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Modelling approaches in sedimentology: Introduction to
the thematic issue
Philippe Joseph, Vanessa Teles, Pierre Weill
To cite this version:
Stratigraphy,
Sedimentology
Modelling
approaches
in
sedimentology:
Introduction
to
the
thematic
issue
Philippe
Joseph
a,*
,
Vanessa
Teles
a,
Pierre
Weill
b aIFPE´nergiesnouvelles,1et4,avenuedeBois-Pre´au,92852Rueil-Malmaison,France
bUniversite´ deCaenNormandie,CNRS,Morphodynamiquecontinentaleetcoˆtie`re(M2C),24,ruedesTilleuls,14000Caen,France
1. Introduction
Whethernumericalorexperimental,modellingisnow widelyusedinsedimentology,butitcoversalargerangeof domainsbothintimeandspace:experimentalanalogical models (notablyused forgeomorphological evolutionof reliefs)enableustocharacterizeatasmallscaleerosion, transport, anddepositionprocesses,toinferquantitative evolutionlaws,andtocalibratetheirrelevantparameters. Hydro-sedimentarymodellingismainlyusedtounderstand the evolution of present environments using a detailed numericalmodellingoftheseerosion–transport–deposition processes(solvingtheNavier–Stokesequations,for exam-ple). Process-basedsimplified approaches are appliedto
geological time scales:they are based eitheron solving deterministic laws describing main processes (genetic models, de Marsily et al., 2005), or with additional introductionof stochastic parameters intothe laws (the so-calledrandom-geneticmethods).Reservoirarchitecture modellingisbasedongeostatisticalapproachesormixed geometric/stochastic methodsmentioned here ashybrid models:theyenableustoquantifytheuncertaintyofthe resultinggeomodels,whicharelinkedeithertothedata,or totheconceptualmodel(depositionalenvironment, corre-lationscheme...).Atthebasinscale,stratigraphicmodelling uses averaged transport and deposition laws (diffusion equation,for example)in ordertoreproduce large-scale depositionalarchitecturesandtotesttheimpactofcontrol parameters(accommodation,climate,clasticsedimentary inputorcarbonateproduction...).
Someoftheseapproachesarecoupled:process-based modelsareoftencalibratedonanalogicalexperiments,and ARTICLE INFO
Articlehistory: Received4April2016
Acceptedafterrevision4April2016 Availableonline11May2016 HandledbySylvieBourquin Keywords:
Analogmodelling
Hydro-sedimentaryprocessmodelling Stratigraphicmodelling Hydrodynamicmodelling Thermo-mechanicalmodelling Geostatistics Reservoir Sedimentarybasin ABSTRACT
Asanintroductiontothisthematicissueon‘‘Modellingapproachesinsedimentology’’, thispapergivesanoverviewoftheworkshopheldinParison7November2013duringthe 14thCongressoftheFrenchAssociationofSedimentologists.Asynthesisoftheworkshop in terms of concepts, spatial and temporal scales, constraining data, and scientific challengesisfirstpresented,thenadiscussiononthepossibilityofcouplingdifferent models,theindustrialneeds,andthenewpotentialdomainsofresearchisexposed. ß2016Acade´miedessciences.PublishedbyElsevierMassonSAS.Thisisanopenaccess
articleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/ 4.0/).
* Correspondingauthor.
E-mailaddress:philippe.joseph@ifpen.fr(P.Joseph).
ContentslistsavailableatScienceDirect
Comptes
Rendus
Geoscience
w ww . sc i e nce d i re ct . co m
http://dx.doi.org/10.1016/j.crte.2016.04.001
then applied to recent systems, before being used on outcrops or subsurface data. Process-based, random-geneticorhybridmodelsproducereservoirarchitectures that may be used as training images for geostatistical methods.Atthebasinscale,stratigraphicmodellingmay becoupledwiththermo-mechanicalmodelsinordertoget thetimingofthedeformationofthebasin, throughthe evolution of thelithosphere, and analyze itsimpact on surfaceprocesses.Stratigraphicmodelsmayalsobeused asaninputoflarge-scalefluidcirculationmodels,which may be coupled with reactive transport simulation for environmentalpurposes(geothermalenergy,CO2storage, wastes),ordiagenesis-relatedproblems.
