Simplified In-Situ Stress Properties in Fractured Reservoir Models

Tim Wynn

AGR-TRACS

Early assessment of the influence of in-situ stresses

Relatively fast model construction and analysis

Iterations with standard reservoir simulators

Ownership by asset team members

Use results to guide more specialised modelling

Before the What and the How is Why………

Potential decrease in fault seal capacity

Potential increase in natural fracture permeability

Simplified? – Stress properties are static, no coupled modelling

Fundamental Principles - Normal and Shear Stresses

σ

σ

σ n τ = Shear stress

High values act to move fractures

σn = Normal Stress

High values act to close fractures

Shear stress is not affected by pore pressure

σ = S - Pp

τ

The Fundamental Principles - Critical Shear

Critical levels of shear stress on fractures leads to small slip events. Can enhance permeability through brecciation and breaking of minor mineral bonds

Normal Effective Stress σn

Shea

r Str

ess

τ

Slope = µ ~ 0.6

µ = Coefficient of sliding friction

CFF = τ – (µ * σn)

CFF = Coulomb Failure Function

If CFF > 0 slip can occur

Building The In-Situ Stress Model

In-situ stress modelling

Input Properties for each cell or fracture Principal stress magnitudes and orientations Pore pressure Fracture dip and dip azimuth

Output Properties for each cell or fracture Normal Stress σn

Shear stress τ CFF

Cellular Model Example

Platform carbonate oil reservoir with small gas cap. Some compositional grading.

Main structures formed in thrust environment

Fractures required for permeability and some storage

Current in-situ stress regime unclear – could be normal or strike-slip

Pore pressures are over-pressured. Higher gradient at top of reservoir.

Stress regime changed from normal to strike-slip

Cellular Model Example – Normal Stress Input Parameters

Virgin Pore Pressure SH Magnitude

SH Orientation Fracture Dip Azimuth

Cellular Model Example – Normal Stress Output Parameters

σn Magnitude τ Magnitude

Coulomb Failure Function

Cellular Model Example – CFF Correlations 1

Outlined circles = strike-slip

Un-outlined circles = normal

Cellular Model Example – CFF Correlations 2

Outlined circles = strike-slip

Un-outlined circles = normal

Cellular Model Example – Conclusions

CFF nearly always negative with modelled values

Some indications that higher CFF values are associated with inflow

However, many locations where higher CFF values are not associated with PLT inflow or mud loss intervals.

Possible correlation with larger scale faults

Further analysis on the correlations of parameters (fractures, faults, dynamic data, mineralisation, CFF)

Further simplified modelling is warranted, possibly leading to fully coupled geomechanical modelling

DFN Model Example

Platform carbonate gas reservoir

Main structures formed in strike-slip environment

Fractures may influence permeability and storage

Current in-situ stress regime probably strike-slip

Reservoir under appraisal, no production data

Preliminary run of in-situ stress parameters

DFN Sector Model – Workflow

Create geocellular sector model in area of interest

Populate with conventional

reservoir parameters

Populate with in-situ stress

parameters eg. Sv, SHmax etc

Create DFN within geocellular grid

volume

Sample relevant grid parameters

onto DFN fractures

Calculate normal and shear stresses,

CFF etc on DFN

Modify fracture permeabilities using stress

parameters e.g. CFF

Upscale DFN: Porosity

Permeability Sigma

Repeat upscaling on different

geocellular grids if required

DFN Sector Model – Geocellular Grid Lithology

Limestone layers

Seismic scale fault

Shale and evaporite interlayers

1 km

Dolomite with best matrix properties

DFN Sector Model – Geocellular Grid Properties

Fracture Intensity

Lithology Controlled

Fracture Dip Azimuth

ESE dominated

ESE

DFN Sector Model – Fracture Network

Layer bound joints & Veins

with facies dependent distributions

Seismic scale fault

Fault damage zone fractures

1 km ~350,000 fractures

Orientation distributions

same for each set in all layers

DFN Sector Model – Property Sampling

Pore pressure

Sampled into DFN

Pore pressure

In geocellular grid

DFN Sector Model – DFN Properties

CFF modified permeability

350° SHmax

CFF on DFN fractures

DFN Sector Model – DFN Stress Modified Permeability

CFF modified permeability

350° SHmax

CFF on DFN

015° SHmax

Upscaled CFF modified Kj permeability

DFN Sector Model – DFN Stress Modified Permeability

CFF modified permeability

350° SHmax

Kk

Kj

Ki

DFN Model Example – Conclusions

25° change in SHmax direction made more difference than other stress parameters (SHmax, Pp etc).

CFF values very low

Too deep in structure?

Stress magnitudes poorly constrained.

Not critically stressed…

Mainly useful for modelling scenarios. Little dynamic data to constrain options.

Some further simplified modelling warranted.

Conclusions

1.  Simplified approach allows better integration of in-situ stress data into the standard reservoir modelling workflow

2.  Can help define uncertainties for constraining additional data gathering or further modelling

3.  Valuable screening tool prior to more advanced geomechanical modelling

4.  In-situ stress parameters available as preliminary input to wellbore stability or fracture design