بهبود کیفیت نشانگر پراشندگی برای تصویرسازی گسل‌ها با استفاده از تابع شباهت محلی اریب در حوزه پس‌برانباشت

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران

2 استاد، گروه فیزیک زمین، مؤسسه ژئوفیزیک، دانشگاه تهران، تهران، ایران

چکیده

پراش­ها اطلاعات مفیدی را درباره عارضه­های زمین‌شناختی زیرسطحی مانند گسل­ها، ناپیوستگی­ها، چین‌خوردگی­ها و مانند آنها ارائه می­دهند. در مطالعه گسل­ها برگشتگی قطبایی موج­های پراشیده از لبه گسل­ها یک چالش بزرگ به­شمار می­رود. در دهه­های اخیر چندین روش­ در حوزه­های پیش و پس­برانباشت برای تعیین ویژگی­ها و محل پراش­ها ارائه شده است ولی بیشتر آنها در مواجهه با برگشتگی قطبایی امواج پراشیده از لبه گسل­ها، توانایی کافی برای آشکارسازی پراش­ها را ندارند. روش­های تابع شباهت و مهاجرت کرشهف به­عنوان دو روش مرسوم، بدون در نظر گرفتن برگشتگی قطبایی، برای تصویرسازی پراش­­های منتشر­شده از لبه گسل­ها دچار مشکل می‌شوند. در این مقاله دو راهکار برای بهبود کیفیت نشانگر پراشندگی معرفی می­شود که حضور برگشتگی قطبایی تأثیری در کارایی آن ندارد. در راهکار ارائه شده برای برطرف کردن مشکل برگشتگی قطبایی، خم برون‌راند پراش به چند گروه تقسیم و سپس تابع شباهت به­صورت محلی برای هر کدام از این گروه­ها محاسبه می­شود. تابع شباهتی محلی به‌کار رفته در این تحقیق، زمان­سیر امواج پراشیده را از معادله ریشه دوم دوگانه به­دست می‌آورد. همچنین روشی برای بهبود بیشتر تصویر چشمه­های پراش­ استفاده می­شود که با به‌کارگیری پنجره اریب در آن، به­نوعی تابع شباهت محلی را به­صورت تابعی از زمان وزن­دار می­کند. کارایی روش تابع شباهت محلی با استفاده از وزن­دهی پنجره اریب و بدون آن بر روی داده­های لرزه­ای مصنوعی و واقعی بدون اعمال هیچ­گونه تصحیح قطبایی بررسی شده که نتایج حاکی از کانونش و تفکیک­پذیری بهتر پراش­ها در لبه گسل­ها است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Improving diffractivity attribute to image faults using tapered local semblance in post-stack domain

نویسندگان [English]

  • Mohammad Hosseini 1
  • Hamid Reza Siahkoohi 2
1 Ph.D. Student, Islamic Azad University, Science and Research Branch, Tehran, Iran
2 Professor, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
چکیده [English]

