closing the loop between geology and reservoir engineering

7/26/2019 Closing the Loop Between Geology and Reservoir Engineering

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Closing the Loop between Geology and Reservoir Engineering in the Building, Calibration, and History-Matching

of Carbonate Reservoir Models*

Patrick Corbett1

Search and Discovery Article #41485 (2014)**Posted November 10, 2014

*Adapted from 2013-2014 AAPG Foundation Distinguished Lecture. Please refer to related article by the author, Search and Discovery Article #41484 (2014).

**Datapages © 2014 Serial rights given by author. For all other rights contact author directly.

1BG Group Professor, Carbonate Petroleum Geoengineering, Heriot-Watt University, Edinburgh, UK ( [email protected] )

Abstract

It is quite common for reservoir engineers to adjust the geological modelling without recoursing to the geologists by multiplying the porosity,

the permeability, the anisotropy (kv/kh), the relative permeabilities, the well factors and many other parameters within their numerical world.Sometimes these factors can be large and global and probably outside the limits of the geological reality. Of course it is not easy to go back and

make these adjustments in a close cooperative environment for all sorts of reasons – logistical, technical, management, contractual to name afew. Rarely are these adjustments discussed and certainly there are very few published examples where the loop has been closed. This article

attempts to illustrate where and how multipliers are applied, what might be the reasons and how the workflows could be streamlined to makeclosing-the-loop a routine process rather than an occasional occurrence.

Selected References

Barnett, A.J. V.P. Wright, and M. Khanna, 2010, Porosity evolution in the Bassein Limestone of Panna and Mukta fields, offshore Western

India: Burial corrosion and microporosity development: Search and Discovery Article #50326 (2010). Website accessed October 30, 2014.(http://www.searchanddiscovery.com/pdfz/documents/2010/50326barnett/ndx_barnett.pdf.html

).

Chandra, V., H. Hamdi, P.W.M. Corbett, and S. Geiger-Boschung, 2011, Improving reservoir characterisation and simulation with near well bore modelling: SPE 148104, SPE Reservoir Characterisation and Simulation Conference, October, Abu Dhabi, 14 p.

Chandra, V.S.S., P.W.M. Corbett, S. Geiger-Boschung, and H. Hamdi, 2013, Improving reservoir characterization and simulation with near-wellbore modeling: SPE Reservoir Evaluation and Engineering, v. 16/2, p. 183-193.

http://www.searchanddiscovery.com/documents/2014/41484corbett/ndx_corbett.pdf



mailto:[email protected]


http://www.searchanddiscovery.com/pdfz/documents/2010/50326barnett/ndx_barnett.pdf.html








Chandra, V., S. Geiger-Boschung, P.W.M. Corbett, R. Steele, P.Milroy, A. Barnett, P.V. Wright, and P. Jain, 2013, Using near well bore

upscaling to improve reservoir characterization and simulation in highly heterogeneous carbonate reservoirs: SPE 166033, SPE ReservoirCharacterisation and Simulation Conference and Exhibition, Abu Dhabi, 14p.

Chandra, V.S.S., A. Barnett, P.W. Wright, R. Steele, S. Geiger-Boschung, P.W.M. Corbett, and P. Milroy, 2014, Novel near wellbore rock-typing and upscaling workflow to improve reservoir characterisation and modelling of carbonates: 76th EAGE Conference and Exhibition,

Amsterdam, 5p.

Chandra, V., P. Wright, A. Barnett, R. Steele, P. Milroy, P.W.M. Corbett, S. Geiger and A. Mangione, 2014, Evaluating the impact of a late

burial corrosion model on reservoir permeability and performance in a mature carbonate field using near wellbore upscaling, in FundamentalControls on Fluid Flow in Carbonates: Current Workflows to Emerging Technologies: Geological Society (London) Special Publication v. 406.

Esteban, M., and C. Taberner, 2003, Secondary porosity development during late burial in carbonate reservoirs as a result of mixing and/or

cooling of brines: Journal of Geochemical Exploration, v. 78-79, p. 355-359.

Kazemi, A., P.W.M. Corbett, and R.A. Wood, 2012, New approach for geomodeling and dynamic calibration of carbonate reservoirs using porosity determined system (PODS). Presented at 74th EAGE conference and Exhibition, Copenhagen, Denmark, 4-7 June 2012.

Oates, M., and V.S. Chandra, 2013, Evaluating the role of meteoric karst vs burial corrosion in an offshore Indian Carbonate Field (abstract):

AAPG Convention and Exhibition, Pittsburgh, PA, Search and Discovery Article #90163 (website accessed October 30, 2014)

(http://www.searchanddiscovery.com/abstracts/html/2013/90163ace/abstracts/o.htm).

https://pureapps2.hw.ac.uk/portal/en/persons/sebastian-geigerboschung(b842f01b-b07d-4da7-aa81-300e092af039).html

https://pureapps2.hw.ac.uk/portal/en/publications/novel-near-wellbore-rock-typing-and-upscaling-workflow-to-improve-reservoir-characterisation-and-modelling-of-carbonates(cf1c3822-d795-49a5-b0d1-827611fcf55e).html


http://www.searchanddiscovery.com/abstracts/html/2013/90163ace/abstracts/o.htm







Closing the Loopbetween geology & reservoir engineering

in building, calibration and history-matchingof carbonate reservoir models

Patrick Corbett

BG Group ProfessorCarbonate Petroleum Geoengineering

AAPG Distinguished Lecture May 2014



Fractured or not?

Reservoir Engineering – YES >>> NO

Well test response

Negative skin >> not fractures >> double matrixCross-flow >> not fractures >> double matrix

Geology – NO

No fractured core

No open fractures on image logs

No significant losses



Fractured or not?

Reservoir Engineering – YES

Well test response

Negative skin >>>> double matrix + fracturesCross-flow >>>> double matrix + fractures

Geology – YES

Fractured core

Open fractures on image logs

Significant losses



Closing the loop

Highly heterogeneous carbonate reservoirs

Fractured vs non-fractured well tests?

Build a model without fracturesCare to distribute RTs appropriately

Check History Match without fractures

Not conclusive but potentially usefulRole for PLTs



Dual porosity

Horizontal well

Closely bounded reservoir

Negative skin

Horizontal well

Dual porosity

Rectangular bounded

Negative skinHorizontal well

Dual porosity

Infinite boundary

Small positive skin

Dual porosity

Vertical well

Negative skin

A2

0.01 1.0 100

Time, hr

1 E + 6

1 E + 7

G a s p o t e n t i a l , p s i a / c pA1

A3 A4

0.1 10 1000

Time, hr

1 E + 6

1 E + 7

G a s p o t e n t i a l , p s i a / c p

0.1 10 1000

Time, hr

1 E + 6

1 E + 7


0.1 10 1000

Time, hr

1 0 0

1

0 0 0

P r e s s u r e ,

p s i a

Fracture performance of well test??

