DATA MATURITY ASSESSMENT

The Oil & Gas Technology Centre recently published a Digital Landscaping Study in conjunction with the Oil & Gas Authority and the industry's Technology Leadership Board.

The study investigated how data from topsides production and operations equipment is being used to improve production efficiency and maintenance planning and to reduce operational costs. You can read the full report here.

A number of recommendations came out of the report and a useful industry tool was developed to assess the overall status of how data analytics technology is used on an asset to improve reliability and maintenance performance.

As shown in the chart below, the report found that the average data maturity of UKCS assets involved in the study was between 2 and 3 (scored out of 5) with exemplars within the basin scoring in the range of 4 to 5. You can find out how your asset compares using the interactive tool below.

Potential Value from Data.jpg

FIND OUT HOW YOU COMPARE

Use the radio buttons below to select the most relevant option and then click the ‘Plot’ button to see how your asset compares to the UKCS average and the North Sea exemplars. Please note that no data is captured from this tool. If you require any guidance, please download the Frequently Asked Questions.

DATA MATURITY ASSESSMENT TOOL

Asset:
Breadth of data usage
5
Integrating unstructured data (inspection reports, imaging, etc.)
4
Integrating additional structured data (production, operations, environmental, etc.)
3
Current historian/sensor data
2
Historic historian/sensor data
1
Little or no regular use of data
Data technologies & methods
5
Optimisation (prescriptive supplemented with AI and machine learning)
4
Prescriptive (applied data science combined with domain expertise )
3
Predictive (packaged analytics/ software - forward projections of previous known events)
2
Rule-based (condition monitoring with alarms)
1
Descriptive (queries, reporting, dashboards)
Operational integration
5
Automation of processes, including closed loop learning
4
Continuous insights, feed into engineers' daily work
3
Alerts passed to human decision makers
2
Selective reports feed human decision making
1
All analytical work offline, discrete from operations
Timeliness
5
Ahead of time (optimising approach to operations and maintenance)
4
Ahead of time (predicting the onset of faults and failures before alerts/alarms)
3
Realtime (interventions in response to alerts/alarms)
2
Ad hoc (interventions based on periodic inspections/readings)
1
No forewarning/anticipation of issues
Scope
5
Process system (equipment & process, operations, interdepency of connected systems)
4
Process system (equipment & process)
3
Equipment across system
2
Select equipment
1
Aggregate view only, no consideration of individual machines
Delivering value
5
A proven core initiative in production and efficiency of related operations
4
Measurable improvements in production, business case to do more
3
Value hard to attribute due to human steps in decision process
2
Appreciation of potential value, no hard figures
1
No measurement, no appreciation of potential value