Practical application of the UKOOA Ignition Model/media/Documents/Subject Groups/Safety_Lo… · PRACTICAL APPLICATION OF THE UKOOA IGNITION MODEL Brian Bain, Matthew Celnik and Geir

PRACTICAL APPLICATION OF THE UKOOA IGNITION MODEL

Brian Bain, Matthew Celnik and Geir Korneliussen

Det Norske Veritas Limited, UK

The UKOOA ignition model [Ignition Probability Review, Model Development and Look-up Cor-

relations; The Energy Institute, London; 2006] is the UK offshore industry standard for determining

the ignition probability of flammable releases on offshore installations. As the model is dependent

on a large number of parameters, several look-up correlations were developed for typical onshore

and offshore modules, to reduce the model to a limited set of parameters. There remains some

debate about how these look-up correlations can best be applied in order to describe all conditions

satisfactorily.

A number of enhancements and clarification to the existing look-up correlations for offshore

installations are proposed. The hot-work hours for a typical offshore module was defined in the

original model as 15 hours/year, however, this may be considered very low if substantial works

are undertaken. Therefore, an enhancement to the look-up correlations is proposed to account

for increased hot-work hours. A change to the model to allow users to specify different splits

between immediate and delayed ignition is also proposed.

INTRODUCTIONIn the field of QRA there are many areas where both themethodology and specific data to be applied to a problemhave a degree of uncertainty. Of these various areas, thetopic of ignition probability perhaps has the greatest levelof uncertainty. Various formulations have been proposedand practitioners have been aware that these can lead to awide range of calculated probabilities for the same situation.This is significant since a large proportion of the risks toboth onshore and offshore installations and personsworking in them come from ignited hydrocarbon and chemi-cal releases, and the ignition probability is a direct multi-plier for these. Consequently, the accuracy of the ignitionprobability has a large effect on the overall calculated riskfigures and therefore on the assessment of measures whichmay be deemed necessary to reduce these risks.

In the UK an attempt to address this situation was madein a project undertaken by ESR Technology, co-sponsored bythe United Kingdom Offshore Operators Association(UKOOA) (now Oil & Gas UK), the Health and SafetyExecutive (HSE) and the Energy Institute (EI) and with con-tributions from operators and other technical consultancies.The work culminated in the issue of the report published bythe Energy Institute entitled “Ignition Probability Review,Model Development and Look-Up Correlations” in January2006 [1]. The review element of the work concluded thatthe commonly applied approach, up to that point, of adoptinggeneric correlation based on mass release rates was overlysimplistic and lead to overly conservative estimates in somesituations. A new model was developed which drew largelyon the work of DNV [2], WS Atkins [3] and the “GasBuild-up JIP Workbook” [4]. The new model wasimplemented within an Excel workbook distributed withthe EI report [1].

It was recognised that the work involved in collectinga large amount of data for the full model may be too onerousfor some risk assessments. Consequently, the EI report [1]also describes a second phase of the work in which the

full model was used to develop a series of correlationsbased on the mass release rate. Although it was intendedthat the look-up correlation version be used in certain cir-cumstances, such as concept studies or where there wasinsufficient data to populate the full model, it has becomecommon practice to use the correlations in all QRA workbecause of the relative ease of implementation.

The model has become generally referred to as the“UKOOA Ignition Model” despite the fact that the UnitedKingdom Offshore Operators Association “UKOOA” effec-tively became Oil and Gas UK in 2007. This name is givento both the full model and the simplified look-up correlationversion. However, the predominant use of the latter meansthat it is this version which practitioners normally meanwhen referring to the “UKOOA ignition Model”. Thecurves are illustrated in the OGP Risk Assessment dataDirectory [5].

This paper looks at five topics associated with the useof the model which may improve its ease of use or its accu-racy. These are presented in summarised form to provide anoverview.

CHANGED TABULATIONThe data underlying the lookup correlations is presented in atable within the report [1] and replicated in Table 1.

In essence the data describes a number of releaserate/ignition probability pairs between which the ignitionprobability for the required release rate can be obtained bylogarithmic interpolation but subject to remaining withindefined limits, that is the “Maximum Prob” and “MinimumProb” columns in Table 1. However, in this format the shapeof the correlation is difficult to visualise and the equationsfor calculating the ignition probability for a given releaserate is more complex than it needs to be.

