Upload
lynhu
View
229
Download
1
Embed Size (px)
Citation preview
Reserves and Resources Core
The Underlying Business of Reserves Management
This section will cover the following learning objectives:
Learning Objectives
Explain importance of integration with other disciplines
Recognize calculations using the volumetric formulas for gas andoil
Explain the importance of dividing into flow units for dynamicreserves in reservoir simulation
Describe what reserves management is and how to do it
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
1
COPYRIGHT
Reserves Management
RESERVESMANAGEMENT
PRODUCTION
Discovery
Delineation
Development
PrimarySecondary
Tertiary
Abandonment
Exploration
Basin
Play
Prospect
Disposal
Reserves management is a key aspect for the reservoir engineer throughout field life
Definitions
Both R & R estimates are uncertain
Reserve classification recognizes uncertainty
Maximum resource size
Minimum resource size
Scope for future recovery (SFR)
Maximum reserves
Minimum reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
2
COPYRIGHT
Definitions
Proven reserves should be based on current economic conditions, including all factors affecting the viability of the projects …. the term is general and not restricted to costs and price only
Probable and possible reserves could be based on anticipated developments and/or the extrapolation of current economic conditions
Reservoir Engineering Functions
Main Functions Tied to Resources and Reserves
Estimation of the original hydrocarbons in place
Estimation of the recoverable reserves and recovery factors
Analysis of past performance
Prediction of future performance
Updating reservoir model as data improves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
3
COPYRIGHT
Resources versus Reserves
Recovery Factor (RF)
Reserves
Resource
(Recoverable hydrocarbons)
(Hydrocarbons-in-place)
Technical Factors
Reservoir Quality
Reservoir Drive
Method of Operation
Economic Factors
Oil and Gas Prices
Concession Terms/Taxes
Costs
Market
Contract
Influenced by:
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
4
COPYRIGHT
Not All Hydrocarbons are Reserves
Not economic with current technology
Not yet discovered
No market
Cannot be produced
within license term
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
5
COPYRIGHT
Common International Hydrocarbon Contracts
Net Profits Interest (NPI) Rights holder has no
responsibility for costs
Rights holder recovers a percentage against the Operators Net Operating Cash Flow
Reserves are obtained by conversion back to volumes as a PS contract by the current year average price
Net Royalty Interest (NRI) Hydrocarbons are
a gross percentage of all production
Rights holder carries none of the costs, only enjoying benefits of production
Normally reserved for governments or mineral rights owners
Production Sharing (PS) Rights holder
carries all of the cost
Rights holder is allowed to recover costs by converting production to a currency amount and recovering capital/operating costs according to a percentage against cost of gas or oil
Open the supplied spreadsheet: NRI-PS-NPI_Contract_Comparison_of_Reserves.xlsx
Gas versus Oil Field Impacts of Contracts
Same elements as oil reserves, with difference in types of models that work best
High recovery requires significant reservoir pressure depletion
Often driven by sales contract
Strong link between surface and sub-surface
Gas Field Reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
6
COPYRIGHT
Gas Well Performance
Actual Rate
Potential Rate
TailGas
CompressionNo Compression(60% Recovery) Stage I
(30% Recovery)
Stage II(10%
Recovery)
0
20
40
60
80
100
120
Time
Pressurepsig
[MPa]
Reservoir Pressure
Surface Pressure 1600 psig800 psig 500 psig0
2000
4000
6000
Gas RateMMSCF/D
[MMSCM/D]
[41]
[28]
[18]
[11 MPa][6 MPa]
[3 MPa]
[3.4]
[2.8]
[2.3]
[1.7]
[1.1]
[0.6]
= DCQ/SDC Low load factor means a lot of facility/production
capacity sits idle for much of the time
The maximum daily rate that the seller must be able to produce (generally specified monthly)
ACQ/365: average daily gas sales rate during a year
Total volume of gas to be sold during the year
Gas Contract Terminology
Annual Contract QuantityACQ
Daily Contract QuantityDCQ
Seller’s Delivery Capacity or Max Daily RateSDCMDR
Load FactorLF
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
7
COPYRIGHT
Typical Gas Contract Requirements
0
20
40
60
80
100
120
140
160
180
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
MM
scf/
dSDC
Take
DCQ[3.4]
[2.8]
[2.3]
[1.7]
[1.1]
[0.6]
[4.0]
[4.5]
[5.1]
[MM
scm
/d]
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
8
COPYRIGHT
Hydrocarbon Volume – Static View of Elements
In the reserves process, there is a creative positive tension between the static view of a Geoscientist and the dynamic view of a Reservoir Engineer.
Derivation Mapping
Well logs, seismic; models
Well logs, cores
Well logs, seismic; models
Petrophysics
Interpretation
Element Area
Thickness
Porosity
Net to gross
HC saturation
Recoverability (reserves)
Reserve Determination
Reserve Determination
Volumetric model comparison and corroboration
Integrating both:
Disciplines – most importantly geology and geophysical
Production System – Sub-surface and surface functions
Value
Flow models
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
9
COPYRIGHT
Offshore Asset
Asset Data Coverage
The magnitude of the uncertainty decreases with more data coverage, which may sometimes be correlative with time
Reserve and Resource Evaluation Throughout Field Life
Relative Risk
Production profile
Range of estimates
Study Methods
Field phase Appraisal Devel. Field review/special projects
Time
Rate
Cumulative
Low
High
Actual Recovery
Volumetric
Performance
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
10
COPYRIGHT
The Dynamic View – Integrated Production System
Symmetry: Does it Exist?
P10 and P90 Evenly Distributed Around Ultimate Predicted EUR (BBLS/M3/SCF/M TONS)
True reserves at this time are
dependent on:• Technology
available• Company view• Etc.
BTE
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
11
COPYRIGHT
Human Factors Affecting Estimates
Time
Estimated ultimate
recovery
Initial
Initial Recovery Estimate
Reserve Growth
Besides technical and economic factors, there are also human factors:
• Cognitive biases
• Heuristic biases
• Misdirected motivational systems
Estimates of ultimate recovery grow with time, improved understanding,technology, etc.
• Financial markets expect this growth
• Not always the case, resulting in overbooking
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
12
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Explain importance of integration with other disciplines
Recognize calculations using the volumetric formulas for gas andoil
Explain the importance of dividing into flow units for dynamicreserves in reservoir simulation
Describe what reserves management is and how to do it
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
13
COPYRIGHT
Analysis Principles of Uncertainty in Reservoirs
Reserves and Resources Core
This section will cover the following learning objectives:
Learning Objectives
Describe the importance of reservoir uncertainty
List some typical reservoir uncertainties and their categories
Understand the relationship of statistical parameters toprobabilistic parameters
Explain what a Probability Distribution Function (PDF) is
Recognize that both the Cumulative Distribution Function (CDF) –also known as the S-Curve – and the Exceedance DistributionFunction (EDF) are derived from the PDF and are just twodifferent ways of presenting the same data
List some typical sources for uncertainty ranges
Describe the typical distribution shapes for reservoir uncertainties,and their advantages and disadvantages
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
14
COPYRIGHT
Probabilistic Approach to Hydrocarbons in Place
Utilizes uncertainty analysis as well as statistics and statistical rules for combining distributions
A range of distribution of values is constructed for each input parameter to a calculation
There are two ways to combine distributions with multiple variant input parameters
Resulting distributions are combined to produce a final estimate of Hydrocarbons Initially in Place (HIIP) ranges
Objectives of Probabilistic Method
Identify interventions to mitigate against potential downsides or to exploit potential upsides
Quantify range/distribution of HIIP, reserves development plans and production profiles
Identify key variables which contribute significantly to uncertainty, appraisal targets
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
15
COPYRIGHT
Does a Structured Approach Help?
You can use astructuredapproach toestimateuncertainties andincorporate theminto a realisticrange of forecasts
Properly assessinguncertainty rangesand their physicalmeaning is thefoundation tomaking goodreserve estimates
Bias can lead to anunrepresentativeview of a project’suncertainty
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
16
COPYRIGHT
Ranges and Distributions
Pro
babi
lity
of O
ccur
renc
e (%
)
Value
Probability Density Function (PDF) Cumulative Distribution Function (CDF)
Pro
babi
lity
of V
alue
or
less
(%
)
Value
Communicating Uncertainties in an Assessment
Pro
babi
lity
of V
alue
or
less
(%
)
Value
The “S-curve”
