Outline
 Contributions to geoneutrino andreactor antineutrino signal at SNO+
 Modeling the geoneutrino flux
 The 3D model of the crust
surrounding SNOLAB Geoneutrino signals from the different
crustal reservoirs
 The next steps: focusing on the closecrustDetecting geoneutrino signals around the world
In one site, for each radioisotope (238U, 232Th) the expected geoneutrino signal
is the sum of three contributions:

EXP = total expected signal
LOC = crust of the region within some
hundreds km from the detector
FFC = Far Field CrustM = mantle signal

SEXP = SLOC + SFFC + SM

12231 – Huang et al. 2014, Geochemistry, Geophysics, Geosystems.
2 - Fiorentini et al 2012 , Physical Review D. 3 - Strati et al. 2015, Progress in Earth and Planetary Science.

Reactor antineutrinos signal at SNO+
• Reactor antineutrinos are the most
severe background for geoneutrino
measurements.
• In the Low Energy Region (LER) weobserve an overlap between geoneutrino
and reactor antineutrinos spectra, with asignal ratio SLER/SGeo ~ 1 at SNO+
• Bruce Power Station includes 8nuclear reactors and produces ~22 GWof thermal power.

Bruce PowerStation• Although the thermal power of Bruce
reactors corresponds to 1.9% of theglobal thermal power, they contribute toabout 38% of total reactor antineutrinosignal SReact at SNO+.
Baldoncini et al. 2015 – Physical Review D 91(6)Reactor antineutrinos and geoneutrino at SNO+
• The temporal fluctuations (~10% at 1σ) of reactor
antineutrino signal resembles the temporal profileof the Bruce Power Station effective thermal power.
• The geoneutrino signal of the Local Crustcorresponds to ~ 50% of the total crustal signal.
Geoneutrinos signal1(TNU)
Local Crust

15.6 +5.3 -3.4

Rest of the Crust

15.1 +2.8-2.4

Cont. Lithos. mantle

2.1 +2.9 -1.2

Mantle9TOTAL

40 +6 -4

Reactor antineutrinos signal2 (TNU)
LERFER

Bruce reactors

17.3 +1.0 -0.7

73.7+2.0 -1.8

Rest of reactors

31.2 +0.9-0.8

118.9 +2.8 -2.6

TOTAL

48.5 +1.8 -1.5

192.6 +4.7-4.4

1 - Huang et al. 2014 Geoch. Geoph. Geosys.
2 - Baldoncini et al. 2016 Journal of Physics: ConferenceSeries.

Modeling the geoneutrino flux
GGε νX ρ ( r ′) a X ( r ′)φ (X ) =G G 2 dr ′∫4π V
R − r′UC

U and Th abundances frompublished database

Literature data, geological maps
and interpreted seismic profiles

SNO LAB

Upper Crust
Middle Crust
Lower CrustΦ (a ; ρ ; dV)

MCLC

U and Th abundances inferredfrom seismic arguments

Estimations from seismic velocities

Geochemical uncertainties~ 15%

Geophysical uncertainties~ 5%

The 3D geophysical model• The first step of the construction of the 3D model isdefining the local crustal structure and Moho
Discontinuity depth.

SNOLABUCMCLC?

• The boundaries between Upper, Middle andLower Crust will be identified on the base ofseismic velocities.

The necessary geophysical inputs come mainly from seismic experiments:
ACTIVE METHODS

δv ~ 2%• Refraction surveys
2D Velocity Models• Reflection surveys
PASSIVE METHOD

δH ~ 1%• Teleseismic data: the crustal thickness is inferred through the analysisof data from distant earthquakes acquired by a network of seismicstations.

The 3D model of the crust surrounding SNO+
• The refined 3D model of the local crust isbuilt using refraction seismic data collectedin the last 30 years.
• Reflection seismic surveys andteleseismic acquisitions provide additional
constraints on the crustal thickness.
Huang et al. 2014, Geochemistry, Geophysics, Geosystems

Experiment

Main investigated areas N° of lines

Type

Reference

Sudbury Basin

2

Refraction

Winardhi and Mereu (1997)

Superior Province

2

Refraction

Winardhi and Mereu (1997)

Kapuskasing Structural Zone

5

Refraction

Percival and West (1994)

COCRUST

Grenville Province

4

RefractionMereu et al. (1986)

O-NYNEX

Appalacchian Province

1

Refraction

Musacchio et al. (1997)

1

Refraction

Epili and Mereu (1991)

1

Reflection

Spence et al. (2010)2

Reflection

Brown et al. (1982)

LITHOPROBE

GLIMPCEGreat Lakes

COCORP

Michigan BasinModeling the TMC, TLC and MD
InputsDepth-controlling points
obtained by 15 refractionlines, 3 reflection lines anddata from 32 seismographicstations.

