Significant ROI on West Africa Ultra Deepwater Project

Two Exceed Performance coaches look back upon a successful project working with the rig team of an ultra-deepwater exploration drillship in West Africa.

The project, which involved an ultra deepwater rig, saw the rig's performance increase from a baseline NPT of 28% for the first six months of the wells campaign to an average of 18% in the first 12 months of the project and a further reduction to 12% realised during the second half of the wells campaign. The increase in productive time from 72% to 82% in the first half and 88% in the second half of the project is equivalent to 65 additional productive days.

"Over the past 12 months Exceed have worked with the Wells Team to implement a continuous improvement programme. As a consequence a more rigorous plan-do-measure-learn approach has become embedded as the way we work.

This has resulted not only in an improved rig perform-ance but it has also contributed to the improved safety performance.  In addition initiatives such as publishing a rig CIP newsletter has also contrib-uted to improved morale onboard."

- Drilling Supervisor, Operator

The implementation, which was guided by two full-time Performance Coaches, had the following highlights:

• The project was named NZILA by the rig team (Nzila = Passage to Excellence)
• The Rig has operated for a year without a single Recordable Injury
• All wells drilled below the AFE and well objectives fulfilled
• Learning (550 LL) at > 85% closure
• Consistent well-supported CIP process
• Continuous improvement principles integrated across the operation
• Performance focus supported by measurable KPIs at all levels

With a high turnover of staff and relatively inexperienced first line supervisors, much of the focus of the Performance Coaches was on introducing a consistent approach to planning, measurement and learning. Exceed's Performance Tracking & Learning software was introduced to establish and measure meaningful KPIs, capture Lessons Learnt in a consistent format,  and perform flat spot tracking to establish benchmark times for specific tasks and identify possible root causes of ILT.