smart fractured reservoir development strategies
TRANSCRIPT
Smart Fractured Reservoir Development
Strategies
TUROGE Event, 9th & 10th April 2014
Dr Mark Cottrell ([email protected])
FracMan Technology Group
Golder Associates Europe
Introduction
Introduction
Presentation describes a strategy that can provide insight into the
improved assessment of unconventional fractured hydrocarbon plays
(e.g. shales, tight gas, coal gas, and fractured carbonates), and also for
renewables (e.g. deep geothermal);
The strategy provides integration of key geological data that can be
used to provide rational descriptions of the fractured rock conditions,
which are normally more complex than those needed for conventional
porous flow systems;
The approach provides a scalable/verifiable approach for understanding
the effects and influences of the natural fracture network, in terms of
specific well trajectories, compartmentalization, completions,
potential hydraulic fracture stimulation and environmental risk. 2
(c) Golder Associates, 2013
14 April 2014
Presentation Overview
Presentation Overview
Questions & Why?
Mechanical Units
The DFN Method
Hydraulic Fracturing
Microseismicity
Simulating Production
Going from Well to Field Scale
Use for Environmental Drivers?
Conclusions
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(c) Golder Associates, 2013
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Key Questions to Smart Fractured Reservoir
Development
What would we like to be smarter about in our fractured reservoir?
What are the Fracture geometries? –Directionality of properties
Are the fractures conductive, closed or sealing? – Contribution to Production
How many & how big? – Volumetrics
What is their spatial distribution? - Layer bound, Pervasive? – Connectivity
How well do they connect? – Drainage volumes, well planning – Optimisation
Fracture Kh? – Flow rate impacts
Do different populations behave differently? Faults, joints? – Heterogeneity
Mechanical sensitivity of properties? –Stress, strength, etc.
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(c) Golder Associates, 2013
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Why are Fractures Important?
FMI Fractures/m Fracture KHWhat the FMI sees…..
What the PLT sees…..
PLT inflows don’t have to coincide
with high fracture frequency
well
well
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(c) Golder Associates, 2013
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Not All Rocks are Similarly Fractured
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Shales: Few natural fractures
Bakken
Shales: Natural fractures but some are healed
Eagle Ford
Barnett
Niobrara
Shales: Persistent, open, natural fractures
Marcellus
Utica
Monterey
Niobrara
Coals: Butts and Face Cleats
Surat Basin Australia
SE Piceance Basin
Niobrara
Utica
(c) Golder Associates, 2013
Surat BasinPiceance Basin
Mechanical Units
Mechanical Units and Natural
Fracturing
Natural fracturing is from the
combined effect of mechanisms
related to material layering and
in situ conditions;
Mechanisms related to layering
are often considered responsible
for both naturally occurring and
hydraulic fracture development
Example of mechanical layering in marly shales;
Fractures intensities can vary significantly across small boundaries; and
Arresting of fractures from crossing between mechanical layers can
effectively inhibit vertical connectivity in the reservoir/play.
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(c) Golder Associates, 2013
Upper
Mechanical
Layer
Lower Mechanical
Layer
7
Discrete Fracture Network (DFN) Model
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+ Major Faults
+ Matrix
+ Natural Fractures
Modern DFN Analysis Workflow
Model Frame-
work & LoadingFracture
Characterisation
Fracture Model
Building
Static-Dynamic
Analysis
DFN Upscaling
& Dynamic
AnalysisAll
Units0
10.0
20.0
30.0
40.0
50.0
60.0
EquivRadius
0
10
20
30
40
50
60
Fre
quency
Orientation
Size analysis
Intensity
analysis
Layered fracture systems
Regular fracture systems
Full field models
Matrix block size analysis
Hydraulic fracture simulation
Volumetrics & TDV
Permeability upscaling
Oil or Gas flow simulation
Geomechanical analysis &
upscaling
Data from:
well logs,
surfaces, grids,
geological,
geomechanical,
geophysical
models
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(c) Golder Associates, 2013
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Example Well Data to DFN Model (Vertical)
Cumulative Fracture Intensity Plot
0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Percent of Total Fractures
40.0
50.0
60.0
70.0
80.0
90.0
100.0
110.0
120.0
Measu
red D
epth
Well_1_Intersecting Fractures_Log
Orientation: Orientation
data taken from image log.
Care needed to correct for
bias
Fracture intensity data taken
from well data
Cumulative intensity graph showing two
lower thicker but lower intensity layers
around thinner higher intensity layer
Final DFN model
of outcrop
Intersecting fractures seen
organised within three main
layers of the reservoir
Conceptual Model: Synthesising intensity
data, orientation and structural knowledge
helps develop a conceptual picture of how to
assemble DFN model.
DFN model from well data requires greater
conceptual push (driven from structural
knowledge & concepts) and results in higher
uncertainty than a model built from outcrop
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(c) Golder Associates, 2013
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Example Well Data to DFN Model (Lateral)
Intensity data from Image logs
Trace Length Exercise
0.0001
0.001
0.01
0.1
1
10
1 10 100 1000 10000
Trace Length (meters)
No
rm
ali
zed
Nu
mb
er
Outcrop Data
Lineament Map Data
Fracture size data from
seismic, well and
outcrop data
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(c) Golder Associates, 2013
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Orientation data from Image logs
Stage 1: Connected Volume
Stage 1 “hydraulic fracture” with top
reservoir layer trace map superimposed
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(c) Golder Associates, 2013
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3D Hydraulic Fracture
Inside Overall Natural
Fracture Network
• The pumped stimulation fluid preferably flows into the connected natural network; and
• If the natural fractures cannot accommodate the pumped water volume, the ‘new’
hydraulic fracture develops further (perpendicular to minimum stress).