Duringthe14thCongressoftheFrenchAssociationof SedimentologistsheldinParisfrom5to7November2013, aworkshopon‘‘Modellingapproachesinsedimentology’’ hasbeenorganizedbetweenresearchersofthesedifferent communitiesinorderto:
exchange on the different concepts and approaches developedtomodelandsolveproblemsin sedimentolo-gy;
discuss the methodologies adopted to honour data, through parameter calibration, and in relation with uncertaintyquantification;
identifythelimitsandkeyissuesoftheseapproaches; evaluatethepossibilityandneedsforcouplingbetween
models, in order to initiate new collaborations and researchdomainsinrelationwithindustrialneeds. 2. Organizationoftheworkshop
Theworkshopwasorganizedinthreestages.
First,apostersession,with27contributions,gathered theparticipantsandillustratedtheirdifferentmodelling approachesandtheirlatestresults.Theelectronicversion ofsomeofthesepostersisavailableonthewebsiteofthe French Association of Sedimentologists (ASF) at the address:http://www.sedimentologie.fr/.
Followingthepostersession,twodiscussionswereheld in parallel between modellers dividedaccording to the scaleoftheirmodels:
theme 1: large-scale modelling of the history and sedimentaryarchitectureofbasins: geodynamical con-trol,datasynthesis,fluidpalaeo-circulations (coordina-tors:P.Joseph,G.Caumon,D.Rouby);
theme 2: modelling of sedimentary and diagenetic heterogeneities: processes, reservoir architecture and properties,fluid-flowbehaviour(coordinators:V.Teles, R.Labourdette,P.LeHir,S.Lopez,P.Weill).
Thesediscussionswerestructuredaroundthree key-pointsandaresummarizedinthenextsection:
presentationofthespatialandtemporalscales,andmain conceptsofeachmodel;
useandavailabilityofconstrainingdata;
identifiedscientificchallengesinmodellingapproaches andcouplingbetweenmodels.
Finally,aroundtablewithalltheparticipantsenabled to share and summarize the conclusions of the two thematic previousdiscussions andinitiated a debateon academicandindustrialneedsandpotentialnewresearch domains.
3. Synthesisoftheworkshop 3.1. Theme1
Thisfirstthemegatheredresearchersworkingatalarge geological scale with different approaches such as stratigraphic, thermo-mechanical, geological and/or flu-id-flow modellingat thebasin scale. Consequently,the consideredspaceandtimescalesarequitehomogeneous betweenthesemodels.Spatialdimensionsspanfromafew to thousands of kilometres, simulated time span from 100katoseveral(tenstoevenhundreds)millionyears.The modelling concepts presented during this workshop covereddifferentaspectsofbasin-scaleprocesses: stratigraphic and geomorphological models represent
large-scale sedimentary processes either with diffu-sion-likeorhydrodynamicequations;
geologicalmodelscanborrowdifferenttechniquesfrom machinelearning(e.g.,neuralnetworks),geostatistical methodsordeterministicmaps;
thermo-mechanicalmodelsuserheologicallawsofsolid behaviour;
basin-scaleflowmodelsmaycouple fluid-flowlaws in porous media, geochemicalreactivelaws and geome-chanicallaws.
Intermsofinputdata,awiderangeofdatahasbeen listedbystratigraphicandgeologicalmodellers:seismic data, fault geometry, climate data, dating, outcrop sedimentological sections, well logs and core data and their geological interpretation in terms of facies and depositionalenvironments,hydrodynamicdata(pressure and flow rates). Palaeogeographic, palaeo-bathymetry/ palaeo-reliefconstructedbythegeologicalmodellers,as wellaspalaeoclimaticmapsareinterpreteddatausedby stratigraphic and basin-scale groundwater modellers. Thermo-mechanical models need information on the lithosphere structure and thermicity, and on mantle convectiveprocesses.
