FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Lecture 14Lecture 14
Alpha
Beta
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Objectives & Relevance
• Relevance:Demonstrate some the tasks that go into
determining the size of the ‘prize’ and the risk associated with a prospect
• Objective:Introduce the types of considerations
necessary to get a prospect ready for management approval
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Overview of Prospect Analysis
Given the geologic framework and the results of our data analysis, our next task is to analyze and assess viable prospects:
• Analyze prospect elements• Source, Migration, Reservoir, Trap, Seal
• Consider the most-likely scenario
• Consider other cases - the range of possibilities
• Assess the prospect• What volumes of HCs can we expect?
• Will it be oil or gas?
• Risk the Prospect
• What is our level of confidence that all the prospect elements work?
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volume
3. HC Type
4. Assessment
5. Risk
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FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volume
3. HC Type
4. Assessment
5. Risk
A “Kitchen”Where Organic
Material Is Cooked
A “Container” From Which Oil & Gas Can Be
Produced
“Plumbing” To Connectthe Container to the Kitchen
CorrectlyPlacedWells
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
A Real HC System
Brent Sandstoneacts as a reservoir
Unconformity
Heather ShaleSognefjord Shale
both organic poor
FaciesChange
Draupne Shaleorganic rich
serves as a source rock
Gas Generation
Gas Generation
Oil Generation
Oil Generation
Immature
Immature
Immature
Immature
HC Generation & Expulsionoil & gas from the Draupne, gas from coals in the BrentHC Migrationinto Brent carrier beds and up faults
HC Fill & Spill
FaultLeakPoint
OilSpillPoint
late gas displaces early oil
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Alpha Beta
Reservoir
Seal
Source
Basement
Overburden
18 Ma
Most-Likely Scenario
OilGeneration
OilMigration
OilFill & Spill
Sea Water
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Alpha Beta
Reservoir
Seal
Source
Basement
Overburden
10 Ma
Most-Likely Scenario
OilGeneration
OilMigration
OilMigration
Sea Water
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Most-Likely Scenario
Reservoir
Seal
Source
Basement
Overburden
Present
Alpha Beta
OilGeneration
GasGeneration
Oil & GasMigration
OilMigration
Sea Water
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Most-Likely Scenario
Map of the Reservoir Unit
Alpha Beta
Oil
Oil
18 Ma
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Most-Likely Scenario
Map of the Reservoir Unit
BetaAlpha
OilOil
10 Ma
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Most-Likely Scenario
Alpha Beta
Oil Oil
Gas
Map of the Reservoir Unit
Present
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Exploration’s Task
To EMDCor EMPC
DropArea
Drill Wildcats
ConfirmationWell
Identify Opportunities
ProcessSeismic Data
CapturePrime Areas
InterpretSeismic Data
AcquireSeismic Data
AssessProspects
Success
Success
Failure
Uneconomic1. Volume2. HC Type3. Assessment4. Risk
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volumes
3. HC Type
4. Assessment
5. Risk
Let’s start an exercise
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Exercise 12 – Parts 1 - 6
We will do some quick estimates using a series of simplifying
assumptions
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
How can we get a rough estimate of the cross-sectional area?
Base 1
Height 1
Consider This ….
Let’s say our trap in cross-section view looks like this….
Base 2
Height 2
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
From Area to Volume
Volume of a Cone = 1/3 Π r2 * h
Consider the trap to be approximately ½ a cone
Alpha
Beta
r
h
r r
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volumes
3. HC Type
4. Assessment
5. Risk
• DHI Analysis• AVO Analysis• HC Systems Analysis
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Oil or Gas???
• Should there be a difference in seismic response (AVO) between an oil-filled reservoir and a gas-filled reservoir?– Model response with different rock & fluid
properties
• If there should be a difference, which fluid type does the seismic data support?– Extract amplitudes from near- and far-angle
stacks
• From our basin modeling & HC systems analysis, which fluid type should we expect– What did the source generate– What did the trap leak or spill
Qu
an
titativ
eQ
ualita
tive
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Model Seismic Responses - Input
10% Porosity
Gas
Oil
Brine
20% Porosity
30% Porosity
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Model Seismic Responses - Output
10% Porosity10% Porosity
OffsetOffset OffsetOffsetOffsetOffset30% Porosity30% Porosity20% Porosity20% Porosity
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Model Seismic Responses - Output
-0.4
-0.2
0.0
0.2
0.4
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
Intercept
Slo
pe
GasOilBrineShale
10%
20%
30%
AVO Crossplot
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Questions???
• How can we verify this scenario?
• To what level are the traps filled with oil & gas?
• What would be the value ($) if our scenario is correct?
• How much more/less HC could there be?
