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By John Kemp
LONDON, May 7 (Reuters) - No one has ever seen an oil field.
Typically buried thousands of feet below the surface, oilfields are like a sponge saturated with a mixture of oil, waterand gas, rather than the underground cavern most people imaginewhen they think about oil and gas reservoirs.
Many rock formations contain limited amounts of oil and gas,especially in sedimentary basins, but only a few contain enoughto be worth the costs of drilling. Finding substantial amountsof oil is therefore akin to seeking a needle in a haystack.
Before deciding whether to sink a well, exploration andproduction firms must estimate how much oil the reservoircontains, and how much might be technically and economicallyrecoverable, usually based on interpreting relatively limitedamounts of data on what is actually down there.
As the easy oil runs out, and exploration and productioncompanies delve deeper below the surface, in tougherenvironments like deepwater and the Arctic, the costs ofdrilling and field development rise sharply, and the risks ofgetting it wrong are correspondingly greater.
Oil companies have resorted to more and more computing powerto "de-risk" the process.
Rather than drill wildcat wells and hope for the best, whichis basically what happened in the 19th and early 20th centuries,most exploration and production companies now rely onsuper-computers to process and combine vast amounts of datagathered from seismic, gravity and magnetic surveys, in additionto well logs, to produce a three-dimensional "map" of thesubsurface.
The aim is to identify drilling locations that maximise thechance of finding an exploitable amount of oil and gas, minimisethe danger of drilling a "dry hole", and target themost-productive "sweet spots" in a formation.
The most modern models often employ four-dimensionalvisualisations to identify how oil, gas and water flow throughthe reservoir during production. They enable field engineers toplan the optimum layout for producing and injection wells, andto scrape some of the oil and gas left behind from primaryproduction through waterflooding and carbon dioxide injection.
WILDCATS AND SUPER-COMPUTERS
Oil majors like BP and Shell own and operatesome of the world's biggest super-computers to help process thevast amounts of information gathered in the exploration process.
BP's computer needs have grown 10,000 times since 1999,according to the company, as a result of its increasinglydata-driven exploration and production process.
Its High Performance Computing Center, in Houston, Texas,has maxed out its computing power and cooling capacity. Thecompany is building a new facility on the same site that willroughly double its computing power.
The new three-story facility at Westlake Campus, scheduledto be operational by the middle of 2013, will have more than67,000 central processing units, and data storage equivalent to147,000 Apple iPods with 160GB of memory each. It will be ableto perform more than 2,000 trillion operations per second (2petaflops).
"This is not just about building a bigger and bettercomputer. BP's new high performance computing centre will be asimportant to our global search for new energy resources as anypiece of equipment we employ today," the company said inDecember.
In the Middle East, Saudi Aramco's Exploration andProduction Engineering Centre (EXPEC) operates a legendarycontrol room that enables engineers to visualise Ghawar, thekingdom's super-giant oil field, as if they were walking throughit, using special eye-pieces and screens, backed by asuper-computer.
Aramco's latest and most powerful simulator is GigaPOWERS,which can break a giant oilfield up into billions of separatecells to analyse it better.
"GigaPOWERS is an innovative reservoir simulation technique(that) helps us to better analyse and predict the productionrate of our oil and gas reservoirs over time so we can managereserves well into the future," Aramco says.
"By combining relevant physics, chemistry and thermodynamicrelationships, we create highly complicated mathematicalequations. The solutions to these equations are then presentedin grid blocks that create a detailed visual picture of an oilfield," Aramco explains on its website.
"The increased resolution of GigaPOWERS has allowed us toidentify bypassed oil zones and additional oil zones, leading usto drill new wells and recover more oil," the company adds.
Oilfield service companies like Schlumberger andBaker Hughes now market their own sophisticatedreservoir visualisation software making it available to evensmall and midsize exploration and production companies.
PROCESSING AND DATA LIMITATIONS
Despite the enormous strides in computing technology,super-computers and geologists still rely on indirectmeasurements such as gravity anomalies, seismic patterns andcores brought back to the surface from test wells to estimatethe amount of oil in place and potential recovery rates.
Petroleum geology remains an art, relying on good judgementand interpretation, as much as a science.
Data remains expensive to acquire and comparatively scarce.
Geologists have to estimate the thickness and extent ofpetroleum-generating source rocks as well as the reservoirformations from which the oil and gas is recovered.
The total organic content of the source rock, and itstemperature-pressure history, all determine how much of theorganic matter has been converted into oil or gas, and have tobe estimated (or intelligently guessed).
The porosity of the reservoir, the connectedness of itspores, and its relative saturation with oil, gas and water alldetermine how much can ultimately be recovered, how many wellsmay be needed, and how far apart, as well as whether specialtechniques like horizontal drilling and hydraulic fracturingwill be needed.
In most cases, initial estimates of the amount ofrecoverable oil and gas across comparatively large areas must bemade based on surface seismic surveys and rock samples and welllogs from just a small number of wells.
Even small changes to estimates of total organic content,porosity, connectedness and other factors can result in enormouschanges in estimated resources and reserves. For this reason,resources and reserve estimates are subject to huge uncertainty.
CONSERVATISM IN RESOURCE ESTIMATES
It is normally good practice to adopt a conservativeapproach, employing the least realistically feasible estimatesfor the various parameters to produce a cautious estimate, andhope any surprises will be on the upside.
As the field is developed, more wells are drilled, and moredata becomes available, it is possible to update the initialestimates. If good practice has been followed, reserves andresource estimates will normally be revised upwards.
This caution is one reason why the recent U.S. GeologicalSurvey estimates for the ultimate technically recoverableresources from the Bakken shale deposits in North Dakota remainlow compared with estimates published by some explorationcompanies and consultants involved in the play.
Technology is the other. Most of the oil originallycontained in a reservoir is never recovered (though exactly whatpercentage remains is left behind is also subject to uncertaintybecause no one knows for certain how much was actually there inthe first place). But as technology improves it has usuallybecome possible to produce more of the oil that was originallyleft behind.
In many cases, it has been possible to identify pools ofstranded oil, or fractured the reservoir rock and pump in waterand chemicals to drive extra oil towards the wells.
Super-giant fields like Saudi Arabia's Ghawar andCalifornia's Wilmington have already produced many times moreoil than geologists originally thought possible, and are stillthought to be capable of producing billions of barrels more.
North Dakota's Bakken is no exception. Once thought to beessentially impossible to produce because there was notsufficient connectivity between the pores, it has alreadyproduced more than 500 million barrels and could ultimatelyyield at least eight times as much, according to USGS.
Given the conservative estimating methods employed by USGSit may eventually yield far more.
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