Society of Petroleum Engineers 2010 ATCE, Florence

Our report from the first SPE ATCE to be held outside of the US covers a popular session on the future of natural gas, a call from ExxonMobil and Chevron for a rethink of upstream standards, Saudi Aramco’s plans for an ‘exacell’ reservoir model and a new approach to risk evaluation.

The SPE sure knows how to stage a good plenary session with around 2,000 present for the opening event—a debate on the future of natural gas. Chairperson Schlumberger CEO Andrew Gould described as ‘spectacular’ the growth in unconventional gas which now makes up over 40% plus of US domestic production. Non-conventional reserves are known to exist in other parts of the world, the question is, can the success be replicated in populated and environmentally sensitive areas such as Western Europe? Whatever the answer, for Gould, gas has come of age. It is no longer an ‘inconvenience.’ Not even just a ‘transition’ fuel and may well represent the ‘fuel of the future.’ Howard Paver (Hess) was a bit more circumspect. Demand growth out to 2035 is forecast at 4000 TCF—the equivalent of 1.3 million Barnett shale wells and a $4.5 trillion investment! Sara Ortwein (ExxonMobil) expects natural gas production in 2030 to be 55% up on 2005 with 50% conventional. Under 15% of the global gas ‘resource’ has been produced to date. Demand growth is mostly from non-OECD countries so energy needs to be cheap. Mike Stoppard (IHS/CERA) noted that gas is being ‘out-competed.’ Not in the marketplace but in the policy area. Gas needs to raise its voice and make its case in the new ‘decarbonized’ energy economy where its rightful position is alongside green energy.

Sticking with the natural gas theme, Mike Economides (University of Houston) offered an entertaining talk on the potential of China’s ‘third coast,’ i.e. its river system, to bring natural gas to internal markets. The clean fuel is urgently needed because today, China’s energy comes 70% from coal and, ‘you can’t see the sky in many Chinese cities.’

Speaking at the Digital Energy special session Mike Crawford (ExxonMobil) and Rick Morneau, (Chevron) noted that although companies want integrated operations, the current state of standards development inhibits interoperability. Most standards today are XML/web services which reduce exchange friction. The Witsml data standard has accomplished this for real time drilling. There may be cooperation between standards bodies or there may be competition leading to a ‘fork’ in their potential value. A gas lift optimization program might involve seven different standards from OPC to ProdML. Today’s standards bodies are uncoordinated. PPDM, OPC, Energistics and ISO represent so much conflicting and competing terminology. The authors consider that the next stage of the digital oilfield requires ‘common purpose and alignment of upstream standards.’ There is neither a lack of standards organization, nor a lack of participation in both personnel and financial commitment. But still, integrated operations eludes the upstream. Maybe the time is ripe for a rethink of standards organizations’ process and methods—perhaps under the auspices of the SPE.

Ali Dogru described how Saudi Aramco has evolved from a ‘silo’ mentality a couple of decades ago that tended to produce ‘conceptual’ reservoir models. These proved inadequate to model unswept zones in Aramco’s massive reservoirs. Today the company has a comprehensive toolset for modeling, intelligent completions and for keeping track of the ‘explosion’ in measurement and the revolution in computing power, graphics and communications. Aramco still has domain specific departments—but no more silos thanks to improved communications. Aramco now uses ‘high precision’ reservoir models to reduce uncertainty and optimize reservoir management. The reservoir simulator is regarded as a powerful integrator. Here Aramco’s objective is to preserve the fine grain geological models—made up of billions of cells—right through to the simulator. This avoids losing resolution of thin beds and other flow barriers. Today’s model of the Ghawar supergiant has a 250 meter grid size and 10 million cells. This is not fine grained enough. Aramco is now working on a 25 meter grid size and a billion cell model. Running the simulator code on such a monster means massively parallel simulators. But the prize is huge. For Ghawar, a 1 % hike in recovery means an extra billion barrels of oil.

Comparisons of different resolution models on the same field have shown that coarse models fail to resolve closely spaced wells. High resolution simulations of water cut against time are ‘much closer to observation.’ Aramco has made a significant investment in cluster technology to run its GigaPowers simulator. A billion cell model of the Safaniya Field, the worlds largest offshore oilfield took 15 hours to match 50 years of history, leveraging Aramco’s 4,000 core cluster. Dogru wound up saying ‘this is all about finding oil in field outliers with our fine grained model—this is what justifies my existence’ and exhorted others to ‘build bigger models.’ Aramco is already planning for a 100 billion ‘exacell’ model for 2014.

Pat Leach (Decision Strategies) believes that we are all too risk averse. We evaluate situations of identical risk differently according to how they are presented to us—a phenomenon captured in Kahneman and Tversky’s ‘prospect theory*.’ For most people, the ‘certain equivalent,’ i.e. how much you would take in exchange for an opportunity, is less than the expected value—even though these should be the same. The caveat is that you must be able to afford to lose—or for companies, that no single project will put them ‘in distress.’ Portfolio managers should be risk neutral and base decisions on the expected value. Applying risk at the project level wastes a company’s ability to absorb losses and share gains, although project managers may not like this approach. Companies are even more averse to development project risk because of the magnitude of the potential loss. Here value of information analyses may help. Efficient frontier analysis is also a great tool for applying set levels of risk tolerance.


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