176 research outputs found

    Modelling of deep wells thermal modes

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    Purpose. Investigation of various heat-exchange conditions influence of the tower liquid on the deep wells thermal conditions. Methods. Methods of heat-exchange processes mathematical modeling are used. On the basis of the developed scheme for calculation, the thermal condition in a vertical well with a concentric arrangement of the drill-string was investigated. It was assumed that the walls of the well are properly insulated, and there is no flow or loss of fluid. The temperature distribution in the Newtonian (water) and non-Newtonian (clay mud) liquid along the borehole was simulated taking into account changes in the temperature regime of rocks with depth. To verify the calculation method and determine the reliability of the results, a comparative analysis of the calculated and experimental data to determine the temperature of the drilling liquid in the well was performed. Findings. A mathematical model for the study of temperature fields along the well depth was proposed and verified. A steady-state temperature distribution along the borehole is obtained for various types (Newtonian or non-Newtonian) tower liquid, with a linear law of change in rocks temperature with depth. It has been established that the temperature of the liquid flow at the face of hole and at the exit to the surface depends on the type of liquid used and the flow regime. It has been established that due to thermal insulation of drill pipe columns, heat-exchange between the downward and upward flow is reduced, which leads to a decrease in the temperature of the downward flow at the face of hole, providing a more favorable temperature at the face, which contributes to better destruction of the rock and cooling the tool during drilling. Originality. The nature of temperature distribution and changes along the borehole under the steady-state mode of heat-exchange in a turbulent and structural flow regime for both Newtonian and non-Newtonian circulating liquid are revealed. Practical implications. The proposed mathematical model and obtained results can be used to conduct estimates of the thermal conditions of wells and the development of recommendations for controlling the intensity of heat-exchange processes in the well, in accordance with the requirements of a specific technology.