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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">geophystech</journal-id><journal-title-group><journal-title xml:lang="ru">Геофизические технологии</journal-title><trans-title-group xml:lang="en"><trans-title>Russian Journal of Geophysical Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2619-1563</issn><publisher><publisher-name>IPGG SB RAS</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18303/2619-1563-2023-2-16</article-id><article-id custom-type="elpub" pub-id-type="custom">geophystech-289</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>Статьи</subject></subj-group></article-categories><title-group><article-title>Определение контрастных границ верхней части разреза путем анализа особенностей дисперсионных кривых скоростей волны Релея на основе эмпирических зависимостей</article-title><trans-title-group xml:lang="en"><trans-title>Determination of the contrast boundaries of the low velocity zone by analyzing the features of the dispersion curves of the Rayleigh wave velocities based on empirical dependencies</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ефремов</surname><given-names>Р. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Efremov</surname><given-names>R. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Магистрант Новосибирского государственного университета, инженер лаборатории динамических проблем сейсмики Института нефтегазовой геологии и геофизики СО РАН, техник Института горного дела им. Н.А. Чинакала СО РАН. Основные научные интересы: геофизика, прямая и обратная задачи, верхняя часть разреза, поверхностные сейсмические волны, метод HVSR, эллиптичность волны Релея.</p></bio><email xlink:type="simple">r.efremov2@g.nsu.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/0000-0002-2726-6904</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сердюков</surname><given-names>А. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Serdyukov</surname><given-names>A. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кандидат физико-математических наук, старший научный сотрудник лаборатории динамических проблем сейсмики Института нефтегазовой геологии и геофизики СО РАН, старший преподаватель Новосибирского государственного университета, старший научный сотрудник Института горного дела им. Н.А. Чинакала СО РАН. Основные научные интересы: сейсмика, численное моделирование, теория упругости, уравнение эйконала, конечно-разностные схемы, сейсмическая томография, миграция, обратные задачи, поверхностные волны, каналовые волны, анизотропия, поглощение, среда Био.</p></bio><email xlink:type="simple">SerdyukovAS@ipgg.sbras.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/0000-0002-3251-0289</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Яблоков</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Yablokov</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кандидат физико-математических наук, научный сотрудник лаборатории динамических проблем сейсмики Института нефтегазовой геологии и геофизики СО РАН, старший научный сотрудник Новосибирского государственного университета, младший научный сотрудник Института горного дела им. Н.А. Чинакала СО РАН. Основные научные интересы: сейсморазведка, верхняя часть разреза, подавление поверхностных волн, спектральный анализ, прямая и обратная задача сейсмики, методы машинного обучения, численное моделирование.</p></bio><email xlink:type="simple">yablokovav@ipgg.sbras.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Институт нефтегазовой геологии и геофизики им. А.А. Трофимука СО РАН&lt;br&gt;&#13;
630090, Новосибирск, просп. Акад. Коптюга, 3&#13;
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Новосибирский государственный университет&lt;br&gt;&#13;
630090, Новосибирск, ул. Пирогова, 1&lt;br&gt;&lt;br&gt;&#13;
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Институт горного дела им. Н.А. Чинакала СО РАН, 630091, Новосибирск, Красный проспект, 54<country>Россия</country></aff><aff xml:lang="en">Trofimuk Institute of Petroleum Geology and Geophysics SB RAS&lt;br&gt;&#13;
Koptyug Ave., 3, Novosibirsk, 630090&#13;
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Novosibirsk State University&lt;br&gt;&#13;
Pirogova Str., 1, Novosibirsk, 630090&#13;
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Chinakal Institute of Mining SB RAS, Krasny Ave., 54, Novosibirsk, 630091<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>01</day><month>09</month><year>2023</year></pub-date><volume>0</volume><issue>2</issue><fpage>16</fpage><lpage>28</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ефремов Р.А., Сердюков А.С., Яблоков А.В., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Ефремов Р.А., Сердюков А.С., Яблоков А.В.</copyright-holder><copyright-holder xml:lang="en">Efremov R.A., Serdyukov A.S., Yablokov A.V.