Diffractions carry useful and important information about subsurface features such as unconformities, faults, pinch-out, and so on. On the other hand, most of the information is encoded in diffractions. Polarity reversal across diffraction move out curves that are generated from fault’s edges, is a great challenge in seismic diffraction imaging. For the last few decades, several conventional methods in the pre-and post-stack domains, have been carried out for the diffractions characteristics and their locations. But most of these methods were not able to deal with the polarity reversal for diffraction imaging, some of them were time consuming, and needed to have some correction to deal with polarity changes, especially in diffraction caused by fault’s edges. Despite a large amount of research that has been carried out on diffraction imaging, very few studies have been devoted to the challenge of the polarity reversal across move out surfaces. We used the semblance function along with the hyperbolic move out curves for the diffractions that their travel times have been calculated using the double-square-root equation. As we know, using both semblance and Kirchhoff migration for diffraction imaging from fault’s edges, without which taking the polarity reversal into account would fail. This is caused by presence of same number of positive and negative wavelets in the diffraction move out curves. For solving this problem, we divided the global scanning window along hyperbolic move out surfaces into several subdivided window and the local semblance measurements over the sub-windows were performed separately. Every point in image domain is considered as a diffraction point that we call this points as image points. The final semblance measure at each image point is calculated by averaging the semblance measurements from sub-divided smaller windows. We also contaminated the synthetic data with white Gaussian noise, having different signal to noise ratios. Results showed no significant differences due to the fact that random arrivals in seismic data do not influence the semblance measurement. In next step to improve the diffraction imaging, we used tapered local semblance due to interference of diffractions with dominated reflection waves, other data and even other diffractions, especially at far offsets from diffraction’s apex. We called the proposed method as tapered local semblance method. The method weights the data from top to the bottom along the time axis, we also use less number of traces at shallow parts and more traces at deeper parts to reduce the harming effect of the interference. To coup with this task, we introduced a triangle taper to take few number of traces at the early arrival parts and more traces at the late arrival parts, instead of using a box with constant number of traces in the apertures from top to the bottom of the window. We tested several tapers with different angles of apex to determine the optimum one. We evaluated both methods on synthetic data as well as field recorded dataset. Both methods required no polarity reversal corrections to be applied. The obtained results showed the ability of our workflow to having higher resolution and good localization for diffractions from fault’s edges in synthetic data. The results obtained from using the tapered local semblance method on field recorded dataset showed more diffractivity than local semblance method.

کلیدواژه‌ها [English]