Management requires ranges ofSTOOIP, rates, EUR and thelinkage to value
These forecasts shouldincorporate the full range ofuncertainty
A project is characterized by theentire S-curve, not just theExpected Value
When you have translated this tothis S-curve, you havecommunicated all of the risks anduncertainties into it
Projects will have different riskprofiles based on the shape oftheir S-curves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
17
COPYRIGHT
Ranges and Distributions
Smaller range of likely outcomes,smaller uncertainty
Range of Values
Larger range of likely outcomes, larger uncertainty
Pro
babi
lity
Uncertainty is generally treated as a continuous probability model where the result can vary anywhere between a selected minimum and maximum
Ranges and Distributions
Uniform
I know the max and min, but otherwise I have no idea as to what lies between
Log-Normal
I know the approximate range, but the probability is asymmetric, positively skewed toward higher values
Triangular
I know the min, most likely, and the max
Normal
I know an approximate range, and I know it is symmetrical about the most likely
Discrete
I know an approximate range, and I know it is symmetrical about the most likely
Histogram
I know distinct numbers that are integers of the parameter, i.e. the number of wells drilled cannot be a fraction of a well. Or my measurement is only accurate to an integer value
Double Triangular
I known it is log normal, but I only know the limits, so I’ll use a simpler function, until I know better
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
18
COPYRIGHT
Ranges and Distributions
Frequency Chart
Certainty is 97.84% from 4.8 to 33.8
Mean = 16.6.000
.006
.011
.017
.023
0
28.25
56.5
84.75
113
4.8 12.1 19.3 26.5 33.8
5,000 Trials 108 Outliers
Forecast: Zone 1 Recoverable Oil (mmbo)
Mode: Most likely
Probability Density Function (PDF)
Cumulative Chart
Certainty is 97.84% from 4.8 to 33.8
Mean = 16.6.000
.250
.500
.750
1.000
0
5000
4.8 12.1 19.3 26.5 33.8
5,000 Trials 108 Outliers
Forecast: Zone 1 Recoverable Oil (mmbo)
Median: Equal probability of being bigger or smaller than (P50)
Mean: Expected value or average
Cumulative Distribution Function (CDF)
For this example
Mean: 16.6 Median: 15.4 Mode: 12.9
Exceedance: Another Way to Look at Distributions and their Combination
HISTOGRAM
05
101520
1 2 3 4 5 6 7 8 9 10 11 12
0
5
10
15
20
1 2 3
0.0
20.0
40.0
60.0
80.0
100.0
1 3 5 7 9 11
0102030405060708090
100
1 2 3 4 5 6 7
PDFs EDFs (derived from PDFs)
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
19
COPYRIGHT
Exceedance: Another Way to Look at Distributions and their Combination
HISTOGRAM
05
101520
1 2 3 4 5 6 7 8 9 10 11 12
0
5
10
15
20
1 2 3
0.0
20.0
40.0
60.0
80.0
100.0
1 3 5 7 9 11
0102030405060708090
100
1 2 3 4 5 6 7
PDFs EDFs (derived from PDFs)
P(x) ≥ x
Exceedance: Another Way to Look at Distributions and their Combination
HISTOGRAM
05
101520
1 2 3 4 5 6 7 8 9 10 11 12
0
5
10
15
20
1 2 3
0.0
20.0
40.0
60.0
80.0
100.0
1 3 5 7 9 11
0102030405060708090
100
1 2 3 4 5 6 7
PDFs EDFs (derived from PDFs)
P(x) ≤ x
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
20
COPYRIGHT
Statistical Parameters from the CDF
Cumulative Chart
Mean = 349.86.000
.250
.500
.750
1.000
0
10000
305.58 327.72 349.86 372.00 394.13
10,000 Trials 9,912 Displayed
Forecast: One hundred
P90 or is it P10? P10 or is it P90?P50
Recognizing Uncertainty in the CDF
90%
Reserve Volume
Cumulative probability reserves greater than this volume
50%
10%
Proven
Probable “expectation”
Possible
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
21
COPYRIGHT
Exceedance versus Cumulative
E
x
P(x)
Exceedance at this P(x) ≥ to value of x
Cumulative at this P(x) ≤ to value of x
Ʃ
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
22
COPYRIGHT
Combination of Parameters Methods
Monte Carlo method Latin hypercube Parametric method
1 Generate curves for individual parameters
2 Combining parameters to obtain an estimate fora reservoir
Combining Distributions
Combining (e.g., adding ormultiplying) two or moreprobability distributions is notalways a simple task
You can combine mean valuesto get resultant mean values
But you generally cannotsimply combine other points onthe distribution
P10a + P10b + P10c ≠ P10total in most cases
There are mathematic formulasthat can combine somedistributions, or that provideclose approximations withothers.
A practical way to combine distributions is by Monte Carlo simulation
Randomly samples each inputdistribution
Combines (e.g., adds ormultiplies)
Sorts the resultant distribution.
