This work presents an alternative computing platform, Field Programmable Gate Arrays (FPGAs), for one of the widely used applications in the oil and gas industry; seismic imaging using reverse time migration (RTM). As with many of the oil and gas applications, RTM involves many computations performed repeatedly over extremely large number of data points. Conventionally, such computations were implemented as a sequence of temoral steps and parallelized using multi-core CPUs or GPUs at various levels of abstractions (task, thread, and instruction-levels). With FPGAs, computations can be parallelized and implemented as spatially separated steps (i.e. the computing fabric can be configured to carry out all the computations, side-bu-side rather than as temoral steps). In this work, we illustrate the spatial computing capabilities of FPGAs using RTM. Two different implementations with different types of optimizations were developed. Performance optimizations and measurements based on experimental test bed are reported.
|Title of host publication||Society of Petroleum Engineers - Middle East Oil, Gas and Geosciences Show, MEOS 2023|
|Publisher||Society of Petroleum Engineers (SPE)|
|State||Published - 2023|
|Event||2023 Middle East Oil, Gas and Geosciences Show, MEOS 2023 - Manama, Bahrain|
Duration: 19 Feb 2023 → 21 Feb 2023
|Name||SPE Middle East Oil and Gas Show and Conference, MEOS, Proceedings|
|Conference||2023 Middle East Oil, Gas and Geosciences Show, MEOS 2023|
|Period||19/02/23 → 21/02/23|
Bibliographical noteFunding Information:
This work has been supported through a research contract from Saudi Aramco. Authors also acknowledge King Fahd University of Petroleum and Minerals facility support.
Copyright © 2023, Society of Petroleum Engineers.
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Fuel Technology