Minimizing and mitigating risks in upstream oil sc (final)

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TABLE OF CONTENTS:
Page No.
Introduction…………………………………………………………………………………………………………………….02
Objectives of the study……………………………………………………………………………………………………04
Supply Chain Network of Drilling Services……………………………………………………………………….04
Research Methodology…………………………………………………………………………………………………..07
Risk Analysis……………………………………………………………………………………………………………………10
Applying AHP for each parameter…………………………………………………………………………………..24
 Average cost per day………………………………………………………………………………………….24
 Loss of Lives factor……………………………………………………………………………………………..29
 Time to Revert to Normal Operations…………………………………………………………………32
 Cost of Mitigating……………………………………………………………………………………………….34
 Decision alternatives factor………………………………………………………………………………..35
Decision Making for risks mitigation using parameters of Judgement…………………………….36
Conclusion……………………………………………………………………………………………………………………..39
References……………………………………………………………………………………………………………………..40

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Introduction:
The upstream oil sector involves the exploration and production of crude oil or natural gas from
oil/gas fields lying in the sedimentary basins across the globe. The activity is spread across
sequential domains such as estimation of reserves, exploration of probable reserves, analysing
feasibility of extraction, field development and production/ supply of hydrocarbon to
customers such as downstream oil players or power plants/ factories. The supply chain involved
in this capital intensive process is very diverse and dynamic, at the same time extremely
complex with multiplicity of risks involved.
The study is undertaken in the light of changing times from the days of easy oil to exploration in
deep water terrains and marginal fields across continents/ oceans. Furthermore, the capital
intensive nature has reinforced the importance of using risk assessment tools in efficient and
effective functioning thereby trying to minimise the costs involved in oil supply chain. The case
analysis focuses on the minimising and mitigating the risks in supply chain of exploration
activities in the high pressure high temperature gas fields of Krishna Godavari Basin, Andhra
Pradesh. It is spread across more than 50,000 square kilometres.
The upstream oil giants predominantly undergoing exploration activities include ONGC,
Reliance Industries ltd., BP and Cairn India etc. This case study would focus on KG Basin project
undertaken by ONGC from their base office at Rajahmundry Asset.
Exploration and Production at KG Basin by Oil and Natural Gas Corporation Ltd.
The exploration activities under Rajahmundry Asset/ KG Project of ONGC are classified into the
different verticals of Engineering services, geological and geophysical services, Drilling services
and Production department supported by functions of Materials management and logistics.
The case analyses the supply chain of 7 onshore oil rigs under Rajahmundry Asset, which
sources its supply of materials from a central warehouse, obtains operating fuel from Tatipaka
refinery and the continuous flow of hydrocarbons through pipelines to group gathering station
(GGS) or Gas compression stations (GCS). The risks are classified into various formats such as
sourcing, production, logistics, ecological and geopolitical risks.
The mobile oil rigs rely on operational materials such as store/ spare items from Central
warehouse located at Narsapur, High speed diesel delivery of approx. 7.5 kilolitres per day to
each of the oil rigs from mini- refinery at Tatipaka and output of crude oil/ natural gas from
flowing oil wells to Group Gathering Stations at Lingala and further movement of natural gas to
Gas Compression Stations.

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The inherent risks involved in the supply chain include:
 Sourcing risks: This encompasses a combination of risk arising from sourcing of
hydrocarbons because the success rate of exploratory oil/ gas drilling wells in India is
under 50%. Moreover, the materials and capital equipment used in daily operations are
made to order/engineer and imported goods which constraints the flexibility of
procurement.
 Production risks: The unforeseen decline in production levels of oil/ gas wells due to
lowering reservoir pressure, seismic activities and oil migration across underground
reservoirs.
 Logistics risk: The transportation of hydrocarbons through pipelines across installations
pose risks of pilferage and leaks due to long routes across unfavourable terrains.
Greater risks exist in the form of trade barriers, embargoes and choke points of crude
exports across the globe.
 Ecological risk: The exploration activities pose risks of damage to the flora and fauna of
adjacent neighbourhoods of exploration, the chemicals rendering the land infertile for
greater radii. Oil spills and hazards of large scale fires in the eventuality of a blowout
feature among the worst man made industrial disasters. KG basin being a high pressure
high temperature gas field had prior blowouts leading to large scale damage to ecology.
 Geopolitical risk: The investments made on exploration activity is immense, whose
capital expenditure recovery takes years to break even by realisation of sales of
hydrocarbons. The highly interventionist policy of natural resource pricing in India