  • Fault detection
  • diffraction imaging
  • polarity reversal
  • tapered local semblance
  • tapered aperture
  • diffractivity attribute
Alshamry, M., 2011, Detection of diffracted waves, BSc, (Geophysics) Kansas state university. Report No.: GPM 3/11.
Alonaizi, F., Pevzner, R., Bόna, A., Alshamry, M., Caspari, E. and Gurevich, B, 2014, Application of diffracted wave analysis to time-lapse seismic data for CO2 leakage detection, Geophysical Prospecting 62(2), 197-209.
BakhtiariRad, P., Schwarz, B., Gajewski, D. and Vanelle, C, 2018, Common-reflection-surface-based prestack diffraction separation and imaging, Geophysics 83(1), S47-S55.
Berkovitch, A., Belfer, I., Hassin, Y. and Landa, E, 2009, Diffraction imaging by multifocusing, Geophysics 74(6), WCA75–WCA81.
Bóna, A., Pevzner, R., Tertyshnikov, K., Greenwood, A., Sun B., Yavuz, S. and Urosevic, M, 2013, Diffraction imaging in hard-rock environments, In 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013 (pp. cp-348).
Burnett, W. and Fomel, S., 2011, Diffraction velocity analysis by path-integral seismic imaging, 81st SEG Annual International Meeting, 3898-3902.
Coimbra, A. T., Jadsom, S. J., Figueiredo, D., Schleicher, J., Novais, A. and Costa, C. J., 2013, Migration velocity analysis using residual diffraction moveout in the poststack depth domain, Geophysics 78(3), S125-S135.
Dalton, D. R. and Yedlin, M. J., 1989, Exact time-domain solu-tions for acoustic diffraction by a half plane: Surveys in Geo-physics, 10, 305–330.
Dell, S. and Gajewski, D., 2011, Common-reflection-surface-based workflow for diffraction imaging, Geophysics 76(5), S187–S195.
Dell, S., Pronrvich, A., Kashtan, B. and Gajewski, D., 2013, Diffraction traveltime approximation for general anisotropic media, Geophysics 78(5), WC15–WC23.
Fomel, S., 2009, Velocity analysis using AB semblance, Geophysical Prospecting 57(3), 311-321.
Fomel, S., Landa, E. and Taner, M. T., 2007, Poststack velocity analysis by separation and imaging of seismic diffractions, Geophysics 72(6), U89–U94.
Gong, X., Yu, C. and Wang, Z., 2016, Separation of prestack seismic diffractions using an improved sparse apex-shifted hyperbolic Radon transform, Exploration Geophysics 48(4), 476-484.
Hagedoorn, J. G., 1954, A process of seismic reflection interpretation, Geophysical prospecting 2(2), 85-127.
Harlan, W. S., Claerbout, J. F. and Rocca, F., 1984, Signal/noise separation and velocity estimation, Geophysics 49(11), 1869-1880.
Khaidukov, V., Landa, E. and Moser, T. J., 2004, Diffraction imaging by focusing-defocusing: An outlook on seismic super resolution, Geophysics 69(6), 1478-1490.
Khoshnavaz, M. J., Bόna, A., Chambers, K., Siahkoohi, H. and Khoshnavaz, A., 2019, Surface passive seismic monitoring by the local use of semblance, the 2nd AEGC International Geophysical Conference and exhibition, Perth, Western Australia.
Khoshnavaz, M. J., Bόna, A. and Urosevic, M., 2017, Post-stack diffraction imaging in vertical transverse isotropy media using non-hyperbolic moveout approximations, Geophysical Prospecting 66(2), 273-281.
Khoshnavaz, M. J., Bóna, A., Hossain, M. S., Urosevic, M. and Chambers, K., 2016, Diffractivity Another attribute for the interpretation of seismic data in hard rock environment, a case study. Interpretation 4(4), B23-B32.
Khoshnavaz, M. J., Siahkoohi, H. R. and Roshnadel Kahoo, A., 2021, Seismic velocity analysis in the presence of amplitude variations using local semblance, Geophysical Prospecting, 69, no. 6, 1208-1217, doi: 10.1111/1365-2478.13118.
Klem-Musatov, K., Kovalevsky, G. L. and Tokmulina, L. R., 1972, On intensity of waves diffracted at their edges, Geol.Geophys. 5, 82-92.
Krey, T., 1952, The significance of diffraction in the investigation of faults, Geophysics 17(4), 843–858.
Landa, E. and Keydar, S., 1998, Seismic monitoring of diffraction images for detection of local heterogeneities. Geophysics 63(3), 1093–1100.
Landa, E., Shtivelman, V. and Gelchinsky, B., 1987, A method for detection of diffracted waves on common-offset sections, Geophysical prospecting 35(4), 359-373.
Li, C., Peng, S., Zhao, J., Cui, X., Du, W. and, Satibekova, S., 2018, Polarity-preserved diffraction extracting method using modified apex-shifted Radon transform and double-branch Radon transform, J. Geophys. Eng.15(2018)1991–2000(10pp).
Moser, T. J. and Howard, C. B., 2008, Diffraction imaging in depth, Geophysical Prospecting 56(5), 627–641.
Papziner, U. and Nick, K. P., 1998, Automatic detection of hyperbolas in georadargrams by slant-stack processing and migration. First Break 16(6).
Reshef, M. and Landa, E., 2008, Post-stack velocity analysis in the dip-angle domain using diffractions, Geophysical Prospecting 57(5), 811–821.
Sava, C. P., Biondi, B. and Etgen, J., 2005, Wave-equation migration velocity analysis by focusing diffractions and reflections, Geophysics 70(3), U19-U27.
Schwarz, B., 2019, Coherent wavefield subtraction for diffraction separation, Geophysics 84(3), V157-V168.
Schwarz, B. and Gajewski, D., 2017, Accessing the diffracted wavefield by coherent subtraction, Geophysical Journal International 211(1), 45-49.
Sheriff, R. and Geldart, L., 1995, Exploration Seismology, Camberidge University Press.
Taner, M. T. and Koehler, M., 1969, Velocity spectra-digital computer derivation applications of velocity functions, Geophysics 34(6), 859–881.
Taner, M. T., Fomel, S. and, Landa, E., 2006, Separation and imaging of seismic diffractions using plane-wave decomposition, SEG Technical Program Expanded Abstracts 25(1).
Trorey, A. W., 1970, A simple theory for seismic Diffraction, Geophysics 35(5), 762-784.
Trorey, A. W., 1977, Diffractions for arbitrary source-receiver locations, Geophysics 42(6), 1177-1182.
Zavalishin, B., 1982, Diffractions over deposit edges, Stanford Exploration Project report SEP-32, 125–136.
Zhao, j., Wang, Y. and, Yu, C., 2014, Diffraction imaging by uniform asymptotic theory and double exponential fitting, Geophysical Prospecting 63(2), 338-353.