An alternative tabulation is presented below in whichthe co-ordinates of the points between which logarithmicinterpolation can take place are given explicitly. This is pre-sented in Table 2.

SYMPOSIUM SERIES NO. 158 Hazards XXIII # 2012 IChemE

363

Tab

le1.

Lookup

Corr

elat

ion

Dat

aF

or

Ignit

ion

Pro

bab

ilit

ies,

rep

roduce

dfr

om

[1].

No.

Type

Max

imum

Pro

b

Min

imum

Pro

b

Poin

t

a

Gra

die

nt

a

Off

set

a

Poin

t

b

Gra

die

nt

b

Off

set

b

Poin

t

c

Gra

die

nt

c

Off

set

c

Poin

t

d

1P

ipe

Liq

uid

Indust

rial

0.0

70.0

01

0.1

0.5

58795

22.1

8593

70

NN

0N

N0

2P

ipe

Liq

uid

Rura

l0.0

07

0.0

01

0.1

0.6

05288

22.1

3944

0.3

0.1

27125

22.3

8946

70

NN

0

3P

ipe

Gas

LP

GIn

dust

rial

10.0

01

0.1

0.7

39652

22.2

1896

1000

NN

0N

N0

4P

ipe

Gas

LP

GR

ura

l1

0.0

01

0.1

0.1

29819

22.8

2879

10

0.8

0103

23.5

1000

NN

0

5S

mal

lP

lant

Gas

LP

G0.6

0.0

01

0.1

0.3

56547

22.6

0206

11.5

6813

22.6

0206

30.7

34824

22.2

0447

1000

6S

mal

lP

lant

Liq

uid

0.1

0.0

01

0.1

0.3

38819

22.6

1979

10.8

09894

22.6

1979

100

NN

0

7S

mal

lP

lant

Liq

uid

Bund

0.0

13

0.0

01

0.1

0.3

38819

22.6

1979

10.8

09894

22.6

1979

100

NN

0

8L

arge

Pla

nt

Gas

LP

G0.6

50.0

01

0.1

0.3

56547

22.6

0206

11

22.6

0206

100

NN

0

9L

arge

Pla

nt

Liq

uid

0.1

30.0

01

0.1

0.3

56547

22.6

0206

10.8

40621

22.6

0206

100

NN

0

10

Lar

ge

Pla

nt

Liq

uid

Bund

0.0

50.0

01

0.1

0.3

38819

22.6

1979

10.8

09894

22.6

1979

100

NN

0

11

Lar

ge

Pla

nt

Confi

ned

Gas

LP

G0.7

0.0

01

0.1

0.3

56547

22.6

0206

11.2

11604

22.6

0206

70

0.3

1737

20.9

5211

1000

12

Tan

kL

iquid

300×

300

mB

und

0.1

20.0

01

0.1

0.0

75721

22.9

0309

10.3

95757

22.9

0309

70.8

8091

23.3

1309

500

13

Tan

kL

iquid

100×

100

mB

und

0.0

15

0.0

01

0.1

0.0

75721

22.9

0309

10.3

95757

22.9

0309

70.8

8091

23.3

1309

500

14

Tan

kG

asL

PG

Sto

rage

Pla

nt

10.0

