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Slide 1
ESP-Reliability Information andFailure Tracking System
ESP-RIFTSJ o in t Indus t r y Pro jec t
-An Over v iew
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Slide 2
The Vision
ESP-RIFTS JIP
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Slide 3
Total Workover Costvs. ESP Run Life (Onshore)
0%
1%
2%
3%
4%
5%
6%
$0
$5
$10
$15
$20
$25
$30
$35
$40
0 120 240 360 480 600 720 840 960
TrueWorkover
Cost(%Revenue)
TrueWorkover
Costs($millions/
year)
Average Operating Period (days)
Total Cost Servicing Cost
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Slide 4
Operators want to
Improve ESP Run-Life in existing applications
Improve the chances of success in new applications
Extend range and reliability of current ESPtechnology
Get a better understanding of the factors affecting
ESP Run-Life
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Slide 5
The Vision
Access a large set of hard ESP reliability data
To avoid educated guessesEnsure this reliability data is consistent
To avoid misunderstanding
Incorporate reliability engineering analysis tools To analyze data appropriately
Benchmark results against other operators To determine attainable performance targets
Learn from others experience To find out what you can do to achieve better performance
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ESP-RIFTS Overview March 2009Slide 6
ESP-RIFTSJIP was formed in 1999 ..
ESP Operators joined efforts to pursue..
development of an industry wide ElectricSubmersible Pump (ESP) - Reliability Informationand Failure Tracking System (ESP-RIFTS), which
will permit sharing of ESP run-life and failureinformation among a number of operators.
ultimate goals ... [they] are two fold: (1) to
accelerate the learning curve associated with newESP applications; and (2) to increase average ESPrun-life and operating range, by transferringknowledge and experience across the industry
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Slide 7
Implementation
Strategy
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Slide 8
System Maintenance
Data Processing Benchmarking Analysis
ESP-RIFTS
End Users
World-WideNetwork
System Concept: Interface
Multiple users world-wideInternet interface
http://www.esprifts.com
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Slide 9
System Features ESP-RIFTS
1. Standard terminology (ESP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General Data Set)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database information
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Slide 10
ESP-RIFTSFailure Nomenclature Standard
Standard terminology for classifying, recording andstoring ESP failure information,
Leading to consistency in failure analysis performed with datagathered by different operating and service companies
Conforms to (as much as possible):1) International Standard ISO/DIS 14224
2) API RP 11S1
In general:Broad definitions and failure attribute classifications were
borrowed from the ISO/DIS 14224*;Nomenclature for components, parts and teardownobservations were borrowed from the API RP 11S1
*ISO 14224: Petroleum and Natural Gas Industries:Collection and Exchange of Reliability and Maintenance Data for Equipment
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Slide 11
System Features ESP-RIFTS
1. Standard terminology (ESP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General and Minimum Data Sets)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database information
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Slide 12
Minimum Data Set
List of ~ 37 key parametersSubset of the General DataSet
Developed with the input ofthe ESP-RIFTS SteeringCommittee
Attempted to be consistent
with other recommendedparameter lists SPE ESP Workshop
The Minimum information
that an ESP Failure recordmust have to be consideredComplete (as per the ESP-RIFTS QualificationStandard)
ESP-RIFTS: MinimumData Set(1)
ParameterField Information Field Name
Field Type
Fluid Information Oil Density
Bottomhole Temperature (BHT)
Well Information Well Name
Reservoir(s) Type
Casing Size
Runtime Data (dates) Production Period No.Date Started(2)
Date Failed / Shutdown
Failure Information ESP System Failed?
Primary Failed Item
Primary Failure Descriptor
Surface Equipment Data Control Panel Type
Downhole Equipment Data Pump Vendor
Pump Type/Model
Number of Pump Stages
Seal Vendor
Seal Type/Model
Motor Vendor
Motor Type/Model
Motor Horsepower
Pump Intake /Gas Separator Vendor
Pump Intake /Gas Separator Type
Cable Vendor
Cable Model/Size
Pump Seating Depth (PSD)
Operating and Production Data Total Flow Rate
Water Cut (or oil and water rates)
Pump Intake Pressure (PIP)
Gas-Oil Ratio (GOR) or gas rate
Sand Production (Concentration)
Scale (None/Light/Moderate/Severe)
Asphaltene (None/ Light/Moderate/Severe)
CO2 (Concentration)
H2S (Concentration)
Emulsion (None/Light/Moderate/Severe)
Number Minimum Data Set Parameters = 37
Average data for period or more frequente.g., monthly or number of intervals (mustprovide start and end dates of theseintervals) during which operating conditionswere reasonalby constant.
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Slide 13
System Features ESP-RIFTS
1. Standard terminology (PCP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General Data Set)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database informationDeveloped for ESP-RIFTS
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Slide 14
Data Processing and QualificationOverview
Participants
C-FER processes andenters data into the
Development Server
Participants send new data& data updates to C-FER
DevelopmentServer
ProductionServer
Feedback from C-FER to the Participants: Apparent problems with the data Processed data sent back to Participants in ESP-RIFTS orPCP-RIFTS Data Input Sheet
Web
DataQualification
Processed data
and New Webpages are
uploaded to theProduction Server
Participants conductanalyses via the web
Data Processing
DataAnalysis
DataCollection
FTP
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Slide 15
Data QualificationObjectives
Our confidence in any analysis will always bestrongly dependant on our perception of the
quality of the data collectedGoal of data qualification process is to yieldquality data; as per the ISO Standard:
Complete in relation to a specification
Compatible and Consistent with a standard set ofdefinitions and formats, with other information pertaining tothe record, with the principles of PCP technology and withbasic laws of engineering/science
Accurate truly representative of the PCP installation that itdescribes
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ESP-RIFTS Overview March 2009Slide 16
Data Input Sheet (DIS)
MicrosoftAccess baseddatabase file withstructure similarto ESP-RIFTSmaster database
Developed to
assist in datacollection andqualification
Field level data
capture andtracking
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ESP-RIFTS Overview March 2009Slide 17
DISBenefits to the Participants
Ability to check and improve their own records before sending thedata to C-FER
DIS can generate automated reports on level of completenessand inconsistencies
Ability to analyze the data shortly after providing data to C-FER
DIS allows for quicker data processing, qualification anduploading by C-FER
Ability to work in different unit systemsSI, British and North Sea units
Ability to work in different languages
Currently English, Spanish, Portuguese, Russian and French
Ability to perform basic Analysis on your own dataRun-Life Calculations (e.g. MTTF, Average Runtime), ReliabilityFunctions (e.g. Survival Probability), Failure Rates by ESPComponent) and Reporting of Results
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Select either chartor table outputformat
Results can besaved and printed
DISRun-Life Calculations
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DISReliability Functions
Grouping Variables:
Company, Division, Field, Well MORE options have been added as
well (e.g. Cable AWG Size, MotorSeries, Solids?, etc.)
Survival Probability and HazardFunction shown
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ESP-RIFTS Overview March 2009Slide 20
DISFailure Rates by ESP Component
Output Options Include:1. Service-Life of Failed
2. Number of Failed ESPs3. Average Runtime of Failed
4. Failure Rate
Outputs Segregated by:1. Failed Item Main Component
2. Failed Item Subcomponent
3. Failure Cause: General
Grouping Variables: Company, Division, Field, Well
MORE options will be addedsoon (e.g. Vendor, Model #), as
in the WebsiteNote: Field names have been masked for confidentiality
Field A
Field B
Field C
Field D
Field E
Field FField G
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ESP-RIFTS Overview March 2009Slide 21
Percentagebreakdown of all the
specific vendors forthe ESP motors andpumps in thespecific DIS file.
DISReporting
Enhanced Summary report
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Slide 22
Data ProcessingLocations of Fields in ESP-RIFTS
BP Kuwait Oil Company Saudi Aramco
Chevron Nexen Shell
ConocoPhillips PDVSA Shell PDO
EnCana Petrobras
TNK-BPExxonMobil Repsol YPF
TOTAL
Statoil
Note: Company IDs have been masked for confidentiality
G f D t b
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16731854 3940
7590 936612606 13897
15272
17898
26071
60237
60813
70548
79754
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
4/25/20
00
7/4/200
0
11/20/2000
4/25/20
01
11/28/2001
4/22/20
02
8/2/200
2
10/11/2002
12/5/20
02
4/7/200
3
10/27/2
003
2/3/200
4
4/8/200
4
10/15/2
004
12/9/20
04
4/14/20
05
11/17/2005
5/19/20
06
11/6/2006
4/1/200
7
11/14/2007
6/15/20
08
12/3/20
08
3/1/200
9
Num
berofProductionPeriods
Date
Slide 23
Grow of Databaseas of March 2009
79,754 ESP Installs as of March 200917 companies88 divisions
494 fields25454 wells
March 2009ESP-RIFTS Overview March 2009
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Slide 24
System Features forESP-RIFTS
1. Standard terminology (PCP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General Data Set)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database informationDeveloped for ESP-RIFTS
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Slide 25
Database Structure
Five main groups of dataField, Well, Fluid, and Reservoir data Field, Reservoir, Drilling/Completion, Fluid, Workovers, Operator info.
