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A NEW APPROACH FOR KIMBERLITE EXPLORATION USING HELICOPTER-BORNE TDEM DATA PRESENTED AT SEG 2018 Nasreddine Bournas Geotech Ltd. Jean Legault Geotech Ltd.

Alexander Prikhodko Geotech Ltd. Vitally Polianichko Kimang, Ltda

Karl Kwan Geotech Ltd. Sergei Treshchev Kimang, Ltda

SUMMARY In this paper, we propose a new exploration strategy fordetectingpipe-likestructuresfromairborneTDEMdata.Wefirst apply the Keating’s pattern recognition technique tothe EM resistive limit calculated from the early andmid-timedecaychannelsandtothemagneticanalyticsignalforpredicting conductive andmagnetic pipes. The automateddetection procedure yielded numerous solutions, whosenumber is downsized after a careful screening and fine-tuningoftheobtainedresults.Further,theselectedtargetsareclassifiedintoseveralcategoriesaccordingtotheirEM,magnetic and IP signatures. Finally, we perform 3DMVIand1DEM inversionon selected targets todetermine thesize,thedepthandthemagneticandelectricalpropertiesofthesetargets.

INTRODUCTION Airborne magnetic and electromagnetic surveys havebeen extensively used for kimberlite exploration. Mostkimberlitesoccur in stableArchaean cratons in swarms.They have distinctive magnetic and electromagneticsignatures, which are in general roughly circularanomalies with various diameters in surface and withcarrot-shapedextensionatdepth(SmithandKlein,1996).Kimberlites’ magnetic susceptibility is variable and itusuallyhigh.However,manyknownkimberlitesinAfricado not have a clearmagnetic signature, yet they exhibitelectromagnetic response due to contrasts in resistivitywithhostrocks(Macnae,1979).Inmanycases,thenear-surface weathered kimberlite portion and overlyingvolcano-sediments exhibit higher conductivity contrastwith the host rocks that can be detected by airborneelectromagneticsystems(Cunion,2009).InAngola,manylarge kimberlite pipes including the Catoca’s large pipehave a clear electromagnetic signature and nomagneticsignature (Le Roux and Steenkamp, 2014). Therefore,AEM techniques have proven as cost-effective for theexplorationofkimberlitepipesinAfrica.

In this paper, we propose a new kimberlite explorationstrategyandweshowresults from itsapplication toEMand magnetic data collected with a helicopter-borneelectromagnetic survey that was recently carried out inthe Cuango area, Angola. First, we apply the Keating’spattern recognition technique (Keating, 1995) to bothmagnetic analytic signal and EM resistive limit data forautomaticdetectionofmagneticandconductivepipe-like

structures, and then we perform a 3D magnetizationvector inversion (MVI), (Elis et al., 2012) and 1D EMinversion (Brodie, 2015) for selected targets for theirbetterdefinition.

PREDICTION METHOD

We apply an automated pattern recognition processbasedontheKeating’smethodtotheanalyticsignaldatato predict magnetic pipe-like structures. To implementthe prediction process we use a series of referencemodels composed of homogeneous magnetic verticalcylinders of various diameters ranging from 100m to500m. The model responses are then compared to thesurvey data using a linear regression analysis. Thisanalysisprovidesclusteredsolutions forpredictedpipeswith associated correlation coefficients (Keating andSailhac, 2004). Well-defined clustered solutions withassociated high correlation coefficients (>80%) aretypically retained whilst sparse and poorly clusteredsolutionsarenormallyrejected.

Unlikethemagneticdata,whicharepresentedasasinglechannel data, the TDEM data are collected in multiplechannels. To implement the prediction analysis,we firstconvert themultichannel EMdata to theResistive Limit(RL),andthenwecrosscorrelatetheobserveddatawiththereferencemodelresponseusingtheKeating’spatternrecognitiontechnique.TheRLisdefinedasastatewheneddycurrentshavefullypenetratedtheconductivebodyandtherateofchangeoftheinducedsecondaryfieldsisnegligible.TheRLconcepthas been extensively used for 2D and 3D modeling offrequencyandtime-domainEMdata(StoltzandMacnae,1997;SchaaandFullagar,2012). Intimedomain, theRLfor a step functionof theprimary field isdefinedas thetime-integral of the magnetic flux density using theconcept of 1st ordermagneticmoments (Smith and Lee,2002)givenbythefollowingequation(1),

𝐌(#) = −∫ 𝐁(𝑡)𝑑𝑡+

, = ∫ .𝐁(/)./

+, · 𝑡𝑑𝑡(1)

whereM(1) is the1st ordermagneticmomentandB, themagneticfluxdensity.