01

0.1

0.0

23065

22.9

3554

11.4

58907

22.9

3554

100

NN

0

15

Tan

kG

asL

PG

Sto

rage

Indust

rial

10.0

01

0.1

0.0

23065

22.9

3554

11.1

45784

22.9

3554

100

0.6

47338

21.9

3865

700

16

Tan

kG

asL

PG

Sto

rage

Rura

l0.5

0.0

01

0.1

0.0

23065

22.9

3554

11.1

23063

22.9

3554

10

0.4

0624

22.2

1872

1000

17

Off

shore

Pro

cess

Liq

uid

0.0

175

0.0

01

0.1

0.4

00548

22.5

5806

100

NN

0N

N0

18

Off

shore

Pro

cess

Liq

uid

NU

I0.0

10.0

01

0.1

0.4

00548

22.5

5806

100

NN

0N

N0

19

Off

shore

Pro

cess

Gas

Open

dec

kN

UI

0.0

25

0.0

01

0.1

0.0

37789

22.9

2082

10.8

80788

22.9

2082

30

NN

0

20

Off

shore

Pro

cess

Gas

Typic

al0.0

40.0

01

0.1

0.7

68182

22.1

9042

30.3

90377

22.0

1017

10

NN

0

21

Off

shore

Pro

cess

Gas

Lar

ge

Module

0.0

50.0

01

0.1

0.8

45058

22.1

1355

50.2

85097

21.7

2215

30

NN

0

22

Off

shore

Pro

cess

Gas

Conges

ted_M

ech

Ven

ted

Module

0.0

40.0

01

0.1

1.1

34699

21.8

2391

10.2

16588

21.8

2391

50

NN

0

23

Off

shore

Ris

er0.0

25

0.0

01

0.1

0.5

25219

22.4

3339

30

NN

0N

N0

24

Off

shore

FP

SO

Gas

0.1

50.0

01

0.1

0.0

72551

22.8

8606

11.2

13764

22.8

8606

50

NN

0

25

Off

shore

FP

SO

Gas

Wal

l0.1

50.0

01

0.1

0.5

44175

22.4

1443

0.3

1.2

31261

22.0

5517

10

NN

0

26

Off

shore

FP

SO

Liq

uid

0.0

28

0.0

01

0.1

0.4

68588

22.4

9002

100

NN

0N

N0

27

Off

shore

Engulf

_blo

wout_

rise

r0.1

0.0

01

0.1

0.6

52869

22.3

0574

100

NN

0N

N0

28

Cox,

Lee

s,A

ng

–G

as0.3

00.5

0.6

41939

21.8

0676

100

NN

0N

N0

29

Cox,

Lee

s,A

ng

–L

iquid

0.0

80

0.5

0.3

92472

21.8

8185

100

NN

0N

N0

30

Tan

kL

iquid

–die

sel,

fuel

oil

0.0

024

0.0

01

0.1

0.0

10724

22.9

8928

10.0

67994

22.9

8928

70.5

54906

23.4

0076

500


364

Tab

le2.

Lookup

Corr

elat

ion

Dat

aP

rese

nte

din

Alt

ernat

ive

Form

Poin

t1

Poin

t2

Poin

t3

Poin

t4

Poin

t5

Poin

t6

Poin

t7

Cas

e

No.

