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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">scienceit</journal-id><journal-title-group><journal-title xml:lang="ru">Наука. Инновации. Технологии</journal-title><trans-title-group xml:lang="en"><trans-title>Science. Innovations. Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2308-4758</issn><publisher><publisher-name>North-Caucasus Federal University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37493/2308-4758.2024.3.7</article-id><article-id custom-type="elpub" pub-id-type="custom">scienceit-691</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>РАЗРАБОТКА И ЭКСПЛУАТАЦИЯ НЕФТЯНЫХ И ГАЗОВЫХ МЕСТОРОЖДЕНИЙ (технические науки)</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>DEVELOPMENT AND OPERATION OF OIL AND GAS FIELDS (technical sciences)</subject></subj-group></article-categories><title-group><article-title>Подход к получению вероятностной оценки прогнозных профилей добычи, конденсатогазового фактора и обводнения</article-title><trans-title-group xml:lang="en"><trans-title>An approach to forecast production profiles, oil-gas ratio and water contamination probabilistic assessment</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9090-0672</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Балин</surname><given-names>Д. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Balin</surname><given-names>D. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Даниил Валерьевич Балин — аспирант</p><p>д. 38, ул. Володарского, Тюмень, 625000</p></bio><bio xml:lang="en"><p>Daniil V. Balin — Postgraduate student</p><p>38, Volodarskogo St., Tyumen, 625000</p></bio><email xlink:type="simple">danilbalin@bk.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Балина</surname><given-names>О. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Balina</surname><given-names>O. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ольга Владимировна Балина — кандидат технических наук, доцент, до­цент</p><p>д. 38, ул. Володарского, Тюмень, 625000</p></bio><bio xml:lang="en"><p>Olga V. Balina — PhD in Technical Sciences, Associate Professor, Associate Professor</p><p>38, Volodarskogo St., Tyumen, 625000</p></bio><email xlink:type="simple">balinaov@tyuiu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8519-7230</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мамчистова</surname><given-names>Е. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Mamchistova</surname><given-names>E. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Елена Ивановна Мамчистова — кандидат технических наук, доцент, про­фессор</p><p>д. 38, ул. Володарского, Тюмень, 625000</p></bio><bio xml:lang="en"><p>Elena I. Mamchistova — PhD in Technical Sciences, Associate Professor, Pro­fessor</p><p>38, Volodarskogo St., Tyumen, 625000</p></bio><email xlink:type="simple">mamchistovaei@tyuiu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Тюменский индустриальный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Industrial University of Tyumen</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>09</day><month>10</month><year>2024</year></pub-date><volume>0</volume><issue>3</issue><fpage>139</fpage><lpage>156</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Балин Д.В., Балина О.В., Мамчистова Е.И., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Балин Д.В., Балина О.В., Мамчистова Е.И.</copyright-holder><copyright-holder xml:lang="en">Balin D.V., Balina O.V., Mamchistova E.I.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://scienceit.elpub.ru/jour/article/view/691">https://scienceit.elpub.ru/jour/article/view/691</self-uri><abstract><p>Рассмотрен подход к получению вероятностной оценки про­гнозных показателей разработки газоконденсатного плас­та с применением многовариантных гидродинамических расчетов. Необходимость подобного решения диктуется стремлением к нивелированию влияния значительного чис­ла неопределенностей, присутствующих в практике работы с цифровыми моделями месторождений. В качестве основ­ного инструмента было использовано программное обеспе­чение «тНавигатор», обладающее широким функционалом в указанном направлении. Изучены возможности задания переменных для параметризации модели, проведен обзор методов планирования эксперимента и оптимизационных алгоритмов. С помощью оптимизационного алгоритма Диф­ференциальной эволюции на первом этапе произведена адаптация исходной версии гидродинамической модели, в которой наблюдались проблемы с воспроизведением отборов по добываемым фазам и динамике давлений, на исторические показатели работы скважин. Полученное каче­ство адаптации контролировалось значениями специально сгенерированной целевой функции. На втором шаге на ба­зе наилучших сценариев настройки исторического периода рассчитаны прогнозные параметры разработки, для которых были построены соответствующие накопленные функции распределения, отражающие интересующую вероятностную оценку. По итогам проделанной работы сформирована необходимая последовательность действий, позволяющая прийти к получению необходимых искомых величин, а так­же сформулированы возможные варианты модификации рассмотренного подхода в области сокращения числа рас­считываемых моделей через выделение трех базовых сце­нариев и использование многомерного масштабирования, позволяющего кластеризовать равновероятные сценарии с последующим выбором представительных реализаций.</p></abstract><trans-abstract xml:lang="en"><p>An approach to probabilistic assessment of field development forecast parameters for gas-condensate reservoir using multi­variant simulation was studied. The necessity of such decision may be explained by the aim to level the influence of large number of uncertainties which occur during the work with res­ervoir simulation models. «tNavigator» software was used as the main instrument since it provides wide functionality in the sphere of interest. The variants of variables implementation were studied, the review of experimental designs and optimiza­tion algorithms was done. At the first step, the simulation model was history matched using Differential Evolution algorithm, since its initial version had problems with phase withdrawals and pressure dynamics. Corresponding history matching qual­ity was controlled by specially generated objective function val­ues. At the second step a series of production forecasts based on the best history matching cases was calculated; cumulative distribution functions for field development parameters under consideration were received to get the necessary probabilistic assessment. As a result, the workflow for values of interest get­ting was provided; also, the variants of further modifications for studied approach were formulated: the number of simulation runs can be decreased through the choice of three base vari­ants and use of multi-dimensional scaling which provides the opportunity for realizations of equal probability clustering with further choice of representative cases.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>адаптация</kwd><kwd>многовариантные расчеты</kwd><kwd>дифференциальная эволюция</kwd><kwd>накопленная функция распределения</kwd><kwd>вероятностная оценка</kwd></kwd-group><kwd-group xml:lang="en"><kwd>history matching</kwd><kwd>multi-variant calculations</kwd><kwd>differential evolution</kwd><kwd>cumulative distribution function</kwd><kwd>probabilistic assessment</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Козырев Н. Д., Вишняков А. Ю., Путилов И. С. Оценка влияния параметров неопределенности на прогнозирование показателей разработки // Недропользование. 2020. Т. 20. № 4. С. 356–368. https://doi.org/10.15593/2712-8008/2020.4.5</mixed-citation><mixed-citation xml:lang="en">Kozyrev ND,VishnyakovAYu,Putilov IS.Assessment of the uncertainty parameters influence on the development indicators forecasting. Nedropolzovanie = Subsoil use. 2020;20(4):356-368. (In Russ.). https://doi.org/10.15593/2712-8008/2020.4.5</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Андронов С. А., Горенкова Е. А., Гомонов А. А., Максименко И. А. Подходы к выбору реализаций при вероятностном моделировании геологической модели и анализ влияния на прогнозный профиль добычи // PROНЕФТЬ. Профессионально о нефти. 2023. № 8 (4). С. 25–32. https://doi.org/10.51890/2587-7399-2023-8-4-25-32</mixed-citation><mixed-citation xml:lang="en">Andronov SA, Gorenkova EA, Gomonov AA, Maksimenko IA. Approaches to selection of realizations in probabilistic modeling of geological model and analysis of influence on forecast production profile. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2023;8(4):25-32. (In Russ.). https://doi.org/10.51890/2587-7399-2023-8-4-25-32</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Шишаев Г. Ю., Матвеев И. В., Еремян Г. А. Геологически обоснованная автоматизированная адаптация гидродинамических моделей на примере реального месторождения // Нефтяное хозяйство. 2020. № 6. С. 58–61.</mixed-citation><mixed-citation xml:lang="en">Shisahev GYu, Matveev IV, Erenyan GA. Geologically justified assisted history matching of flow models using real field as an example. Neftyanoe hozyajstvo = Oil industry. 2020;6:58-61. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Syrtlanov V., Golovatskiy Y., Ishimov I., Mezhnova N. Assisted history matching for reservoir simulation models // SPE Russian Petroleum Technology Conference. Moscow, Russia. October 2019. https://doi.org/10.2118/196878-MS</mixed-citation><mixed-citation xml:lang="en">Syrtlanov V, Golovatskiy Y, Ishimov I, Mezhnova N. Assisted history matching for reservoir simulation models. SPE Russian Petroleum Technology Conference. Moscow, Russia. October 2019. https://doi.org/10.2118/196878-MS</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Сметкина М. А., Мелкишев О. А., Присяжнюк М. А. Уточнение значений проницаемости при адаптации гидродинамической модели // Недропользование. 2020. Т. 20. № 3. С. 223–230. https://doi.org/10.15593/2712-8008/2020.3.3</mixed-citation><mixed-citation xml:lang="en">Smetkina MA, Melkishev OA, Prisyaznyuk МA. Refining the values of permeability when adapting the hydrodynamic model. Nedropolzovanie = Subsoil use. 2020;20(3):223-230. (In Russ.) https://doi.org/10.15593/2712-8008/2020.3.3</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">тНавигатор 24.2. Адаптация и оптимизация. Руководство пользователя // Июль 2024.</mixed-citation><mixed-citation xml:lang="en">tNavigator 24.2. AHM and Uncertainty. User guide. July 2024.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Макаричев Ю. А., Иванников Ю. Н. Методы планирования эксперимента и обработки данных: учеб. пособие. Самара: Самар. гос. техн. ун-т, 2016. 131 с.</mixed-citation><mixed-citation xml:lang="en">Makarichev YuA, Ivannikov YuN. Methods of experimental design and data processing: technical manual. Samara: Samara State Technical University; 2016. 131 p. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Симонов М. В., Пенигин А. В., Маргарит А. С., Пустовских А. А., Смирнов Н. А., Ситников А. Н. Методология построения метамоделей и перспективы их применения для решения актуальных задач нефтяного инжиниринга // PROНЕФТЬ. Профессионально о нефти. 2019. № 2 (12). С. 49–53.</mixed-citation><mixed-citation xml:lang="en">Simonov MV, PeniginAV, MargaritAS, Pustovskikh АA, Smirnov NA, Sitnikov AN. Methodology of surrogate Models (MetaModels) and their prospects for solving petroleum engineering challenges. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2019;2(12):49-53. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Mohamed L., Christie M., Demyanov V. History Matching and Uncertainty Quantification: Multiobjective Particle Swarm Optimisation Approach // Conference SPE 143067. Vienna, Austria, 23-26 May 2011. https://doi.org/10.2118/143067-ms</mixed-citation><mixed-citation xml:lang="en">Mohamed L, Christie M., Demyanov V. History Matching and Uncertainty Quantification: Multiobjective Particle Swarm Optimisation Approach. SPE 143067. Vienna, Austria, 23-26 May 2011.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Nelder J. A., Mead R. A simplex method for function minimization // Comput. J. 1965. No. 7. P. 308.</mixed-citation><mixed-citation xml:lang="en">Nelder JA, Mead R. A simplex method for function minimization. Comput. J. 1965;7:308.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Kathrada M. Uncertainty evaluation of reservoir simulation models using particle swarms and hierarchical clustering. Doctoral dissertation. Heriot-Watt University, 2009. 221 p.</mixed-citation><mixed-citation xml:lang="en">Kathrada M. Uncertainty evaluation of reservoir simulation models using particle swarms and hierarchical clustering. Doctoral dissertation. Heriot-Watt University; 2009. 221 p.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Amirian E., Fedutenko E., Yang C., Chen Z., Nghiem L.Artificial neural network modeling and forecasting of oil reservoir performance // Lecture Notes in Social Networks. 2018. P. 43–67.