TWO-PHASE ICP 2: Process-specific relations describing the change of hydraulic porous-medium properties due to biogeochemical reactions

Department of Hydromechanics and Modelling of Hydrosystems

Research Project funded by the German Research Fondation (DFG) - Project number 380443677

Description

Carbon Capture and Storage (CCS) will be have to be utilized in the near future to mitigate the global climate change by reducing the emissions of CO2, which is thus not emitted, but rather injected in the subsurface. Also for an optimal use of renewable energies, gas will need to be stored underground to buffer the fluctuating supply and demand. Such gases may be either natural gas or synthetic methane (CH4) or hydrogen (H2) or simply compressed air. Optimal reservoirs for gas storage are located in variable depths, depending on geological conditions and the gas which is to be stored. They are separated from overlying aquifers by an impermeable cap rock. For a successfully operating storage, it is a necessity to avoid any leakage of stored gases.

Thus, further research to improve sealing technologies used to mitigate potential leakage, like the injection of cement or biomineralization is necessary, which requires understanding of both the (bio-) and geochemical reactions and the transport of the different components in both gas and water phase. Microbially induced calcium carbonate precipitation (MICP) is currently becoming an established method of biomineralization and in previous projects, a numerical model was developed for this biomineralization method. However, precipitation may also be induced by injection of extracted or plant-based sources of urease or at elevated temperatures. Experimental investigations of our collaborators at Montana State University (MSU) in Bozeman, USA focus on ureolysis-based methods involving enzyme (EICP) or elevated temperatures (TICP) instead of microbes to incude calcium carbonate precipitation. The applicability of a certain method is largely determined by the depth below ground surface and the local geothermal gradient. MICP relies on the activity of living bacterial cells, which only thrive within a limited temperature range (<45°C). This temperature range may include the shallow subsurface, where CH4 or natural gas may be stored, but is lower than the temperatures commonly present at depths suitable for CO2 storage. As a consequence, other technologies such as EICP or TICP have to be developed and demonstrated in the field.
The main goal of this project is to include the effects of ICP on the two-phase flow behavior as, with regard to using ICP to mitigate gas leakage from subsurface reservoirs, sufficient sealing might not necessarily depend on reducing the intrinsic permeability, but rather rely on increasing the entry pressure of the cap rock to values higher than the reservoir pressure. Further, in two phase flow, an effect described by the so-called relative permeability occurs, when the presence of one fluid phase hinders the movement of another. Relative permeability is depending not only on the fluid properties, but also on the geometry and surface properties of the porous medium. Thus, ICP likely has an effect on relative permeability as well, as the pore sizes decrease and calcium carbonate, potentially not present before, is covering the pore surfaces and thus determining the solid-fluid interactions. Additionally, of course also the intrinsic permeability for a fully-saturated single-fluid-phase case is reduced, as more and more mineral is precipitated. All these effects of ICP on porous medium properties in turn also affect the ICP processes themselves, as the (bio-)geochemical reactions depend on the supply of reactants with the fluid flow. E.g. when a pore throat is completely blocked, the adjacent pore bodies may end up as dead-end pores into which no further flow occurs and all further reactants can only reach them by diffusion, limiting the supply of reactants to the initial plugging precipitated mineral, thus reducing its further growth rate. Similar effects may occur also on larger scales.
Therefore, it is important to include such effects of ICP on porous medium properties into the models for ICP to be able to not only correctly assess the effects of ICP in terms of sealing success, but also, to predict the actual ICP processes as accurately as possible.

