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Li B.,CAS Institute of Geology and Geophysics | Liu H.-W.,CAS Institute of Geology and Geophysics | Liu G.-F.,CAS Institute of Geology and Geophysics | Tong X.-L.,Beijing Geostar Science and Technology Co. | And 3 more authors.
Chinese Journal of Geophysics (Acta Geophysica Sinica) | Year: 2010

Comparing with one-way wave migration algorithm, reverse time migration (RTM) is more attractive because of the theory advantages. Two-way wave equation has been used to extrapolate wave field in RTM, instead of separating the up going wave and down going wave. However, due to the large amount of computation and I/O, RTM is most time-consuming in industrial applications. In this article, we analyze several computational strategies and propose our method, which uses CPU/GPU as computational core and builds random velocity boundary, for solving I/O problem and computational efficiency problem. In the actual test, it has been proved that this method can largely decrease storage memory units and improve computational efficiency. Source


Liu H.-W.,CAS Institute of Geology and Geophysics | Liu H.,CAS Institute of Geology and Geophysics | Tong X.-L.,Beijing Geostar Science and Technology Co. | Liu Q.,Beijing Geostar Science and Technology Co.
Computers and Geosciences | Year: 2012

Pre-stack one-way wave equation (OWE) is a useful tool for seismic imaging and modeling. Since the idea of OWE appeared in the 1970s, geophysicists have made great effort to improve the accuracy of the one-way wave equation extrapolators. In this paper, we present the idea of solving OWE using the Fourier integral method, which represents OWE as a Fourier integral equation and solves it in dual spaces (both space and wave-number domains). By doing this, we can propagate wave-fields up to nearly 90° angle from the vertical direction in the presence of lateral velocity variations. The proposed method is stable, does not suffer from the numerical dispersion, and overcomes the azimuthal anisotropy problem when extended to three dimensions. The computation cost of the Fourier integral method is too high and was considered impractical for a conventional computer. In this paper, we take advantages of the Graphic Processing Unit (GPU) and use the matrix multiplication technique to accelerate the algorithm. The speedup ratio we obtained is tens of hundreds times so that the method can be applied to a real project for pre-stack depth imaging. © 2011 . Source


Liu H.,CAS Institute of Geology and Geophysics | Li B.,CAS Institute of Geology and Geophysics | Tong X.,Beijing Geostar Science and Technology Co. | Liu Q.,Beijing Geostar Science and Technology Co. | And 2 more authors.
Geophysical Prospecting | Year: 2012

Prestack reverse time migration (RTM) is a very useful tool for seismic imaging but has mainly three bottlenecks: highly intensive computation cost, low-frequency band imaging noise and massive memory demand. Traditionally, PC-clusters with thousands of computation nodes are used to perform RTM but it is too expensive for small companies and oilfields. In this article, we use Graphic Processing Unit (GPU) architecture, which is cheaper and faster to implement RTM and we obtain an order of magnitude higher speedup ratio to solve the problem of intensive computation cost. Aiming at the massive memory demand, we adopt the pseudo random boundary condition that sacrifices the computation cost but reduces the memory demand. For rugged topography RTM, it is difficult to deal with the rugged free boundary condition with the finite difference method. We employ a simplified boundary condition that avoids the abundant logical judgment to make the GPU implementation possible and does not induce any sacrifice on efficiency. Besides, we have also done some tests on multi-GPU implementation for wide azimuth geometries using the latest GPU cards and drivers. Finally, we discuss the challenges of anisotropy RTM and GPU solutions. All the jobs stated above are based on GPU and the synthetic data examples will show the efficiency of the algorithm and solutions. © 2012 European Association of Geoscientists & Engineers. Source


Liu H.W.,Chinese Academy of Sciences | Li B.,Chinese Academy of Sciences | Liu H.,Chinese Academy of Sciences | Tong X.L.,Beijing Geostar Science and Technology Co. | Liu Q.,Beijing Geostar Science and Technology Co.
73rd European Association of Geoscientists and Engineers Conference and Exhibition 2011: Unconventional Resources and the Role of Technology. Incorporating SPE EUROPEC 2011 | Year: 2011

Pre-stack reverse time migration (RTM) is a very useful tool for seismic imaging. But it has not been widely used because of the highly intensive computation cost, imaging noise and massy memory demand. In this paper, we illustrate the implementation process of RTM and analyze the stability condition and dispersion relation of finite difference (FD) method. For the problem of intensive computation cost, we use the Graphic Processing Unit (GPU) architecture to realize RTM and get an order of magnitude higher speedup ratio compared to the traditional CPU architecture. Compared to the one way wave equation migration methods, RTM does not have the imaging dip limit and the imaging effect is significantly improved. We use the random boundary condition method to realize RTM using GPU/CPU collaborative computation which avoids the communication between GPU and CPU and the additional amount of computation could be partially remedied by reducing the communication cost. Source


Liu H.-W.,CAS Institute of Geology and Geophysics | Liu H.,CAS Institute of Geology and Geophysics | Li B.,CAS Institute of Geology and Geophysics | Wang X.,Sinopec | And 2 more authors.
Chinese Journal of Geophysics (Acta Geophysica Sinica) | Year: 2011

Pre-stack reverse time migration (RTM) for rugged topography is a very useful tool for seismic imaging in the areas with rugged surface topography andcomplex subsurface structures. In this paper, we illustrate the implementation process of RTM for rugged topography. For the difficulty in dealing with the rugged free boundary condition with the finite difference method, we employ a simplified boundary condition which can avoid the abundant logical judgment. On this basis, we use the Graphic Processing Unit (GPU) algorithm to accelerate RTM and get an order of magnitude higher speedup ratio compared to the traditional CPU algoritm. The tests on synthetic data and the comparison with the pre-stack one-way wave method for rugged topography prove that RTM does not have the imaging dip limit, and the imaging results for near surface structures and subsurface steep structures are significantly improved. The problems of imaging noise removal and massy memory demand of RTM have been stated previously and will not be discussed in this paper. Source

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