ارائه راهبرد خودکار به‌روز‌رسانی مدل سرعت به کمک کاهش برون‌راند عمقی باقیمانده در حالت وجود تغییرات جانبی و بی‌هنجاری سرعت

نوع مقاله : مقاله تحقیقی‌ (پژوهشی‌)

نویسندگان

1 دانش آموخته کارشناسی ارشد، لرزه شناسی، دانشکده مهندسی معدن، نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود، شاهرود، ایران

2 دانشیار دانشکده مهندسی معدن، نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود، شاهرود، ایران

چکیده

وجود تغییرات جانبی در سرعت انتشار موج در محیط و وجود بی‌هنجاری­های سرعت، به‌ویژه بی‌هنجاری­هایی که تباین مثبت زیادی با مقدار سرعت زمینه دارند، در کنار ساختارهای زمین­شناسی با هندسه پیچیده، تصویرسازی لرزه‌ای را با دشواری روبه‌رو می­کند. وجود بی‌هنجاری سرعت باعث نادرست شدن مقدار سرعت در سلول­های مجاور بی‌هنجاری در به‌روز­رسانی مدل سرعت خواهد شد. کنترل و تصحیح برون‌راند رخدادهای بازتابی در ورداشت تصویر مشترک، روش مرسوم در به‌روزرسانی مدل سرعت است. به همین دلیل افزایش دقت تصویر لرزه‌ای در حوزه عمق نیازمند کاهش میزان برون‌راند عمق باقیمانده در ورداشت عمقی مشترک است. در روش­های مرسوم، فرایند به‌روز­رسانی مدل سرعت و کاهش برون‌راند عمق باقیمانده، با معرفی پارامتر گاما که برابر با نسبت مدل سرعت دقیق به مدل سرعت اولیه است، به فرایند تعیین مقدار بهینه پارامتر گاما تغییر می­کند. در روش پیشنهادی در این تحقیق، برای کاهش زمان فرایند به‌روز­رسانی مدل سرعت و افزایش دقت مدل سرعت نهایی، با تعیین بازه و گام افزایش مناسب، همه جواب­های ممکن برای پارامتر گاما درنظر­گرفته می‌شود و با استفاده از همه مدل­های سرعت، تصویرسازی عمقی صورت می­گیرد. سپس با توجه به میزان برون‌راند عمق در ورداشت عمقی مشترک، پارامتر گاما در بالا و پایین بی‌هنجاری سرعت در مدل لایه‌ای و سلول­های اطراف بی‌هنجاری در مدل شبکه‌ای با بازه و گام جدید دوباره تعیین می­شود، مدل­های جدید سرعت به‌دست­می‌آید و دست‌چین کردن خودکار مقادیر سرعت در این محدوده­ها دوباره انجام می­شود. فرایند پیشنهادی روی یک مدل مصنوعی و دو داده واقعی مربوط به شمال شرق و غرب ایران، اولی با داشتن تغییرات جانبی و دومی با وجود سازند پرسرعت گچساران اجرا شد. نتایج نشان داد که روش پیشنهادی، تغییرات مدل سرعت را خوب مدل می­کند و باعث بهبود تصویر لرزه‌ای در مقایسه با روش معمول می­شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Presenting automatic velocity model updating by reducing residual depth move-out in the presence of lateral velocity changes and velocity anomaly

نویسندگان [English]

  • Ehsan Aghabarar 1
  • Mehrdad Soleimani monfared 2
  • Amin Roshandel Kahoo 2
1 Post graduate student, Seismic Exploration, Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
2 Associate Professor in Seismic Exploration, Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
چکیده [English]

