maintenance scheduling tool in the oil & gas industry
TRANSCRIPT
Maintenance Scheduling Tool in the Oil & Gas Industry
2016 Anylogic Conference
Jonatan Casiet; J.Pablo Rodriguez Varela;Patricio Pipp; Marina Pérez Gaido
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
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…
• “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
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
Cost = Resources Utilization + Wells′ Prod Loss + Dist covered
𝑓𝑓𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑓𝑓𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑𝑑𝑑𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐻𝐻𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀+ 𝑓𝑓𝑛𝑛𝑒𝑒𝑑𝑑𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀𝐶𝐶𝐶𝐶 𝐻𝐻𝑀𝑀𝐶𝐶𝐶𝐶𝑀𝑀
𝑓𝑓𝑛𝑛𝑛𝑛𝑛𝑛𝑑𝑑 × (𝑈𝑈𝑀𝑀𝑈𝑈𝐶𝐶𝐶𝐶𝑀𝑀𝑀𝑀𝐶𝐶𝑈𝑈 +𝑃𝑃𝐶𝐶𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝑃𝑃𝑃𝑃𝐶𝐶𝑈𝑈) 𝐼𝐼𝑀𝑀𝑀𝑀𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀
Cost function
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
Resources
Position
Tasks1. Preparation
(30’)
2. Functional Verification
(60’)
3. Maintenance (90’)
4. Sign off (30’)
Lunch
Lunch
Lunch
Work order complexity
Position
Tasks1. Preparation
(30’)
2. Functional Verification
(60’)
3. Maintenance (90’)
4. Sign off (30’)
Work order complexity
NEW AGENT REQUIRED: WORK ORDER
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.
KRON Screens
Scheduler integration
Other Data Sources
automated input feed
automated output feed
InternalDatabase
OptimizationEngine
Cool UserInterface
MultipleUsers
local export
KRON Results
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%
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
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
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
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
18 MMUSD per yearAt Rincón de los Sauces Asset
NPV@12%: 234 MMUSDWith this project implemented in all the YPF assets
Economical impact
Final words
Thanks for your time!
Suggestions? Questions?
Jonatan Casiet; J.Pablo Rodriguez VarelaPatricio Pipp; Marina Pérez Gaido
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