Production History Variation
Based Probabilistic Simulation
Analysis of Gas-to-Wire
Monetisation of Associated
Natural Gas
Nnamdi Benedict Anosike
Prof. Pericles Pilidis (supervisor)
© June 2013
Cranfield University
Disclaimer
 The views expressed here are those of the presenter, and may
not necessarily reflect those of Cranfield University.
 The information in this presentation is part of on-going
research, and is not enough on its own for investment advice.
 Use of information contained in this presentation is at your
own risk. The presenter recommends you seek independent
professional advice before making any investment decisions.
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Oder of Presentation
Introduction
. Motivation of study
1
2.
3.
4.
Associated gas monetization
Monetization technologies
GTW monetization
Case Study
.
1 Reserves Specifications
2. Powerplant Specifications
3. Economic Parameter/Conditions
4. @RiskTM MCS
Result and Conclusion
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Introduction
Motivation of Study
Monetization of associated gas or associated
petroleum gas (APG)
GTW—Onsite electric power generation
utilization of stranded natural gas reserves
 Capturing the effect of production decline
both technologically and economically
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Introduction
Associated Gas Management Drawbacks
1.
Vented to open air or flared
pose environmental problems and economic waste , which is no
longer acceptable
------
2.
Gas re-injection for oil recovery
------ “what goes up will always come down” hence this tends towards a
sunk cost.
3. Monetization options
------ depends on terrain, local market for gas, proven gas reserve size, and
most reserve are not economically feasible for matured technologies.
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Introduction
Transportation Mode
Technological
Amount of Gas
Maturity
needed for Project
PNG (pipeline natural gas)
Mature
Depends on distance
LNG (liquefied natural gas)
Mature
>1-3 Tcf
GTW (gas-to-wire)
Developing
10 Bcf – 1 Tcf
GTL (gas-to-liquid)
Developing
> 500 Bcf
NGH (natural gas hydrate)
Future
> 400 Bcf
CNG (compressed natural gas)
Developing
> 300 Bcf
GTC (gas-to-commodity)
Mature
< 1 Tcf
Natural Monetisation Technologies Adapted from Rajnauth et al., 2008
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Introduction
GTW Monetization Scheme
Source: Watanabe et al., 2006
A typical variation of annual power as
production decline
GTW-CTRA (GTW-Combined
Technoeconomic and Risk Assessment)
Framework
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Case Study
Scenario-1: ~1 Tcf
Scenario-2: ~480 Bcf
Scenario-3: ~10 Bcf
@ 12% decline
Reserves Specifications:
Production Decline:
 APG production increase as oil production decline, or
 APG production decline exactly like oil production, or
 APG decline production different from oil production decline.
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Case Study
Reserves Specifications
Name
Log Rate-Time
Shape
Exponential
Straight
Exponential
Straight
Arps
Continuous straight
Hyperbolic
Curved but
converging
Curved but limit
Arps
Continuous curve
Arps
Continuous curve which
nearly converges
Harmonic
Amended
Curved but not
converging
Model
Decline
Stepwise
Dual – Infinite acting
amended to a limiting curve
Production decline type : Hyperbolic decline
Annual production decline: 12 – 20%
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Case Study
Case Study
Powerplant Specifications
Scenario-1: 1000MW
Scenario-2: 450MW
Scenario-3: 15MW
TUBORMATCH GT Engine thermodynamic model Parameters








power output in MW,
fuel flow (kg/s)/ specific gas consumption,
thermal efficiency in % or heat rate in kJ/kWh,
pressure ratio,
ambient temperature K,
mass flow in kg/s,
turbine entry temperature (TET) in K, and
exhaust gas flow (EGF) in kg/s.
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Powerplant Specifications
Case Study
Power Plant Type: Simple cycle or combustion turbine powerplant
Engine parameter
Engine #
Power Output (MWe)
Thermal efficiency (%)
Fuel flow (kg/s)
Pressure ratio
Ambient temperature (K)
Mass flow (kg/s)
TET (K)
EGT (K)
EGF (kg/s)
Design point figures (ISO conditions)
1
2
3
4
5
6
7
8
200
100
80
50
20
30
10
5
33
13.87
15.5
288
700
1400
801
713.87
36
6.19
21.5
288
340
1400
764
346.45
38
4.88
22.4
288
260
1400
744
264.88
39
1.80
38.4
288
120
1400
654
121.80
34
0.67
38.4
288
45
1400
678
45.67
37
0.31
22.4
288
10.9
1600
512
11.21
38
31
3.04
1.51
22.4
38.4
288
288
162
100
1400
1400
743
699
165.04 101.50
Gas turbine parameter description and simulation figures
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Case Study
Economic Parameter/Conditions
Economic assumptions
Case Study
 2012 US$,
 GTW overnight specific capital investment cost of 798 $/kW
 Fixed annual O&M costs: 8.04 $/kw/year
 Operates for 8000 hours/year, allowing for maintenance
 Variable O&M costs: 0.012 $/kWh
 APG production/processing cost: 0.24 $/kg
 Interest rate used for carrying charges: 12%
 Monetization project duration: 25 years
 Electricity is sold to the grid at the cost of 0.29 $/kWh
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Economic Determination Index
Case Study
Required to find
The engine sets mix for various scenarios while keeping
track of the required NPV, and utilized reserve limits, using
MCS of the highly sensitivity factors ( production decline
rate and GTW capital investment cost)
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@ Risk Monte Carlo Simulation
Case Study
Probability distributions used for parameters
Parameters
Type of probability distribution and why they are used
Project overnight specific
Pert distribution was used here since improvement in technology
investment cost,
will lower the cost of equipment over time.
Production decline rate
Normal distribution
Gas wellhead cost
US wellhead gas price from the year 2000 to 2012 from EIA was
used to establish the distribution for gas price. The result was a
Log-normal distribution.
Fixed O&M cost
Triangular distribution
Variable O&M cost
Triangular distribution
Electricity price
Log-normal distribution
Plant initial Size
Triangular distribution
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GTW-CTRA @RiskTM MSC Monte Carlo
Simulation
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Results
Scenario-1
Engine units mix matrix from divestment simulation results.
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Results
Scenario-2
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Results
Scenario-3
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Conclusion
 GTW-CTRA tool is developed with MCS capability using @RiskTM
 GTW monetization of APG case study for reserves between 10 Bcf to
1Tcf have been done using @RiskTM
 A contrast between probabilistic reserves data and available
powerplant MWe have been investigated
 Two major GTW operational risk factors were analysed and their
techno-economic impact estimated.
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Question and Comment
Thank you!
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