IMPERIAL COLLEGE LONDON Department of Earth Science and Engineering Centre for Petroleum Studies MANAGING OPERATIONAL WELL INTEGRITY – PRIORITISING REPAIRS TO MINI- MISE RISK. By Chimdike Emmanuel Ihe A report submitted in partial fulfilment of the requirements for the MSc and/or the DIC September 2012 Imperial College London
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Title Page IMPERIAL COLLEGE LONDON
Department of Earth Science and Engineering
Centre for Petroleum Studies
MANAGING OPERATIONAL WELL INTEGRITY – PRIORITISING REPAIRS TO MINI-
MISE RISK.
By
Chimdike Emmanuel Ihe
A report submitted in partial fulfilment of the requirements for
the MSc and/or the DIC
September 2012
Imperial College London
ii Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
DECLARATION OF OWN WORK
I declare that this thesis
‘Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk’
is entirely my own work and that where any material could be construed as the work of others, it is
fully cited and referenced, and/or with appropriate acknowledgement given.
Signature:………………………………………………………….
Name of student: Chimdike Emmanuel Ihe
Name of supervisor: PROFESSOR PETER KING (Imperial College)
MR. IAN TAYLOR (Industry)
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk iii
ACKNOWLEDGEMENTS
This project would not have been completed without the support of my supervisors Prof. Peter
King (Imperial College) and Ian Taylor (Shell) whose confidence in this work, assistance and gentle
steer has resulted in this product. Special thanks to Stathis Kitsios (Shell) for the opportunity. I am
grateful to the staff of Shell U.K. Limited for access to the database used in this work and for the help
received.
I am indebted to Petroleum Technology Development Fund (PTDF) and the government of
Nigeria, without whose sponsorship I may not have had a great program at Imperial College London.
Finally, I appreciate my wife and daughter, Hope and Chimemerie, for their support, patience
and understanding throughout my MSc programme.
London, August 2012.
Chimdike Ihe
iv Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
Table of Contents Title Page ............................................................................................................................................................... i
DECLARATION OF OWN WORK ......................................................................................................................... ii
ACKNOWLEDGEMENTS ..................................................................................................................................... iii
Table of Contents ................................................................................................................................................. iv
LIST OF FIGURES ............................................................................................................................................... vi
LIST OF TABLES ................................................................................................................................................ vii
ABBREVIATIONS ............................................................................................................................................... viii
Problem Statement/Justification......................................................................................................................................... 2
Literature Review .................................................................................................................................................. 2
Explanation of Terms. ........................................................................................................................................................ 3
Well Barrier. .................................................................................................................................................. 3
Failures, Faults and Errors ............................................................................................................................ 4
Wellhead Integrity Test (WIT). ..................................................................................................................... 4
Well Failure Model (WFM). .......................................................................................................................... 5
Data Extraction. ................................................................................................................................................................. 5
Data Filtration. .............................................................................................................................................. 6
Well Failure Frequency. ................................................................................................................................ 6
Deviation and Failure Causes........................................................................................................................ 6
Data Set-up. ....................................................................................................................................................................... 6
Results and Discussion ........................................................................................................................................ 7
Failure History Analysis. ................................................................................................................................................... 7
Severity Frequency (SF). .................................................................................................................................................. 11
Use of Severity Frequency (SF) in Sparing Level Determination .................................................................................... 12
Qualitative Risk Assessment of Deviated Wells. ............................................................................................................. 15
Recommendation for Further Studies ................................................................................................................. 16
Figure C - 1: WIMS Interface ............................................................................................................................................ 38 Figure C - 2: The grace period is based on the Well Failure Model ........................................................................... 39 Figure C - 3: Action Codes................................................................................................................................................ 39
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk vii
LIST OF TABLES
Table 1: Well Type Classification in NNS ............................................................................................................................. 7 Table 2: Failure Analysis Result (NNS) ................................................................................................................................. 8 Table 3: Well Classification on SNS ...................................................................................................................................... 9 Table 4: Failure Analysis Result (SNS) .................................................................................................................................. 9 Table 5: IR and SF values of different well types (NNS) ....................................................................................................... 12 Table 6: IR and SF values of different well types (SNS) ........................................................................................................ 12 Table 7: SF result for Claron field ........................................................................................................................................ 13 Table 8: MTBF values per well type..................................................................................................................................... 13 Table 9: Failure rate determination ....................................................................................................................................... 13 Table 10: Valve Availability ................................................................................................................................................. 13 Table 11: Expected failures in period ................................................................................................................................... 14 Table 12: PWV stocking levels and test frequency ............................................................................................................... 15 Table A- 1: Milestone in Well Integrity Management. ................................................................................................... 18 Table B-1: Definition of terms. .......................................................................................................................................... 37
This equation returns ‘Good’ if the statement is true or ‘Check’ if otherwise. The ‘Expiry Date’ column was determined for
control purpose.
