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منظم‌سازی داده‌های نامنظم لرزه‌ای چند‌بُعدی با استفاده از تبدیل فوریه سریع با فواصل نامساوی | ||
| فیزیک زمین و فضا | ||
| مقاله 5، دوره 50، شماره 3، مهر 1403، صفحه 617-635 اصل مقاله (2.09 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2024.372021.1007591 | ||
| نویسندگان | ||
| حجت حق‌شناس لاری* 1؛ عباس زارعی2؛ مصطفی عباسی2؛ یوسف حسن‌پور مطلق2؛ حامد سعادت نیا2 | ||
| 1گروه ژئوفیزیک، دانشکده علوم زمین، دانشگاه تحصیلات تکمیلی علوم پایه زنجان، زنجان، ایران. | ||
| 2مدیریت اکتشاف نفت، شرکت ملی نفت ایران، تهران، ایران. | ||
| چکیده | ||
| یکی از روش‌های نوین عملیات لرزه‌نگاری روش لرزه‌نگاری نامنظم است. در این روش به‌منظور کاهش هزینه‌های لرزه‌نگاری، تعداد نقاط چشمه و گیرنده از تعداد نقاطی که توسط قانون نایکوئست تعیین می‌شود کمتر است و داده‌ها در مکان به‌صورت تصادفی و نامنظم نمونه‌برداری می‌شوند. از این رو نیاز است تا داده‌های نامنظمِ برداشت‌شده را قبل از انجام پردازشِ مرسوم، به داده‌های منظم تبدیل کرد. برای منظم‌سازی این‌گونه داده‌ها از روش نمونه‌برداری فشرده استفاده می‌شود. در روش‌های مرسوم نمونه‌برداری فشرده داده‌ها باید بر روی یک شبکه منظم، تصادفی برداشت شوند. اما در واقعیت نمی‌توان داده‌های لرزه‌ای را به‌علت وجود موانع بر روی یک شبکه منظم برداشت کرد و این مسئله چالش بزرگی برای مراحل پردازش به حساب می‌آید. از این‌رو، در این مقاله دستورالعملی برای برداشت داده‌های لرزه‌نگاری به‌صورت نامنظم و تصادفی معرفی شده است. در این روش لازم نیست داده‌ها بر روی یک شبکه با فواصل یکسان برداشت شوند. به‌علاوه، روشی نیز برای بازیابی این داده‌ها معرفی شده است که از تبدیل فوریه سریع با فواصل نامساوی به‌عنوان یک تبدیل تُنک‌کننده استفاده می‌کند. از این روش می‌توان علاوه‌بر منظم‌سازی داده‌های تصادفی، در منظم‌سازی داده‌هایی که به‌علت وجود موانع، برخی از ردلرزه‌های آنها جابه‌جا یا حذف شده‌اند نیز استفاده کرد. نتایج آزمایش روش بر روی داده‌های لرزه‌ای مصنوعی و واقعی توانایی روش معرفی‌شده را در منظم‌سازی و درون‌یابی داده‌های لرزه‌نگاری که بر روی یک شبکه نامنظم با فواصل نامساوی که به‌صورت تصادفی برداشت شده‌اند را نمایش می‌دهند. | ||
| کلیدواژه‌ها | ||
| نمونه‌برداری فشرده؛ تبدیل فوریه سریع با فواصل نامساوی؛ لرزه‌نگاری نامنظم | ||
| عنوان مقاله [English] | ||
| Jittered Multidimension Seismic Data Regularization Using Non-uniquespace Fast Fourier Transform | ||
| نویسندگان [English] | ||
| Hojjat Haghshenas Lari1؛ Abbas Zarei2؛ Mostafa Abbasi2؛ Yousef Hassanpour Motlagh2؛ Hamed Saadatnia2 | ||
| 1Department of Geophysics, Faculty of Earcth Sciences, Institute for advanced studies in basic sciences, Zanjan, Iran. | ||
| 2Exploration Directorate, National Iranian Oil Company (NIOC), Tehran, Iran. | ||
| چکیده [English] | ||
| Seismic data jitter sampling is one of the new seismic data acquisition methods developed recently to reduce seismic data acquisition costs. In this method, the number of seismic sources and receivers is less than the number determined by the Nyquist-Shannon Theorem. The Nyquist-Shannon theorem states that the sampling rate of a digital signal must be more than twice the bandwidth of the signal to avoid aliasing. To circumvent aliasing, the jitter sampling method uses compressed sensing technique. This technique is based on the principle that the sparsity of a signal can be used to recover it from fewer samples than required by the Nyquist–Shannon sampling theorem in two conditions. First, the signal needs to be sparse in some domains, like the frequency domain. Second, the signal must be randomly sampled in the main domain, like the time or space domain. In this type of data sampling method, the randomness of sampling appears as a white noise in the transform domain. Therefore, it can be said that the compressed sensing method plays the role of a denoising technique in the transformation domain. In conventional compressed sensing methods, it is assumed that the data is undersampled on a regular grid. Fourier transform, Curvelet transform, and wavelet transform are some of the transforms that are used in these types of compressed sensing methods. On the other hand, sometimes in real seismic data acquisition, the shots and receivers cannot have a regular geometry due to the natural and civil obstacles. Therefore, sampling on a regular grid is not always possible in seismic data acquisition. This means that using the conventional compressed sensing method for seismic data regularization doesn’t seem to be an appropriate choice. To address this issue, some geophysicists have proposed to use discrete Fourier transform as the data transformation technique in compressed sensing. Discrete Fourier transform does not require sampling on a uniquespace grid. However, this transform is slow and needs a huge number of computations. In this paper, we used the non-uniquespace fast Fourier transform instead of the discrete Fourier transform. The method doesn’t need a sampling scheme on a regular grid and is much faster than discrete Fourier transform. This method is based on the conventional fast Fourier transform and an interpolation technique. The method can be applied on multidimensional pre-stack seismic data. Therefore, it can consider correlation between traces in different dimensions while interpolating the lost traces. On the other hand, a problem with fully random sampling is that there is no control over the locations of the samples on a signal. This means that, if a signal is sampled randomly, some parts of the signal may be oversampled while the other parts may not be sampled with enough points. This phenomenon may have a bad impact on the regularized result if the signal changes erratically. To avoid this situation, in this paper, a sampling protocol will be introduced to improve the control over random sampling. In this protocol, the samples are picked randomly in small windows over the length of the signal. In this sampling technique, the size of the windows and the number of random samples can be controlled easily. Moreover, the sampling scheme doesn’t need to be on a regular grid and the samples can be chosen anywhere along the signal. A set of 2D and 3D synthetic and 2D real seismic data were used to examine the performance of the proposed method. The results show that the method can regularize irregular seismic data properly. | ||
| کلیدواژه‌ها [English] | ||
| Compressed sensing, Non-usniquespace Discrete Fourier Transform, Jitter Sampling Seismic Data Acquisition | ||
| مراجع | ||
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