IBM Oil| IBM has helped Repsol enter the future of oil exploration

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Repsol is an international company that focuses on oil and gas exploration. Learn why Repsol trusts IBM's advanced multi-core technology to spot likely oil and gas discoveries more accurately and bring it to market faster than any other oil exploration company.
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  Building a Smarter Planet Repsol shows the future of offshoreexploration with more powerful anddetailed seismic imaging Repsol is an international integrated oil and gas company, operating in over 30 countries. It is the leader inSpain and Argentina, one of the ten largest private oil companies in the world and the largest privateenergy company in Latin America in terms of assets. Overview ■  Business Challenge For its oil exploration activities in the deep waters of the Gulf of Mexico—a region known for complex geological conditionsthat make finding oil and gas hard—Repsol needed to aug- ment its seismic imaging capa- bilities to reduce the risk of drilling “dry holes” and shortenthe time to “first oil.” ■ Solution Repsol worked with IBM to build a powerful new systemcapable of running the next generation of more accurate seismic algorithms—and do sofaster than the rest of the indus-try. Leveraging advanced multi-core technology, and optimizing algorithm code for maximum performance—Repsol can spot likely opportunities for oil and gas discovery more accurately  and bring it to market faster. ■  Key Benefits — 85 percent reduction in time required to run next genera-tion seismic algorithms — Substantially lower power  and cooling costs — Fewer dry holes and wasted resources  The world’s petroleum producers rec-ognize that when it comes to findingand exploiting new sources, the days of “easy oil”—that which is found in largereservoirs either on shore or in shallowcoastal waters—are largely over. Thenew frontier for exploration, and thebiggest hope for future large discover-ies, lies farther offshore, in reservoirsmiles beneath the seafloor in watersthat can be miles deep. These extremeconditions make deep-water oil explo-ration and production an expensiveproposition. In the Gulf of Mexico, forexample, the total cost of developing adeep-water field is often measured in “We see IBM’stechnology and expertise as gamechanging in the area of oil exploration becausethey enable a newlevel of analyticalinsight that fits withour need for costeffectiveness,sustainability and fasttime-to-market.”  —Francisco Ortigosa, Director of Geophysics, Repsol YPF   Achieving a new level of accuracy and efficiency in deep-sea oil exploration Business Benefits ● 85 percent reduction in time requiredto run the next generation of highly accurate—and compute-intensive—seismic algorithms ● More detailed rendering of complexsubsurface structures such as saltdomes, resulting in fewer dry holesand wasted resources ● Faster time to market for new oil andgas properties by shortening theseismic data analysis phase ● Reduced risk in bidding for offshore oiland gas leases ● Substantially lower power and coolingcosts resulting from the increase incomputing efficiency enabled by themulticore optimization of Repsol’sseismic algorithms “Our ability toleverage advanced seismic algorithms fundamentally changesthe way we managethe risks and seize theopportunities of deep-sea oil exploration.”  —Francisco Ortigosa the billions of dollars, while the cost of operating just a single offshore platformexceeds half a million dollars per day. That’s not to mention the perennial threat of hurricanes damaging infrastructure and disrupting exploration and productionefforts. What draws many of the world’s largest oil exploration and production com-panies to the Gulf of Mexico despite these costs and challenges are the region’senormous reserves of recoverable oil, a figure the U.S. Department of the Interior’sMinerals Management Service puts at 56 billion barrels. Getting a better picture While pinpointing the exact location of oil and gas reservoirs is always a challenge,the geological complexities of the Gulf of Mexico accentuate the challenge consid-erably. More than 100 million years ago, evaporating seas left a thick, extremelydense layer of salt, which was then gradually covered by the newer sediments thatmake up today’s seafloor. Over time, intense pressure caused the salt to well up atvarious points and form “salt domes,” mushroom shaped structures that provedideal for trapping oil deposits but are notoriously difficult to see beneath. To find oildeposits, exploration companies use advanced seismic imaging technologies toget as detailed a picture as possible of the subsurface landscape, much like mag-netic resonance imaging is used to scan the inside of a human body. The level of detail ultimately achieved is a function of complex algorithms, which translate hugeamounts of seismic data into 3-D maps that are then visually interpreted by teamsof experts. Like any business decision, their judgment—as to the presence of possible hydrocarbon-bearing structures—is only as accurate as the data it’sbased on. Therein lies the unique challenge of salt domes. Because of crystalline structure(which creates “noise” in the seismic data), it takes far more complex algorithmsto achieve the accuracy oil companies need to drill precisely in the right locationand thus avoid “dry holes,” whose costs can exceed $125 million. As an oil andgas company with a big stake in the Gulf of Mexico, Madrid-based Repsol(www.repsol.com) was determined to maximize the effectiveness of its explorationefforts—which meant adapting its methods to meet the challenges posed by saltdomes. Its intent was to better delineate geological structures deep below the sur-face by applying a far more powerful algorithmic approach known as reverse timemigration, whose extreme computational intensity had until then prevented oil com-panies from employing it. Repsol turned to IBM to help make this significant break-through in applied seismic techniques.Companies involved in oil exploration need to make practical decisions. They needto know when and how much to bid on offshore drilling leases. And perhaps mostimportantly, with oil more likely to be found in smaller, localized pockets, they needto know where to drill. Given the huge financial stakes and the limited duration of   drilling leases, time is the enemy. A dry hole exacts not only explicit drilling costs,but also the cost of missed opportunities and delayed cash flow, both of whichdestroy value. The same logic holds true for pre-drilling analysis. Despite