Results and Discussion In this section, the results from the failure and deviation history analyses are presented and discussed. Severity Frequency
(SF) is introduced and applied in reliability techniques to determine stocking levels. This section finally ends with a risk
assessment of wells with deviation.
Failure History Analysis.
Northern North Sea – NNS
Out of the 504 analysed wells, 305 are in NNS, the majority of which are oil wells. They are classified based on their char-
acteristics, operating philosophy and environment. Table 1 shows the well types in NNS.
Table 1: Well Type Classification in NNS
Well Type Number of Wells
Natural Flowing 38
Disposal Well 1
Water Injector 14
Gas Lift 119
Other Artificial Lift 10
Subsea Natural Flowing 52
Subsea Gas Lift 35
Subsea Other Artificial Lift 2
Subsea Water Injector 9
Normally Unmanned 1
Subsea Abandoned 24
Table 2 shows that WIT failures (808 failure cases) account for the majority of recorded failures occupying three-fifths of
total failures, 719 (about 90%) of these have been fixed. About half (~52%) of this did not meet the target time.
Furthermore, about 68% of outstanding failures (~10%) had exceeded the specified target period.
8 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
Table 2: Failure Analysis Result (NNS)
Number of failures cases (from Jan. 1, 2006 – June 1, 2012) 1349
Number of component failures from WITs 808, about 60% of total failures
Number of repaired failures (as at June 1, 2012) 719
Failures fixed outside target time 373
Outstanding repairs exceeding target time (as at June 1,
2012)
57
Master Valve related failures 256
SCSSSV related failures 134
Wing Valve failures 136
WIT failure deviation with documented reasons 101 (This is for 2009 – 2012. Pre-2009 data
for deviation was not recorded).
In addition, master valve failures accounting for an average of 30 failures year-on-year (Figure 6) make up a third of
wellhead integrity failures. The next major contributors are subsurface safety valves (SSSVs) (i.e. including control line
failures) and wing valve failures taking 16% and 13% respectively. Together these three valve type failures account for
about 60% of wellhead integrity failures. In NNS, master valves are most prone to failures with the Production Upper
Master Valve (PUMV) particularly being more affected of the two. The 2012 data (Figure 6) are for only half the year,
hence the apparent dip in the plot.
Figure 6: Valve Failure Contribution (NNS)
Figure 7 shows the repair performance on target times. It can be observed that every year about 50% of failures are not
fixed by the target time. To project the total number of failures at year end, a factor of 1.8 was applied on the number of
failures at mid-year June 1, 2012. This factor was obtained by averaging the trend of previous years for the same period.
Figure 7: Repair Performance (NNS)
0
20
40
60
80
100
120
2006 2007 2008 2009 2010 2011 2012
Tota
l Fai
lure
Year
Valve Failure Contribution (Total)
Swab Valves
SSSVs
Wing Valves
Master Valves
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 9
Southern North Sea – SNS
The SNS has 199 gas wells which are managed under a slightly different management approach. Table 3 shows the well
types in SNS.
Table 3: Well Classification on SNS
Well Type Number of Wells
Natural Flowing 47
Normally Unmanned 151
Subsea Abandoned 1
The data from table 4 again shows that WIT failures (196 failure cases) account for a majority of the failures, occupying
over three-quarters in this instance. This underscores the importance of the focus on well integrity failures. Out of this, 93%
(182) have already been repaired. However, about 45% (82) of these fixed cases did not meet the target repair time and
93% (13) of outstanding failures have exceeded the target repair period.
Table 4: Failure Analysis Result (SNS)
Number of failures cases (from Jan. 1, 2006 – June 1, 2012) 255
Number of component failures from WITs 196, about 77% of total failures
Number of fixed failures (as at June 1, 2012) 182
Failures fixed outside grace period 82
Outstanding repairs exceeding grace period (as at June 1, 2012) 13
Master Valve related failures 55
SCSSSV related failures 50
Wing Valve failures 60
WIT failure deviation with known reasons 25 (This is for 2009 – 2012. Pre-2009
data for deviation was not recorded).
