Italy-based energy major Eni and US-based Stone Ridge Technology (SRT) have entered into a cooperative agreement designed to advance and accelerate the development of ECHELON, SRT’s pioneering high-performance reservoir simulator. The agreement initially covers a three-and-a-half year period during which SRT and Eni will work together to enhance and promote next-generation simulation technology and workflows that are enabled by ECHELON’s exceptional performance.

Reservoir simulation codes such as ECHELON model the subsurface flow of hydrocarbons and water in a petroleum reservoir. They allow energy companies to optimize recovery from their assets by simulating numerous what-if scenarios for well placement and development strategies. ECHELON is the fastest, most scalable simulator in the world and is built to run entirely on NVIDIA Tesla GPUs and CUDA software.

Recently, Eni announced the successful completion of a breakthrough calculation using ECHELON and its 18.6 petaflops HPC4 supercomputer cluster. A high-resolution model of a deep-water reservoir with 5.7 million active cells was used to generate 100,000 realizations with different petro-physical properties.

All 100,000 models completed in 15 hours running on HPC4’s 3,200 NVIDIA Tesla GPUs. Each individual model simulated 15 years of production in an average of 28 minutes.

Image of reservoir model showing horizontal transmissibility (red= high, blue=low). Click to enlarge.

By comparison, most reservoir engineers in the industry can run just one single simulation in a few hours with legacy CPU-based hardware and software.

Modeling oil reservoirs is no small computing problem. First exploration experts need to find the reserves by essentially drumming the Earth’s surface and capturing the reflected sound waves.

After massive numerical processing this reflected wave data is turned into images that geoscientists can use to determine if a reservoir prospect contains hydrocarbons and where the hydrocarbons are located within the image. Over the past decade, GPUs have played an increasingly important role in reservoir simulations.

Drilling can cost hundreds of millions of dollars. After locating hydrocarbons, quickly determining the most profitable strategies for new or ongoing production matters. For this task oil companies use reservoir simulators.

These reservoir simulators are technical software applications that model how hydrocarbons and water flow under the ground in the presence of wells. They let oil companies such as Eni evaluate virtual production strategies and “what-if” scenarios on supercomputers before committing to a new project as well as readjusting their models on production wells in the real world.

Simulators traditionally run on CPU-based hardware and are limited in both performance and in the size of the models. It’s not uncommon to have models that take days to run. To improve the odds of hitting production targets, the energy giants are increasingly turning to higher-resolution models and faster software powered by NVIDIA GPUs.