WO2015110499A1

WO2015110499A1 - Method and system for condition and performance based maintenance (cpbm) of oilfield equipment

Info

Publication number: WO2015110499A1
Application number: PCT/EP2015/051198
Authority: WO
Inventors: Claudia Patricia ZULUAGA
Original assignee: Shell Internationale Research Maatschappij B.V.; Shell Oil Company
Priority date: 2014-01-24
Filing date: 2015-01-22
Publication date: 2015-07-30

Abstract

A system for Condition and Performance Based Maintenance (CPBM) of oilfield equipment at one or more a hydrocarbon fluid production and/or processing plants (1-3) comprises: - measuring lubrication, reliability, performance, vibration, emission and other CPBM Key Performance Indicators (KPIs) of the oilfield equipment; - supplying the measured CPBM KPIs to an automated reliability engine that is equipped with a dual level reliability engine visualisation dashboard (4-16) comprising a CPBM KPI dashboard that displays the measured CPBM KPIs at displays (11-16) and a high level CPBM dashboard (4-6) that shows for each plant (1-3) a single high level collective Condition and Performance Based Maintenance (CPBM) score (70% for plant 1, 30% for plant 2 and 50% for plant 3) that is an accumulation of all CPBM KPIs with weight factors associated with the criticality of the CPBM KPIs, thereby providing a plant operator a CPBM dashboard (4-16) that provides a clear insight of upcoming CPBM requirements both at a high and at a more detailed level.

Description

METHOD AND SYSTEM FOR CONDITION AND PERFORMANCE BASED MAINTENANCE (CPBM) OF OILFIELD EQUIPMENT

BACKGROUND OF THE INVENTION

The invention relates to a method and system for

Condition and Performance Based Maintenance (CPBM) of rotating and other oilfield equipment that may be used at crude oil and/or natural gas production and/or processing plants .

Condition Based Maintenance (CBM) generally involves complex analysis to determine whether a need for

maintenance arises. CBM is performed after one or more signals show that equipment has a potential to fail and/or that equipment performance is deteriorating.

Developments in the last decades have generated extensive instrumentation for monitoring the condition and performance of equipment and better tools for real time analysis of condition and performance data, which allow expert personnel to advise operators on key process changes and the optimum moment for just in time

Corrective Maintenance; more proactive, less intrusive.

Commercially available Condition Based Maintenance (CBM) systems are the Bently Nevada CBM system and the Meridium Reliability Engine offered by General Electric (GE), and CMMS systems offered by SAP. These known CBM systems manage raw maintenance data and do not predict upcoming maintenance requirements.

There is a need to facilitate the interpretation of Condition Based Maintenance (CBM) data such that

personnel at any level, not solely technical experts, of a crude oil and/or natural gas production and/or

processing plant obtains a fast and easier understanding of Condition and Performance Based Maintenance (CPBM) of the rotating and other oilfield equipment deployed at the plant .

Furthermore there is a need for quantifying a ROI (Return On Investment ) of CPBM benefits and to provide a simple and real time method to report the effectiveness of online and offline monitoring technologies, the

combination of its data with more fundamental raw

reliability calculations and display these values in real time Key Performance Indicators (KPIs) that will allow not only operators at the plant, but managers and directors of the company to obtain one version of the truth in order to make fast decisions and transform the reactive way maintenance is executed into Proactive Maintenance.

Furthermore there is a need for an improved method for Condition and Performance Based Maintenance (CPBM) of rotating and other oilfield equipment at a hydrocarbon production and/or processing plant which can be adequately planned and executed such that downtime of the plant can be minimized and the time periods between any CPBM operations at the plant can be maximized.

SUMMARY OF THE INVENTION

In accordance with the invention there is provided a system for Condition and Performance Based Maintenance (CPBM) of oilfield equipment at a hydrocarbon fluid production and/or processing plant, the system

comprising :

- measuring lubrication, reliability, performance, vibration, emission and other CPBM Key Performance

Indicators (KPIs) of the oilfield equipment;

- supplying the measured CPBM KPIs to an automated reliability engine; and

- providing the automated reliability engine with a dual level reliability engine visualisation dashboard that displays the measured CPBM KPIs together with a single collective Condition and Performance Based Maintenance (CPBM) score that is an accumulation of all CPBM KPIs with weight factors associated with the criticality of the CPBM KPI based on CPBM best practice experiences, which weight factors are stored in the automated

reliability engine, thereby providing a plant operator a dual level reliability engine visualisation dashboard that provides a clear insight of upcoming CPBM

requirements and that induces the plant operator to perform proactive CPBM in a manner that is consistent with CPBM best practice experiences.

The dual level reliability engine visualisation dashboard may comprise high level CPBM displays that may be configured as dials that each display a single collective CPBM or Maintenance Benchmark score as a percentage on a scale from 0 to 100%, wherein 100% indicates excellence in Maintenance strategy and 0% indicates poor Maintenance strategy and urgent need for change of mind set assisting resources to move away from reactive approaches and act more proactively.

The hydrocarbon fluid production and/or processing plant may be part of a cluster of hydrocarbon fluid production and/or processing plants and a collective CPBM dashboard may be provided for the cluster of plants that displays an overview of the individual single collective CPBM factors that each CPBM dashboard generates for each of the hydrocarbon fluid production and/or processing plants .

The hydrocarbon fluid production and/or processing plant may be an onshore or offshore crude oil and/or natural gas production facility.

If the facility is an offshore crude oil and/or natural gas production facility then it may comprise one or more crude oil and/or natural gas production wells that are connected to topside facilities, comprising an assembly of rotating and other oilfield equipment equipped with lubrication, reliability, performance, vibration, emission technologies where information is gathered from the machinery sensors, transducers, meters and others that are mounted on a single floating or seabed mounted offshore platform.

If the facility is an onshore crude oil and/or natural gas production facility then it may comprise one or more crude oil and/or natural gas production wells that are connected to common crude oil and/or natural gas treating and export facilities that comprise an assembly of rotating and other oilfield equipment equipped with lubrication, reliability, performance, vibration, emission technologies where information is gathered from the machinery sensors, transducers, meters and others.

The plant may form part of a cluster of hydrocarbon fluid production and/or processing plants and a sequence of Condition and Performance Based Maintenance

(CPBM) operations may be scheduled and executed in advance on the basis of the number of signals classification being quantified to determine if action is required or not at each plant of the cluster of plants, which sequence may be based on the sequence of single CPBM factors displayed for each of the plants, so that CPBM or Proactive Maintenance is first done for the plant which has the lowest CPBM score and CPBM is done last for the plant which has the highest CPBM score.

These and other features, embodiments and advantages of the method and system according to the invention are described in the accompanying claims, abstract and the following detailed description of non-limiting

embodiments depicted in the accompanying drawings, in which description reference numerals refer to reference numerals shown in the drawing.

BRIEF DESCRIPTION OF THE DRAWING FIGURE 1 shows an example of a dual level

reliability engine visualisation and Condition and

Performance Based Maintenance (CPBM) dashboard according to the invention. DETAILED DESCRIPTION OF THE DEPICTED EMBODIMENT

The bottom section of Figure 1 shows three floating oil and/or gas production platforms 1, 2 and 3 that are each equipped with known online oilfield equipment performance monitoring systems .

The upper section of Figure 1 shows three high level

CPBM displays 4, 5 and 6 that each show an overall CPBM Benchmark score for the oilfield equipment at platform 1, 2 and 3, respectively. The overall Maintenance Benchmark score shown by left hand display 4 for the oilfield equipment at platform 1 is 70%. The overall Maintenance Benchmark score shown by central display 5 for the oilfield equipment at platform 2 is 30% and the overall Maintenance Benchmark score shown by right hand display 6 for the oilfield equipment at platform 3 is 50%.

Each percentage 70%, 30% and 50%, displayed by the top level displays 4, 5 and 6 provides a single collective Condition and Performance Based Maintenance (CPBM) score for the oilfield equipment at each of the platforms 1,2 and 3, respectively, that is an accumulation of all CPBM KPIs displayed by displays 11-16 multiplied by weight factors associated with the criticality of the CPBM KPI shown by the displays 11-16 based on CPBM best practice experiences, thereby providing a plant operator a dual level reliability engine visualisation dashboard (4-16) that provides a clear insight of upcoming CPBM

requirements for each platform 1,2 and 3.

Each of the overall CPBM technology scores 70%, 30% and 50% shown by the top level displays 4-6 for the platforms 1-3 in Figure 1 is based on information about the condition and performance of rotating and/or other oilfield equipment generated by an automated online monitoring system placed offshore or onshore and its calculations run in the reliability engine of which more detailed scores are displayed by the intermediate reliability engine visualization dashboard 10.

In the example shown the intermediate reliability engine visualization dashboard 10 is temporarily

connected to oilfield monitoring equipment at platform 2 and comprises six CPBM KPI displays 11-16 that display more detailed information about the performance and condition of the oilfield equipment at platform 2. The intermediate reliability engine visualisation dashboard 10 may be switched and connected to oilfield monitoring equipment at one of the other platforms 1 or 3 to show the condition and performance thereof. Alternatively the intermediate reliability engine visualisation dashboard 10 may comprise three parallel sets (not shown) of displays 11-16 that simultaneously display more detailed information about the performance and condition of oilfield equipment at each of the platforms 1-3.

In the example shown the intermediate reliability engine visualisation dashboard 10 comprises a first CPBM KPI display 11 that shows emission of the rotating and other oilfield equipment of platform 2, a second CPBM KPI display 12 that shows vibration of the rotating and other oilfield equipment of platform 2, a third CPBM KPI display 13 that shows performance of the equipment of platform 2, a fourth CPBM KPI display 14 that shows reliability of the equipment of platform 2, a fifth CPBM KPI display 10 that shows lubrication of the equipment of platform 2 and a sixth CPBM KPI display that shows an average score of other CPBM Key Performance Indicators (KPIs)for the equipment of platform 2.

The intention of the CPBM KPI displays 11-16 of this intermediate reliability engine visualisation dashboard 10 is to understand the effectiveness of CPBM techniques applied to or health of all rotating and other oilfield equipment used at platform 2 by alert severities from 1 to 4, where 1 is "no attention is required" and 4 means "action should be raised based on analysis".

The calculation to establish the health may be as follows: CPBM Health % (per technology i.e. Vibration, Lubrication etc) = 100 * [1 - (# of points requiring attention (per technology) / Total # of points in the CPBM technology) ] .

In the example shown, the single overall CPBM score displayed by each of the dashboard displays 4, 5 and 6 for each of the platforms 1-3 may vary from 0% to 100%, where 100% means excellent or top Maintenance performance and 60% and below means bottom Maintenance performance.

Since in the example shown the overall CPBM score for platform 2 is 30%, this will induce the managers and supervisors of the platform 2 to address behaviours of personnel or plan or revisit the maintenance strategy at platform 2.

The review of the maintenance strategy will address issues and bad actors in order to minimize downtime of each platform 1-3 for scheduled and unscheduled

maintenance of rotating and other oilfield equipment, which may involve downtime due to partial or complete interruption of oil and/or gas production by the platforms 1-3 and will maximize the time period between any

scheduled and unscheduled maintenance operations at the platforms 1-3 amongst other multiple important factors in Maintenance approaches .

The "other CPBM-KPIs dial" display 16 at the right hand side of the reliability engine visualisation

dashboard 10 may display an average of a variety of planned or corrective work orders raised proactively as a result of the CPBM effectiveness. The display 16 may be linked to other displays (not shown) that provide more detailed information about the underlying series of the other CPBM Key Performance Indicators (KPIs) including bottom line benefits for rotating and other oilfield equipment as a result of practising Proactive Maintenance. These other CPBM KPIs may be displayed in different units i.e. as a %, $ or just as a number with an arrow (up-green or down-red) and may be based on the following underlying other CPBM KPIs that are described in the following paragraphs A-D :

A) Reliability Measuring CPBM KPIs:

The following CPBM KPIs may be utilized to measure the Reliability of the rotating and other oilfield equipment in the Proactive CPBM method according to the invention.

The following CPBM KPIs 1 to 5 will assist operators to identify the frequency of failures, repairs and overhauls :

1. Failure Mode Pared to Frequency Analysis:

Provides the ability to identify most prevalent failure modes for Assets. Calculation is based upon SAP Notifications and Failure Mode Entered.

2. Failure Mode Pared to Cost Analysis:

Provides the ability to identify the failure modes which have the most Work Order Cost. Calculation is based upon SAP Notification Failure Mode and

associated SAP Work Order Cost.

3. Mean Time between Failures:

Provides the average time between failures over the last 12 month period. Calculation is based upon SAP

Notifications with Breakdown Flag selected and

Malfunction Start Date with Request Type M3 & Z3. Also includes Work Orders where Activity Type includes 72WC, 72FC, and 72EC.

