Fast Seismic Modeling and Reverse Time Migration on a GPU Cluster

Best Paper Award at HPCS'09International audienceWe have designed a fast parallel simulator that solves the acoustic wave equation on a GPU cluster. Solving the acoustic wave equation in an oil exploration industrial context aims at speeding up seismic modeling and Reverse Time Migration. We consider a finite difference approach on a regular mesh, in both 2D and 3D cases. The acoustic wave equation is solved in either a constant density or a variable density domain. All the computations are done in single precision, since double precision is not required in our context. We use CUDA to take advantage of the GPUs computational power. We study different implementations and their impact on the application performance. We obtain a speed up of 10 for Reverse Time Migration and up to 30 for the modeling application over a sequential code running on general purpose CPU

FDTD Based Seismic Modeling and Reverse Time Migration on a GPU Cluster

International audienceWe have designed a fast parallel simulator that solves the acoustic wave equation on a GPU cluster. Solving the acoustic wave equation in an oil exploration industrial context aims at speeding up seismic modeling and Reverse Time Migration. We use a finite difference approach on a regular mesh, in both 2D and 3D cases. The acoustic wave equation is solved in either a constant density or a variable density domain. We use CUDA to take advantage of the GPUs computational power. We study different implementations and their impact on the application performance. We obtain a speedup of 11 for Reverse Time Migration and up to 30 for the modeling application over a sequential code running on general purpose CPU

Anelastic sensitivity kernels with parsimonious storage for adjoint tomography and full waveform inversion

We introduce a technique to compute exact anelastic sensitivity kernels in the time domain using parsimonious disk storage. The method is based on a reordering of the time loop of time-domain forward/adjoint wave propagation solvers combined with the use of a memory buffer. It avoids instabilities that occur when time-reversing dissipative wave propagation simulations. The total number of required time steps is unchanged compared to usual acoustic or elastic approaches. The cost is reduced by a factor of 4/3 compared to the case in which anelasticity is partially accounted for by accommodating the effects of physical dispersion. We validate our technique by performing a test in which we compare the $K_\alpha$ sensitivity kernel to the exact kernel obtained by saving the entire forward calculation. This benchmark confirms that our approach is also exact. We illustrate the importance of including full attenuation in the calculation of sensitivity kernels by showing significant differences with physical-dispersion-only kernels

Analysis of GPU-based convolution for acoustic wave propagation modeling with finite differences: Fortran to CUDA-C step-by-step

textBy projecting observed microseismic data backward in time to when fracturing occurred, it is possible to locate the fracture events in space, assuming a correct velocity model. In order to achieve this task in near real-time, a robust computational system to handle backward propagation, or Reverse Time Migration (RTM), is required. We can then test many different velocity models for each run of the RTM. We investigate the use of a Graphics Processing Unit (GPU) based system using Compute Unified Device Architecture for C (CUDA-C) as the programming language. Our preliminary results show a large improvement in run-time over conventional programming methods based on conventional Central Processing Unit (CPU) computing with Fortran. Considerable room for improvement still remains.Geological Science

Fast and High Accurate Algorithm and Its Implementation for Acoustic waves and Elastic Waves in Reverse Time Migration

逆时偏移技术（Reversetimemigration，RTM）主要应用于解决地震成像问题，是现行偏移方法中最精确的一种。逆时偏移成像的优势在于其成像过程是基于数值方法求解双程波动方程，不仅没有角度限制，还充分考虑了回转波、棱柱波、多次反射等复杂传播路径，因此能够在高倾角、速度变化剧烈的复杂地下结构中得到高质量的图像。逆时偏移成像质量优于基于射线理论的Kirchhoff偏移或基于单程波动方程的其他偏移方法，然而求解双程波动方程计算量大、计算需要的存储资源多，导致逆时偏移成像计算成本较高，这在一定程度上限制了其在工业应用中的推广。 缓解计算瓶颈可以从两个方面入手：一方面使用快速、高精度算法求解...Reverse time migration (RTM) is a high-efficiency tools for seismic imaging. RTM has been considered to be one of the most accurate seismic pre-stack depth migration methods, especially for imaging geologically complex structures. RTM calculates the two-way wave equations numerically. It has no angle limit, and has considered complex propagating paths, such as turning, prismatic and multiple refle...学位：理学博士院系专业：物理科学与技术学院_无线电物理学号：1982011015405

Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft