1 عضو هیات علمی
2 دانش آموخته کارشناسی ارشد/دانشگاه شاهرود
عنوان مقاله [English]
The conventional approach to seismic data analysis consists of two main steps: estimating seismic velocities, (the subsurface macro-model), and seismic imaging, (mapping of the reflected seismic energy to the reflector positions). The aim and the major challenge in the seismic data analysis is the construction of the best undistorted image. This challenge would be more problematic when geometrical complexity and lateral heterogeneity increase. It is obvious that conventional reflection seismic data processing methods cannot solve the problem of seismic imaging in complex geological structures. It is because of that most of those processing methods are strongly depended on seismic velocity propagation model. However, obtaining a precise velocity model as accurate as possible is always a controversial task. For this purpose, imaging methods are employed that do not rely on the explicit knowledge of subsurface velocity model. Therefore, in most of the researches of new seismic imaging methods, efforts are oriented to develop velocity independent imaging algorithms. The first idea of velocity-independent time-domain seismic imaging belongs to authors considered decomposing seismic data into a range of local slopes. Then methods that consider inversion of full waveform from the data were introduced. However, these methods are not the ultimate solution, because we need the velocity model for final depth imaging. Thus some methods are introducing to use advantage of pre-stack migration with iterative velocity model updating while using seismic imaging methods that don’t fully rely on velocity model. These integration methods aims to combine new updating formula for the first part (estimating seismic velocities) of the processing chain and use new velocity independent methods for the second part (Seismic imaging).
Time migration is a common fast and robust process of obtaining seismic image. This process is considered adequate for the areas with mild lateral velocity variation. Moreover, time migration produces images in very specific time migration coordinates (x0; t0). However, even mild lateral velocity variations can significantly distort subsurface structures on the time migrated images. The main reason that this velocity variation will make distortion in the section is that reflected and diffracted energies will be placed in wrong positions. If this displacing could be slightly removed by any operator, e. g. Kirchhoff migration operator, in each offset section, another surface operator could be used to stack offset sections and enhance the final migrated section. In this study, we selected pre-stack time imaging with Kirchhoff migration algorithm method and the common reflection surface stack method for integration. Common reflection surface stack method is among velocity independent methods used for imaging in complex structures. The CRS operator will gathers any reflected and/or diffracted energy that could not be gathered by the conventional Kirchhoff summation operator. Thus if the geometrical distortions were corrected by the Kirchhoff operator and reflected energies were placed in their true locations, CRS operator will collects all the related diffracted energy from a depth point and will coherently stack these energies to image that point. The equation that comes in the following is the Kirchhoff operator:
that defines the wave-field parameter, ΔP in each (x, t) point. To integrate these two methods, the CRS operator would be created for each (x, t) point and will be inserted in the above equation. These equations are:
where the angles are the take-off and emergence angle of the central ray and Ki are wave-front curvatures. aCO and bCO are related to x and t, respectively. Diffraction curve would be obtained for each point and the CRS surface would be created for that point.
To investigate the efficiency of this method, the algorithm applied on a 2D seismic data. This data is from west of Iran which contains complex geometry with mild to strong lateral velocity change. After pre-processing steps, a smooth initial velocity model was derived for performing ray tracing. The kinematic ray tracing was used to define the common reflection surface operator. Afterwards, data were processed by Kirchhoff migration. In the next step, velocity model were corrected for residual move out. Finally pre-stack data was migrated again by the new corrected velocity model. This section should be compared with the result of PSTM and CRS integration method. The new migrated section could better shows faulting and bending of the reflectors. High thickness of Gachsaran formation in the region and strong lateral velocity change in different parts of the section, makes low illumination of the beneath Gachsaran structure. However, the new algorithm could gathers as much as possible reflected and/or diffracted energy from those structures in the data. Therefore, more clear structures and reflectors would be observed in the section and the general quality of the data would be enhanced. Finally, it could be concluded that by applying this proposed integration method will gives high quality image by increasing the signal to noise ratio and solving the problem of conflicting dips.