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?