Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:


insideHPC Guide to HPC/AI for Energy

In this technology guide sponsored by our friends over at Dell Technologies, we take a deep dive into how the team of Dell Technologies and AMD is working to provide solutions for a wide array of needs for more strategic cultivation of oil and gas energy reserves. We’ll start with a series of compelling use-case examples, and then introduce a number of important pain-points solved with HPC and AI. We’ll continue with some specific solutions for the energy industry by Dell and AMD. Then we’ll take a look at a case study examining how geophysical services and equipment company CGG successfully deployed HPC technology for competitive advantage. Finally, we’ll leave you with a short-list of valuable resources available from Dell to help guide you along the path with HPC and AI.

This technology guide, insideHPC Guide to HPC/AI for Energy, explores how the dynamic confluence of HPC and AI is now considered essential to any organization involved in energy exploration and the process of bringing the resulting energy resources to market.

HPC/AI for Energy – An Overview

Advanced new hardware and software technologies like High Performance Computing (HPC) and Artificial Intelligence (AI) continue to enable the discovery and understanding of the location of energy deposits with  more precision than ever before.

Finding new oil and natural gas deposits requires a significant investment in a broad array of capital equipment, from exploration platforms to the computer systems that analyze the raw data and give engineers information on where to drill with increasing accuracy. Important tools to achieve these goals, AI-powered software and HPC hardware designed to drive the training and inference tasks for the algorithms,  assist engineers in making sense of the inordinate amounts of data collected in the field.

With 5.3 million barrels of oil typically pumped every day of the year, Texas ranks only behind Russia and Saudi Arabia in production. One driver for this level of output is advanced technology such as HPC/AI to  model oil resources and guide drilling activities. HPC system architecture has evolved dramatically over the  past two decades, from massive supercomputers to clusters of industry standard servers to heterogeneous  nodes incorporating CPUs and GPUs. These new architectures have provided an incredible increase in  performance while enabling new application areas beyond traditional HPC, most notably big data analytics,  machine learning, deep learning, and AI.

HPC systems have been used for many years to understand much of the seismic data acquired from sensitive  sonar equipment. Obtaining more accurate information from within the ground leads to a more focused  drilling plan, which reduces costs as well as minimizes environmental effects. While HPC systems could always be expanded to include more and faster processors, this could become prohibitively expensive over time.  New techniques using innovative hardware systems, such as simultaneously using thousands of GPUs, along with state-of-the-art software, allows companies to confidently find new reserves, as well as maximize the  efficiency of existing oil fields. A reduction in cost at the start of the workflow process can lead to significant  savings downstream. According to the U.S. Department of Transportation, a seismic survey costs about  $30,000 per square mile, while the cost for an offshore oil well can approach $1 billion.

In this technology guide, we take a deep dive into how the team of Dell Technologies and AMD is working to provide solutions for a wide array of the above described needs for more strategic cultivation of oil and gas  energy reserves. We’ll start with a series of compelling use-case examples, and then introduce a number of  important pain-points solved with HPC and AI. We’ll continue with some specific solutions for the energy  industry by Dell and AMD. Then we’ll take a look at a case study examining how geophysical services and  equipment company CGG successfully deployed HPC technology for competitive advantage. Finally, we’ll  leave you with a short-list of valuable resources available from Dell to help guide you along the path with HPC and AI.

Over the next few weeks we will explore how with the accelerated use of HPC and AI in the energy industry,  there are strategic options for laying a directed path for these technologies to become a strong competitive advantage. Dell Technologies and AMD is a team that can help you travel down this path:

  • HPC/AI for Energy – An Overview
  • Use Cases: HPC/AI for Energy
  • Energy Industry Pain-Points Solved by HPC/AI
  • HPC/AI Technology for Energy
  • Case Study: CGG, Next Steps with Dell Technologies Solutions for the Energy Industry, Summary

Download the complete insideHPC Guide to HPC/AI for Energy, courtesy of Dell.

Leave a Comment

*

Resource Links: