Interpreting temperature–strain data from mesoscale clathrate experiments
Highlights
► Development/ application of data processing methods to analyze/visualize DSS data. ► Graphs and movies of temperature–strain value vs sensor position on the fiber. ► TSV data interpolated along each fiber plane to highlight gas hydrate formation.
Introduction
Gas hydrates, a type of clathrates, are cagelike structures of water molecules bonded to form cavities, which are populated by gas molecules such as carbon dioxide or methane. Natural gas hydrates are stable at low temperatures and moderate pressures, making the seafloor an ideal environment for methane hydrate formation. Gas hydrates are sensitive to changes in pressure and temperature; dissociation can be triggered by lowering the water column or by increasing temperature (Buffet and Archer, 2004, Makogon et al., 2007, Sloan, 1998). Hydrates are also subject to action by chemical inhibitors, which increase the required pressure and decrease the temperature conditions for clathrate stability.
Gas hydrates have been proposed as a sequestration mechanism for carbon dioxide (Brewer et al., 2000, Gabitto and Tsouris, 2006, Goel, 2006, Jadhawar et al., 2006) and hydrates of natural gases could provide significant volumes of methane for energy production (Boswell, 2007, Moridis et al., 2009, Walsh et al., 2009). Gas hydrates could also be used as a transport or storage mechanism for gases under low temperature and moderate pressure conditions (Chatti et al., 2005). In addition, dissociation of gas hydrates may have contributed to past global warming events (Kennett et al., 2000, Beauchamp, 2004, Dickens et al., 1997, Maclennan and Jones, 2006, Max et al., 1999, Padden et al., 2001, Weissert and Erba, 2004). Dissociation of hydrates present in seafloor sediments could also result in seafloor instability (Mienert et al., 2005, Kvenvolden, 1999). However, current estimates of hydrate volume vary by many orders of magnitude (Klauda and Sandler, 2005) and constraining these values would be of great aid in determining both the role of gas hydrates in global climate change and the feasibility of producing natural gas from hydrate reservoirs. Therefore, experiments examining and visualizing the formation and dissociation pathways of gas hydrates within sediments have an impact on the assessment of both geological and industrial hazards.
High-resolution data collected through long experiments and effective visualization methods are required to understand the complex behavior of a sediment–hydrate system. Previous workers have used X-ray (Kneafsey et al., 2007) and acoustical (Waite et al., 2004) tomography, neutron diffraction (Thompson et al., 2006), and magnetic resonance imaging (Gao et al., 2005) to observe hydrate formation and dissociation in situ. Fiber optic sensing can also be utilized for effective visualization of hydrate formation within sediment. This paper focuses on data processing methods developed to analyze and visualize large data sets collected by a fiber optic distributed sensing systems (DSS) within complex, multicomponent hydrate experiments in the Seafloor Process Simulator (SPS) at ORNL (Phelps et al., 2001, Rawn et al., 2011).
Section snippets
Materials and methods
Mesoscale laboratory experiments help bridge the gap between expensive and difficult field-based analysis of natural hydrates in situ or within preserved cores, and microscopic or molecular-scale measurements of synthetic hydrates, which lack sufficient scale to realize the complexity of natural systems. The SPS is a 72-L pressure vessel 0.33 m in diameter and 0.9 m in length. Designed and constructed at Oak Ridge National Laboratory, the SPS is capable of maintaining pressures up to 20 MPa
Data processing
The large volume of data produced with the DSS is difficult to process and display in a fashion that allows the full experiment to be visualized in 4-D without shadowing any data. Three-dimensional data plots for an individual fiber can be constructed with graphing software. These plots display the time steps on the x-axis, TSV on the z-axis, and sensor number on the y-axis (Ulrich et al., 2008). Though all the data points are plotted in these figures, some are shadowed by other data in the TSV
Data analysis
Data analysis begins by producing all relevant visualization tools, or products: graphs of headspace P–T data with time through the experiment and graphs of DSS data from the sediment column. data are used to identify time periods and fiber locations of interest. The TSV and P–T products are then inspected, with special attention given to the areas identified in the animations (Fig. 6). This results in a more efficient analysis, likely drawing more conclusions than one could without
Results and discussion
The data shown in Fig. 7, Fig. 8 are from a split column experiment in which sand was on the left side of the column, as shown, and silt was on the right side of the column. The branched diffuser assembly was placed just above the P1 fiber grid. The split sediment column experiment showed little or no hydrate forming on the P1 grid (below the diffuser assembly), significant formation on the P2 grid immediately above the diffuser, and moderate formation on the top two grids (P3, P4). To compare
Concluding remarks
Fiber optic sensing and data analysis methods developed here can also be applied to effectively evaluate the geological behavior of gas hydrates in complex sediment systems during drilling operations, understand the effects of environmental change on gas hydrate reservoirs, and evaluate carbon sequestration techniques. The fiber optic technology utilized here provides data from within the sediments at a resolution and spatial precision that P–T data cannot match. The large network of
Acknowledgments
This work was supported by the U.S. Dept. of Energy, Methane Hydrates Program through the Office of Fossil Energy field work proposal FEAB 111. We gratefully acknowledge technical support by Jonathan Alford. J. R. Leeman was supported through the Higher Education Research Experiences (HERE) program managed by the Oak Ridge Institute for Science Education (ORISE)/Oak Ridge Associated Universities (ORAU) and through the University of Oklahoma School of Geology and Geophysics. Oak Ridge National
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