ΠœΠ΅Ρ‚Π°. ДослідТСння Π²ΠΏΠ»ΠΈΠ²Ρƒ Ρ€Ρ–Π·Π½ΠΈΡ… ΡƒΠΌΠΎΠ² Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΡ–Π½Ρƒ Ρ†ΠΈΡ€ΠΊΡƒΠ»ΡŽΡŽΡ‡ΠΎΡ— Ρ€Ρ–Π΄ΠΈΠ½ΠΈ Π½Π° Ρ‚Π΅ΠΏΠ»ΠΎΠ²ΠΈΠΉ Ρ€Π΅ΠΆΠΈΠΌ Π³Π»ΠΈΠ±ΠΎΠΊΠΈΡ… свСрдловин. ΠœΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ°. Використано ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈ ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½ΠΎΠ³ΠΎ модСлювання процСсів Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΡ–Π½Ρƒ. На основі Ρ€ΠΎΠ·Ρ€ΠΎΠ±Π»Π΅Π½ΠΎΡ— схСми Π΄ΠΎ Ρ€ΠΎΠ·Ρ€Π°Ρ…ΡƒΠ½ΠΊΡƒ дослідТувався Ρ‚Π΅ΠΏΠ»ΠΎΠ²ΠΈΠΉ Ρ€Π΅ΠΆΠΈΠΌ Ρƒ Π²Π΅Ρ€Ρ‚ΠΈΠΊΠ°Π»ΡŒΠ½Ρ–ΠΉ свСрдловині Π· ΠΊΠΎΠ½Ρ†Π΅Π½Ρ‚Ρ€ΠΈΡ‡Π½ΠΈΠΌ Ρ€ΠΎΠ·Ρ‚Π°ΡˆΡƒΠ²Π°Π½Π½ΡΠΌ Π±ΡƒΡ€ΠΈΠ»ΡŒΠ½ΠΎΡ— ΠΊΠΎΠ»ΠΎΠ½ΠΈ. ΠŸΠ΅Ρ€Π΅Π΄Π±Π°Ρ‡Π°Π»ΠΎΡΡ, Ρ‰ΠΎ стінки свСрдловини Π½Π°Π»Π΅ΠΆΠ½ΠΈΠΌ Ρ‡ΠΈΠ½ΠΎΠΌ Ρ–Π·ΠΎΠ»ΡŒΠΎΠ²Π°Π½Ρ–, ΠΏΡ€ΠΈΠΏΠ»ΠΈΠ² Ρ– Π²Ρ‚Ρ€Π°Ρ‚ΠΈ Ρ€Ρ–Π΄ΠΈΠ½ΠΈ відсутні. МодСлювався Ρ€ΠΎΠ·ΠΏΠΎΠ΄Ρ–Π» Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ Ρƒ ΠΏΠΎΡ‚ΠΎΠΊΠ°Ρ… Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΎΡ— (Π²ΠΎΠ΄ΠΈ) Ρ‚Π° Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΎΡ— (глинистого Ρ€ΠΎΠ·Ρ‡ΠΈΠ½Ρƒ) Ρ€Ρ–Π΄ΠΈΠ½ ΡƒΠ·Π΄ΠΎΠ²ΠΆ стовбура свСрдловини Π· урахуванням Π·ΠΌΡ–Π½ΠΈ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½ΠΎΠ³ΠΎ Ρ€Π΅ΠΆΠΈΠΌΡƒ Π³Ρ–Ρ€ΡΡŒΠΊΠΈΡ… ΠΏΠΎΡ€Ρ–Π΄ Π· глибиною. Для Π²Π΅Ρ€ΠΈΡ„Ρ–ΠΊΠ°Ρ†Ρ–Ρ— ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ Ρ€ΠΎΠ·Ρ€Π°Ρ…ΡƒΠ½ΠΊΡƒ Ρ– визначСння достовірності Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ–Π² Π±ΡƒΠ² Π²ΠΈΠΊΠΎΠ½Π°Π½ΠΈΠΉ ΠΏΠΎΡ€Ρ–Π²Π½ΡΠ»ΡŒΠ½ΠΈΠΉ Π°Π½Π°Π»Ρ–Π· Ρ€ΠΎΠ·Ρ€Π°Ρ…ΡƒΠ½ΠΊΠΎΠ²ΠΈΡ… Ρ‚Π° Π΅ΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΈΡ… Π΄Π°Π½ΠΈΡ… Π· визначСння Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ΠΈ ΠΏΡ€ΠΎΠΌΠΈΠ²Π½ΠΎΡ— Ρ€Ρ–Π΄ΠΈΠ½ΠΈ Ρƒ свСрдловині. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΈ. Π—Π°ΠΏΡ€ΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½Π° Ρ– Π²Π΅Ρ€ΠΈΡ„Ρ–Ρ†Ρ–ΠΉΠΎΠ²Π°Π½Π° ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Π° модСль для дослідТСння Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½ΠΈΡ… ΠΏΠΎΠ»Ρ–Π² Π· глибиною свСрдловини. ΠžΡ‚Ρ€ΠΈΠΌΠ°Π½ΠΎ стаціонарний Ρ€ΠΎΠ·ΠΏΠΎΠ΄Ρ–Π» Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ ΡƒΠ·Π΄ΠΎΠ²ΠΆ стовбура свСрдловини для Ρ€Ρ–Π·Π½ΠΈΡ… Ρ‚ΠΈΠΏΡ–Π² (Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΈΡ… Π°Π±ΠΎ Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΈΡ…) Ρ†ΠΈΡ€ΠΊΡƒΠ»ΡŽΡŽΡ‡ΠΈΡ… Ρ€Ρ–Π΄ΠΈΠ½ ΠΏΡ€ΠΈ Π»Ρ–Π½Ρ–ΠΉΠ½ΠΎΠΌΡƒ Π·Π°ΠΊΠΎΠ½Ρ– Π·ΠΌΡ–Π½ΠΈ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ΠΈ Π³Ρ–Ρ€ΡΡŒΠΊΠΈΡ… ΠΏΠΎΡ€Ρ–Π΄ Π· глибиною. ВиявлСно, Ρ‰ΠΎ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π° ΠΏΠΎΡ‚ΠΎΠΊΡƒ Ρ€Ρ–Π΄ΠΈΠ½ΠΈ Π½Π° Π²ΠΈΠ±ΠΎΡ— свСрдловини Ρ– Π½Π° Π²ΠΈΡ…ΠΎΠ΄Ρ– Π½Π° Π΄Π΅Π½Π½Ρƒ ΠΏΠΎΠ²Π΅Ρ€Ρ…Π½ΡŽ Π·Π°Π»Π΅ΠΆΠΈΡ‚ΡŒ Π²Ρ–Π΄ Ρ‚ΠΈΠΏΡƒ використовуваної Ρ€Ρ–Π΄ΠΈΠ½ΠΈ Ρ– Ρ€Π΅ΠΆΠΈΠΌΡƒ Ρ‚Π΅Ρ‡Ρ–Ρ—. ВстановлСно, Ρ‰ΠΎ Π·Π° Ρ€Π°Ρ…ΡƒΠ½ΠΎΠΊ тСрмоізоляції ΠΊΠΎΠ»ΠΎΠ½ΠΈ Π±ΡƒΡ€ΠΈΠ»ΡŒΠ½ΠΈΡ… Ρ‚Ρ€ΡƒΠ± Π·Π½ΠΈΠΆΡƒΡ”Ρ‚ΡŒΡΡ Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΡ–Π½ ΠΌΡ–ΠΆ Π½ΠΈΠ·Ρ…Ρ–Π΄Π½ΠΈΠΌ Ρ– висхідним ΠΏΠΎΡ‚ΠΎΠΊΠ°ΠΌΠΈ, Ρ‰ΠΎ ΠΏΡ€ΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚ΡŒ Π΄ΠΎ зниТСння Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ΠΈ Π½ΠΈΠ·Ρ…Ρ–Π΄Π½ΠΎΠ³ΠΎ ΠΏΠΎΡ‚ΠΎΠΊΡƒ Π½Π° Π²ΠΈΠ±ΠΎΡ— свСрдловини, Π·Π°Π±Π΅Π·ΠΏΠ΅Ρ‡ΡƒΡŽΡ‡ΠΈ Π±Ρ–Π»ΡŒΡˆ сприятливий Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½ΠΈΠΉ Ρ€Π΅ΠΆΠΈΠΌ Π½Π° Π²ΠΈΠ±ΠΎΡ—, який сприяє ΠΊΡ€Π°Ρ‰ΠΎΠΌΡƒ руйнування ΠΏΠΎΡ€ΠΎΠ΄ΠΈ Ρ‚Π° ΠΎΡ…ΠΎΠ»ΠΎΠ΄ΠΆΠ΅Π½Π½ΡŽ інструмСнту ΠΏΡ€ΠΈ Π±ΡƒΡ€Ρ–Π½Π½Ρ–. Наукова Π½ΠΎΠ²ΠΈΠ·Π½Π°. ВиявлСно Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ Ρ€ΠΎΠ·ΠΏΠΎΠ΄Ρ–Π»Ρƒ Ρ‚Π° Π·ΠΌΡ–Π½ΠΈ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ΠΈ Π²Π·Π΄ΠΎΠ²ΠΆ стовбура свСрдловин ΠΏΡ€ΠΈ стаціонарному Ρ€Π΅ΠΆΠΈΠΌΡ– Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΡ–Π½Ρƒ Π² Ρ‚ΡƒΡ€Π±ΡƒΠ»Π΅Π½Ρ‚Π½ΠΎΠΌΡƒ Ρ– структурному Ρ€Π΅ΠΆΠΈΠΌΠ°Ρ… Ρ‚Π΅Ρ‡Ρ–Ρ— як для Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΈΡ…, Ρ‚Π°ΠΊ Ρ– Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½Ρ–Π²ΡΡŒΠΊΠΈΡ… Ρ†ΠΈΡ€ΠΊΡƒΠ»ΡŽΡŽΡ‡ΠΈΡ… Ρ€Ρ–Π΄ΠΈΠ½. ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π½Π° Π·Π½Π°Ρ‡ΠΈΠΌΡ–ΡΡ‚ΡŒ. Π—Π°ΠΏΡ€ΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½Π° ΠΌΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π½Π° модСль Ρ– ΠΎΡ‚Ρ€ΠΈΠΌΠ°Π½Ρ– Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΈ ΠΌΠΎΠΆΡƒΡ‚ΡŒ використовуватися для провСдСння ΠΎΡ†Ρ–Π½ΠΎΡ‡Π½ΠΈΡ… Ρ€ΠΎΠ·Ρ€Π°Ρ…ΡƒΠ½ΠΊΡ–Π² Ρ‚Π΅ΠΏΠ»ΠΎΠ²ΠΈΡ… Ρ€Π΅ΠΆΠΈΠΌΡ–Π² свСрдловин Ρ‚Π° Ρ€ΠΎΠ·Ρ€ΠΎΠ±ΠΊΠΈ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†Ρ–ΠΉ Π· управління Ρ–Π½Ρ‚Π΅Π½ΡΠΈΠ²Π½Ρ–ΡΡ‚ΡŽ Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΡ–Π½Π½ΠΈΡ… процСсів Ρƒ свСрдловині Π²Ρ–Π΄ΠΏΠΎΠ²Ρ–Π΄Π½ΠΎ Π΄ΠΎ Π²ΠΈΠΌΠΎΠ³ ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½ΠΎΡ— Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³Ρ–Ρ—.