CMGWebinar Unconventional Reservoir Modelling 18Feb15

 Al ex No  Alex Novl vl es esk ky Sr.. Rese Sr Reservoi rvoi r Simul Simulation ation Engi nee neerr

 Ag  A g en end da • Sh Shal ale e Oil Oil & Ga Gas s Pr Prod oduc ucti tion on • Why use use Reservoi Reservoirr Simulatio Simulation n for modellin modelling g Tight Tight reser reservoir voirs, s, includi including ng Shales? Shales? • What Phy Physics sics are bein being g modelle modelled d in Ti Tight ght & Shale Shale play plays? s? • New Ad Advan vances ces in in Modell Modelling ing Hyd Hydrau raulic lic Fract Fractur ures es • How has has simulatio simulation n helped helped in understa understandin nding g the physics physics & produc production tion/rec /recover overy y mechanisms of these plays? • Ti Tight ght & Shal Shale e Reser Reservoir voir Mode Modelling lling:: Chal Challeng lenges, es, Oppo Opportun rtunitie ities s & Less Lessons ons Learned? • Why use CM CMG G for Mo Model dellin ling g Tigh Tightt & Shal Shale e plays plays? ?

 Ag  A g en end da • Sh Shal ale e Oil Oil & Ga Gas s Pr Prod oduc ucti tion on • Why use use Reservoi Reservoirr Simulatio Simulation n for modellin modelling g Tight Tight reser reservoir voirs, s, includi including ng Shales? Shales? • What Phy Physics sics are bein being g modelle modelled d in Ti Tight ght & Shale Shale play plays? s? • New Ad Advan vances ces in in Modell Modelling ing Hyd Hydrau raulic lic Fract Fractur ures es • How has has simulatio simulation n helped helped in understa understandin nding g the physics physics & produc production tion/rec /recover overy y mechanisms of these plays? • Ti Tight ght & Shal Shale e Reser Reservoir voir Mode Modelling lling:: Chal Challeng lenges, es, Oppo Opportun rtunitie ities s & Less Lessons ons Learned? • Why use CM CMG G for Mo Model dellin ling g Tigh Tightt & Shal Shale e plays plays? ?

Nor orth th Americ A merica a Shale Shale Plays Plays

USA Shale Shale & Tig ight ht Oil & Gas Produc Prod ucti tion on (2000-2013) USA Shale & Tight Oil Production (mmbpd)

USA Dry Shale Gas Production (bcfd) 2.8

Eagle Ford (TX) Bakken (MT & ND)

2.4

30

Marcellus (PA and WV)

Granite Wash (OK & TX)

Haynesville (LA and TX)

2.0

Bonespring (TX Permian)

35

Rest of US

25

Eagle Ford (TX)

Wolfcamp (TX Permian) Spraberry (TX Permian) Niobrara-Codell (CO)

1.6

Bakken (ND)

1.2

Woodford (OK)

20 15

Fayetteville (AR)

Woodford (OK) Monterey (CA)  Austin Chalk Chalk (LA & TX)

0.8

Barnett (TX)

0.4

 Antrim (MI, IN, and and OH)

10 5

0.0 2000

2002

2004

2006

2008

2010

2012

0 2000

2002

2004

2006

2008

2010

2012

USA Gas Production (1990-2040) History

2012

Projections

40 100

35

90 30

80

  y 25    /    f   c    T 20

70 60

Shale gas

50

15 10 5

40

Tight gas

Non-associated onshore

20

Non-associated offshore

1990

 Associated with oil 1995

2000

30

2005

2010

2015

Coalbed methane 2020 2025 2030

 Alaska

2035

10

2040

   d    /    f   c    B

USA Oil Production (1990-2040) History

2012

Projections

10

U.S. maximum production level of 8 9.6 million barrels per day in 1970 Tight oil 6

   d   p    b   m   m 4

Lower 48 offshore  Alaska

2

1990

Other lower 48 onshore

1995

2000

2005

2010

2015

2020

2025

2030

2035

2040

Why Use Reservoir Simulation? For Physics-based EUR’s & Optimization • • • • • • • • •