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renders market forces irrelevant. Extraneous factors such as global demand and supply
of crude also play a critical role in the pricing of domestic crude.
These major forms of risks in upstream oil sector risks occur simultaneously but in varying
degrees of intensity. Tackling these risks when they occur simultaneously, using statistical tools
rather than intuition can reduce financial expenditure in the face of an eventuality.
Objectives of the study:
 Understanding the risks facing upstream exploration activities of ONGC in KG basin.
 Deciding the statistical process adopted to mitigate and minimise risks – Analytic
Hierarchy Process
 Prioritization of the risks based on Saaty’s scale.
 Pair-wise analysis of the risks.
 Assigning probability weights to occurrence of each risk.
 How to tackle the activity based on statistical finding.
Supply Chain Network of Drilling Services at the KG Basin:
7 onshore oil rigs under Rajahmundry Asset
1. Mummidivaram Central Warehouse: Narsapuram
2. Narsapur Mini Refinery: Tatipaka
3. Bantumilly Group Gathering Station (GGS): Lingala
4. Mandapeta
5. Malleswaram
6. Kesanapalli
7. Katrenikona

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Material Flow Routes
Operational Fuel Supply Routes
Crude Supply Pipeline Routes
Gas Supply Routes
Mapping of the Rigs from the Mini- Refinery

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Mapping of the rigs from the Central Warehouse
RIG Location Remarks X<->Central
Warehouse
X<->Refinery
E-2000-III Mummidivaram, near
Amalapuram, EG
Exploratory 93.8 km ,
1 hour 56 mins
39.5 km,
51 mins
E-2000-1 Narsapur, EG Exploratory 4 kms,
15 mins
29.6 km,
33 mins
BI-2000-II Katrenikona near
Amalapuram ,EG
Exploratory 102 km,
2 hours 16mins
45.5 km,
1 hour 8 mins
F-6100-III Bantumilly, Krishna Exploratory 158 km,
2 hours 53 mins
84.3 km,
1 hour 33 mins
E-1400-16 Mandapeta, EG Exploratory 55.8 km,
1 hour 6 mins
52.9 km,
1 hour 10 mins

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E-1400-17 Malleswaram, Krishna Development 152 km,
2 hours 59 mins
177 km,
3 hours 7 mins
E-760-M Kesanappalli, EG Development 275 km,
4 hours 32 mins
272 km,
4 hours 13 mins
Table 1: Transport Routes and Distances for ONGC KG Basin
Research Methodology:
Here we use Multiple Criteria Analysis and Analytic Hierarchy Process to analyse and mitigate
the upstream Petroleum Supply Chain Risks.
Management decision making problems often involve multiple criteria/objectives/attributes.
Multiple-Criteria Analysis (MCA) is a collection of methodologies to compare, select, or rank
multiple alternatives that involve incommensurate attributes. It organizes the basic rationality
by breaking down a problem into its smaller constituent part and then guides the decision
maker through a series of pair-wise comparison judgment to express relative strength or
intensity of impact of the elements of the hierarchy.
The Analytic Hierarchy Process (AHP) provides a framework to cope with multiple criteria
situations involving intuitive, rational, quantitative and qualitative aspects. Hierarchical
representation of a system can be used to describe how changes in priority at upper levels
affect the priority of criteria at the lower levels. The report discusses AHP in detail as the case
study analysis is based on this method of upstream supply chain risk mitigation.
Reasons for selecting AHP as the basis of our case analysis:
 The AHP methodology is a flexible tool that can be applied to any hierarchy of
performance measure.
 It has been successfully used to solve Transportation problems in petroleum supply
chain.
 Has been successful in solving decision problems of supplier selection, forecasting, risk
opportunities modelling, plan and product design.

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 AHP is used in decision support systemfor inspection and maintenance of oil pipelines.
AHP Process:
1. Decompose the decision-making problem into ahierarchy
2. Make pair wise comparisons and establishpriorities among the elements in the
hierarchy
3. Synthesize judgments (to obtain the set of overallor weights for achieving your goal)or
weights for achieving your goal)
4. Evaluate and check the consistency of judgments.
The basic procedure is as follows:
1. Develop the ratings for each decision alternative for each criterion for each criterion
by:
 developing a pair wise comparison matrix for each criterion
 normalizing the resulting matrix
 averaging the values in each row to get the corresponding rating
 calculating and checking the consistency ratio
2. Develop the weights for the criteria by
 developing a pair-wise comparison matrix for each criterion
 normalizing the resulting matrix
 averaging the values in each row to get the corresponding rating
 calculating and checking the consistency ratio
3. Calculate the weighted average rating for each decision alternative. Choose the one
with the highest score.
4. Aggregating the weights of the decision elements to provide a set of ratings for the
decision alternative. Finally the sensitivity determined enables the decision maker to
graphically explore to what extent the overall priorities are sensitive to changes in the
relative importance (weight) of each attribute or criteria.