4. Mean Time between Repairs:

Provides the average time between failures over the last 12 month period. Calculation is based upon SAP Notifications with Malfunction Start Date with

Request Type M3 & Z3. Also includes Work Orders where Activity Type includes 72WC, 72FC, 72EC.

5. Mean Time Between Overhaul:

Provides the average time between overhaul over a 12 month period Calculation is based upon SAP Work Orders with Activity Type = PSE Servicing/Overhaul and Work Order Actual Start Date.

B) Maintenance Measures:

The following CPBM KPIs may be utilized to measure the performance of the various aspects of the Proactive

Maintenance program.

These CPBM KPIs will help to identify the maintenance costs, percentages of the various maintenance activities and understand how shell is moving to a more proactive maintenance culture. "Identification of corrective activities before breakdown lowers total cost".

1 Percentage of Total Maintenance Man Hours driven by Proactive Maintenance/CPBM .

This CPBM KPI provides the maintenance man hours driven by CPBM as a percentage of the total maintenance man hours. Calculated from SAP Work Orders where Notifications were reported by CPBM. A higher is better than a lower score.

2 Cost of Corrective activities driven from CPBM. This CPBM KPI provides the total cost for all Corrective

Work which was driven from the identification of potential malfunctions by Machine Diagnostics Services (MDS) or CBM team analysis via CPBM technology. Calculation of this CPBM KPI is based upon Work Order Costs which were initiated by CPBM.

3 Number of Corrective Activities driven from

CPBM.

This CPBM KPI provides the total number of Corrective Work which was driven from the identification of potential malfunctions by MDS via CPBM. Calculation is based upon the number of Notifications which were reported by CPBM only .

4 Average Cost of Corrective Activities driven from CPBM.

This CPBM KPI provides the ability to track the average cost of corrective maintenance driven by CPBM over time. Calculation is based upon Work Order Cost which is initiated by CPBM Program

5 Percentage of Corrective Work Driven from

PdM/CPBM.

This CPBM KPI measures the amount of Corrective Work which is identified by the CPBM Program vs. all other Identified Corrective Work. Calculated from SAP Notifications which were reported by CPBM

6 Maintenance Cost as a percentage of Replacement

Asset Value (RAV) .

This CPBM KPI demonstrates the amount of annual

maintenance spend as a percentage of the Asset Replacement Value. It is calculated from Work Order Costs and compared to documented Platform RAV Values; to demonstrate

reduction of Maintenance expenditure before and after CPBM/Proactive Maintenance; to encourage Maintenance to invest in predictive Maintenance technologies and full Proactive Maintenance program across the board.

C) CPBM ROI Measures:

The following CPBM KPIs may be utilized to measure effectiveness, value and return on investment for the CPBM program. These CPBM KPIs will help identify the number of faults measured by the CPBM team, the criticality and consequence of potential failures and the estimated benefit for the corrective work generated from the CPBM program.

1 Average Cost of Corrective work from CPBM

Program vs. Average Corrective cost from all alternative programs (Corrective & Preventive) : Measures the average costs associated with corrective work reported by the CPBM program relative to the average costs from all alternative sources of corrective work. Calculated from SAP Work

Order Cost Data based upon where the origination of the SAP Notification to determine if CPBM program is reducing the cost of corrective work through earlier detection of malfunctions .

2 Total Financial Costs which were mitigated through implementation of CPBM Activities: Measures all of the financial cost which was identified by the CPBM Team and created Corrective Work which was completed.

Calculated by evaluating all of the SAP Work Order cost where the corrective work was completed (TECO) .

2a CPBM Financial Cost avoidance: Measures the potential financial risk from faults identified and implemented by the CPBM Program. Calculated from CPMT Risk Evaluation and CPBM Recommendation Completion.

3 Risks Mitigated through the implementation of CPBM Activities: Measures risk (Asset Deferral,

Environmental, People & Reputation) for CPBM identified faults that were implemented through corrective

activities. Calculated from risk values populated as part of the CMPT Process when corrective work is generated as SAP Notifications and completed (TECO) .

4 Unmitigated Risks identified by CPBM program:

Measures risk (Asset Deferral, Environmental, People, & Reputation) for CPBM identified faults that have not been implemented through corrective activities. Calculated from risk values populated as part of the CMPT Process when corrective work is generated as SAP Notifications but has not reached a completed state (TECO) .