Kazemi et al, 2011



Composite log

Layer 2

Layer 3

Layer 4

Prograding ramp facies with higher frequency cycling

Layer 1

Kazemi

et al, 2011



11020 200 290 370 460 550 640

W e l l b o t t o

m h o l e p r e s s u r e ,

p s i a

A4

A3

A2

A1

Time, day

Kazemi et al, 2011



11020 200 290 370 460 550 640

11020 200 290 370 460 550 640

A1

A2

A3

A4

W e l l

g a s p r o d u c t i o n r a t e ,

M M

s m 3 / d a y

W e l l o i l p r o d u c t i o

n r a t e ,

s m 3 / d a y

Time, day

Time, day Kazemi et al, 2011



Facies Model

Simple depositonal model – with dolomite modification>>>PODS

Kazemi

et al, 2011



Well Location in Facies Model

Interdigitation of Mid- to Outer- Ramp facies

From Simpson, 2010

Low Porosity

Intragranular Porosity

Foraminiferal Packstone

Higher Inter XL Porosity

Higher Permeability

Un-dolomitised

Strong primary control

on property distribution

Dolomitised

Kazemi

et al, 2011



Review of H Field Rock Types

0.001

0.010

0.100

1.000

10.000

100.000

0.00 0.05 0.10 0.15 0.20 0.25 0.30

P e r m e a b i l i t y m D

Porosity

L1

L2

L3

L4

0.001

0.010

0.100

1.000

10.000

100.000

0.00 0.05 0.10 0.15 0.20 0.25 0.30

P e r m e a b i l i t y m D

Porosity %

H1

H2

H3H4

0.001

0.010

0.100

1.000

10.000

100.000

0.00 0.05 0.10 0.15 0.20 0.25 0.30

P e r m e

a b i l i t y

Porosity

GB

GN

GPB

GPN

MWB

MWT

By facies?0.01

0.1

1

10

100

0 0.05 0.1 0.15 0.2 0.2

By well?

By layer?

By RRT?By GHE?

Simpson, 2010

How do we distribute

properties?

From full field model?

Kazemi et al, 2011



Composite log

Layer 2

Layer 3

Layer 4

Based on given Log Porosity

H Field – Well H2

NB: “super-k >16%F >40mD?

GHE Proportion

Curve

GHE Grouping

Layer 2U

Layer 2L

Layer 1

Use GHE grouping approach

Kazemi

et al, 2011



H Field Model



Distribution of Rock Types

Kazemi et al, 2011



Cell dimension (m): 100X100X1

Total number of cells: 95760

Local grid refinement: 5X5X3

Porosity

Permeability

Simulation Model

Kazemi

et al, 2011



Horizontal correlation length, m

V e r t i c a l c o r r e l a t i o n l e n g t h ,

m

1000500100

1

3

6

PODS Distribution lengths

Kazemi

et al, 2011



SHORT CORRELATION

LONG CORRELATION

Example Models

Kazemi et al, 2011



Kv/Kh<>0

Kv/Kh= 0

Short correlation length Long correlation length

Bars

Vertical Permeability

Kazemi et al, 2011



Short correlation lengthLong correlation lengthHomogenous model

G a s p o t e n t i a l

Time, hr

Numerical Well Tests

Kazemi et al, 2011



H100V1 H1000V6

Short correlation length vs. long correlation length

Numerical PLT

Kazemi et al, 2011



Porosity

PermeabilityShort correlation length

Long correlation length

Full Field Model

Kazemi et al, 2011



Full fieldSector modelShort correlation

Full Field vs Sector Model

Kazemi

et al, 2011



Sector model

Full field model

Short correlation length Long correlation length

Bars


Kazemi et al, 2011



Short correlation lengthLong correlation lengthShort correlation length, field

G a s p o t e n t i a

l

Time, hr

Long correlation length , field


Kazemi et al, 2011



Short correlation lengthLong correlation length

G a s p o t e n t i a l

Time, hr

sector Full field GHE

long

GHE

Short

Next stage:PLT and WT history matching

Kazemi et al, 2011



Poroperm data and effective RT’s



PC and Saturation Height

0

5

10

15

20

25

30

0.0 0.2 0.4 0.6 0.8 1.0

H e i g h t ( m ) a b o v

e F W L

Water Saturation

Capillary Pressure Data

Plug 1 (Por:=18.7%)

Plug 2 (Por: =14.4%)

Plug 3 (Por: 12.4%)

