SMARTER STRATEGIES

Seeking Less Guesswork in Drilling for 'Black Gold'

Dennis McCafferty | Date: 04-20-10 | Comments

IBM is joining forces with Shell to help the oil-industry giant streamline the exploration process in order to boost business bottom line as well as reduce environmental impact.

Face it: When you watch old Dallas reruns � or, better yet, catch that cool scene in �Giant� where James Dean swaggers on the screen covered in oil � you get a sense that drilling for �Texas tea� is a pretty cool gig.

But the truth is that this messy business involves a lot of upfront investment, guesswork and ultimately failure. Geoscientists must pinpoint where the �black gold� exists beneath a dusty plain, a task that requires much data crunching. They've traditionally resorted to scouring endless printed geological surveys to find where organic matter exists underneath that has the greatest probability of containing hydrocarbons that produces oil. They need to figure out where there are rich deposits of sedimentary rock, the kind that's likely to hold such deposits.

After the spots are picked and drilling starts, researchers need to analyze time-lapse seismic data from subsurface rock formations, well and lab information, and sound waves covering wide spaces between the wells. Sometimes, it's not easy to reach consensus on what the data is saying.

�The information is not always sufficient enough to resolve all possibilities,� says Ulisses Mello, manager of Petroleum and Energy Analytics at IBM. �People may have different views and try to make their best recommendations based upon what they know. But it can be tricky.�

Given this scenario, Mello and his IBM team are leading a partnership effort with Shell Oil Company to reduce the risk factor of production drilling � specifically with respect to the scientific modeling of these wells and the reservoirs. The IBM-Shell Joint Seismic Inversion project is intended to reformulate and automate the task of reconciling the various data collected to create a clearer picture, and, thus, a more accurately predictive reservoir model. The IBM team is taking extensive algorithms, simulation software, and advanced analytics capabilities and other data and using this to provide the well models. The effort will launch at first from an offshore North Sea field operated by Shell called Draugen off the coast of Norway.

�We're seeking to minimize the difference between the prediction and the reality,� Mello says. �We also hope to reduce the time required to produce a model from six months to a matter of weeks.�

Shell is seeking to blend traditional and novel types of data into new information to better evaluate complex, geological settings, says Hans Potters, manager of Shell's Reservoir Surveillance Technologies. �We need to do this faster than we can at the moment,� he says. �With this collaboration, we break new ground in this area, and we expect this will increase oil and natural gas production in the future.�

Such an outcome wouldn't simply save Shell on operational costs. It would benefit the environment as well. �Anytime you increase efficiencies,� Mello says, �you reduce impact on the environment and save energy too. Ultimately, we seek to drill less wells to get the same results.