One in three of all wellhead integrity failures is a wing valve failure, having the major contribution year on year (until
recently) of the total failure (figure 8). The next major contributors are master valve failures occupying about a third also
(~28%) and the subsurface safety valve (SSSV) account for a quarter.
Figure 8: Valve Failure Contribution (SNS)
Figure 9 shows that at least 50% of failures are not fixed within the target time from year to year in SNS. A factor of 1.7 was
applied on the number of failures as at mid-year June 1, 2012 to project the number of failures at year end by same means
described for NNS. The available failure data for 2006 exists very late in the year, hence the abnormally low figure in 2006.
10 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
Figure 9: Repair Performance (SNS)
In conclusion, this shows that an operator may have processes in place for the timely repair of well failures. This is the
expectation. However, repairs are not usually accomplished in target time (for various reasons). If these failures are not
repaired within the target time a Deviation is then required and the reason for the Deviation is recorded.
Observations
The next phase examined the reasons for not managing to repair failure in time to see what improvements could be made.
Causes of Deviation.
It was shown earlier that over 50% of failures do not get fixed by the target time as required by the maintenance plan. Three
major reasons have been identified as the cause of deviation from the data. Figure 10 shows the relative contribution of the
deviation causes:
Figure 10: Causes of Deviation
Planning: Delays in schedules, planning of activities or writing job program is a major cause for deviations.
Personnel: These are deviations caused by the unavailability of service personnel. This could be as a result of being
engaged in other activities deemed more critical or having higher risk.
Spares: This refers to deviations as a result of insufficient spares for repairs.
Furthermore, it is observed that critical activities are contributors to the inability to fix failures within the target time.
Examples of such activities include platform shutdown, fire pump repairs, etc. During such times, access is not permitted to the
well to make the repair. Deliberate effort is required to prioritise risk reducing opportunities without deferring on critical
0
10
20
30
40
50
60
2006 2007 2008 2009 2010 2011 2012
Failu
res
Year
Repair Performance
Fixed in time
Not fixed in time
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 11
activities. WBF refers to items that ‘will not be fixed’. ‘Personnel’ and ‘spares’ are separated from the broader ‘planning’
subject to focus on factors that can be directly improved upon. This study has focused on spares because of a need to improve
on sparing strategy.
The reason for the deviation is not recorded in all cases. Historical records for some were ambiguous or could not be located.
To have a better picture for improvement, there is the need for better accurate recording measures by operators.
Causes of Failure.
Some of the observed causes of failure include:
Corrosion
Salt precipitation
Sand
Scale formation
The major cause of well failures can be attributed to sand production from the reservoir. As much as 60% of failures in NNS is
due to sand production. A review of the significant well events data for wells in NNS and SNS with major failures, indicate
that severe and medium sand producers have the highest failure numbers. The wells with the highest numbers of failures from
column 3 (Figure 5) were independently used to verify this. The highest failures in NNS are from gaslift sand-producing wells.
Although, the failure severity of other non-gaslift sand producers is high, they are less significant when compared to gas-lift
wells. Furthermore, master valve failures appeared for all these wells, usually with multiple occurrences.
Sand is also a principal cause of failure in SNS even though salt precipitation presents an equally major problem. The pattern
observed suggests that subsurface safety valves are more affected by salt while sand affects the production wing valve.
In conclusion, an understanding of failures and what drives them is important. If the causes of failures and the affected
components are understood, priorities can be adjusted to cater for these ‘failure prone’ items. For example, by changing the test
frequency and procedure or requiring that salt prone wells are flushed more regularly in a given interval. An operator would
need to be more diligent in testing and maintenance in these areas.
Severity Frequency (SF).
In the course of this study, we have developed the following parameters – Intensity Ratio, IR and Severity Frequency SF because of a need to compare failure trends per well group. These parameters create a ‘common platform’ for comparing well
failures in an area. Area here not only refers to a given geographical region but to wells grouped by a defined characteristic.
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 15
Table 12: PWV stocking levels and test frequency
The underlying assumption here is that a failure is equivalent to a valve change-out. More data (e.g. stock history) would
be required to take this work to the next level to determine actual stocking values for valve sub-components like seals, etc.