Cas

eD

escr

ipti

on

Q(k

g/s

)P

ign

Q(k

g/s

)P

ign

Q(k

g/s

)P

ign

Q(k

g/

s)P

ign

Q(k

g/s

)P

ign

Q(k

g/s

)P

ign

Q(k

g/

s)P

ign

1P

ipe

Liq

uid

Indust

rial

0.0

10.0

0100

0.0

3493

0.0

0100

0.1

00

0.0

0180

70.0

00

0.0

7000

100000

0.0

7000

2P

ipe

Liq

uid

Rura

l0.0

10.0

0100

0.0

3787

0.0

0100

0.1

00

0.0

0180

0.3

00

0.0

0350

70.0

00

0.0

0700

70.0

00

0.0

0700

100000

0.0

0700

3P

ipe

Gas

LP

GIn

dust

rial

0.0

10.0

0100

0.0

8791

0.0

0100

0.1

00

0.0

0110

1000

1.0

0000

100000

1.0

0000

4P

ipe

Gas

LP

GR

ura

l0.0

10.0

0100

0.0

4799

0.0

0100

0.1

00

0.0

0110

10.0

00

0.0

0200

1000.0

00

0.0

8000

23408.5

47

1.0

0000

100000

1.0

0000

5S

mal

lP

lant

Gas

LP

G0.0

10.0

0100

0.0

7654

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0250

3.0

00

0.0

1400

498.9

91

0.6

0000

100000

0.6

0000

6S

mal

lP

lant

Liq

uid

0.0

10.0

0100

0.0

7548

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0240

100.0

00

0.1

0000

100000

0.1

0000

7S

mal

lP

lant

Liq

uid

Bund

0.0

10.0

0100

0.0

7548

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0240

8.0

53

0.0

1300

100.0

00

0.0

1300

100000

0.0

1300

8L

arge

Pla

nt

Gas

LP

G0.0

10.0

0100

0.0

7654

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0250

100.0

00

0.2

5000

260.0

00

0.6

5000

100000

0.6

5000

9L

arge

Pla

nt

Liq

uid

0.0

10.0

0100

0.0

7654

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0250

100.0

00

0.1

2000

109.9

90

0.1

3000

100000

0.1

3000

10

Lar

ge

Pla

nt

Liq

uid

Bund

0.0

10.0

0100

0.0

7548

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0240

42.4

92

0.0

5000

100.0

00

0.0

5000

100000

0.0

5000

11

Lar

ge

Pla

nt

Confi

ned

Gas

LP

G0.0

10.0

0100

0.0

7654

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0250

70.0

00

0.4

3000

325.0

28

0.7

0000

100000

0.7

0000

12

Tan

kL

iquid

300×

300

mB

und

0.0

10.0

0100

0.0

5250

0.0

0100

0.1

00

0.0

0105

1.0

00

0.0

0125

7.0

00

0.0

0270

519.6

17

0.1

2000

100000

0.1

2000

13

Tan

kL

iquid

100×

100

mB

und

0.0

10.0

0100

0.0

5250

0.0

0100

0.1

00

0.0

0105

1.0

00

0.0

0125

7.0

00

0.0

0270

49.0

35

0.0

1500

100000

0.0

1500

14

Tan

kG

asL

PG

Sto

rage

Pla

nt

0.0

10.0

0104

0.0

0160

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0116

100.0

00

0.9

6000

102.8

38

1.0

0000

100000

1.0

0000

15

Tan

kG

asL

PG

Sto

rage

Indust

rial

0.0

10.0

0104

0.0

0160

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0116

100.0

00

0.2

2700

988.1

06

1.0

0000

100000

1.0

0000

16

Tan

kG

asL

PG

Sto

rage

Rura

l0.0

10.0

0104

0.0

0160

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0116

10.0

00

0.0

1540

52551.5

38

0.5

0000

100000

0.5

0000

17

Off

shore

Pro

cess

Liq

uid

0.0

10.0

0100

0.0

7882

0.0

0100

0.1

00

0.0

0110

100.0

00

0.0

1750

100000

0.0

1750

18

Off

shore

Pro

cess

Liq

uid

NU

I0.0

10.0

0100

0.0

7882

0.0

0100

0.1

00

0.0

0110

24.7

31

0.0

1000

100.0

00

0.0

1000

100000

0.0

1000

19

Off

shore

Pro

cess

Gas

Open

dec

kN

UI

0.0

10.0

0101

0.0

0803

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0120

30.0

00

0.0

2400

31.4

23

0.0

2500

100000

0.0

2500

20

Off

shore

Pro

cess

Gas

Typic

al0.0

10.0

0100

0.0

8833

0.0

0100

0.1

00

0.0

0110

3.0

00

0.0

1500

10.0

00

0.0

2400

37.0

08

0.0

4000

100000

0.0

4000

21

Off

shore

Pro

cess

Gas

Lar

ge

Module

0.0

10.0

0100

0.0

8933

0.0

0100

0.1

00

0.0

0110

5.0

00

0.0

3000

30.0

00

0.0

5000

100000

0.0

5000

22

Off

shore

Pro

cess

Gas

Conges

ted_M

ech

Ven

ted

Module

0.0

10.0

0100

0.0

9194

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

1500

50.0

00

0.0

3500

92.6

24

0.0

4000

100000

0.0

4000

23

Off

shore

Ris

er0.0

10.0

0100

0.0

8340

0.0

0100

0.1

00

0.0

0110

30.0

00

0.0

2200

38.2

67

0.0

2500

100000

0.0

2500

24

Off

shore

FP

SO

Gas

0.0

10.0

0100

0.0

2688

0.0

0100

0.1

00

0.0

0110

1.0

00

0.0

0130

50.0

00

0.1

5000