Duration

04/2021 - 01/2026

Funding

Publications

(Journal-) Articles
1. Lee, D., Weinhardt, F., Hommel, J., Piotrowski, J., Class, H., & Steeb, H. (2023). Machine learning assists in increasing the time resolution of X-ray computed tomography applied to mineral precipitation in porous media. Scientific Reports, 13, 10529. https://doi.org/10.1038/s41598-023-37523-0
  Abstract
  Many subsurface engineering technologies or natural processes cause porous medium properties, such as porosity or permeability, to evolve in time. Studying and understanding such processes on the pore scale is strongly aided by visualizing the details of geometric and morphological changes in the pores. For realistic 3D porous media, X-Ray Computed Tomography (XRCT) is the method of choice for visualization. However, the necessary high spatial resolution requires either access to limited high-energy synchrotron facilities or data acquisition times which are considerably longer (e.g. hours) than the time scales of the processes causing the pore geometry change (e.g. minutes). Thus, so far, conventional benchtop XRCT technologies are often too slow to allow for studying dynamic processes. Interrupting experiments for performing XRCT scans is also in many instances no viable approach. We propose a novel workflow for investigating dynamic precipitation processes in porous media systems in 3D using a convent.
  BibTeX
  @article{Leeetal2023, abstract = {Many subsurface engineering technologies or natural processes cause porous medium properties, such as porosity or permeability, to evolve in time. Studying and understanding such processes on the pore scale is strongly aided by visualizing the details of geometric and morphological changes in the pores. For realistic 3D porous media, X-Ray Computed Tomography (XRCT) is the method of choice for visualization. However, the necessary high spatial resolution requires either access to limited high-energy synchrotron facilities or data acquisition times which are considerably longer (e.g. hours) than the time scales of the processes causing the pore geometry change (e.g. minutes). Thus, so far, conventional benchtop XRCT technologies are often too slow to allow for studying dynamic processes. Interrupting experiments for performing XRCT scans is also in many instances no viable approach. We propose a novel workflow for investigating dynamic precipitation processes in porous media systems in 3D using a convent.}, author = {Lee, Dongwon and Weinhardt, Felix and Hommel, Johannes and Piotrowski, Joseph and Class, Holger and Steeb, Holger}, doi = {10.1038/s41598-023-37523-0}, journal = {Scientific Reports}, pages = 10529, title = {Machine learning assists in increasing the time resolution of X-ray computed tomography applied to mineral precipitation in porous media}, url = {https://doi.org/10.1038/s41598-023-37523-0}, volume = 13, year = 2023 }
  Link
  https://doi.org/10.1038/s41598-023-37523-0
2. Hommel, J., Gehring, L., Weinhardt, F., Ruf, M., & Steeb, H. (2022). Effects of Enzymatically Induced Carbonate Precipitation on Capillary Pressure-Saturation Relations. Minerals, 12(10), Article 10. https://doi.org/10.3390/min12101186
  Abstract
  Leakage mitigation methods are an important part of reservoir engineering and subsurface fluid storage, in particular. In the context of multi-phase systems of subsurface storage, e.g., subsurface CO2 storage, a reduction in the intrinsic permeability is not the only parameter to influence the potential flow or leakage; multi-phase flow parameters, such as relative permeability and capillary pressure, are key parameters that are likely to be influenced by pore-space reduction due to leakage mitigation methods, such as induced precipitation. In this study, we investigate the effects of enzymatically induced carbonate precipitation on capillary pressure–saturation relations as the first step in accounting for the effects of induced precipitation on multi-phase flow parameters. This is, to our knowledge, the first exploration of the effect of enzymatically induced carbonate precipitation on capillary pressure–saturation relations thus far. First, pore-scale resolved microfluidic experiments in 2D glass cells and 3D sintered glass-bead columns were conducted, and the change in the pore geometry was observed by light microscopy and micro X-ray computed tomography, respectively. Second, the effects of the geometric change on the capillary pressure–saturation curves were evaluated by numerical drainage experiments using pore-network modeling on the pore networks extracted from the observed