Accuracy generally increaseswith the number of iterations
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
23
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Describe the importance of reservoir uncertainty
List some typical reservoir uncertainties and their categories
Understand the relationship of statistical parameters toprobabilistic parameters
Explain what a Probability Distribution Function (PDF) is
Recognize that both the Cumulative Distribution Function (CDF) –also known as the S-Curve – and the Exceedance DistributionFunction (EDF) are derived from the PDF, and are just twodifferent ways of presenting the same data
List some typical sources for uncertainty ranges
Describe the typical distribution shapes for reservoir uncertainties,and their advantages and disadvantages
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
24
COPYRIGHT
Static and Dynamic Uncertainties in R & R Estimates
Reserves and Resources Core
This section will cover the following learning objectives:
Learning Objectives
Describe static uncertainties
Describe the differences between various reserve calculationapproaches, including deterministic, scenario, and probabilistic
Describe the hybrid impacts of obtaining deterministic andscenario approaches incorporating probabilistic analysis, which isthe best approach the industry has found to get the best of bothtypes of approaches
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
25
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Describe static uncertainties
Describe the differences between various reserve calculationapproaches, including deterministic, scenario, and probabilistic
Describe the hybrid impacts of obtaining deterministic andscenario approaches incorporating probabilistic analysis, which isthe best approach the industry has found to get the best of bothtypes of approaches
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
26
COPYRIGHT
Deterministic Volumetric Model and Use in Flow Models
Reserves and Resources Core
This section will cover the following learning objectives:
Learning Objectives
Estimate original oil-in-place and gas-in-place given maps andaverage petrophysical data
Define the basis for net reservoir thickness
Explain grid overlay and contour methods of volumetric estimation
Calculate the mobile hydrocarbon volume in a reservoir
Use a HCPV plot with depth to determine reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
27
COPYRIGHT
Volumetric Calculations
1. Gross bulk volume = A hgross
2. Net bulk volume = A hgross NTG
3. Pore volume = A hgross NTG ϕ4. Hydrocarbon pore volume = A hgross NTG ϕ (1-Sw )
5. Hydrocarbons-in-place = A hgross NTG ϕ (1-Sw )/ Boi
NTG=hnet
hgross
hgross
NTG, ϕ, Sw
Boi
A
Volumetric Hydrocarbon in Place Calculation – Oil Zone at Undisturbed Conditions
Rock with Hydrocarbon
Total of Bulk Volume
Oil
Water
Matrix
HCVOL = A * h * (N/G) * ϕ * (1 - Sw)
Hydrocarbon Volume
Reservoir Volume
Net toGross
Porosity
Water Saturation
Reservoir
A = area
hh * (N/G)Sand
Clay
You may want to PAUSE a moment to review this slide.PAUSE
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
28
COPYRIGHT
Volumetric Estimates of OHIP
Net pay thickness: The portion of the gross thickness thatcontains porous, permeable, and hydrocarbon-bearing rock
Usually estimated using petrophysical cut-offs
• Porosity > 0.10
• Swirr < 0.70
• Permeability > 1.0 md (oil), 0.1 md (gas)
The cut-off values vary depending on lithology, pore sizedistribution, hydrocarbon quality, and other considerations
Cut-offs are usually determined by
• Cased-hole logging
• Core analysis
• Well test results (DST or MDT)
• Production logging (flowmeter)
• Analogue reservoir values
• Hydrocarbon type (oil or gas)
Net Reservoir Thickness
P o r o s i t y L o g
8 0 0 0
8 0 10
8 0 2 0
8 0 3 0
8 0 4 0
8 0 5 0
8 0 6 0
8 0 7 0
8 0 8 0
8 0 9 0
8 10 0
0 0 . 0 5 0 . 1 0 . 15 0 . 2
P or o s it y
Porosity
Dep
th
You may want to PAUSE a moment to review this slide.PAUSE
Pay used in the volumetric formula H NET, after applying
appropriate cut-offs
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
29
COPYRIGHT
Used when reservoir will be (or is) impacted by encroachment of water or gas
Volumetric calculation that describes the hydrocarbon volume distribution vs. depth in the reservoir
Encroachment into the reservoir occurs as a level plane (i.e., contacts move uniformly)
Downdip water injection Gas injection at crest of
structure
Aquifer influx Gas cap expansion
Hydrocarbon Pore Volume vs. Depth Plot
Natural water encroachment Artificial injection
Assumptions
Bulk Volume by Depth Increment
Top of structure map
Bottom of structure map(when not underlain by water)
Contours define enclosed areas,Ai and contour interval, h
Pyramidal Formula for eachdepth increment
ΔVb = (h/3) * [Ai + Ai+1 + (Ai*Ai+1)^0.5]
1 mi [1.6 km]
-5750 ft[-1753 m]
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
30
COPYRIGHT
Appropriate Recovery Factor and Reserves
Reserves
= Ultimate Recovery –Cumulative Production
Recovery factor is most appropriately determined by combining:
Detailed reservoirdescription
Development plans(number of wells, type offacilities, reservoirmechanisms employed)
Economics and marketconstraints
Ultimate Recovery
= Hydrocarbons Initially in Place * Recovery
Factor
Range of Recovery Efficiencies
Oil Reserves % OOIP Key Variables
Undersaturated Expansion 3–5% Rock Compressibility
Solution Gas Drive 10–17%Gas-Oil Relative Permeability
