The Role of Big Data in Operational Excellence and Real Time Fleet Performance Management—The Key to Deepwater Thriving in a Low-Cost Oil Environment

Bolen, Matt (Chevron) | Crkvenjakov, Vladimir (Schlumberger) | Converset, Julien (Schlumberger)



Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive. Considering that deepwater upstream capital projects are some of the most expensive projects in the industry, capital costs on a per well basis must be reduced in order for deepwater to continue to attract capital. Achieving operational excellence by embracing the big data revolution will help answer the challenge in thriving in a low-cost oil environment.

Oil and gas operators as well as others suffer from data overload. A major challenge in the process of achieving operational excellence is to find a way harness big data and capitalize on its benefits. The paper outlines the solution that a major operator and service company developed that established a unique well construction optimization process, improved consistency and moved every operation closer to the technical limit.

The solution was developed for the major operator in Gulf of Mexico (GOM) deepwater fleet and was successful in reducing the well cycle times by:

Applying a unique approach and workflow to transform big data into usable knowledge and enable critical thinking in the process of data analysis. This led to challenging current established operational procedures, making adjustments to actual well conditions and maximizing the efficiency of the rig.

Enhancing a standard set of key performance indicators (KPIs) so that each operation is measured and the performance is understood.

Establishing an effective in-house real-time data analysis center that fully supports the integrated drilling teams in order to drive data-driven decision making.

Utilizing concise visualization of surface digital data so that clarity from the data can be gained and insights communicated to the rig teams.