</copyright-holder><license 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://www.rjgt.ru/jour/article/view/289">https://www.rjgt.ru/jour/article/view/289</self-uri><abstract><p>Важным приложением метода многоканального анализа поверхностных волн (MASW) является оценка сейсмической безопасности. Ключевыми параметрами при расчете приращений балльности в ходе сейсмического микрорайонирования является толщина и средняя скорость массива грунтов, лежащих на основании из более жестких скальных горных пород. Специально для определения этих параметров нами предлагается новый метод построения горизонтально-слоистых моделей верхней части геологического разреза с использованием особенностей (положений экстремумов второй производной) дисперсионных кривых фазовых скоростей поверхностной волны Релея, которые, как показали численные эксперименты, связаны с положением контрастных границ в исследуемой среде (т. е., например, граница между грунтами и скальными породами). Такой подход значительно проще традиционно решаемой в методе MASW задачи восстановления горизонтально-слоистой модели по набору значений фазовых скоростей для последовательности частот и не требует задания начального приближения и/или каких-то ограничений на возможные значения параметров модели. В случае двухслойных и трехслойных сред наш подход сводится к простому и быстрому применению явных формул.</p></abstract><trans-abstract xml:lang="en"><p>An important application of the multichannel surface wave (MASW) method is seismic safety assessment. The key parameters in the calculation of increments in the input of seismic microzoning are the thickness and average velocity of the soil mass lying on the base of more rigid rocks. To determine these parameters, we propose a new method for constructing horizontally layered models of the upper part of the geological section using the features (positions of extrema of the second derivative) of the dispersion curves of phase velocities of the Rayleigh surface wave, which, as shown by numerical experiments, are associated with the position of contrasting boundaries in the medium under study. (e.g., the boundary between soils and rocks). This approach is much simpler than the problem of recovering a horizontally layered model traditionally solved in the MASW method from a set of phase velocities for a sequence of frequencies and does not require an initial approximation and/or any restrictions on the possible values of the model parameters. In the case of two-layer and three-layer media, our approach is reduced to a simple and fast application of explicit formulas.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Сейсмическое микрорайонирование</kwd><kwd>MASW</kwd><kwd>дисперсионная кривая</kwd><kwd>волна Релея</kwd></kwd-group><kwd-group xml:lang="en"><kwd>MASW</kwd><kwd>dispersion curve</kwd><kwd>Rayleigh wave</kwd><kwd>seismic hazard assessment</kwd></kwd-group><funding-group xml:lang="ru"><funding-statement>Работа выполнена в рамках проекта ФНИ № FWZZ-2022-0017.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Алешин А.С. Апология метода сейсмических жесткостей // Сейсмостойкое строительство. Безопасность сооружений. – 2016. – № 3. – С. 13–21.</mixed-citation><mixed-citation xml:lang="en">Abdialim S., Hakimov F., Kim J., Ku T., Moon S.W. Seismic site classification from HVSR data using the Rayleigh wave ellipticity inversion: A case study in Singapore // Earthquakes and Structures. – 2021. – Vol. 21 (3). – P. 231–238, doi: 10.12989/eas.2021.21.3.231.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Свод правил 283.1325800.2016 «Объекты строительные повышенной ответственности. Правила сейсмического микрорайонирования». – Москва: Минстрой России, 2016. – 24 с.</mixed-citation><mixed-citation xml:lang="en">Aleshin A.S. Apology of seismic rigidity method // Earthquake Engineering. Construction Safety. – 2016. – Vol. 3. – P. 13–21.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Abdialim S., Hakimov F., Kim J., Ku T., Moon S.W. Seismic site classification from HVSR data using the Rayleigh wave ellipticity inversion: A case study in Singapore // Earthquakes and Structures. – 2021. – Vol. 21 (3). – P. 231–238, doi: 10.12989/eas.2021.21.3.231.</mixed-citation><mixed-citation xml:lang="en">Boaga J., Cassiani G., Strobbia C.L., Vignoli G. Mode misidentification in Rayleigh waves: Ellipticity as a cause and a cure // Geophysics. – 2013. – Vol. 78 (4). – P. EN17–EN28, doi: 10.1190/geo2012-0194.1.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Boaga J., Cassiani G., Strobbia C.L., Vignoli G. Mode misidentification in Rayleigh waves: Ellipticity as a cause and a cure // Geophysics. – 2013. – Vol. 78 (4). – P. EN17–EN28, doi: 10.1190/geo2012-0194.1.</mixed-citation><mixed-citation xml:lang="en">Constable S.C., Parker R.L., Constable C.G. Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data // Geophysics. – 1987. – Vol. 52 (3). – P. 289–300, doi: 10.1190/1.1442303.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Constable S.C., Parker R.L., Constable C.G. Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data // Geophysics. – 1987. – Vol. 52 (3). – P. 289–300, doi: 10.1190/1.1442303.</mixed-citation><mixed-citation xml:lang="en">Cox B.R., Teague D.P. Layering ratios: a systematic approach to the inversion of surface wave data in the absence of a priori information // Geophysical Journal International. – 2016. – Vol. 207 (1). – P. 422–438, doi: 10.1093/gji/ggw282.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Cox B.R., Teague D.P. Layering ratios: a systematic approach to the inversion of surface wave data in the absence of a priori information // Geophysical Journal International. – 2016. – Vol. 207 (1). – P. 422–438, doi: 10.1093/gji/ggw282.