MapReduce Implementation of Prestack Kirchhoff Time Migration (PKTM) on Seismic Data

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Babaii Rizvandi, Nikzad; Boloori, Ali Javadzadeh; Kamyabpour, Najmeh; Zomaya, Albert

Babaii Rizvandi, Nikzad; Boloori, Ali Javadzadeh; Kamyabpour, Najmeh; Zomaya, Albert


2011-09-23


Conference Material


The 12th International Conference on Parallel and Distributed Computing, Applications and Technologies


Gwangju, South Korea


200-206


The oil and gas industries have been great consumers of parallel and distributed computing systems, by frequently running technical applications with intensive processing of terabytes of data. By the appearance of cloud computing which gives the opportunity to hire high-throughput computing resources with lower operational costs, such industries have started to adopt their technical applications to be executed on such high-performance commodity systems. In this paper, we first give an overview of forward/inverse Prestack Kirchhoff Time Migration (PKTM) algorithm, as one of the well-known seismic imaging algorithms. We then explain our proposed approach to fit this algorithm for running on Google MapReduce framework. Toward the end, we will analyse the relation between MapReduce-based PKTM completion time and the number of mappers/reducers on pseudo-distributed MapReduce mode.


Mapreduce, parallel/distributed computing, Prestack Kirchhoff Time Migration (PKTM)


www.ftrai.org/pdcat2011/


nicta:4979


Babaii Rizvandi, Nikzad; Boloori, Ali Javadzadeh; Kamyabpour, Najmeh; Zomaya, Albert. MapReduce Implementation of Prestack Kirchhoff Time Migration (PKTM) on Seismic Data. In: The 12th International Conference on Parallel and Distributed Computing, Applications and Technologies; Gwangju, South Korea. 2011-09-23. 200-206.



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