Run time information
Install, Start, Stop, Pull dates, etc.
Production and Operating Information Producing rates, GOR, BSW, Fluid Level, Wellhead and Bottom Hole
Pressure and Temperature
Failure data Item(s), Descriptor, Mode, Cause
Teardown/Inspection reports, bench test reports, photographs,
scanned documents Comments
Equipment data Motor model, Motor HP, Intake Model, Cable Size, Manufacturer
Catalogue information
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Slide 26
Database Structure (contd)
The link between these groups of data is aProduction Period, which includes
One specific ESP or PCP assembly
Installed, Started, Stopped and Pulled
Serial numbers, completion assembly/sequence in the welland associated surface/downhole equipment
Well Service and Production/Operating histories
1
10
100
1000
Mar-95 Sep-95 Mar-96 Sep-96 Mar-97 Sep-97 Mar-98 Sep-98 Mar-99
OilRate
WaterRate
WOR
Daily Oil
Daily Water
WOR
Production Period
Workove
r
Workove
r
Workove
r
Workove
r
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Slide 27
System Features for ESP-RIFTS
1. Standard terminology (PCP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General Data Set)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database informationDeveloped for ESP-RIFTS
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Slide 28
Measures of Run-Life
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Slide 29
Some Key ConceptsCensoring
For some systems, the RL is not known:Systems still running
Systems pulled for reasons other than a system failureThe data is said to be censored
However, proper analysis must consider all data
Considering only the failed items will tend to underestimatethe reliability of the system
Therefore, all systems must be tracked:Pulled systems
FailedNot Failed
Running systems
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Slide 30
Run-Life Flow Chart
Running
Completed ESP System Failed ?
Yes
No
Period Status
failed#
Valid Last Date
failednot#
runningstill#
completed#
periodsall#
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Slide 31
Reliability Functions
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Slide 32
Survival and Hazard Curves
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Slide 33
Component Failure Rates
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Slide 34
Failure Rates of Cables for a Field
FR of New Cable is
4 times smaller thanthat of Used Cable
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Slide 35
System Features for ESP-RIFTS
1. Standard terminology (PCP Failure Nomenclature Standard)Consistency in classifying, recording and storing information
2. Common set of parameters (General Data Set)Tracked by all Participants in the project
3. Data Input Sheet (DIS)To assist in data collection, maintenance and upload
4. Procedure to ensure certain standards of data quality
5. Database structure to store the data collected6. Internet based system
Participants select records of interestExamine the contents of such recordsConduct a variety of analyses with them
7. Set of reliability tools to support data analysisVarious run-life measures, reliability functions and distributionsConfidence level calculations
8. Model to predict run-life under new conditions (What if)
Calibrated with database informationDeveloped for ESP-RIFTS
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Slide 36
What-If Model
A Proportional-Hazard-Model based on data inthe System
Some details presented by C-FER in the 2003 ESP-Workshop
Has evolved with time
Allows for benchmarking taking into accountdifferences in operating conditions
One way to identify key influential factors affectingRun-Life
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Slide 37
What-If Model (contd.)
High R-L
but below expectations
Low R-L
but above expectationsNote: Field names have been masked for confidentiality
Field A Field B Field C
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Slide 38
Some Analysis ExamplesUsing Website Data and Tools
H i M Fi ld d i ?
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Slide 39
How isMy Fielddoing?- MTTF and Average Run-Life -
Based on Date Installed, MTTF shows continuous improvementUncertainty bars on MTTF depend on number of failed systems
Average Run-Life decrease in 2003-3005 is does not necessarilyindicate worse performance
Only indicates that more recently installed systems are younger
How is My Field doing?
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Slide 40
How isMy Fielddoing?-Cumulative and Moving Window metrics -
Based on more recent data (i.e. Moving Window of last 1200 days at each point in time),MTTF and Average Run-Life shows larger improvement than based on all (cumulative)dataNot shown (but available): Other R-L metrics used by Operators
All have advantages and disadvantages
Some are indicators of age of population and not necessarily equipment reliability
How is My Field doing?
