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Clark G.,Acceleware Corporation
2nd EAGE Workshop on High Performance Computing for Upstream | Year: 2015

Full waveform inversion (FWI) is an increasingly popular algorithm for automatically improving earth models in seismic exploration. The method is incredibly computationally expensive because the earth model is built up with many iterations of forward modelling and reverse time migration (RTM). Current research is helping to reduce the number of iterations and improve the robustness of convergence, but the prohibitive cost of FWI makes running real world datasets impractical for many researchers. Furthermore, information regarding the geological region can be used to accelerate convergence. Therefore, an FWI implementation must be both high performance, and flexible. This commercial case study outlines our approach to minimizing the cost of a flexible implementation. The key feature of our approach is that we divide the algorithm into low cost and high cost steps. Fortunately, the low cost steps in the FWI algorithm are also the ones subject to the most research. The extremely high cost full wave modelling steps are comparatively consistent between variations of the FWI algorithm. Therefore, the full wave modelling is hardware optimized and all other steps can be quickly rewritten in Python. Copyright © 2015 by the European Association of Geoscientists & Engineers (EAGE) All rights reserved.


Trademark
Acceleware Corporation | Date: 2009-01-06

Computer software, namely, software computational engines, algorithm accelerators, software platforms, computational kernels, computer software constituting a component of or a library in computer aided engineering or computer aided design software for use in the electromagnetic, biomedical, bioinformatics, energy, industrial and military industries; computer peripheral devices, computer hardware, namely, DSP boards, accelerator boards, supercomputers, computer work stations comprising graphics processing units and/or accelerator boards; special purpose processors, multi-core processors. Consulting services for computer software and hardware; consulting services in the field of information technology and integration of computer software and computer hardware components; updating and maintenance of computer software; computer programming; computer system analysis; custom software development.


Pasalic D.,Acceleware Corporation | Vaca P.,Acceleware Corporation | Okoniewski M.,University of Calgary
Proceedings - 2014 International Conference on Electromagnetics in Advanced Applications, ICEAA 2014 | Year: 2014

An algorithm for rigorous analysis of electromagnetic (EM) heating of heavy oil reservoirs is presented in the paper. The algorithm combines an FDTD-based EM solver with a reservoir simulator, utilizing the fact that the two simulators operate at completely different time scales. The two simulators also utilize different grids. Special attention needs to be taken when interpolating the values between the two grids to avoid occurrence of non-physical effects. An example of a vertical 50-m long dipole antenna heating a heavy oil reservoir in northern Alberta, Canada is presented. © 2014 IEEE.


Qin Y.,Acceleware Corporation | Okoniewski M.,Acceleware Corporation
76th European Association of Geoscientists and Engineers Conference and Exhibition 2014: Experience the Energy - Incorporating SPE EUROPEC 2014 | Year: 2014

Reverse-Time Migration (RTM) is routinely used for depth velocity model building and imaging in deepwater exploration around the world. In this study, we employed analytical redatuming to improve the efficiency of true-amplitude RTM for deepwater Earth model. This method analytically redatums both the source and receiver wavefields from surface to water bottom and injects the redatumed wavefield into the computational domain while preserving true-amplitude in the migrated common-shot image. By using analytic redatuming in deepwater area, the total runtime, memory and disk space requirements are significantly reduced. In addition, the image quality is improved by overcoming the singularity of pointsource injection in the finite difference method, accurate positioning of source and receivers, and the reduction of numerical dispersion noise. The underlying theories developed in this paper can be extended to some other important applications such as Full-Waveform Inversion (FWI), true-amplitude layerstripping RTM/FWI.


Lemieux J.-F.,McGill University | Tremblay B.,McGill University | Sedlacek J.,ETH Zurich | Tupper P.,Simon Fraser University | And 3 more authors.
Journal of Computational Physics | Year: 2010

We have implemented the Jacobian-free Newton-Krylov (JFNK) method to solve the sea ice momentum equation with a viscous-plastic (VP) formulation. The JFNK method has many advantages: the system matrix (the Jacobian) does not need to be formed and stored, the method is parallelizable and the convergence can be nearly quadratic in the vicinity of the solution. The convergence rate of our JFNK implementation is characterized by two phases: an initial phase with slow convergence and a fast phase for which the residual norm decreases significantly from one Newton iteration to the next. Because of this fast phase, the computational gain of the JFNK method over the standard solver used in existing VP models increases with the required drop in the residual norm (termination criterion). The JFNK method is between 3 and 6.6 times faster (depending on the spatial resolution and termination criterion) than the standard solver using a preconditioned generalized minimum residual method. Resolutions tested in this study are 80, 40, 20 and 10 km. For a large required drop in the residual norm, both JFNK and standard solvers sometimes do not converge. The failure rate for both solvers increases as the grid is refined but stays relatively small (less than 2.3% of failures). With increasing spatial resolution, the velocity gradients (sea ice deformations) get more and more important. Nonlinear solvers such as the JFNK method tend to have difficulties when there are such sharp structures in the solution. This lack of robustness of both solvers is however a debatable problem as it mostly occurs for large required drops in the residual norm. Furthermore, when it occurs, it usually affects only a few grid cells, i.e., the residual is small for all the velocity components except in very localized regions. Globalization approaches for the JFNK solver, such as the line search method, have not yet proven to be successful. Further investigation is needed. © 2009 Elsevier Inc. All rights reserved.

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