Please note that the process terminating in equation 5 was built around a batch production process. Application of a relia-
bility procedure would start on single wells and then aggregated to the well type group. No two wells are entirely the same.
They differ in characteristics and failure modes. Refer to appendix D for more on availability and reliability basics.
Qualitative Risk Assessment of Deviated Wells.
Risk is defined as the combination of the probability of occurrence of harm and the severity of that harm (NORSOK Z-
013, 2001). It is hence made up of two components – the probability (of an event) and the consequence (usually
represented by a factor) of that event. The event considered in well integrity is a leak to the environment.
A barrier vector diagram was developed for a typical oil producing well from which a cut set (leak path) is produced. A cut
set (Figure 13) shows the possible path(s) for the occurrence of a leak to the surrounding. The barrier components occur
between each rounded numbered rectangle. Corneliussen (2006) provides a detailed explanation on the process adopted by
this study. This study has only considered leak paths concerned with wellhead and xmas tree valves (Ref. Appendix E).
Figure 13: Cut set diagram
The first possible leak path (K1) through the lower master valve shows fluid flow from reservoir (R) to the tubing cavity
above the subsurface safety valve (1) and then to the surrounding (S). This is represented by the vectors R-1 and 1-S.
The analysis led to the conclusion that a single component failure may not significantly increase the risk of exposure to an
intolerable level because of multiple redundancies in the system to prevent the escape of fluids. If the failure(s) is
intolerable, then all actions are directed to restoring the well to a safe state as soon as practicably possible.
Conclusions The following conclusions can be made from this work:
1. The majority of well integrity component failures occur between the SCSSV, PUMV and PWV and priority should
be given to these because of their safety critical function as barrier elements.
2. Failure analysis based on well type helps in establishing priorities in testing frequency, well maintenance and stock-
ing strategies. Furthermore, assets with different characteristics might require different prioritization strategies.
3. The Severity Frequency (SF) and Intensity Ratio (IR) parameters can be very useful tools for planning, well integrity
management and performance assessment.
4. If systematic failures can be established, integrity management strategies can be attuned in order of priority.
5. Reliability approach can be used to determine appropriate test frequencies while maintaining the integrity of the well
(field, asset, region, etc).
6. Well management processes can be improved upon so as to bring about a reduction in deviations.
Min. Actual Max Min. Actual Max Min. Actual Max
1 1 2 1 1 2 2 3 7
Water Injector Subsea Gaslift Gas Lift
Annual Test Annual Test 6-Monthly Test
PWV Stocking Levels and Test Frequency
R
E
S
E
R
V
O
I
R
R
Tubing
above
SCSSSV 1
Cavity
between UMV
and LMV
2
Tubing
hanger
cavity 5
Cavity
between SV
and UMV 3
Cavity between
SV and adapter
assembly
4
S
U
R
R
O
U
N
D
I
N
G
S
K1 = {R-1, 1-S}
K2 = {R-1, 1-2, 2-S}
K3 = {R-1, 1-5, 5-S}
K4 = {R-1, 1-2, 2-3, 3-S}
K5 = {R-1, 1-2, 2-3, 3-4, 4-S}
16 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
7. A well with a deviation does not necessarily have a significant increase in its risk. Risk increases in multiple failures.
8. The quality of analysis and resulting decisions depends on the quality of failure and repair data, good data capture,
storage and retrieval is therefore very important.
Recommendation for Further Studies The underlying assumption in this study is that a failure is equivalent to a complete valve change-out. It is therefore rec-
ommended that actual stocking values for valve sub-components like seals, etc be determined from more data like order
history.
Nomenclature
λ = Failure Rate (failure/month).
t = test time (months)
SF = Severity Frequency (Failures per well type/year)
References
Alaska Oil & Gas Conservation Commission (AOGCC). Investigation of Explosion and Fire at Prudhoe Bay Well A-22 North Slope,
Alaska August 16, 2002. Alaska Oil & Gas Conservation Commission (AOGCC) Staff Report. 2003. Alaska, Canada.
American Petroleum Institute RP 14B. Design, Installation, Repair and Operation of Subsurface Safety Valve Systems, fourth edition.
1994. Washington, DC: API.
American Petroleum Institute RP 14H. Recommended Practice for Installation, Maintenance, and Repair of Surface Safety valves and
Underwater Safety Valves Offshore, fourth edition. 1994. Washington DC: API.