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Slide 41
How isMy Fielddoing?-Primary Failed Items and Failure Mechanisms -
Primary Failed Items:
Motors 36.8%Cables 21.1%
Pumps 21.1%
Intakes 9.2%
Seals 9.2%
Most Severe Mechanisms:Short Circuited Motors 14.5%
Short Circuited Cables 14.5%
Phase Unbal. Motors 9.2%
Plugged Pumps 7.9%
Broken/Fract. Intakes 7.9%Overheated Motors 4.0%
Low Impedance Motors 4.0%
Failure Mechanisms are different for early andall failures
Primary Failed Items:
Pumps 33.8%Motors 22.4%
Intakes 18.8%
Cables 16.5%
Seals 6.5%
Most Severe Mechanisms:Broken Pumps 14.1%
Short Circuited Cable 11.5%
Short Circuited Motor 10.6%
Stuck Pumps 6.5%
Fractured Pumps 6.2%Phase Unbal. Motors 4.4%
Plugged Pumps 2.9%
All Failed PeriodsPeriods with Failures at t 90 days
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Slide 42
How isMy Fielddoing?- Failure Rates (FRs) by ESP system component: evolution with time -
FRs of Pump Intakes, Seals and Cables show deceasing trend (improving)FR of Motors shows increasing trendFR of Pumps varies with no clear trendPump and Motors are components currently with higher FRs
Note: Dashed red lines represent eye-balled trend.
H i M Fi ld d i ?
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Slide 43
Moderate
Severe
How isMy Fielddoing?- Failure Rates (FRs): effect of scale -
Primary
FailedItem
...ESP
Assembly
ESP
Cable
ESP
Motor
ESP
Pump
ESP
PumpIntake
ESP SealESP
Shroud
Failure
Rate
Failure
Rate
Failure
Rate
Failure
Rate
Failure
Rate
Failure
Rate
Failure
Rate
... (10-6/day)(10-
6/day)
(10-
6/day)
(10-
6/day)
(10-
6/day)
(10-
6/day)
(10-
6/day)
Moderate ... 12.47 130.97 180.86 224.51 155.91 81.07 0
Severe ... 8.2 143.57 192.79 324.05 159.97 36.92 4.1
Total ... 9.9 138.57 188.05 284.56 158.36 54.44 2.47
9.6% 6.6% 44.3% 2.6% -54.5%
Scale?
ESP Pumps are affected by severescaling conditions: +44% higher FRsthan for moderatescaling conditions.
How does My Field compare with similar fields?
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Slide 44
How doesMy Fieldcompare with similar fields?
-Search data in the system -
Field B has a large # of similar records
Other fields have just a few records
Average MTTFMedium Total RatesHigh WC
Medium SandMedium-High APIHigh CO2Low GOR
Low TemperatureShallow PSDOne dominantvendor
Onshore
[Artificial Lift Type]='ESP' AND [Production Role]='Oil Production' AND [Qualification Status]'Incomplete-No Dates orFailure Information' AND [Qualification Status]'Inconsistent Records' AND [Qualification Status]'Historical' AND[Pump Seating Depth MD]>'700' AND [Pump Seating Depth MD]'50' AND [WaterCut]>'70' AND [Total Flow Rate]
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Slide 45
Comparison of Cumulative MTTF andAverage Run-Life
MTTF is approximately 4 months lower in My Field
B Field My Field
1443
1318
512 507
Note: Field names have been masked for confidentiality
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Slide 46
Closure
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Slide 47
Current Project Participants
Project Phases
I: Nov. 1999 Jul.2000
II: Aug.2000 Apr. 2001 Project Web Site: online since
July 2000
III: May 2001 Apr. 2002
IV: May 2002 Apr. 2003V: May 2003 Apr. 2004
VI: May 2004 Apr. 2005
VII: May 2005 Apr. 2006VIII: May 2006 Apr. 2007
IX: May 2007 Apr. 2008
X: May 2008 Apr. 2009
Current Participants
BP
ChevronTexacoConocoPhillipsEnCanaExxonMobil
NexenPetrobrasRepsol-YPFShell Intl.StatoilHydroTNK-BPTOTAL
Benefits to New Participants
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Slide 48
Benefits to New ParticipantsUpon joining ESP-RIFTS
1. Immediate access to the system - user accounts will beassigned to a number of New Participant personnel
2. Ability to query the data and conduct analyses - display theresults in a number of numerical and graphical formats
3. Improved ability to make good decisions on issues affectingESP run life
4. Access to about US$ 3,500,000 worth of work conducted in
the previous phases of the JIP (phases I - IX)5. Two-Three day workshop (at a location of choice) to quickly
bring the New Participant personnel up to speed6. Improved understanding of run-life and failure tracking issues
and analysis techniques7. Opportunity to upgrade current ESP failure tracking systemsto the ESP-RIFTS standard:
Achieving consistency within own CompanyAchieving consistency within the group of industry Participants
Benefits to New Participants
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Slide 49
Benefits to New ParticipantsLong-Term Benefits