0

5

10

15

20

25

30

0.0 0.2 0.4 0.6 0.8 1.0

H e i g h t ( m ) a b o v e F

W L

Water Saturation

Saturation Height Modelling

GHE2

GHE4

GHE5



Well H2

Petrotype Model Calibration

Layer 2

Layer 4

Layer 3

2U

2L



Porosity Permeability

Full Field RT based poroperm scenarios

Kazemi et al, 2011



Porosity Permeability

Full Field RT-based poroperm scenarios

Kazemi

et al, 2011



Days

G a s p r o d u c t i o n r a t e

O i l p r o d u c

t i o n r a t e

History

History Match – Gross Production

Kazemi

et al, 2011



1 11 1 1 1 1 1

A1

A2

A4A3

Time, hr

P r e s s u r e

History

R a

t e

P r e s s u r e

R a t e

6000 8000 10000 12000 14000 3000 4000 6000 8000 10000

400 600 8000 1000 12001000 3000 5000 7000 9000 1400 1600

12000 14000 16000

History

History

History

History Match - Pressure

Kazemi et al, 2011



A1

A2

1 E + 6

1 E + 7


1 E + 8

1 E + 6

1 E +

7


1 E + 8

1E-3 0.1 10 1000

1E-3 0.1 10 1000

Time, hr

History Match – well rate

Kazemi et al, 2011



1

1

1

1

A3

A4

1

E + 7


1 E + 8

1

1 0

P r e s s u r e ,

p s i a

1E-3 0.1 10 1000

1E-3 0.1 10 1000

1E-3 0.1 10 1000

History Match – Well rate

Kazemi et al, 2011



A2

A1

1 E + 7

1 E + 8


1 E + 6

1 E + 7


1E-3 0.1 10 1000

1E-3 0.1 10 1000

Time, hr

Model WT match

Kazemi et al, 2011



Atlernative match option

Kazemi et al, 2011



• Applied a new modelling strategy based on PODS –

Porosity Defined System for a carbonate reservoir.

• The effect of horizontal and vertical correlation length of

PODS observed on WT response.

• Matching WT and PLT data in sector before going to full

field modelling

• Sector model and full field model compare well

• WT and PLT Calibration of full field model• Reasonable match achieved without incorporating any

fractures

H Field study conclusions



SPE 166033: Using Near Wellbore Upscaling

to Improve Reservoir Characterization andSimulation in Highly Heterogeneous

Carbonate Reservoirs

V. Chandra1,2, S. Geiger 1,2 , P.W.M. Corbett1,2,4,R. Steele3, P. Milroy3 , A. Barnett3 , P. Wright3 , P. Jain3

1Institute of Petroleum Engineering, Heriot-Watt University2International Centre for Carbonate Reservoirs

3BG Group, Reading, U.K.4 Universidade Federal do Rio de Janeiro

Acknowledgements:



Key points of this research

Overall aim

Using novel near wellbore upscaling (NWU) workflow to obtain

improved permeability model of Field X

Main conclusions

Improved characterisation of key small-scale geological

heterogeneities

Revised permeability model eliminated the K-multipliers

Scientific impact

Improved reservoir characterisation and simulation of

carbonates using NWU workflow

Chandra et al, 2012



Low relief anticline trap

Thin oil rim, gas cap, deep-seated aquifer

Main HC-bearing layers: Zone A, Zone B

Field X Background

E-W section: see gas over oil over water. See the two main reservoir

layers (Image courtesy: Zoe Watt)

A/B Unconformity

Chandra et al, 2012



Field X Production Profiles:

Oil, Gas and Water

Chandra et al, 2012



Re-evaluating Field X Permeability

- DST K-transform >> core K-transform

- Average K in geomodel ~ 20 mD and Ke in

simulation model ~ 200 mD

ØWhat was undersampled?

ØHow should it be modelled?

Kh-multiplier required for history match : x20 in Zone A, x10 in Zone B

Plus local well K and well PI multipliers

Around 90% of the permeability missing !?

Correct the K = Better Simulation Model = Better Production Forecast



Removing the K-multiplier

C a n b e r e s o l v e d u s i n g

r e v i s e

d K - m o d e l ?

All K-multipliers

removed

History matched case

with K-multipliers

Chandra et al, 2012



Evaluating the Role of Meteoric Karst vs Burial Corrosion

in an Offshore Indian Carbonate Field

Michael Oates

Viswa Santhi Chandra

Patrick Corbett



Outline

Field G overview

Evidence of late burial corrosion

Impact on poropermKey conclusions

Oates et al, 2012



Ramp foraminifera facies

Depositional Facies

Coskinolina

1000 μm

Miliolids

1000 μmCoskinolinids and

Alveolinids

1000 μm

Platy corals

1000 μm

Fine bioclastic Hash

with Rotalid forams

1000 μm

Fine bioclastic Hash with

Echinoderm debris

1000 μm

Nummulitids

1000 μm

Discocyclinids

1000 μm

Oates et al, 2012



“Cold Karst” ?

