modelling hydralic frac - ian gates u of c

25
Modelling hydraulic fracturing and new insights for increased recovery Ian D. Gates ([email protected] ), Nancy Chen, Ron Wong, Jacky Wang, Xuemin Huang, Mahta Sadeghvishkaei, Belladonna Maulianda Dept. of Chemical and Petroleum Engineering Schulich School of Engineering University of Calgary 1

Upload: dangdan

Post on 14-Dec-2016

215 views

Category:

Documents


1 download

TRANSCRIPT

Page 1: Modelling Hydralic Frac - Ian Gates U of C

Modelling  hydraulic  fracturing  and  new  insights  for  increased  recovery  

Ian  D.  Gates  ([email protected]),  Nancy  Chen,  Ron  Wong,  Jacky  Wang,  Xuemin  Huang,  Mahta  Sadeghvishkaei,  Belladonna  Maulianda  

 Dept.  of  Chemical  and  Petroleum  Engineering  

Schulich  School  of  Engineering  University  of  Calgary  

1  

Page 2: Modelling Hydralic Frac - Ian Gates U of C

IntroducMon  

§  Modelling  Hydraulic  Fracturing  is  Difficult  –  the  Physics  involves  MulMphase  Fluid  Flow,  ParMcle  Transport,  Geomechanical  DeformaMon,  Rock  Fracturing,  ParMcle  Embedment,  Temperature  Changes,  …  

§  AnalyMc  Models  such  as  PKN  and  KGD  are  simplisMc  and  have  severe  assumpMons  

§  At  this  point,  very  few  reservoir  simulaMon  based  models  have  predicMve  capability  that  can  be  calibrated  and  run  rapidly  

§  Highlight  today  some  of  our  modelling  and  experimental  acMviMes  

Page 3: Modelling Hydralic Frac - Ian Gates U of C

Four  Thrusts  of  Current  Research  

1.  Simple  Reservoir  SimulaMon  Models  for  Hydraulic  Fracturing  using  the  Quad  Model  –  these  models  approximate  matrix  +  natural  fracture  system  as  conMnuum  §  Rich  in  MulMphase  Flow  Physics,  Lean  in  Geomechanics  

2.  Geomechanical  Finite  Element  Analysis  Models  with  Fluid  Invasion  §  Rich  in  Geomechanics,  Lean  in  Fluid  Flow  (Single  Phase  Only)  

3.  GeostaMsMcal  Geomechanical  Models  §  The  beginnings  of  integrated  MulMphase  Flow  and  Complex  

Geomechanics  

4.  MulMphase  Flow  in  Fractures  and  Gaps  §  Experiments  –  insights  for  mulMphase  flow  

Page 4: Modelling Hydralic Frac - Ian Gates U of C

Most often used in steam fracturing in Cyclic Steam Stimulation (Beattie-Boberg McNab 1991) Porosity depends on Pore Pressure; Permeability depends on Porosity –

thus Permeability depends on Pore Pressure

Simple Dilation-Recompaction Model:

Dynamic Fracturing – Quad Model

Page 5: Modelling Hydralic Frac - Ian Gates U of C

•  1400 m long horizontal well at depth equal to 2835 m •  Hydraulic fracturing - 18 stages •  Water based fracturing fluid plus nitrogen plus proppants •  Initial reservoir pressure: 37,000 kPa •  Fracturing pressure: 48,000 kPa •  Injection bottom hole pressure: 60,000 kPa Reservoir Properties - heterogeneous model: •  Average Permeability: 1.7 mD; Std. Dev. 0.17 mD •  Average Porosity: 0.08; Std. Dev. 0.008 •  Compressibility: 10-6 1/kPa

•  Two Stages •  For Injection, do Time Stretch (Scale Hydraulic Fracturing

Operation to Occur Over Simulated Days rather than Minutes) •  No Time Stretch done for Production

Case Study

Page 6: Modelling Hydralic Frac - Ian Gates U of C

•  Pure Prediction Mode – all data taken from logs, core, literature data •  Porosity Evolution