Stage 2: Microseismicity in Shales
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(c) Golder Associates, 2013
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Microseismicity Inside
Fracture Network
• Based on critical stress conditions, the timing and locations of microseismicity can be
simulated; and
• Microseismicity maps can be compared with observed, and can also help understand
the combined effect of in situ stress and natural fracture conditions.
Critical Stress Calculation
Stage 3: Stimulated Rock Volume
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(c) Golder Associates, 2013
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Static Prediction of Stimulated
Rock Volume (SRV) • Stimulated Rock Volume
provides poor 1st order
estimate of drainage
volume per stimulation;
• Can help guide treatment
design and well spacing;
• Helps understand
interference.
Stage 4: Simulation of Production
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Pressure derivative curves may not
have distinct fracture and matrix flow
regimes, but may produce
derivatives with slopes between a
half and one, similar to actual
deconvoluted production data; and
Can help predict long term
production characteristics.
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(c) Golder Associates, 2013
Answering Well Scale to Field Scale Question
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(c) Golder Associates, 2013
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Fracture ParametersCumulative Fracture Intensity Plot
0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Percent of Total Fractures
9600.0
9800.0
10000.0
10200.0
10400.0
10600.0
10800.0
11000.0
Mea
sure
d D
epth
Duncan_5-13A2_Log_Duncan_5-13A2_LGROpenBOF ...Duncan_5-13A2_LGRBedding
P10=0.227
P10=0.610
P10=0.127
P10=0.934
Segment ID Starting Depth Ending Depth P10 C31 P32
1 9677.35 9966.11 0.23 3.37 0.76
2 9997.05 10394.11 0.13 3.37 0.43
3 10409.58 10564.27 0.93 3.37 3.14
4 10563.536 10771.271 0.61 3.37 2.05
LGR only
1
-41•10
-31•10
-21•10
0.1
-51•10
Perc
entile
102
1•103
1•104
1•105
1•10
Trace Length
CCDF Graph
PowerLaw Distr. parameters selected by user
minimum = 600 exponent = 2.4858
K-S statistics 0.173649
signif. level 0
0.01
0.1
1
0.1 1 10 100
Rate
-no
rm
ali
zed
P
ressu
re D
eriv
ati
ve (p
si(
a)/
bb
l/d
ay)
Time (hour)
Ute Tribal Test #2
Ute Tribal Test 1
Chevron Hatch 1-5B1 Test 1
Chevron Hatch 1-5B1 Test 2
Gulf Campbell Ute 1-7B1 Test 1Gulf Campbell 1-7B1 Test 2
T=2,100 md-ft/cP
T=720 md-ft/cP
T=400 md-ft/cP
T=430 md-ft/cP
T=280 md-ft/cP
T=200 md-ft/cP
T=290 md-ft/cP
Well Test Fracture Property
Fracture Hydraulic Properties
Orientation
Size
Local Intensity
Seismic Attributes
3D DFN Model, can then be either
a) Well scale
b) Sector scale, or
c) Field scale
All Units
Geomechanical Upscaling
Flow Solver Upscaling
Drainage Volume
Drill Here Map
Hydro-frac Simulation
Attribute Analysis
Field Scale Fracture Intensity Map
Well Scale Correlation
Example CFI correlation between
observed and predicted
Good correlation between seismic
attributes & well control fracture intensity
Field Scale Prediction
Using CFI correlations for multiple wells,
and 3D seismic it is possible to produce
fracture intensity map “drill here map”
Intensity in unexplored locations can be
proven in future appraisal wells.
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Observed Well Scale CFI Log
derived from
Predicted CFI Log (Combined
Stiffness & Density)
Predicted CFI Log
(Stiffness only)
(c) Golder Associates, 2013
Question of Field Compartmentalization?
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(c) Golder Associates, 2013
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Oil/Gas that is not in a large
compartment may be difficult or
uneconomic to produce
Drainage is not a
simple ellipse!
E&P Models For Environmental Protection
Not just in E&P that such
approaches can help answer
questions and reduce risk
These approaches can help
minimise environmental
requirements and risk:
1) water requirements for
hydraulic fracture stimulation
2) hydraulic fracturing induced
seismicity on fault structures
3) deep injection strategies for
waste water disposal
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(c) Golder Associates, 2013
Some Clients and Fracture Project Locations
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Conclusions
Conclusions
We’ve presented an approach that can be used to provide smarter
assessment of naturally fractured reservoirs, e.g. shale's; fractured
carbonates, coals, volcanic basements;
Strategy provides integration of key geological data to provide a rational
and representative description of the fractured rock conditions and
importantly the connectivity;
Provides a scalable and verifiable approach for understanding the
effects and influences in terms of fracture connectivity, specific well
trajectories, compartmentalization, completions, and potential
effectiveness for hydraulic fracture stimulation.
Thank you for your attention! [email protected]
April 14, 2014 21
(c) Golder Associates, 2013
Smart Fractured Reservoir Development
Strategies
TUROGE Event, 9th & 10th April 2014
Dr Mark Cottrell ([email protected])
FracMan Technology Group
Golder Associates Europe