Water Drive 40–60%Aquifer Strength,
Producing Rate
Gas Cap Expansion 40–60%Gas Cap Integrity,
Producing Rate
Gravity Drainage 60+% Formation Dip Permeability
Volatile Oil - Oil
- Gas
17–25%
60–80%Condensate Content of Separator Gas
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
31
COPYRIGHT
Range of Recovery Factors
Gas Reservoirs % OGIP Key Variables
High Permeability, Volumetric
70–90%Abandonment Pressure
Low Permeability, Volumetric
40–60% Well Spacing
Water Drive 50–70%Aquifer StrengthProducing Rate
Gas Condensate Reservoirs
% OGIP % OOIP Key Variables
Pressure Depletion 70–90% 30–70%Condensate Yield
API Gravity
Water Drive 50–70% 40–65%Aquifer StrengthProducing Rate
Going Forward from the Static View
One role of a reservoir engineer is deterministic• Provide a number at year end
• In the previous problem it is:– 93.6 million barrels
– You have produced 70.5% of your EUR that you calculate from the field
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
32
COPYRIGHT
Going Forward from the Static View
1Build static geo-model within the design space
2Identify the unique uncertainty variables and ranges
3Generate 25–50 geo-models, honoring the available data
4 As the field is produced compare these geo-models to the dynamic constraints
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
33
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Estimate original oil-in-place and gas-in-place given maps andaverage petrophysical data
Define the basis for net reservoir thickness
Explain grid overlay and contour methods of volumetric estimation
Calculate the mobile hydrocarbon volume in a reservoir
Use an HCPV plot with depth to determine reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
34
COPYRIGHT
Volumetric and Flow Models
Reserves and Resources Core
This section will cover the following learning objectives:
Learning Objectives
Discuss the need for integration across disciplines, especially thegeology and geophysics (G & G) functions
Recognize when models are used in the life of a field
List the advantages and disadvantages of flow models
Explain the importance of corroborating the static (volumetric) anddynamic (flow) view of the reservoir
Explain the business goals of models for estimating reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
35
COPYRIGHT
Integration with Disciplines
If you bring people from different disciplines together, then you will achieve unexpected insights!
Theoretical Physicist1901 - 1976
Werner Karl Heisenberg
Position Momentum
∆x ∆p ≥ hUncertainty Principle
Reserves Evaluation
Resource Based
Approach
Hydrocarbonvolume in place
Recovery factor
Reserves
Scope for Recovery
Developmentplan
Production forecast
Project Based
Approach
Hydrocarbonvolume in place
Developmentplan
Production forecast
Economic evaluation
Reserves
Scope for Recovery
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
36
COPYRIGHT
Reserves Process Output
Surface Seismic
Well Testing
Wireline
Permanent Monitoring
Geology Petrophysics
PVT Data
Pressures – Fluid Contacts
Sedimentology
StructuralGeology
LWD / MWD
Cores
Reservoir Study
Sand type
Mineralogy
Porosity
Horizontal/vertical permeability
Layering
Shale extension
Fracture
Reservoir geological
modelPressure decline
Well productivity history
Reservoirperformance
Structure
Fault pattern
Aquifer size
Well pattern
Areal sand development
Reservoir geometry
Completion
Impairment
Stimulation
Wellperformance
Oil/gas PVT data
Viscosities
Reservoir fluid
Relative permeabilities
Residual oil/ gas saturations
Fluid flow data
Material Balance / sector modelling / full field simulation
Well patterns (both production and injection)
Production forecasts / Estimation of Ultimate Recovery
Reservoir Studies
Petrophysicalanalysis
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
37
COPYRIGHT
Decline Analysis
Volumetric or Static Method
Analogy
Reservoir Simulation
Material balance calculations for oil and gas reservoirs
Types of Reserve Determination Models
Early Stages of Development
Flow Models
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
38
COPYRIGHT
Oil Material Balance
Upward curve indicates water influx
slope = N
Eo+Ef,w
F
Oil material balance is a simplemass balance between the fluidsproduced from a reservoir and theexpansion of the fluids remainingin the reservoir
Oil material is written in terms ofOOIP, given that you know thefollowing:
• How much oil has been produced• Average reservoir pressure• How fluids expand versus
pressure• Rock compressibility
A special form of the materialbalance from Havlena and Odeh isshown, where the slope is N orOOIP
P = P1 P = P2
Original Fluids = Remaining Fluids + Produced Fluids
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
39
COPYRIGHT
Gas Material Balance
P = P1 P = P2
Original Gas = Remaining Gas + Produced Gas
Cum Gas Prod - BCF
P/Z
Initial Pressure/Z
Original GasIn Place
Gas Recovery@ Paban
Abandonment Pressure/Z
Gas material balance is a massbalance between the gasproduced from a reservoir andthe expansion of the gasremaining in the reservoir
Gas material balance is usuallyused to estimate OGIP andultimate gas recovery given youknow:
• How much gas has beenproduced
• Reservoir pressure
• How gas expands vs. pressure
• Abandonment pressure
• Rock compressibility
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
40
COPYRIGHT
Static vs Dynamic Material Balance
Gas
Water
Ground
Comparing Volumetric to Flow Model
Why compare volumetric to flow models?
