Then there is the "downstream" work of refining crude oil into something usable, such as gasoline or diesel, and of getting those products sold and delivered. Those jobs generate information on refinery capacity and throughput, for example, and the cost of marketing and distribution.

Exxon and Chevron, the biggest oil companies in the United States, are known as "integrated," meaning they work both the upstream and downstream ends of the business. Petrobras does, too, though Ehrlich points out that no company is perfectly integrated, meaning that what it finds in the ground always ends up in its own refineries. Chevron might find crude that its refineries don't handle, he says. "Some types of oil require more complex refining capability to process." Chevron produces about 2 million barrels of oil per day and only refines about 15 percent in its own refineries.

Others focus on just one end or the other. Valero, for example, is the biggest U.S. refiner, concentrating on the downstream work of turning oil into other things to sell.

Upstream usually costs more than downstream. Exxon, for example, spent $15.7 billion on upstream jobs in 2007. Chevron, $15.5 billion. But downstream costs stack up, too. Exxon's were $1.1 billion and Chevron's $3.4 billion.

Prices at the pump reflect these expenses. The cost of crude oil constitutes most of the price of gas, accounting for 73 percent of today's $4-plus figure, according to the U.S. Department of Energy. Refining, meanwhile, is 8 percent; so is distribution and marketing. The remaining 12 percent goes to state and federal taxes. Each oil company analyzes its costs and potential income, says David Smith, an IT consultant to the oil industry at Electronic Data Systems, trying to profit at each step (except for taxes, which are fixed).

Traditional economic principles of supply and demand alone fall short when you try to forecast prices, Smith says. "With political instability, fear about Iran and Iraq—those have ripple effects and an emotional response at the pump," he says.

"You have to blend that volatility with real-time market data and factors you can't predict."

Big Oil's Big Picture

After oil, the best kind of gusher to discover and manage these days is data, and therefore profits, in real time. Or close to it. That's what Hess is after.

For the past four years, the $32 billion integrated oil company has been building BI systems to trace and interpret data from start to finish along the exploration and production value chain in as close to real time as possible, says Lensing. The idea is to be able to see activity at all its assets in Norway, Denmark, the U.K., the U.S., Thailand and Africa. Are its four fields in Equatorial Guinea producing as expected today? Is the refinery in New Jersey running at capacity, or can it take in more barrels of oil before the end of the month? What have sales at its 1,370 gas stations been since last Saturday at noon?

No one business intelligence product can do it all, though. For financial analysis, Hess mainly uses tools from Hyperion, which Oracle bought last year. To estimate how much oil or natural gas its wells can produce, the company develops a model of the reservoir terrain based in part on readings from bouncing seismic waves in the area. For a look at patterns in well production, Hess runs a tool popular among pharmaceutical firms called Spotfire, from Tibco. Spotfire lets analysts visualize data by producing graphs, charts and other pictures, into which users can drill down with queries.

The company is also installing OSIsoft performance management software—in part to collect operations data—to measure, for example, how efficiently platforms and storage tanks are running. That project isn't finished yet. Meanwhile, Hess receives daily uploads about the performance of its joint ventures, such as one with Shell in the Gulf of Mexico, via secured FTP transfers.

One of the real-time parts of this BI chain is well data. An engineer in Houston can monitor drilling activity in West Africa, see an anomaly in how the drill bit sinks into the ocean floor and can send that data over satellite to a geoscientist in Houston, who can view the visualization and e-mail a recommendation on how to adjust the machines, Lensing says.

"The ability for people on a platform to communicate with people in the home office and work on the same set of data means we can get more production done faster and more accurately," he says. "How you choose to analyze the data and the decisions you make—there's your competitive advantage."

More production faster means Hess could, in theory, sell more crude or refined products sooner while market prices are high, as they are now.

The Cost of New Business

For Petrobras, an oil field discovered off the coast of Brazil could become the world's third biggest, after one in Saudi Arabia and another in Kuwait. The potential bounty: 33 billion barrels.

That's an unofficial estimate attributed in April to Brazil's National Petroleum Agency. Petrobras officials decline to confirm it, insisting that more testing must be done. Olinto Gomes de Souza Jr., a senior geologist there, is helping analyze some of the test data.

After four years of exploration and computerized modeling, the company last November announced that it had hit oil 6,500 feet beneath the ocean surface and another 16,000 feet into the ocean floor. Now proof drilling continues, boring through rock and salt layers atop the oil. At each centimeter, Petrobras looks at 10 to 12 variables, including temperature, pressure, and weight of rock and sediment. Stored in an Oracle database, the information is queried with analytics software from SAS Institute.