HPCwire: Linux Clusters Target Oil & Gas Applications

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HPCwire >> Industry >> Oil & Gas

August 25, 2006

Linux Clusters Target Oil & Gas Applications

, Carbon Management Program, Lawrence Livermore National Laboratory

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As an industry, hydrocarbon exploration and production operates in an increasingly challenging environment. The new challenges include more than high risk and high capital commitments, or declining fields and complex operations. Unconventional plays have become conventional, with fractured and/or tight porosity systems becoming commonplace. New environmental challenges require sophisticated and constrained operations. In this evolving regulatory, economic, and political environment, it is not enough to be creative, aggressive and technically adroit. One also wants to be smart.

The good news is that smart is a lot cheaper than it used to be. Specifically, high performance computers (HPCs) are a lot less expensive than they used to be, and a lot more powerful. The fastest computer in the world, Blue Gene/L, runs at nearly 300 teraflops, or 300 trillion floating point operations per second. The real revolution is that regular computer servers have become HPCs through parallel architectures, increasing industrial and market penetration.

A small cluster of Linux boxes -- 32 regular servers -- now outperforms the world's fastest computers from only a few years ago at 1/100th of the cost. They also are compact and easily serviced. A 128-cluster computer would take only three or four racks, easily fitting in a kitchen. These machines, the "big iron" of the world, have become readily available and powerful tools to tackle tough exploration, drilling and production problems.

Figure 1 shows the Thunder Linux cluster at Lawrence Livermore National Laboratory (LLNL). It is an 18-teraflop machine with more than 1,000 nodes and 4,000 central processing units, and ranks as the 11th fastest computer in the world. However, Thunder is about to be surpassed by an even faster and more powerful cluster system now being built for Lawrence Livermore. In late June, the Peloton supercomputing project was awarded to Appro for three 1U Quad XtremeServer clusters with a total of 16,128 cores based on next-generation AMD Opteron processors with DDR2 memory. To provide a production quality computing capacity, Peloton features a novel architecture that groups identical scalable units of 1,152 cores to form three shared-memory multiprocessor clusters.

Appro cluster

The Peloton clusters will be used in an unclassified environment as a multi-programmatic and institutional (M&IC) resource and in the classified environment to solve complex computational problems related to the National Nuclear Security Administration's (NNSA) Stockpile Stewardship Program. This program ensures the safety, security and reliability of the nation's nuclear deterrent. Identical scalable units with 1,152 cores will be grouped together to form the three shared memory multiprocessor clusters. Multiple organizations and programs within LLNL will share these supercomputing clusters for large, medium and small scale scientific simulations.

With scalable computing power at affordable pricing points, it is not surprising that massively parallel computers are becoming more common in oil and gas companies and their allied service companies. They mostly operate in seismic processing, although they also tackle problems from financial modeling to molecular chemistry. And more and more companies are looking to HPCs to solve tough problems in reservoir characterization and management. The reasons are simple: improved recovery, reserves stewardship and cost reduction.

Like any tool, however, they must be pointed at the right problem and operated well. Despite the high power and low cost of high performance computers, any commercial oil and gas company must understand why it should buy a machine, what it could do with one, and how it would fit sensibly into its business model. It must also know how to deploy the techs and scientists hired to work these machines. This is where the challenges to conventional operations and approaches can inform smart business how to wield big iron to solve big problems and turn big profits.

Two areas come to the fore. First, how can one handle uncertainty in the subsurface and in geophysical interpretation? Second, how can one simulate reservoirs in the increasingly difficult operational environment to obtain extremely high recoveries?

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