kuwait environmental remediation program (kerp): south ... · kuwait environmental remediation...
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Kuwait Environmental Remediation Program (KERP): South East Kuwait oil field FEED works and Remediation Program
Presented by : Mr. Muthanna Al-Mumin Ms. Aisha-Al-Barood *
* Kuwait Oil Company – Soil Remediation Group
26th IPEC: INTERNATIONAL PETROLEUM ENVIRONMENTAL CONFERENCESan Antonio, Texas, USA. Oct 7-9, 2019
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1. FEED Objectives
2. KERP Overview- Background
3. KERP Stakeholders Organization
4. KERP-KOC Claim of elements awarded
5. Contaminated Features
6. KERP Strategy - Total Remediation Solution
7. KERP Projects
8. Data Analysis and Results
9. Conclusion
Index
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FEED Objectives
FEED (Front End Engineering Design).
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Bringing the picture into focus.
Treatable contaminated soil vs. Landfill volumes within the time
frame.
Remediation contractors technical and financial assessment of
most suitable technology to treat contamination.
Provide sufficient data for tender pricing.
Minimizing risk pricing by contractors. Assignment of treatment / landfill areas and reservation.
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KERP - Background
KOC
Kuwait Government
UNCC
KERP Stakeholders Organization
3 Claims
KERP Stakeholders Organization
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KNFP
MEW
KMOD
PAAF
KEPA
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KERP - KOC Claim Elements Awarded
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Claim No. 5000259
(Coastal & Marine Resources)
Claim No.5000450
(Remediation of areas in and around wellhead
pits and Tarcrete)
Claim No. 5000454
(Remediation of areas damaged by oil lakes,
oil-contaminated piles, oil trenches & oil spills)
The following Environmental Claim elements were awarded to KOC by UnitedNations Compensation Commission under Decision 258.
Dry Oil Lakes
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Contaminated Features
Wet Oil Lake
Dry Oil Lakes
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Contaminated Features
Dry Oil Lake
Dry Oil Lakes
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Contaminated Features
Oil Contaminated Piles
Heavily contaminated surface layer -1
Visibly contaminated layer -2
Visibly uncontaminated soil
Dry Oil Contaminated Soil
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Wet Oil Contaminated Soil
Heavily contaminated layer below the sludge
Visibly uncontaminated soil
Oily liquid sludge-Layer 1
Visibly contaminated layer -2
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RBATPH 0.5%-2%
Ex-situ BioTPH 2%To 7%
TreatmentMethods
TPH 5%-10%
Non treatment
>10% (stabilize, oil
recovery, reuse, landfill
SludgeOil Recovery,
temp storage for re-use or
stabilize/landfill
KERP Strategy - Total Remediation Solution
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Projects Name Phase
Engineered Landfill (South East Kuwait) Completed
Engineered Landfill (North Kuwait) Completed
Excavation &Transportation (North Kuwait) Completed
Excavation &Transportation (South East Kuwait) Completed
UXO Phase-1 On going
Mega Remediation NK (4 Mm3)Under Committee
Approval
Mega Remediation SEK-I (9 Mm3) Under Preparation
KERP Projects
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FEED Characterization
KOC conducted a limited
soil characterization study
in south East Kuwait areas
in 2014 and 2017.
FEED Characterization
KOC/Worley conducted a
more detailed soil
characterization study in
south East Kuwait areas in
2019.
2000 locations across a contaminated area of approx. 70 km2 .
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FEED Characterization
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FEED Characterization
KERP Optimization Plan
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FEED Characterization
Data Maps via EQUIS software
KERP Optimization Plan
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Feature TypeLand
Coverage (km2)
Material Type#
SamplesMean TPH
Concentration
Potential Remediation
ApproachComment
DOL 64.17
Layer 1 –hardened crust
103 6.40%Treatment
Technologies or landfill
Layer 2 - Oil contaminated
soil322 2.20%
Enhanced bioremediation
Depth profiling suggests potentially
shallower contamination
WOL 5.59
Layer 1 - Oily Sludge
20 18%Recovery/re-use or
landfill
Sludge thickness varies but may be
shallower
Layer 2 - Oil contaminated
soil45 2.90%
Enhanced bioremediation
Depth profiling suggests potentially
shallower contamination
OCP 5.19
Oil contaminated soil and free product (oil)
123 7.20%Treatment
Technologies (i.e. Soil washing)
Correlation between outward colour and
contamination profile.
The FEED characterization work has provided essential data to support the developmentof remediation packages in line with the UN approved TRS.
FEED CharacterizationFEED Characterisation Works (2019)
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Data Informing Strategy
26 million m3 designated for landfill.
Original Data All 26 M m3 heavily contaminated soils designated for landfill
Updated data Sustainable remediation achievable on much higher percentage
[Assessed using a basic hydrocarbon screen]
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Data Assessment – Bringing Into Focus
9.0%
7.2% 7.3%
6.4%
2.5%2.2% 2.1%
2.2%
1%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
CIC (2003) LSSC (2015) SEK E&T (6B) 2017 SSC (2019)
TPH
(H
EM)
%
Layer 1 Layer 2 Layer 3 RTC
Example of findings from various characterization campaigns• Surficial DOL Layer 1 (oil dominated material) general trend in concentration reduction, likely
from weathering.• Underlying DOL Layer 2 remains reasonably consistent across various sampling campaigns
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• Most recent TPH SARA analysis showing higher proportion of resins and asphaltenes
13%16%
4%
5%
51%
55%
33%
24%
0%
20%
40%
60%
80%
100%
Layer 1 Layer 2
SAR
A (
%)
Saturates Aromatics Resins Asphaltenes
Incr
easi
ngl
y ch
alle
ngi
ng
for
bio
rem
ed
iati
on
w
ith
po
ten
tial
‘re
-bo
un
d’
Data Assessment – Bringing Into Focus
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Physical Parameters• The physical composition can impact
choice of remediation technique
• FEED characterization undertook wetsieve assessment to try and simulatefurther this phenomenon, showing anincrease in fines over earlier dry sievedata
• Lessons learned from other KOCremediation projects identified higherfines content (silt/clay) than expected
• Identified that sand can be weaklycemented silts that break apart underattrition (such as during soil washing).