5 Number of documented CPBM events that did not require follow up work: Measures all the events potential malfunctions of an asset managed via CPBM that did not become corrective work and therefore (not captured in SAP) and resolved without maintenance engagement. Calculated by measuring the number of CPBM events which did not progress to a CPBM Recommendation.

6 Number of root cause of problems eliminated: To understand the CPBM program's ability to identify mechanical faults and solve root causes. Measures the number of CPBM Recommendations which drove a root cause analysis and identified a resolution to the root cause of the malfunction. Calculated by evaluation of the CPBM Recommendations where the Root Cause was eliminated

7 Total RCA Hrs invested to eliminate root causes: To understand the CPBM program's ability to identify mechanical faults, solve root causes and the associated cost. Measures the number of hours captured on the CPBM Recommendations which drove a root cause. Calculated by evaluation of the CPBM Recommendations where the Root Cause was eliminated

8 Total Mitigated Financial Risks through RCA:

Measures the total amount of potential mitigated risks by addressing the root causes of mechanical faults.

Calculated by assessing the potential financial risk identified in the CMPT process where Root Causes where eliminated.

9 Mitigated Safety Risk as a result of PdM/CPBM: Measures the amount of Safety Risk identified through the CPBM program which generated corrective work and was completed. To quantify the amount of Safety risks reduced from the implementation of the CPBM recommendations.

Calculated from the CMPT People Risk Score which is defined as part of the SAP Notification generation process .

9a Avoided Intrusive Work: To understand the amount of faults being detected which did not require intrusive work or presence of people thus reducing people risk.

Calculated by measuring the number of Severity 3 and Severity 4 events

10 CPBM Analyst Hours vs. Total Maintenance Hours: To understand the percentage of CPBM hours to total

Maintenance hours. Measures the relative amount of time CPBM Team spends against the overall maintenance

activities. Calculated by comparing the CPBM Analyst hours to all maintenance hours .

D) Availability, Downtime and Capability Measures (not shown in figure 1) 1 Downtime: Measurement of equipment downtime hours as monitored directly from the CPBM program.

Calculated on downtime hours from equipment instrumented and monitored by the CPBM Dashboard 6 to 9 and reviewed by the CPBM Team.

2 Planned Downtime: Measurement of planned equipment downtime hours as monitored directly from the CPBM program. Calculated from Downtime hours on equipment instrumented and monitored by CPBM dashboard 4-16 and reviewed by the CPBM Team and flagged as a planned

downtime event .

3 Unplanned Downtime: Measurement of unplanned equipment downtime hours as monitored directly from the CPBM program. Calculated from Downtime hours on equipment instrumented and monitored by CPBM dashboard 4-16 and reviewed by the CPBM Team and flagged as an unplanned downtime event .

4 Potential Downtime Impact: Measurement of the potential impact of equipment downtime which can impact the production of the platform in Barrels of Oil

Equivalent. Calculated by evaluating the Downtime hours against the equipment which can interrupt platform

production accounting for production buffering.

5 Operational Availability: Percentage time available for operation of the equipment monitored by CPBM when all downtime (Planned, Unplanned and other) is included in the analysis time period. Calculated from downtime identified from instrumented equipment events which are reviewed and validated by the CPBM team.

6 Technical Availability: Percentage time

available for operation of the equipment monitored by CPBM when external or other operational factors which led to downtime are not included in the analysis time period. Calculated from downtime identified from instrumented equipment events which are reviewed and validated by the CPBM team.

7 Technical Maximum Availability: Percentage time available for operation of the equipment monitored by CPBM when planned downtime is not included in the analysis time period. Calculated from downtime identified from

instrumented equipment events which are reviewed and validated by the CPBM team.

The CPBM Dashboard 5-10 according to the invention may also offer the capability to retrieve further CPBM KPIs details from the Reliability Engine in terms of plots (Trends, Pie, Paretos and/or other charts) .

The CPBM dashboard 5-10 according to the invention may be integrated with commercially available Condition

Based Maintenance (CBM) systems, such as the Bently Nevada online monitoring system and the Meridium Reliability Engine offered by General Electric (GE) , and CMMS systems offered by SAP .

The following tools may provide input to the CPBM dashboard 5-10 according to the invention.

A. An export tool coding between the Bently Nevada Online monitoring System and the Meridium Reliability Engine, developed by GE to push the health status and technology signals to understand online CBM status index/gauges as shown in Figure 1, section 2 of the CPBM Dashboard 16.