Long time to pseudo-steady-state Multi-phase flow Non-darcy (turbulent) flow Multi-component phase behavior, adsorption & diffusion Compaction of fractures Heterogeneous rock properties Heterogeneous fractures Geomechanics Geochemistry

Why Use Reservoir Simulation? To Represent Current Development Practices • Analyze & Forecast multi-well pad models exhibiting interference • Model re-fracs & infill drilling • Interpret production surveillance data • Simultaneously account for many uncertain parameters

Commonly Modelled Physics Reservoir Description • Matrix porosity & permeability • Natural & propped fractures • Pore volume compaction/dilation • Non-darcy (turbulent) flow

PVT • Black Oil  ‒ Primary production • EoS  ‒ Miscible gas injection EOR & near-critical fluids

Commonly Modelled Physics  Adsorbed components • •

Gas phase only, dry tight/shale gas Multi-component gases & liquids

Diffusion • •

Multi-component gas Miscible gas injection EOR

Rock Physics • •

Tight rock Rel Perm & Cap Press in matrix Straight line Rel Perm & no Cap Press for fractures

Source: SPE 164132

Commonly Modelled Physics Simulation Model Gridding LS-LR-DK or Tartan Grids surrounding the propped fractures •

Transient multiphase fluid flow from matrix to natural fractures & from matrix to propped fracs

•

Non-darcy flow in propped fracs near laterals

Simulation Model Initialization Initialize propped & natural fracture network with water •

Flowback of injected fracture fluid

CMG’s LS-LR-DK “ Tartan” Grids

The “ key” to modelling “ transient flow” from matrix to fractures!

Modelling Planar & Complex Geometry Propped Fractures

Planar Fractures in SRV

Complex Fractures in SRV

Product Suite  Advanced Processes & Thermal Simulator Compositi onal & Unconventional Reservoir Simulator Three-Phase, Black-Oil Reservoir Simulator Sensiti vity Analysis , History Matching, Optimization & Uncertainty  Analy sis Too l Integrated Production & Reservoir Simulation Intelligent Segmented Wells Phase Behaviour and Fluid Property Application Pre-Processing : Simulation Model Build ing Applic ation Post-Processing: Visualization and Analysis Application

CMG has the Right Physics Physics

IMEX

GEM

BO, VO, GC, WG

EOS

Gas Phase

Multi-Comp

-

Multi-Comp/OWG Phases

Natural Fracs (NF)

Dual Perm

Dual Perm

Propped Fracs (PF)

LS-LR in Matrix (MT)

LS-LR in Matrix (MT)

MT, NF & PF

MT, NF & PF

-

MT

Krel & Pc

MT, NF, PF & time

MT, NF, PF & time

Press-dependent Compaction

MT, NF, PF & time

MT, NF, PF & time

Stress-dependent Compaction

-

Geomechanics-based

Chemical Reactions

-

Ion Exchange & Geochemistry

PVT  Adsorbed Components Molecular Diffusion w/ Dispersion

Non-Darcy (turbulent) Flow Non-Darcy (slip) Flow

Primary Productio n

Primary Productio n & EOR

CMG Milestones in Unconventional Reservoir Modelling Capabilities & Workflow s

Microseismic Data • Can use to estimate the extent of the unpropped SRV during pumping & the geometry of its fractures • Acquired to monitor or even control the treatment* • Easily incorporated into Builder’s workflow using the Microseismic import wizard

Geomechanics • Model permeability change, with hysteresis, as a function of stress change during production and shut-in periods • Fracture opening during hydraulic fracturing treatments  ‒ using GEOMECH’s Barton-Bandis feature

New Advancements In Hydraulic Fracture Modelling

Existing Situation Dataset keywords: **$ Fracture RESULTS FRACTURE BEGI N RESULTS FRACTURE WELLNAME

‘ Wel l 1'

