Transcript Igneous thermobarometry

Reservoir mixing
408/508 Lecture 8-9
5 minutes
• Allow for questions from last week;
• Talk about resources within department
for isotopic measurements;
• Quick resources for phase chemistry;
• Talk about projects.
5 minutes- additional web
resources
• GEOROC - modern volcanic database
• USGS pluto - any rocks from the US,
major and traces only;
• CONTACT 88- Barton database - agevolume (= flux) and depth of
emplacement values for western US
• DEEP Lithosphere data - global
• PetDB - for oceanic rocks
More rock names
• These are rocks that are
petrographically characterized by the
criteria given in the first lectures;
• The additional names are only meant to
inform the reader about the unusual
characteristic of these rocks.
Komatiite
• Super High temperature magmas
originating form the mantle from depths
of up to 1600 C;
• Low SiO2 (so they are basalts), high
MgO, up to 40%;
• Found in cratons and when in younger
settings, related to hot jets in the mantle
Shoshonite
• Highly potassic calc-alkaline rocks;
• Found in a variety of convergent margin
settings;
• Origin still highly debated
• Source is either K-enriched crust or mantle;
• Appear to be more common in collisional
settings
Boninite
• Boninite is a mafic extrusive rock high in both magnesium and
silica, formed in fore-arc environments, typically during the early
stages of subduction. The rock is named for its occurrence in
the Izu-Bonin arc south of Japan.
• It is characterized by extreme depletion in incompatible trace
elements that are not fluid mobile (e.g., the heavy rare earth
elements plus Nb, Ta, Hf) but variable enrichment in the fluid
mobile elements (e.g., Rb, Ba, K). They are found almost
exclusively in the fore-arc of primitive island arcs (that is, closer
to the trench) and in ophiolite complexes thought to represent
former fore-arc settings.
•
They are actually high Mg andesites, or just andesites…
Adakites
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•
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Adakites include a range of resulting rock types: they are recognized by
specific chemical and isotopic characteristics, mainly high Sr/Y and
La/Yb ratios and low Y and Yb trace element content. Adakites have, in
the literature, the following reported composition: SiO2 >56 wt percent,
Al2O3 >15 wt percent, MgO normally <3 wt percent, Mg number 0.5, Sr
>400 ppm, Y <18 ppm, Yb <1.9 ppm, Ni >20 ppm, Cr >30 ppm, >Sr/Y
20, La/Yb >20, and 87Sr/86Sr <0.7045.
Volcanic or intrusive rocks that originated from crustal sources at great
depths - without plag but with gar in residue
Originally thought to be slab melts, they could be all kinds of other stuff
such as delaminated crust melts, or melted forearcs that underwent
subduction erosion.
QuickTime™ and a
decompressor
are needed to see this picture.
Homework #6
• Plot the Sr/Y vs. Y for the Rotberg data
and determine if his rocks (or at least
some) are “adakites”.
• How do your findings (adakite or not)
compare to the REE patterns of these
rocks?
• What is the possible origin of these
adakites?
I-type and S-type granitoids
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An old Chappel and White discrimination between sed-derived and igderived granitoids;
Different people use different criteria:
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–
–
–
–
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Isotopes
Mafic phases
Types of enclaves
Silica enrichment
Etc.
I suggest using ACKN - peraluminous granitoids are S and
metaluminous are I.
S-types typically have two micas and garnet
QuickTime™ and a
decompressor
are needed to see this picture.
I vs S significance
• Realistically, an I type granitoid can be 70% I and 30 % S.
• S-types are probably more relevant when found, primarily
because they are marking the beginning of a tectonic melting
cycle in the crust.
EXAMPLE - the Wilderness granitoid in the Catalina Mts. Is clearly
S-type yet it forms at a time when many I type rocks preceed its
emplacement and other formed later. Its presence may signal
the shallow underplating of a new piece of crust underneath
Arizona.
Mixing and Box Models: Motivation
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•
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Much of geochemistry consists of measuring the compositions of natural
samples and trying to make sense of the measurements.
What sort of conclusions can usefully be drawn from such data?
– What source or sources contributed to the observed samples?
– What process or processes acted on the source to produce the observed
samples?
The fundamental physical law used to trace matter from sources through
processes to products is conservation of atoms (modified by radioactive
decays)
– Every process is either a differentiation, which takes a uniform source and
makes two or more distinct products (e.g., core formation, partial melting,
fractional crystallization…)
– Or a mixing process, which combines two or more distinct sources to make
a range of products with intermediate compositions or, in the extreme, a
uniform complete mixture.
Mixing Theory
• Geochemistry often tries to model variations in measured composition
as the result of mixing of a small number of components [N.B. a
different use of component from the thermodynamic usage] or end
members
– This reduces highly multivariate data to a few manageable
dimensions
– It allows identification of the end members with particular source
or fluxes, hence a meaningful interpretation of data
– Many geochemical processes are easily understood in terms of
mixing or unmixing:
• river water + ocean water = mixing
• primary liquid – fractionated crystals = unmixing
• We will work out the mixing relations for several spaces:
– Element-element plots
– Element-ratio plots (including elemental and isotope ratios)
– Ratio-ratio plots
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Mixing Theory
• Mixing is simplest to see and understand when there are only two end
members: Binary mixing
• For concreteness, instead of a bunch of general symbols, let’s do all
this with two end members, Archean gneiss (a) and basalt (b), with
the following compositions:
a
b
[Sr]
100 ppm 400 ppm
[Nd]
2 ppm
20 ppm
87
Sr/86Sr
0.712
0.704
143
Nd/144Nd 0.511
0.513
• The same relationships will apply for mixing of major elements
as for trace elements.
• The same relationships will apply for ratios of major elements,
ratios of trace element concentrations, and ratios of isotopes.
– I’ll leave it up to you to generalize the specific equations
from this lecture, rather than the other way around.
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Binary Mixing I: element-element
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•
•
•
•
This is the simplest case. Binary mixing in concentration-concentration space
always generates lines.
Let mixtures be generated with mass fraction fa of end member a and fb of
end member b, such that fa + fb = 1.
Then for two species, say Sr and Nd, we have conservation of atoms and
mass in the form
[Sr]mix = fb[Sr]b + (1 – fb)[Sr]a
[Nd]mix = fb[Nd]b + (1 – fb)[Nd]a
This can be written
[Sr]mix – [Sr]a = fb([Sr]b – [Sr]a)
[Nd]mix – [Nd]a = fb([Nd]b – [Nd]a)
Dividing these two equations gives the equation of the mixing relationship in
([Sr],[Nd]) space:
Sr b  Sra
Sr mix  Sra 
Nd mix  Nd a 