Themultichannel EM data are first converted to the RLaccording to equation (1). Next, a more complexkimberlite conceptual model is used for the predictionanalysis. It is composed of a surface conductive andweathered crater zone, locatedon topof a resistive andunweathered diatreme zone. The kimberlite pipe ishosted by resistive rock featuring the Precambrianbasement. A moderately conductive thin overburden

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layeroverliesthewholemodel.ThismodelfeaturesmostoftheconductivekimberlitepipesknowninAngola.The forward calculations are performed with the 3DCSIRO Samair Code (Raiche et al., 2007) using variousmodeldiametersofthekimberlitepipesrangingfrom100mto500m.Anamountofchargeabilityisincludedinthecrater infill sediments to account for IP effect in theEMdata.Figure 1 displays the forwardmodeling results and thecalculatedresistive limit fora300m-diameterkimberlitemodel.Only the first twentydecay channels (Figure 1b)are used to calculate the RL (Figure 1c) to avoid theinclusionofnegativedecaysassociatedwiththeIPeffect.The RL grid (Figure 1d) depicts a well-focused circularresponse above the kimberlite pipe model alike themagneticanalyticsignal.

Figure 1: Calculated EM decays for a 300m-widekimberlitepipe;a)Alldecaychannels(0.055-8.08ms),b)First twenty decay channels (0.055-0.766 ms), c)Resistive limit profile, and d) Resistive limit grid imagewiththepipemodeloutline(whitecircle).Theblacklinerepresentsthetraceofthecentralline.APPLICATION AND RESULTS Weapplythepredictionanalysis tothehelicopter-borneTDEM data from a survey carried out over the Cuangoarea,locatedinnortheasternAngola(Figure2).AEMsurveyTheaimofthesurveywastodetectmagnetickimberlitepipes with the gradiometer system and to map localconductive zones with the EM system that may beassociated with conductive crater infill volcano-sediments and conductive weathered kimberlite zones.

The high-resolution survey combined EM and magnetichorizontalgradientmeasurementsandcoveredanareaofapproximately 2,000 square kilometres. The traverselines were flown in the north-south direction andwerespaced at 150m apart. The tie lines were flown in theeast-west direction and were spaced at 1,500 m apart.Thehelicopterwasflyingatameanspeedof80km/handatanaveragealtitudeof75maboveground.Theaveragegroundclearanceofthehelicopter-borneEMtransmitter-receiversystemwas40mandthemagneticgradiometrysystemwaslocatedat50maboveground,inaverage.Geologyofthesurveyarea

The study area lieswithin the Congo-Kasai Craton. It islocated in the northeast of Angola within the Lucapastructure,aNEtrendingriftsystemformedfollowingtheGondwanabreak-upduringtheJurassic(Figure2).

Figure2: KimberliteprovincesofAngolaandassociatedLucapa rift zone. The study area is located in north-eastern Angola (modified after Pereira et al., 2003 andEgorovetal.,2007).The rift zone, which has facilitated the emplacement ofalkaline,carbonatiticandkimberliticmagmas(Pereiraetal., 2003), is known to hostmost of the diamondiferouskimberlitesinAngola(Jelsmaetal.,2009).Locally, the survey area lies within the Cuangodiamondiferous province. Diamonds are extracted fromrecentalluvialdepositsand theCretaceoussedimentsofthe Calonda Formation that unconformably overlie thePrecambrianbasementrocks.MagneticpipespredictionresultsFigure 3 shows the predicted magnetic pipe-likestructuressuperimposedontheanalyticsignalimageforthe eastern portion of the survey area. The white dotsrepresent the centresof thepredictedpipe-like featuresusing various model diameters. Only solutionscorresponding to correlation coefficients > 80 %,normalized relative errors < 13 % and amplitudes > 3nT/mareretainedandtherestofsolutionsarerejected.

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Figure3: Predictedpipe-likemagneticstructures(whitedots)over thecolour shadedreliefof theanalytic signalimageNumerous solutions are obtained and most of themappeartobealignedalonglinearandcurvilinearfeatures.It is unlikely that all these solutions represent potentialtargets; however, many identified isolated anomaliesappear to representgoodcandidates forkimberlitepipeexploration. These targets are occurring in theeasternmost edge of this area in association with localconductiveEManomaliesasshowninthenextsection.Itis worth mentioning, that a number of magnetickimberlite pipes are known outside of the survey area,near to its eastern boundary. Therefore, thesemagnetictargets may belong to known kimberlite clusters of thenearbyCuango-Cucumbiprovince.ConductivepipespredictionresultsFigure 4 shows the predicted conductive pipesrepresented by white dots. The retained solutionscorrespond to correlation coefficients>75%and toRLamplitudes>50pT·ms/A;however,onlytargetsthatarerepresented by well-defined clustered solutions have ahighconfidenceandarethereforeretainedforfollow-up.Solutions that are represented by sparse and poorlyclustered solutions are rejected from further analysis.There are 04 well-defined clusters occurring in thesoutheasternedgeofthistargetareathatdeservefurtheranalysis.Theseareoutlinedbytheblackrectangle.

