Modelling the Evolution of Natural Fracture Networks: Methods for Simulating the Nucleation, Propagation and Interaction of Layer-Bound Fractures

237 Pages·2020·11.43 MB·English

by  Michael John Welch, Mikael Lüthje, Simon John Oldfield

Michael John Welch
Mikael Lüthje
Simon John Oldfield
Modelling
the Evolution
of Natural Fracture
Networks
Methods for Simulating the Nucleation,
Propagation and Interaction
of Layer-Bound Fractures
Modelling the Evolution of Natural Fracture
Networks
· ·
Michael John Welch Mikael Lüthje
Simon John Oldfield
Modelling the Evolution
of Natural Fracture Networks
Methods for Simulating the Nucleation,
Propagation and Interaction of Layer-Bound
Fractures
MichaelJohnWelch MikaelLüthje
DanishHydrocarbonResearchand DanishHydrocarbonResearchand
TechnologyCentre TechnologyCentre
TechnicalUniversityofDenmark TechnicalUniversityofDenmark
KongensLyngby,Denmark KongensLyngby,Denmark
SimonJohnOldfield
DanishHydrocarbonResearchand
TechnologyCentre
TechnicalUniversityofDenmark
KongensLyngby,Denmark
ISBN978-3-030-52413-5 ISBN978-3-030-52414-2 (eBook)
https://doi.org/10.1007/978-3-030-52414-2
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Preface
Naturalfracturenetworksareimportantincontrollingthemechanicalbehaviourand
flowoffluidsthroughgeologicalformations.Itis,therefore,essentialtoincludefrac-
turenetworksinthestaticgeomodelsthatareusedtomodelsuchbehaviour,inappli-
cations ranging from tunnel excavation and mining to groundwater management,
hydrocarbon exploration and production, geothermal energy extraction and CO
2
sequestration.However,fracturescannotnormallybemappeddirectlyinthesubsur-
face,astheyarebelowtheresolutionofgeophysicaldata,andboreholesprovideonly
very limited data coverage. Traditional solutions to this problem include building
stochasticfracturemodels,inwhichfracturesofarbitrarysizeareplacedatrandom
locationsinanattempttomatchthefracturedensitiesmeasuredintheboreholes,or
using numerical methods such as the finite element method to simulate the nucle-
ationandgrowthofthefractures.However,theformermethodproducesinaccurate
andgeologicallyunrealisticfracturemodels,whilethelatteristoocomputationally
expensivetobepracticalforanybutthesimplestfracturesystems.
Inthisbook,wepresentanewmethodofsimulatingthegrowthoflayer-bound
fracture networks, which is based on fundamental geomechanical principles, but
is simple enough to model large networks containing hundreds of thousands of
fractures across major geological structures such as anticlines and diapirs. This
is achieved by combining the established theories of subcritical fracture propaga-
tion,linearelasticfracturemechanicsandfracturedistributiontoderivequantitative
expressionsdescribingtheevolutionofthefracturenetwork,basedonthemechanical
propertiesofthehostrockandthedeformationhistory.
We start by modelling the growth of small circular fractures within a homoge-
neouslayer.Wethenfocusonlayer-boundfracturesthatareconfinedwithinbrittle
competent layers (which often act as aquifers or reservoirs) sandwiched between
moreductilelayers(whichoftenactasseals).Byapplyingtheexpressionsforfrac-
turegrowthtocumulativedistributionfunctionsdescribingthefracturepopulations
asawhole,wecanmodeltheevolutionofthesepopulationsthroughtimewithout
needingtomodelthegrowthofeachfractureindividually.Todothisaccurately,we
must also model the effects of fracture interaction; this includes both intersection
withperpendicularorobliquefracturesandstressshadowinteractionwithparallel
fractures.Theresultingexpressionscanpredictthedensityoffracturesofdifferent
v
vi Preface
sizes,andindifferentorientations,atdifferentlocationsacrossthegeologicalstruc-
ture we are modelling, as well as predicting important properties of the fracture
networksuchasfractureporosityandconnectivity.Finally,wecanusetheseresults
togenerateageomechanicallyconsistentexplicitDiscreteFractureNetwork(DFN)
model.