geometries. Finally, parameters of both the Brooks–Corey and Van Genuchten relations were fitted to the capillary pressure–saturation curves determined by pore-network modeling and compared with the reduction in porosity as an average measure of the pore geometry’s change due to induced precipitation. The capillary pressures increased with increasing precipitation and reduced porosity. For the 2D setups, the change in the parameters of the capillary pressure–saturation relation was parameterized. However, for more realistic initial geometries of the 3D samples, while the general patterns of increasing capillary pressure may be observed, such a parameterization was not possible using only porosity or porosity reduction, likely due to the much higher variability in the pore-scale distribution of the precipitates between the experiments. Likely, additional parameters other than porosity will need to be considered to accurately describe the effects of induced carbonate precipitation on the capillary pressure–saturation relation of porous media.
  BibTeX
  @article{min12101186, abstract = {Leakage mitigation methods are an important part of reservoir engineering and subsurface fluid storage, in particular. In the context of multi-phase systems of subsurface storage, e.g., subsurface CO2 storage, a reduction in the intrinsic permeability is not the only parameter to influence the potential flow or leakage; multi-phase flow parameters, such as relative permeability and capillary pressure, are key parameters that are likely to be influenced by pore-space reduction due to leakage mitigation methods, such as induced precipitation. In this study, we investigate the effects of enzymatically induced carbonate precipitation on capillary pressure–saturation relations as the first step in accounting for the effects of induced precipitation on multi-phase flow parameters. This is, to our knowledge, the first exploration of the effect of enzymatically induced carbonate precipitation on capillary pressure–saturation relations thus far. First, pore-scale resolved microfluidic experiments in 2D glass cells and 3D sintered glass-bead columns were conducted, and the change in the pore geometry was observed by light microscopy and micro X-ray computed tomography, respectively. Second, the effects of the geometric change on the capillary pressure–saturation curves were evaluated by numerical drainage experiments using pore-network modeling on the pore networks extracted from the observed geometries. Finally, parameters of both the Brooks–Corey and Van Genuchten relations were fitted to the capillary pressure–saturation curves determined by pore-network modeling and compared with the reduction in porosity as an average measure of the pore geometry’s change due to induced precipitation. The capillary pressures increased with increasing precipitation and reduced porosity. For the 2D setups, the change in the parameters of the capillary pressure–saturation relation was parameterized. However, for more realistic initial geometries of the 3D samples, while the general patterns of increasing capillary pressure may be observed, such a parameterization was not possible using only porosity or porosity reduction, likely due to the much higher variability in the pore-scale distribution of the precipitates between the experiments. Likely, additional parameters other than porosity will need to be considered to accurately describe the effects of induced carbonate precipitation on the capillary pressure–saturation relation of porous media.}, article-number = {1186}, author = {Hommel, Johannes and Gehring, Luca and Weinhardt, Felix and Ruf, Matthias and Steeb, Holger}, doi = {10.3390/min12101186}, issn = {2075-163X}, journal = {Minerals}, number = 10, title = {Effects of Enzymatically Induced Carbonate Precipitation on Capillary Pressure-Saturation Relations}, url = {https://www.mdpi.com/2075-163X/12/10/1186}, volume = 12, year = 2022 }
  Link
  https://www.mdpi.com/2075-163X/12/10/1186
3. Scheurer, S., Schäfer Rodrigues Silva, A., Mohammadi, F., Hommel, J., Oladyshkin, S., Flemisch, B., & Nowak, W. (2021). Surrogate-based Bayesian comparison of computationally expensive models: application to microbially induced calcite precipitation. Computational Geosciences. https://doi.org/10.1007/s10596-021-10076-9
  Abstract
  Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface reservoirs that currently contains strong conceptual uncertainty. This means, several modeling approaches describing the biogeochemical process are plausible and modelers face the uncertainty of choosing the most appropriate one. The considered models differ in the underlying hypotheses about the process structure. Once observation data become available, a rigorous Bayesian model selection accompanied by a Bayesian model justifiability analysis could be employed to choose the most appropriate model, i.e. the one that describes the underlying physical processes best in the light of the available data. However, biogeochemical modeling is computationally very demanding because it conceptualizes different phases, biomass dynamics, geochemistry, precipitation and dissolution in porous media. Therefore, the Bayesian framework cannot be based directly on the full computational models as this would require too many expensive model evaluations. To circumvent this problem, we suggest to perform both Bayesian model selection and justifiability analysis after constructing surrogates for the competing biogeochemical models. Here, we will use the arbitrary polynomial chaos expansion. Considering that surrogate representations are only approximations of the analyzed original models, we account for the approximation error in the Bayesian analysis by introducing novel correction factors for the resulting model weights. Thereby, we extend the Bayesian model justifiability analysis and assess model similarities for computationally expensive models. We demonstrate the method on a representative scenario for microbially induced calcite precipitation in a porous medium. Our extension of the justifiability analysis provides a suitable approach for the comparison of computationally demanding models and gives an insight on the necessary amount of data for a reliable model performance.
  BibTeX
  @article{scheurer_surrogate-based_2021, abstract = {Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface reservoirs that currently contains strong conceptual uncertainty. This means, several modeling approaches describing the biogeochemical process are plausible and modelers face the uncertainty of choosing the most appropriate one. The considered models differ in the underlying hypotheses about the process structure. Once observation data become available, a rigorous Bayesian model selection accompanied by a Bayesian model justifiability analysis could be employed to choose the most appropriate model, i.e. the one that describes the underlying physical processes best in the light of the available data. However, biogeochemical modeling is computationally very demanding because it conceptualizes different phases, biomass dynamics, geochemistry, precipitation and dissolution in porous media. Therefore, the Bayesian framework cannot be based directly on the full computational models as this would require too many expensive model evaluations. To circumvent this problem, we suggest to perform both Bayesian model selection and justifiability analysis after constructing surrogates for the competing biogeochemical models. Here, we will use the arbitrary polynomial chaos expansion. Considering that surrogate representations are only approximations of the analyzed original models, we account for the approximation error in the Bayesian analysis by introducing novel correction factors for the resulting model weights. Thereby, we extend the Bayesian model justifiability analysis and assess model similarities for computationally expensive models. We demonstrate the method on a representative scenario for microbially induced calcite precipitation in a porous medium. Our extension of the justifiability analysis provides a suitable approach for the comparison of computationally demanding models and gives an insight on the necessary amount of data for a reliable model performance.}, author = {Scheurer, Stefania and Schäfer Rodrigues Silva, Aline and Mohammadi, Farid and Hommel, Johannes and Oladyshkin, Sergey and Flemisch, Bernd and Nowak, Wolfgang}, doi = {10.1007/s10596-021-10076-9}, issn = {1573-1499}, journal = {Computational Geosciences}, month = {08}, publisher = {Springer Science and Business Media {LLC}}, title = {Surrogate-based Bayesian comparison of computationally expensive models: application to microbially induced calcite precipitation}, url = {https://doi.org/10.1007/s10596-021-10076-9}, year = 2021 }
  Link
  https://doi.org/10.1007/s10596-021-10076-9
4. von Wolff, L., Weinhardt, F., Class, H., Hommel, J., & Rohde, C. (2021). Investigation of Crystal Growth in Enzymatically Induced Calcite Precipitation by Micro-Fluidic Experimental Methods and Comparison with Mathematical Modeling. Transport in Porous Media, 137(2), Article 2. https://doi.org/10.1007/s11242-021-01560-y
