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| Titel |
Interactive Visual Analytics Approch for Exploration of Geochemical Model Simulations with Different Parameter Sets |
| VerfasserIn |
Janis Jatnieks, Marco De Lucia, Mike Sips, Doris Dransch |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250112806
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| Publikation (Nr.) |
 EGU/EGU2015-12984.pdf |
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| Zusammenfassung |
| Many geoscience applications can benefit from testing many combinations of input
parameters for geochemical simulation models. It is, however, a challenge to screen the input
and output data from the model to identify the significant relationships between input
parameters and output variables. For addressing this problem we propose a Visual Analytics
approach that has been developed in an ongoing collaboration between computer science and
geoscience researchers.
Our Visual Analytics approach uses visualization methods of hierarchical horizontal axis,
multi-factor stacked bar charts and interactive semi-automated filtering for input and output
data together with automatic sensitivity analysis. This guides the users towards significant
relationships. We implement our approach as an interactive data exploration tool. It
is designed with flexibility in mind, so that a diverse set of tasks such as inverse
modeling, sensitivity analysis and model parameter refinement can be supported. Here
we demonstrate the capabilities of our approach by two examples for gas storage
applications.
For the first example our Visual Analytics approach enabled the analyst to observe how
the element concentrations change around previously established baselines in response to
thousands of different combinations of mineral phases. This supported combinatorial
inverse modeling for interpreting observations about the chemical composition of the
formation fluids at the Ketzin pilot site for CO2 storage. The results indicate that,
within the experimental error range, the formation fluid cannot be considered at local
thermodynamical equilibrium with the mineral assemblage of the reservoir rock.
This is a valuable insight from the predictive geochemical modeling for the Ketzin
site.
For the second example our approach supports sensitivity analysis for a reaction involving
the reductive dissolution of pyrite with formation of pyrrothite in presence of gaseous
hydrogen. We determine that this reaction is thermodynamically favorable under a
broad range of conditions. This includes low temperatures and absence of microbial
catalysators.
Our approach has potential for use in other applications that involve exploration of
relationships in geochemical simulation model data. |
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