Simulation results of these models are calibrated mostlythroughatrial-and-errorprocess,althoughsome inversiontechniquesarealsodeveloped.Validationisdone by comparison against well and seismic data, or inter-preted palaeogeographic maps in the case of thermo-mechanicalmodels.
It has been highlighted that the coupling of these differentmodelswouldbeaveryinterestingstepforward. Forexample,stratigraphicmodelsneedabetterestimate ofsubsidenceandupliftratesthroughtimethatcouldbe modelled by lithosphere thermo-mechanical models actingasprovidersof‘‘boundaryconditions’’.Basin-scale fluid-flow models are dependent on the timing and durationofthediageneticeventsandonthegeochemical P.Josephetal./C.R.Geoscience348(2016)473–478
composition of the fluids. Thermo-mechanical models would benefit from a better description of continental evolution and dismantlement. It was also noted that couplingwithclimatemodelswouldallowbetter estima-tesofwaterfluxesandtemperaturefluctuationsthrough time.
3.2. Theme2
This second theme gathered different modelling communities working at a smaller scale from hydro-sedimentaryorexperimentalmodelsonmodern environ-ments, topetroleum reservoir-scale models witheither stochastic,geometric,hybridorprocess-basedapproaches. Timeandspacescalesofthesemodelsaremorevariable thantheonesoftheprevioustheme.Hydro-sedimentary numericalorexperimentalmodelsfocususuallyononeor several processes from the grain or ripple scale tothe sedimentary body. Thustime scalestaken into account spanfromsecondstoseveralyears.Process-basedmodels simulatethesedimentaryprocessesata geologicalscale andtheyconsidersimplifiedoraveragedlawsoftenbased onempiricalobservations.Simulateddurationscanaswell be that of a specific sedimentary event as of several thousandyears,becausetheobjectiveistoreproducethe architectureandheterogeneityofthereservoirbystacking severalsedimentarybodies.Stochasticandhybridmodels also have this same objective and are mostly use at reservoirscale.Stochasticmodelsfirstcharacterize mathe-matically the geometry and heterogeneity of the sedi-mentsfromavailabledata,andthentheycanreproduce them into several equiprobable simulations. Several algorithms are available depending on the object of interest.Hybridmethodsweredevelopedforspecificcases whosestructureandheterogeneityaredifficulttomodel withstochasticmethods:fluvialorturbiditicmeandering channels(Lopezet al.,2008;Labourdette,2007), deltaic mouth bars (Hu et al., 1994)... These models embed sedimentaryconceptstoproducegeometries.Theyusually focus on significantheterogeneities or relationbetween geobodies.Hybridmodelsareclosetostochasticmodels due to the fact that they usually can simulate several equiprobablerealizationsthroughstochasticconcepts.The usualtrade-offtobefoundbetweenbothalternativesis that stochastic models may explore unrealistic phase spaces, whereas over-simplified physical models may generatebiasedresultsandwillnotexploreall possibili-ties. But both modelling approaches can easily lead to uncertaintyassessment.
Intermsofdata,hydro-sedimentarymodelsarebasedon field measurementsofhydrodynamicsandbottom mor-phology, and they also use mechanical, rheological characteristics.Theresultsgivethespatialandtemporal (4D) distributionof sedimentsbothinside theflow and over thefloor surface, information such as bathymetry variation,stateandcompositionofthefloordowntothe millimetre-scale. Inputs to process-based models are an initial topography, sediments description (grain size, density), and transport processes history (flow regime, successionsofevents).Calibrationoftheinputparameters relies on trial-and-error testing. Eventually, they give
architectureand faciesdistribution ofdepositsover the initialtopography.Theyarealsoabletogiveinformation on the chronology and thus on genetic relationships betweensedimentarystructures.Finally,bothgeostatistics and hybrid models use well data (facies, porosity, permeability), production data, as well as geological concepts along with outcropand seismicdata (seismic attributesandhorizons).Whetherthevariableofinterest iscontinuous(petrophysical,mechanical,thermal,elastic parameters) or discrete (facies, diagenetic phase), both methods are able to produce spatially distributed data fieldshonouringtheactualobserveddata.
