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Ray Seikel (Intrepid Geophysics), Kurt Stüwe (Graz University), Helen Gibson (Intrepid Geophysics), Betina
Bendall (Petratherm), Louise McAllister (Petratherm), Peter Reid (Petratherm), Anthony Budd (GeoScience
Australia)
Forward Prediction of Spatial Temperature Variation From 3D Geology Models
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1) Building 3D geology models2) Prediction of spatial temperature variation from
3D geology model. Develop a method for rapid computation directly from a 3D geology model
3) Case Study - Compare predictions with measured
Collaboration
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ConductionProduction Radiogenically Mechanically
ChemicallyAdvection by Fluids
by Erosion by Deformation by Magma
)/()(2p
cmech
Schem
Srad
SUdt
dT
Heat Transfer Processes
+ Schem + Smech
Summary of heat flow theory
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Heat production via radioactive sources is important
In contrast no highly active tectonism, metamorphism or volcanism is occuring in the upper crust today, which might otherwise contribute to mechanical or chemical heat production. So we do not take these into account
Assumptions for Australia
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It is sufficient to consider only the case of thermal steady state for the Australian crust
We must take into account the variation of conductivity with rock types
Assumptions for Australia (Cont)
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Conduction *
Production Radiogenically * Mechanically
Chemically
Advection by Fluids * by Erosion by Deformation by Magma
)/()(2p
cmech
Schem
Srad
SUdt
dT
Heat Transfer Processes
+ Schem + Smech X X
Simplified Equations
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Software Implementation
• Fourier’s first and second laws• Steady state• Variable thermal conductivity (k) & heat production rate (S)
The final equation allows us to solve in 3D using finite difference approximation
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Surface Topography
Surface: Mean surface temperature
Sides: Neumann-type
Base: Constant Heat Flow or
Constant Temperature
Support for•surface topography•fixed internal temperatures
Isotherms with Increasing depth
Boundary Conditions
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Solve in Voxet space<Discretise the model>
<Assign: Thermal ConductivitiesHeat Production Rates
<Assign:Boundary Conditions
<InputVoxet> <ForwardModel3DTemperature> <OutputVoxet(s)>
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Case 1 - Constant qbase and layered geology• Case 2 – Constant temperature at base and layered geology• Case 3 – Uniform thermal conductivity and heat production rate through out• Case 4 – Step heat production rate• Case 5 – Same as Case 2 expect one voxel is held at fixed temperature• Case 6 – Topo test• Case 7 – Uniform advection through out• Case 8 – Advection through a 3x3 vertical column
Unit testing: 8 cases
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•To validate FD approximations against analytical solutions and expected T distributions
•Different initial settings and boundary conditions
all passed
Unit testing: 8 cases
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Example: Unit Test 3 Results Uniform conductivityUniform radiogenic heat production
TemperatureHeat Production
De
pth
Conductivity
De
pth
De
pth
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Heat ProductionConductivity Temperature
De
pth
De
pth
De
pth
Uniform conductivityNo heat productionSetting drill hole temperature data as fixed(Unrealistic scenario but ok for testing!)
Example: Unit Test 5 Results
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Example: Test Localised advection
Assuming
Uniform conductivity and constant basal heat flow
Fluid flow upwards through 150x150m vertical column
Properties adjusted to give visible results
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1) Compare with measured values2) Consider potential field data, re-fine the model,
repeat
This case study assists in software testing
Brief overview of Paralana Case Study
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Petratherm Ltd’sParalana Project Tenements
~20 km east of Mt Painter Inlier
Northern Flinders RangesSouth Australia
ParalanaProject
Mt Painter Inlier
•Adelaide
•
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Generalised W-E section: Poontana Graben
126-129 mW/m2
Paralana-1B
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Paralana Case Study
Geology model constraints
• 9 interpreted seismic sections (Petratherm) simple, linear depth conversion (in GeoModeller)
• Paralana-1B well (Petratherm)
• ~50 shallow drill holes (SARIG dataset, PIRSA)
• SEEBASE economic basement depth (PIRSA / SRK)
• 1:700,000 Basement map Arrowie Basin (PIRSA / SRK)
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Tops and faults from seismic
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Paralana-1B
SeeBase: Top Curnamona
Paralana Fault(s) Shallow drill holes
Seismic
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Solid geology model
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Forward temperature modelling
• Conduction
• Heat Production (U, Th, K)
Advection x (but soon possible)
Possible small heat contribution from fluids fluxing via Paralana Fault and (?) deeper fracture networks/pathways
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Steps <Assign Thermal ConductivitiesHeat Production Rates
<SetBoundary Conditions
<Discretise the model
<Input Voxet<Forward Model 3D Temperature<Output Voxet(s)
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model inputs
run24
Thermal Conductivity
Watts m–1
K –1
Heat Production Rate
Watts / m3
Rec - Mesozoic 1.5 ~1 x10-6
Carboniferous 2.0 ~1 x10-6
Lake Frome Gp 5.3 ~1 x10-6
Lwr Arrowie 3.2 ~1 x10-6
Brachina Sh 2.0 ~1 x10-6
Lwr Adelaidean 2.4 ~1 x10-6
Moolawatana 3.2 ~22 x10-6
Mt Painter MesoP 3.2 ~22 x10-6
U-depleted base 3.2 ~2 x10-6
BOUNDARY
CONDITIONS
Top: 19°C Bottom: 0.035 Wm-2
Constant heat flow
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Model discretisation: run 24Input model
extents
Number of
cells
Discretisation
cell size
X 55 km 40 1350 m
Y30 km 40 750 m
Z10 km 40 250 m
Total voxels: 64,000 Run-time: 14 mins
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Set iterations controls (run24)
• Maximum residual in Degrees C: 0.0001(the maximum change allowed in temperature in any cell)
• Maximum Iterations: 15,000
When either condition is met, iterations cease, as thermal equilibrium is said to be reached
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Model outputs
• Voxet: x, y, z, lithologies (initial earth model)
• Voxet of results: temperature, vertical heat flow, vertical temperature gradient,
total horizontal temperature gradient
• jpegs (for every 2D section in the geology model)
• grid files (ditto)
• record of run (inversions.xml; COMPUTE_LOG.txt)
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‘Verify‘: W-E section•Temperature•Modelled geology•Wells (projected to section)Result ~103°C at bottom hole / Paralana–1B(compared measured 109 °C)
286 degC
19 degC
Paralana-1B
Section line: 55 km long
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140 mWm-2
63 mWm-2
Horizontal section at -500m•Vertical Heat FlowResult ~108 mWm-2
(compared measured 129 mWm-2 within Paralana–1B)
Paralana-1B
55 km x 30 km
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Concluding points•Initial geology model is reasonable
Together with estimated thermal properties:•Measured T data in Paralana-1B can be matched•Surface Heat Flow data can be (~) matched•Software implementation performs to specifications
•Geology model still needs refining (assisted by forward modelled gravity and magnetics in GeoModeller)
•Geology dominates the T distribution- Hence true 3D modelling is crucial !
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grateful acknowledgement !
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Disclaimer
Data have been manipulated to show software features and may not reflect
actual conditions at Paralana