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Structure of the Hierarchy
Table 2: Saaty’s scale of 1 to 9 for relative Pair-wise comparison of Risks

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Risk Analysis:
Table 3: Various Risks, their Outcomes and Severity
The risks have been analyzed on the basis of 4 parameters:
• Average cost per day
• Time to revert to Normal Operations
• Loss of Lives
• Cost of mitigating the risk
Raw Material shortage:
The operations at an oil rig or a refinery are highly dependent on critical equipment either
falling under the category of static equipment or rotary equipment. These materials are further

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classified based on their utility and their life in the organization. The importance of raw
materials is obvious to those stakeholders that operate upstream extracting, refining, and
processing material into products; such stakeholders are intimately aware of the vagaries of
material supply and prices. If those raw materials become difficult to acquire, market forces
may shift demand to other goods and therefore other supply chains.
a) Proprietary Materials: Proprietary materials are those which are manufactured by the
makers of the main plants themselves such as spare parts for Willys' Jeeps.
b) Non-Proprietary Materials: Non-Proprietary materials are those which are manufactured by
many firms such as chemicals and laboratory equipments.
c) Stock Items: Fast moving items of regular consumption as also spares required for running
repairs and periodical overhaul of machinery and equipments are considered `Stock Items'.

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Capital Items:
All items costing Rs.5000/- or more and with a life of more than one year are categorized
as “Capital Items". Items costing less than Rs.5000/- which have a life of more than one
year and can be regarded as complete units in themselves (e.g. small compressors,
pumps, electrical motors, welding sets, electrical testing instruments etc.) are also to be
categorized as "Capital Items".
Stores & Spares: All the items, which cost less than Rs.5, 000/- and have a life of less than one
year are to be treated as "Stores & Spares". Stores items being the items of daily utility in HSE
activities and the dependent items such as spare parts of capital equipment come under the
spares category.
Consequence of Raw Material Shortage : Operational Downtime at Rig + Well Safety cost
= (657000000 + 600000) / 365  INR 1801643.84 per day
Operational fuel shortage:
The operations at the drilling rigs are catered to by High Speed diesel provided by the Tatipaka
Refinery, which are dependent on umpteen number of factors. They depend on the
transportation planning between the various rigs, the production pattern and operations at the
refinery and the quantity demanded at the rig depends on the critical operation. Each
operation at the rig requires a different power varying from 1 MW to 4 MW, provided by the 4 x
1 MW generator bay of Caterpillar.
The stakeholders under consideration include the lighting systems for the entire oil rig, the well
control equipment and the entire operations at the oil rig. Power is of paramount importance in
keeping the well in safety more than anything else. The operational fuel is provided by the oil
tankers of 12 KL capacity and the storage tank available at the rig has approximately 50 KL.
Consequence of Operational Fuel Shortage :Operational Downtime at Rig
= (657000000/ 365)  INR. 1800000.00
Customs clearance delay:
Customs clearance delay includes demurrage and operational downtime at the rig. Demurrage
charges are the charges paid to hold the raw materials and other inventory items at the port

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before it is collected by the concerned authority. For example the demurrage charges at the
Chennai port are given as follows:
The usual container size for oil industry is 40 feet (40’). The 40’ is required to handle the drill
pipes, heavy weight drill pipes and drill collars which have an average size of 30 feet. The above
charges are pertaining to Chennai Port clearance, which cater to drilling material requirements
of K.G. Basin, Andhra Pradesh.
Considering the average demurrage per day if it were held up for an year Chennai Port:
=
((
1805109.04
Consequence of Customs Clearance Delay : Operational Downtime at Rig + Demurrage
= (657000000 + 1864800 ) /365  INR. 1805109.04
Container Size Currency 20’ 40’ 40’HQ 45’HQ
Free days
(Calendar day)
15 days 15 days 15 days 15 days
1 - 15 days USD 10 20 20 -
16 - 21 days USD 18 36 36
>= 22 days USD 45 90 90
Table 4: Demurrage Charges for Chennai Port
Hydrocarbon Migration Risk:
The hydrocarbons that form within the mother rock are generally scattered in the sediments
and must have the possibility of migrating and concentrating to build up economically

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significant deposits. It has been calculated that only 5% of the hydrocarbons that form
accumulate in oil fields of a certain importance.
The presence of hydrocarbons under the crust is determined by the carrying out seismic studies
and the probable reserves are found. The wild cat wells or exploratory wells are drilled with this
data in mind and sometimes migration of hydrocarbons between the period of seismic studies
and exploration might lead to lower than expected production levels.
In such a scenario once all the enhanced recovery methods are considered and the well runs
dry, abandonment of the well is carried out. This permanently shuts the vent for the
hydrocarbons to the earth’s crust.
Consequence of Hydrocarbon migration risk: Abandonment cost + Expendables cost+
Exploration cost
(
1151506.85
Reservoir Pressure Depletion risk:
The hydrocarbon reservoir beneath the earth’s surface at the target depth will have reservoir
pressure due to which initial self-flow of hydrocarbons will occur. This self-flow of oil or natural
gas happens till the atmospheric pressure matches the reservoir pressure. Thereafter artificial
lift methods are utilized such as sucker rod pumps, gas lift valves and electrical submersible
pumps. Even after these techniques are used a maximum of 35-40 % can be extracted.
Then work-over procedures are undertaken to improve the production capabilities by
revamping the entire tubular system which would have worn out due to continued
hydrocarbon flow over a long period of time. The average time required for a work over
procedure is 10 days and the average cost of operation of a land rig is taken at INR. 1800000
per day. The tubular cost is considered the average value of drill collar, drill pipe and heavy
weight drill pipe. The average depth of the well at K.G Basin is 3000 m .