What can the impact of water
be on the recovery factor for a gas? Why?
12345678910 12345678910
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
41
COPYRIGHT
Proven Reserve Constraints
Existing wells
Proven undeveloped locations
Can Include:
Immediate offsets toexisting wells
Locations betweenexisting wells withdemonstrated pressurecommunication
Oil shown to exist downto Lowest Known Oil(LKO)
What Are the Implications of These Cases?
Click PAUSE to review these comparative cases.
Case #1
Volumetric Calculation: 184 million barrels of oil
Decline Curve Projection: 125 million barrels of oil
Material Balance: 135 million barrels of oil
Case #2
Analogue: 350 million barrels of oil
Decline Curve Projection: 320 million barrels of oil
Reservoir Simulation (after risking): 330 million barrels of oil
Reservoir Simulation (un-risked): 430 million barrels of oil
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
42
COPYRIGHT
Static Uncertainty of Connectivity
Connectivity is the ability of fluids to move from one portion of thereservoir to another
It is a function of one or more of these reasons:• Geobody configuration
• Barrier locations and seal(faults, shales, pinchouts)
• Horizontal permeability
• Vertical permeability
Case #1
Volumetric Calculation: 184 million barrels of oil
Decline Curve Projection: 125 million barrels of oil
Material Balance: 135 million barrels of oil
Static Uncertainty of Connectivity
Connectivity is the ability of fluids to move from one portion of thereservoir to another
It is a function of one or more of these reasons:• Geobody configuration
• Barrier locations and seal(faults, shales, pinchouts)
• Horizontal permeability
• Vertical permeability
Case #2
Analogue: 350 million barrels of oil
Decline Curve Projection: 320 million barrels of oil
Reservoir Simulation (after risking): 330 million barrels of oil
Reservoir Simulation (un-risked): 430 million barrels of oil
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
43
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Discuss the need for integration across disciplines, especially thegeology and geophysics (G & G) functions
Recognize when models are used in the life of a field
List the advantages and disadvantages of flow models
Explain the importance of corroborating the static (volumetric) anddynamic (flow) view of the reservoir
Explain the business goals of models for estimating reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
44
COPYRIGHT
Reserves and Resources Core
Linking Physical Models to Probabilistic Results
This section will cover the following learning objectives:
Learning Objectives
Describe the differences, advantages, and disadvantagesbetween the following:A. Deterministic approaches
B. Scenario approach and the use of the decision tree in reservesevaluation
C. Probabilistic analysis
Derive deterministic and scenario approaches from theprobabilistic approach
Use design of experiments as an add-on to probabilistic analysisto improve selecting the right models
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
45
COPYRIGHT
Why Do We Need Real Physical Cases?
Since assets are complex reservoir systems that are difficult toanalyze using conventional reservoir engineering methods
Reserve Management requires a thorough understanding of:
Original Hydrocarbon-in-Place and it’s distribution inthe reservoir
Well deliverability under changing reservoir conditions
Recovery estimates to support business planning,investments, and reserves bookings
Field development planning requires tools that can evaluatealternatives that have dimensional aspects (e.g., welllocations, completion intervals, operating conditions andlimitations)
Deterministic is a Real Physical Case
Directly linked tophysical models (maps,development plans, etc.)