REFI NE 303, 343, 7 I NTO 2 5 1 CORNERS RG 303, 343, 7 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 7550. 0000 2*7562. 5000 7575. 0000 4*8550. 0000 8*8560. 5481 8*8562. 1952 8*8562. 8048 8*8564. 4519 4*8575. 0000 4*8550. 0000 8*8560. 5481 8*8562. 1952 8*8562. 8048 8*8564. 4519 4*8575. 0000 472. 5700 2*472. 5335 472. 4970 472. 5770 2*472. 5417 472. 5065 472. 5770 2*472. 5417 472. 5065 472. 5780 2*472. 5430 472. 5080 472. 5780 2*472. 5430 472. 5080 472. 5785 2*472. 5435 472. 5086 472. 5785 2*472. 5435 472. 5086 472. 5795 2*472. 5448 472. 5101 472. 5795 2*472. 5448 472. 5101 472. 5865 2*472. 5530 472. 5196 474. 5700 2*474. 5335 474. 4970 474. 5770 2*474. 5417 474. 5065 474. 5770 2*474. 5417 474. 5065 474. 5780 2*474. 5430 474. 5080 474. 5780 2*474. 5430 474. 5080 474. 5785 2*474. 5435 474. 5086 474. 5785 2*474. 5435 474. 5086 474. 5795 2*474. 5448 474. 5101 474. 5795 2*474. 5448 474. 5101 474. 5865 2*474. 5530 474. 5196

Refinements: 17 wells 117 stages 8,129 refined blocks 203,225 refinement cells 32,516 property specs ~ 720,000 lin es of inp ut deck

Solution? •

Concise Fracture Definitions

•

Remove the refinements keywords from the datasets  ─  Fractures created upon simulator initialization

•

Builder and Simulator share the same code  ─  What you see in Builder is exactly what the simul ator will create

While We’re At It… Fracture Templates • • •

Contain refinement definitions Re-use multiple fractures or wells Single place to parameterize in dataset

Make Hydraulic Fractures a simulator keyword • • •

Apply different fracture templates Fracture properties recognizable in dataset Parameterization of fractures available outside Builder

Fractures defined as an ‘Object’ • •

Assign properties by fracture name Block Groups allow for quick & easy defining/editing

New Setup- Fracture Template RESULTS PLNRTEMPLATE NAME 'Templat e_I_Dir ectio n'

Primary Width (Intri nsic )

RESULTS PLNRTEMPLATE PRIMFRACWIDTH 0.0018 RESULTS PLNRTEMPLATE PRIMFRACPERM 100000

Fracture Perm (Intrin sic )

RESULTS PLNRTEMPLATE PRIMFRACTIP 100 RESULTS PLNRTEMPLATE END *PLNRFRAC_TEMPLATE 'Template_I_Direction' *PLNR REFINE *INTO 5 5 1 *BWHLEN 65

Fracture Tip Perm Half-Length

*IDIR *INNERWIDTH 0.6096

Direction

*LAYERSUP 0 *LAYERSDOWN 0 *PERMI MATRIX *FZ 295.3 0.2953

Heigh t (via Layers)

*PERMJ MATRIX *FZ 295.3 0.2953 *PERMK MATRIX *FZ 295.3 0.2953 *END_TEMPLATE

Fracture Perm (Effective)

New Setup- Fracture Definition RESULTS PLNRSTAGE NAME 'Planar Stage 8' RESULTS PLNRSTAGE WELL ‘Well 1' RESULTS PLNRSTAGE DATE 2006-08-14 RESULTS PLNRSTAGE BASENAME ‘Well 1 - Frac'

Fractu re Name Well

RESULTS PLNRSTAGE FRACS 'Well 1 - Frac 1' ' Well 1 - Frac 2' RESULTS PLNRSTAGE FRACS 'Well 1 - Frac 3' ' Well 1 - Frac 4'

