Transferring Analytics into Oil & Gas
Nick Clarke – Head of Analytics, Tessella
Powerful stories of the unexpected crossover of data analytics
techniques between industry sectors
Analytics Technology Transfer Across Industries
Increasing volume and complexity of data
New ways forward can be found in unexpected places
Outside Oil and Gas
Questions we may want to answer
Oil & Gas context Wider context
Is this pump close to failing whilst in active service?
Is this train close to failing whilst in active service?
When should I replace my drill bit
to ensure expected progress?When should I maintain my train in order to maintain expected service?
Is my drilling operation performing as expected?
Is my radioactive waste vitrification plant performing as expected?
Is rig operator behaviour adhering to safety measures?
Is the train driver behaviour adhering to safety regulations?
Operational
Questions we may want to answer
Oil & Gas context Wider context
What is the profile of the rock formation we are drilling into?
What is the threat profile of the area of sea we are sailing into?
How can I adapt my seismic data to get better formation resolution of this region?
How can I adapt my radar data to get better threat resolution of this region?
Based on available reporting data, which out of this group of wells in my field are showing highest risk of under performing?
Based on available reporting data, which out of these companies are showing highest financial risk and need closer inspection?
Planning
Webinar Agenda• The right environment
Making analytics technology transfer possible• Crossing Sector Boundaries
Transferring Analytics technology between different industries
• Crossing internal organizational boundariesTransferring Analytics technology within the same company
Webinar AgendaThe right environment
Making analytics technology transfer possible• Crossing Sector Boundaries
Transferring Analytics technology between different industries
• Crossing internal organizational boundariesTransferring Analytics technology within the same company
Mapping analytics solutions
Origin DomainKnowledge
(context)
Available Data
Math & Statistics
Knowledge
Mapping analytics solutions
Origin DomainKnowledge
(context)
Available Data
Math & Statistics
Knowledgespecific solution
Mapping analytics solutions
Origin DomainKnowledge
(context)
RequiredData
Math & Statistics
Knowledgegeneralized
solution
Mapping analytics solutions
RequiredData
Math & Statistics
Knowledgegeneralized
solution
New DomainKnowledge
(context)
Mapping analytics solutions
New DomainKnowledge
(context)
NewAvailable Data
Math & Statistics
Knowledge
Mapping analytics solutions
New DomainKnowledge
(context)
NewAvailable Data
Math & Statistics
Knowledgerefine
Mapping analytics solutions
New DomainKnowledge
(context)
NewAvailable Data
Math & Statistics
Knowledgenewspecific solution
Automated Image AnalysisGovernment
Facial Recognition
MedicineDigital Pathology
Oil & GasDrill Bit Damage/Wear
ConsumerDog Coat Condition
Webinar AgendaThe right environment
Making analytics technology transfer possibleCrossing Sector Boundaries
Transferring Analytics technology between different industries
• Crossing internal organizational boundariesTransferring Analytics technology within the same company
Radar tracking techniques• Huge amounts of data, but very noisy• Tracks a large numbers of targets simultaneously• Extract information of interest quickly from mass of data
– Requires robust, automated tracking algorithms
The complete package• Bayesian filters for new track initiation from clutter
• Maximum likelihood solution for optimal association between new measurements and existing tracks
• Extended Kalman Filter for optimal tracking oftarget position and velocity
Radar technology transfer – example 1/4
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Human hair growth tracking
Direct measurement to track pain signal transmission along nerves
microneurography
Radar technology transfer – example 2/4
Automated acoustic signal processing
Remote detection of asset integrity failure in radioactive waste processing
Radar technology transfer – example 3/4
Competitive intelligence on gear ratios – optimal fusion of available knowledge
Radar technology transfer – example 4/4
LWD and MWD rig telemetry data• Noise reduction• Filter out and track key features of interest
Applying analytics to Oil & Gas – 3/3
Webinar AgendaThe right environment
Making analytics technology transfer possibleCrossing Sector Boundaries
Transferring Analytics technology between different industries
Crossing internal organizational boundariesTransferring Analytics technology within the same company
Technology Transfer Within A Company:Crossing organizational boundaries
Ingest & reduce data
2008 2013
Driver performance
Fleet Reliability
Chronic asset reliability issues• Fleet of 50 commuter trains
• Legacy asset base (> 30 years old)
• High cost for every failure (> 40 per month)
• No on-board intelligence, only human fault reporting
• Units overhauled many times
• Original design specifications no longer relevant
• Periodic maintenance ineffective
• Uncontrolled introduction of new problems in the depot
Data driven analytics solution• Fleet Reliability
– A 60% improvement in reliability after 1 year– A further 10% improvement after the second year
• Service Impact – A 60% reduction in cancellations and delays in the first year– This saved the client over £1m annually in fines
• Engineering Effort – A 50% reduction in depot time spent keeping this fleet
running, because of a massive reduction in the frequency with which they failed to find the fault during an inspection
data
Trains are highly individual• In the past, expert knowledge from specialist
maintenance teams allowed each train to be understood and maintained as an individual
• Modern engineering teams are much smaller
• Expert knowledge has been replaced by guesswork and overreliance on book values. Old trains are too individual for this to work
• The high rate of train failures is a result of engineers making the wrong interventions, rather than specific component failure.
• The use of analytics provides once more the knowledge required to understand each train and its components as an individual.
Driver are individuals too!• Automated driver analytics
– Measurement-driven analytics for every journey replaces infrequent manual inspection
– Early warning of falling standards
– Personalised training programmes
• Driver safety metrics– Speeding through restrictions– Safe approach to red signals– Automatic activation of protective braking – Incorrect door release
• Population analytics– Improve the driving crews collectively as a team
Oil and Gas applicationsStaff: adherence to safety standards and operational performance• drill operators, rig operators• maintenance and inspection regimes, hazard management
Webinar AgendaThe right environment
Making analytics technology transfer possibleCrossing Sector Boundaries
Transferring Analytics technology between different industries
Crossing internal organizational boundariesTransferring Analytics technology within the same company
Analytics Technology Transfer
Origin DomainKnowledge
(context)
Available Data
Math & Statistics
KnowledgeO&G
solutions
Questions ?Powerful stories of the unexpected
crossover of data analytics techniques between industry sectors
Transferring Analytics into Oil & Gas
Nick Clarke – Head of Analytics, Tessella
Follow me: @Analytics_Lab
http://blog.tessella.com/category/inside-the-analytics-lab/