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Society of Petroleum Engineers
Distinguished Lecturer Program
www.spe.org/dl
1
Unconventional Reservoirs Require
Unconventional Analysis
Techniques
David Anderson
Society of Petroleum Engineers
Distinguished Lecturer Program
www.spe.org/dl
2
This Presentation…
 Introduction to rate transient analysis (RTA)
 The challenge of analyzing unconventionals
 Current methodologies – how has the technology
evolved?
 The future of production analysis and modeling
 Probabilistic approach
 Field examples
3
Rate Transient Analysis (RTA) is the science (and art)
of extracting useful information about the reservoir,
completion and/or surface operations based on the
interpretation, analysis and modeling of continuous
measurements of production volumes and flowing
pressures from a single well.
4
Concept of Rate Transient Analysis
Company:
On Stream: 03/28/2013
Field:
Current Status: Flowing
Gp: 1775 MMscf
Np: 0.000 Mstb
Wp: 0.000 Mstb
Qcond: 0.000 Mstb
W ell 01
3600
5200
- Production occurs under
changing constraints
- Reservoir “signal” may be in
rates or pressures (or both)
3200
2800
2400
4000
3600
3200
1600
2800
1200
2400
800
2000
400
1600
0
1200
-400
800
-800
400
-1200
0
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
Time (days)
Normalized Time (month)
30
32
34
36
38
40
42
44
46
48
5
Run Depth Pressure (psi(a))
Op Gas Rate (Mscfd)
4400
pwf (psia)
q (Mscfd)
2000
4800
Concept of Rate Transient Analysis
Comparison View
9 . 10-3
Legend
6
Normalized Gas Rate vs. Normalized Time
Normalized Gas Rate vs. MBT (2)
4
3
Normalized Gas Rate (MMscfd/psi)
q/Dp (Mscfd/psi)
2
10-3
Instantaneous normalization
Superposition (Material Balance Time)
6
4
3
2
10-4
6
4
3
2
10-5
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
130
140
150
160
Normalized Time (month)
0
10
20
30
Time, Material Balance Time (months)
40
50
60
70
80
90
100
110
120
MBT
6
Type Curve Analysis – Characterize Reservoir
Comparison View
2.
100
4 . 100
1.0
Legend
q/D  - TC
Normalized Gas Rate vs. MBT
2
Log-Log Plot
- Identify flow regimes
Boundary Dominated Flow
(connected HCPV)
1.0
4
2
4
10-1
2
10-2
4
2
10-3
4
q/D  (MMscfd/(106psi2/cP))
4
q/Dp (Mscfd/psi)
2
10-1
4
2
10-2
4
Transient Flow
(permeability, skin)
2
10-3
2
10-4
4
2
4
10-4
Adapted from Palacio and Blasingame: “Decline-Curve
Analysis Using Type Curves” (SPE 25909) 1993
2
5
10-5
5 . 10-6
3
2 . 10-5
10-2
2
3 4 5 6 7 10-1
2
3 456
1.0
2
3 4 56
101
2
3 4 56
102
2
3 4 56
103
2
3 4 5 6 7 104
2
3 456
105
2
3 4
t ca (d)
Material Balance Time (days)
3 . 10-4 5 6
10-3
2
3 4 56
10-2
2
3 4 56
10-1
2
3 4 5 6 7 1.0
2
3 456
101
2
3 4 56
102
2
3 4 56
8 . 105
7
103
2
3 4 56
104
2
3
7 . 104
Flowing Material Balance – Estimate HCPV
Company:
On Stream: 10/01/2002
Field: Apollo
Current Status: Unknown
7000
30
6500
28
Gp: 3409 MMscf
Np: 224.268 Mstb
Wp: 16.566 Mstb
Qcond: 0.000 Mstb
Example 1
Legend
Gas Rate
Flowing Pressure
26
6000
24
Production Rate (Mscfd)
5500
22
5000
Pressure (psi(a))
pwf (psia)
4000
3500
3000
2500
Operated Gas Rate (MMscfd)
20
4500
18
Measured
flowing
pressure
16
14
12
10
2000
8
1500
1000
4
500
2
0
Measured rate
6
0
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
5.50
6.00
6.50
7.00
7.50
Cumulative Production (bcf)
Cumulative Gas Production (Bscf)
8.00
8.50
9.00
9.50
10.00
8
10.50
Flowing Material Balance – Estimate HCPV
Company:
On Stream: 10/01/2002
Field: Apollo
Current Status: Unknown
7000
30
6500
28
Example 1
Legend
Flowing p/Z**
Gas Rate
Flowing Pressure
26
6000
Calculated p/z
24
Production Rate (Mscfd)
5500
Gp: 3409 MMscf
Np: 224.268 Mstb
Wp: 16.566 Mstb
Qcond: 0.000 Mstb
22
Pressure, p/Z** (psi(a))
4500
4000
3500
3000
2500
2000
p  p
    qbpss
z  z  wf
20
Operated Gas Rate (MMscfd)
pwf and p/z (psia)
5000
18
16
14
12
10
8
1500
6
1000
4
500
2
- Mattar L., Anderson, D., Dynamic Material Balance – Oil or Gas
Original Gas-In-Place
In Place Without Shut-ins - 2, CIPC 2005-113
0
0
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
5.50
6.00
6.50
7.00
7.50
Cumulative Production (bcf)
Cumulative Gas Production (Bscf)
8.00
8.50
9.00
9.50
10.00
9
10.50
Modeling – Validate and Forecast
Results
11500
9.00
11000
10000
10500
9500
8.50
8.00
10000
7.50
9500
9000
Production Forecast
8500
9000
7.00
8000
8500
7500
6.50
7000
7500
5.50
7000
6500
6500
6000
6000
5500
5500
5000
5.00
4.50
4.00
3.50
Gas Cum (MMscf)
6.00
5000
4500
4500
4000
4000
3.00
3500
3500
2.50
Pressure match
3000
3000
2500
2.00
2500
1.50
2000
2000
1500
1500
1000
1000
500
500
1.00
0.50
0.00
0
2002
2003
2004
2005
2006
Pressure (psi(a))
Cal Gas Rate (MMscfd)
8000
Benefits of RTA
 Evaluation of reserves
 Reliable early evaluation- choked wells
 Scientific support for reserves auditors
 Dynamic reservoir characterization
 Estimate permeability and in-place hydrocarbons
 Estimate completion effectiveness
 Calibrate reservoir simulation models
 Reservoir surveillance
 Distinguish productivity fall-off from depletion
 Identify optimization candidates
The Challenge of Analyzing Unconventionals…
 Unconventional reservoirs are more complex
 Complex, non-uniform fracture networks
 Reservoir properties are significantly altered by
completion
 Low permeability – long term transient flow
 Drainage area continually expands
 Difficult to distinguish clear drainage boundaries
Flow Characterization – Conventional vs.
Unconventional
Radial Flow - Conventional
Linear Flow - Unconventional
 Fluid flows to the sandface
 Pressure drawdown localized
at sandface
 Fluid flows to the fracture(s)
 Pressure drawdown throughout
fracture(s)
High Permeability
Low Contact Area
Low Permeability
High Contact Area
Unconventional Analysis Methods…
Square Root Time Plot- Linear Flow
Simple A = 4 nf xf h
h
2 xf
A k
Complex A 
Dp
q
Skin
Dp
 m t b
q
t
A
f
Boundaries and Drainage – Conventional vs.
Unconventional
a) Conventional Reservoir
b) Unconventional Reservoir
Horizontal Wells
Vertical Wells
Parallel Fractures
Fracture
interference
Stimulated
Reservoir Volume
(SRV)
Geological features
Parallel and Orthogonal
Fractures
Well interference
15
Unconventional Analysis Methods…
Flowing Material Balance
Stimulated Reservoir Volume
h
2 xf
Le
p
wf
z
In-place
hydrocarbons
(SRV)
Cumulative Productioni
Unconventional Analysis Methods…
Simplified Approachtetf = SRV
Anderson et al 2010, Analysis of Production
Data from Fractured Shale Gas Wells – SPE
131787
A√k
skin
SRV
Assume – uniform fractures
Calculated- xf, k, skin, SRV
Illustrating the Challenge of Analyzing
Unconventionals
Simulation of flow into a complex fracture network in a gas shale
Company:
On Stream: 25/06/2013
Field:
Current Status: Flowing
Gp: 705 MMscf
Np: 0.000 Mstb
Wp: 0.000 Mstb
Qcond: 0.000 Mstb
W ell 02
3 . 104
540
520
500
480
2
460
440
420
360
9
340
8
320
7
300
6
280
260
5
240
4
220
200
180
3
2
-
160
Non-uniform frac length,
spacing and conductivity
Ultra low matrix permeability
Six months production,
constant pwf
140
120
100
80
60
40
20
103
0
June
July
August
September
October
2013
November
December
Run Depth Pressure (psi(a))
Op Gas Rate (Mscfd)
380
104
pwf (psia)
q (MMscfd)
400
tetf = SRV
A√k
skin
Contacted
HCPV
q/Dp (MMscfd/psi)
Dp/q (psi/MMscfd)
Simplified Approach – Bulk Reservoir Properties
Gpa/ceDp (bcf)
Square Root Time
q/Dp (MMscfd/psi)
SRV =
0.75 bcf
Time (d)
Contacted
HCPV = 1.1 bcf
Simplified Approach – Comparison of Analyzed
Reservoir Properties with Actual
As Analyzed
Actual
Stimulated reservoir width = 120 ft
k (stimulated zone) = 0.011 md
k (matrix) = 0.0005 md
Contacted OGIP = 2 bcf
Hz fractures – 250 ft, FCD=50
Vert fractures – 500 ft, FCD = 100
k (matrix) = 0.0001 md
OGIP = 46 bcf (1 section)
Simplified Approach – Comparison of Analyzed
SRV with Actual
As Analyzed
Actual
SRV = 0.75 bcf
SRV ~ 0.75 bcf
Simplified Approach – Comparison of 5 year
Production Forecasts
Comparison View
2 . 101
Gp = 1.8 bcf
101
Gp = 1.9 bcf
8
6
q (MMscfd)
Cal Gas Rate (MMscfd) / Rate Forecast 1 (MMscfd)
5
4
3
2
1.0
8
6
5
4
3
2
10-1
2013
0
4
2014
8
12
2015
16
20
24
2016
28
2017
Time (years)
32
36
40
Time (month)
44
48
2018
52
56
60
2019
64
68
72
76
80
Field Example - Bakken Oil
Company:
On Stream: 06/05/2008
Field: Undefined Field
Current Status: Flowing
2 . 103
Gp: 72 MMscf
Np: 98.451 Mstb
Wp: 19.879 Mstb
Qcond: 0.000 Mstb
Bakken Oil
Bakken
103
5200
5000
7
4800
103
5
4600
4
7
4400
3
5
4200
4
2
4000
3
3800
2
3600
102
3400
3
Op Gas Rate (Mscfd)
Op Water Rate (stb/d)
Op Oil Rate (stb/d)
4
5
3000
4
2800
3
2600
2400
2
2200
2
2000
1800
101
101
1600
7
1400
7
5
5
1200
4
4
1000
3
3
2
800
600
2
400
200
1.0
1.0
0
04
05
06
07
08
2008
09
10
11
12
01
02
03
04
05
06
07
2009
08
09
10
11
12
01
02
03
04
05
06
07
08
09
10
2010
23
Casing Pressure (psi(a))
5
3200
Calculated Sandface Pressure (psi(a))
Run Depth Pressure (psi(a))
7
7
Tubing Pressure (psi(a))
102
Dp/q (psi/stb/d)
tetf = SRV
A√k
FCD’
Contacted HCPV = 2,800 Mstb
SRV = 850 Mstb
Np/ceDp (Mstb)
q/Dp (stb/d/psi)
Square Root Time
q/Dp (stb/d/psi)
Field Example – RTA – Simplified
Time (d)
24
Field Example – RTA - Modeling
High efficiency “short” fracs
Ozkan et al. 2009, “Tri-Linear Flow”
Low efficiency “long” fracs
Stalgorova et al, 2013, “Five Region
Model”
Summary of Current Unconventional RTA
Technology
 Provides a “bulk” reservoir interpretation
 Reliable estimation of stimulated and total
connected HCPV
 Identification of effective system permeability and
apparent skin damage
 No unique interpretation of fracture properties
(orientation, distribution, density, length and
conductivity)
 No unique interpretation of matrix permeability
 Analytical models with different geometries are
available
The Future of Unconventional RTA –
Probabilistic Approach
Rate Transient Analysis:
Deterministic
Data
q, pwf
Modeling – Realizations of RTA results:
Probabilistic
27
Probabilistic Well Performance Analysis
 Define ranges or distributions of input parameters
 Completion properties
 Reservoir properties
 Run the reservoir model probabilistically using Monte
Carlo simulation
 Keep only history matches that meet a minimum
goodness of fit criteria
 Report reservoir characteristics and production
forecasts as distributions, not single values
28
Probabilistic Well Performance Analysis –
Forecasts
Rate vs Time
Expected Ultimate Recovery
Rate vs Cumulative
Original Gas in Place
29
Conclusions
 RTA provides “bulk” reservoir interpretation
 Ideal for establishing connected HCPV
 Assists in understanding recovery mechanism
 Yields reliable production forecasts
 Analyzing unconventional well production presents
significant challenges
 Analysis and modeling technology has evolved
 Unconventional plays are statistical in nature – many
wells must be analyzed to understand behavior
 A probabilistic approach will help to manage and
communicate uncertainty
30
Thank-you…
Questions?
31
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32