N°
pointsTop of MC (TMC)343

Top of LC (TLC)

343

Moho discontinuty (MD)392

ORDINARY KRIGING: a stochastic estimator that considers the spatial continuity ofinput variables and infers the values in unobserved locations providing the result in termof probability: it’s possible to quantify the estimation errors.

Output• Estimated maps ofTMC, TLC and MD depthwith a 1 km × 1 kmresolution.
• Maps provides theNormalized EstimationErrors (NEE).

The Ordinary Kriging method
GENERAL ESTIMATOR

nz *(x0 ) = ∑ λi z(xi )i =1

x0 = target pointz( xi ) = measured samples

λi = weight assigned to the samples
Different weights on the base of the spatial correlation
Goals:• Minimization of the variance of the estimate (kriging variance)• Distribution of the predictions similar to the distribution of thereal values.

Spatial variability of the crustal discontinuity in Sudbury region
Experimental Semi-Variogram (ESV):

1 m( h )2m(h) = number of sample()()
γ (h) =Zx+h−Zx[]∑iivalue pairs within distance h2m(h) i =1The number and the dimensions of the lags
depend on features of the dataset and spatial
distribution of the samples.
Variogram Map

Top of the Lower Crust

The semivariogram iscomputed for different
directions in the space: inthe first lags there aren’t
preferred directions ofvariability.
For each surface, an omnidirectional ESV with 12 lags of 30 km is computed.

The semivariogram modeling• A theoretical function (e.g. spherical, exponential, gaussian) is used todescribe the experimental semivariogram.
• The model parameters are tested and the best fit is chosen.
Moho Discontinuity

1) NUGGET EFFECT
γ(0) ~ 5% of the total spatial
variabilityA priorivariance
Sill(20.2 km2)

ESV

There is a good correlationbetween adjacent points fromdifferent seismic lines.

Model2) SPHERICAL STRUCTURE
For h > ‘Range’ the data are
not spatial correlated and theγ is constant andcorresponds to ‘Sill’.

N°of pairs
Nugget effect(1.8 km2)

Range (269 km)

The Cross Validation
This procedure allows for testing different models and for verifying thecompatibility between the dataset and the structural model.
• Each sample is in turn assumed
as a missing value and theestimates are realized.
• For each sample we have thereal value and the estimatedvalue.

Moho Discontinuity

MSE = 0.005
VSE = 1.04

Mean Standardized Errors Æ 0Variance Standardized Errors Æ 1The results of the spatial interpolation
Map of the crustal depths: the continuous models of the three surfaces have beenobtained in the form of a regular GRID file. The estimations in each 1 km x 1 km cell are
performed on the base of the study of spatial correlation.

Normalized Estimation Errors (NEE) maps: the uncertainties of the estimation interms of variance are obtained and are normalized with respect to the estimated valuesof the depth. They are expressed in the maps in percentage.

Moho Discontinuity

SNO LABUCMCLC?
?
42.3 ± 2.6 km

The depth map of the MD highlights
the presence of the Grenville Front
Tectonic Zone and theKapuskasing Structural Zone.

In the velocity models, the Moho discontinuity
is marked by an evident increase of the Pwave velocity. It constraints the averagecrustal thickness at 6% level.

Top of the Lower Crust

SNO LABUCMCLC?
26.7 ± 1.4 km
42.3 ± 2.6 km

The depth of the TLC depth is ratherconstant in the Superior Province(about 25 km). In the Grenville
Province is variable in a range

The values of the uncertainties arecomprised between 18 and 40 km.

close to 1% in the sampled locations.

Top of the Middle Crust

SNO LABUCMCLC

20.3 ± 1.2 km
26.7 ± 1.4 km
42.3 ± 2.6 km

According to the model, the Upper
Crust accounts for about half of thethickness of the bulk regional crust

The higher values of the uncertainties

and reaches the higher thickness inare obtained in the southwest of thethe Grenville Province.

area far from the detector.

Summary of geophysical uncertainties• The realization of the continuous models of depth for the three surfaces allows

for the calculation of the thicknesses and volumes of UC, MC and LC.
• These results, together with densities, permitted to estimate the masses ofthe main crustal reservoirs together with their uncertainties.
CRUST 1.0*

Huang et al. 2014

M [1018 kg]

Thickness

Volume [106 km3]

ρ [g/cm3]

M [1018 kg]

UC

6.6

20.3± 1.1

4.2 ± 0.2

2.73 ± 0.08

11.5 ± 0.6MC8.1

6.4 ± 0.4

1.3 ± 0.1

2.96 ± 0.03

3.8 ± 0.3

LC8.0

15.6 ± 1.0

3.2 ± 0.2

3.08 ± 0.06

9.9 ± 0.6

Total

22.7

42.3 ± 2.6

8.7 ± 0.5

-25.2 ±1.6

• The relative uncertainties of the reservoirs masses are of ~ 6%.
• Respect to CRUST 1.0 this crustal model of the region surrounding SNOLAB
estimates geophysical uncertainties and it is more refined because includes
local input data.
* Laske et al. [2013] at http://igppweb.ucsd.edu/~gabi/rem.html