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Consequence of Reservoir Pressure Depletion: Revival cost + Extra expendables cost
(
213698.63
Dry well risk
The exploratory wells drilled worldwide have an average success rate of 60% , based on the
amount of recoverable hydrocarbons. This is a scenario when the target depth is attained and
the perforation to the hydrocarbon formation does not yield adequate pressure for production.
This requires complete abandoning of the well to prevent the scenario of a self-flow due to
seismic activity, hydrocarbon migration etc.
Consequence of Dry Well : Exploration cost + Abandonment cost
(
987123.29
Cargo Operators strike risk
The mode of logistics for movement of crude oil from the oil wells is by pipelines to the group
gathering stations and gas compression stations. From the GGS and the GCS, the hydrocarbon is
taken to the refinery by specialized pipelines for natural gas and crude oil. The mode of
transport for materials for the operations takes the mode of roadways, railways and freight
liners. The strikes that hinder the smooth flow of material in the supply chain have a chain
reaction across the different linkages of the supply chain.

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The mitigation of such a scenario is done by striking wage deals with the workers across the
supply chain.
Consequence of Striking Cargo Operators: Operational downtime at refinery + Operational
downtime at rig
Operational Cost the refinery has been found as follows:
Annual Revenue of Tatipaka Refinery is approximately: INR. 1,32,00,00,000
(
5435616.44
Pilferage Risk
Pilferage in the oil supply chain involves the illegal intervention by trespassers into the logistics
modes such as oil and natural gas pipelines, railway tanker carriages etc. for siphoning out
produce. This is an international menace across the major oil producing fields. This can lead to
stoppage in production from the mini refineries if the downstream pipelines are damaged in
this illegal activity.
The annual output value of oil movement from the refinery is .
Consequence = Pipeline damages/ Property loss + product costs
( ) 362465.75

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Oil Spill Risk
Oil spill has been an environmental issue deeply affecting marine life and onshore flora and
fauna leading to endangerment and extinction of various marine species. Oil spills are a
consequence of either damages to undersea pipelines for transport of oil from unmanned
platforms, process platforms, subsea wells or even crude tanker transit across the international
shipping routes. A major disaster related to oil spill was the deep water horizon incident of BP.
The Macendo blowout at Transocean rig lead to huge amount of oil spill and consequent
mitigation efforts by BP for shoreline clean up and marine spill containment.
Consequence = Marine cleanupcost+ Shoreline cleanupcost
( 44958.90
Geopolitical risks and Environmental risks
These risks cannot be quantified and are highly subject to change across geographies and with
passage of time. The consequence and severity of these forms of risks are tabulated below.

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Risks Outcomes Severity
Environmental
Risk
Ground watercontamination
risk
Remedial systemsinstallation+Aquiferdamage costs+
Liabilitycosts
Drilledcuttingsandeffluents
risk Effluenttreatmentcosts+ Aquiferdamage costs
Gas Flaringand pollutionrisk Collateral damage liabilities+Pollutioncontrol systemcosts
Geo Political Risk Trade Embargo Operational Downtime atrig+ Product movementdelay
Unavailabilityof imported
OEM equipment Operational Downtime atrig
Safetyof Producingwells Total well cost+ Collateral damage liabilities
Table 5: Environmental and Geopolitical Risks
Ranking of Risks based on the average cost per day for the opportunity is given above. Using
this data, rank ordering of the risks is done to understand which risk features on a scale of 1-9
when encountered simultaneously.
Ranking of the above mentioned risks on the basis of Average Cost per day:
Risks Outcomes Severity
Average costs Involved /
day
Sourcing Risk Raw Material Shortage
Operational Downtime at Rig + Well
Safety cost 1801643.84
Operational Fuel shortage Operational Downtime at Rig 1800000.00
Customs Clearance Delay
Operational Downtime at Rig +
Demurrage 1805109.04
Production
Risk
Hydrocarbon migration
risk
Abandonment cost + Expendables
cost+Exploration cost 1151506.85
Reservoir pressure
depletion risk Revival cost+ Extra expendablescost 213698.63
Dry well risk Explorationcost+ Abandonmentcost 987123.29
Logistics Risk
Cargo Operatorsstrike risk
Operational downtime at refinery +
Operational downtime at rig 5435616.44
Pilferage risk
Pipeline damages/ Property loss +
product costs 362465.75
Oil spill risk
Marine cleanup cost + Shoreline
cleanup cost 44958.90
Table 6: Average Cost Per Day of the risks

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To apply AHP to this process, we need to come up with a ranking of the various risks on the
basis of the 4 factors mentioned. This ranking can either be based on solid data or can be
intuitive depending on the availability of data from dependable sources.
In the first case the rankings for the risks on the basis of Average Cost per day is decided as per
the data give in the above table (Table 6.)
Table 7: Rankings on the basis of Average Cost Per day
Table 8: RANKING ON SAATY’S SCALE – TIME TO REVERT TO NORMAL OPERATIONS
Outcome Time to revert to normal operations
Raw Material Shortage 4
Operational Fuel shortage 2
Customs Clearance Delay 5
Outcome
Average costs
Involved / day
Hydrocarbon migrationrisk 5
Reservoirpressure depletionrisk 8
Dry well risk 6
Cargo Operators strike risk 1
Pilferage risk 7
Oil spill risk 9