</mixed-citation><mixed-citation xml:lang="en">Amirian E, Fedutenko E, Yang C, Chen Z, Nghiem L. Artificial neural network modeling and forecasting of oil reservoir opperformance. Springer. Cham. 2018.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Evensen G. Data assimilation: The ensemble Kalman filter. Springer, NY. 2007. 279 p.</mixed-citation><mixed-citation xml:lang="en">Evensen G. Data assimilation: The ensemble Kalman filter. Springer, NY; 2007.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Поспелова Т. А. Развитие методов регулирования работы скважин на основе цифровых технологий: автореф. дис. … д-ра техн. наук. Тюмень: Тюменский индустриальный университет, 2021. 48 с.</mixed-citation><mixed-citation xml:lang="en">Pospelova ТА. The development of methods of well work regulation based of digital technologies: author’s summary of dissertation of doctor of technical sciences. Tyumen: Industrial University of Tyumen; 2021. 48 p.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Santhosh E. C., Sangwai J. S. A hybrid differential evolution algorithm approach towards assisted history matching and uncertainty quantification for reservoir models // Journal of Petroleum Science and Engineering. 2016. Vol. 142. P. 21–35.</mixed-citation><mixed-citation xml:lang="en">Emil C. Santhosh, Jitendra S. Sangwai. A hybrid differential evolution algorithm approach towards assisted history matching and uncertainty quantification for reservoir models. Journal of Petroleum Science and Engineering. 2016;142:21-35.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Jianwei Gu, Wei Liu, Kai Zhang, Liang Zhai, Yigen Zhang, Fuzhen Chen. Reservoir production optimization based on surrograte model and differential evolution algorithm // Journal of Petroleum Science and Engineering. 2021. Vol. 205.Art. 108879.</mixed-citation><mixed-citation xml:lang="en">Jianwei Gu, Wei Liu, Kai Zhang, Liang Zhai, Yigen Zhang, Fuzhen Chen. Reservoir production optimization based on surrogate model and differential evolution algorithm. Journal of Petroleum Science and Engineering. 2021;205:108879.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Hajizadeh Y., Christie M., Demyanov V. Application of differential evolution as a new method for automatic history matching // In Society of Petroleum Engineers - Kuwait International Petroleum Conference and Exhibition, KIPCE 2009: Meeting Energy Demand for Long Term Economic Growth. 2009. P. 272–284. https://doi.org/10.2118/127251-MS</mixed-citation><mixed-citation xml:lang="en">Hajizadeh Y, Christie M, Demyanov V. Application of differential evolution as a new method for automatic history matching. https://doi.org/10.2118/127251-MS</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Степанов С. В., Бекман А. Д., Ручкин А. А., Поспелова Т. А. Сопровождение разработки нефтяных месторождений с использованием моделей CRM. Тюмень: ИПЦ «Экспресс», 2021. 300 с.</mixed-citation><mixed-citation xml:lang="en">Stepanov SV, Bekman AD, Ruchkin AA, Pospelova TA Oil field development support using CRM models. Tyumen: IPC “Express”; 2021. 300 p. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Спирина Е. А., Давыдов И. В., Сазонов Д. Н., Таранин Р. М., Камалетдинов Р. Х. Экспресс-оценка выбора оптимальных параметров системы разработки в условиях геологической неопределенности // PROНЕФТЬ. Профессионально о нефти. 2023. № 8 (2). С. 165–175. https://doi.org/10.51890/2587-7399-2023-8-2-165-175</mixed-citation><mixed-citation xml:lang="en">Spirina EA, Davydov IV, Sazonov DN, Taranin RM, Kamaletdinov RH. Express assessment of the choice of optimal parameters of the development system under the conditions of geological uncertainty. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2023;8(2):165-175. (In Russ.). https://doi.org/10.51890/2587-7399-2023-8-2-165-175</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Каневская Р. Д. Математическое моделирование гидродинамических процессов разработки месторождений углеводородов. Москва-Ижевск: Институт компьютерных исследований, 2002. 140 с.</mixed-citation><mixed-citation xml:lang="en">Kanevskaya RD. Mathematical modelling of hydrodynamic processes of hydrocarbon fields development. Moscow-Izhevsk: Institute of computer research; 2002. 140 p. (In Russ.)</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
