SambaNova Systems, the company delivering the industry’s only comprehensive software, hardware, and solutions platform to run Artificial Intelligence (AI), deep learning, and Foundation Model workloads, today announces new seismic analysis capabilities for oil and gas discovery. Seismic analysis, a common process used to identify oil and gas deposits, can successfully identify deposits that represent billions of dollars in potential profit for oil, gas, and energy producers.
“Deep learning computer vision models improve and accelerate the analysis of seismic data by capturing high dimensional information that uncover the resource patterns that experts need to identify,” said Rodrigo Liang, CEO and co-founder, SambaNova Systems. “These patterns enable more accurate discovery predictions while simultaneously speeding up the seismic analysis process to as little as one week.”
Correctly predicting the location of oil and gas accumulations is time-consuming and complex, involving highly- trained specialists who need to analyze hundreds of km3of geospatial image data. The accuracy of the predictions is critical, as an incorrect prediction could represent billions in missed opportunities and a wasted capital investment of $100M or more.
Marshall Choy, SVP Product at SambaNova Systems states: “The hardware available today was not designed to handle complex AI workloads and the size requirements of global oil and gas companies. SambaNova provides an integrated AI hardware, software and services offering that can handle the largest 3D networks that users want for geologic study and exploration.”
Benefits of SambaNova’s DataScale for Oil and Gas:
- SambaNova’s computer vision models improve and accelerate seismic analysis The amount of specialized labeled data available necessary to train seismic analysis computer vision models is limited. The labeling process is complex and requires experts who can recognize and label the 3D features critical to seismic analysis and prediction. Most organizations do not have the necessary data needed to train the computer vision models for the seismic analysis process. SambaNova accelerates the training of computer vision models SambaNova accelerates the time-consuming model training process by reducing the labeled data required to train a model by 97.6%, while simultaneously resulting in more detailed 3D features that improve the accuracy of the analysis.
- The limitations of GPU-based AI infrastructure are avoided GPU-based AI infrastructures are not able to analyze high resolution 3D images, which impacts accuracy. SambaNova’s large 3D networks overcome limitations by leveraging multi-scale, 3D correlations that identify the most relevant features in the data to improve the quality of the predictions. “This is a pivotal time for the oil and gas sector, with uncertainties about energy sources, public demand and business models,” stated Liang. “To manage project costs, it is critical to leverage Foundation Models and LLMs to reduce cycle time. SambaNova has demonstrated the ability to rapidly generate training data examples faster and with the highest accuracy, resulting in reduced project costs and more accurate analysis.”