Meteoric karstic porositydevelopment caused the

conduits?

Diagenesis vs Permeability concepts

Indication of dissolution

porosity

Solution enhanced stylolites

and associated fractures in

well cores

— Evident high perm network, pervasive

and “stratiform”

— Long producing data and tracer data

indicating good lateral and verticalcommunication in reservoir

— The dissolution porosity +stylolites

+associated fractures are the pervasive

permeability network ?

“Hot Karst” ?

Late stage (hydro)thermalkarstification could have

formed the conduits?

Oates et al, 2012



Proposed Paragenetic Sequence

Transpressional tectonics at

the end of Miocene

Early stageà extensive microporosity

Late stageàmacroporosity along fractures, unconformities, vertical pipes

Corrosive fluids penetrated the

unloaded dissolution seams and

stylolites – predating the HC charge

Unloading event

Depositional setting:

Ramp setting

Transgressive stacking patterns

Cementation

+Compaction+Pressure dissolution

=

Very tight carbonate units

ü Very common

ü Associated with late

carbonate cementscalcite

dolomite

ankerite

siderite

Dissolution seamsStylolites

Tension gashes

Oates et al, 2012

l ld l



Burial Corrosion- Field Scale

(Modified from Esteban)

Oates et al, 2012



Burial Corrosion- Field Scale

(Modified from Barnett et al . 2010)

Oates et al, 2012



Corrosion along Stylolites and SAF

Corrosion vs Stylolite Correlation

Density of distribution of corroded zones is proportional to that of stylolites.

2 cm

Oates et al, 2012



Corrosion fluid

front

Corrosion fluid

front

Invasion of Corrosiv

Fluids

Corrosion enhanced porosity



Burial Corrosion Mechanism at Core Scale

Oates et al, 2012



Post-Saddle Dolomite Dissolution

Fractures with leached bladed calcite

cement, saddle dolomite and dickite

Saddle

dolomite

Bladed

calcite

cement

Dickite

Saddle dolomite in a fracture has

undergone corrosion followed by

dickite precipitation

Dickite

Corroded saddle dolomite

0.5 mm 0.5 mm

Oates et al, 2012



Dissolution of Tectonic Vein-filling

Calcite

Corroded calcite cement in a fracture

0.5 mm

Oates et al, 2012



Dickite and Pyrite

ü Dickite is not common in

carbonate reservoirs in general

ü BUT it is a very common

mineral phase in Field G

Deeply etched stylolites

and associated fracturespyrite nodules this

size (up to 10mm

across) are rare

Dickite is a kaolin mineral thought to indicate the

former activity of organic-rich acidic fluids

Oates et al, 2012



Highlights: Diagenetic Features

(Courtesy Paul Wright

Oates et al, 2012



Highlights: Diagenetic Features

2 cm

(Courtesy Paul Wright

Oates et al, 2012



Key Observations from Core

Key Characteristics of Corroded Zones:

- Higher porosity

- Higher miniperm

- Dark patches of highly conductive zones on image logs

- High Uranium signature

R1= unmodified limestone matrixR2= corroded matrix

Oates et al, 2012



Corrosion Enhanced Porosity

Collapse breccia porosityVuggy/Moldic porosity Corrosion along Stylolites and SAF

BSEM images of typical corroded matrix with

microporosity

2 cm

Oates et al, 2012



Reservoir Permeability Issues

- DST K- transform >> core K- transform

- Average K in geomodel ~ 20 mD and Ke in

simulation model ~ 200 mD

ØWhat was undersampled?ØHow should it be modelled?

Core and miniperm data

Sample insufficiency

Sample bias towards tighter zones

K-multiplier required for History match :

x20 in A Zonex10 in B Zone

Plus local well K and well PI multipliers

Around 90% of the permeability ‘missing’ !?