# of Fractures

RESULTS PLNRSTAGE SLABS '262, 268, 275, 281' RESULTS PLNRSTAGE PERFOPTION 1 RESULTS PLNRSTAGE LAYERMIN 4 RESULTS PLNRSTAGE LAYERMAX 4 RESULTS PLNRSTAGE END *PLNRFRAC 'Template_I_Direction' 298,262,4 *BG_NAME 'Well 1 - Frac 1' *PLNRFRAC 'Template_I_Direction' 298,268,4 *BG_NAME 'Well 1 - Frac 2' *PLNRFRAC 'Template_I_Direction' 298,275,4 *BG_NAME 'Well 1 - Frac 3' *PLNRFRAC 'Template_I_Direction' 298,281,4 *BG_NAME 'Well 1 - Frac 4'

Template Appli cation Block Group

Setup Comparison What does this imply? Well with 4 stages:

Old: New:

~ 9500 lines of refinements ~ 5600 lines of property specif

31 Lines

Fast Saving Fast Loading

Fast Generation

Block Groups Make Life Easier Refinements, permeability alterations, and non-Darcy flow corrections done automatically by simulator With Block Group definitions, apply additional properties to fractures: •

Relative Permeability Tables

•

Rock Types / Compaction Tables

•

Initial Saturations

•

Etc.

Define Block Groups by Dual Permeability Systems •

Matrix

•

Natural Fractures

Hydraulic Fractures •

Main Fracture Conduit (Fractured Zone)

•

Enhanced Near-Fracture Region (Non-Fractured Zone)

Converting Old Datasets • Builder and Results 3D views are the same as before • Old datasets run with new simulator  ─  No Conversion Required

• Old datasets can be converted to new syntax using Builder (automatically when saved)  ─  May be easier and faster to work with

Workflow Demo

What is CMOST?

• Better understanding • Identify important parameters

• Calibrate simulation model with field data • Obtain multiple history-matched models

• Improve NPV, recovery, etc. • Reduce cost

• Quantify uncertainty • Understand and reduce risk

Easily Vary Propped Frac Properties & SRV Size Propp ed Frac Properties: Half-length, Width, Perm, Spacing, Height & Perm Gradient Stimulated Natural Frac Properties: Width, Perm

SRV Size & Shape: • • • •

# MS events per gridblock MS Moment Magnitude MS Confidence Value Etc.

How is it Done? CMOST uses Master Datasets to specify parameters to be altered • Datasets with CMOST keyword strings

Files can be created: • Manually • Through CMOST (CMM Editor) • Through Builder

Parameterization With CMOST

Physics-based EUR’s History-Match Run Progress Plot

Engineer only has to monitor HistoryMatch progress……and so is free to work on other projects while CMOST does the rest!

Physics-based Optimization Cum Oil & NPV after 30 years vs # of Wells 6.00e+6 Cumulative Oil SC OPT_1 Well Cumulative Oil SC OPT_3 Wells Cumulative Oil SC OPT_5 Wells Cumulative Oil SC OPT_7 Wells Cumulative Oil SC OPT_9 Wells

5.00e+6

NPV (MMUSD) 13.0 39.0 64.6 85.3 80.7

# of Wells 1 3 5 7 9

   ) 4.00e+6    l    b    b    (    C    S    l    i    O3.00e+6    e    v    i    t    a    l    u    m    u    C2.00e+6

100 1.00e+6

0.00e+0 2015

2020

2025

2030

Time (Date)

2035

2040

2045

   D 80    S    U    M 60    M  , 40    V    P 20    N 0 1

3

5 # of Wells

7

9

Benefits of Reservoir Simulation Understand and predict tight & shale well production • Reservoir heterogeneity • Well complexity • Physics of fluid flow & heat flow • Geomechanics • Geochemistry

Enable “physics-based” analysis and optimization of tight & shale plays in an efficient manner, when using CMOST: • EUR Calculation & Validation • Well Completion Design Optimization • Well Spacing Optimization

Tight & Shale Reservoir Modelling: Challenges • Lack of PVT data in Shale Liquids plays • Lack of BHP data • Shale reservoir property measurement is uncertain, costly & time-consuming • Microseismic data acquisition and analysis is not well understood or accepted • Frac Treatment design software lacks proper modelling initiation and propagation of naturally fractured rocks

