Reduction of unplanned events creates savings in offshore operations.

Oil companies are adding typically 20% to 40% to their total costs, and losing up to 20% of their production, without realizing it, because of poor process design and control, leading to excessive variability, in offshore operations.

The industry can't afford to carry such costs, given the multitude of challenges facing it at present. Not least is the challenge of maintaining revenues and margins when production is slowly declining in mature fields and more rapidly in deepwater fields and question marks hang over how quickly and how productively new fields can be brought onstream.

In the Gulf of Mexico, a major oil and gas exploration and production company undertook a pilot project across four platforms to raise operational performance to levels that would help arrest the steep rise in lifting costs and maintain margin levels in the face of the decline challenges. The results achieved owe much to improving steady state operations and reducing unintended trips. Both have been made possible through better usage of data that was already available to reduce operational variability.

Common issues

Symptoms of the need for change on the major operating company's platforms were typical of the offshore industry at large. On most offshore platforms, production tends to be variable in an unpredictable way. The production losses due to such variability can be considerable, often, in the more extreme cases, the equivalent of having one in every five wells standing idle all the time. This variability, in turn, creates unpredictable workloads, leading to expensive unplanned use of contractors, overtime, logistics, additional spares; this list is by no means exhaustive, as there are many other additional costs. Most modern and even some older assets have highly sophisticated fault-monitoring equipment in place to indicate when something has happened that may make intervention - and, in some cases, shutdown - necessary. But the data captured by such equipment is rarely used to maximum effect, to monitor accurately the production lost and to optimize the start-up process. The results are unnecessary costs, and more increases in deferred and lost production.

One producer reports a sharp gain in production performance improvement achieved at one of the operator's locations that was part of a pilot implementation program with Celerant Consulting Inc. with better steady state operations and heavily reduced trips. These results have since been repeated across all the production company's US assets as the original pilot has been rolled-out across all assets over the past 18 months. Clearly, the impact is significant. Production is much more consistent - which, in turn, allows staffing reduction (initially 10%, 15% after 12 months) from lean complements. Moreover, maintenance scheduling is made more effective (helped by a new contractor management process): in 2002, more than 70% of workgroup available time was scheduled for activity with about 70% attainment. By holding unit costs flat to 15% down, the project made a major contribution to maintaining a flat unit lifting cost (UOC) to help offset field declines.

Fact-based decision-making

Reducing platform trips was central to the operator's strategy for enhancing steady state operations. Implementing that strategy meant simplifying and sharing information already available such that the right information flowed to the right people, and effective corrective action loops were built in to optimize the whole process. "The way we do things around here" was replaced by rigorous, fact-based decision-making focused on key indicators of production operations.

The approach applied to effect this change was drawn from Six Sigma, a way of combining hard and soft management tools to change the things people do and the way they do them. On the "hard" side are tools for quality improvement (e.g. Pareto charts), process mapping and design, process control and optimization, and design optimization. The Six Sigma approach also encompasses skill development in areas such as communication, leadership, process management, stakeholder management and teamwork.

The name Six Sigma comes from a statistical foundation, where sigma is the standard deviation in a normal distribution of outcomes. It measures the deviation from "perfect" of the real performance in an operation or organization. For example, in a plate-making factory operating at Three Sigma level, there will be over 68,000 defects in every million plates - whereas, at Six Sigma level, there will be 3.4 defects per million plates. The factory's cost of poor quality, measured as a percentage of sales, will be reduced from 15% to 25% to 1% to 3% by transforming from Three Sigma to Six Sigma levels of performance.
A plate-making factory and producing hydrocarbons are obviously very different types of operations; but the aims of minimizing costs and optimizing throughput are the very same, tackled with equal vigor. Six Sigma's 3-D approach to achieving those aims - by reducing variability, reducing complexity, and increasing customer focus - applies equally well across industries.

Companies such as GE, Motorola, Texas Instruments and DuPont are already well advanced in applying, and gaining competitive advantage from, Six Sigma techniques. It is only a matter of time before the triple focus on variability, complexity and customers becomes a significant difference between leaders and followers in exploration and production as well.

A new approach to steady state

In the Gulf of Mexico pilot project, a joint operator-consultant taskforce team was engaged in an overall drive to increase hydrocarbon throughput, reduce key areas of operational expenditure, and take out non-value-add or low-value-add work. The project focused on accelerating the implementation and usage of effective management systems for production and maintenance in order to increase asset reliability and sustain the results achieved. Clearly, surface and sub-surface steady state operations would be a central focus in this effort.

The taskforce team concentrated its efforts in three work streams: operational excellence (OE), maintenance planning and scheduling (MPS) and production system optimization (PSO).
The OE work stream's goal was to enable better understanding of the root causes of problems and faster development of solutions for them. Because process variability was a significant barrier to sustainable production levels and a major cause of unintended trips, the team designed a set of "process" short-interval controls. Combined with a new standardized reporting mechanism, this approach helped to maximize throughput and efficiencies at the same time.

The MPS work stream focused on improving uptime and equipment reliability. The team's first step was to fine-tune a standardized scheduling and planning process that would maximize resource utilization across the assets involved in the project. Next, a management control and reporting system was developed to streamline reporting and give employees ready access to key indicators of maintenance and reliability performance. Interpersonal communication was enhanced through a new process for sharing best practices and encouraging continuous improvement.

The third work stream, PSO, was assigned the task to enable the offshore operations staff to make better use of the operating company's existing - and very comprehensive - production loss accounting system. By focusing on key production parameters, operators were able to routinely identify and categorize causes of production loss, in a new culture with much higher expectations that action would be taken to remove or reduce those causes.

In steady state operations, all three work streams contributed to enhanced performance. Undetermined deferment was reduced to below 1% in places, and uptime increased by 5%.

Now, with the right systems in place, managers and staff at all levels receive reliable timely data, at the appropriate frequency, to make decisions and take action to maximize performance. People throughout the business have a clear understanding of what is expected of them. And their decisions and actions are driven by an increased level of accountability, made possible by the new ways of working.

Conclusion

Even if no one aspect of platform operations stands out as requiring urgent correction and improvement, nonetheless the cumulative costs and production losses due to not properly using the data available, and not optimizing each process, can be dramatic.

The results achieved in the production company's pilot project alone provide compelling evidence. In total, over 3.2 million boe in additional annualized production and US $3.9 million in annualized cost savings; increase in uptime across the asset base, yielding asset utilization in excess of 98% at the largest pilot asset; plus reductions in the maintenance backlog, and in required manning levels. Pilot areas continue to deliver at these levels of performance. As we stated earlier, the company has been able to deliver similar results across all its US assets after the pilot project was rolled-out in late 2002.

If a typical supermajor took the kind of action described above to reduce variability - installing in every one of its platforms the management systems, processes, tools, methodologies and skills needed to ensure attention is focused on the right data, and that the data is distributed and utilized in the best way, with efficient, consistent and predictable processes - the impact on annual earnings could run into hundreds of millions of dollars.

Comments