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Dry well risk 9
Pilferage risk 6
Oil spill risk 1
The above ranking has been done based on criticality in resuming normal operations. Crisis
management in the oil industry is highly dependent on time. Incidents such as fire hazard, spills
and oil well blowouts get destructive with time.
Oil spill containment from sub-sea wells, pipelines and well head platforms use containment
mechanisms such as oil zapper, well killing using unmanned robotic vehicles etc. The greater
the delay greater would be the amount of the spill and proportionally increases the damage to
marine flora and fauna. The shoreline damage is yet another concern.
Operational fuel shortage shall render the installations and oil rigs without power. Exploration
is a continuous activity and intervention through cleaning of the wellbore, proper well control
mechanism and circulation of drilling mud for stabilizing the wellbore is dependent on power/
fuel availability. The greater the time lost, higher are the chances of the well caving in or
leading to a stuck up.
The critical well control equipment are OEM items sourced globally and unavailability renders
the working conditions highly unsafe for the crew. Thus mitigating it by sourcing it from other
projects or fast track cargo or logistics handling is paramount.
Raw material including HSE items at the rig which are required for the safe operations such as
rubber padded cotton gloves and escape mechanism from the different levels of the rig. These
materials are minimum requirements for the operations at the rig.
Customs clearance delay is in many cases blamed for the unavailability of critical equipment on
time. The clearing and forwarding agents need to diligently cater to the intermodal transport
requirements at the various refineries and installations.
Oil Pilferage is done mostly on pipelines in hinterlands and greater the time lost in replacing or
capping the pipeline; greater will be the loss of the produce by the company.

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Hydrocarbon migration, reservoir pressure depletion and hitting a drywell are situations
beyond the immediate handling capability. These are subject to geological conditions or less
reliable geophysical data being considered while undertaking drilling or developmental
projects. Thus in terms of time required in reverting back to daily operations they feature at the
bottom, but forms the premise for consideration while designing the next geotechnical order
for drilling of an oil well.
Table 9: RANKING ON SAATY’S SCALE – RESULTINGLOSS OF LIFE
Outcome Loss of life involved
Dry well risk 9
Pilferage risk 3
Oil spill risk 1
In any industry across the globe, life is of ultimate importance and all costs and associated time
become secondary. The chances of loss in life associated with the above risks pertain to marine
life surrounding the industry installation and life of the crew involved in the daily operations.
The rankings have been based on the danger to health hazards and safety criteria.
Oil Spill has the highest risk of loss to marine life, spanning square kilometers and even
endangering the shoreline flora and fauna. The BP spill in Gulf of Mexico has led to tremendous
loss of marine life and the shift crew of 11 members succumbed to injuries.
Raw material shortage can lead to ill functioning of well control equipment in the eventuality
of a gas kick or a blowout in the rare scenarios. Furthermore the escape devices are to be
tested regularly for adherence to API standards and their availability has to be ensured at any
cost.

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Pilferage has led to accidents in semi urban and urban areas due to the illegal intervention in
the otherwise hazard proof supply chain of hydrocarbon pipelines.
Operational Fuel shortage can lead to non-functionality of the critical well control equipment.
This includes the blow out preventer mounted on the well head, the accumulator bank for
pressuring the BOP, the kill lines and choke lines for diversion of hydrocarbon influx. The
sensors for presence of H2S gas at the installations are also electrically driven hence depriving
the safety measures in the absence of fuel.
Customs clearances delays lead to unavailability of required equipment for mitigating an
unforeseen scenario. The equipment used is highly customized and capital intensive. Thus
inventorying each form of equipment at warehouses is not a possibility.
Hydrocarbon migration across the reservoir can lead to unpredicted gas pockets, excess
pressures and aquifers in a well being drilled. The well control equipment installed may not be
able to handle this excess pressure due to the migration of hydrocarbon. Seismic activity and
faults can lead to this hazard.
Reservoir pressure depletion can lead to phenomenon called draw down in new wells being
drilled. Thus the drilling mud being used has a tendency to percolate deeper across the
circumference of the well. The contamination of water table in the initial phase of oil well
drilling can be hazardous to those dependent on it for water.
Cargo operations strike and dry wells has minimum consequence of loss to life in operations,
unless the cargo handling concerns equipment which are critical for well control.
Table 10: RANKING ON SAATY’S SCALE – COST OF MITIGATION
Outcome Cost Of Mitigation

