Update paper.md

Author: ActiveMargins

paper/paper.md

@@ -35,9 +35,12 @@ Naturally occurring hydrogen (H2) in the Earth's subsurface represents a novel s
 # Statement of Need
 
 New resource modelling tools are urgently required to explore for He and natural H2, given their emerging and critical role in low-carbon energy generation and in research, medical, and industrial processes [@Danabalan:2022; @Jackson:2024; @IEA:2024; @SherwoodLollar:2025]. LithoGas addresses this need by: 1) calculating H2 and He production rates via radiolysis and serpentinization from rock geochemical and physical properties; 2) back-projecting these generation rates into deep time to estimate cumulative production; 3) summarising and plotting results, including novel source-rock-volume-scaling plots focused on resource estimation metrics. These functions provide the foundation for basin-scale modelling of radiolysis- and serpentinization-dominated H2 systems, analogous to exploration workflows for conventional hydrocarbon systems.
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 The Monte Carlo approach (monteProd()) follows the equations of [@Warr:2023] and [@Ardakani:2026], incorporating truncated normal distributions (controlled by min/max/mean/standard deviation parameters) for sample geochemistry (Fe, U, Th, and K concentrations), physical rock properties (rock density and porosity), and fluid properties (fluid density) (Table 1). Two pathways are available for assigning rock physical properties: user-defined sample-specific distributions, or automatic lookup from The Canadian Rock Physical Property Database [@Enkin:2018] based on the known lithology. If a deterministic rather than probabilistic model is desired, the standard deviation of any model parameter can be set to zero. Serpentinization H2 production can be modelled via two methods [@Ardakani:2026] depending on data availability: an iron speciation approach using measured Fe2O3 and FeO concentrations (monteSerpFeSpecies()), or a total iron approach using bulk Fe2O3T where speciation data are unavailable (monteSerpFeTotal()). Both serpentinization methods use the change in Fe³⁺/FeT ratio between initial and current states to estimate magnetite (Fe3O4) production and the associated stoichiometric H2 yield.
-Monte Carlo results from multiple samples are summarised using monteSum(), which collapses the full trial distribution to minimum, mean, and maximum production rates per sample group. Source rock volume scaling plots are generated by monteH2Plot() and monteHePlot(), which scale per m³ production rates across a range of source rock volumes (0.1 to 100 km³), producing log-log plots that allow direct comparison of H2 and He prospectivity across samples and lithologies. These source rock volume scaling plots are a simple yet important development, allowing prospecting for natural H2 and He from abundant lithogeochemical samples. A secondary axis on both plots converts molar production rates (mol/year for specified source rock volume) to mass rates (kg/year for specified source rock volume) for direct economic interpretation.
-Lastly, production rates produced by monteProd() can be projected into deep time wit the deepTimeProd() function. For radiolysis, U, Th, and K concentrations are back calculated using radioactive decay law. For serpentinization, and average rate of serpentinization is applied. These can the then be used by the user to look at cumulative volumes produced over time.
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+Monte Carlo results from multiple samples are summarised using monteSum(), which collapses the full trial distribution to minimum, mean, and maximum production rates per sample group. Source rock volume scaling plots are generated by monteH2Plot() and monteHePlot(), which scale per m³ production rates across a range of source rock volumes (0.1 to 100 km³), producing log-log plots that allow direct comparison of H2 and He prospectivity across samples and lithologies (Fig. 1). These source rock volume scaling plots are a simple yet important development, allowing prospecting for natural H2 and He from abundant lithogeochemical samples. A secondary axis on both plots converts molar production rates (mol/year for specified source rock volume) to mass rates (kg/year for specified source rock volume) for direct economic interpretation.
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+Lastly, production rates produced by monteProd() can be projected into deep time wit the deepTimeProd() function. For radiolysis, U, Th, and K concentrations are back calculated using radioactive decay law (Fig. 2). For serpentinization, and average rate of serpentinization is applied. These can the then be used by the user to look at cumulative volumes produced over time.
 
 # Conclusion