Duringthediscussion,itappearedthatthesemodelling approachesfacesimilarissueslinkedtotheirdimensions/ scalesandupscalingpossibilities.Laboratoryexperiments needanappropriatescalingtoadequatelyrepresent real-worldprocesses.Oneoftheissuesofhydro-sedimentary numericalmodelsaswellasforprocess-basedapproaches istheupscalingoftheirequationsbothintimeandspace forthesimulationofsuccessiveevents.Thelinkbetween processesor eventsand depositsand their preservation through time is an open question to know what is significanttoconsideratthesimulationscale.Stochastic and hybrid models are confronted with the issue of upscalingwhenthemodellingresultsmustbetransferred tothedynamicreservoirmodel.
Otherwise, specific issues were mentioned for each approach and could be solved by coupling different methods:
definitionofinitialandboundaryconditions, condition-ingtoharddatathroughstochasticmethods,uncertainty analysisandcomputing timeare difficultiesof hydro-sedimentaryandprocess-basedmodels;
lack of realism in some cases, difficulty to take into accountaprioriconnectionsorgeologicalconceptsfor stochasticmethods;
extensiontoothersedimentaryenvironments,inclusion ofnewsedimentaryobjectsforhybridmodels.
4. Mainconclusions
4.1. Needsandpossibilityofcoupling
fittedtoconditioningdata,whichisthebasisandoneofthe main benefits of geostatistical techniques.In that case, process-based results may be used as constraints for geostatisticalmethods(databaseofmodellingparameters, trainingimages...).Thus,couplingbetweenthese approa-ches has been naturally identified: the introduction of stochastic approaches in hydro-sedimentary process modelling,andthecouplingofprocess-basedapproaches withmethodsofuncertaintyquantification.
Thefocalpointbetweenthetwothemescouldbefound aroundtheconstructionofa3Dstaticgeologicalmodel, eventhoughscalesandresolutionsareverydifferent.This resultingobjectcouldbeafederative,commonobjective wherethedifferentapproachescouldbecoupledthrougha nested-scale3Dgeologicalmodel.
4.2. Industrialneedsandchallenges
Thereareatleastthreemainscalesofmodelsusedin theindustry.
Thesimulationofhydro-sedimentaryprocessesisused forenvironmentalpurposes(continentalerosion,littoral evolution, ortransport and dispersion ofpollutants, for example).Thereisaneednowtointroducenewforcings suchasvegetationorbiology.Forancientsystems,their application may be limited by the difficulty of recon-structingpasthydrodynamicparametersfrom sedimenta-ryrecords(rainfallforexample). Achallengeisalsothe upscalingoferosionortransportlawsinordertosimulate geomorphological evolution over long geological time scales.
Reservoir modelling is mainly used for resource productionorsequestrationonhumantimescale (hydro-carbons, nuclear,water, CO2).A significant number of techniquesandmethods havealready beendeveloped, butthekey point remainsthe quantificationof uncer-taintiesthroughmulti-realizations,andthecalibrationto well data. Geostatistical methods may be used in an inappropriate way because they are easy to apply. However,whenavailabledataarescarce,itisessential tointegrategeologicalconceptsashybridmodelsdoor by the use of trends or additional constraints in stochastic methods (constraints could derived from seismic images).Upscaling is also a key issue in order tocorrectly transferinformationfrom geological static models to fluid-flow dynamic model (notably for complexenvironmentssuchascarbonates,where diage-neticimprintsarecrucial).
Basinmodellingisusedduring explorationto recon-struct the large-scale architecture of permeable and impermeable layers through the simulation of their evolution along geologicaltimes. One main difficultyis linkedtodataavailabilityandintegration,particularlyin termsofquantity,spatialdistribution,identificationand eliminationofaberrantdata,assimilationofnewdatainto existingmodels.
