Tips to Perform a Ram Study Webinar Presentation_tcm4-539661 (1)

Victor Borges, RAM Product Manager

Tips to perform a RAM study

DNV Software - Webinar materialFeb 28 2013

© Det Norske Veritas AS. All rights reserved.


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AgendaWhat is advanced RAM analysis?Quantitative picture of PerformanceDNV solutionTop 5 tips to perform an effective RAM Study



“Defeat is ensured for the one who beforehand does not have all things in order, people call it misfortune. While victory is ensured for the one who beforehand has learned to be prepared, people call it luck.”

Roald AmundsenWe call it RAM!

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DNV calls it…



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What is Advanced RAM Analysis?



What is Advanced RAM analysis?

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What is Advanced RAM analysis?

RAM is a methodology used to predict asset performance for a given configuration in terms of Reliability, Availability and Maintainability

Our products go beyond traditional RAM analysis by adding capabilities related to operations tailored to the Oil and Gas industry which provides as result utilisation and production efficiency.

Takes into consideration all factors affecting production in order to forecast performance over the life of the asset

Examples of factors are Equipment Performance, Redundancy, Maintenance Strategies, Logistics, Demand Requirements etc.



Simulation How it works

- The user specifies a configuration in terms of equipment reliability and dependencies, as well as the associated asset operations

- By discrete event simulation using a Monte Carlo method, a number of life cycles given the specified configuration are simulated

- By performing a large enough number of life cycle simulations a reliable prediction of the asset performance is produced

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The benefits with simulation are- It can be used with process complexities

and uncertainties where exact analytical solutions are not possible

- It allows for easy extension of the analysis to include large inventories & sensitivity studies (‘what-ifs’)

- It highlights the weak links in the configuration (equipment criticality) and allows you to optimise asset configuration and operations



Why are we doing this?

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Maximizing Plant efficiency / reliability levels Product generation/throughput

Minimizingmanning costsmaterials costsmaintenance work load transportation and support downtime affecting revenue/operating costs

whilst

Maintaining contractual nominations safety case requirements

and



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Quantitative picture of Performance



Quantitative Picture Of Performance

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Reliability Equipment performance data

(failure frequencies) System configuration

Maintainability Maintenance resources Shift constraints Mobilization delays Spares constraints

Availability Equipment/System uptime



Availability

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Pump onPump failed

Pump onPump failed

Pump on

Actual

Pump always on

Potential

Time

%




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Operability Plant interdependencies Plant re-start times Production/demand rates Storage Size Tanker Fleet and Operations

Production Efficiency

Achieved production Production losses Criticality Contract shortfalls Delayed cargoes



Production Efficiency (Utilization)

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Time

Production Rate

Pump always on

PotentialVolume

Pump onPump failed

Pump onPump degraded

Pump on

ActualVolume

%




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Operability Plant interdependencies Plant re-start times Production/demand rates Storage Size Tanker Fleet and Operations

Unit Costs/Revenue Product price Man-hour/spares costs Transport costs Discount rates

Net Present Value Lost Profit Opportunity


Achieved production Production losses Criticality Contract shortfalls Delayed cargoes



Operational Expenditure (OPEX) / Lost Revenue

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MaintenanceExpenditure Lost Profit Opportunity

Pump onPump off

Pump onPump degraded

Pump on

ActualVolume

Lost Revenue



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Products



Maros Maintainability Availability Reliability

Operability Simulation program

Tool of choice for analysis of upstream and LNG assets for the past 25 years

In use since 1984 with continuous development efforts

Provides functionality for modelling of all issues pertinent to process equipment and units in the upstream market

Features include time varying production flow profile, multiple products, production recovery techniques, tanker export operations, financial modelling and more

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Taro Total Asset Review & Optimization

Specialised for modelling of refinery complexes

Developed since in 1995

Provides capability for the integration of shipping and storage into performance models

Features include multiple streams, unit interdependencies, yield rates, blending rules, advanced storage and more

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Top 5 tips to perform an effective RAM Study



Top 5 tips to perform an effective RAM Study1. Definition

- Define the objectives and scope- Define boundaries for the study

2. Collecting- Collate all required data

3. Preparation- Prepare a study basis- Build the model in stages- Verify model operation at each stage

4. Results- Compare over all results with expectations- Perform sensitivity analyses- Generate reports

5. Document and archive model files

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Definition



Define Objectives and Scope Most common objective is “what production efficiency can we expect from this

design”

Some other examples:- What reliability should we specify for the export compressor?- What platform availability gives an acceptable overall security of oil supply?- What is the most cost effective way to improve security of gas supply?- What is the impact of alternative maintenance strategies?