B. The embedded CMPT process in the automated CPBM work flow and the Proactive Maintenance Key Performance Indicators developed to measure Online Reliability as a combination of information coming from the Bently Nevada online monitoring system and the SAP system. C. The interface coding between the Meridium Reliability Engine and the SAP CBM system, still under development, to automate Zl notifications and work order reporting .

D. All the rule packs and Bently Nevada CBM System enhancements that have been developed under the CPBM project except the rule packs shown in Table 1.

industrial

gas turbines

Table 1

Optionally the fifth display "CPBM-Maintenance

Benchmark" of the web dashboard 16 may display a high level Maintenance Benchmark Score as a result of

practicing Proactive Maintenance - a visible way for personnel at all levels to realise how they are performing as they embark in the proactive Condition and Performance Based Maintenance (CPBM) or Proactive Maintenance journey.

To come up with a Score or Waiting Factor Score (WF) a spread sheet that summarises in detail the elements required to run a maintenance organisation in a Proactive manner may be adapted and automated in an online CPBM monitoring system. The spread sheet may contain as many tabs as necessary that address the key elements of

Maintenance strategy in an organisation, some of them mentioned below:

CPBM or Maintenance Benchmark

1. The Organizational Culture and PRIDE in Maintenance

2. Maintenance Organization, Administration and Human Resources

3. Resources Skills Development and PRIDE in maintenance

4. Operator-Based Maintenance and PRIDE in Ownership

5. Maintenance Supervision/Leadership

6. Maintenance Business Operations, Budget and Cost Control

7. Work Management and Control: Maintenance and Repair

8. Work Management and Control: Shutdowns and Major Overhauls 9. Working-Level Maintenance Planning and Scheduling

10. Shutdown and Major Maintenance Planning/Scheduling and Project Management

11. Manufacturing Facilities Planning and Property

Management

12. Production Asset and Facility Condition Evaluation Program

13. Logistics: Warehouse Operations, Internal Maintenance and/or Repair Operations and Customer Service

14. Materials Management and Procurement

15. Preventive Maintenance and Lubrication

16. Predictive Maintenance and Condition Monitoring

17. Process Control and Instrumentation System Technology

18. Maintenance Engineering Support

19. Safety and Regulatory Compliance

20. Maintenance and Quality Control

21. Maintenance Performance Measurement

22. Computerized Maintenance Management Systems (SAP) And Business System

23. Facilities, Equipment and Tools

24. Continuous Reliability Improvement

25. Criticality Assessment Facilitation and Overall Equipment Effectiveness (OEE)

26. Overall Resources Effectiveness (ORE)

Each of the above elements from 1 to 26 may comprise a tab containing a series of questions pertaining to the organization's opinion, attitude, and processes toward Condition and Performance Based Management (CPBM) or

Proactive Maintenance. An internal audit per asset (i.e. platform 1, 2, 3, etc) may be performed monthly or bimonthly or quarterly or sixth monthly or yearly until the Operating Unit (OU) that manages the platforms 1,2,3, etc. reaches best in class. Each of the questions may be rated with a value from 1-10. The total number of rated points may be summed for each sheet and a percentage ratio may be calculated with the total possible points for each sheet. An overall health percentage may be calculated and displayed at the fifth "Maintenance Benchmark" dial by summing all of the rating points from each of the sheets and calculating a ratio with the total number of points from all of the sheets which then indicates the final score for a particular OU . The rating or score may be displayed at the fifth

"Maintenance Benchmark" Poor<60%, Average 60-69%; Good 70- 79%, Very Good 80-89% and Excellent 90-100%.

In the examples shown the CPBM dashboard 4-16 according to the invention has been described for use with offshore floating oil and/or gas production platforms 1-3, but it will be understood that the CPBM dashboard 4-16 according to the invention may also be used for planning and executing Condition and Performance Based Maintenance (CPBM) operations of rotating and other oilfield equipment at other offshore and onshore oil/ gas and other

hydrocarbon fluid production and or processing plants.