0 10 20 30 40 50 60 70 80 90
Fines
Sand
Gravel
Averaged Particle Size Analysis Comparison
FEED Data (2019) CIC Data (2003)
Data Assessment – Bringing Into Focus
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Coming into focus…
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Risk Mitigation
• In summary, greater data wealth mitigates risk and consequently, reduces overalluncertainty and associated cost.
• KOC have invested in de-risking complex remediation programs.
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KERP – Remediation SEK Project
TPH Range %Indicative Total
Volume Mm3
Approximate Percentage SK (%)
Min. Treatment Requirement as
Percentage of Total Volumes (%)
1.0 - 5.0 4.7 52% 90%
5.0 - 7.0 0.6 6% 80%
7.0 - 10 0.4 4% 70%
10 - 15 0.3 4% N/A
15 3 34% N/A
TOTAL 9
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Expected distances to be travelled to transport contamination 4-8 million km to
complete works (100 to 200 times around the earth)
Dependent on Contractor Strategy (in-situ vs ex-situ)
High pressure abrasive soil wash will result in an increase in waste production due to
increasing fines
Bioremediation TPH rebound to be considered in treatment period
No HTTD allowed as per client directive
Contractor Considerations
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Minimising Potential Claim against Company in the Future
Avoid scenarios of remediation failures
Competitive rates due to de-risking
Achieve Kuwait Environmental Public Authority clean-up criteria.
Less reliance on Landfill
TRS provide more ecologically sustainable treatment solutions
FEED / TRS Benefits
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Thank you
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Limited Scope Investigation - Burgan - South East Kuwait (2014):
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Table 1 : Minimum, Maximum & Mean for TPH level in Layers-1&2 of Wet and Dry Oil Lakes
Material Type /
Analysis
Minimum
(mg/kg)
Maximum
(mg/kg)
Geometric
Mean (mg/kg)
Arithmetic
Mean (mg/kg)
Standard
Deviation
(mg/kg)
Wet Oil Lake
Layer 1 94,835 166,171 133,373 135,557 25,310
Layer 2 11,585 87,450 32,847 39,749 24,840
Dry Oil Lake
Layer 1 718 126,811 17,576 27,847 10,271
Layer 2 9,923 35,126 23,660 28,507 4,847
Data Analysis and Results
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Petroleum Hydrocarbons Investigations in S&EK fields:
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Table 2 : Minimum, Maximum & Mean for TPH level in Layers-1&2 of Wet and Dry Oil Lakes
Material Type /
Analysis
Minimum
(mg/kg)
Maximum
(mg/kg)
Geometric
Mean (mg/kg)
Arithmetic
Mean (mg/kg)
Standard
Deviation
(mg/kg)
Wet Oil Lake
Layer 1 305,816 624,513 466,424 480,068 13,644
Layer 2 73,941 169,045 131,966 13,6521 4,555
Dry Oil Lake
Layer 1 1,074 326,421 62,440 89,456 27,016
Layer 2 9,866 203,760 30,310 40,052 9,742
Data Analysis and Results
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Data Assessment – Bringing Into FocusExample of findings from various characterization campaigns• TPH Criteria Working Group (CWG) banding and speciation comparison demonstrating larger
chain length dominance (C35-C90) and absence of “light end” hydrocarbons.
0.000
0.500
1.000
1.500
2.000
2.500
3.000
3.500
C5-C6 C6-C8 C8-C10 C10-C12 C12-C16 C16-C21 C21-C35 C5-C6 C6-C8 C8-C10 C10-C12 C12-C16 C16-C21 C21-C35 C35-C90
VolatileAliphatics
VolatileAliphatics
VolatileAliphatics
ExtractableAliphatics
ExtractableAliphatics
ExtractableAliphatics
ExtractableAliphatics
VolatileAromatics
VolatileAromatics
VolatileAromatics
ExtractableAromatics
ExtractableAromatics
ExtractableAromatics
ExtractableAromatics
Fraction-ated PHC
TPH
%
TPH Banding and Speciation Comparison on DOL Layer 2
LSSC (2015) FEED (2019)
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Data Assessment – Bringing Into Focus
0
10000
20000
30000
40000
50000
60000
70000
TPH SARA Total Saturates Aromatics Resins Asphaltine
Co
nc.
mg
/kg
Weathered Crude Oil Constituents
FJPEC/KISR(1997) vs. PMC 2014 Chemical Constituents Data Dry Oil Lakes (Layer
1 & Layer 2) & Wet Oil Lake (Layer 2)
JPEC/KISR 1997 PMC-2014 DOL Layer-1 PMC 2014 DOL Layer-2 PMC 2014 WOL Layer 2
Utilizing detailed characterization for more predictive remediation approaches• Utilizing TPH composition analysis when considering bioremediation or
combination of bioremediation with other techniques
Increasingly challenging for bioremediation
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Data Analysis and Results
AOI 1
AOI 2
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Attributes
Data Analysis and Results
36
Data Analysis and Results
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