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Modeling arc chemistry with ADIABAT_1ph

Explore the importance of modeling in understanding arc chemistry with ADIABAT_1ph. Learn about forward modeling, program limitations, and examples of realistic scenarios. Discover how modeling helps in constraining geological models and predicting compositions.

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Modeling arc chemistry with ADIABAT_1ph

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  1. Modeling arc chemistry with ADIABAT_1ph Gelu COSTIN James GIRARDI

  2. Why need modeling? • Forward modeling • How can we do it? ADIABAT_1ph • Limitations of the program • Example

  3. 1. Why need modeling • -different processes and mechanisms  similar effects • (e.g. modify the composition of a magma to obtain increasing of SiO2) • -fractional crystallization of a basic magma • -different % of crustal assimilation of a basic magma • -different % of partial melting of crustal rocks • experiments  partial melting should leave behind important amounts of residuum with high densities • Arc models  • need quantifying to better constrain geologic models • Modeling need constrains to be realistic

  4. 2. Forward modeling We start from unknown (or guessed), trying to arrive to what we know Try end error method What do we know? -several plutons with different composition, age etc  we can estimate an average composition -from the exposed area  we can do some estimations of the volume of plutons -scarce knowledge of the plutons development and composition at greater depths Models can work on: -individual protoliths, plutons, residual solids etc (at local scale) -averaged compositions of the protoliths, plutons, residual solids etc (at arc scale)

  5. Program used for modeling compositions and physical properties  ADIABAT_1ph Smith, P. M., and P. D. Asimow (2005), Adiabat_1ph: A new public front-end to the MELTS, pMELTS, and pHMELTS models, Geochem. Geophys. Geosyst., 6, art. no. Q02004, doi:10.1029/2004GC000816. It uses the MELTS family of algorithms Ghiorso, M.S., and R.O. Sack, Chemical Mass-Transfer in Magmatic Processes IV. A Revised and Internally Consistent Thermodynamic Model for the Interpolation and Extrapolation of Liquid-Solid Equilibria in Magmatic Systems at Elevated-Temperatures and Pressures, Contributions to Mineralogy and Petrology, 119 (2-3), 197-212, 1995. Asimow, P.D., and M.S. Ghiorso, Algorithmic modifications extending MELTS to calculate subsolidus phase relations, American Mineralogist, 83 (9-10), 1127-1132, 1998.

  6. ADIABAT_1ph version 1.6 • calculates equilibrium assemblages from a given bulk composition of multicomponent systems • anhydrous, water-undersaturated, or water-saturated systems • options of buffering oxygen fugacity • control on water activity • subsolidus or suprasolidus calculations • melting and crystallization models may be batch, fractional, or continuous. • can simultaneously calculate trace element distributions. • can calculate along a thermodynamic path set by the user

  7. 4. Limitations of the program • the compositions of liquids are not realistic above 30-35 kb • TiO2 overestimate the stability of pyroxene over other solids • MnO overestimates the stability of liquid and olivine over other phases • The amphibole stability field is underestimated • pMELTS routine is to be used for ultrabasic compositions only

  8. The compositions of melts and solids, as well as the phase proportions, are dependent on: • small variation of H2O content • initial composition of the system (SiO2, Al2O3 etc...) • T • P • Thermodynamic type of calculation (isobaric, isentropic, fractional crystallization .....) More variables Need simplifications: e.g. keep some variable = ct e.g. P=ct Assumptions: -isobaric processes at different depths according to a geologic model

  9. EXAMPLE – ADIABAT runs for the a pluton from BC 10-15 kb • plutons with heterogeneous compositions, forms, ages, depths etc • -only limited parts of the arcs are exposed • -no direct exposure of the lower levels of the arcs need a geological model before starting quantifying

  10. EXAMPLE – ADIABAT runs starting at 1500 ºC Lherzolite Partial melting of lherzolite (+ H2O) to produce basaltic melt Runs at 30 kb pMELTS routine Basaltic melts in MASH zone  andesitic basalt Runs at 15 kb MELTS routine Acid melts + residue Runs at 4 kb MELTS routine Compare the result with the composition of plutons

  11. 30 kb -Lherzolite • 3% H2O • Ts ~1180 ºC • small amount of melt (~ 1 % melt at ~ 1200 º C with SiO2~ 35 % • not enough melt • not “normal” basalt composition • not realistic!!!

  12. Assuming a basic melt arrived at MASH zone By assimilation and homogenization  crystallization  andesitic basalt or basaltic andesite Protolith for future melts Runs at 15 kb Andesitic basalt From Georoc database Estimated composition of the residue Average composition of the pluton

  13. Initial composition: 1, 2..... X ..... • ...slightly modifying composition, water content etc.... • untill... • ...we get an acid melt similar with our pluton... • then... • The guessed initial composition protolith • ..... and we can also estimate: • proportion of liquid and solid residue • temperature where the composition of pluton is valid • chemical and petrographic composition of residual solid • Estimates on the mineral chemistry of phasesof the residual solid • density of melt and residual solid

  14. Andesitic basalt as starting composition (from Georoc database) CENTRAL AMERICAN VOLCANIC ARC / HONDURAS / SEGMENT 4 / BOQUERON / PACIFIC OCEAN [4231] Averaged Great Tonalite Sill Samples averaged Andesitic basalt SiO2 53.1 TiO2 1.14 Al2O3 18.3 Fe2O3 2.85 FeO 6.8 CaO 9.62 MgO 3.59 MnO 0.19 K2O 1.33 Na2O 3.21 P2O5 0.22 H2O 0.59 Adiabat_1ph

  15. T solidus ~ 700 ºC T liquidus ~ 1420 º C Composition ~ pluton  composition similar with pluton averaged at ~ 1080 ºC ( with ~ 15% melt)  Melt is 17.91 %  The residue is68.4% cpx + 13.69 %grt P = 15 kb ~45 km depth

  16. Liquid composition at T=1180ºC Residue composition at T=1080ºC Starting composition (Protolith) Real average calculated SiO2 52 TiO2 0.1 Al2O3 13 Fe2O3 0.9 FeO 8.5 CaO 12.2 MgO 10.1 K2O 0.5 Na2O 3.0 H2O 0.5 Residue

  17. At T=1180 º C Densities (g/cm3) solid 3.345 liquid 2.586

  18. Further Constraints on the Composition of Deep Crustal Rocks • Using the output modeling programs we can calculate seismic properties of rocks of that composition. • We can compare the calculated seismic properties to what we see in the batholith. • How is this possible?

  19. Mineral Physical Properties • Database of mineral physical properties (Hacker et al. 2003). • Hackers’ spreadsheet is an Excel workbook which includes database and a macro which will calculate rock physical properties (Hacker and Abers 2004). • Input into this spread sheet is Vol% of minerals in rock.

  20. CIPW norms • A norm is a synthetic mineralogy calculated by apportioning chemical components into hypothetical (but hopefully realistic) minerals. • Mode is the actual mineralologic composition of a rock, volume percentage of minerals. • Using CIPW norms we can convert the chemical composition attained from the output of modeling programs such as Adiabat, and input the mineral assemblage into Hackers spreadsheet

  21. Calculating CIPW norms • What was once a The process of calculating CIPW norms can be done in Excel. The volume % of normative minerals can be input into Hackers spreadsheet to calculate the seismic properties of a rock with that composition. input

  22. Input into Hackers’ Spreadsheet

  23. An example from CMB Calculated properties for average Great Tonalite Sill and residue.

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