Brattbakk, M., Østvold, L., Van der Zwaag, C., and Hiim, H. Investigation of Gas Blowout on Snorre A, Well 34/7-P31A, 28 November
2004 (Gransking av gassutblåsning på Snorre A, brønn 34/7-P31 A 28.11.2004). 2005. Norway: PSA.
Chitale, A. A., Blosser, W. R., and Arias, B. J.: “Use of Real-Time Data in Well Integrity Management,” SPE 128688 paper prepared
for presentation at the SPE Intelligent Energy Conference and Exhibition held in Utrecht, The Netherlands, 23-25 March 2010.
Corneliussen, K.: Well Safety – Risk Control in the Operational Phase of Offshore Wells. PhD dissertation, 2006. Department of
Production and Quality Engineering, The Norwegian University of Science and Technology, Trondheim.
Corneliussen, K., Sørli, F., Brandanger Haga, H., Tenoid, E., Menezes, C., Grimbert, B., and Owren, K.: “Well Integrity Management
System (WIMS)–A Systematic Way of Describing the Actual and Historic Integrity Status of Operational Wells,” SPE 110347,
paper presented at the 2007 SPE Annual Technical Conference and Exhibition of the Society of Petroleum Engineers, Anaheim,
California, U.S.A., 11-14 November 2007.
[DCR guidance], A guide to the well aspects of the Offshore Installations and Wells (Design and Construction, etc) Regulations 1996.
L84, second edition 2008. ISBN 978 0 7176 6296 8. United Kingdom: HSE .(http://www.hse.gov.uk/pubns/priced/l84.pdf)
Haga, J., Corneliussen, K., and Sørli, F.: “Well Integrity Management: A Systematic Way of Describing and Keeping Track of the
Integrity Status for Wells in Operation,” SPE 120946 paper prepared for presentation at the 2009 SPE Americas E&P
Environmental & Safety Conference held in San Antonio, Texas, U.S.A., 23-25 March 2009.
Hon. Lord Cullen: “The Public Inquiry into the Piper Alpha Disaster”, Vol. 1 & 2, 1990.
International Electrotechnical Commission 61508, Functional Safety of Electrical/Electronic/Programmable Electronic Safety-Related
Systems, part 1 – 7. 1997. Geneva, Switzerland: International Electrotechnical Commission.
Kairon, S., Lane, T., and Murrey, M. D.: “Optimizing Well Integrity Surveillance and Maintenance,” IPTC 12624 paper prepared for
presentation at the International Petroleum technology Conference held in Kuala Lumpur, Malaysia, 3-5 December 2008.
Nichol. J. R., Kariyawasam, S. N. Risk Assessment of Temporarily Abandoned or Shut-in Wells. Final Report, Contract No. 1435-01-
99-RP-3995, Project 99041, US DOI, Minerals Management Service (MMS), Washington, DC (October 2000).
NORSOK D-010. Well Integrity in Drilling and Well Operations, Rev. 3, 2004. Lysaker, Norway: NORSOK.
NORSOK Z-013. Risk and emergency preparedness analysis, Rev. 2, 2001. Oslo, Norway: NORSOK (see http://www.standard.no/).
The Norwegian Oil Industry Association OLF 070, Guideline on the application of IEC 61508 and IEC 61511 in the petroleum
activities on the Norwegian Continental Shelf. The Norwegian Oil Industry Association, OLF Report 070 rev. 2. 2004. Stavanger,
Norway: OLF (see http://www.itk.ntnu.no/sil).
The Norwegian Oil Industry Association OLF 117, OLF Recommended Guidelines for Well Integrity. The Norwegian Oil Industry
Pettersen, G., Moldskred, I. O., and Ytredal, E. B.: “The Snorre-A Incident 28 November 2004: Lessons learned,” SPE 98739 paper
prepared for presentation at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and
Production held in AbuDhabi, U.A.E, 2-4 April, 2006.
Rausand, M. and Høyland, A. System Reliability Theory. Models, Statistical Methods, and Applications, second edition, 2004. Hoboken,
New Jersey: Wiley series in probability and statistics, John Wiley & Sons, Inc. Smith, L., and Milanovic, D.: “The Total Control of Well Integrity Management,” SPE 117121 paper presented at the 2008 Abu Dhabi
International Petroleum Exhibition and Conference held in Abu Dhabi, UAE, 3-6 November 2008.