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Define Boundaries For The Study Model core system

Can external influences be synthesised or must they be explicitly included

Can we estimate the influence of external factors? If so we can decide which to include and which to exclude

A good model contains the minimum amount of detail that still yields a valid answer i.e. most complex is not necessarily the best

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Collecting



Collate All Required Data What is unique to this study??

Reservoir data

Gas sales agreements

Basis of design document

PFDs, P&IDs, schematics, cause and effect charts

Maintenance logistics and strategies

Reliability data

Etc……….

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Reliability data Getting the right data is a crucial step in a RAM Study

Sources- Generic Reliability Data- In-House Reliability Data- OREDA Offshore Reliability Data- AEA Reliability Databank- European Reliability Industry Data Bank Handbook (EIReDA)- RAC Reliability Data books- CCPS Process Equipment Reliability Database (PERD)- Cox, Lees & Ang

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Generic data Versus In-house data

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Data Sources Advantages Disadvantages

Generic-published Easy to obtain Non-specific boundaries and

assumptions unknown

Generic-applied Can be produced relatively

quickly

Requires detailed knowledge of proposed application and

factors influencing reliability

Collected-maintenance data Uses existing records

Many not have data in the correct form or detail required,

or sufficient amount of data

Collected-formal scheme

Very detailed reliability parameters can be obtained on

specific items and in correct form

Long term project in order to collect sufficient experience



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Preparation



Prepare The Study Basis Assumptions

Objectives

Description of model to be built

Reliability Block Diagrams (RBDs)

Data Register

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Typical Model Development Path

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Final model runs

Run model, review results, reconfigure

Operational considerations

Maintenance strategies

Maintenance resources - manpower, spares, tools

Equipment configuration and reliability data

Flow/Reservoir Deliverability



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Results



Compare Results With Expectations Can the results be explained?

Are there any areas of unexpectedly low or high criticality?

If necessary generate and check log files to investigate further

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Analysis Results Availability (uptime)


Production Statistics

Complex / Platform / Equipment Criticality

Frequency of Shutdowns

Maintenance Resource Expenditure

Utilization

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RAM Applications (Study Types) Conceptual Design Screening Studies

Facilities Optimization

Detailed Engineering

Development of Operations Reference Plan / Asset Reference Plan

Maintenance Strategy Evaluation (RCM)

Manning Studies

Workload Assessments (e.g. Vessel utilization)

Risk Analysis (e.g. Well Risk)

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RAM Applications (Asset Types) Subsea (Remote & Deep water)

Normally Unmanned Installations (NUIs)

Minimum Manned Platforms

Central Processing Facilities

Onshore Oil & Gas Processing Terminals

LNG Plants

Refinery Unit and Site Optimisation

Co-generation Power Plants

Petrochemical Plants

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Life Cycle Performance AnalysisAnalysis is not just about producing one availability figure, which can then be quoted

as the performance figure for the development.

Analysis is about a picture of performance (transparency) which the project team can use to make decisions

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Life Cycle Performance Analysis Performance assessed to a number of criteria - build a picture of performance

Transparency of performance criteria leads to confidence in the assessment

Analysis is best in a comparative assessment of competing designs or operating scenarios

Utilize sensitivity scenarios to understand risk or uncertainty in the performance figures

Where absolute figures are required some degree of calibration or benchmarking is required

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For further interest, trial version, software demo or a quotation please do not hesitate to contact us:

[email protected]

Best regards,DNV Software



Safeguarding life, property and the environment

www.dnv.com

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Tips to Perform a Ram Study Webinar Presentation_tcm4-539661 (1)