</mixed-citation><mixed-citation xml:lang="en">Dal Moro G. Some aspects about surface wave and HVSR analyses: a short overview and a case study // Bollettino di Geofisica Teorica ed Applicata. – 2011. – Vol. 52 (2). – P. 241–259, doi: 10.4430/bgta0007.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Dal Moro G. Some aspects about surface wave and HVSR analyses: a short overview and a case study // Bollettino di Geofisica Teorica ed Applicata. – 2011. – Vol. 52 (2). – P. 241–259, doi: 10.4430/bgta0007.</mixed-citation><mixed-citation xml:lang="en">Mendiguren J.A. Inversion of surface wave data in source mechanism studies // Journal of Geophysical Research. – 1977. – Vol. 82 (5). – P. 889–894, doi: 10.1029/JB082i005p00889.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Mendiguren J.A. Inversion of surface wave data in source mechanism studies // Journal of Geophysical Research. – 1977. – Vol. 82 (5). – P. 889–894, doi: 10.1029/JB082i005p00889.</mixed-citation><mixed-citation xml:lang="en">Mirjalili S., Mirjalili S.M., Lewis A. Grey wolf optimizer // Advances in Engineering Software. – 2014. – Vol. 69. – P. 46–61, doi: 10.1016/j.advengsoft.2013.12.007.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Mirjalili S., Mirjalili S.M., Lewis A. Grey wolf optimizer // Advances in Engineering Software. – 2014. – Vol. 69. – P. 46–61, doi: 10.1016/j.advengsoft.2013.12.007.</mixed-citation><mixed-citation xml:lang="en">Nakamura Y. A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface // Railway Technical Research Institute. Quarterly Reports. – 1989. – Vol. 30 (1). – P. 25–33.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Nakamura Y. A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface // Railway Technical Research Institute. Quarterly Reports. – 1989. – Vol. 30 (1). – P. 25–33.</mixed-citation><mixed-citation xml:lang="en">Nakamura Y. What is the Nakamura method? // Seismological Research Letters. – 2019. – Vol. 90 (4). – P. 1437–1443, doi: 10.1785/0220180376.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Nakamura Y. What is the Nakamura method? // Seismological Research Letters. – 2019. – Vol. 90 (4). – P. 1437–1443, doi: 10.1785/0220180376.</mixed-citation><mixed-citation xml:lang="en">Park C. MASW for geotechnical site investigation // The Leading Edge. – 2013. – Vol. 32 (6). – P. 656–662, doi: 10.1190/tle32060656.1.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Park C. MASW for geotechnical site investigation // The Leading Edge. – 2013. – Vol. 32 (6). – P. 656–662, doi: 10.1190/tle32060656.1.</mixed-citation><mixed-citation xml:lang="en">Park C.B., Miller R.D., Xia J. Multichannel analysis of surface waves // Geophysics. – 1999. – Vol. 64 (3). – P. 800–808, doi: 10.1190/1.1444590.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Park C.B., Miller R.D., Xia J. Multichannel analysis of surface waves // Geophysics. – 1999. – Vol. 64 (3). – P. 800–808, doi: 10.1190/1.1444590.</mixed-citation><mixed-citation xml:lang="en">Socco L.V., Boiero D. Improved Monte Carlo inversion of surface wave data // Geophysical Prospecting. – 2008. – Vol. 56 (3). – P. 357–371, doi: 10.1111/j.1365-2478.2007.00678.x.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Socco L.V., Boiero D. Improved Monte Carlo inversion of surface wave data // Geophysical Prospecting. – 2008. – Vol. 56 (3). – P. 357–371, doi: 10.1111/j.1365-2478.2007.00678.x.</mixed-citation><mixed-citation xml:lang="en">Song X., Tang L., Zhao S., Zhang X., Li L., Huang J., Cai W. Grey wolf optimizer for parameter estimation in surface waves // Soil Dynamics and Earthquake Engineering. – 2015. – Vol. 75. – P. 147–157, doi: 10.1016/j.soildyn.2015.04.004.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Song X., Tang L., Zhao S., Zhang X., Li L., Huang J., Cai W. Grey wolf optimizer for parameter estimation in surface waves // Soil Dynamics and Earthquake Engineering. – 2015. – Vol. 75. – P. 147–157, doi: 10.1016/j.soildyn.2015.04.004.</mixed-citation><mixed-citation xml:lang="en">SP 283.1325800.2016 "Construction objects of increased responsibility. Rules of seismic microdistricting". – Ministry of Construction of Russia, Moscow, 2016. – 24 p.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Yablokov A.V., Serdyukov A.S., Loginov G.N., Baranov V.D. An artificial neural network approach for the inversion of surface wave dispersion curves // Geophysical Prospecting. – 2021. – Vol. 69 (7). – P. 1405–1432, doi: 10.1111/1365-2478.13107.</mixed-citation><mixed-citation xml:lang="en">Yablokov A.V., Serdyukov A.S., Loginov G.N., Baranov V.D. An artificial neural network approach for the inversion of surface wave dispersion curves // Geophysical Prospecting. – 2021. – Vol. 69 (7). – P. 1405–1432, doi: 10.1111/1365-2478.13107.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Yablokov A.V., Lugovtsova Y., Serdyukov A.S. Uncertainty quantification of multimodal surface wave inversion using artificial neural networks // Geophysics. – 2023. – Vol. 88 (2). – P. KS1–KS11, doi: 10.1190/geo2022-0261.1.</mixed-citation><mixed-citation xml:lang="en">Yablokov A.V., Lugovtsova Y., Serdyukov A.S. Uncertainty quantification of multimodal surface wave inversion using artificial neural networks // Geophysics. – 2023. – Vol. 88 (2). – P. KS1–KS11, doi: 10.1190/geo2022-0261.1.</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>
