Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Volume 7, issue 9
Biogeosciences, 7, 2925–2941, 2010
https://doi.org/10.5194/bg-7-2925-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 7, 2925–2941, 2010
https://doi.org/10.5194/bg-7-2925-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Sep 2010

24 Sep 2010

A transfer function for the prediction of gas hydrate inventories in marine sediments

M. Marquardt, C. Hensen, E. Piñero, K. Wallmann, and M. Haeckel M. Marquardt et al.
  • Leibniz-Institut für Meereswissenschaften, IFM-GEOMAR, Kiel, Germany

Abstract. A simple prognostic tool for gas hydrate (GH) quantification in marine sediments is presented based on a diagenetic transport-reaction model approach. One of the most crucial factors for the application of diagenetic models is the accurate formulation of microbial degradation rates of particulate organic carbon (POC) and the coupled formation of biogenic methane. Wallmann et al. (2006) suggested a kinetic formulation considering the ageing effects of POC and accumulation of reaction products (CH4, CO2) in the pore water. This model is applied to data sets of several ODP sites in order to test its general validity. Based on a thorough parameter analysis considering a wide range of environmental conditions, the POC accumulation rate (POCar in g/m2/yr) and the thickness of the gas hydrate stability zone (GHSZ in m) were identified as the most important and independent controls for biogenic GH formation. Hence, depth-integrated GH inventories in marine sediments (GHI in g of CH4 per cm2 seafloor area) can be estimated as:

GHI = a · POCar · GHSZb · exp (– GHSZc/POCar/d) + e

with a = 0.00214, b = 1.234, c = –3.339,

        d = 0.3148, e = –10.265.

The transfer function gives a realistic first order approximation of the minimum GH inventory in low gas flux (LGF) systems. The overall advantage of the presented function is its simplicity compared to the application of complex numerical models, because only two easily accessible parameters need to be determined.

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