Figure 4: Predicted conductive structures (white dots)overthecolourshadedreliefoftheResistiveLimitimage.Targetingresults

Given the large number of obtained solutions, furtherscreening and classification are required before targetselection and prioritization. Only solutions associatedwith high correlation coefficients and forming well-defined clusters are considered for further screening.Next, the targets are classified into 04 categoriesdependingontheirmagnetic,EMandIPsignatures.Sometargets have clear and well-defined magnetic and EMsignatures and others have either EM or magneticsignature. Additionally, for some targets, IP effect isobserved in the EM decays. This IP effect, which ingeneral,isindicatedbythepresenceofnegativelatetimedecays, represents an important criterion for kimberliteexploration, since it may be linked to chargeable lakesediments (clays) thatmayoccurwithin the crater zoneofthekimberlitepipe.

Two targets, namely K231 and K228 are selected for afurtherstudyandarepresentedhere.

• TargetK231

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Figure 5: EM and magnetic inversion results for thetargetK231ofFigure4;a)EMdecays(linearscale),b)EMdecays in log scale (blue) and AIIP curve (red), c) 1Dinversion results, d) CVG profile, e) 3D MVI results, f)conductivitydepthslice(10m),andg)3DMVIdepthslice(100 m). The dashed line is the suggested kimberliteoutlineandtheboldlineisthesectiontrace.Figure 5 presents the EM and magnetic responses andtheir inversion results for this target. The latter belongstothe1stcategory(circularmagneticanomaly,occurringin coincidencewithEManomaly and includes IP effect).The IP effect is clearly indicated by the presence ofnegativelatetimedecaysandaclearAIIPanomaly(Kwanet al., 2015), (Figure 5b). The 1D EM inversion results(Figure 5c) indicates the presence of a resistive featureattributed more likely to unweathered kimberlite pipe.Thethinconductivelayeroccurringontopoftheresistivefeature may be associated with chargeable andconductive sediments (clay) and/or with weatheredkimberlite.Theresistivefeatureoccurringincoincidencewith a magnetic structure is supporting its kimberlitenature. The topographical relief low may represent asmall crater. On the planmap, the suggested kimberlitestructure is roughly oval-shaped with estimateddimensionsof400m×500masshowninFigures5fand5g.

• TargetK228TargetK228belongstothe4thcategoryandisassociatedwith a moderately strong early and mid-time EMresponsewithIPeffectandwithnomagneticassociation.The resistivity depth imaging (RDI) section shown inFigure 6e indicates the presence of a shallow seatedconductive feature similar to those observed over non-magnetic kimberlite pipes occurring in other areas. Theconductivefeature,ofapproximately50minthickness,ispotentiallyassociatedwithaconductiveweatheredzoneand/or chargeable sediments that typicallyoccuron topofkimberlitestructures.

Figure6:EMandmagneticresponsesforthetargetareaofFigure4;a)Analyticsignal,b)RDIdepthsliceat50m,c) CVG profile, d) VTEM decays and AIIP, and e) RDIsection. The coloured circles in a) and b) correspond topredicted solutions calculated from the EM ResistiveLimit (usingvariousmodeldiameters) and thebold linerepresentsthesectiontraceacrossthetargetK228.CONCLUSIONS Theproposednewexplorationapproachappliedtobothmagnetic data (Analytic Signal) and EM data (ResistiveLimit) helped predict numerous potential pipe-likestructures within the Cuango area. Further analysis ofselected targets using 1D EM and 3D MVI inversionshelpedbetterdefinethesestructuresanddeterminetheirshapeandsize.Theseresultsconfirmedtheirlinktopipe-likestructuresconsistentwithkimberlitepipes. ACKNOWLEDGEMENTS WearegratefultoKIMANGLtdaofAngolaforpermissiontopublishtheseresults.REFERENCESBrodie, R.C., 2015, GALEISBSTDEM: A deterministicalgorithm for 1D sample by sample inversion of time-domain AEM data–theoreticaldetails: GeoscienceAustralia.Cunion, E., 2009, Comparisonof groundTEMandVTEMresponses over kimberlites in theKalahari of Botswana,Exploration Geophysics, 40, 308–319,https://doi.org/10.1071/eg09019.Egorov, K.N., E.F. Roman’ko, V.T. Podvysotsky, S.M.Sablukov, V.K. Garanin, and D.B. D’yakonov, 2007, Newdata on kimberlite magmatism in southwestern Angola:Russian Geology and Geophysics, 48, 323–336,https://doi.org/10.1016/j.rgg.2006.08.001.Ellis,R.G.,B.deWet,andI.N.Macleod,2012,Inversionofmagneticdatafromremanentandinducedsources.ASEGExtendedAbstracts 2012: 22ndGeophysical Conference,1–4,https://doi.org/10.1071/aseg2012ab117.

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