ЦСль. ИсслСдованиС влияния Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… условий Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΠ΅Π½Π° Ρ†ΠΈΡ€ΠΊΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ Тидкости Π½Π° Ρ‚Π΅ΠΏΠ»ΠΎΠ²ΠΎΠΉ Ρ€Π΅ΠΆΠΈΠΌ Π³Π»ΡƒΠ±ΠΎΠΊΠΈΡ… скваТин. ΠœΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ°. Π˜ΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ матСматичСского модСлирования процСссов Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΠ΅Π½Π°. На основС Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠΉ схСмы ΠΊ расчСту исслСдовался Ρ‚Π΅ΠΏΠ»ΠΎΠ²ΠΎΠΉ Ρ€Π΅ΠΆΠΈΠΌ Π² Π²Π΅Ρ€Ρ‚ΠΈΠΊΠ°Π»ΡŒΠ½ΠΎΠΉ скваТинС с концСнтричСским располоТСниСм Π±ΡƒΡ€ΠΈΠ»ΡŒΠ½ΠΎΠΉ ΠΊΠΎΠ»ΠΎΠ½Ρ‹. ΠŸΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°Π»ΠΎΡΡŒ, Ρ‡Ρ‚ΠΎ стСнки скваТины Π½Π°Π΄Π»Π΅ΠΆΠ°Ρ‰ΠΈΠΌ ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ ΠΈΠ·ΠΎΠ»ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹, ΠΏΡ€ΠΈΡ‚ΠΎΠΊ ΠΈ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ Тидкости ΠΎΡ‚ΡΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‚. ΠœΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π»ΠΎΡΡŒ распрСдСлСниС Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ Π² ΠΏΠΎΡ‚ΠΎΠΊΠ°Ρ… Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΎΠΉ (Π²ΠΎΠ΄Ρ‹) ΠΈ Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΎΠΉ (глинистого раствора) ТидкостСй вдоль ствола скваТины с ΡƒΡ‡Π΅Ρ‚ΠΎΠΌ измСнСния Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½ΠΎΠ³ΠΎ Ρ€Π΅ΠΆΠΈΠΌΠ° Π³ΠΎΡ€Π½Ρ‹Ρ… ΠΏΠΎΡ€ΠΎΠ΄ с Π³Π»ΡƒΠ±ΠΈΠ½ΠΎΠΉ. Для Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ расчСта ΠΈ опрСдСлСния достовСрности Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² Π±Ρ‹Π» Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ ΡΡ€Π°Π²Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ Π°Π½Π°Π»ΠΈΠ· расчСтных ΠΈ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Ρ… Π΄Π°Π½Π½Ρ‹Ρ… ΠΏΠΎ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΡŽ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Ρ‹ ΠΏΡ€ΠΎΠΌΡ‹Π²ΠΎΡ‡Π½ΠΎΠΉ Тидкости Π² скваТинС. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. ΠŸΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΠΈ Π²Π΅Ρ€ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π° матСматичСская модСль для исслСдования Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½Ρ‹Ρ… ΠΏΠΎΠ»Π΅ΠΉ ΠΏΠΎ Π³Π»ΡƒΠ±ΠΈΠ½Π΅ скваТины. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½ΠΎ стационарноС распрСдСлСниС Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€ вдоль ствола скваТины для Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Ρ‚ΠΈΠΏΠΎΠ² (Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΈΡ… ΠΈΠ»ΠΈ Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΈΡ…) Ρ†ΠΈΡ€ΠΊΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… ТидкостСй ΠΏΡ€ΠΈ Π»ΠΈΠ½Π΅ΠΉΠ½ΠΎΠΌ Π·Π°ΠΊΠΎΠ½Π΅ измСнСния Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Ρ‹ Π³ΠΎΡ€Π½Ρ‹Ρ… ΠΏΠΎΡ€ΠΎΠ΄ с Π³Π»ΡƒΠ±ΠΈΠ½ΠΎΠΉ. ВыявлСно, Ρ‡Ρ‚ΠΎ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π° ΠΏΠΎΡ‚ΠΎΠΊΠ° Тидкости Π½Π° Π·Π°Π±ΠΎΠ΅ скваТины ΠΈ Π½Π° Π²Ρ‹Ρ…ΠΎΠ΄Π΅ Π½Π° Π΄Π½Π΅Π²Π½ΡƒΡŽ ΠΏΠΎΠ²Π΅Ρ€Ρ…Π½ΠΎΡΡ‚ΡŒ зависит ΠΎΡ‚ Ρ‚ΠΈΠΏΠ° ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅ΠΌΠΎΠΉ Тидкости ΠΈ Ρ€Π΅ΠΆΠΈΠΌΠ° тСчСния. УстановлСно, Ρ‡Ρ‚ΠΎ Π·Π° счСт тСрмоизоляции ΠΊΠΎΠ»ΠΎΠ½Ρ‹ Π±ΡƒΡ€ΠΈΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚Ρ€ΡƒΠ± сниТаСтся Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΠ΅Π½ ΠΌΠ΅ΠΆΠ΄Ρƒ нисходящим ΠΈ восходящим ΠΏΠΎΡ‚ΠΎΠΊΠ°ΠΌΠΈ, Ρ‡Ρ‚ΠΎ ΠΏΡ€ΠΈΠ²ΠΎΠ΄ΠΈΡ‚ ΠΊ сниТСнию Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Ρ‹ нисходящСго ΠΏΠΎΡ‚ΠΎΠΊΠ° Π½Π° Π·Π°Π±ΠΎΠ΅ скваТины, обСспСчивая Π±ΠΎΠ»Π΅Π΅ благоприятный Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π½Ρ‹ΠΉ Ρ€Π΅ΠΆΠΈΠΌ Π½Π° Π·Π°Π±ΠΎΠ΅, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ способствуСт Π»ΡƒΡ‡ΡˆΠ΅ΠΌΡƒ Ρ€Π°Π·Ρ€ΡƒΡˆΠ΅Π½ΠΈΡŽ ΠΏΠΎΡ€ΠΎΠ΄Ρ‹ ΠΈ ΠΎΡ…Π»Π°ΠΆΠ΄Π΅Π½ΠΈΡŽ инструмСнта ΠΏΡ€ΠΈ Π±ΡƒΡ€Π΅Π½ΠΈΠΈ. Научная Π½ΠΎΠ²ΠΈΠ·Π½Π°. ВыявлСн Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ распрСдСлСния ΠΈ измСнСния Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Ρ‹ вдоль ствола скваТин ΠΏΡ€ΠΈ стационарном Ρ€Π΅ΠΆΠΈΠΌΠ΅ Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΠ΅Π½Π° Π² Ρ‚ΡƒΡ€Π±ΡƒΠ»Π΅Π½Ρ‚Π½ΠΎΠΌ ΠΈ структурном Ρ€Π΅ΠΆΠΈΠΌΠ°Ρ… тСчСния ΠΊΠ°ΠΊ для Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΈΡ…, Ρ‚Π°ΠΊ ΠΈ Π½Π΅Π½ΡŒΡŽΡ‚ΠΎΠ½ΠΎΠ²ΡΠΊΠΈΡ… Ρ†ΠΈΡ€ΠΊΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… ТидкостСй. ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π΅ΡΠΊΠ°Ρ Π·Π½Π°Ρ‡ΠΈΠΌΠΎΡΡ‚ΡŒ. ΠŸΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Π°Ρ матСматичСская модСль ΠΈ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΠΌΠΎΠ³ΡƒΡ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒΡΡ для провСдСния ΠΎΡ†Π΅Π½ΠΎΡ‡Π½Ρ‹Ρ… расчСтов Ρ‚Π΅ΠΏΠ»ΠΎΠ²Ρ‹Ρ… Ρ€Π΅ΠΆΠΈΠΌΠΎΠ² скваТин ΠΈ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΉ ΠΏΠΎ ΡƒΠΏΡ€Π°Π²Π»Π΅Π½ΠΈΡŽ ΠΈΠ½Ρ‚Π΅Π½ΡΠΈΠ²Π½ΠΎΡΡ‚ΡŒΡŽ Ρ‚Π΅ΠΏΠ»ΠΎΠΎΠ±ΠΌΠ΅Π½Π½Ρ‹Ρ… процСссов Π² скваТинС Π² соотвСтствии с трСбованиями ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½ΠΎΠΉ Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ.The authors thank the Institute of Geotechnical Mechanics named by N. Poljakov of National Academy of Sciences of Ukraine (Dnipro, Ukraine) for providing technical and informational support in this work

