TT-8-Evaluation Techniques Thin Beds SPE2013 Fin

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The 20th SPE Bergen One Day SeminarApril 10th 2013 | Bergen, Norway

Evaluation Techniques for ThinlyBedded Sandstones

Petrophysics

Jan van der Wal, Senergy

Outline

• What are Thin Beds?

• Part 1: Evaluation Techniques

• Part 2: Revisiting Normalised Qv of Juhasz

• Example

(NL: Spekkoek)

• Introduction

Introduction

Thin Beds Concept

• What are ‘Thin Beds’?

• Laminations of sand and shale, with..

• .. beds so thin that logs do not read true properties.

• Why do we care? In Thin Beds..

• .. conventional evaluation can miss pay,

• .. phi & perm are too low,

.. resistivity reads too low, and• .. saturation height functions give too low HC.

Introduction

When to Apply?

• Consider

• Bed thickness

• Shale percentage, ~50 %?

• Laminated, or dispersed?

• Depositional Environments, can we model it?

Introduction

What is Thin?

• Depends on logging tool as well, < 1m?

Thomas Stieber paper

Introduction

What is Thin?

• Porosity• Old logs < 0.5-1 m

• High res < 0.4 m?

• Resistivity• Old indution < 2m

• Recent < 0.8m?

c o r r

Bed Thickness

R meas

Techniques

Vshale from Images

• Core Photos in XLS• detailed Sand flag

• Smooth to logresolution (por

~1ft, res 1m)

Techniques

Vshale from Image Logs Conductive Dark

Resistive Light

NEU/DEN/SON

Techniques

Vshale from NMR (1/2)

• Assumes ClayBoundFluid relates to Vshale

• Shale volume

• Vshale = (CBFV/ClayPhiShale)

Vshale = (BFV/PhiShale)• Complications:

• dispersed components with additional BF

Techniques

Vshale from NMR (2/2)

• Clay bound

• Laminated: Cap.BF

and FFV

• Clean sand

Techniques

Vshale from 3D-res

• 2000’s, revived thin beds

• Tensor Model

• Horizontal and Vertical, or

• Parallel Conductivity and Serial Resistivity

Res HOR

s V E R

Techniques

Volumetric / Probabilistic

• Probabilistic

• Allows for more components, glauconite?

• Cementation?

• Requires more input curves

• Deterministic: Thomas Stieber (1975)

• Input: Phi and Vsh,

• Outputs: Phi_sand, Vsh_lam, Vsh_disp

Techniques

Core Porosity – of sands!

Techniques

Saturation from core

• Dean Stark

• Capillary Pressures

1. Get Swirr.

2. What is max Rsand?

3. Optimize shale model

Techniques

Saturation - Height Function

• Derive SHF from thick beds

• Apply to thin beds

• But is rock quality the same?

Techniques

Summary – part 1

• Fairly common, also in North Sea

• Vshale: Cuttings, Core, Image logs, NMR, 3D-res

• NTG curve

• Porosity: Core Phi <-> sand lamination• Porosity of sand

• If Resistivity still problematic -> SHF

• Part 2. 3D resistivity workflow

Thomas Stieber• Conductive dispersed components

3D-resistivity workflow

Case Study data – where is the HC?

Vshale

OriginalPublication

Neutron &

Density Deep Res

Case Study, Clavaud, 2005

•Aim: properties of sand lamination

1. Thomas Stieber (1975)

• Φ, Vsand, Vsh.disp

2. Resistivity of the sand lamination• 3D-res 2000’s

• Rsand

3. Saturation computation (SwRT)

• Juhasz 1981

Thomas Stieber Definitions

•Shale (not clay)

• Shale types:

i i i kfl

3D-resistivity workflow - Step 1

Thomas & Stieber, 1975

2 endpoints + 1

P o r o s i t y

Volume of Shale

Clean Sand

‘Pure Shale’

3D i i i kfl S 2

3D-resistivity workflow - Step 2:

Resistivity of Sand Laminations 3D-res

• 2a) Tensor Model

• Horizontal and Vertical, or

• Parallel Conductivity and Serial Resistivity

2b) Anisotropy Model• Smart Tensor Model;

• Inputs Thomas Stieber

Res HOR

R e s V E R

3D i i i kfl S 3

3D-resistivity workflow - Step 3

Saturation Calculation

Which equation?• Conventional (deterministic)

• Laminated Shaly sand eqs:•

Poupon, Indonesia, Simandoux

• Thin Beds (dispersed clay/shale in sandlamination)

• Dispersed Shaly sand eqs:

• Dual Water, Waxman Smits, Normalised Qv Juhasz

Poupon, parallel conductor

3D i ti it kfl

Saturation from Resistivity

• Waxman Smits equation

• For waterleg assume SWT = 1, (and a*=1):

Shale corrArchie

3D i ti it kfl

Waxman Smits in Xplot

Y = a X + b

Slope B

(cousin of Pickett-plot)

3D i ti it kfl

Juhasz

• Juhasz: if no core Qv available,• Qv = f(Vshale)

1/Rw_shale

shale conductivity

100%Shale

1/Rw ~

C o n d u c t i v i t y

Qv_shale

1/Rw_shale

3D i ti it kfl

Juhasz Normalised Qv

• Juhasz: Qv = f(Vsh), or Qv = f(Phi), f(1/Phi)

• Qv = f(1/Phi, Vsh) = f(RPD), (similar to ~Qvn)

• Relative Porosity Difference

• Assume Qv = RPD*C, substitute

3D i ti it kfl

To better pick BC

Slope B*C

3D resistivity workflow

Data Example

RPD in Thin Beds?

• RPD of Bulk not good enough

• => RPD of Sand lamination (RPDs)

• RPDs = f(1/PHIs, Vsh.disp), or

POROSITY POROSITYV h l N t & H V R &

CPI with eval

POROSITY

Conv &

Par.Cond.

POROSITY

Thin Beds &

3D-Res

Vshale

Original

Publication

Neutron &

Density

H+V Res &

Parallel

Conductor

Case Study, data of Clavaud

Summary

• In case of: 3D resistivity, no core, water leg

• Optimise Thomas Stieber with Tensor Model

• Resistivity Sand from Anisotropy model• Relate Qv to RPD

• Compute RPD for sand lamination only

New Xplots for picking Rw and ‘BQv’

References

• Cao-Minh, C., Clavaud, J., Sundararaman, P., Froment, S., Caroli, E., Billon, O., Davis, G. & Fairbairn, R., GraphicalAnalysis of Laminated Sand-Shale Formations in the Presence of Anisotropic Shales, 2008, PETROPHYSICS, Vol 49,

No. 5, October 2008, pp. 395 –405.• Clavaud, J. B., Nelson. R., Guru, U. K. and Wang, H., 2005, Field Example of Enhanced Hydrocarbon Estimation in

Thinly Laminated Formation with a Triaxial Array Induction Tool: A Laminated Sand- Shale Analysis with AnisotropicShale, SPWLA 46th Annual Logging Symposium, June 26-29, 2005.

• Juhasz, I., 1981, Normalised Qv. The Key to Shaly Sand Evaluation using the Waxman-Smits Equation in the Absenceof Core Data. SPWLA 22nd Annual Logging Symposium, June 23rd-26th, 1981.

• Passey, Dahlberg, Sullivan, Yin, Brackett, Xiao, Guzman-Garcia, 2006,Petrophyscial Evlauation of HydrocarbonPore-Thickness in Thinly Bedded Clastic Reservoirs, AAPG Archie Series, No 1

• Stromberg S., Nieuwenhuijs R., Blumhagen, C., Edwards, J., Ramamoorthy R., Herold, B., 2007, Reservoir Quality,Net-to-Gross and Fluid Identification in Laminated Reservoirs from a new generation of NMR logging tools.Examples from the Gharif Formation, Southern Oman. Transactions of the SPWLA 1st Annual SPWLA Middle EastRegional Symposium April 15- 19.

• Thomas, E. C., Stieber, S. J., 1975, The distribution of shale in sandstones and its effect on porosity. Transactions ofthe SPWLA 16th Annual Logging Symposium, June 4-7, 1975.

• Van der Wal, J., Stromberg S., 2012, Correcting the water saturation calculation for dispersed clay in thinly

bedded sandstones, Revisiting the Normalised Qv Equation of Juhasz, Transactions of the SPWLA 53rd

Annual Logging Symposium• Waxman, M.H. & Thomas, E. C., 1974. Electrical Conductivities in Shaly Sands-I. The Relation between

Hydrocarbon Saturation and Resistivity Index; II. The Temperature Coefficient of Electrical Conductivity. J. Pet Tech.213-23. Trans., AIME, 257.

• Worthington, P.F., 2000, Recognition and evaluation of low-resistivity pay, Petroleum Geoscience, Vol 6 2000 (aspublished in Geological Society London, one-day seminar Hidden Hydrocarbons, 2001)

• Backup

Logging programs

• Dip meter

• Image logs

• NMR

• 3D resistivity

• High resolution, Consider slow logging

• See AAPG Archie series No 1

Conclusions

• Workflow can be based on log data only

• New form of Norm Qv of Juhasz applied to thin beds

• Qv estimate refined

• Conventional: low HC

•Conventional with 3D res (Parallel Res): more HC

• Thin Beds with 3D res: most HC

What is RPD?