100000

0.1

5000

25

Off

shore

FP

SO

Gas

Wal

l0.0

10.0

0100

0.0

8393

0.0

0100

0.1

00

0.0

0110

0.3

00

0.0

0200

10.0

00

0.1

5000

100000

0.1

5000

26

Off

shore

FP

SO

Liq

uid

0.0

10.0

0100

0.0

8160

0.0

0100

0.1

00

0.0

0110

100.0

00

0.0

2800

100000

0.0

2800

27

Off

shore

Engulf

_blo

wout_

rise

r0.0

10.0

0100

0.0

8642

0.0

0100

0.1

00

0.0

0110

100.0

00

0.1

0000

100000

0.1

0000

28

Cox,

Lee

s,A

ng

–G

as0.0

10.0

0081

0.5

0000

0.0

1000

100.0

00

0.3

0000

100000

0.3

0000

29

Cox,

Lee

s,A

ng

–L

iquid

0.0

10.0

0215

0.5

0000

0.0

1000

100.0

00

0.0

8000

100000

0.0

8000

30

Tan

kL

iquid

–die

sel,

fuel

oil

0.0

10.0

0100

0.1

0000

0.0

0100

1.0

00

0.0

0103

7.0

00

0.0

0117

25.5

51

0.0

0240

100000

0.0

0240


365

This table defines each of the curves using between 4and 7 points. As an example, the curve for “OffshoreProcess Gas Typical” is shown in Figure 1.

A specific ignition probability is then obtained fromthe equation.

Pign = elog pn+

(logQ−logQn )(logPn+1−logPn )

logQn+1−logQn

WherePign is the Ignition probability at release rate QPn is the ignition probability at release rate Qn, andPn+1 is the ignition probability at release rate Qn+1

and where the points (Qn, Pn) and (Qn+1, Pn+1) areadjacent points in Table 2 between which the value ofQ lies.

INTERPOLATED IGNITION PROBABILITIESIt is usual for analysts to utilise a single look-up correlationin determining an ignition probability. In this case theanalyst selects the correlation they consider to be the bestrepresentation of the situation they are dealing with.However, there are many situations where none of the cor-relations are strictly appropriate. One scenario described inthe reporting of the use of the correlations [1] is the case offlashing releases. Correlations are provided for gas/LPG(full flash) releases and for liquid releases where the flashfraction is less than 10%. This does not cover 2-phasereleases or liquid releases with a flash fraction between10% and 100%. It is suggested that an ignition probabilitycan be calculated by combining the results from two differ-ent but appropriate correlations. For example, if we con-

sider a 10 kg/s release of well fluids release with liquidhydrocarbon (80%) and gas (20%) fractions on an offshoreinstallation then this could be considered as an 8 kg/srelease of liquid occurring simultaneously with a 2 kg/srelease of gas. The EI Report [1] suggests that the ignitionprobabilities for these could be calculated separately usingtheir appropriate correlations and then combined by calcu-lating the overall probability of non-ignition. This approachrecognises that the leak would be simultaneously producinga gas cloud and liquid pool which could be susceptible todifferent ignition sources. The two are combined in theequation.

Pign−overall = 1 − [(1 − Pign−gas) × (1 − Pign−liquid)]

This can result in the overall probability being some-where between the ignition probability for the two look-upcorrelations or higher. The results are shown in Figure 2.

However, it may be considered inappropriate tocombine the two probabilities in this way, given that theareas covered by the gas and liquid are likely to overlapso that the two are not additive. In this case, it may bemore appropriate to use the higher of the two ignitionprobabilities based on the total release rate (10 kg/s inthis case).

A further alternative could be to evaluate the ignitionprobability at the full release rate on both correlations andobtain an estimate for the 2-phase release using a linearinterpolation. This is shown in Figure 3 and indicates arather different result for the same scenario (1.04% com-pared with 1.73%).

Figure 1. Example Look-up Curve (Tank Liquid 300 × 300 m Bund)


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The same techniques could also be used for gas orliquid releases if an analyst considers that a situation is some-where between two of the standard cases. For example if thesize of the module is considered to be greater than “typical”but not sufficient to be classed as “large”. Figure 4 shows anexample of a case of a 10 kg/s gas release considered to bemid-way between the two standard cases.

