Big Data in Subsea Solutions

(1)

Big Data in Subsea Solutions

Subsea Valley Conference 2014

Telenor Arena, Fornebu, April 2-3 Roar Fjellheim, Computas AS

(2)

Computas AS - Brief company profile

• Norwegian IT consulting company providing services and solutions for work processes, business systems and knowledge-based collaboration • 280 highly qualified project managers, software architects and

developers, and business consultants • Large customers in government

and private sector, including the oil & gas industry

• 1985 spinoff from DNV, Høvik • Located at Lysaker,

Stavanger and Romania

(3)

Computas - Solutions and services

• Business process management

• System architecture and integration

• Software engineering services

• Integrated operations (CODIO)

• Compliance solutions (UCMS™)

• Big Data - Information Management

• Knowledge management services

• Consulting and project management

(4)

Outline

• What is Big Data?

• Big Data in Oil & Gas

• Subsea Applications

• Big Data Enablers

• What’s next?

(5)

What is Big Data?

Gartner’s definition: “Big Data is highvolume,

-velocity and -variety information assets demanding innovative forms of information processing for

(6)

Big Data – Drivers and enablers

• The world now creates 5 Exabyte (10

6

_{Terabyte) per 2 days}

(= all data created from dawn of civilization to 2003)

• The Internet and WWW – 1/3 of world’s population online

• The Internet of Things (IoT) – Sensors everywhere

• How will society and industries be able to manage and benefit

from this avalanche of information?

• Rapid advances in digital technologies

• Smart algorithms and intelligent machines

• New business models

(7)

Digitalization of field operations

Integration of people, process and technology for faster and

better decisions, based on real-time data and integrated work

processes

• Smart sensors, downhole etc. • High bandwidth networks • Simulators and models • Advanced optimization • Data visualization

• Higher levels of automation • Offshore/onshore workflows

(8)

Subsea challenges and Big Data opportunities

• The “usual suspects”: Longer, deeper, colder, …

• HSE, reliability, cost and efficiency ever more important

• Increasingly sophisticated machinery deployed subsea

• Big Data opportunities:

• Condition Based Monitoring and Maintenance

• Integrated Production Optimization

• Enhanced Logistics Support

(9)

Condition based maintenance (CBM)

• Technical integrity - Strict operational and regulatory requirements • Inspection, maintenance and repair - major OPEX drivers

• CBM requirements

• Continuous analysis and diagnostic of equipment sensor data (descriptive analytics)

• Model-based prediction of probable failures and remaining equipment life time (predictive analytics)

• Planning (re-planning) and optimization of inspection and intervention activities (decision analytics)

• New business models for operator – supplier relationships, cf. how the auto industry uses remote car monitoring

(10)

Example - Router module leakage detection

Cause: Fault in fiber penetrator in router module

Effect: Leakage into module leading to communication failure

Mitigation: CPM identified increased internal pressure due to leakage 3 months

prior to communication issues

Action: Router module changed out in planned intervention campaign

Condition indicator

3 months from CPM detection to automatic switch over

Pressure B Normal

(11)

Big Data enabler - Data Science

• How to extract knowledge from data in order to better

understand, predict and decide

• Predictive modeling • Event classification • Semantic analysis • Data mining • Visualization • Machine learning • Decision optimization • Smart Algorithms!

(12)

Example - Decision network for drilling

12

• Based on data from sensors and other sources

• Predicts and simulates

consequences

of different decisions

• Recommends action with highest expected value

(13)

Integrated production optimization

• Daily well-related decisions to optimize production

• Goal: Fully utilize production and process system capacity • Multi-well, cannot optimize single wells in isolation

• Constrained by

• Reservoir properties (changing) • Technical layout and capacities

• Enablers

• Increased instrumentation and data rates allows better models • Improved control mechanisms -

Choking, lifting, routing

• Result

• More frequent, optimized control

(14)

(15)

Big Data enabler – New IT frameworks

• Big Data Volume and Velocity

• Parallel computation

• MapReduce

• Hadoop

• Real time data processing

• In-memory data management

• Stream processing

• Intelligence engines

• Complex event processing (CEP)

(16)

Enhanced logistics support

• ELH - EPIM Logistics Hub

• A common platform for operators and suppliers to exchange logistics events, e.g. container movements

• EPIM is a association of companies operating on the Norwegian

Continental Shelf, creates common solutions with a 5x advantage over individual solutions

• The objective is to trace all containers going in and out to facilities on the NCS, improving efficiency, reliability and economy of logistic movements

Supplier

Supply Base Operator

(17)

Big Data enabler – Semantic technology

• Big Data Variety

• Structured and «unstructured» data

• Many different data types and data sources

• Large scale Information Management

• Relational view of data

• Simplifies complex data models

• Supports meta-data management

• Enables data integration

• Based on open, international standards

(18)

A look ahead - Autonomous subsea systems

• Future subsea systems will be required to operate for extended periods of time without human guidance

• Autonomy, the ability to to self-diagnose and repair, and to plan (and re-plan) actions based on high-level goals, using Big Data and related technologies

• Autonomy already exists in selected areas, like ROVs for pipeline inspection, but will

Big Data in Subsea Solutions