1. Business results, which can span over a variety of aspects,including:
Improved chances of overall economic success in new projects
Because there will be less uncertainty in the expected run-lifeReduced production losses in the upcoming years Because improved rig scheduling will be possible
Improved overall run-life and reduced operational costs Because best practices can be implemented
2. Business results can start to be obtained as soon as possible In terms of run-life, the effects of good decisions made at one point in
time are only felt in the long term
3. Ability to make direct benchmark comparisons
Within own Companys operations Within the Participants' operations
4. Guidelines for negotiations between the Participant and ESPvendors (e.g., as in alliance situations)
Using benchmarks established with the system
Fee Structure
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Slide 50
Fee StructureYear 2009/2010 (Phase XI)
New Participant FeeUS$ 48,000 (one-time)
CoversInitial Development Cost Sharing
New Participant Orientations (in-house training)
Mapping and Input of Historical Data
JIP Participation FeeUS$48,000Covers Core Tasks
Data Processing and QualificationData Analysis (within the limits of the System)
Web Site Maintenance
Project Steering Committee Meetings (Nov/Dec 2009 and Apr/May 2010)
Project Management and Reporting
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Slide 51
Further Documentation Available
Project web site: http://www.esprifts.comGeneral Information on the ESP-RIFTS JIP
Benefits to New Participants: http://www.esprifts.com/Benefits.pdf
Detailed work scope, deliverables, and milestone schedule forPhase X:http://www.esprifts.com/Workscope%20Phase%20X.pdf
2001 SPE - ESP Workshop PaperESP Failures: Can We Talk the Same Language?
2003 SPE - ESP Workshop PaperBenchmarking ESP Run Life Accounting for Application
Differences
For addition information, please contact:Jess E. Chacntel: (780) 450-8989 ext 224e-mail: [email protected]
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Slide 52
Support Slides
Predicting ESP Run Life
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Slide 53
Predicting ESP Run Lifefor New Applications
Questions in field development feasibility studiesWhat is the expected ESP run life for the field?
What are the future service rig requirements for the field?
What type of equipment is best suited for a given application? E.g., Is the run life for wells equipped with VSDs the same as wells
equipped with switch boxes?
E.g., Are coiled tubing deployed systems less reliable than systems
deployed on jointed tubing? If so, how much?What is the effect of well completion type on ESP run life? E.g., Should sand control (gravel pack) be used to prevent sand inflow
(but perhaps at the cost of lower well productivity)? Would the ESPrun-life be acceptable if the sand is produced?
What operating practices/conditions are best? E.g., Should the wells be produced at a flowing bottomhole pressure
that is above the bubble point pressure to avoid failures associatedwith free gas?
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March 2009ESP-RIFTS Overview March 2009
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Early Stages of a Feasibility Study
How ESP run-life affects the project economics?Offshore Platform Example
20 WellsAverage oil production per well: 1200 bopd
Average intervention cost: 150 k (10 days @15k/day)
Average equipment cost: 100 k
Average workover & waiting time 60 days
Onshore Example 100 wells
Average oil production per well: 200 bopdAverage intervention cost: 20 k
Average equipment cost: 50 k
Average workover & waiting time: 7 days
Total Workover Cost
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March 2009ESP-RIFTS Overview March 2009
Slide 55
Total Workover Costvs. ESP Run Life (Offshore)
0%
5%
10%
15%
20%
25%
30%
35%
40%
$0
$100
$200
$300
$400
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0 120 240 360 480 600 720 840 960
TrueWorkover
Cost(%Revenue)
TrueWorkover
Costs($millions/
year)
Average Operating Period (days)
Total Cost Servicing Cost
Total Workover Cost
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Total Workover Costvs. ESP Run Life (Onshore)
0%
1%
2%
3%
4%
5%
6%
$0
$5
$10
$15
$20
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0 120 240 360 480 600 720 840 960
TrueWorkover
Cost(%Revenue)
TrueWorkover
Costs($millions/
year)
Average Operating Period (days)
Total Cost Servicing Cost
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