SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
REAL TIME EXPERT SYSTEMS FOR PRODUCTION OPTIMIZATION
Edson Henrique Bolonhini - UN-RNCE/ST/ELVJosé Francisco Corrêa - UN-BA/ST/ELVSthener R.V. Campos - CENPES/PDP/TE
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
OUTLINE OF PRESENTATION
Field Production IntegrationStrategy and concept of intelligent systems
Expert System for Continuos Gas Lift Variable definitionsControl strategyField examples
Expert System for Intermittent Gas LiftIntroductionSystem ArchitectureHardwarePattern RecognitionControlOver all architectureRemarks
Conclusions
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
INTEGRATIONPRODUCTION
MANAGEMENT
DATAMANAGEMENT
ARCHITECTUREMODEL
MONITORING
OPTIMIZATION
CONTROL
Field Production Integration
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
DecisionIt is a process that, considering the uncertainty and preferences, choose just one action among several possibilities.
Intelligent SystemAn intelligent system must be capable to self adaptation undernew situations, understand relations between facts, discovermeanings, recognize strategies and learn based on experience.
$$$ Investments proportional to uncertainty $$$
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Field Production IntegrationStrategy and concept of intelligent systems
Expert System for Continuous Gas Lift Variable definitionsControl strategyField examples
Expert System for Intermittent Gas LiftIntroductionSystem ArchitectureHardwarePattern RecognitionControlOver all architectureRemarks
Conclusions
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
PROCESS VARIABLE DEFINITIONPROCESS VARIABLE DEFINITION
ion using flowrate injection asurement together with the valve
Control Valve - Globe ¾”
IxP converter
Pressure Transmitter
Dif Pressure Transmitter
Temperature Trasmitter
3 x solenoide
Flow Computer
Pressure Gauge
Coaxial Cable
Filter / Regulator
Eletric cable – instrumentsBottom hole Cable
Field PLC Data integration / analysis
Closed Loop System
Otis Valve
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
DATA FLOW CHARTDATA FLOW CHART
SCADASCADA
SCADASCADAClientClient
[ Petrobras Net ][ Petrobras Net ]SoftwareSoftware
Process
Communication
Control
Trends
OPERATIONFIELD UPN & RFQ
REMOTE ACESSNatal
TRANSMISSIONRiacho da Forquilha
ardwareardware
DATA BASEDATA BASE
SoftwareSoftware Software & HardwareSoftware & Hardware
SoftwareSoftware
DiagnosticControl Update
HardwareHardware
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. OptimizationSUPERVISORY INFORMATIONSUPERVISORY INFORMATION
SME/API/ISO Spring 2005 Gas-Lift Workshop
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RT Expert System for Prod. Optimization
100 21OperationCondition Strategy
Verification
PwfrefIdentification
10Step
Identification
6
51Strategy
Execution
5System
Reconfiguration
OptimizatinOptimizatinOptimizatinTriangleTriangleTriangle
mização de Pwf, com controle de gás injetado.
wf
Qgi
Pwf(min)
Qgi (pto de trabalho)
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
WellWell onon StableStable Operation Operation –– Switching states 51 and 21Switching states 51 and 21
Analysis Time = 3h Well stabilized with state 21 extended
Waiting Time
40 min
Wellhead Pressure [kgf/cm2 ]StateGas lift injection flowrate - Qgi [m3 /d ]Gas lift Pressure Line [kgf/cm2 ]
Casing Pressure Setpoint [kgf/cm2 ]Casing Pressure [kgf/cm2 ]Valve opening [%]Bottom Hole Pressure [kgf/cm2 ]
Reference Bottom Hole Pressure [kgf/cm2 ]Filtered Bottom Hole Pressure [kgf/cm2 ]
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
ControlControl CicleCicle
Injection setpoint change afterprocess reach the minimum
value of the function..
