计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2013年
11期
115-118
,共4页
GPU%CUDA%逆时偏移%加速%地震资料
GPU%CUDA%逆時偏移%加速%地震資料
GPU%CUDA%역시편이%가속%지진자료
GPU%CUDA%reverse time migrations%acceleration%seismic data
叠前逆时偏移(RTM)方法是目前地震勘探领域最为精确的一种地震数据成像方法，其运用双程声波方程进行波场延拓，可实现对复杂构造介质的准确成像。文中采用互相关成像条件对震源波场与检波点波场在同时刻相关成像。针对RTM方法计算量大的问题，将图形处理器(GPU)引入到RTM计算中，充分挖掘GPU的众核结构优势，利用基于CUDA架构的并行加速算法取代传统CPU的串行运算，对逆时偏移算法中较为耗时的波场延拓和相关成像过程进行加速。复杂模型测试结果表明，在确保 RTM 成像精度的前提下，相比于传统 CPU 计算， GPU并行加速算法可大幅度地提高计算效率，进而实现基于GPU加速的叠前逆时偏移算法对复杂介质的高效率、高精度成像。
疊前逆時偏移(RTM)方法是目前地震勘探領域最為精確的一種地震數據成像方法，其運用雙程聲波方程進行波場延拓，可實現對複雜構造介質的準確成像。文中採用互相關成像條件對震源波場與檢波點波場在同時刻相關成像。針對RTM方法計算量大的問題，將圖形處理器(GPU)引入到RTM計算中，充分挖掘GPU的衆覈結構優勢，利用基于CUDA架構的併行加速算法取代傳統CPU的串行運算，對逆時偏移算法中較為耗時的波場延拓和相關成像過程進行加速。複雜模型測試結果錶明，在確保 RTM 成像精度的前提下，相比于傳統 CPU 計算， GPU併行加速算法可大幅度地提高計算效率，進而實現基于GPU加速的疊前逆時偏移算法對複雜介質的高效率、高精度成像。
첩전역시편이(RTM)방법시목전지진감탐영역최위정학적일충지진수거성상방법，기운용쌍정성파방정진행파장연탁，가실현대복잡구조개질적준학성상。문중채용호상관성상조건대진원파장여검파점파장재동시각상관성상。침대RTM방법계산량대적문제，장도형처리기(GPU)인입도RTM계산중，충분알굴GPU적음핵결구우세，이용기우CUDA가구적병행가속산법취대전통CPU적천행운산，대역시편이산법중교위모시적파장연탁화상관성상과정진행가속。복잡모형측시결과표명，재학보 RTM 성상정도적전제하，상비우전통 CPU 계산， GPU병행가속산법가대폭도지제고계산효솔，진이실현기우GPU가속적첩전역시편이산법대복잡개질적고효솔、고정도성상。
Currently,prestack reverse-time migration is the most accurate imaging method for seismic data in seismic prospecting domain. It extrapolating the wave field with the two-way acoustic wave equation, and it can image complex geological structure accurately. The cross-correlation imaging condition is used for the imaging of source wavefield and receiver wavefield at the same time in the paper. For computationally intensive problems of RTM,we introduce the graphics processing unit (GPU) into RTM algorithm, and exploit the multicore advantages of GPU. In this paper,we use the parallel acceleration algorithm base on the CUDA architecture to replace the serial computation on the traditional CPU and accelerate the process of the wavefield extrapolation and cross-correlation imaging in reverse time migration. The test on complex modeling show that we can achieve imaging result for complex medium with high efficiency and precision by pre-stack reverse time migration algorithm base on GPU acceleration. Under the premise of ensuring the calculation accuracy of the RTM, comparing with the traditional CPU calculation,GPU parallel acceleration algorithm can improve the computational efficiency greatly.