    Psychological and Pedagogical Aspects of the Development of Integrative Readiness of Future Specialists for Professional Activity

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    The need to develop an integrative readiness of future specialists is a relevant scientific problem. The reasons for this could be based on the fact that that the specialists-to-be were expected to be involved in the fierce competition for vacancies and areas of activity, have modern information and communication tools, i.e. have an integrative readiness for professional activity. Institutions do not, however, have a single integration (interdisciplinary) framework for training, do not provide a comprehensive educational information, technical tools, strategies and technologies of education, reasoned psychological and pedagogical conditions. According to the author, the integrative readiness of future specialists for professional activity is a system-personality formation that reflects the unity of theoretical and managerial training and practical ability of students to comprehensively apply regulatory, socio-economic, psychological and pedagogical methods and technologies for solving different problems. This readiness reflects the unity of the motivational inclination of future specialists to professional activity and knowledge of practical technologies for solving a wide range of professional problems in personal and business interactions. The research methodology is based on the concept of key competence, which provides systematization, classification of significant problems, development of a matrix of significant problems, and determination of overall strategy, management technology of professional training development process. Students and teachers can use research materials can be used by in educational and practical activities; developers of content, organizational forms and methods of professional training to improve the practical component of curricula and standards of their development

    Comparison of ratioing and RCNA methods in the detection of flooded areas using Sentinel 2 Imagery (case study: Tulun, Russia)

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    Climate change and natural disasters caused by hydrological, meteorological, and climatic phenomena have a significant impact on cities. Russia, a continental country with a vast territory of complex geographic–ecological environments and highly variable climatic conditions, is subject to substantial and frequent natural disasters. On 29 June 2019, an extreme precipitation event occurred in the city of Tulun in the Irkutsk oblast, Russian Federation, which caused flooding due to the increase in the water level of the Iya River that passes through the city, leaving many infrastructures destroyed and thousands of people affected. This study aims to determine the flooded areas in the city of Tulun based on two change detection methods: Radiometric Rotation Controlled by No-change Axis (RCNA) and Ratioing, using Sentinel 2 images obtained before the event (19 June 2019) and during the flood peak (29 June 2019). The results obtained by the two methodologies were compared through cross-classification, and a 98% similarity was found in the classification of the areas. The study was validated based on photointerpretation of Google Earth images. The methodology presented proved to be useful for the automatic precession of flooded areas in a straightforward, but rigorous, manner. This allows stakeholders to efficiently manage areas that are buffeted by flooding episodes.LA/P/0069/2020info:eu-repo/semantics/publishedVersio

    Rare steppe plant communities in Ukraine: Status, threats and their minimization

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    Nowadays, the impact of anthropogenic activities on natural vegetation is constantly increasing, the level of threats is raised, and newer risk factors are emerging. Recent trends in the anthropogenic impact on plant communities are extremely pronounced, especially on those listed in the Green Book of Ukraine (GBU). Identifying such trends is required for the further development of strategic and tactical planning for the preservation and restoration of rare grass, shrub, and subshrub steppe, petrophyte and psammophyte plant communities of the steppe and forest-steppe zones of Ukraine. In addition to well-established threat factors that cause changes in the habitat of plant communities or mechanically affect plants, new specific threats occur. Today, the most important among them in Ukraine are as follows: climate change, military activity, growing population in the industrial cities, population poverty and government corruption, changes in forms of land ownership and the creation of a land market, lack of knowledge and effective policy, including lack of popular scientific information about the status of specific species and plant groupings, inadequate management of protected areas, uncoordinated environmental protection measures, ineffective sanctions, insufficient monitoring of the consumption of natural biological resources. The preservation of rare grass, shrubby and subshrubby communities in the steppe zone of Ukraine should be provided with proper support at the state level. There is a pressing need for a law of Ukraine β€œOn the preservation of the steppes in Ukraine” and this will require mechanisms for its implementation. The issue of developing a strategy for the conservation and balanced use of steppe ecosystems in Ukraine, whose area is one of the largest in Europe, has long been raised. The main goal of the strategy is the actual preservation of steppe communities (most of which are currently rare) ensuring their restoration, minimizing degradation, and stopping biodiversity loss. In order to develop specific actions to eliminate threats or reduce their impact on rare plant groupings, it is required to investigate the causes of threats and assess their level and duration. This is required to preserve the landscape and biotic diversity in the steppe zone of Ukraine