Seismic velocity analysis is the main part of seismic imaging. Quality of the final seismic image, in velocity dependent imaging methods, strongly depends on the accuracy of the velocity model and consistency of the model with the data. Various types of methods and strategies were presented for velocity model building, such as gridded based and layered based velocity tomography inversion and migration velocity analysis. Conventionally, most of  velocity model building methods use an initial velocity model and some approaches to the final velocity model through several updating steps, mostly by means of the semblance values as the velocity picking criteria. However, this is a time consuming approach and mostly unreliable in the presence of strong velocity variations. Therefore, a new strategy was presented by introducing a parameter called  which is the ratio of the true velocity and the initial velocity. In this strategy, updating the velocity model would be performed through optimization of this parameter. Afterwards, depth imaging would be performed by the new velocity model and accuracy of the velocity would be evaluated by analyzing of common image gathers. For better parameter selection, the concept of the residual depth move-out in the common depth gathers was introduced. It defines the value of deviation in depth of the imaged reflector compared to its true depth. This strategy did not handle the effect of velocity anomalies and had some deficiencies in handling lateral velocity changes. Here, we present a new strategy based on the method of the residual depth move-out in the common depth gathers for velocity model building and depth imaging through appropriate selection of parameter , automatic correction and velocity picking during residual depth move-out correction on common depth gathers. In the presented strategy, we first define a range of possible  parameter for an initial velocity model, which can be obtained by any conventional method. Then, by defining a rational increment in this predefined range for parameter , all of the possible velocity models would be obtained. Subsequently, seismic depth imaging would be performed using all the possible velocity models. Afterwards, common depth gathers will be analyzed automatically to define residual depth move-out. By defining a threshold in correcting of this residual depth move-out, the common depth gathers that exhibit higher move-out than the threshold value will be corrected automatically. Here, those common image gathers that were affected by the velocity anomaly, would be analyzed by selecting a new range and new increment of the parameter to handle the effects of velocity anomaly. This procedure would be iterated until finding a satisfying depth image through depth imaging. This strategy was applied on a synthetic data and two field land data examples with lateral velocity variations and a layer with very high velocity value as velocity anomaly. Results have shown that the presented strategy can be considered as an alternative to the conventional velocity analysis methods.

کلیدواژه‌ها [English]

  • Velocity anomaly
  • seismic imaging
  • residual depth move-out
  • common depth gather
  • Common image gather
Alaei, B., 2006, An integrated procedure for migration velocity analysis in complex structures of thrust belts: Journal of Applied Geophysics, 59, 89–105, https://doi.org/10.1016/j.jappgeo.2005.08.004.
Cameron, M., Fomel, S., and Sethian, J., 2008, Time to depth conversion and seismic velocity estimation using time-migration velocity: Geophysics, 73(5), VE205–VE210, https://doi.org/10.1190/1.2967501.
Dong, C., Wang, S., Zhang, J., Ma, J., and Zhang, H., 2019, Automatic migration velocity estimation for prestack time migration: Geophysics, 84(3), U1-U11, https://doi.org/10.1190/geo2018-0254.1.
Duveneck, E., 2004, Tomographic Determination of Seismic Velocity Models with Kinematic Wavefield Attributes: Ph.D. thesis, Karlsruhe Institute fur Technology, Karlsruhe, Germany.
Feng, Y. E., and Reshef, M., 2016, The Eastern Mediterranean Messinian salt-depth imaging and velocity analysis considerations: Petroleum Geoscience, 22, 333-339, https://doi.org/10.1144/petgeo2015-088.
Fomel, S., and Landa, E., 2014, structural uncertainty of time migrated seismic image: Journal of Applied Geophysics, 101, 27-30, https://doi.org/10.1016/j.jappgeo.2013.11.010.
Jiao, J., Lowrey, D. R., Willis, J. F., and Martínez, R. D., 2008, Practical approaches for subsalt velocity model building: Geophysics, 73, VEL183-VEL194, https://doi.org/10.1190/1.2969084.
Jiao, J., Stoffa, P. L., Sen, M. K., and Seifoullaev, R., 2002, Residual migration velocity analysis in the plane-wave domain: Geophysics, 67, 1258–1269, https://doi.org/10.1190/1.1500388.
Jones, I. F., 2010, An Introduction to: Velocity Model Building: EAGE publication.
Jones, I. F., 2013, Tutorial: The seismic response to strong vertical velocity change: First Break, 31(6), 79-90, https://doi.org/10.3997/1365-2397.2013018.
Jones, I. F., Sugrue, M., and Hardy, P., 2007, Hybrid gridded tomography: First Break, 25, 15-21, https://doi.org/10.3997/1365-2397.2007013.
Lee, M., Keehm, Y., and Song, D., 2017, Quantitative analysis of resolution and smoothing effects of digital pore microstructures on numerical velocity estimation: Geosciences Journal, 21(3), 431–44, https://doi.org/10.1007/s12303-017-0102-9.
Leite, L. W. B., and Vieira, W. W. S., 2019, Automatic seismic velocity analysis based on nonlinear optimization of the semblance function: Journal of Applied Geophysics, 161, 182-192, https://doi.org/10.1016/j.jappgeo.2018.12.015.
Majdański, M., Trzeciak, M., Gaczyński, E., and Maksym, A., 2016, Seismic veloci    estimation from post-critical wide-angle reflections in layered structures: Studia Geophysica et Geodaetica, 60(3), 565-582, https://doi.org/10.1007/s11200-015-1268-0.
McDermott, C., Collier, J. S., Lonergan, L., Fruehn, J., and Bellingham, P., 2019, Seismic velocity structure of seaward-dipping reflectors on the South American continental margin: Earth and Planetary Science Letters, 521, 14-24, https://doi.org/10.1016/j.epsl.2019.05.049.
Montazeri, M., Uldall, A., Moreau, J., and Nielsen, L., 2018, Pitfalls in velocity analysis for strongly contrasting, layered media – Example from the Chalk Group, North Sea: Journal of Applied Geophysics, 149, 52-62, https://doi.org/10.1016/j.jappgeo.2017.12.003.
Nazari Velashani, E., Soleimani Monfared, M., and Roshandel Kahoo, A., 2020, Seismic imaging in complex structures by hybrid gridded tomography velocity model: Journal of Analytical and Numerical Methods in Mining Engineering, 10(22), 59-76.
Nowroozi, A. A., 1990, Interpretation of seismic reflection records: Direct calculation of interval velocities and layer thicknesses from travel times: Puer and Applied Geophysics, 133, 103-115, https://doi.org/10.1007/BF00876705
Rabbel, W., Jusri, T., Köhn, D., Motra, H. M., Niederau, J., Schreiter, L., Thorwart, M., and Wuttke, F., 2017, Seismic velocity
 
