11/18/2008

1

SPE Distinguished Lecturer Program

The SPE Distinguished Lecturer Program is funded principally through a grant from the SPE Foundation.

The society gratefully acknowledges the companies that support this program by allowing their professionals to participate as lecturers.

Special thanks to the American Institute of Mining, Metallurgical, and Petroleum g gEngineers (AIME) for its contribution to the program.

Society of Petroleum Engineers Distinguished Lecturer Programwww.spe.org/dl

Pitfalls to Avoid in AssessingA ifi i l Lif R Lif P fArtificial Lift Run-Life Performance

Francisco AlhanatiC-FER Technologies

Society of Petroleum Engineers Distinguished Lecturer Programwww.spe.org/dl

11/18/2008

2

Impact on Economics

• Artificial Lift Run Life Performance• Artificial Lift Run-Life Performance directly affects: – Work over frequency– Work over costs– Production losses

Impact of ESP Run-Life

20 Wellsaverage oil production per well: 1,000 bpdaverage intervention cost: 150 k US$average workover & waiting time: 60 daysoil price: US$60/bbl

Overall Workover CostsOverall Workover Costs

$100

$150

$200

$250

llion

s / y

ear

15%

20%

25%

30%

% re

venu

e

$0

$50

$100

0 120 240 360 480 600 720 840 960

Average Runtime (days)

mil

0%

5%

10%

%

11/18/2008

3

AL Run-Life Performance is important

• Key Performance Indicator (KPI)• Key Performance Indicator (KPI) – effects of changes in operational

conditions, equipment selection and operational practices

– used in many alliance contracts between operators and vendorsoperators and vendors

Assessing AL RL Performance

• Not as simple as it may sound• Not as simple as it may sound– Several measures used throughout the

industry– Trends are often misleading

• Issues must be understood, so that– Pitfalls can be avoided– Proper RL measures can be selected

11/18/2008

4

• For many installations Run Life is not

Run-Life and Runtime

• For many installations, Run-Life is not known, only Runtime– Systems that are still running– Systems that were pulled for other reasons

than system failure

Censoring

• The data is said to be “censored”• The data is said to be censored• One can only hope to obtain estimates

of average Run-Life• Based on all the systems Runtime

11/18/2008

5

Run-Life Estimates

• Average Runtime can be calculated for: – All systems (pulled or still running)y (p g)– Running systems only – Pulled systems only – Pulled and Failed systems only

• All these averages can be calculated based on different exposure timesp– Time-in-Hole, Total Runtime, Actual Runtime

• Over different (calendar) periods of time– Last two years, last five years, etc.

Run-Life Estimates• Average Runtime of pulled systems:

• Includes failure of other “systems”: tubing, sand control etcsand control, etc.

• It is a reasonable indicator of the overall production system reliability

• But not of the AL system reliability

• Average Runtime of failed systems:g y• Also affected by failures of other “systems”• Not a good indicator of the AL system

reliability either

11/18/2008

6

Run-Life Estimates

• At a certain point of time, all you can have is a statistical “best estimate” orhave is a statistical best estimate , or “expected value” of average Run-Life or Mean Time to Failure (MTTF)

Run-Life Estimates• Average Failure Rate:

– Number of failures per well over a period of time

• MTTF estimate:– the inverse of the average failure rate– ratio of the total time in operation (for all

systems pulled or still running) to thesystems, pulled or still running) to the number of failures:

failed

TTMTTF running

pulled

#∑ ∑+

=

11/18/2008

7

What is a Failure?

• Failure:Failure:– The termination of the ability

of an item to perform its required functions

ISO 14224: Petroleum and Natural Gas Industries: Collection and Exchange of Reliability and Maintenance Data for Equipment

Common Pitfalls

• Early Failures versus Frequent Failures• Early Failures versus Frequent Failures • Improvement versus Aging• Component Reliability and System RL • Failure Mechanism versus Failure

CauseCause

11/18/2008

8

ESP-RIFTS DataLocations of Fields

BP Nexen Shell

Chevron PDVSA Shell PDO

ConocoPhillips Petrobras TNK-BP

EnCana Repsol YPF TOTAL

ExxonMobil RosneftKuwait Oil Company Saudi Aramco

ESP-RIFTS: ESP Reliability and Failure Tracking System

Common Pitfalls

• Early Failures versus Frequent Failures• Early Failures versus Frequent Failures• Improvement versus Aging• Component Reliability and System RL • Failure Mechanism versus Failure

CauseCause

11/18/2008

9

What is the least reliable component?Is it the gas

Average Runtime of Failed

200

300

400500

600

700800

900

erag

e R

un T

ime

(day

s)

Is it the gas separator?

