Case Study: Methods for Automated Drilling … Study: Methods for Automated Drilling Performance...
Transcript of Case Study: Methods for Automated Drilling … Study: Methods for Automated Drilling Performance...
Case Study: Methods for
Automated Drilling Performance
Analysis Based on Downhole
MeasurementsHamza Sellami
Institute of Dynamics and Vibration Research (IDS)
Leibniz Universität Hannover
Pedro Arevalo (BHGE), Ilja Gorelik (IDS), Hatem Oueslati (BHGE)
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Introduction and Motivation
▪Up to 30% of tools failure.
▪750 Mi. USD/year for tools maintenance.
▪Low performance, poor borehole quality, high NPT…
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Drilling Performance Framework
Drilling
Parameters
BHA Design
Well Path
Hydraulics
Etc…
Drilling
Performance
Drilling
Environment
RT Parameter
Optimization
Drilling Optimization
Post-Well Data Analysis
Drilling
System
▪ „The culture, where the decisions needed to achieve improvements
in drilling performance are driven by detailed data analysis.”
Drilling Performance Framework
Performance
Qualifiers
(PQ)
Performance
Evaluators
(PE)
Drilling
Optimization
▪PQ describe the drilling operation from an efficiency standpoint.
▪PE inspect the behavior of the drilling system.
Drilling
Performance
Performance
Attributes
Key
Performance
Indicators Recommendations
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Performance Qualifiers
Power In from rig
▪ RPM/Torque
▪ WOB
▪ Flow Rate
Power In from motor
▪ RPM/Torque
Power Out drill bit
▪ ROP
▪ Vibrations
Power Out drill string
▪ Torque and
Drag
▪ Vibrations
MSE =WOB
A+
120 ∙ π ∙ TOB ∙ RPM
A ∙ ROP
▪MSE is the work expended
per volume of rock.
Surface
MSE
Downhole
MSE
Drill string
MSE
MEE =Downhole MSE
Surface MSE
Performance Qualifiers
Power = MSE ∙ ROP ∙ A
Efficient
Drilling
Inefficient
Drilling
Power Graph: ROP vs. MSE Day Curve: Depth vs. Duration
▪The slope is the instantaneous ROP.
Downhole Surface Power Lines
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Performance Evaluators
Steering
Unit
MWD (Directional,
Gamma, etc…)Drill
Bit
▪Loads Control
▪Formation Change Index
▪Drill Bit Performance
▪Vibration Management
• Average and High-Speed Data
• Accelerations: Lateral, Axial and
Torsional
• Loads: Torque, Bending, Weight
• RPM, Pressure, Temperature
Dynamics Measurement Tool
Drill Bit Performance
WOB
RO
P
TO
B
TO
B
WOB 1 WOB 2
Bit 1
Bit 2
DO
C
Given
TOB
Bit 1
Bit 2Given
TOB
DO
C 1
DO
C 2
Given
WOB
RO
P 1
RO
P 2
Bit 1
Bit 2
Bit Response Bit Aggressiveness Bit Efficiency
WOB
▪A more aggressive bit generates the same torque with less WOB.
▪A more efficient bit drills faster at a given TOB and withstands
Stick-Slip.
Vibration Management
Lateral Vibration
e.g. Whirl
Axial Vibration
e.g. Bit Bounce
Torsional Vibration
e.g. Stick-Slip, HFTO
Stability Map: WOB vs. RPM
Vibration ManagementHFTO Graph
Tangential Acc. vs. RPM
Bending DistributionBending Moment vs. Whirl RPM
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Data Acquisition
Memory
File
Tool Memory Dumping
LAS File Creation
Graphs
Statistics
KPIs
Customer
Operation
Research
Groups
Data Processing
Analytics Application
LAS
File
Drilling Optimization
1 2 3 4
Requirements:
▪Modular structure.
▪ Intuitive and simple user Interface.
▪LAS File as input.
Analytics
Application
Analytics Application UI
▪Overview
▪QuickCheck
▪Performance
▪Drill Bit
▪Logs
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Case Studies Scope
▪Special Task Force.
▪Offshore Field in the North Sea.
▪12“ sections of three drilled
wells (A), (B), (C).
▪Hard formations
▪Dominant vibration modes: Low
and high frequency torsional
oscillations.
Analysis of Time and Depth based Data using the Analytics
Application.
Well A Objective: Study the influence of the mud Motor and the moderate
Stick-Slip on HFTO.
▪ The position of the motor can be
strategically planned to decouple
a portion of the BHA.
▪ The moderate Stick-Slip should be
avoided to limit the amplitudes of
the tangential accelerations.
Well B Objective: Investigation of the root cause of severe Stick-Slip and the
performance of the AST Tool.
▪ The AST Tool cannot be considered as efficient
solution for the mitigation of Stick-Slip.
▪ It is unlikely that the root cause of Stick-Slip is the
interaction between the drill string and the wellbore.
▪ Hybrid bits generate smoother and more controlled
torque.
Outline
• Introduction and Motivation
• Drilling Performance Framework
• Performance Qualifiers
• Performance Evaluators
• Analytics Application
• Field Case Studies
• Summary
Summary
▪ The defined KPIs establish a solid
framework to better understand the
drilling dynamics.
▪ The analytics application provides
full-scale techniques to speed up
the data analysis process.
▪ The success of the analytics
application in supporting the
drilling operations in the North Sea
paves the way for an expanded
usage in other Regions.
Thank you for your attention
!!!Questions?