Anessentialstepinbasinmodellingistherestoration phase of initial stages with decompaction of previous deposits,butitistimeconsuming.Thereisaclearneedfor couplingwithgeodynamicalanddeformationmodelsto validatethebasin’sevolution.‘‘Global’’modelsintegrating
plate tectonics, palaeogeographical maps and climate evolution do exist now, but they must be used with caution,andthecriticalpointremainstheestimationofthe palaeo-reliefsandofthepalaeo-rainfalls.
For themodellingoflarge-scalefluidtransfers,a key pointisthecharacterizationofthepalaeothermicityandof the nature and geochemistry of the fluids, with a progressive transition towards full 3D thermo-hydro-mechanical models. Basin-scale fluid-flow simulation might benefit fromthe development made in reservoir production models (local grid refinement, inversion methods).
Forallthesemodels,thegrowingcapacityofcomputers andthepromisesofHighPerformanceComputing(HPC) open new areas for testing the coupling of complex phenomena. Ithas beennoted, however,that dialog or interconnection between modelsis difficultif notoften impossible,andthereforethereisaclearneedforshared accesstodifferentmodels(opensource,interoperability) andtodata(opendata).
5. Examplesofapproaches
Several contributions from the workshop have been selected for this thematic issue to illustrate the high diversityofmodellingapproachesusedinsedimentology, involvingawiderangeofspaceandtimescales.
Poirieretal.(2016)showtheapplicationof aRUSLE soil erosion model to compute denudation rates and simulate sediment supply from the Charente River catchment since 1500. The forcing parameters of the model are the climate (through the rainfall intensity) and the nature of the land cover (crops, pastures, or forests).Themodeltakesintoaccountthesensitivityof the soil to erosion and the topography. It correctly predicts present-dayCharenteRiversedimentloadand confirms thatthis contributionis minor comparatively totheinputfromtheGirondeEstuary.Theapplicationto the 16th and18th centuries shows that the sediment supplydidnotchangesignificantly,becausesoilerosion resulting from the 18th century’s deforestation was compensated by a drier climate reducing the average rainfall.Thecomparisonofthesimulatedsedimentload with the sediment record reveals the control of sedimentation (silt–sand alternations) by sub-decadal rainfallvariability.
Teles et al. (2016) present new developments on a process-based model for the simulation of submarine dilutedturbiditycurrents.TheCATSmodelisderivedfrom CellularAutomataconcepts,withaflowdistributionruled byabalancebetweenpotentialenergyandkineticenergy. Empiricallaws areusedfor waterentrainment, erosion, and depositionofseveral lithologies.Anewapproachis proposed, which takes into account the concentration profileofdifferentgrainsizesandtheflowcapacitytocarry sediments in suspension. The model can simulate a sequence of several turbidityevents in ordertopredict theresultingreservoirarchitectureandfaciesdistribution. The application to a synthetic topography (sinuous channelandunconfinedbasin)andtoarealcase(Makran P.Josephetal./C.R.Geoscience348(2016)473–478
accretionary wedge in offshore Pakistan) gives realistic results,inagreementwithobservations.
In subsurface, the building of a geological reservoir model is very dependent on the correlation scheme betweenwells,becausethecorrelationlinesaregenerally usedaslimitsofthemodellingunits.Lallieretal.(2016)
addressthequantificationofuncertaintiesonthe strati-graphiccorrelations,andthusontheconceptualgeological model whichisthebasisfornumericalmodelling.They generate several possible correlations between strati-graphic logs by developing a stochastic and sequential applicationoftheclassicDynamicTimeWarping(DTW) algorithm. The correlations can beconstrained by prior knowledgesuchascorrelationlinesextractedfromseismic interpretation.Thisnewtechniqueenablesustoquantify the cost of each correlation, using sedimentological knowledge, for example consistency with the slope palaeo-angle andwiththepalaeo-depositionalprofile in thecaseofacarbonaterampinsoutheasternFrance.This case study shows the strong impact of the correlation uncertainty on the facies distribution in the resulting reservoirmodel.
BeucherandRenard(2016)describenewgeostatistical methodsthathelptobuildgeologicalreservoirmodelsby distributingfaciesorlithotypesinspace:thiscanbedone inanestedmanner(heterogeneitieswithinsedimentary bodiesforexample),andcategoricalvariables(facies)and continuous properties(grade,porosity, permeability...) canbejointlysimulated.Thesesimulationmethodsare basedonaGaussianframework.TheTruncatedGaussian Simulation(TGS)hasfirstbeendevelopedtoreproduce orderedsedimentarydepositionalsequences:its flexibil-ityenables toaccountfor external constraints(trends) andtoeasilyconditiontonumerousdata.Pluri-Gaussian simulation (PGS) takes into account several Gaussian fieldsandenablesonetoreproduceverydiversetextures, at the level of the rock sample, the outcrop or the subsurface field.New developments are in progressto better simulate oriented/anisotropic shapes or high-frequencylayering.
Hamonetal.(2016)presentaninnovativeworkflowfor the3Djointmodellingoffaciesanddiagenesisatreservoir scale applied to a carbonate formation outcropping in Spain.Thestudyisbasedonadetailedsedimentological characterization,which ledtoadepositionalmodel and correlationofdifferentmodellingunitsthroughasequence stratigraphyapproach.Diageneticphaseswereidentified and quantified through thin sections analysis (point counting).Thesedifferentphasesareputinrelationwith thesedimentaryfaciesandabi-plurigaussiansimulation (Bi-PGS) is used to model both facies distribution and diageneticimprintsinaconsistentway.Thisapplication demonstratestheabilitytomodelheterogeneitieslinked both to sedimentation variability and postdepositional diagenetic development, and the need to integrate the sedimentaryand petrographic analysisinthemodelling workflow.
In order to evaluate the impact of sedimentary heterogeneity on CO2 storage efficiency, Issautier et al.
(2016)leadasensitivityanalysisona3Dmodelofafluvial meanderingreservoir, composedof stacked sandypoint
bars (first-order level of heterogeneity) embedded in a shalyfloodplain.TheCO2storagecapacityafter50yearsof injection canvary by more than50% between different realizations of the model, because of the different connectivitiesbetween pointbars. When asecond level ofheterogeneityisintroduced(shalyplugscorresponding totheinfillingofoxbowlakesinsidethemeanderingbelts), thefinal capacity can be reduced by 30% and dynamic simulationsshowastrongeffectonthepressurefield,on theshape oftheCO2plumeandontheCO2dissolution, whichimpactsthestorageefficiency.Acomparisonwith staticestimatesofthestoragecapacityhighlightsthat,in such heterogeneous reservoirs, dynamic simulations on severalgeostatisticalrealizationsarenecessarytoaccess therealstoragepotential.
Lastly,atbasinscaleandongeologicaltimescaleof several millions of years, Violette et al. (2016) test numerically the hypothesis of carbonate cementation duetometeoricrechargeofBathoniancarbonateaquifers at the edge of the Paris Basin during the Lower Cretaceous. They use a 1D reactive transport model, couplingpalaeo-fluid-flowsimulationandfluid-mineral geochemical reactions. With a parameter sensitivity analysis, they show that this process alone does not sufficetoreachthereductionby10%ofprimaryporosity observed in subsurfacein the basin’s centre, and that otherprocessessuchasinfiltrationofmeteoricwatersor upward migration of deeper fluids might probably be involved.
Acknowledgments
WethankassociateeditorSylvieBourquin(Universite´ deRennes-1)whoinvitedustogatherthisthematicissue andhelpedusinthereviewprocess.Weareverygrateful to our colleagues Guillaume Caumon (Universite´ de Lorraine), Richard Labourdette (TOTAL), Pierre Le Hir (IFREMER), Simon Lopez (BRGM), and Delphine Rouby (GETObservatoireMidi-Pyre´ne´es)whohostedwithusthe workshop ‘‘Modelling approaches in sedimentology’’ duringthe 14thFrenchCongress of Sedimentology.We also thank Sylvie Bourquin and Simon Lopez for their reviewofthisintroductivepaper.
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