Sultan, A. A.: “Well Integrity management Systems; Achievements versus Expectations,” IPTC 13405 paper prepared for presentation
at the International Petroleum Technology Conference held in Doha, Qatar, 7-9 December 2009.
Vignes, B., Andreassen, J., and Tonning, S. A.: PSA Well Integrity Survey, Phase 1 Summary Report, 21 September 2006.
Wallace, G., Kiddie, N., Kearns, J., Robinson, P.: “A Compliance-based Approach to Well Integrity Management,” SPE 115585, paper
presented at the SPE Annual Technical Conference and Exhibition held in Denver, Colorado, U.S.A., 21-24 September 2008.
Well integrity guidelines. Issue 1. 2012. Oil & Gas UK, London, United Kingdom: ISBN 1 903 003 82 9.
Tarrants, W.E. 1980. The measurement of Safety Performance. Garland STPM Press, New York. ISO 8402. 1986. Quality Vocabulary. International Standards Organization. Geneva, Switzerland:ISO.
38 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
APPENDIX C - WIMS Database
A well serves both as a conduit and containment for hydrocarbons. The effective management of a
well is described within the Shell’s global Well Integrity Management Manual (WIMM), which is a
part of the global well standards and technical integrity framework. The well failure model concept is
based on the well standard of maintaining two barriers. The WIMM and the WIMS tool both support
the technical integrity elements within an overall structure of asset and safety management.
WIMS is an IM/IT application that provides a completely transparent view (Figure C – 1) of the in-
tegrity related data for every single well that Shell operates. So it is the means by which compliance
with the WIMM (Well Integrity Management Manual) is applied.
Figure C - 1: WIMS Interface
Integrity issues are highlighted on a zero to ten degree and made more visible using standard traffic
light colours that are mapped from the well failure model. Most important of all, the action codes,
sourced from the well failure model have been signed off and committed to by the owning operating
unit. For instance, if the action code states level 9, ‘make safe immediately’, that is the commitment.
Well Failure Model
The well failure model is at the heart of the WIMS tool. It is a set of rules which define the actions to
be taken resulting from a well integrity test state. The model maps well types, failure modes and ac-
tion codes, and identifies the urgency to fix a failure based on a Risk Assessment Matrix (RAM). In
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 39
simple terms, it specifies a grace period used to prioritise repairs (Figure C – 2) and does so by pull-
ing together the business rules to ensure that the results of a well test are interpreted effectively. A
simple example illustrates this.
A production operator conducts a standard set of integrity tests on a well. WIMS captures the meas-
ured results from this test. Checked against the logic of the well failure model – which is specifically
tailored for the well type in question – the tool will indicate the appropriate action code (Figure C – 3)
needed to ensure the integrity of the well. If the failure model indicates that maintenance work is re-
quired within, say, two months (AC – 6), an amber traffic light will show while the corrective work
remains outstanding. If the repair is not completed within the required time then the well becomes
non-compliant and the traffic light turns red. Should a deviation from the required schedule be re-
quired, a deviation may be approved consistent with approved procedures, following review and risk
assessment and the ‘deviated’ status is updated in WIMS. Communicating with other systems and live
data, the result is a managed process, driven by business logic and controls.
Figure C - 2: The grace period is based on the Well Failure Model
Figure C - 3: Action Codes
Resulting
Well Traffic
Light
Action
Code
G 0
1
2
3
4
5
6
7
8
9
10
R
Repair at the earliest opportunity but within 2 months - the well can be flowed during this grace period. See note 'J'.
Implement installation/field Emergency Response procedures immediately, make well safe at earliest opportunity and plan repair / suspension / abandonment. Deviations
will not be approved for Action Code 10 failures.
Make well safe immediately and plan repair / test / suspension / abandonment. Make well safe may be carried out by repairing defect at initial visit to well. See note 'K'.
O Repair at the earliest opportunity but within 3 months - the well can be flowed during this grace period. See note 'J'.
Required Action
Repair at next planned maintenance / intervention
Carry out formal Technical Review within 7 days to determine mitigating actions and when/how to repair and/or continue operation. The minimum action resulting from a
Technical Review outlined in AC8 is to make the well safe as per action code 1 - 10 : ie a repair is required. See Failure Code Guidance Notes for required attendees.
