment, it is promising to use micro- and nanostructured metals and alloys, as well as metal-matrix composites. Conventional and nanostructured samples of aluminum, copper, BrA9ZhZL bronze, AMg6 alloy, and alumina-matrix dispersion-reinforced composite containing 6.3 wt % titanium were studied. Structuring treatment of metal materials was carried out in the liquid phase. The aluminum matrix composite was synthesized by powder metallurgy. A model electrolyte solution without forced circulation containing 30 g/L NaCl and an addition of acetic acid to pH = 4.0 was used as a corrosive medium. The test base was 144 h, the temperature was +22 °C, the volume of the solution in the cell with three samples was 500 ml. The relative calculated error of the tests was 5%. For all the studied samples, a continuous uniform distribution of corrosion damage to the metal surface is observed. At the same time, the corrosion rate (P, mm/year) of nanostructured samples of metals and alloys is approximately 11 % less than the corrosion rate of samples of the same metals and alloys that were not subjected to structuring treatment. For the aluminum matrix composite, it was noted that the dispersed reinforcement of aluminum with titanium provides an increase in the corrosion resistance of the matrix metal by 9.6 %. The results of the studies performed indicate an increased corrosion resistance of nanostructured metallic materials and an aluminum matrix composite, which is important when they are used as part of equipment operating in a corrosive environment.
Perm Journal of Petroleum and Mining Engineering. 2023;23(3):133-140
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Assessment of Rock Geochemical Properties of the Bazhenov Formation According to Well Logging Data Using Machine Learning Methods
Shadrin A.O., Gulin A.B., Ashikhmin S.G., Melekhin A.A.

Abstract

The Bazhenov formation in the West Siberian oil and gas province is of interest to researchers not only as a potential industrial development object, but also in connection with forecasting oil content and assessing the risks of exploratory drilling. The results of a study aimed at developing machine learning models to assess the relationships between the geochemical parameters of the Bazhenov formation and data obtained from well logging are presented. Modern machine learning methods provide powerful tools for data analysis and forecasting. Geological data is often characterized by a large number of parameters and complex relationships that can be difficult for humans to understand. In this context, the application of machine learning methods provides researchers with new tools. This work focuses on the Boosted Trees model, which demonstrated better results compared to other regression methods, having the lowest error (MAE and MSE) and the highest coefficient of determination ( R 2). Boosted Trees models provided accurate and stable prediction results, which were confirmed by visual analysis. As a result of the work, using machine learning methods, geochemical parameters were calculated, including S1, S2 and Tmax , which was previously difficult. This increased the accuracy of the geochemical parameters assessment in wells, which contributed to the improvement of models for the rock properties distribution along the well section, and in the future will lead to an increase in the detail of the parameters distribution over the area. It also emphasizes the importance of careful data preprocessing and selecting the best models and training methods. Despite its technical challenges, machine learning provides researchers with a powerful tool to more accurately analyze and interpret geodata and make operational decisions based on this data.
Perm Journal of Petroleum and Mining Engineering. 2023;23(3):141-150
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