Refining the Upper CrustInput• Geological Map of North America - 1:500000 scale• Geological cross sections• Interpreted seismic profiles
7 lithologic units in the Upper Crust are clusteredon the base of compositional, stratigraphic andevolutional arguments.
Paleozoic sediments (Great Lakes)
Hurionan Supergroup and Sudbury Basin rocks
Granite or granodioritic intrusions
Sudbury Igneous Complex
Volcanics and metavolcanics rocks
Tonalite and tonalite gneiss
Central Gneiss Belt

(Reed et al., 2005)

Modeling the 7 lithological units
Motivations
A
Although the volumes of theseoutcropping subreservoirs are often
small, their U and Th content canvary of one order of magnitude.

A’AB

Easton RM 2000

A’

• The contacts between the 7 dominant
lithological units in the physical model ofupper crust are defined using 16
interpreted crustal cross sections ofthe area.
• For each lithologic unit the top and thebottom surfaces are obtained by spatial
interpolation.

B

The numerical 3D Model
Input

GRIDs of surfaces of MD, TLC, TMC and the top and the bottom ofeach lithological unit.
OutputNumerical 3D MODEL made up of VOXELS of
1 km x 1 km x 100 m. Total Number of voxels ~ 9 x 107.

XYZGNESVirtual sections of the 3D model
Huronian Supergroup
MCLC

Sudbury IgneousComplex

MCLCTonalite gneiss
MCLC

Central Gneiss Belt

Geoneutrino signal at SNO+ from the local crust• After the refinement, the regional geoneutrino signal expected at SNO+ decreases
from 18.9 +3.5 -3.3 TNU (Huang et al. 2013) to 15.6 +5.3 -3.4 TNU (Huang et al. 2014).
• The Huronian Supergroup is predicted to be the dominant source of the geoneutrinosignal and the primary source of the large uncertainty.
Lithologic unit of UCVol. (%)

U (ppm)Th (ppm)

S(U+Th) [TNU]

Tonalite/Tonalite gneiss (Wawa-Abitibi)

29.0

0.7 +0.5 -0.3

3.1 +2.3 -1.3

2.2 +1.4 -0.9

Central Gneiss Belt (Grenville Province)

14.5

2.6 +0.4 -0.4

5.1 +6.0 -2.8

2.1 +0.4 -0.3

(Meta)volcanic rocks (Abitibi sub-province)

1.4

0.4 +0.4 -0.2

1.3 +1.2-0.6

0.02 +0.01 -0.01

Paleozoic sediments (Great Lakes)

0.7

2.5 +2.0 -1.1

4.4 +1.6 -1.2

0.05 +0.04 -0.02

Granite or granodiorite (Wawa-Abitibi)

1.0

2.9 +1.6 -1.0

19.9 +8.4 -6.0

0.5 +0.2 -0.1

Huronian Supergroup, Sudbury Basin

1.3

4.2 +2.9 -1.7

11.1 +8.2 -4.8

7.3 +5.0 -3.0

Sudbury Igneous Complex

0.1

2.3 +0.2 -0.2

10.6 +0.7 -0.7

0.8 +0.1 -0.1

Middle Crust

15.0

0.8 +0.5 -0.3

3.5 +2.3 -1.6

1.2 +0.7 -0.4

Lower Crust

37.0

0.2 +0.2 -0.1

1.4 +1.8 -0.7

0.7 +0.6 -0.3

2014
• First refinedmodelNov 2015• Refined characterizationof the unit
• Planning of the samplingMay 2016• Sampling of the HS unit
• Measurements withHPGe detectors.

2017• New refined modelFocusing on close crustContribution to the crustal geoneutrino signal
48 %

26 %
440 km X 460km

26 %
50 km X 50km
SNOLAB

92% of the signalof the HS-SB

Global crustal model LOcal Crust (LOC)
Huang et al 2013

Huang et al 2014

CLose Crust (CLC)
New 3D geophysicaland geochemical modelReference geological map
Bedrock Geology of Ontario map 1:250,000-scale. Ontario Geological
Survey, Miscellaneous Release-Data 126, 2003

Close Crust(CLC)
50 x 50 km

Local Crust(LOC)
440 x 460 km

Rock sampling in the CLC
TOTAL SAMPLES = 112

20The sampling has been planned considering:• exposure surface of reservoirs (A/S ~ 15 km2)
• estimated volume• proximity to the detector• accessibility to the outcrops

18
16

10

14

Area (%)

12

9

10
8

2
6
4

7

12

4
3

18

6

5

92

44

2

1

1

3

1

1

1

0
11

15

17b

18a

Gneisses Tonalite suite

18c

19a

19b

20a20b

Huronian Supergroup

2130a

28a28b28c

29a

Sudbury IgneousComplex

29b30b40

41

Grenville Front
Tectonic zone

43