Wellhead Pressure [kgf/cm2 ]StateGas lift injection flowrate - Qgi [m3 /d ]G lif P Li [k f/ 2 ]
Casing Pressure Setpoint [kgf/cm2 ]Casing Pressure [kgf/cm2 ]Valve opening [%]B H l P [k f/ 2 ]
Reference Bottom Hole Pressure [kgf/cm2 ]Filtered Bottom Hole Pressure [kgf/cm2 ]
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Comparation Manual x AutomaticComparation Manual x Automatic
Formation TestComparation P and T = OK
Modo de operação: ManualStatus do algoritmo: State 5 cte
Operation Mode: AutomaticStatus do algoritmo: : On States
Wellhead Pressure [kgf/cm2 ]StateGas lift injection flowrate - Qgi [m3 /d ]G lif P Li [k f/ 2 ]
Casing Pressure Setpoint [kgf/cm2 ]Casing Pressure [kgf/cm2 ]Valve opening [%]B H l P [k f/ 2 ]
Reference Bottom Hole Pressure [kgf/cm2 ]Filtered Bottom Hole Pressure [kgf/cm2 ]
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
OperationalOperational Comparation Comparation -- Qgi manual x QgiQgi manual x Qgi automaticautomatic
Modo de operação: ManualStatus do algoritmo: State 5 cte
Operation Mode: AutomaticStatus do algoritmo: On States
Wellhead Pressure [kgf/cm2 ]StateGas lift injection flowrate - Qgi [m3 /d ]Gas lift Pressure Line [kgf/cm2 ]
Casing Pressure Setpoint [kgf/cm2 ]Casing Pressure [kgf/cm2 ]Valve opening [%]Bottom Hole Pressure [kgf/cm2 ]
Reference Bottom Hole Pressure [kgf/cm2 ]Filtered Bottom Hole Pressure [kgf/cm2 ]
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Field Production IntegrationStrategy and concept of intelligent systems
Expert System for Continuous Gas Lift Variable definitionsControl strategyField examples
Expert System for Intermittent Gas LiftIntroductionSystem ArchitectureHardwarePattern RecognitionControlOver all architectureRemarks
Conclusions
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
INTRODUCTION
Intermittent Gas Lift Typical Installation
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
INTRODUCTION
IGL cycle - Casing & Tubing pressure vs. timeCP
A
B
C
D E
Time
A B
C
D E
Time
TP
ITTc
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
SYSTEM ARCHITECTURE
Central Office
•Well mechanical characteristics•CP/TP graphic patterns•Control algorithm
•First stage supervisory action•Matching
•Polling•Injection scaling•Supervision•Major Data base
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Hardware
Gas Injection ON/OFFDI
DI
DI Man/Auto Key
AI
Tubing PressureAI
DO–Motor valve Gas Injection
SGLPCasing Pressure
Plunger magnetica sensor
DO– Motor valve Prod Line
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Hardware cycleIntermittent Gas Lift
AQUISITIONProcess
Neuro-Fuzzy
PR
On/Off
PT
Gas lift well SGLiP
Action Module
User editedControl
Algorithm
SignificantPoints
PatternRecognition
Data acquisition
ACTUATION
Plg
Casing and TubingPressure
Acquisition
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
CP
A
BC
D E
Time
A B
C
D E
Time
TP
Pre
ssur
eP
ress
ure
PATTERN
Rec.
Over all cycleIntermittent Gas Lift
ALGORITHM
CONTROL
Act i oniT
cT
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
CP Patterns
A
B
C
D E
1
A
C
D
E
2
A
C
D E
3
1 - Normal
2 - Motor-valve Leakge
3 - GL valve leakge
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RT Expert System for Prod. Optimization
CP Patterns
A
C E4
A
C
E
5
A
C
E
6
D
A
C
E
7
D
4 - GL valve closed
5 - GL valve open
6 - GL valve take to long to close
7 - After pattern 4
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Over all cycle
ALGORITHM
CONTROL
Intermittent Gas Lift
CP
A
BC
D E
Time
A B
C
D E
Time
TP
Pre
ssur
eP
reur
e
PATTERNS
Act i on
ss
iTcT
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Control Algorithm
Estructure:
VARIABLES
START// coments
IF (condition)
THENCode
ELSECode
ENDIFCode
RETURN
END
Code
Functions:
VM ( xx ) Read / Write integer values
VD ( xx ) Read / Write real values
SetMsgMCI ( Cod , text ) To send messages to central office
SetTimer(x,yy) Timer setting;
ValTimer(x) To get timer value
Matching(x,1) Matching result to CP patterns
Matching(x,2) Matching to TP patterns
Confiança(x,1) Similarity degree to CP patterns
Confiança(x,2) Similarity degree to TP pattern
PreFundo (prof, press) To calculate pressure at prof. depth
SelCiclo ( x ) To set cicle X to the system
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Control Algorithm
EXAMPLE:
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Graphic User Interface
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Graphic User Interface
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
Engineering Analysis GUI
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. OptimizationOver all architecture
COP- FBM
OP-FBM
PCP – 81ESP – 02SRP –177 COP- BA
OP-BA
PCP –120SRP – 68COP- CAN
OP-CAN
IGL – 105
COP- AGOP-AG PCP – 07
ESP – 36SRP – 10IGL – 99
COP- AROP-AR
PCP – 10SRP – 97IGL – 60
COP-MGOP-MG PCP – 53
SRP – 22IGL –167
431 IGL wells
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
IMPORTANT REMARKS
• The system was installed in 431 wells located at four production areas;• Now a days the production team is been trained to manage the system
and develop and implement the algorithm and patterns;• The culture changes and production personnel motivation to use the full
system potential is proven to be a big chalange;• A learning curve is now being developed, and a big effort is being done in
training production and maintenance teams;• An improvement in the IGL well operational control were reported by the
field personel;• A reduction in production losses was also reported by field personel.
SME/API/ISO Spring 2005 Gas-Lift Workshop
Rio de Janeiro-Brazil February 24 and 25 2005olonhini Corrêa Sthener - PETROBRAS
RT Expert System for Prod. Optimization
CONCLUSIONS
• The technology used allows the field engineer to put his own knowledge and experience in the controller;
• The use of AI concepts were successfully used to analyse the IGL;
• The use of control algorithm need to be improved to obtain better optimation results;
• Time has to be given to field personel explore the system full potencial.