SPE 199601 Large-Scale Deployment of a Closed …SPE 199601 Large-Scale Deployment of a Closed-Loop Drilling Optimization System Stephen Lai 2 3–5 March 2020 Galveston Island Convention

13–5 March 2020Galveston Island Convention Center, Galveston, Texas

IADC/SPE International Drilling Conference and Exhibition

SPE 199601

Large-Scale Deployment of a Closed-Loop Drilling Optimization System:

Implementation and Field Results

Stephen Lai, James Ng, Aaron Eddy, Sergey Khromov,

Dan Paslawski, Ryan van Beurden, Lars Olesen, Pason Systems

Gregory Payette, Benjamin Spivey, ExxonMobil Upstream Research Company

SPE 199601 Large-Scale Deployment of a Closed-Loop Drilling Optimization System Stephen Lai



Introduction

• Reduce well cost:

• Minimize spud-to-TD time.

• Maximize ROP / minimize flat-time.

• Rotary drilling optimized by continuous adjustment of

process parameters (WOB, RPM).

• Challenge: Formations can change rapidly.

• Automation solution:

• Closed-loop system based on proven advisory application.

• Field results from 270 rigs and 1700 wells.

Rock

Strength

Rock

Composition

35

0 fe

et

Sandstone Shale

0 25ksi

Coal




Optimization Application

Control

Measurements

1 Hz data rate

Outer Loop

Control

Control Scheme

Driller supervises process and manages parameter limits.

Driller

On/Off

Optimization Limits

Autodriller Limits

Autodriller

Control

Measurements Rig

Drilling

Inner Loops

Top Drive PLC

Control

Measurements

>20 Hz data rate

The Plant




Main Optimization Loop

Main loop runs once per second: Start

Read inputs

Calculate internal signals

In drilling dysfunction?

N

Y

ROP/MSE optimization:

• calculate new WOB

• calculate new RPM

Update ADR and top drive setpoints

Execute ADRmanagement protocol

Execute dysfunction mitigation protocol

Need ADR management?

Y

N

• If drilling dysfunction is detected,

- mitigation protocol is executed.

• If autodriller (ADR) is not in good state,

- ADR management protocol is executed.

• Otherwise,

- perform ROP/MSE optimization.




ROP/MSE Optimization

Challenges:

• Extremum Seeking Control (input signal dithering):

• Simple – minimal tuning parameters.

• Adaptable – continuously seeks the peak.

• Robust – no model-based assumptions.

Solution:

Drill-off testing

ESC algorithm

start

• Formation variation is random and non-stationary.

• Drilling process is difficult to model accurately.

• Scalability – must work at all rigs/formations/basins.

RPM WOB

f (R

OP,

MSE

)




ROP/MSE Optimization

ROP

increase

WOB

increase

RPM

increase

constant

MSE




Dysfunction Mitigation

When drilling dysfunction is detected, an automated protocol is used to remove the condition.

• Stick-slip protocol

• Stringer protocol

• RCD protocol

• Motor stall protocol

• Etc.

Stick-slip exceeds threshold.

1

Optimization stops to focus on stick-slip. WOB decreased. Stick-slip

reduced below threshold.

3

RPM increased. WOB is returned to original value.

Optimization resumes.

5

Stick-Slip Protocol

4

2




Autodriller (ADR) Management

ADR Condition System Response

Control loop oscillationsAdjust setpoints to put ADR back in WOB-control mode

Torque limiting

DIFP limiting

• Operating state of ADR is critical for closed-loop optimization.

• ADR control issues [1]:

• Poor setpoint tracking.

• Control loop oscillations.

• ADR should be in a favorable control state for optimization.

[1] Pastusek et al. “Drill Rig Control Systems: Debugging, Tuning, and Long Term Needs”. SPE-181415.




Deployment Challenge #1: Human Factors

• User trust is needed:

• Driller must have confidence that system operating as designed → notifications/alerts.

• Organizational buy-in is needed [2].

[2] Behounek et al. “Change Management Challenges Deploying a Rig-Based Drilling Advisory System”. SPE-194184.




Deployment Challenge #2: Conservative Parameter Limits

For optimal drilling, true equipment limits should be used.

Upper WOB Limit

RPM

WOB

Lower WOB Limit

Low

er

RP

M L

imit

Upp

er

RP

M L

imit

optimization space

Upper WOB Limit

RPM

WOB

Lower WOB Limit

DIFP Limit (Autodriller)

ROP Limit (Autodriller)

Low

er

RP

M L

imit

Upp

er

RP

M L

imit

reduced optimization

space




Depth (ft)0 2000 4000 6000 8000 10000 12000

Depth (ft)

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Deployment Challenge #3: Following the Limit Roadmap

• Small optimization window

• Frequent, ad-hoc changes

Bad Practice:

• Wide limit window

• Infrequent changes

• Allow system to optimize

Good Practice:




Field Deployment




ROP Improvement

1st well

No system

2nd well

No system

3rd well

With system

Each drilling trial has 3 consecutive wells.

~90 trials ~90 trials

Top quartile ROP improvement = 18.1% and 17.4%.




Conclusions

• Formations change rapidly → need closed-loop optimization:

• Simple (no model) algorithm is best for scalability.

• Mitigate dysfunction with triggered protocols.

• Create a good limit roadmap and follow it.

• Large-scale deployment: 270+ rigs, 1700+ wells, 8 countries.

• Average rotary ROP improvement of 7% (top quartile = 18%)

in 90 drilling trials.




Acknowledgements / Thank You / Questions

The staff at ExxonMobil Upstream Research Company.

The many field and office personnel who contributed to deployment of this system.

Mark Pawson, David Holoboff, Abdulkareem Dolapo, and Usman Farooq.

Special thanks to:

Documents

SPE 199601 Large-Scale Deployment of a Closed …SPE 199601 Large-Scale Deployment of a Closed-Loop Drilling Optimization System Stephen Lai 2 3–5 March 2020 Galveston Island Convention