Nd b  Nda
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Binary Mixing I: element-element
Sr b  Sra
Sr b  Sr a
Sr mix  Sra 
Nd mix  Nd a 

Nd b  Nda
Nd b  Nd a
•
Passing through points ([Nd]a,[Sr]a) and ([Nd]b,[Sr]b)
•
This is the equation of a line with slope
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Binary Mixing I: element-element
•
If you know the compositions of the end members, you can solve for fb using
the lever rule:
Sr mix  Sra Ndmix   Nda
fb 

Sr b  Sra
Ndb  Nda
•
•
If you don’t know the end members, but only the data, what can you learn from a graph
showing a linear correlation?
– You can infer that if generated by mixing there are only two end members, otherwise
the data would fill a triangle
– You can infer that both end members lie on the mixing line, outside the extreme
range of the data on both ends if they must have positive amounts (additive mixing)
Because mixing is linear in concentration space, you can use linear least squares analysis
to interpret data in any number of dimensions for any number of end members.
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Binary Mixing II: element-ratio
• In geochemistry we very frequently work with ratios, either isotope
ratios or ratios of concentrations.
– Sometimes a ratio is all you can measure accurately
– Sometimes ratios have significance where concentrations are
more or less arbitrary (example: during fractionation of olivine
from a basalt, [Sr] will change because it is incompatible and the
amount of liquid is decreasing, but [Sr]/[Nd] will not)
• You might think that the 87Sr/86Sr ratio of mixtures could be obtained
in the same way as for [Sr]:
(87Sr/86Sr)mix = fb (87Sr/86Sr) b + (1 – fb) (87Sr/86Sr) a
•
•
You would be wrong!
The isotope ratio of the mixture is going to be weighted by the concentration of Sr in
each end member
– More generally, the weighting of ratios in the mixture is controlled by the
denominator of the ratio, in this case 86Sr.
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Binary Mixing II: element-ratio
• Let’s do it right: we have
[87Sr]mix = fb [87Sr] b + (1 – fb) [87Sr] a
[86Sr]mix = fb [86Sr] b + (1 – fb) [86Sr] a
• Taking the ratio of these, we have
 
 b
fb 87Sr
87
 
 a
 1  fb  87 Sr
Sr 
b
a

86 
 Sr mix fb 86 Sr  1  fb  86 Sr
•
And substituting [87Sr] = (87Sr/86Sr)[86Sr] for a and b:
87
Sr 
86  
 Sr mix
•
fb
87 Sr 
Sr 86   1 fb  86Sr
b  Sr 
b
 