Repair at the earliest opportunity but within 1 months - the well can be flowed during this grace period. See note 'J'.
Repair at the earliest opportunity but within 6 months - the well can be flowed during this grace period. See note 'J'.
Repair at the earliest opportunity but within 24 months - the well can be flowed during this grace period. See note 'J'.
Repair at the earliest opportunity but within 12 months - the well can be flowed during this grace period. See note 'J'.
No faults found, well tested within operating parameters
40 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
APPENDIX D – Failure Rate, MTTF and Reliability.
Time to failure
This refers to the elapsed time between when an item is put into operation and when it fails the first
time. It is assumed that the time to failure T is continuously distributed and the distribution function
is:
𝐅(𝐭) = 𝐏𝐫(𝐓 ≤ 𝐭) = ∫ 𝐟(𝐮)𝐝𝐮𝐭
𝟎 𝐟𝐨𝐫 𝐭 > 𝟎 Eqn. D- 1
F(t) denotes the probability that the item fails within the interval (0,t]. The probability density func-
tion f(t) is defined as
𝐟(𝐭) =𝐝
𝐝𝐭 𝐅(𝐭) = 𝐥𝐢𝐦∆𝐭→𝟎
𝐅(𝐭+∆𝐭)−𝐅(𝐭)
∆𝐭= 𝐥𝐢𝐦∆𝐭→𝟎
𝐏𝐫(𝐭<𝑻≤𝒕+∆𝒕)
∆𝐭 Eqn. D- 2
Reliability function
This is defined as the probability that an item performs a required function under given conditions for
a given period of time. The Reliability function is defined by,
𝐑(𝐭) = 𝟏 − 𝐅(𝐭) = 𝐏𝐫(𝐓 > 𝒕) 𝐟𝐨𝐫 𝐭 > 𝟎 Eqn. D- 3
Or
𝐑(𝐭) = 𝟏 − ∫ 𝐟(𝐮)𝐝𝐮𝐭
𝟎= ∫ 𝐟(𝐮)𝐝𝐮
∞
𝐭 Eqn. D- 4
R(t) is therefore the probability that the item is still functional at time t.
Failure rate function
The probability that an item fails within the time interval (t, t+Δt] when it is known that the item is
functioning at time t is
𝐏𝐫(𝐭 < 𝑻 ≤ 𝒕 + ∆𝒕 | 𝐓 > 𝒕) = 𝐏𝐫(𝐭<𝑻≤𝒕+∆𝒕)
𝐏𝐫(𝐓>𝒕)=
𝐅(𝐭+∆𝐭)−𝐅(𝐭)
𝐑(𝐭) Eqn. D- 5
Dividing this probability by the length of time Δt and as Δt→0, the failure rate function becomes
𝐳(𝐭) = 𝐥𝐢𝐦∆𝐭→𝟎𝐅(𝐭+∆𝐭)−𝐅(𝐭)
∆𝐭
𝟏
𝐑(𝐭)=
𝐟(𝐭)
𝐑(𝐭) Eqn. D- 6
From eqns. D-2 and D-3;
𝐟(𝐭) =𝐝
𝐝𝐭𝐅(𝐭) =
𝐝
𝐝𝐭[𝟏 − 𝐑(𝐭)] = −𝐑′(𝐭) Eqn. D- 7
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 41
Therefore,
𝐳(𝐭) = −𝐑′(𝐭)
𝐑(𝐭)= −
𝐝
𝐝𝐭𝐥𝐧 𝐑(𝐭) Eqn. D- 8
And,
𝐑(𝐭) = 𝐞𝐱𝐩 (− ∫ 𝐳(𝐮)𝐝𝐮𝐭
𝟎) Eqn. D- 9
From eqn. D-6 𝐟(𝐭) = 𝐳(𝐭). 𝐑(𝐭) Eqn. D- 10
Therefore,
𝐟(𝐭) = 𝐳(𝐭). 𝐞𝐱𝐩 (− ∫ 𝐳(𝐮)𝐝𝐮𝐭
𝟎) , 𝐭 > 𝟎 Eqn. D- 11
Mean Time to Failure
The mean time to failure (MTTF) of an item is defined by,
𝐌𝐓𝐓𝐅 = 𝐄(𝐓) = ∫ 𝐭. 𝐟(𝐭)𝐝𝐭∞
𝟎 Eqn. D- 12
When the time required to repair a failed item is very short compared to the MTTF, then MTTF also
represents mean time between failures (MTBF).