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Dry well risk 7
Pilferage risk 4
Oil spill risk 9
The maximum amount of risks that can be mitigated with a budget for crisis management is
the criteria for arriving at a solution for this parameter of judgment. The highest amount for
mitigation is for oil spill containment which involves huge amount of damage liabilities and
environmental balance restoration. Hydrocarbon migration too requires huge investments in
the form of drilling developmental wells which is almost equivalent to exploratory costs.
Seismic studies and further logging operations are performed to analyze reasons for the
hydrocarbon migration. A dry well requires abandonment operation which involves cementing
the well bore from the surface to the target depth. The reservoir pressure depletion requires
enhanced oil recovery techniques such as in-situ combustion, polymer flooding, water injection
etc. These are expendable requirements that improve the recovery of hydrocarbons.
Operational fuel shortage can be mitigated by entering into short term fuel supply contracts
with third party downstream fuel suppliers or sourcing alternative options for powering the
machinery at the rigs and installations. The pilferage of fuel from pipelines and tankers can be
avoided by improving the security conditions to prevent trespassers and in case of pilferage;
the entire segment of the pipeline may have to be replaced. Raw material shortage can be
avoided by entering into rate contracts with long term suppliers to ensure timely delivery of
material and warehousing facilities need to be improved. Customs delays can be avoided by
applying for green channel clearance of critical oil field equipment and C & F clearance agents
can be used to fast track the landing the material. Logistics risk can be avoided by maintaining
an in house fleet of cranes, trailers if they are feasible, else long term service contracts can be
signed for reliable supply of material.
Table 11: RANKING ON SAATY’S SCALE – PARAMETERS OF JUDGEMENT
Ranking
Average costs / day 3
Time to revert to normal operations 2
Loss of life involved 1
Cost Of Mitigation 4

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The ranking of parameters are based on their importance in tackling a scenario. In any
operational scenario worldwide, maximum importance is given to avoid risk to life or in
mitigating health hazards.
The next important criteria in countering crisis involve deriving a strategy that mitigates the risk
in the minimum amount of time. The greater the time involved in solving a risk, greater the
damage inflicted on the various stakeholders. The amount of oil spill from an undersea pipeline
or subsea well leak is directly proportional to the time taken in capping the leak.
The opportunity cost in utilizing the resources which are rendered unusable by a particular risk
takes higher priority than cost in mitigating the risk. The hazard caused in the supply chain has
to be avoided at any cost, and thus mitigation cost takes the least priority
Applying AHP for each parameter:
This process involves following steps.
Average Cost Per Day:
1. Pair-wise Comparison:
Here we form a 9x9 matrix of the risks that we need to analyze. The matrix is formed by
comparing the risks with each other as a pair. For this we use the Saaty’s scale of 1 to 9.
Against 2 3 4 5 6 7 8 9
1 3 5 7 9
Table 12: Ranking as per the Saaty Scale
Since we need to use the values 1, 3, 5, 7 and 9, we consider the above table while making the
pair wise comparison of the risks. So if the rank of Pilferage Risk (say) is 4 against Cargo
Operators Strike Risk (Say), we consider the rank ofCargo Operators Strike Riskwith respect to
Pilferage to be 5. Consequently, the rank of Pilferage with respect to Cargo Operators Strike
Risk is 1/5 = 0.2.
So, basis this we create a 9x9 matrix comparing all the risks pair wise. The matrix is shown
below:

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Table 13: Pair wise Matrix for the risks based on “Average Cost Per Day”
2. Normalization:
In this particular step we “normalize” the above matrix. Normalizing the matrix means that we
find the total value of each column and divide the values in each cell with the corresponding
total.
This value is known as the average of the risk under consideration.
The Average value for each risk is given in the last column. This average would be used for
further calculations and hence holds high importance in the AHP process.
The matrix for this step is given below:

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Table 14: Normalization of the risks
3. Consistency Analysis:
This step involves 3 sub-steps in which we analyze the consistency of the matrix formed.
Consistency gives us an idea of whether the rankings have been done correctly or not.
The matrix is said to be consistent if the value for ƛMAX is less than 0.1. If this value is
more than 0.1, the matrix is said to be inconsistent which infers that some parameter
has been overlooked while coming up with the rankings for the risks. The 3 sub-steps
are as follows:
a. Calculate the consistency measure:
The consistency measure is calculated for each of the risks by Matrix multiplying
the each cell in the row of Table 13with the Average value column in Table
14and diving the product by the Average value for the particular risk.
For this we use the notation in MS-Excel :
=MMULT(B14:J14,U$14:U$22)/U14
b. Calculate the value for Consistency Index (CI):
For calculating the CI, we use the following formula:

27 | P a g e
c. Calculate the Consistency Ratio (CR)
Consistency Ratio is the ratio between the Consistency Index (CI) and the
Random Index (RI)
The Random Index here is a predefined table with the values of RI based on the
number of risks to be analyzed.
Table 15. Saaty’s Approximated scale of Random Indices
Table 16: Consistency Measure for the risks

28 | P a g e
Table 17: Consistency Ratio Calculation
Here we see that the CR for this set of rankings is < 0.1 which means that the rankings are
consistent with each other. From this we find out the Average weights for each of the risks which
have been shown in the figure below:
Table 18: Average weights for each risk
Average Daily Cost Factor
CI 0.114590317
Random Index 1.45
CR 0.079028