  Abstract
  Enzymatically induced calcite precipitation (EICP) is an engineering technology that allows for targeted reduction of porosity in a porous medium by precipitation of calcium carbonates. This might be employed for reducing permeability in order to seal flow paths or for soil stabilization. This study investigates the growth of calcium-carbonate crystals in a micro-fluidic EICP setup and relies on experimental results of precipitation observed over time and under flow-through conditions in a setup of four pore bodies connected by pore throats. A phase-field approach to model the growth of crystal aggregates is presented, and the corresponding simulation results are compared to the available experimental observations. We discuss the model's capability to reproduce the direction and volume of crystal growth. The mechanisms that dominate crystal growth are complex depending on the local flow field as well as on concentrations of solutes. We have good agreement between experimental data and model results. In particular, we observe that crystal aggregates prefer to grow in upstream flow direction and toward the center of the flow channels, where the volume growth rate is also higher due to better supply.
  BibTeX
  @article{vonWolff2021-Weinhardt, abstract = {Enzymatically induced calcite precipitation (EICP) is an engineering technology that allows for targeted reduction of porosity in a porous medium by precipitation of calcium carbonates. This might be employed for reducing permeability in order to seal flow paths or for soil stabilization. This study investigates the growth of calcium-carbonate crystals in a micro-fluidic EICP setup and relies on experimental results of precipitation observed over time and under flow-through conditions in a setup of four pore bodies connected by pore throats. A phase-field approach to model the growth of crystal aggregates is presented, and the corresponding simulation results are compared to the available experimental observations. We discuss the model's capability to reproduce the direction and volume of crystal growth. The mechanisms that dominate crystal growth are complex depending on the local flow field as well as on concentrations of solutes. We have good agreement between experimental data and model results. In particular, we observe that crystal aggregates prefer to grow in upstream flow direction and toward the center of the flow channels, where the volume growth rate is also higher due to better supply.}, author = {von Wolff, Lars and Weinhardt, Felix and Class, Holger and Hommel, Johannes and Rohde, Christian}, day = 24, doi = {10.1007/s11242-021-01560-y}, issn = {1573-1634}, journal = {Transport in Porous Media}, month = {02}, number = 2, publisher = {Springer Science and Business Media LLC}, title = {Investigation of Crystal Growth in Enzymatically Induced Calcite Precipitation by Micro-Fluidic Experimental Methods and Comparison with Mathematical Modeling}, url = {https://doi.org/10.1007/s11242-021-01560-y}, volume = 137, year = 2021 }
  Link
  https://doi.org/10.1007/s11242-021-01560-y
5. Hommel, J., Akyel, A., Frieling, Z., Phillips, A. J., Gerlach, R., Cunningham, A. B., & Class, H. (2020). A Numerical Model for Enzymatically Induced Calcium Carbonate Precipitation. Applied Sciences, 10(13), Article 13. https://doi.org/10.3390/app10134538
  - BibTeX
  BibTeX
  @article{Hommel2020, author = {Hommel, Johannes and Akyel, Arda and Frieling, Zachary and Phillips, Adrienne J. and Gerlach, Robin and Cunningham, Alfred B. and Class, Holger}, doi = {10.3390/app10134538}, journal = {Applied Sciences}, month = {06}, number = 13, pages = 4538, title = {A Numerical Model for Enzymatically Induced Calcium Carbonate Precipitation}, volume = 10, year = 2020 }
6. Cunningham, A. B., Class, H., Ebigbo, A., Gerlach, R., Phillips, A., & Hommel, J. (2019). Field-scale modeling of microbially induced calcite precipitation. Computational Geosciences, tbd. https://doi.org/10.1007/s10596-018-9797-6
  - BibTeX
  - Link
  BibTeX
  @article{NULL, author = {Cunningham, Alfred B. and Class, Holger and Ebigbo, Anozie and Gerlach, Robin and Phillips, Adrienne and Hommel, Johannes}, doi = {10.1007/s10596-018-9797-6}, journal = {Computational Geosciences}, month = {04}, note = {, IWS2ID=4551 , Partnerinstitution: Montana State University , Partneraddress: Bozeman, Montana, USA }, page = {tbd}, title = {Field-scale modeling of microbially induced calcite precipitation}, url = {http://link.springer.com/article/10.1007/s10596-018-9797-6}, volume = {tbd}, year = 2019 }
  Link