Case Study

Page 7: Modelling Hydralic Frac - Ian Gates U of C

•  Pure Prediction Mode – all data taken from logs, core, literature data •  Permeability Evolution

Case Study

Page 8: Modelling Hydralic Frac - Ian Gates U of C

•  Oil Production

Case Study

Page 9: Modelling Hydralic Frac - Ian Gates U of C

•  Pure Prediction Mode – all data taken from logs, core, literature data •  Oil Saturation Evolution – at end pressure drive depleted

Case Study

Page 10: Modelling Hydralic Frac - Ian Gates U of C

•  Use fluid invasion into rock to understand stress and pressure evolution in reservoir rock

•  Use Abaqus – a finite element analysis package that supports fluid injection into porous media

•  Simple model for now – linear elastic rock + Forchheimer modification of Darcy`s law for Fluid

•  Size of Stimulated Reservoir Volume (SRV) constrained by Microseismic Data

•  Glauconite Formation, Hoadley Field, Alberta •  From analysis can estimate nature of fractured rock in SRV

Finite Element Analysis

Injection Port

Page 11: Modelling Hydralic Frac - Ian Gates U of C

•  Evolution of Pore Pressure

Results

Prior to Run

Initial Condition

After 1 s

After 552 s

After 1102 s

After 2250 s •  To match bottom hole pressure, SRV effective permeability = 22.3 D

Page 12: Modelling Hydralic Frac - Ian Gates U of C

Maximum Horizontal Stress

Results Minimum Horizontal Stress

Minimum Horizontal Stress

From pressure and flow rate, can back out an interpretation of the fractures created during hydraulic fracturing To match 22.3 D, one realization: 1.46 mm, major fractures = 4 with spacing 14.8 m, minor fractures = 12 with spacing 14.5 m

Page 13: Modelling Hydralic Frac - Ian Gates U of C

•  Construct detailed heterogeneous 3D earth models of reservoir rock including flow and geomechanical properties and state of stress

•  Surface to Understrata Model •  Investigating state of stress in the Montney Formation at Initial State

(Pre-Hydraulic Fracturing)

•  Model from 500 m to 3500 m, 15 km x 15 km area

Geostatistical Geomechanical Models

Page 14: Modelling Hydralic Frac - Ian Gates U of C

Wells positions used in this study (from Accumap, 2014) Wells highlighted by the radial spokes had GR and RHOB log data Wells with the box also had sonic log data.

Sonic logs Sonic logs

Sonic logs

Sonic logs

Source Data – Montney Formation

Page 15: Modelling Hydralic Frac - Ian Gates U of C

Data

15  

Well No.   UWI  DTC/DTS

LOGS   GR LOG   RHOB LOG  

1   09-22-063-03W6        

2   09-30-063-04W6        

3   05-31-063-04W6        

4   16-34-063-05W6        

5   04-35-063-05W6        

6   01-06-064-03W6        

7   12-07-064-03W6        

8   09-05-064-04W6        

9   04-09-064-04W6        

10   09-12-064-04W6        

11   12-14-064-04W6        

12   11-18-064-04W6        

13   09-23-064-04W6        

14   08-29-064-04W6        

15   11-09-064-05W6        

16   02-28-064-05W6        

17   12-20-063-04W6        

18   06-24-063-05W6        

Summary of available well data for constructing the mechanical earth model (dark color indicates data exists)

Page 16: Modelling Hydralic Frac - Ian Gates U of C

Comparison of UCS estimated from Sonic Logs to Core Mechanical Data

16  

Blue  line  is  UCS  from  sonic  log  Points  are  core  data    

Page 17: Modelling Hydralic Frac - Ian Gates U of C

From 500 m Down

17  

Lithology BEARPAW BELLYRV WAPIABI COLRAD MUSKIKI CARD CARDSD KASKAPAU 2WSPK DPECK SHAFTBR BFSC PEACERV FALHBSD FALHCSD FALHDSD FALHESD WILRICH BLUSKY GETH CADOMIN FERNIE MONTNEY CHARLK DOIG BELLOY DEBOLTL

