Python Notes for mca i year students osmania university.docx
Probabilistic Approach To U Resource Modelling
1. by Prof.Richard Sinding‐Larsen and Dmitry Surovtsev
INTERNATIONAL ATOMIC ENERGY AGENCY
Technical Meeting on Uranium Provinces
and Mineral Potential Modelling
20‐22 June 2011, IAEA Headquarters, Vienna,
Austria
2. About Authors, Disclaimer and Acknowledgement
Richard Sinding‐Larsen, Board Member and Co‐Founder of GeoKnowledge A.S.,
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is a professor of resource geology at the Norwegian University of Science and
Technology (NTNU). Richard has advised extensively on play assessment to
government agencies both in Norway and in South East Asia. He has been
Secretary General of the IUGS (International Union of Geological Sciences) and
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is currently Senior Advisor and responsible for the non‐renewable resources part
of the UN‐IUGS initiative on Planet Earth. Richard has a MSc in Applied
Geology and a PhD in Resource Geology, both from NTNU.
Dmitry Surovtsev is Head of Representation in Kazakhstan of Effective Energy
N.V., a member of Uranium Holding ARMZ. Before joining the uranium mining
industry in 2010 Dmitry followed a seventeen years career in the international
petroleum industry (business , consulting and academic ). Dmitry has a MSc in
International Economics from Moscow State Institute of International Relations
(MGIMO) and a certificate of postgraduate education in Banking & Finance
from the London School of Economics & Political Sciences (LSE).
DISCLAIMER: No proprietary sources and materials of authors’ companies and institutions were
used in the preparation of this presentation. Authors’ opinions may differ from the views of their
respective organizations.
ACKNOWLEDGEMENT: We would like to acknowledge the significant contribution of Charles
Stabell of Geoknowledge by allowing us to use his Economic Potential of a Shale Gas Resource Play
presentation as the ISL analogue.
3. Overview
• G
Genesis of HC & Uranium fields
i f HC & U i fi ld
• Uranium production by ISL vs. Oil Production
• ISL and Shale gas engineering issues
• Cost and economic parameter
• GeoX a Probabilistic Resource and Valuation tool
• The Uranium Play_Assessment_Process
• The Situation – Initial Position in Shale Gas Resource Play
• Approach
• Results
• Concluding remarks
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4. Genesis of HC & Uranium fields (hydrogenous)
G i f C& i fi ld (h d )
ρ (HC field) = ρ1 (Source) * ρ2 (Migration/Timing) * ρ 3(Reservoir) * ρ4 (Trap) * ρ5 (Seal) * ρ6 (Preservation)
ρ (U fi ld) (S
(U field) = ρ (Source Rock) * ρ (Mi ti /Ti i ) * (S d t
R k) * (Migration/Timing) * ρ (Sandstones) * ρ (S l) * (T
) * (Seal) * ρ (Trap)
)
5. Uranium production by ISL vs. Oil Production
i d i b S Oil P d i
Minimum economic U concentration in pregnant ISL parameters are close to HC parameters
solutions, minimum economic initial and terminal like water cut and economic well flow rates
well flow rate appear more relevant for ISL mining used for HC reservoir engineering.
engineers than ore grades in the ground.
Important issues are: Important issues are:
• permeability of the mineralised horizon; • changes of residual oil saturation to water
• hydrological confinement of the mineralized horizon; flood (Sorw) with changing permeability
and
• amenability of the uranium minerals to dissolution
by weak acid or alkaline solutions.
6. ISL and Shale gas engineering issues
T diti
Traditional open‐pit mining industry parameters (ore volume, cutoff and
l it i i i d t t ( l t ff d
average grade) are not entirely adequate for ISL projects.
Unlike open‐pit mining, ISL ore volume cannot be calculated with certainty
p p g, y
and is a function of subsoil fluid embayment area determined by Darcy law
and poroperm properties of the sandstones.
ISL and Shale gas assets presents unique assessment challenges Estimate of in‐
ISL and Shale gas assets presents unique assessment challenges. Estimate of in‐
place resources are not very useful as recovery is key.
Confidence in the conversion from resources to reserves, will be greatly
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enhanced if an ISL field leach trial can be undertaken.
Exploration for ISL and Shale gas assets is more like appraisal, where the key
decision is made after doing a pilot test production that can prove the potential
for commercial production.
7. Cost and economic parameters
Fortunately, cost engineering and economic concepts are not much
different whether we speak about open‐pit, ISL or Oil & Gas projects.
different whether we speak about open pit ISL or Oil & Gas projects
In all cases we would need to account for:
CAPEX
project size‐dependent
project si e dependent
size‐independent
OPEX
fixed (time dependent)
variable (output‐dependent)
Sales Price
Main Product
Associated By‐Products
Tax Regime
Concession
PSA
The results of economic assessment by DCF analysis in all cases are NPV
and IRR and, for exploration projects, EMV
EMV = ρ (Success) * NPV – ρ (Failure) * PV (Exploration costs)
8. "A tool meeting CCCP requirements"
B h i
Both integrated project evaluation teams and top
d j l i d
management of exploration ventures need an assessment
tool that meet the CCCP requirements :
Consistent methodology & deliverables
Cross‐Discipline (Full‐Cycle)
Common Database
Probabilistic Assessment (Monte Carlo)
S h t l h b
Such a tool has been developed and constantly improved in
d l d d t tl i d i
Norway since 1985 to serve the needs of 70+ international
oil & gas companies in 20+ countries .
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Let's see how the concept may be applicable for ISL
Uranium projects.
18. Concluding
C l di remarks
k
Assessment tools (GeoX) for Exploration Decision &
Management Support allows for:
Integrated probabilistic modelling that reflects both
static and dynamic uncertainties can be performed for
Uranium ISL in a similar way as for shale gas resources
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Multiple target – multiple activity sequences can be
used to model conditional pilot‐infrastructure‐full
p
production activities
Support for entry, full development and abandonment
pp y, p
decisions
