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Maintenance Scheduling Tool in the Oil & Gas Industry
2016 Anylogic Conference
Jonatan Casiet; J.Pablo Rodriguez Varela;Patricio Pipp; Marina Pérez Gaido
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Continente Siete (C7 S.A.) is an algorithm workshop,where mathematical models are constantly being developed to address complex business problems.
YPF S.A. is the largest oil & gas company in Argentina and the third in South America.
Simcastia is C7’s Simulation and Optimization division.
Who we are
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Business processes analyzed:
• Wells and facilities operation
• Wells and facilities maintenance
• Well services with pulling rig
Value stream mapping
methodology:
Identification and
prioritization of issues for each
process:
Ishikawa diagram for
identification of root causes:
Brainstorming for improvement
opportunities:
Clustering:
Mess mapping; inter
relationships between clusters of improvement
opportunities
Critical businessProcess selection
Processmapping
Identification ofImprovement opportunities
Root causeanalysis
Clustering ofImprovementopportunities
Prioritization ofImprovementopportunities
Once upon a time…
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• “Rincón de los Sauces” is anoil field located in Neuquén,Argentina.
• Aprox. 700 wells (amongwater injection and oil wells)
• About 100 working crews.• More than 100 weekly
maintenance orders.
Pilot location
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Proposed solution
Flexibility
Is needed to develop a fully
customized tool
Optimization
Is core to the solution in order to drive objective
efficiency
Multi-paradigmSimulation
Allows the tool to be better accepted
Eye-catchingInterfaces
Help the tool to be better accepted
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Cost = Resources Utilization + Wells′ Prod Loss + Dist covered
𝑓𝑓𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑓𝑓𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑𝑑𝑑𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐻𝐻𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀+ 𝑓𝑓𝑛𝑛𝑒𝑒𝑑𝑑𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀𝐶𝐶𝐶𝐶 𝐻𝐻𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀
𝑓𝑓𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × (𝑈𝑈𝑀𝑀𝑈𝑈𝐶𝐶𝐶𝐶𝑀𝑀𝑀𝑀𝐶𝐶𝑈𝑈 +𝑃𝑃𝐶𝐶𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑃𝑃𝑃𝑃𝐶𝐶𝑈𝑈) 𝐼𝐼𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀
Cost function
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Skills: type of tasks for each resource.
Parameters: Working hours, maximum extra hours.Resources
Georeferenced map: distances in between each point.
Status: conditions in the point to be maintained.Positions
Preventive & predictive: they can be planned.
Corrective: after fail detection.Tasks
Agent-based focus
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Resources
Position
Tasks1. Preparation
(30’)
2. Functional Verification
(60’)
3. Maintenance (90’)
4. Sign off (30’)
Lunch
Lunch
Lunch
Work order complexity
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Position
Tasks1. Preparation
(30’)
2. Functional Verification
(60’)
3. Maintenance (90’)
4. Sign off (30’)
Work order complexity
NEW AGENT REQUIRED: WORK ORDER
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Scheduling Methodology
PriorityLocation
Aging
Work Order Characteristics
SequenceSimultaneityDuration
Task Characteristics
1. Order priority: lists the work order according to characteristics.2. Greedy: Analyzes possible day/time for each operation.3. Final iteration per Work Order: Adjusts tasks to minimize work order duration.
Optimization Process
1.2.3.
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KRON Screens
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Scheduler integration
Other Data Sources
automated input feed
automated output feed
InternalDatabase
OptimizationEngine
Cool UserInterface
MultipleUsers
local export
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KRON Results
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0
200
400
600
800
1000
1200
1400
1600
sep-14 oct-14 nov-14 dic-14 ene-15 feb-15 mar-15 abr-15 may-15 jun-15 jul-15 ago-15 sep-15 oct-15 nov-15 dic-15 ene-16 feb-16 mar-16 abr-16
+11%After pilot program
was initiated.
PilotProgram
Work orderexecution
Work order execution increased 11%
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7377
8591 93 95 97 97 98 98 98 98 98 98
0
20
40
60
80
100
120
янв.15 фев.15 мар.15 апр.15 май.15 июн.15 июл.15 авг.15 сен.15 окт.15 ноя.15 дек.15 янв.16 фев.16 мар.16 апр.16
+25%
Upstream YPF Avg 84%
In just six months…
With just one scheduler…
With just one tool
Preventivemaintenance
Improved 25%Pilot
Program
Preventive maintenance improvement
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0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Prom2014
ene-15 feb-15 mar-15 abr-15 may-15 jun-15 jul-15 ago-15 sep-15 oct-15 nov-15 dic-15 ene-16 feb-16 mar-16 abr-16
- 56%
CorrectiveMaintenance
backlog
PilotProgram
-56%Reduction from avg
2014
Backlog reduction
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0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
40,0
Avg2013
Avg2014
abr-15 may-15 jun-15 jul-15 ago-15 sep-15 oct-15 nov-15 dic-15 ene-16 feb-16 mar-16 abr-16
- 50%
-50%Reduction from avg
2013 and 2014
Oil productionLosses due tomechanical
failures
PilotProgram
Downtime due to mechanical failures was improved
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73; 80 98; 97
0
20
40
60
80
100
120
40 50 60 70 80 90 100 110
% P
reve
ntiv
e m
aint
enan
ce e
nfor
ceab
le b
y la
w
% Total preventive maintenance
AssetBPP
AssetAPP
Rincón de los sauces asset before and after the pilot program
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18 MMUSD per yearAt Rincón de los Sauces Asset
NPV@12%: 234 MMUSDWith this project implemented in all the YPF assets
Economical impact
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Final words
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Thanks for your time!
Suggestions? Questions?
Jonatan Casiet; J.Pablo Rodriguez VarelaPatricio Pipp; Marina Pérez Gaido
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Lessons learned
• Start with a pen and paper
• Do not animate just because you can
• Validation at each turn
• Optimal is great, but better is good enough