Commit 244b1a7f by Denis Anikiev

### fixes

parent cab12e7d
 %% Cell type:markdown id: tags: # Py4HIP: Python tool for Heat In Place calculations **Py4HIP** is a **Py**thon tool **for** **H**eat **I**n **P**lace calculations. This tool was created to perform **Heat In Place (HIP)** calculations for your region of choice. *Copyright (Bott et al., 2022). Licensed under the EUPL-1.2 or later.* %% Cell type:markdown id: tags: Calculating the Heat In Place (HIP) for certain geological units or confined reservoirs is a standard method performed in various regions to assess the spatial variability of geothermal potential ([Nathenson, 1975](#Nathenson1975); [Muffler and Cataldi, 1978](#MufflerCataldi1978); [Garg and Combs, 2015](#GargCombs2015)). The respective implementation in **Py4HIP** is based on a volumetric (\$V\$) quantification of contained energy (\$H\$) after [Muffler and Cataldi (1978)](#MufflerCataldi1978), where the geological unit at hand is considered as spatially variable in terms of its thickness (\$M\$), porosity (\$\phi\$), as well as density (\$\rho\$) and specific heat capacity (\$c_p\$) (for the solid rock (\$m\$) and brine (\$brine\$)). Finally, \$H\$ represents (i) the excess energy stored under mean temperature (\$T_{mean}\$) conditions with respect to a reference temperature (\$T_{ref}\$, here taken as the temperature at the Earth's surface (\$Z_{topo}\$)); (ii) the sum of stored heat in the solid and fluid parts of the rock: \$\$ H = V ((1 - \phi) \rho_{m} c_{p,m} + \phi \rho_{brine} c_{p, brine}) (T_r - T_{ref}) \$\$ %% Cell type:markdown id: tags:
x
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y
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\$d_{mean}\$
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\$M_{total}\$
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\$T_{mean}\$
| |:------------|:-----|:-----------|:-------------|:------------| | 0 | 0 | 0 | 161.0944798 | 12.69794223 | | 1004.016064 | 0 | 0 | 160.4305277 | 12.67989258 | | 2008.032129 | 0 | 0 | 159.1173317 | 12.64417627 | | ... | ... | ... | ... | ... | %% Cell type:markdown id: tags: ### Define parameters for calculation Define several steady parameters for your calculation: |
Variable
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Description
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Unit
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SI-unit
| |:----------------------------------------|:-------------------------------------------|:-----------------------------------|:---------------------------------------| | \$g\$ | standard gravity | \$\frac{m}{s^2}\$ | \$\frac{m}{s^2}\$ | | \$atm\$ | atmospheric pressure | \$Pa\$ | \$\frac{kg}{ms^2}\$ | | \$T_{ref}\$ | temperature at topography,model reference temperature |\$°C\$ | \$K\$ | | \$\phi\$ | porosity | % | - | | \$\rho_{brine\ 0}\$ | density of brine (empirical) | \$\frac{kg}{m^3}\$ | \$\frac{kg}{m^3}\$ | | \$Cp_{brine}\$ | speciifc heat capacity of brine | \$\frac{J}{kgK}\$ | \$\frac{m^2}{Ks^2}\$ | | \$S\$ | Salinity of brine | \$\frac{kg}{m^3}\$ | \$\frac{kg}{m^3}\$ | | \$\rho_{solid}\$ | density of solid | \$\frac{kg}{m^3}\$ | \$\frac{kg}{m^3}\$ | | \$Cp_{solid\ 0}\$ | speciifc heat capacity of solid (empirical) | \$\frac{J}{kgK}\$ | \$\frac{m^2}{Ks^2}\$ | These steady parameters need to be defined here: %% Cell type:code id: tags: ``` python g = 9.81 #[m/s^2] atm = 101325 #[Pa; kg/(m*s^2)] Tref = 8 #[°C; K] Phi = 0.14 #[%] Rho_brine_0 = 1040 #[kg/m^3] Cpm_brine = 3.925*1000 #[J/(kg*K); m^2/(K*s^2)] S = 60 #[kg/m^3] Rho_solid = 2680 #[kg/m^3] Cp_solid_0 = 810 #[J/(kg*K); m^2/(K*s^2)] ``` %% Cell type:markdown id: tags: ## Perform calculation Now, with all preparations done, you should be able to smoothly run the calculation by running the following cells.
Be aware: There is one option implemented in the skript which is to additionally generate figures to your calculation output. You can decide whether executing or skipping the option by ticking or unticking the checker box 'Want to generate figures?'.