FRACTION OF IMMEDIATE RELEASESThe use of the look-up correlations has been generallyaccepted and implemented by risk analysts and a consistentevaluation of the “total” ignition probability has beenachieved. However, there remain differences in approach

as to how this probability should be apportioned between“immediate” and “delayed” ignitions.

For much of the time during the development of theUKOOA model only the total ignition probability was con-sidered. However, the steering group also acknowledgedthat typical QRA studies split the overall value between“immediate” ignitions in which ignition occurs at thepoint of release and “delayed” ignitions requiring thebuild-up of a vapour cloud which is ignited by a remotesource. These two scenarios may be treated differently interms of consequences and therefore of overall risk. Thereis insufficient reliable information from historical recordsto determine the fraction in overall terms, let alone to deter-mine the dependence on release rate.

Figure 2. Calculation of Ignition Probability for a 2-Phase Release

Figure 3. Calculation of Ignition Probability for a 2-Phase Release Using Interpolation


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The EI report concluded the following;

“The DNV TDIM Project also analysed ignition eventsto estimate the occurrence of self-ignition (i.e. where the leakand ignition had a common cause/dependancy). This con-cluded that a common leak and ignition effect may only bepresent in�0.1% of releases, giving a probability of ignitiondue to this mechanism of approximately 0.001. This is inreasonable agreement with the values suggested inTable 1.32, and has been adopted within the ignition model”

The table referred to essentially provided valuesderived from the correlation Pign,imm ¼ 0.0001 Q, wherethe mass release rate, Q, is measured in kg/s. This wouldgive the value for immediate ignition of 0.001 for a10 kg/s release. Inspection of the “full” UKOOA spread-sheet model confirms that this is the value calculated andthat there is no dependence on the release rate.

An examination of the use of the look-up correlationsby different practitioners suggest that many, perhaps themajority, do not follow this practice but instead employ a pro-portional split between the “immediate” and “delayed” cases.The origins of this approach are based partly on practiceemployed prior to the development of the model and partlyfrom text contained in a later section of the report [1]dealing with ignition timing and which states the following;

“Assuming early ignition relates to ignition withinone minute or so of the leak commencing, then the typicalQRA practice to assume a 50:50 or 30:70 distributionbetween early and delayed ignition appears to be reason-able given the data available. Based on the data availablein Table 2.11, a 30:70 (early: delayed) distribution maybe representative of early ignition within 30 s, whereas a50:50 distribution may be representative of early ignitionwithin 60 s.”

It should be noted in the above that the term used is“early” rather than “immediate” and can be applied to

ignitions occurring up to 60 seconds after the start of therelease.The term“delayed” in this sense isused todenote igni-tions after this time, whereas, in this paper, “delayed” refers tothose ignition cases which aren’t immediate. During this“early” period a substantial vapour cloud can form which, ifignited, would give rise to an explosion with large overpres-sure. Given that the split between “immediate” and“delayed” is primarily intended to distinguish between “fireonly” and “explosion plus fire” cases, it is considered thatthe use of a 30:70 or 50:50 split does comply with the trueimplementation of the UKOOA model. There are also caseswhere 70% of the total ignition have been taken as immediate.

Figure 5 shows the difference between the use of aPign ¼ 0.001 approach and a 30:70 split approach.

As can be seen from figure 5, the two approaches cangive very different results. This difference may be reflectedin the overall results of the QRA. It is not clear whether aproportional split is appropriate or not and the correctapproach may be dependent on the approach taken in thecorresponding explosion analysis. However, a proportionalsplit does not comply with the intent of the UKOOA model.

In order to allow a convenient means of apportioningthe total ignition probability it is proposed that the immedi-ate ignition probability can be calculated as

Pign−imml = a + bPign

where the parameters a and b are selected by the analyst.Consequently the delayed ignition probability would

be calculated as

Pign−del = Pign − Pign−imm = (1 − b)Pign − a

In the examples shown in Figure 5, the first graph usesa ¼ 0.001, b ¼ 0. In the second graph, a ¼ 0, b ¼ 0.3.