86
87Sr 

a 
86 Sr a
 
fb 86 Sr   1 fb 86 Sr
b
a
Because differences in isotope ratios are much smaller than differences in
concentrations, we can approximate this using [Sr] instead of [86Sr] as the weighting
factors.
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Binary Mixing II: element-ratio
• Now let’s consider plotting the isotope ratio of the mixture against an
elemental concentration, perhaps [Nd].
• If we eliminate fb between the mixing equation for (87Sr/86Sr) and [Nd],
we obtain the following equation (using the approximation Sr ~ 86Sr):
87 
87 
Sr
Sr
A86   B[Nd]mix 86   C[Nd]mix  D  0
 Sr mix
 Sr mix
A  [Nd]b [Sr]a  [Nd]a [Sr]b
B  [Sr]b  [Sr]a
87Sr 
87Sr 
C  [Sr]a 86   [Sr]b 86 
 Sr a
 Sr b
87Sr 
87 Sr 
D  [Nd]a [Sr]b 86   [Nd]b [Sr]a 86 
 Sr b
 Sr a
• What curve has general equation Ax +Bxy +Cy + D = 0?
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Binary Mixing II: element-ratio
• In general, element-ratio mixing generates a hyperbola.
– The only case in which it is linear is B = [Sr]b–[Sr]a = 0
• The index of curvature r = [Sr]b/[Sr]a tells you “how
hyperbolic” the hyperbola is going to be.
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Binary Mixing III: inverse element-ratio
• Although there is nothing special about the element-ratio case A/B vs.
B (thus (87Sr/86Sr) vs. [Sr] is still hyperbolic), there is an especially
useful test for mixing if you plot A/B vs. 1/B (in this case, (87Sr/86Sr) vs.
1/[Sr]).
– Going back to our hyperbolic equation, if we replace [Nd]mix, [Nd]a
and [Nd]b with [Sr]mix, [Sr]a and [Sr]b we have:
87Sr 
87 Sr 
A86   B[Sr]mix86   C[Sr]mix  D  0
 Sr mix
 Sr mix
A  [Sr]b [Sr]a  [Sr]a [Sr]b  0, B  [Sr]b  [Sr]a
87Sr 
87Sr 
C  [Sr]a 86   [Sr]b 86 
 Sr a
 Sr b
87 Sr  87Sr  
D  [Sr]a [Sr]b 86   86  
 Sr b  Sr a 
87 Sr 
1
 0 , which is a line.
• Or, B86   C  D
[Sr]mix
 Sr mix
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Binary Mixing III: inverse element-ratio
• Mixing in A/B vs. 1/B space always generates a line.
• The value of r = [Sr]b/[Sr]a now controls how hyperbolic the spacing of
equal increments of mixing fraction are along the line. Since linear
correlation is easy to calculate, it is much easier to test whether data are
consistent with binary mixing in this space than in ratio-element space.
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Binary Mixing IV: ratio-ratio
•
•
•
Our final case is plots of ratios against ratios, whether isotope ratios, trace
element ratios, or major element ratios.
For example, let’s do (87Sr/86Sr) vs. (143Nd/144Nd).
We now have two equations of the same form:
87 Sr 
86  
 Sr mix
143 Nd 
144  
 Nd mix
87 Sr 
87 Sr 
fb Sr b 86   1  fb Sr a 86 
 Sr b
 Sr a
fb Sr b  1 fb Sr a
143 Nd 
143 Nd 
fb  Nd b 144   1 fb  Nd a 144 
 Nd b
 Nd a
fb  Nd b  1 fb  Nd a
Where once again for the particular case of small variations in isotope ratios I have
weighted by concentration rather than by the stable denominator isotope.
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Binary Mixing IV: ratio-ratio
• This time eliminating fb between the mixing equations gives
87Sr 
87 Sr  143 Nd 
143 Nd 
A86   B86  144   C 144   D  0
 Sr mix
 Sr mix Nd mix
 Nd mix
143 Nd 
143 Nd 
A  [Nd]b [Sr]a 144   [Nd]a [Sr]b 144 
 Nd b
 Nd a
B  [Nd]b [Sr]a  [Nd]a [Sr]b
87 Sr 
87 Sr 
C  [Nd]b [Sr]a 86   [Nd]a [Sr]b 86 
 Sr a
 Sr b
143 Nd  87 Sr 
143 Nd  87 Sr 
D  [Nd]a [Sr]b 144  86   [Nd]b [Sr]a 144  86 
 Nd a  Sr b
 Nd b  Sr a
• Still a hyperbola. Now term B gives the curvature index
r = ([Sr]a/[Sr]b)/([Nd]a/[Nd]b) = ([Sr]a/[Nd]a)/([Sr]b/[Nd]b)
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IV:
ratioratio
This looks different
from the element-ratio
hyperbola because
now the spacing of
equal increments of
mixing fraction is no
longer regular.
Given an array of
ratio-ratio data, you
can constrain the
curvature parameter as
well as the isotope
ratios of the end
members.
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Binary Mixing IV: a practical example
.703
(87Sr/86Sr)
.704
We’d like to know whether the lower mantle has high 3He/4He because it is rich in 3He or because it is
poor in 4He. Degassing at eruption makes this question very hard to answer. Assuming Loihi represents
the plume or lower mantle component, mixing with an upper mantle MORB-like component richest at
Mauna Loa, what does this plot say about the (4He/Sr) ratios of the upper and lower mantles?
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