0

100

Cable DownholeSensors

GasSeparator

Motor Pump PumpIntake

Seal

ESP Component

Ave

Failure Rate

300

350

400

6 / d

ay)Which is more

li bl ?

0

50

100

150

200

250

ESP Cable DownholeSensors

GasSeparator

Motor Pump PumpIntake

Seal

ESP Component

Failu

re R

ate

(x10

-6reliable?The motor or the cable?

Common Pitfalls

• Early Failures versus Frequent Failures• Early Failures versus Frequent Failures • Improvement versus Aging• Component Reliability and System RL • Failure Mechanism versus Failure

CauseCause

11/18/2008

10

Is the system reliability improving?Or are the systems just aging?

4 0 MTTF (3 Wi d )

1 5

2.0

2.5

3.0

3.5

4.0

Run

-Life

Est

imat

e

MTTF (3 yr Window)

Average Runtime of Running

0.0

0.5

1.0

1.5

1997 1998 1999 2000 2001 2002 2003

Calendar Year

R

Common Pitfalls

• Early Failures versus Frequent Failures• Early Failures versus Frequent Failures • Improvement versus Aging• Component Reliability and System RL• Failure Mechanism versus Failure

CauseCause

11/18/2008

11

Is the equipment from both

manufacturers

Survival Curve

20

30

40

50

60

70

80

90

100

S (t

)Manufacturer AManufacturer B

equally reliable?

Failure Rate

300

350

400

6 / d

ay) Manufacturer A

Manufacturer B

0

10

20

0 12 24 36 48 60 72 84 96

time in operation (months)

0

50

100

150

200

250

Cable Gas Separator Motor Pump Pump Intake Seal

ESP Component

Failu

re R

ate

(x10

-6

Common Pitfalls

• Early Failures versus Frequent Failures• Early Failures versus Frequent Failures • Improvement versus Aging• Component Reliability and System RL • Failure Mechanism versus Failure

CauseCause

11/18/2008

12

Failure Classifications

• Reason for Pull – Suspected system failure or any other reason– Suspected system failure or any other reason – e.g.: stimulation, re-completion

• Primary Failed Item and Descriptor– Component (or part) in which the failure likely

initiated, and likely mechanism – Based on observations during pull or teardown– e.g. motor burn g

• Failure Cause:– The circumstances during design, manufacture or

use which have led to a failure– e.g. improper assembly during installation

Failure Analysis Process

System Failure Reason for Pull defined:

System Pull and Teardown- Items and Descriptors defined:

e.g., Shorted MLE

- Reason for Pull defined:e.g., No flow to surface

Failure Investigation- Cause defined:e.g., Installation; Improper Assembly

11/18/2008

13

Do I have a manufacturing (QC) problem?Or do I have an operational problem?

Number of Failures by Failure Cause

40

60

80

100

120

mbe

r of F

ailu

res

Completion

Installation

Manufacturing

Normal or ExpectedWear-and-TearOperation

Other

0

20

Cable GasSeparator

Motor Pump PumpIntake

Seal

ESP Component

Num

Other

Storage andTransportationSystem Design /Selection

Conclusions

• There are several measures used throughout the industrythroughout the industry

• One needs to understand their meaning to properly interpret the trends

• Best picture of the situation likely requires looking at several measuresI t i th h• Improvement requires thorough investigation of the failure causes

• Be aware of the pitfalls !

11/18/2008

14

Acknowledgement

• ESP-RIFTS JIP Participants:ESP RIFTS JIP Participants:– BP - Petrobras– Chevron - Repsol-YPF– ConocoPhillips - Rosneft– EnCana - Shell

ExxonMobil StatoilHydro– ExxonMobil - StatoilHydro– KOC - TNK-BP– Nexen - Total