Thismethodcanbeusedtoexplorethecontrolsondifferentaspectsofthefracture
networks that develop under different conditions. We show that the mean linear
density(P )oflayer-boundfracturesismainlycontrolledbythepresenceofstress
32
shadowsandthelayerthickness,whilethevolumetricdensity(P )andmeanlength
30
of layer-bound fractures are controlled by many factors, including the duration of
deformation,thesubcriticalfracturepropagationindex(whichcontrolsthefracture
propagationrate),theinitialmicrofracturepopulationandtheinteractionsbetween
thefractures(whichareinturndependentonanisotropyintheappliedstrain).We
showthatfracturenetworksmaynotstarttodevelopimmediatelywhenhorizontal
strainisapplied,butthatoncetheydostarttodeveloptheygrowveryrapidly,often
reaching“saturation”(whennofurtherfracturescannucleateorpropagate)within
tensofthousandsofyearsorless.Onalargescale,thefracturenetworkoftenappears
firstatthelocationofgreateststrainonthelarge-scalegeologicalstructure(e.g.on
thecrestofananticlineordiapir),andthensweepsoutwardsacrossthestructureasa
sharp“deformationfront”.Ifwelookatthelarge-scalestructureatanyspecificpoint
in time, therefore, we can divide it into unfractured and fully fractured (saturated)
zonesseparatedbyaclearlydefinedboundary,ratherthanseeingagradualvariation
in fracture density across the structure. We also show that mode of the fractures
(i.e.Mode1dilatantfracturesverseMode2shearfractures)isdependentnotonly
on the mechanical properties and fluid overpressure (which we might expect), but
alsothepropagationrate(Mode1fracturesaremorelikelytoformifthesubcritical
fracturepropagationindexishigh).Finally,weinvestigatewaysofcharacterisingthe
anisotropyandconnectivityofthefracturenetworkandshowhowtheseproperties
evolveasthefracturenetworkdevelops.
A method of this complexity requires calibration against real fracture networks
beforewecanapplyitwithconfidencetothesubsurface.Wehaveselectedthreefrac-
turedoutcropsfromtheUKforthispurpose.TheNashPointoutcropinsouthWales
exposesauniaxialfracturenetwork(i.e.comprisingasinglesetofparallelfractures)
in thin brittle limestone beds sandwiched between ductile shales (Maerten et al.
2016).Weshowthatthethicknessofthelimestonebedscontrolstheobservedfrac-
turespacing,andweshowhowtoreplicatetheobservedfracturelengthsbyadjusting
thesubcriticalfracturepropagationindexandtheinitialmicrofracturedensity.The
Robin Hood’s Bay outcrop in northeast England exposes an orthogonal fracture
network,comprisingtwoperpendicularsetsoflayer-boundfractures,againconfined
withinthinbrittlelimestonebedssandwichedbetweenductileshales(Rawnsleyetal.
1993).Theanisotropyofthisnetworkvarieslaterallyacrosstheoutcrop;weshow
thatthisvariationinfractureanisotropyistheresultoflateralvariationinthelocal
strainaroundthekm-scalePeakFault,whichliestotheeastoftheoutcrop.Finally,
thePegwellBayoutcropinsoutheastEnglandexposesaseriesoffracturecorridors
propagatingoutwardsfromstrike-slipfaultsinchalk(Souqueetal.2019).Weshow
Preface vii
that it is possible to reproduce the growth of these fracture corridors, but only in
conditions of high fluid overpressure, high subcritical fracture propagation index
andwithoutthedevelopmentofstressshadowsaroundthefractures.
Finally we use this new method to predict fracture networks in two subsurface
examples.TheKrakafieldisahydrocarbonfieldoffshoreDenmark,producingfrom
afracturedchalkreservoiroverlyingasaltpillow.Weshowthatthefracturenetwork
generated by a combination of growth of the salt pillow and local strain around a
set of seismically-mapped faults gives a good match for the fractures observed on
boreholeimagesandincore(describedbyAabøetal.2019).TheAnloosaltdiapir
near Drenthe in the Netherlands is considered a potential prospect for geothermal
energy extraction, utilising several fractured reservoir layers overlying the diapir.
Although the large-scale structure has been mapped out from seismic data, there
is very little well data available with which to constrain the fracture population.
We show how the new method can be used to identify the areas most likely to be
fracturedandpredictthemostlikelyfracturegeometriesatdifferentpointsaround
the structure. We then show how to quickly build multiple, geologically realistic
fracturemodelsfromthislimiteddatasetforuseinuncertaintyandriskanalysis.
KongensLyngby,Denmark MichaelJohnWelch
July2020 MikaelLüthje
SimonJohnOldfield
Acknowledgements
TheauthorskindlyacknowledgetheDanishUndergroundConsortium(TotalE&P
Denmark, Noreco & Nordsøfonden) for providing data for the Kraka field and
granting the permission to publish this work. This research has received funding
fromtheDanishHydrocarbonResearchandTechnologyCentre(DHRTC)underthe
AdvancedWaterFloodingprogramme.
We would also like to thank Total E&P Denmark, and especially Amit Singh,
AlainLejay,MauritsdeHeer,KlaasKostroandAlanCunninghamfortheirhelpin
testingthemodeloutputintheirdynamicsimulations,providingfeedbackandgood
discussions.
We would like to thank everyone at DHRTC and partner institutions who have
contributedtothisresearchproject.InparticularwewouldliketothankFlorianSmit
providinguswithinputandhelpbuildingtheDrenthemodel.Thanksalsogoesto
TalaAabø,JesperDramschandSolomonSeymunforprovidinguswithresultsfrom
their analysis of borehole images, seismic data and core for the Kraka field. We
wouldliketoacknowledgeFredericAmourlettingususeresultsfromhisextensive
workcharacterisingtheelasticmoduliofthechalkinKraka.Wewouldliketogivea
specialthankstoAslaugClemmensenGladforherworkonthesensitivityanalyses.