Does not capture orquantify full range ofuncertainty
Required for bookingreserves
Deterministic
Cannot be uniquelylinked to a singlephysical reservoir model
Captures the full rangeof uncertainties
Cannot be used forreserves directly
Probabilistic
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
46
COPYRIGHT
Integrating Real Physical Cases and Probabilistic Models
Both real physical cases and probabilistic models are needed for acomprehensive subsurface assessment
One hybrid method integrates deterministic cases and probabilisticmethods and gets the required real physical cases
Use real physical cases tocalculate an outcome for eachset of uncertainty values
Capture the full range ofuncertainty
A series of deterministiccases can create aprobabilistic assessment
Logically link physical modelsinto Low-BTE-High scenariosthat are technicallydefendable
Use these models to testalternative development plansand upside/downsidescenarios
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
47
COPYRIGHT
Scenario Outputs of Original Oil in Place
R &
R
Case
Low
Medium
High
CDF: P10 – P20EDF: P80 – P90
Scenario Outputs of Original Oil in Place
R &
R
Case
Low
Medium
High
CDF: P40 – P60EDF: P40 – P60BTE: P50
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
48
COPYRIGHT
Scenario Outputs of Original Oil in Place
R &
R
Case
Low
Medium
High
CDF: P80 – P95EDF: P20 – P5
Decision Trees
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
49
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Describe the differences, advantages, and disadvantagesbetween the following:A. Deterministic approaches
B. Scenario approach and the use of the decision tree in reservesevaluation
C. Probabilistic analysis
Derive deterministic and scenario approaches from theprobabilistic approach
Use design of experiments as an add-on to probabilistic analysisto improve selecting the right models
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
50
COPYRIGHT
Reserves and Resources Core
Tracking of Reserves and Transfers within Legal and Professional Framework
This section will cover the following learning objectives:
Learning Objectives
Describe how to track reserves with time and information gainedthrough the industry standard
Recognize how the law in the United States defines reserves
Describe the risk, uncertainty, and commerciality definitions thatdrive the standardized process between reserve estimates
Discuss how resources become reserves
Define 1P, 2P, and 3P reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
51
COPYRIGHT
Security Exchange Commission Reg 210.4-10
“Proved oil and gas reserves are the estimated quantities of crude oil, natural gas and natural gas liquids which geologic and engineering data demonstrates with reasonable certainty to be recoverable on future years from known reservoirs under existing economic and operating conditions.”
Reserves
1 2
3 4
Future quantities of petroleum expected to be recovered from naturally occurring underground accumulations
Working separately, the Society of Petroleum Engineers (SPE) and the World Petroleum Congresses (WPC) produced definitions for known accumulations (adopted in 1996)
Preferred standards across the industry
Attempts to standardize reservesterminology began in the mid 1930s
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
52
COPYRIGHT
Estimation of Reserves
Methods of Estimation are Called:
Deterministic if a single best estimate of reservesis made based on known geological, engineering,and economic data
• There is a high degree of confidence that the quantitieswill be recovered
Probabilistic when the known geological,engineering, and economic data are used togenerate a range of estimates and their associatedprobabilities
• There is at least 90% probability that the quantitiesactually recovered will equal or exceed the estimate
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
53
COPYRIGHT
Resource Classification System
TotalHydrocarbons
Initially In Place
DiscoveredHydrocarbons
InitiallyIn Place
Sub-Commercial Low
EstimateBest
EstimateHigh
Estimate
Unrecoverable
LowEstimate
BestEstimate
HighEstimate
Unrecoverable
Commercial
PRODUCTION
Proven Proven plus
Probable
Proven plus
Probable plus
Possible
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Undiscovered Hydrocarbons Initially
In Place
Industry Resources Classification System
Reserves
Discovered, recoverable, commercial, remaining
Proven, probably, possible
1P, 2P, 3P (now formalized)
Contingent Resources
Discovered, potentially recoverable, not yet commercial, remaining
1C, 2C, 3C (new terms)• Equivalent to low, best,
and high estimates
Prospective Resources
Undiscovered, potentially recoverable, potentially commercial, remaining
Low, best, and high estimates
Unrecoverable
Discovered or undiscovered, not recoverable
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
Classificatio
n
Categorization
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
54
COPYRIGHT
Project Maturity – Prospective Resources
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
On Production
Approved for Development
Justified for Development
Development Pending
Development Unclarified or On Hold
Development Unclarified or On Hold
Prospect
Lead
Play
Project Maturity Sub-Classes
Prospect
A project associated with a potential accumulation that is sufficiently well defined to represent a viable drilling target
Lead
A project associated with a potential accumulation that is currently poorly defined and requires more data acquisition and/or evaluation in order to be classified as a prospect
Play
A project associated with a prospective trend of potential prospects, but which requires more data acquisition and/or evaluation in order to define specific leads or prospects
Classificatio
n
Categorization
12345678910
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
55
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Describe how to track reserves with time and information gainedthrough the industry standard
Recognize how the law in the United States defines reserves
Describe the risk, uncertainty, and commerciality definitions thatdrive the standardized process between reserve estimates
Discuss how resources become reserves
Define 1P, 2P, and 3P reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
56
COPYRIGHT
Following R & R after Production Starts
Reserves and Resources Core
This section will cover the following learning objectives:
Learning Objectives
Describe transfer mechanism from probable and possible toproven, once an asset is undergoing development
Use a diagram of secondary and primary exploration objectives todescribe how resources become reserves
Recognize some limitations of the law on transfers to avoidoverbooking
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
57
COPYRIGHT
Non-Commercial Reserves Prior to Discovery
What do you need to do to move this
project along?