its impor-tance, oil companies simply can’t afford to delay their exploration programs byrunning seismic algorithms that can take as much as four months to run. That’swhy—when faced with the trade-off between imaging precision and computationaltime—oil companies largely choose the latter out of necessity. Making the jump to more accuracy Repsol, however, believed that the unique challenges of deep-sea drilling in theGulf called for a rethinking of this paradigm, and that the key to enabling thischange was a quantum jump in computational capabilities that would make reversetime migration practical. Like its peers, Repsol has long relied on supercomputingclusters to run its seismic algorithms. In mapping out its next strategy, the com-pany saw the use of higher performance multicore processors as integral to itsplans. What became increasingly clear over time, however, was just howimportant—and challenging—it was to optimize seismic algorithms to fully leveragemulticore technology. After evaluating servers based on quad core technology,Repsol saw that processor scalability limitations would necessitate a much largerinfrastructure to handle its massive computing requirements, which would produceunacceptably high power and cooling costs. That’s when it took a closer look atthe IBM PowerXCell™ 8i processor.In the PowerXCell 8i, Repsol saw not only the power of its heterogeneous,nine-core processing architecture—which is well-suited to the specializedprocessing demands of reverse time migration—but also the opportunityto fully exploit it by capitalizing on the unmatched expertise of IBM Research inoptimizing algorithms to run on multicore systems. What’s more, Repsol saw thePowerXCell’s 16-x advantage in computing power per watt as a way around thepower and heat dissipation issues that would threaten the viability—both economicand technical—of a less efficient architecture. Repsol ultimately chose thePowerXCell 8i, running on a series of IBM BladeCenter® QS22 blade servers asthe foundation of an initiative now known as Project Kaleidoscope.Deployed by IBM located in Houston, Texas, the Project Kaleidoscope infrastruc-ture is comprised of 288 IBM BladeCenter QS22 blade servers supported by alarge network of IBM TotalStorage® storage hardware. In parallel with this deploy-ment, staff from IBM STG Cell Ecosystem & Solutions Enablement Group and theIBM T.J. Watson Research Center’s Multicore Computing Group worked closelywith parallelization experts from the Barcelona Supercomputing Center (BSC) tooptimize the reverse time migration algorithms for peak processing on the Solution Components Processor  ● IBM PowerXCell 8i Hardware ● IBM BladeCenter QS22 ● IBM System Storage™ ● IBM TotalStorage Services ● IBM T.J. Watson Research Center –Multicore Computing Group ● IBM STG Cell Ecosystem & SolutionsEnablement Group Smarter Petroleum Exploration Repsol is breaking new ground inimproving the accuracy of deep-sea oilexploration by harnessing the mostpowerful and efficient multicoreprocessing technology on the planet. Bybuilding a new seismic computinginfrastructure—and optimizing its seismicalgorithms to fully leverage its advancedmulticore properties—Repsol can nowrun the most comprehensive algorithms,which have until now been out of reachof oil and gas companies due to theirextreme computational intensity.  PowerXCell. Testing of the system on BCS’s MareNostrum supercomputer—built by IBM and the most powerful in Europe—showed that IBM PowerXCell 8iprocessor ran these algorithms as much as six times faster than existing seismicanalysis platforms. Changing the game In the larger scheme, Repsol’s embrace of a new approach to processing seismicdata puts the company in a stronger competitive position because it has gainedthe ability to look deeper into seismic data—without having to compromise the tim-ing and quality of its decisions. In this sense, Repsol has broken through the accu-racy-versus-speed trade-offs that have defined seismic exploration until today. Ithas done so by reducing the time required to run complex imaging algorithms likereverse time migration from four months to two weeks. Access to more detailedand fine-grained seismic images enables Repsol to make more accurate and data-driven drilling decisions, substantially mitigating the risk of dry holes associated withthe Gulf of Mexico’s salt domes. Elsewhere, this richer view of potential petroleumdeposits provides Repsol with an advantage in bidding for offshore properties,both by lessening the likelihood of paying too much and helping Repsol spotundervalued properties.Francisco Ortigosa, Director of Geophysics, sees Repsol’s leadership in the area of advanced seismic algorithms as greatly enhancing the company’s ability to find andcapitalize on the Gulf of Mexico’s rich deep sea exploration and production oppor-tunities. “Our ability to leverage advanced seismic algorithms fundamentallychanges the way we manage the risks and seize the opportunities of deep-sea oilexploration,” says Ortigosa. “In the same way, we see IBM’s technology andexpertise as game changing in the area of oil exploration because they enable anew level of analytical insight that fits with our need for cost effectiveness,sustainability and fast time-to-market.” For more information Please contact your IBM sales representative or IBM Business Partner. Visit us at: ibm.com  /chemicalspetroleum ©Copyright IBM Corporation 2009IBM Corporation1 New Orchard Rd. Armonk, NY 10504U.S.A.Produced in the United States of AmericaJanuary 2009 All Rights ReservedIBM, the IBM logo, ibm.com, BladeCenter,PowerXCell, System Storage and TotalStorageare trademarks or registered trademarks of International Business Machines Corporation inthe United States, other countries, or both. If these and other IBM trademarked terms aremarked on their first occurrence in thisinformation with a trademark symbol (® or ™),these symbols indicate U.S. registered orcommon law trademarks owned by IBM at thetime this information was published. Suchtrademarks may also be registered or commonlaw trademarks in other countries. A current listof IBM trademarks is available on the Web at“Copyright and trademark information” at ibm.com  /legal/copytrade.shtmlOther company, product or service names maybe trademarks or service marks of others. This case study illustrates how oneIBM customer uses IBM products. Thereis no guarantee of comparable results.References in this publication to IBM productsor services do not imply that IBM intends tomake them available in all countries in whichIBM operates.ODC03119-USEN-00
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