The variation in approaches can be more significant ifmore than one analyst is involved in the overall work and

Figure 4. Calculation Using Interpolation for a Gas Release


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are adopting different approaches. One example of this iswhere one consultant is responsible for explosion analysisand another is responsible for incorporating the results ofthese into the overall QRA. If the two consultants areusing different approaches, it may be possible for part ofthe true risk to be omitted or for it to be double counted.

SINGLE PARAMETER MODIFICATIONThe look-up correlations were derived from running a seriesof representative cases through the full UKOOA model andfitting a simplified curve to achieve the correlations tabu-lated above. There may be scenarios when it is knownthat one of the parameters is significantly different fromthe value assumed in the derivation of the correlation. Asan example, if the number of hot-work hours is significantlyhigher than what was assumed in the initial derivation, theremay be concerns that use of the correlation will underesti-mate the true value.

The EI report [1] provides some information on theinputs required for some of the runs of the full modelwhich were used to derive the correlations.

To develop a simple model to account for a singleadditional parameter, for example hot-work hours, the fol-

lowing procedure was used for each scenario and release-rate point Q in Table 2:

1. Run the full UKOOA model with default hot-workhours (HW0) to get the base ignition probability, Pign,0.

2. Run the full UKOOA model with a range of hot-workhours, hi to get a set of ignition probabilities, pi. Suffi-cient points in log-space were used to cover the appli-cable range of hot-work hours per year.

3. Fit a straight line to the (hi, pi) points to determine agradient, k.

4. For the actual number of hot-work hours, calculateignition probability:

Pign = Pign,0 + k · (HW − HW0)

Table 3 gives values of k calculated for offshorescenarios, and also lists the basis hot-work hours for eachscenario. These new (Q, Pign) points then replace those inTable 2, and the subsequent methodology for calculationof ignition probability is identical to that discussed pre-viously. This method assumes that the ignition probabilityis approximately linearly dependent (in log-space) on theparameter of interest. For the case of hot-work, this is

Figure 5. Alternative Approaches in Splitting Total Ignition Probability

Table 3. Default Hot-Work Hours for Offshore Correlation Scenarios

UKOOA Correlation Basis Hot-work (hrs/yr)

Hot-work Pign Gradients, k

Point a Point b Point c Point d

Offshore Process Liquid 15 1.14E-07 1.73E-05 N/A N/A

Offshore Process Liquid NUI 0 1.18E-07 1.74E-05 N/A N/A

Offshore Process Gas Opendeck NUI 0 5.09E-09 1.61E-07 8.07E-07 N/A

Offshore Process Gas Typical 15 2.88E-06 3.72E-05 3.69E-05 N/A

Offshore Process Gas Large Module 15 1.32E-06 4.37E-05 4.31E-05 N/A

Offshore Process Gas Congested_Mech Vented Module 15 1.03E-06 2.83E-05 3.65E-05 N/A

Offshore Riser 0 2.36E-09 1.17E-06 — N/A

Offshore FPSO Gas 0 7.93E-09 2.50E-07 5.19E-05 N/A

Offshore FPSO Gas Wall 0 7.93E-09 4.12E-08 7.57E-06 N/A

Offshore FPSO Liquid 0 1.94E-08 1.47E-05 N/A N/A

Offshore Engulf_blowout_riser 15 1.41E-08 3.54E-05 N/A N/A


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indeed the case, as can be seen in Figure 6, which shows the(hi, pi) points for the “UKOOA Proc Gas” scenario for arelease rate of 3 kg/s.

Figure 7 shows the change to the ignition probabilityfor the “UKOOA – Proc Gas” scenario when the number ofhot-work hours are increased from the base (15 hours/year)to 2000 hours/year.

IMPLEMENTATION IN SAFETI OFFSHOREThe UKOOA ignition modelling methodology is beingincorporated into the Offshore QRA software currently

being developed by DNV Software so that it can be usedas one of a number of alternatives. This implementationalso aims to improve the usability of the full model sothat less reliance is placed on the more approximate look-up correlation approach.

One key element of an offshore QRA is to assess thelikelihood of getting an explosion overpressure above toler-ance limits for barriers, equipment and personnel:

f pressure.limit = frelease · Pignition|release · P pressure.limit|ignition

where f is frequency and P is conditional probability.