Tight & Shale Reservoir Modelling: Challenges • Costly to acquire reservoir rock geomechanical properties and initial stress states • Not enough Reservoir Engineers: • To conduct physics-based reservoir modelling work • Are cross-trained in Production/Well Completions Technology and/or Geomechanics

• Technology discipline silos inhibit learning between companies and even within companies

Tight & Shale Reservoir Modelling: Opportunities • Constrain reservoir parameters using known relationships between natural frac geometry, width, perm & density • These should not be independent variables

• Constrain rock-physics relationships • Rel perm & cap pressure should not be independent functions

• Natural fracture characterization via Discrete Fracture Network (DFN) modelling

Tight & Shale Reservoir Modelling: Opportunities • Correlate Seismic Attributes & Microseismic analysis with “Fracability” • Monitor production using Distributed Temperature Sensors & Tracer Surveys • Incorporate production logging data into reservoir simulation history matching

• Predict optimum well locations and design multiple coincident well treatments using Geomechanics • E.g. Simultaneous Fracs like Zipper Fracs

Tight & Shale Reservoir Modelling: Lessons Learned Statistical Analysis of “early time rates” and “unqualified EUR’s” can lead to new oilfield “myths” that incorrectly become “rule of thumb” • 30-day, 90-day, 180-day rate versus cumulative well plots that aren’t normalized for flowing pressure (BHP or WHP) and for “effective” propped fracture parameters are very misleading • EUR versus cumulative production plots can be even more misleading given the uncertainty with which EURs are generally being determined using analytical-solution based production decline analysis methods

Tight & Shale Reservoir Modelling: Lessons Learned Reservoir Simulation can also be misleading if model design and physics is not appropriate for the problem at hand • Shale well models that don’t use Logarithmically-Spaced grids yield misleading results •

Similar to models that don’t use radial grids around wells to model pressure transient tests

•

Those models cannot properly model transient inflow performance behavior (IPRs)

Effect of Not Using LS-LR-DK Grids Simple DK approach cannot model the initial transient correctly because the grid blocks are too large! Well-1 shale gas model constant perm fcd 60.irf  3,000

Well Bottom-hole Pressure shale gas model_constant perm_fcd_60.irf  Well Bottom-hole Pressure Shale Gas Model_Simple DK.irf 

2,000    )    i   s   p    (   e   r   u   s   s   e   r    P   e 1,000    l   o    h     m   o    t    t   o    B    l    l   e    W

0

Companies using CMG to Model Unconventional Reservoirs 90

16

14

Canada

USA

80

ROW

70

12

60

   S 10    R    E    M    O 8    T    S    U    C    W 6    E    N

50 40 30

4

20

2

10

0

0 2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

   h    t   w   o   r    G   r   e   m   o    t   s   u    C   e   v    i    t   a    l   u   m   u    C

2014 SPE Papers featuring CMG Reservoir Simulation Technology • 216 papers • 54 Unconventional, Tight or Shale, including 6 on Gas Injection EOR

Why use CMG for Modelling Tight & Shale Plays? 1. CMG has the physics required to understand and forecast production from Unconventional Wells & Reservoirs 2. Import geologic models from geologic modelling software to jump-start your modelling workflows 3. Add planar, complex or mixed geometry propped and stimulated natural fractures to your models 4. Use microseismic data in the model building process

Why use CMG for Modelling Tight & Shale Plays? 5. Add only the LGR required to model transient flow from matrix to fractures 6. Easily and efficiently build single and multi-well models 7. Parameterize matrix & fracture properties & dimensions when doing history-matching & optimization, • No limitations to only a few half-lengths, spacings, etc. • No need to manually pre-create

8. CMG’s track record of continually enhancing our capabilities and workflows for Unconventional Wells & Reservoirs

Training

• Register for courses on www.cmgl.ca/training • Available at worldwide CMG offices or on-site • All skill levels • Contact: [email protected]