In summary it will be understood that the

invention provides a user friendly method and system for Condition and Performance Based Maintenance (CPBM) of rotating and other oilfield equipment at one or more hydrocarbon fluid production and/or processing plants (1- 3) where sensors measure lubrication, reliability, performance, vibration, emission and other CPBM Key Performance Indicators (KPIs) of the rotating and other oilfield equipment. In accordance with the invention the measured CPBM KPIs are supplied to an automated

reliability engine which is equipped with a dual level CPBM dashboard comprising a reliability engine

visualisation dashboard (10) that displays at least some of the measured CPBM KPIs and a high level CPBM dashboard (4-6) that displays for each plant (1-3) a single high level collective Condition and Performance Based

Maintenance (CPBM) score (in the example shown 70% for platform 1, 30% for platform 2 and 50% for platform 3) that is an accumulation of all CPBM KPIs shown by the displays 11-16 of the intermediate CPBM dashboard 10 with weight factors associated with the criticality of the displayed CPBM KPIs based on CPBM best practice

experiences, thereby providing a plant operator a dual level CPBM dashboard (4-16) that provides a clear insight of upcoming CPBM requirements.

Claims

CLAIMS :

A system for Condition and Performance Based

Maintenance (CPBM) of oilfield equipment at a hydrocarbon fluid production and/or processing plant, the system comprising:

- measuring lubrication, reliability, performance, vibration, emission and other CPBM Key Performance Indicators (CPBM KPIs) of the oilfield equipment;

- supplying the measured CPBM KPIs to an automated reliability engine; and

- providing the automated reliability engine with a dual level reliability engine visualisation

dashboard that displays the measured CPBM KPIs together with a single collective Condition and Performance Based Maintenance (CPBM) score that is an accumulation of all CPBM KPIs with weight factors associated with the criticality of the CPBM KPIs based on CPBM best practice experiences, which weight factors are stored in the automated

reliability engine, thereby providing a plant operator a CPBM dashboard that provides a clear insight of upcoming CPBM requirements and that induces the plant operator to perform proactive CPBM in a manner that is consistent with CPBM best practice experiences.

The system of claim 1, wherein the dual level reliability engine visualisation dashboard is configured to display the single collective CPBM score as a percentage on a scale from 0 to 100%. The system of claim 1 or 2, wherein the hydrocarbon fluid production and/or processing plant is part of a cluster of hydrocarbon fluid production and/or processing plants and a collective dual level reliability engine visualisation dashboard is provided for the cluster of plants that displays an overview of the individual single collective CPBM factors that each dual level reliability engine visualisation dashboard generates for each of the hydrocarbon fluid production and/or processing plants .

The system of claim 3, wherein a sequence of

Condition and Performance Based Maintenance

(CPBM) operations is scheduled and executed on the basis of the overview.

The system of any one of claims 1-4, wherein the hydrocarbon fluid production and/or processing plant is an onshore or offshore crude oil and/or natural gas production facility.

The system of claim 5, wherein the facility is an offshore crude oil and/or natural gas production facility comprising one or more crude oil and/or natural gas production wells that are connected to topside facilities, comprising an assembly of rotating and other oilfield equipment equipped with lubrication, reliability, performance, vibration, emission technologies where information is gathered from the machinery sensors, transducers, meters and others that are mounted on a single floating or seabed mounted offshore platform.

The system of claim 5, wherein the facility is an onshore crude oil and/or natural gas production facility comprising one or more crude oil and/or natural gas production wells that are connected to common crude oil and/or natural gas treating and export facilities that comprise an assembly of rotating and other oilfield equipped with

lubrication, reliability, performance, vibration, emission technologies where information is gathered from the machinery sensors, transducers, meters and others that are mounted on a single floating or seabed mounted offshore platform.

A method for Condition and Performance Based

Maintenance (CPBM) of oilfield equipment at a hydrocarbon fluid production and/or processing plant, the method comprising:

- measuring lubrication, reliability, performance, vibration, emission and other Key Performance

Indicators (KPIs) of the oilfield equipment;

- supplying the measured CPBM KPIs to an automated reliability engine; and

dashboard that displays the measured CPBM KPIs together with a single collective Condition and Performance Based Maintenance (CPBM) score that is an accumulation of all CPBM KPIs with weight factors associated with the criticality of the CPBM KPI based on CPBM best practice experiences, which weight factors are stored in the automated

The method of claim 8, wherein the dual level reliability engine visualisation dashboard displays the single collective CPBM score as a percentage on a scale from 0 to 100%.

The method of claim 8 or 9, wherein a the plant forms part of a cluster of hydrocarbon fluid production and/or processing plants and a sequence of Condition and Performance Based Maintenance (CPBM) operations is scheduled and executed on the basis of the single CPBM score displayed by the dual level reliability engine visualisation dashboard for each plant of the cluster of plants.