Figure 6. Ignition Probability vs. Hot-Work Hours for “UKOOA Proc Gas” Scenario at a Release Rate of 3 kg/s

Figure 7. Effect of Increase in Hot-Work Hours on Ignition Probability


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Whereas, it is generally more convenient to modular-ise a QRA study in models dealing with aspects of theoverall problem, it is found that the interaction of theignition timing and the explosion analysis is such that itnecessary to treat the two methodologies together in thesame piece of analysis.

The worst case overpressure is typically higher thanwhat is possible to design barriers to withstand. Sincethe overpressure is sensitive to the size of the ignited flam-mable cloud it is important to be able to model the prob-ability of ignition vs. time and not only the total ignitionprobability. Safeti Offshore models the uncertainty inrelease rate, cloud build up, detection, ignition, etc. Thereliability of safety systems such as automatic (andmanual) detection, isolation & blowdown and shutdown ofignition sources are included.

The full UKOOA model has a built in dispersionmodel and can predict the probability of ignition versustime. It also allows site specific parameters such as releasedmaterial, process conditions, hotwork, module dimensions,weather/ventilation, etc. to be incorporated. This can alsobe applied to the look–up correlation approach.

Both the full UKOOA ignition model and the look-upcorrelations are implemented in Safeti Offshore. Defaultdata is provided in accordance with the values provided inthe full spreadsheet model to overcome the complexity of

having to enter all the detailed information that the fullmodel needs.

In the ignition modelling part of Safeti Offshore theanalyst can select from the following options:

. Use the full UKOOA cloud build up and ignition model

. Use the UKOOA look-up correlation with UKOOAcloud build up model

. Use the UKOOA look-up correlation with the moredetailed cloud build up model available in Safeti Off-shore

. Use TDIIM [2]

. Use an Expert correlation (total ignition probability vs.release rate).

CONCLUSIONSThe “UKOOA Ignition Model” has become the standardapproach for calculating the ignition probability of offshorehydrocarbon releases for offshore platforms in the UnitedKingdom continental shelf. If is also used for QRAstudies of offshore installations in other parts of the worldand in onshore studies. Typically, the look-up correlationform of the method has been adopted and this has broughtbenefits in terms of ease of use and consistency amongpractitioners.

Figure 8. Incorporation of the Look–up Correlation Approach Into Integrated Offshore QRA


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Despite this, there are some areas where the approachcould be amended to make it easier to use or adapted it toallow for the effects of variation of some key parameters.These include;

. Retabulation of the data defining the curves in order tomake its meaning more obvious.

. Interpolation of new look-up correlations to addresssituations which are intermediate between the standardcurves.

. A consistent treatment of the division of the overallignition probability into its “immediate” and “delayed”constituents.

. A means of incorporating changes in a single parameterto produce a more accurate result or to examine the sen-sitivity of the results to that parameter.

. Incorporation of the methodology into QRA studies andin particular its integration with explosion overpressureexceedence analysis where the distribution of ignitiontimes are important.

WORKS CITED

1. Energy Institute. Ignition Probability Review, ModelDevelopment and Look-up Correlations. IP ResearchReport. London: Energy Institute; 2006 IP, EnergyInstitute, HSE, UKOOA. ISBN 978 0 85293 454 8.

2. DNV. Ignition Modelling Time Dependent IgnitionProbability Model. Technical Report. Det NorskeVeritas; 1998. 96-3629.

3. WS Atkins. Development of a Method for the Deter-mination of On-site Ignition Probabilities. HSEResearch Report. HSE Books; 1998. ISBN 0 71761657 6.

4. BP Amoco, CERN, BG Technology. Gas Build-upfrom High Pressure Natural Gas Releases in NaturallyVentiliated Offshore Modules, JIP Workbook on GasAccumulation in a Confined Area. JIP Workbook.BP Amoco, CERN, BG Technology; 2000.

5. International Association of Oil and Gas Producers.Ignition Probabilities. Risk Assessment Data Direc-tory. OGP Publications; 2010. 431-6.1.


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