Page 18: Modelling Hydralic Frac - Ian Gates U of C

3D Earth model

18  

Porosity (%)

Density (g/cm3)

Page 19: Modelling Hydralic Frac - Ian Gates U of C

3D Earth model – Poisson’s ratio

19  

Page 20: Modelling Hydralic Frac - Ian Gates U of C

20  

09-­‐30-­‐063-­‐03W6  

Long  Name   Short  Name   TVD  (m)   MD  (m)  

BELLY  RIVER   BELLYRV   942.0   942.0  PUSKWASKAU   PUSKWSK   1278.8   1278.8  COLORADO   COLRAD   1378.6   1378.6  BADHEART   BADHRT   1482.6   1482.6  MUSKIKI   MUSKIKI   1497.6   1497.6  CARDIUM   CARD   1540.0   1540.0  

CARDIUM  SAND   CARDSD   1559.0   1559.0  KASKAPAU   KASKAPAU   1604.2   1604.2  DUNVEGAN   DUNVG   1964.9   1964.9  SHAFTESBURY   SHAFTBR   2063.4   2063.4  

BASE  OF  FISH  SCALES   BFSC   2126.3   2126.3  PADDY   PADDY   2199.5   2199.5  

CADOTTE   CADOTT   2212.2   2212.2  HARMON   HARMON   2238.4   2238.4  NOTIKEWIN   NOTIK   2248.4   2248.4  

FALHER  A  SAND   FALHASD   2276.1   2276.1  FALHER  B  SAND   FALHBSD   2315.2   2315.2  FALHER  C  SAND   FALHCSD   2334.8   2334.8  FALHER  D  SAND   FALHDSD   2386.8   2386.8  FALHER  E  SAND   FALHESD   2454.7   2454.7  

WILRICH   WILRICH   2476.7   2476.7  BLUESKY   BLUSKY   2532.5   2532.5  GETHING   GETH   2556.1   2556.1  CADOMIN   CADOMIN   2651.7   2651.7  NIKANASSIN   NIKANSN   2670.2   2670.2  

FERNIE   FERNIE   2716.2   2716.2  NORDEGG   NORD   2792.6   2792.6  

CHARLIE  LAKE   CHARLK   2816.3   2816.3  MONTNEY   MONTNEY   2864.3   2864.3  

3D Earth model – Young’s modulus (GPa)

Page 21: Modelling Hydralic Frac - Ian Gates U of C

•  Oil-water co- and counter current flow in thin gaps (both smooth and rough) – atmospheric pressure system

•  With and without surfactants •  If funding arrives, will expand to look at fate of particles in flow

Flow in Fractures

Can configure in horizontal or vertical arrangement with co- and countercurrent flow

Page 22: Modelling Hydralic Frac - Ian Gates U of C

•  Examining phase interference and interface development

Results

Page 23: Modelling Hydralic Frac - Ian Gates U of C

•  Examining phase interference and interface development

Results

Page 24: Modelling Hydralic Frac - Ian Gates U of C

Final Remarks •  Quad Model can model dynamic fracturing process to create fracture network and

fractured zone •  Quad Model does not create fractures but reflects impact of fractured zone (or

fracture rock network) on formation properties •  Oil flow dynamics suggest that gas injection (cyclic) may have benefit as drive/

displacement process as seen in CSS

•  Finite element analysis provides tools to understand potential configurations of fracture networks in reservoir rock and interaction of hydraulic and natural fractures

•  Mechanical stratigraphy provides a framework to compare formations and it can be described by standard log-based measurements such as the rock density, sonic velocity, and GR

•  Variability of mechanical properties implies that they may be optimum well placement for HF – work is ongoing on this at this point

•  Experiments reveal hysteresis of relative permeability – need to be used in HF simulations – HF = re-saturation/saturation as invasion / oil in flow occurs

•  Work in progress – stay tuned

Page 25: Modelling Hydralic Frac - Ian Gates U of C

Acknowledgements

•  Seven Generations •  NSERC •  Accumap •  Schlumberger •  Computer Modelling Group