Dana Kayshibaeva SLB

1. Reducing ESP Failures using
Autonomous Corrosion & Scale
Chemical Injection
Dana Kayshibaeva
15 February 2023

2. SLB-Private
Customer challenge
 Onshore oilfield
 148 wells – exclusively ESPs
 58,000 BOPD / 228,000 BWPD
 Many remote locations
 Consistent operational issues
– Injection pump availability
– Variable injection pressures
– Over previous year, on average wells have
been over/under-treated 50% of the time
 > 20% failure rate each of past 2 years directly
attributed to corrosion and scale
Production
Losses
Workover
Costs $8M Annually
$5.3M Annually

3. SLB-Private
Standardized Digitalization Approach
Understand
data we need
at higher
frequency
Determine if
we can get
required data
by connecting
existing
equipment/
systems
Identify
where
modeling
can be used
Install
instrumentation
to fill gaps
Implement
closed-loop
control
Enable cloud
visualization
and control

4. Inherent delays in critical decision data
Corrosion and scale coupon
Water sample
Target vs. actual
injection rate
record Inventory
60DAYS
Elapsed Time
Routine analysis
Scale prediction
Well test
Injection pump
Chemical tank
Manual Data
Sources
Manual
Monitoring
Spreadsheets
Traditional Monitoring Process

5. Reduce the time from insight to action with
Production Chemicals Optimization on DELFI
Connected data
sources
1MIN
Elapsed time
ESP
Production data system
Injection pump
Corrosion probe
Surface PT sensors
Edge intelligence Cloud intelligence
Virtual flowmeter
Agora edge AI
and IoT solutions
Scale prediction
Corrosion
prediction
Target rate
Autonomous injection
Chemical pump
control
Production Chemicals
Optimization on DELFI
Agora and DELFI are marks of Schlumberger.

6. SLB-Private
Approval mode
to transition
from traditional
manual to
automated
optimization

7. SLB-Private
Real-time
System in
Action –
Transition to
Autonomy
Approvals
Client
Trust
Autonomy

8. SLB-Private
Autonomous
mode to
optimize every
minute with no
human
intervention
required

9. SLB-Private
Results after 20 months of field trial
 Autonomous injection adjusted 250-300 times per
day
 Actual rate vs target injection rate compliance
increased from 60% to 99%
 Virtual flow model (VFM) has been within 3% of all
well tests
 Scale prediction results 100% matching manually
run simulations
 ZERO failures to date
 Remote surveillance and control reduces required
field trips vs manual by >75%
– Limited exposure to safety risks, and reduced
CO2 footprint
 Estimated value: > $800K for 2 wells to date**

10. Production Chemicals Optimization on DELFI
Real-time corrosion and
scale risk identification
Autonomous optimization
of chemical injection
Automated generation
of actionable insights
DELFI is a mark of Schlumberger.

11. SLB-Private
Learnings Through the Digital Journey
• Digitalization projects should be focused on reducing specific
problems present in your operations
• Walk before you run – start with a subset of high risk wells
and field trial
• Give it time to prove it’s value
• Be invested as a partner
• Start by assessing what is possible with existing equipment
and systems – use your data
• Leverage your historical data to validate models
• Economic feasibility analysis needs to be thorough
• Not every well makes sense
• Traditional monitoring may not always be the most cost-
efficient approach
This Photo by Unknown Author is licensed
under CC BY-NC

12. SLB-Private
Thank you
Connect with us to learn more about
Production Chemicals Optimization
dkayshibaeva@slb.com
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