By John Kemp
LONDON May 7 No one has ever seen an oil field.
Typically buried thousands of feet below the surface, oil
fields are like a sponge saturated with a mixture of oil, water
and gas, rather than the underground cavern most people imagine
when 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 enough
to be worth the costs of drilling. Finding substantial amounts
of oil is therefore akin to seeking a needle in a haystack.
Before deciding whether to sink a well, exploration and
production firms must estimate how much oil the reservoir
contains, and how much might be technically and economically
recoverable, usually based on interpreting relatively limited
amounts of data on what is actually down there.
As the easy oil runs out, and exploration and production
companies delve deeper below the surface, in tougher
environments like deepwater and the Arctic, the costs of
drilling and field development rise sharply, and the risks of
getting it wrong are correspondingly greater.
Oil companies have resorted to more and more computing power
to "de-risk" the process.
Rather than drill wildcat wells and hope for the best, which
is basically what happened in the 19th and early 20th centuries,
most exploration and production companies now rely on
super-computers to process and combine vast amounts of data
gathered from seismic, gravity and magnetic surveys, in addition
to well logs, to produce a three-dimensional "map" of the
The aim is to identify drilling locations that maximise the
chance of finding an exploitable amount of oil and gas, minimise
the danger of drilling a "dry hole", and target the
most-productive "sweet spots" in a formation.
The most modern models often employ four-dimensional
visualisations to identify how oil, gas and water flow through
the reservoir during production. They enable field engineers to
plan the optimum layout for producing and injection wells, and
to scrape some of the oil and gas left behind from primary
production through waterflooding and carbon dioxide injection.
WILDCATS AND SUPER-COMPUTERS
Oil majors like BP and Shell own and operate
some of the world's biggest super-computers to help process the
vast 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 increasingly
data-driven exploration and production process.
Its High Performance Computing Center, in Houston, Texas,
has maxed out its computing power and cooling capacity. The
company is building a new facility on the same site that will
roughly double its computing power.
The new three-story facility at Westlake Campus, scheduled
to be operational by the middle of 2013, will have more than
67,000 central processing units, and data storage equivalent to
147,000 Apple iPods with 160GB of memory each. It will be able
to perform more than 2,000 trillion operations per second (2
"This is not just about building a bigger and better
computer. BP's new high performance computing centre will be as
important to our global search for new energy resources as any
piece of equipment we employ today," the company said in
In the Middle East, Saudi Aramco's Exploration and
Production Engineering Centre (EXPEC) operates a legendary
control room that enables engineers to visualise Ghawar, the
kingdom's super-giant oil field, as if they were walking through
it, using special eye-pieces and screens, backed by a
Aramco's latest and most powerful simulator is GigaPOWERS,
which can break a giant oilfield up into billions of separate
cells to analyse it better.
"GigaPOWERS is an innovative reservoir simulation technique
(that) helps us to better analyse and predict the production
rate of our oil and gas reservoirs over time so we can manage
reserves well into the future," Aramco says.
"By combining relevant physics, chemistry and thermodynamic
relationships, we create highly complicated mathematical
equations. The solutions to these equations are then presented
in grid blocks that create a detailed visual picture of an oil
field," Aramco explains on its website.
"The increased resolution of GigaPOWERS has allowed us to
identify bypassed oil zones and additional oil zones, leading us
to drill new wells and recover more oil," the company adds.
Oilfield service companies like Schlumberger and
Baker Hughes now market their own sophisticated
reservoir visualisation software making it available to even
small and midsize exploration and production companies.
PROCESSING AND DATA LIMITATIONS
Despite the enormous strides in computing technology,
super-computers and geologists still rely on indirect
measurements such as gravity anomalies, seismic patterns and
cores brought back to the surface from test wells to estimate
the amount of oil in place and potential recovery rates.
Petroleum geology remains an art, relying on good judgement
and interpretation, as much as a science.
Data remains expensive to acquire and comparatively scarce.
Geologists have to estimate the thickness and extent of
petroleum-generating source rocks as well as the reservoir
formations from which the oil and gas is recovered.
The total organic content of the source rock, and its
temperature-pressure history, all determine how much of the
organic matter has been converted into oil or gas, and have to
be estimated (or intelligently guessed).
The porosity of the reservoir, the connectedness of its
pores, and its relative saturation with oil, gas and water all
determine how much can ultimately be recovered, how many wells
may be needed, and how far apart, as well as whether special
techniques like horizontal drilling and hydraulic fracturing
will be needed.
In most cases, initial estimates of the amount of
recoverable oil and gas across comparatively large areas must be
made based on surface seismic surveys and rock samples and well
logs from just a small number of wells.
Even small changes to estimates of total organic content,
porosity, connectedness and other factors can result in enormous
changes 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 conservative
approach, employing the least realistically feasible estimates
for the various parameters to produce a cautious estimate, and
hope any surprises will be on the upside.
As the field is developed, more wells are drilled, and more
data becomes available, it is possible to update the initial
estimates. If good practice has been followed, reserves and
resource estimates will normally be revised upwards.
This caution is one reason why the recent U.S. Geological
Survey estimates for the ultimate technically recoverable
resources from the Bakken shale deposits in North Dakota remain
low compared with estimates published by some exploration
companies and consultants involved in the play.
Technology is the other. Most of the oil originally
contained in a reservoir is never recovered (though exactly what
percentage remains is left behind is also subject to uncertainty
because no one knows for certain how much was actually there in
the first place). But as technology improves it has usually
become possible to produce more of the oil that was originally
In many cases, it has been possible to identify pools of
stranded oil, or fractured the reservoir rock and pump in water
and chemicals to drive extra oil towards the wells.
Super-giant fields like Saudi Arabia's Ghawar and
California's Wilmington have already produced many times more
oil than geologists originally thought possible, and are still
thought to be capable of producing billions of barrels more.
North Dakota's Bakken is no exception. Once thought to be
essentially impossible to produce because there was not
sufficient connectivity between the pores, it has already
produced more than 500 million barrels and could ultimately
yield at least eight times as much, according to USGS.
Given the conservative estimating methods employed by USGS
it may eventually yield far more.
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