    Substantiation of thermomechanical technology parameters of absorbing levels isolation of the boreholes

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    The aim of the work is to improve the thermomechanical absorption insulation technology horizons of drilling wells by the established regularities of change and the substantiation of its regime parameters from the composition and physical-mechanical properties strengthen thermoplastic composite material and, on this basis, development a technological regulation containing recommendations on the manufacture of composites and organizations laying work, designing and isolation of the absorption zones of the washing liquid in the drilling rigs wells. The tasks set were solved by complex method research that contains analysis and synthesis of literary and patent sources, conducting analytical, experimental and industrial research. Experimental processing data was carried out using methods of mathematical statistics. Experimental research is carried out using the provisions of the theory of scientific experiment and theory random processes. The evaluation of the effectiveness of the results was carried out in production conditions

    Disturbance indicator values for European plants

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    Motivation Indicator values are numerical values used to characterize the ecological niches of species and to estimate their occurrence along gradients. Indicator values on climatic and edaphic niches of plant species have received considerable attention in ecological research, whereas data on the optimal positioning of species along disturbance gradients are less developed. Here, we present a new data set of disturbance indicator values identifying optima along gradients of natural and anthropogenic disturbance for 6382 vascular plant species based on the analysis of 736,366 European vegetation plots and using expert-based characterization of disturbance regimes in 236 habitat types. The indicator values presented here are crucial for integrating disturbance niche optima into large-scale vegetation analyses and macroecological studies. Main types of variables contained We set up five main continuous indicator values for European vascular plants: disturbance severity, disturbance frequency, mowing frequency, grazing pressure and soil disturbance. The first two indicators are provided separately for the whole community and for the herb layer. We calculated the values as the average of expert-based estimates of disturbance values in all habitat types where a species occurs, weighted by the number of plots in which the species occurs within a given habitat type. Spatial location and grain Europe. Vegetation plots ranging in size from 1 to 1000 m(2). Time period and grain Vegetation plots mostly sampled between 1956 and 2013 (= 5th and 95th quantiles of the sampling year, respectively). Major taxa and level of measurement Species-level indicator values for vascular plants. Software format csv file

    Ellenberg-type indicator values for European vascular plant species

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    Aims: Ellenberg-type indicator values are expert-based rankings of plant species according to their ecological optima on main environmental gradients. Here we extend the indicator-value system proposed by Heinz Ellenberg and co-authors for Central Europe by incorporating other systems of Ellenberg-type indicator values (i.e., those using scales compatible with Ellenberg values) developed for other European regions. Our aim is to create a harmonized data set of Ellenberg-type indicator values applicable at the European scale. Methods: We collected European data sets of indicator values for vascular plants and selected 13 data sets that used the nine-, ten- or twelve-degree scales defined by Ellenberg for light, temperature, moisture, reaction, nutrients and salinity. We compared these values with the original Ellenberg values and used those that showed consistent trends in regression slope and coefficient of determination. We calculated the average value for each combination of species and indicator values from these data sets. Based on species’ co-occurrences in European vegetation plots, we also calculated new values for species that were not assigned an indicator value. Results: We provide a new data set of Ellenberg-type indicator values for 8908 European vascular plant species (8168 for light, 7400 for temperature, 8030 for moisture, 7282 for reaction, 7193 for nutrients, and 7507 for salinity), of which 398 species have been newly assigned to at least one indicator value. Conclusions: The newly introduced indicator values are compatible with the original Ellenberg values. They can be used for large-scale studies of the European flora and vegetation or for gap-filling in regional data sets. The European indicator values and the original and taxonomically harmonized regional data sets of Ellenberg-type indicator values are available in the Supporting Information and the Zenodo repository
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