29 | P a g e
Graph that suggests that Cargo Operators’ risk is the most prominent of them all
A similar process is carried out for all the other 3 parameters in order to come to a logical
decision on as to what step has to be taken towards these risks.
Now moving on to the next parameter:
Loss of Lives Involved:
Following the same process for this parameter, we will be focusing on the charts and tables on
MS-Excel. With reference to the ranking table given previously (Table 9) we create the 9x9
matrix for pair wise comparison. Then Normalize the matrix and in the end check for
consistency.
0 0.1 0.2 0.3 0.4
Raw Material Shortage
Operational Fuel shortage
Hydrocarbon migration risk
Reservoir pressure depletion risk
Dry well risk
Cargo Operators risk
Pilferage risk
Oil spill risk
Average daily cost factor
Average daily
cost factor

30 | P a g e
Table 19: Pair wise comparison of risks basis “LOSS OF LIVES”
Table 20: Normalization and CR Calculations

31 | P a g e
Loss of Life Factor
CI 0.126512
Random Index 1.45
CR 0.08725
Table 21: Consistency Index and Consistency Ratio
Table 22: Average weights of each risk based on the loss of lives
The Graph below suggests that Oil Spill Risk is the most significant one amongst all others. E.g
Oil spill can lead to mass wipe out of marine life.
0 0.1 0.2 0.3 0.4
Reservoir pressure…
Dry well risk
Cargo operators risk
Pilferage risk
Oil spill risk
Loss of Life Factor
Loss of Life Factor

32 | P a g e
Time torevert toNormal Operations
Table 23. Pairwise comparison of risk basis “Time to revert back to operations”
Table 24. Normalisation and CR calculation
Time to revert to
normal operations
Raw Material
Shortage
Operation
al Fuel
shortage
Customs
Clearance
Delay
Hydrocarb
on
migration
Reservoir
pressure
depletion risk
Dry well
risk
Cargo
Operators
strike risk
Pilferage
risk
Oil spill
risk
Raw Material Shortage 1 3 0.3333333 0.2 0.2 0.142857 3 0.333333 5
Operational Fuel
shortage 0.333333333 1 0.2 0.1428571 0.142857143 0.111111 0.33333333 0.2 3
Customs Clearance
Delay 3 5 1 0.2 0.333333333 0.2 3 0.333333 5
Hydrocarbon migration
risk 5 7 5 1 3 0.333333 7 3 9
Reservoir pressure
depletion risk 5 7 3 0.3333333 1 0.333333 5 3 7
Dry well risk 7 9 5 3 3 1 7 5 9
Cargo Operators strike
risk 0.333333333 3 0.3333333 0.1428571 0.2 0.142857 1 0.2 3
Pilferage risk 3 5 3 0.3333333 0.333333333 0.2 5 1 7
Oil spill risk 0.2 0.3333333 0.2 0.1111111 0.142857143 0.111111 0.33333333 0.142857 1
Total 24.86666667 40.333333 18.066667 5.4634921 8.352380952 2.574603 31.6666667 13.20952 49

33 | P a g e
Loss of Life Factor
CI 0.11459
RI 1.45
CR 0.079028
Table 25. Consistency Index and Consistency Ratio
Outcome Matrix
Time To revert
factor
Raw Material Shortage 0.05
Operational Fuel shortage 0.02
Customs Clearance Delay 0.08
Hydrocarbon migrationrisk 0.22
Reservoirpressure depletionrisk 0.15
Dry well risk 0.32
Cargo Operators strike risk 0.04
Pilferage risk 0.11
Oil spill risk 0.02
Total 1
Table 26. Average weights of each risk based on Time to revert back to Operations
Graph showing that dry well scenario would take maximum time to revert back to Operations
0 0.1 0.2 0.3 0.4
Reservoir pressure depletion…
Dry well risk
Cargo Operators risk
Pilferage risk
Oil spill risk
Time to Revert to Operations
Time to Revert to
Operations

34 | P a g e
Cost of MitigationFactor
Table 27: Pair wise comparison of risks basis “Cost of Mitigating Risk”
Table 28: Normalization and CR calculation
Cost of MitigationFactor
CI 0.11459
RI 1.45
CR 0.079028
Table 29. Consistency Index and Consistency Ratio

35 | P a g e
Graph showing that mitigating a dry well requires highest amount of cost
Table 30 :Pair wise Judgment of Decision Criteria
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
Reservoir pressure depletion risk
Dry well risk
Cargo Operators strike risk
Pilferage risk
Oil spill risk
Cost of Mitigation Factor
Cost of Mitigation Factor

