Re-appraisal and enhancement of processes to overcome perennial operating challenges is required perhaps more than ever before. No area should be off limits, not least those that attempt to reduce maintenance and lifting costs. Fortunately, within this space, there have been innovative developments in approach.

Specifically, taking advantage of good quality production performance data as an additional lens on the prioritisation of maintenance work.

This approach is exemplified within one of our clients, a major UKCS operator with an excellent reputation for operating a ‘Best in Class’ loss/deferment management and optimisation process.

Significant effort over the years had enabled them to develop a highly effective and collaborative  approach to minimising production and injection losses. What was once seen as a clumsy and low value process, had been turned around to provide high value information for the leadership team and ensured that losses were fully understood and prevented from recurring.

This mindset of chasing every barrel  helped deliver class leading performance across multiple assets.

The improvement in the quality of their data was a crucial milestone in their performance improvement journey. It served as the bedrock for everything that followed. It meant data was now trusted and in turn relied upon more than ever. This led to additional demand for the data, which in turn motivated those providing the data. It established an effective ‘self-driving’ symmetry between the provision of and demand for quality data.

What happened next was interesting. The business looked to utilise this data within increasing aspects of asset management.

The Innovation

A regular meeting between the optimisation and maintenance management teams. It sounds simple and obvious on the face of it, but to many, it is like bringing oil and water together!

With higher confidence in their underlying data our client decided to bring the maintenance management and production optimisation teams together in order to compare their analyses. The result was as surprising as it was illuminating, there was very little alignment between the maintenance management team’s list of “bad actors” and the known main sources of production loss.

The big disconnect between these two overlapping disciplines indicated there was a substantial prize in terms of:

  • more efficient maintenance spend
  • improved production efficiency/reduced lifting costs/reduced emissions

The result from this particular example was that the meeting prompted further investigation into a particular compression system by the rotating equipment specialists. They discovered that it was the ancillary facilities such as cooling water that were causing the poor compression performance and the resulting production losses.

Appropriate new maintenance work was prioritised over other planned work and added to the schedule to address these issues. This decision might well not have happened without that initial discussion.

Applied to cost reduction, the high value decisions are often “What can we not do?”

If we can prioritise new work over existing scheduled work based on good production performance intelligence, then we can challenge the priority of other scheduled maintenance on the grounds that the systems to which the work is related seem to be performing well (i.e. not related to known sources of production loss). If the original prioritisation decisions still stand up, then they are more robust as a result. If not, there is an opportunity to save money or spend it more effectively.

The Practicalities 

Our client achieved this change in approach due to the following:

  • Good quality, trusted production & injection loss data.
    This, of course, is a subject in its own right that we have written extensively about. There is a useful takeaway towards the end of this article to help you improve your data quality.
  • Senior level influence.
    Good quality trusted data enhances management engagement and provides the influence required to convene such meetings.
  • A common frame of reference
    To help facilitate discussions between the optimisation and maintenance teams.

These are now considered in a little more detail:

Good quality, trusted production & injection loss data

The more relevant, trusted and easily digestible information there is available, the better supported these difficult decisions are.

Good quality, detailed data around where and why Production (and Injection) losses have happened over the last 3-6 months, providing the total $ value of each source and cause of loss, is therefore an important perspective on what the priorities should be. This perspective can be used to challenge maintenance decisions.

Taken alongside other important information sources (e.g. maintenance costs, lead time for spares, system redundancies, trip reports etc.), this will become an important part of a more holistic view of the production process. The good news is that it works both ways. The production optimisation team will also benefit from a better understanding of what is going on “under the bonnet”, in terms of production health, helping the transition to a more preventative, proactive mindset.

Senior level influence

With our client, it took senior level influence to bring the different disciplines together and challenge the status quo. This is why it is important for field/ops managers to receive intelligence from your loss management system. For example, Top ten Sources of Loss over the last 3-6 months. The time perspective is very important. Everyone knows about the large one-off events that happen, but it is often the low level but chronic issues that add up, over time to be the most significant. These may be easy to fix, but have been overlooked as they were considered low level and therefore low priority.

A common frame of reference

To easily collate and analyse data from all disciplines and data sources, there needs to be a common framework. A breakdown of facilities by specific named system (already the standard for maintenance), will provide this. It means, of course, that your production loss data must include that element (i.e. System or “Source” of loss plus “Cause”). Unfortunately, many operators still work with a more basic “Reason code”, which contains a mixture of Sources and Causes of loss, but only one is allocated against each loss event. If that sounds like your organisation, don’t worry, we can help.

Although the Younglight Choke Model toolkit now facilitates the bringing together of all of these different sources of information at a system based level, it can only be effective in presenting the bigger picture if that information is of good quality, trusted and can therefore be relied upon to backup good decision making.

An Added Bonus

Our major North Sea client has experienced and benefited from the self perpetuating dynamic that appears when those consuming data to support decision making are supplied by those providing data of the appropriate quality and relevance. This jointly increased the confidence and satisfaction within the team – in those making the decisions and in those effecting change through the provision of high quality data.

I have already written articles on the subject of ensuring good data quality and it remains the key to unlocking many opportunities. It is still more about people and process rather than some silver bullet technology. As such, it is a very low-cost strategy with great long term benefit and when we return to some kind of normality, this strategy will help boost production, reduce lifting costs, reduce flaring emissions and better focus maintenance spend.

The very same levels of collaboration and ownership that have successfully been applied to improving production efficiency, can help engage frontline teams in the need to ‘chase every dollar’.



It is crucial that someone drives the process and you are obviously better off with an enthusiastic, experienced and committed driver, rather than  someone who has been handed the job, but would rather be doing something else. This “driver” is responsible for getting all participants to do their bit well and on time. Whether it be allocating daily losses correctly and with sufficient detail, each day (not at the end of the week), or simply attending the review meetings as a priority, rather than not being able to make it because something “more important” has come along. If driven well, the process becomes part of the normal routine.


Ensuring good quality, reliable data is a process in itself. Here are a few example questions from our checklist for you to consider:

  1. What processes are in place to identify and communicate the maximum production levels that should be attainable day by day? How effective are they?
    2.      How have you communicated the importance of effective loss management and reduction to your team?
    3.      Are losses recorded on a daily basis?
    4.      Are the teams clear around expectations for completing Root Cause Analyses and closing actions?
    5.      How effective are the RCA’s in identifying actual root causes?
    6.      How frequently do your onshore and offshore teams meet to review loss events and to identify improvement actions?
    7.      Are your loss reduction efforts delivering the results you want?

Next Steps?

We are fortunate that the lead coach on the above programme with our key client continues to work closely with us to ensure we are able to provide the very best support and advice to both new and existing clients. In these difficult times, we are more than happy to meet with you (virtually) to discuss ways in which your own process can be focused on the most valuable areas that are currently providing the greatest challenges to your business.

Please contact us to arrange a no obligation meeting to discuss your current process and where it could be further enhanced. We can help walk you through the full checklist and advise on best practice.

If you would like an Excel version of the full checklist or any other information, please just send me an email or give me a call.

Neil Hardy

+44 (0)7767 890636