•Middle East for Carbonate stringers (PDO)

• Shaliness indicator

• Combines 1/PHIT and Vshale (~ Neu-Den separation)

• RPD= (Neu + Co – PhiT)/ PhiT

• How to get ‘Co’ • Use ND overlay

• For clean sand: RPDs ~ 0

Clean but conduct: RPDs > 0

What if no 3D resistivity available?

• Make cases for vertical resistivity

• Check with Thomas Stieber

• Simplest: Rv = Rh * C

• Better: Rv = Rh * C * Vsh_lam, or

• Rv = Rh + C * Vshl * (Rh – RshH)• Rv = Rh + (C* Vshl / ((1/RshH – 1/Rh))

What is Parallel Conductor model?

• Ct = Vsand * Csand + Vsh.lam * Cshale, or

• 1/ RT = Vsand / Rsand + (1-Vsand) / Rsh.hor

Res HOR

When to apply Thin Beds

• Neutron Density Data

• Intermediate GR?

• Dispersed, Laminated,

or Both?

D e n s i t y

3 < Neutron > 2

• Conductive dispersed shale?

D e n s i t y

3 < Neutron > 2

DeepRes

What if you do have core?

• Are plugs of the sand lamination?

• Porosity:• Calibrate Clean Sand endpoint to match the high porosity

• Optimise input PHIT

• Calibrate BC & RPD to match the predicted QV curve

Depositional Environments

Fluvial systems (1/2)

Static Model

(25x25x0.5)

Dynamic Model

(100x100x10)

Arbroath, Scotland

Introduction

Also in North Sea

Sele and Forties

Article:Turbidite reservoirs of the Sele Formation, Central North Sea: geological challengesfor improving productionM. HEMPTON, J. MARSHALL, S. SADLER, N. HOGG, R. CHARLES and C. HARVEY

From Abstract• Fields: Forties, Nelson, Montrose –Arbroath, Scoter, Pierce, the Gannet cluster, Guillemot A, Mirren and Merganser, Phyllis, Starling and

Blane are under appraisal/development.

• ‘Forties’ submarine fan system sourced from feeder channels in northwest andwest.

From 3D seismic & wells:

• Near sources (updip): thicker, higher N/G, and more channelized.

• Downdip: thinner, finer grained and stacked lobes and minor channels (controlled by accommodation space and salt movement).

Introduction

Techniques

Bed Thickness vs Occurrence

• Altered carbon cycling and coupled changes in Early Cretaceousweathering patterns: Evidence from integrated carbon isotope andsandstone records of the western Tethys

• Ulrich Georg Wortmanna, , , Jens Olaf Herrleb, , Helmut Weissertb

Bed Thickness

N r o f B e d s t h i c k e r t h a n

• Where (and when) should we expect Thin

Beds issues?

How much shale

Sw vs computed Sw

• Theoretical parallel conductor modelVshale 0.15;

PhiShale 0.18; ShaleRes 3.09;

PhiSand 0.2; SandRes from Archie

Techniques

Rock quality

• Does NTG correlate to bed-thickness?

• Does bed-thickness correlate with quality?

• Geo Models

Scale - Fluvial systems

Static Model

(25x25x0.5)

Dynamic Model

(100x100x10)

Arbroath, Scotland

Good news: Turbidites

(image fromgeo ExPro)

Kota KinabaluSabah,

Oligocenedeepwater,among mostsand-richoutcrops

How much shale

Shale vs Sw

• In ideally laminated,more than 10% of shale

is problem

Model:

• Sw = 20% in sands

• Assumed perfect

(theoretical) parallel

conductor model

Workflow

• Conventional

• Vshale

• Porosity

• Saturation

• Thin Beds

• Vshale

• Porosity

• Sand Phi & Shale

• Rsand & Saturation

Techniques

Vshale from Core (2/2)

Calibrate traditionaltechniques (GR, ND)

to downscaled (i.e.

smoothed) core

sand/shale flag

calcite

calcitecalcite

Introduction

The 20thSPE Bergen One Day Seminar

April 10th 2013 | Bergen, Norway

• Neutron Density Data

• Intermediate GR?

• Dispersed, Laminated,

or Both?

D e n s i t y

3 < Neutron > 2

TT-8-Evaluation Techniques Thin Beds SPE2013 Fin

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