36 | P a g e
Table 31: Pair wise analysis of the parameters
Decision Alternatives
CI 0.039489
RI 0.9
CR 0.043876
Table 31: Consistency Index and ratio
Graph showing that loss of lives is the most critical parameter
DECISION MAKING FOR RISKS MITIGATION USING PARAMETERS OF
JUDGEMENT
The set of nine risks being mitigated are assigned different probability weights based on pair
wise comparison.
The parameters are given the following variables. (m)
1. Average Cost Factor
0 0.5 1
Average costs / day
Time to revert to normal
operations
Loss of life involved
Cost Of Mitigation
Decision Alternatives Factor
Decision Alternatives
Factor

37 | P a g e
2. Loss of Life Factor
3. Time to revert Factor
4. Mitigation Cost Factor
The risks for mitigation are given the following variables. (n)
1. Raw Material Shortage
2. Operational Fuel Shortage
3. Customs clearance delay
4. Hydrocarbon migration
5. Reservoir pressure migration
6. Dry well risk
7. Cargo Operations risk
8. Pilferage risk
9. Oil Spill risk
The risk values are In,m as shown in the table shown below.
Outcome Matrix
Avg. Cost
Factor
Loss of Life
Factor
Time To
revert
factor
Mitigation
Cost Factor
Raw Material Shortage 0.153 0.220 0.052 0.052
Operational Fuel shortage 0.107 0.109 0.025 0.025
Customs Clearance Delay 0.217 0.062 0.075 0.075
Hydrocarbon migrationrisk 0.075 0.075 0.217 0.217
Reservoirpressure depletionrisk 0.025 0.035 0.153 0.153
Dry well risk 0.052 0.016 0.318 0.318
Cargo Operators strike risk 0.318 0.025 0.036 0.036
Pilferage risk 0.036 0.164 0.107 0.107
Oil spill risk 0.017 0.295 0.017 0.017
Total 1 1 1 1
The judgement criteria factors are as shown by variables Jk.
Judgmentcriteria Matrix Factor
Average costs / day 0.121872613
Loss of life involved 0.557892475
Time to revertto normal operations 0.263345111

38 | P a g e
Cost Of Mitigation 0.056889801
Total 1
The final decision values for the 9 risks against the 4 judgment criteria are shown in the table
below.
Decision
Values
Raw Material Shortage 0.018670149
Operational Fuel shortage 0.013077183
Customs Clearance Delay 0.026472028
Hydrocarbon migration 0.009156292
Reservoirpressure depletion 0.003013878
Dry well 0.006379297
Logistics Problems 0.038746327
Pilferage 0.004329987
Oil spill 0.002027473
The supply chain risks according to the multivariate decision making tool AHP is as shown.
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
Supply Chain Risk
Supply Chain Risk

39 | P a g e
CONCLUSION
The case analysis has attained the initial objectives laid out to understand the supply chain of K.G Basin
operations of ONGC, along with a set of 9 risks involved. The pairwise comparison of risks has been
successfully performed using 4 judgment criteria. The AHP has helped understand if the risks internal
to the organization or the risks external to the organization contribute highest towards operational
downtime and loss of capital.
 External risks such as logistics risks (Cargo Operations risk) with a value of 0.038 cause the
highest amount of downtime or resource loss. This can be solved by entering into long term
contracts with third party logistics providers to ensure minimum blockage of material flow in
this critical supply chain. The same has to be ensured for intermodal transport from cargo ships
to road trucks for meeting tight delivery schedules.
 Customs clearance delay with a value of 0.0264 is the second greatest contributor to lack of
agility and responsiveness in the supply network. A green channel clearance at the major ports
for critical oil field equipment for exploration industry can be set up. The essentiality certificate
clearance for imported items has to be cleared faster by the Director General of Hydrocarbon,
GOI.
 Internal factor such as raw material shortage (0.018) and operational fuel shortage (0.013)
contribute comparatively less compared to external factors. These internal shortcomings can be
mitigated by improving the inventory levels of critical equipment and fuel at rig sites in a cost
effective manner.
The classification of risks into three levels of mitigation is as shown below.
AcceptandControlRisk
•Logistics Problems
•Customs Clearance
Delay
•Raw Material
Shortage
•Operational Fuel
shortage
Transferandsharerisk
•Hydrocarbon
migration
•Dry well
•Pilferage
Terminateandforgo
•Reservoir pressure
depletion
•Oil spill

40 | P a g e
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1. Financial Costs of Oil Spillsin the UnitedStates.
Etkin, D.S. 1998b. Oil Spill Intelligence Report, Cutter Information Corp., Arlington,
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2. Applying Analytic Hierarchy Process Framework for Assessing Risk in Pharmaceutical Supply
Chain Outsourcing.
Enyinda, C.I., Briggs, C.A., & Bachkar, K. (2009). The Journal of Business and Accounting, Vol. 2,
No.1, pp.32-41.
3. Multiple Attribute Decision MakingApproach to PetroleumPipeline Route Selection.
Dey, P. K., Tabucanon, M. T., Ogulana, S. O., & Gupta, S. S. (2001). International Journal for
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Cheng, L., & Duran, M. (2003), In I. E. Grossmann & C. M. McDonald (Eds.). Proceedings of
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SvenssonG.(2000), InternationalJournal forPhysical DistributionandLogisticsManagement,
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