Non-Commercial Reserves Prior to Discovery
• Terms of agreement?• Do you have a reservoir?• Offshore or onshore?• Producing characteristics?• Analog fields?• Where are potential sources?• How much source is available?• Migration path?• Where’s the “kitchen”?• Is it oil or gas?• Do you have a trap?• Does trap contain hydrocarbons?• Potential development costs?• Will it be commercial?• Can terms be renegotiated?• Should you partner with someone?• What did you miss?
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
58
COPYRIGHT
Industry Resources Classification System
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
Classificatio
n
Categorization
You Have a Contract to Drill, Prior to Discovery
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
59
COPYRIGHT
Whoops, No Discovery, But You Have a Reservoir
Whoops, No Discovery, But You Have a Reservoir
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
Classificatio
n
Categorization
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
60
COPYRIGHT
Now You Have a Discovery
Here, you have a hydrocarbon-filled reservoir tested at commercial rates.
Now You Have a Discovery
Here, you have a hydrocarbon-filled reservoir tested at commercial rates.
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
Classificatio
n
Categorization
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
61
COPYRIGHT
Industry Resources Classification System
Tota
l Pet
role
um In
itial
ly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Com
mer
cial
Sub
-Com
mer
cial
Und
isco
vere
d P
IIP
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Incre
asin
g Ch
an
ce o
f Co
mm
erciality
Classificatio
n
Categorization
Proven Producing Reserves
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
62
COPYRIGHT
Another Idea and the Process Continues
Tota
l Pe
tro
leu
m In
itia
lly-I
n-P
lace
(P
IIP)
Dis
cove
red
PII
P
Co
mm
erc
ial
Su
b-C
om
mer
cia
l
Un
dis
cove
red
PII
P
Production
Unrecoverable
Unrecoverable
RESERVES
CONTINGENT RESOURCES
PROSPECTIVE RESOURCES
Proven Probable Possible
1P 2P 3P
1C 2C 3C
Low Estimate
Best Estimate
High Estimate
Range of Uncertainty
Increasing Chance of C
omm
erciality
Reserve Classification
High Degree of Certainty of Estimate Low
Proven Probable Possible(50%)*
Proven Undeveloped (PUD) (50%)*
(0%)*
Proven Developed (PD) Producing
(100%)*
Proven Developed Behind Pipe (75%)*
Proven Developed Non-Producing
(90%)*
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
63
COPYRIGHT
This section has covered the following learning objectives:
Learning Objectives
Describe transfer mechanism from probable and possible toproven, once an asset is undergoing development
Use a diagram of secondary and primary exploration objectives todescribe how resources become reserves
Recognize some limitations of the law on transfers to avoidoverbooking
PetroAcademyTM Applied Reservoir Engineering Skill Modules
This is Reservoir Engineering Core
Reservoir Rock Properties Core
Reservoir Rock Properties Fundamentals
Reservoir Fluid Core
Reservoir Fluid Fundamentals
Reservoir Flow Properties Core
Reservoir Flow Properties Fundamentals
Reservoir Fluid Displacement Core
Reservoir Fluid Displacement Fundamentals
Properties Analysis Management
Reservoir Material Balance Core
Reservoir Material Balance Fundamentals
Decline Curve Analysis and Empirical Approaches Core
Decline Curve Analysis and Empirical Approaches Fundamentals
Pressure Transient Analysis Core
Rate Transient Analysis Core
Enhanced Oil Recovery Core
Enhanced Oil Recovery Fundamentals
Reservoir Simulation Core
Reserves and Resources Core
Reservoir Surveillance Core
Reservoir Surveillance Fundamentals
Reservoir Management Core
Reservoir Management Fundamentals
Reserves and Resources Core
Reserves and Resources Core ═══════════════════════════════════════════════════════════════════════════════════
©PetroSkills, LLC. All Rights Reserved. _________________________________________________________________________________________________________
64
COPYRIGHT