Correct K = Better Simulation Model = Better Production Forecast

Oates et al, 2012



Key Conclusions

Distribution of high permeable corroded zones

correlated with stylolites+fractures

Evidence supports the occurrence of thermal

karstification causing stratiform pervasive highpermeable network

The reservoir permeability model should be

improved with considerations to late burial

corrosion

Oates et al, 2012



Near wellbore rock-typing and upscaling

GeoRT NWRTNWRTàCm-dm scale models

àFlow-based upscaling

Upscaled poroperm

Kv/Kh vs Kh correlation

GeoPoDSGeoPoDS

Chandra et al, 2014



Core vs upscaled permeability

Corroded

matrix

porosity

Leached

stylolites and

tension gashes

in highly

Corroded matrix

Chandra et al, 2014



Poroperm trends used for GeoPoDS

Chandra et al, 2014



J-functions applied to near wellbore

upscaled permeability

Chandra et al, 2014



GeoPoDS summaryGeoPoDS NWRT PHIE K-Transform Kv/Kh Sw-H

function

Kr curve

Shale Shale <0.01 K= 0.001 Kv=Kh G0 G0

G0 NWRT-A1 [0.01,

0.05)

K= 766.42*(PHIE)3.2229 G0 G0

G1 NWRT-A2,

A3, NWRT-

B1, B2, B3

[0.05,

0.15)

K= 101278*(PHIE)5.0483 y = 8E-07*(Kh)2 +

0.0016*(Kh)+ 0.878

G1 G1

G2 NWRT-A4,

A5,

A6NWRT-

B4, B5, B6

>0.15 K = 663749*(PHIE)5.5071 y = 8E-07*(Kh)2 +

0.0016*(Kh)+ 0.878

G2 G2

G2 = CEP2à y = 0.1055x2 - 0.5597x - 0.3878, R² = 0.9987

G1= CEP1à y = 0.1386x2 - 0.7188x - 0.14, R² = 0.999

G0= Tight rockà y = 0.1224x2 - 0.624x - 0.016, R² = 0.9963

Shaleà y = 0.0972x2 - 0.473x + 0.055, R² = 0.9923

Poroperm transforms

Chandra et al, 2014



Now

History

match

Chandra et al, 2014



Field G Conclusions

Mismatch between geological model andreservoir simulation modelled resolved

Finer detail petrophysics

Very high resolution NWB model

Upscaled Rock Types ( GeoPODS)

Improved History Match (without tuning)

No significant fracturesapart from the stylolite-related fractures that areincorporated in stylolite GeoPOD.



Triple Matrix Porosity Systems

Indian Field GNorth African Field H

Three RT’s only needed in the Models for Reasonable History Matching

without need for fracture modelling



Acknowledgements

Total Professorship (1994-2011)BG Group Professorship (2012-2017)

ColleaguesSebastian Geiger, Alireza Kazemi

StudentsViswasanthi Chandra

International Centre for Carbonate ReservoirsDynaCARB Project

Schlumberger (Eclipse), Weatherford (PanSys),Geomodelling (SBED), CMG (CMOST, IMEX)



Fracture Reservoir Agreement

Fractures are difficult to locate but easy to predict withthe correct structural model (Lewis, HWU)

Fracture Models should be driven by data and concepts(Riva, GE Plan)

Fractures develop though complex history of burial andmany stress episodes(Bezerra, UFRN; Betotti (TUDelft)

Lithology and facies have an impact on fracturedistributions (Cazarin, Petrobras)

Need to model fractures in 3D (Hartz, Det Norske

Oljeselskap; Moos, Baker-Hugues)A multidisciplinary approach to tackle fractures isnecessary

Source: EAGE-SBGf Fracture workshop – Rio Nov 2013



All reservoirs are fractured!

What Gary Couples and I can agree on:

“We think all carbonates are fractured, but thefractures MAY not be playing a major role inflow”

So “All reservoirs are fractured – and somefractures are useful for flow”

And “Sometimes reservoirs that appear fracturedmay actually have very high matrix contrasts”

closing the loop between geology and reservoir engineering

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