The demand for NVIDIA’s NVDA graphic processing units (GPUs) has surged significantly, positioning it as a leading player in the artificial intelligence (AI) revolution and one of the world’s most valuable companies. NVIDIA’s GPU-accelerated computing is transforming various industries, including oil and gas, by expediting complex calculations and enhancing data analysis. This technology improves seismic imaging, reservoir simulations and real-time data analysis, all of which are essential for locating oil and gas reserves more quickly and accurately.
Energy giants like Shell plc SHEL, SLB SLB and Petrobras PBR are well-positioned to benefit from this trend, as they already leverage NVIDIA GPUs to conduct complex simulations and boost productivity. This adoption is driving more efficient and sustainable operations in the sector.
NVIDIA’s GPUs in Seismic Imaging and Reservoir Simulation
NVIDIA’s GPUs provide substantial benefits to oil and gas companies by significantly improving the speed and precision of their operations, especially upstream activities. A major advantage is seen in seismic imaging, where the parallel computing capabilities of GPUs greatly accelerate data processing. This enables companies to produce detailed subsurface images much faster than traditional CPU-based systems. The quicker imaging allows for faster identification of potential reservoirs, which enhances exploration decisions and helps reduce both the time and cost involved in locating oil and gas deposits.
NVIDIA’s GPUs also optimize reservoir simulations and real-time data analysis. Reservoir simulations, which model the movement of oil and gas within underground formations, are computationally intensive and typically slow. By leveraging GPUs, companies can run more accurate models in real time, enabling quicker, data-driven decisions and optimized extraction processes. Additionally, real-time data analysis powered by GPUs allows continuous monitoring of operations, predicting equipment failures and improving overall operational efficiency, reducing costs and mitigating risks.
3 Energy Stocks to Watch: SHEL, SLB, PBR
Shell: Accelerating Upstream Activities With NVIDIA AI
Shell’s utilization of NVIDIA DGX A100 systems, based on NVIDIA A100 Tensor Core GPUs, for seismic processing enhances its capability to create more precise reservoir models by enabling iterative image reconstructions. This technology allows Shell to more effectively map subsurface structures, identifying critical features such as salt boundaries that impact hydrocarbon flow.
By harnessing these advanced tools, Shell not only increases the efficiency of locating and managing oil reserves but also accelerates data-driven decision-making that aligns with its sustainability goals. For instance, more accurate models help reduce unnecessary drilling, leading to cost savings and a minimized environmental footprint.
Petrobras: Identifying New Reserves While Employing GPUs
The #3 Ranked Petrobras has integrated NVIDIA’s Tesla GPUs, particularly the Tesla K10 model, into its operations to boost seismic data processing capabilities. This integration allows Petrobras to handle complex computational tasks more efficiently, including reverse time migration, full waveform inversion, and Kirchhoff time/depth migration.
These sophisticated algorithms enhance the precision of seismic imaging, enabling Petrobras to more accurately identify new oil and gas reserves. Paulo Souza, a developer in the Geophysical Technology Group at Petrobras RTM, noted that their seismic application runs 1.8 times faster on the Tesla K10 compared to the Tesla M2090 GPU, greatly accelerating the process of discovering and safely accessing new reserves.
NVIDIA A100’s MIG Feature Lets SLB Run Multiple Simulations
SLB, with a Zacks Rank of 3, has experienced significant benefits from using NVIDIA’s A100 80GB Tensor Core GPUs with its INTERSECT high-resolution reservoir simulator. Compared to traditional CPU-based systems, these GPUs provide substantial performance improvements.
The Multi-Instance GPU feature of NVIDIA’s A100 allows SLB to run multiple simulations concurrently, boosting throughput by up to 7.5x for larger models (2.3 million cells) and up to 11x for smaller models (575,000 cells). This results in considerable time savings, enabling SLB to perform up to 1,571 daily simulations instead of just 143 with CPUs. Using NVIDIA’s GPUs enhances computational performance and significantly improves operational efficiency and cost-effectiveness.
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Source: nasdaq.com