  http://link.springer.com/article/10.1007/s10596-018-9797-6
7. Hommel, J., Coltman, E., & Class, H. (2018). Porosity-Permeability Relations for Evolving Pore Space: A Review with a Focus on (Bio-)geochemically Altered Porous Media. Transport in Porous Media, 2(124), Article 124. https://doi.org/10.1007/s11242-018-1086-2
  - BibTeX
  - Link
  BibTeX
  @article{NULL, author = {Hommel, Johannes and Coltman, Edward and Class, Holger}, doi = {10.1007/s11242-018-1086-2}, journal = {Transport in Porous Media}, month = {05}, note = {, IWS2ID=4501 }, number = 124, page = {589-629}, title = {Porosity-Permeability Relations for Evolving Pore Space: A Review with a Focus on (Bio-)geochemically Altered Porous Media}, url = {https://link.springer.com/article/10.1007%2Fs11242-018-1086-2}, volume = 2, year = 2018 }
  Link
  https://link.springer.com/article/10.1007%2Fs11242-018-1086-2
Datasets
1. Lee, D., Weinhardt, F., Hommel, J., Class, H., & Steeb, H. (2023). Time resolved micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in sintered glass bead columns. DaRUS. https://doi.org/10.18419/darus-2227
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-Leeetal2023, author = {Lee, Dongwon and Weinhardt, Felix and Hommel, Johannes and Class, Holger and Steeb, Holger}, doi = {10.18419/darus-2227}, publisher = {DaRUS}, title = {Time resolved micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in sintered glass bead columns}, url = {https://doi.org/10.18419/darus-2227}, version = {V1}, year = 2023 }
  Link
  https://doi.org/10.18419/darus-2227
2. Ruf, M., Hommel, J., & Steeb, H. (2022). Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of medium column (sample 3). DaRUS. https://doi.org/10.18419/darus-2906
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-Rufetal2022a, author = {Ruf, Matthias and Hommel, Johannes and Steeb, Holger}, doi = {10.18419/darus-2906}, publisher = {DaRUS}, title = {Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of medium column (sample 3)}, url = {https://doi.org/10.18419/darus-2906}, version = {V1}, year = 2022 }
  Link
  https://doi.org/10.18419/darus-2906
3. Hommel, J., & Gehring, L. (2022). Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - column samples. DaRUS. https://doi.org/10.18419/darus-1713
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-HommelGehring2022, author = {Hommel, Johannes and Gehring, Luca}, doi = {10.18419/darus-1713}, publisher = {DaRUS}, title = {Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - column samples}, url = {https://doi.org/10.18419/darus-1713}, version = {V1}, year = 2022 }
  Link
  https://doi.org/10.18419/darus-1713
4. Ruf, M., Hommel, J., & Steeb, H. (2022). Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of high column (sample 4). DaRUS. https://doi.org/10.18419/darus-2907
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-Rufetal2022b, author = {Ruf, Matthias and Hommel, Johannes and Steeb, Holger}, doi = {10.18419/darus-2907}, publisher = {DaRUS}, title = {Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of high column (sample 4)}, url = {https://doi.org/10.18419/darus-2907}, version = {V1}, year = 2022 }
  Link
  https://doi.org/10.18419/darus-2907
5. Hommel, J., & Weinhardt, F. (2022). Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - microfluidics samples. DaRUS. https://doi.org/10.18419/darus-2791
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-HommelWeinhardt2022, author = {Hommel, Johannes and Weinhardt, Felix}, doi = {10.18419/darus-2791}, publisher = {DaRUS}, title = {Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - microfluidics samples}, url = {https://doi.org/10.18419/darus-2791}, version = {V1}, year = 2022 }
  Link
  https://doi.org/10.18419/darus-2791
6. Ruf, M., Hommel, J., & Steeb, H. (2022). Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of low column (sample 10). DaRUS. https://doi.org/10.18419/darus-2908
  - BibTeX
  - Link
  BibTeX
  @dataset{darus-Rufetal2022c, author = {Ruf, Matthias and Hommel, Johannes and Steeb, Holger}, doi = {10.18419/darus-2908}, publisher = {DaRUS}, title = {Enzymatically induced carbonate precipitation and its effect on capillary pressure-saturation relations of porous media - micro-XRCT dataset of low column (sample 10)}, url = {https://doi.org/10.18419/darus-2908}, version = {V1}, year = 2022 }
  Link
  https://doi.org/10.18419/darus-2908

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TWO-PHASE ICP 2: Process-specific relations describing the change of hydraulic porous-medium properties due to biogeochemical reactions

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