wellbore logs in rittershoffen, alsace: acquisition ... · wellbore logs in rittershoffen, alsace:...

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Wellbore logs in Rittershoffen, Alsace:

acquisition, analysis and integration

for fractured reservoir characterization

Giovanni Sosio, Andreia Mandiuc, Annalisa Campana, Schlumberger

Jeanne Vidal, Régis Hehn, ES Géothermie

SPWLA France – Technical Session

Paris, SGF, 27 November 2018

The ECOGI project in Rittershoffen, Alsace

Log acquisition in Rittershoffen

1500 m of ultrasonic images analyzed in GRT-1 and GRT-2

360 individual fractures observed in both wells

GRT-1: N10°E to N20°E steeply dipping westward

GRT-2: N160°E to N-S steeply dipping eastward

Geological interpretation: natural fractures

1500 m of ultrasonic images analyzed in GRT-1 and GRT-2

360 individual fractures observed in both wells

GRT-1: N10°E to N20°E steeply dipping westward

GRT-2: N160°E to N-S steeply dipping eastward

Fracture orientation more homogeneous in GRT-1: GRT-2 collinear to the main fault intersects fractures with different orientations

(Vidal et al., EGC 2016)

Geological interpretation: natural fractures

Alte

red

Gra

nite

Fa

ult

Co

reF

resh G

ranite

Permeable fracture zonesassociated to total mud lossesand negative thermal anomaly

Geological interpretation: natural fracture permeability

Permeable fracture zonesassociated to total mud lossesand negative thermal anomaly

Less than 3% of fractures in GRT-1and 1% in GRT-2 are permeable

Geological interpretation: natural fracture permeability

K

U

B

G

M

Computation of mechanical propertiesand stress magnitude based on sonic (DT, DTS) and density logs

Geomechanical interpretation: wellbore stability

GRT-1

Mechanical properties and stress

from input logs (density and sonic)

K

U

B

G

M

Observed events

Computation of mechanical propertiesand stress magnitude based on sonic (DT, DTS) and density logs

Stress orientation derived from drilling-induced tensile fractures(Hehn et al., EGC 2016)

“Mechanical earth model” validated against observedwellbore stability events(drilling-induced fracturesfrom wellbore images and ovalization from caliper)


GRT-1

K

U

B

G

M


GRT-1

Computed critical mud weights

compared with actual mud weight

K

U

B

G

M

Observed events


GRT-1

Synthetic events


K

U

B

G

M

Impact of thermal stresses

GRT-1


0.95 g/cc 2.15

K

L

B

M

G

GRT-2 (prediction)


0.95 g/cc 2.15

K

L

B

M

G1.25 g/cc 1.50

Critical breakout mud weight

GRT-2 (prediction)

From data acquisition to modeling

- Wireline Logging, LWD

> Petrophysical

> Acoustic

> Imaging

- 2D/3D Seismic,EM, Gravimetry

- Well tests

- Core data

- Drilling data

SUITABLE INPUTS

- Inputs QC

- Integration in a single platform

- Advanced processing and interpretation

DATA INTEGRATION

- Build 3D static model:

> geological structure

> rock properties

> fracture network

- Model dynamic behavior:> production/injection

> heat flow and temperature changes

> stress and strain

ANALYSIS & MODELLING

- Well placement/design

- Completion optimization

> Casing/tubing size

> Optimum flow rates

> Stimulation design

- Risk mitigation

> Drilling risks

> Well integrity

> Subsidence

> Induced seismicity

APPLICATION & DESIGN

Integrated geothermal modelling workflow

Seismic data

Drilling data

Logs & offset well info

Structural model

Well test data

Microseismic data


Seismic data

Drilling data


Structural model

Petroph. & image interp

ba d ec

Losses

K

U

B

G

M

1D MEM

Well test data

Microseismic data


Seismic data

Drilling data


Structural model

Inversion


Geological model

DFN

ba d ec

Losses

K

U

B

G

M

1D MEM

Well test data

Microseismic data


Seismic data

Drilling data


Structural model

Inversion


Geological model

DFN

ba d ec

Losses

K

U

B

G

M

1D MEM

Flow model

Well test data

Microseismic data


Seismic data

Drilling data


Structural model

Inversion


Geological model

DFN

ba d ec

Losses

K

U

B

G

M

1D MEM

Flow model

3D MEM

Well test data

Microseismic data

Discrete fracture networkusing image interpretationand structural model –tectonic-based approach

Integration and modeling: natural fractures

Input – image log interpretation

and structural model



Geomechanical engine

identifies stress regime

linked to observed faults/fractures



Geomechanical engine

identifies stress regime

linked to observed faults/fractures

Resulting DFN

Mechanical properties propagated based on 2D seismic inversion

FEM stress simulation to identifycritically stressed fracturesand forecast induced seismicity

Integration and modeling: geomechanical model

Acoustic impedance

Mechanical properties propagated based on 2D seismic inversion

FEM stress simulation to identifycritically stressed fracturesand forecast induced seismicity


Acoustic impedance

Stress tensor

Stress rotation due to geological structure


Plastic strain

(irreversible deformation)

= fault reactivation

Estimated microseismic events


Estimated microseismic events

Measured microseismic events


Accurately designed log acquisition plan:wellbore images and dipole sonic logs from surface

Detailed analysis of natural fracture geometryand of mechanical properties

Conclusions



Integration of different domain data(images and temperature; sonic and images; etc.)

Insight on reservoir behavior (permeability, stress…)

Conclusions



Integration of different domain data(images and temperature; sonic and images; etc.)

Insight on reservoir behavior (permeability, stress…)

Multi-disciplinary 3D model (geological, fluid flow and geomechanical) based on the above

Understanding of site performance and risks

Conclusions

Thanks for your attention!

[email protected]

Many thanks to Charidimos Spyrou, Oleksandr Burachok, Ann-Sophie Boivineau,

Claudia Sorgi, Vincenzo De Gennaro, Karsten Fischer, Clément Baujard, Albert Genter

slb.com geothermie.es.fr

Data kindly provided by the ECOGI consortium

Modeling software used courtesy of Schlumberger

Acknowledgments

http://www.slb.com/

https://geothermie.es.fr/

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