Substituting eqn. D-7 in D-12,
𝐌𝐓𝐓𝐅 = − ∫ 𝐭 𝐑′(𝐭)∞
𝟎 𝐝𝐭 Eqn. D- 13
By partial integration,
𝐌𝐓𝐓𝐅 = −[𝐭𝐑(𝐭)]𝟎∞ + ∫ 𝐑(𝐭)
∞
𝟎𝐝𝐭 Eqn. D- 14
It can be shown that [𝑡𝑅(𝑡)]0∞ = 0. Therefore,
𝐌𝐓𝐓𝐅 = ∫ 𝐑(𝐭)∞
𝟎𝐝𝐭 Eqn. D- 15
Using Exponential Distribution
Time to failure T of an item put into operation at time, t=0 has the probability density function
𝐟(𝐭) = {𝛌𝐞−𝛌𝐭 𝐟𝐨𝐫 𝐭 > 𝟎, 𝝀 > 𝟎𝟎 𝐨𝐭𝐡𝐞𝐫𝐰𝐢𝐬𝐞
Eqn. D- 16
42 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
The Reliability function of the item is
𝐑(𝐭) = 𝐏𝐫(𝐓 > 𝒕) = ∫ 𝐟(𝐮)∞
𝐭𝐝𝐮 = 𝐞−𝛌𝐭 𝐟𝐨𝐫 𝐭 > 𝟎 Eqn. D- 17
The mean time to failure is
𝐌𝐓𝐓𝐅 = ∫ 𝐑(𝐭)∞
𝟎𝐝𝐭 = ∫ 𝐞−𝛌𝐭∞
𝟎𝐝𝐭 =
𝟏
𝛌 Eqn. D- 18
The failure rate function is
𝐳(𝐭) =𝐟(𝐭)
𝐑(𝐭)=
𝛌𝐞−𝛌𝐭
𝐞−𝛌𝐭= 𝛌 Eqn. D- 19
Availability, 𝑨(𝒕)
Availability, 𝐴(𝑡) at time t is the probability that an item is functioning in time t.
𝑨(𝒕) = 𝑷𝒓(𝑿(𝒕) = 𝟏) Eqn. D- 20
If an item is not repaired, then the availability is equal to the survivor function 𝑅(𝑡) expression.
𝑨(𝒕) = 𝑹(𝒕) = 𝒆−𝝀𝒕 Eqn. D- 21
The unavailability of an item is the probability that the item is not functioning in time t.
�̅�(𝒕) = 𝟏 − 𝑨(𝒕) = 𝑷𝒓(𝑿(𝒕) = 𝟎) Eqn. D- 22
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 43
APPENDIX E – Qualitative Risk Assessment.
Risk is defined as the probability of an unwanted event and the consequence of that event. Well risk
therefore combines the probability of occurrence of a hazardous event and its consequence. A hazard-
ous event is one that has the potential of causing harm. The hazardous event most commonly consid-
ered for the well is the blowout and the possible consequences are damage to life, environment and
asset. Risk can be assessed quantitatively or qualitatively.
A qualitative risk assessment of deviated wells was carried out by coming up with cut-set table of well
barrier vectors for a typical oil producing well. The project adopted the process outlined in the PhD
work of Corneliussen (2006).
Figure E- 1: Well Cross-section (Corneliussen, 2006)
44 Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk
Figure E-2 shows the barrier vector diagram of a typical well. Corneliussen (2006) dealt with the
procedure of arriving at this diagram in his PhD thesis. The rectangles represent the barrier component
while the rounded rectangles with circled numbers are the cavities between each barrier component.
As a point for correction, the rounded circle with number 1 is part of the tubing above the SCSSV.
Figure E- 2: Barrier Vectors (Corneliussen, 2006)
Table E-1 shows the possible cut sets of the barrier vectors in the well from figure E-2. A cut set is a
set of basic events whose occurrence (at the same time) ensures that a top event (leak) occurs
(Rausand, M and Høyland, A., 2004). Simply put, a cut set shows the possible leak path(s) from
reservoir to the surrounding through one or several barriers (gates). The cut sets of interest in this
study have been shaded since the focus of this project is on well head and xmas tree valves.
Managing Operational Well Integrity – Prioritising Repairs to Minimise Risk 45