• How risky is this prospect (chance that we are totally wrong)?
Many times the seismic data will give us clues!
Many times the seismic data will give us clues!
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Seismic Line Across ‘Alpha’
Fluid Contact?Oil over Water?
Fluid Contact?Gas over Oil?
Alpha
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volumes
3. HC Type
4. Assessment
5. Risk
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Types of Assessments
• Deterministic Assessment– One value for each parameter– One final number, e.g., 200 MBO
• Probabilistic Assessment– A range of values for each parameter– A range of outcomes, e.g. 200 ± 50
MBO
Once a lead has been high-graded into a prospect, we have to assess its potential value
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Scenarios & Probabilities
Gas Cap & Oil Leg
Alpha
40% Chance of Occurrence
Scenario 3
Scenario 1 Scenario 2
Scenario 4Alpha
Alpha
Alpha
Gas Only
Oil Only Low Gas Saturation
30% Chance of Occurrence 10% Chance of Occurrence
20% Chance of Occurrence
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
ESTIMATES Alpha Beta
1. Gross Rock Volume
2.91 km3
2.12 km3
2. Reservoir Volume
1.02 km3
0.66 km3
3. Pore Volume
0.25 km3
0.15 km3
4. In-Place Volume
0.20 km3
0.12 km3
5. In-Place – Barrels
1280 MBO
735 MBO
6. EUR – Unrisked
288 MBO
132 MBO
7. EUR – Risked
MBO
MBO
Deterministic Prospect Assessment
To Assess a Prospect, We Assign Numbers to the Parameters related to HC Volumes
In our exercise, we have assumed the all oil case (Scenario 3)
Unrisked means everything in the HC System has worked!
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Alpha Prospect Assessment Results
0 MOEB0 GCF0 MBOScenario 4Low Gas Saturation
288 MOEB0 GCF288 MBOScenario 3Oil Only
86 MOEB515 GCF0 MBOScenario 2Gas Only
178 MOEB97 GCF162 MBOScenario 1Oil & Gas
Oil Gas Oil-Equivalent
Assuming 100 MOEB is needed to make prospect economic
Uneconomic
Million Barrels Oil Billion Cubic Ft Gas Million Oil Equivalent Barrels
6 GCF = 1 MBO
Uneconomic
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Probabilistic Assessment
• The Goal is to Get A Number and a Range of Possible Outcomes
• We Input a Range of Values for Each Assessment Parameter – usually minimum, most-likely, maximum
Area
2012 27
MLMin Max
HC Sat.
Thickness Net:Gross Porosity
FVF Recovery
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Unrisked Results
Million Barrels of Oil
Alpha Prospect – Unrisked
0%
20%
40%
60%
80%
100%
0 100 200 300 400
100
Econ
om
ic M
inim
um
50% Chance of finding 200 MBO or more75% Chance of finding the economic minimum
Exc
edan
ce P
rob
abil
ity
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Outline
1. Define prospect elements
2. Estimating trap volumes
3. HC Type
4. Assessment
5. Risk
75% Chance of Success
25% Risk
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
9 Key Elements of the HC System
Biodegra-dation
Not Low Gas Saturation
HC Migration
Source Maturation
Source Quality
Trap Quality
Seal Adequacy
Reservoir Quality
Reservoir Presence
• A team of experts consider these key elements for each prospect.
• They rate the chance of success (COS) for each on a scale of 0 to 1
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
COS for Alpha
• Alpha’s biggest risk is that the fault does not seal.
• There is also some risk that the trap holds low gas saturation and that reservoir quality is poor• Reservoir Presence
• Reservoir Quality
• Trap Quality
• Seal Adequacy
• Source Quality
• Source Maturation
• HC Migration
• Not Low Gas Saturation
• Biodegradation
- - - - 1.0
- - - - 0.85
- - - - 1.0
- - - - 0.8
- - - - 1.0
- - - - 1.0
- - - - 1.0
- 0.9
- - - - 1.0
}0.61
chance of success
(COS)
Some Risk
Highest Risk
Some Risk
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Risked Probabilistic Assessment Results
0.0
0.2
0.4
0.6
0.8
1.0
0 100 200 300 400 500
Million Oil Equivalent Barrels
Alpha Prospect – Main Compartment - Risked
Gas Cap & Oil Leg
Gas Only 61 % COS
51 % Chance of Finding More
Than theEconomicMinimum
72% Chance to find any hydrocarbons58% Chance to find 100 MBOE 5% Chance to find 400 MBOE
100
Oil Only
Econ
om
ic M
inim
um
FWS 2005 L14 – Prospect AnalysisCourtesy of ExxonMobil
Exercise 14 – Part 7
In the exercise we will use • A COS of 61%• An economic minimum of 100
MBOE