WewouldliketothankOleRønøClausenandKenniPetersenatAarhusUniversity
forprovidinguswithstraindatafortheKrakafield,andforallowingustousethe
strain history modelling software that they developed to generate strain data for
Drenthe.
We would like to thank Bertrand Gauthier and his colleagues in the Naturally
FracturedReservoirTeamatTotalforhelpfulfeedbackanddiscussion.
We would like to acknowledge Ordnance Survey data and style sheets shared
undertheOpenGovernmentLicence.
WewouldliketoacknowledgedatasharedbytheGeologischeDienstNederland,
partofTNO,throughdinoloket.nl.
Finally,wewouldalsoliketoacknowledgeourcolleagues,students,familiesand
friendswhohaveoftencontributedtoourworkthroughdiscussionandquestioning
oftheprocessesandconceptsbehindthisbook.
ix
Contents
1 Introduction .................................................. 1
1.1 BackgroundandPreviousWork ............................ 2
1.1.1 Impact of Fracture Networks on Bulk Rock
Properties:The“TM”Approach .................... 3
1.1.2 Modelling Fractures Explicitly: The “DFN”
Approach ........................................ 4
1.1.3 SimulatingFractureGrowth:TheMechanical
Approach ........................................ 5
1.1.4 Implementation and Practical Application
ofFractureModels ................................ 7
1.2 ObjectivesofThisStudy .................................. 9
1.3 StructureofThisBook .................................... 12
References .................................................... 13
2 ConceptualModelforFractureNetworkGrowth ................ 17
Reference ..................................................... 20
3 ModellingMicrofractures ...................................... 21
3.1 MicrofracturePropagationRate ............................ 21
3.2 MicrofractureGrowth ..................................... 23
3.3 VolumetricMicrofractureDensity .......................... 24
3.4 MeanLinearMicrofractureDensity ......................... 25
References .................................................... 26
4 ModellingLayer-BoundMacrofractures ........................ 29
4.1 MacrofracturePropagationRate ............................ 30
4.2 VolumetricMacrofractureDensity .......................... 30
4.3 MeanLinearMacrofractureDensity ........................ 32
4.4 CalculatingMacrofracturePorosityandStressShadow
Volume ................................................. 33
References .................................................... 36
xi
xii Contents
5 ActiveandStaticFractures .................................... 37
5.1 CalculatingtheFractureDeactivationProbabilities ............ 39
5.1.1 ProbabilityofMicrofractureDeactivationDue
toInteractionwithMacrofractureStressShadows ..... 40
5.1.2 ProbabilityofHalf-MacrofractureDeactivation
DuetoStressShadowInteraction ................... 42
5.1.3 ProbabilityofHalf-MacrofractureDeactivation
DuetoIntersection ................................ 46
5.1.4 CombiningtheHalf-MacrofractureDeactivation
Probabilities ..................................... 49
5.2 CalculatingActiveandStaticMicrofracturePopulations ....... 50
5.2.1 VolumetricMicrofractureDensity ................... 50
5.2.2 MeanLinearMicrofractureDensity ................. 51
5.3 Calculating Active and Static Half-Macrofracture
Populations .............................................. 52
5.3.1 VolumetricHalf-MacrofractureDensity .............. 52
5.3.2 MeanLinearHalf-MacrofractureDensity ............ 59
5.4 CalculatingResidualMacrofracturePopulations .............. 68
5.4.1 CalculatingtheVolumetricDensityofResidual
ActiveHalf-Macrofractures ........................ 68
5.4.2 CalculatingtheVolumetricDensityofResidual
StaticHalf-Macrofractures ......................... 73
5.4.3 CalculatingtheMeanLinearDensityofResidual
ActiveHalf-Macrofractures ........................ 75
5.4.4 CalculatingtheMeanLinearDensityofResidual
StaticHalf-Macrofractures ......................... 76
6 ElasticModuli,StressandFractureGrowth ..................... 79
6.1 ElasticModuliintheStressShadowScenario ................ 80
6.2 ElasticModuliintheEvenlyDistributedStressScenario ....... 82
References .................................................... 85
7 ApplyingtheMethodtoGeologicalFormations .................. 87
7.1 GeometryoftheStaticGeomodel ........................... 87
7.2 GeneratingImplicitFractureData .......................... 88
7.3 GeneratingtheExplicitDFN ............................... 91
7.4 ComparingtheImplicitandExplicitOutput .................. 94
8 ControlsonFractureEvolution ................................. 99
8.1 ControlsonMeanLinearFractureDensity ................... 100
8.1.1 StressShadows ................................... 100
8.1.2 LayerThickness .................................. 101
8.1.3 FractureModeandFrictionCoefficient .............. 101
8.1.4 DurationofDeformation ........................... 104
8.2 ControlsonFractureDistribution ........................... 109