Transferring Analytics into Oil & Gas: Powerful stories of the unexpected crossover of data analytics techniques between industry sectors

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

Analytics Technology Transfer

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



Mapping analytics solutions

Origin DomainKnowledge

(context)



(context)

Available Data



(context)

Available Data

Math & Statistics

Knowledge



(context)

Available Data

Math & Statistics

Knowledgespecific solution



(context)

RequiredData

Math & Statistics

Knowledgegeneralized

solution


RequiredData

Math & Statistics

Knowledgegeneralized

solution

New DomainKnowledge

(context)


New DomainKnowledge

(context)

NewAvailable Data

Math & Statistics

Knowledge


New DomainKnowledge

(context)

NewAvailable Data

Math & Statistics

Knowledgerefine


New DomainKnowledge

(context)

NewAvailable Data

Math & Statistics

Knowledgenewspecific solution

Analytics Technology Transfer Examples

Automated Image AnalysisGovernment

Facial Recognition

MedicineDigital Pathology

Oil & GasDrill Bit Damage/Wear

ConsumerDog Coat Condition

Directional ControlMedicine

Steerable NeedlesOil & GasGeosteering


Making analytics technology transfer possibleCrossing Sector Boundaries



Bayesian methods in Radar tracking

Radar has evolved

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


Automated acoustic signal processing

Remote detection of asset integrity failure in radioactive waste processing


Competitive intelligence on gear ratios – optimal fusion of available knowledge


Applying analytics to Oil & Gas – 1/3Image based drill bit condition assessment

Seismic data• Inversion• Data reduction

Applying analytics to Oil & Gas – 2/3

LWD and MWD rig telemetry data• Noise reduction• Filter out and track key features of interest

Applying analytics to Oil & Gas – 3/3




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 applicationsAssets: reliability and performance• pumps• compressors• motors• etc …

Oil and Gas applicationsStaff: adherence to safety standards and operational performance• drill operators, rig operators• maintenance and inspection regimes, hazard management




Crossing internal organizational boundariesTransferring Analytics technology within the same company

Analytics Mantra

Analytics Technology Transfer


(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/




Data & Analytics

Transferring Analytics into Oil & Gas: Powerful stories of the unexpected crossover of data analytics techniques between industry sectors