      uncertainties and their effect on geothermal predictions: a case study: Energy Procedia, 125, 283-290, https://doi.org/10.1016/j.egypro.2017.08.178.
Sedek, M., and Gross, L., 2017, Normal move-out
correction in anisotropic and laterally
heterogeneous media using simultaneous
velocity variation with offset: Journal of Natural Gas Science and Engineering, 45, 399-414, https://doi.org/10.1016/j.jngse.2017.05.014.
She, D., Guan, L., Xu, Y., and Li, P., 2006, Use of low-frequency signals to improve imaging quality under high-velocity basalt: Applied Geophysics, 3(2), 112-119, https://doi.org/10.1007/s11770-006-0017-0.
Soleimani, M., 2017, Challenges of seismic imaging in complex media around Iran, from Zagros overthrust in the southwest to Gorgan Plain in the northeast: The Leading Edge, 36(6), 499–506, https://doi.org/10.1190/tle36060499.1.
Soleimani, M., Adibi, E., Shahsavani, H., and Sokooti, M. R., 2014, Seismic imaging in geologically complex thrust belts by kinematic wavefield attributes: Iranian Journal of Geophysics, 7(4), 95-116.
Soleimani Monfared, M., and Kalilzadeh, A., 2016, Seismic imaging of complex structures by integrating pre-stack time migration and surface stacking methods: Journal of Earth and Space Physics, 42(2), 293-308.
Vahid Hashemi, M., and Soleimani, M., 2015, Lateral velocity heterogeneties modelling in seismic tomography by introducing different initial velocity models: Iranian Journal of Geophysics, 8(4), 132-167.
Woodward, M. J., Nichols, D., Zdraveva, O., Whitfield, P., and Johns, I. F., 2008, A decade of tomography: Geophysics, 73(5), 5-11, https://doi.org/10.1190/1.2969907.
Yang, F., and Ma, J., 2019, Deep-learning inversion: A next-generation seismic velocity model building method: Geophysics, 84(4), R583–R599, https://doi.org/10.1190/geo2018-0249.1.