scholarly journals Estimation of the global inventory of methane hydrates in marine sediments using transfer functions

2013 ◽  
Vol 10 (2) ◽  
pp. 959-975 ◽  
Author(s):  
E. Piñero ◽  
M. Marquardt ◽  
C. Hensen ◽  
M. Haeckel ◽  
K. Wallmann
Keyword(s):  
Transfer Function ◽  
Marine Sediments ◽  
Gas Hydrates ◽  
Gas Hydrate ◽  
Large Scale ◽  
Transfer Functions ◽  
Methane Hydrates ◽  
Continental Margins ◽  
Transport Reaction ◽  
Methane Generation

Abstract. The accumulation of gas hydrates in marine sediments is essentially controlled by the accumulation of particulate organic carbon (POC) which is microbially converted into methane, the thickness of the gas hydrate stability zone (GHSZ) where methane can be trapped, the sedimentation rate (SR) that controls the time that POC and the generated methane stays within the GHSZ, and the delivery of methane from deep-seated sediments by ascending pore fluids and gas into the GHSZ. Recently, Wallmann et al. (2012) presented transfer functions to predict the gas hydrate inventory in diffusion-controlled geological systems based on SR, POC and GHSZ thickness for two different scenarios: normal and full compacting sediments. We apply these functions to global data sets of bathymetry, heat flow, seafloor temperature, POC input and SR, estimating a global mass of carbon stored in marine methane hydrates from 3 to 455 Gt of carbon (GtC) depending on the sedimentation and compaction conditions. The global sediment volume of the GHSZ in continental margins is estimated to be 60–67 × 1015 m3, with a total of 7 × 1015 m3 of pore volume (available for GH accumulation). However, seepage of methane-rich fluids is known to have a pronounced effect on gas hydrate accumulation. Therefore, we carried out a set of systematic model runs with the transport-reaction code in order to derive an extended transfer function explicitly considering upward fluid advection. Using averaged fluid velocities for active margins, which were derived from mass balance considerations, this extended transfer function predicts the enhanced gas hydrate accumulation along the continental margins worldwide. Different scenarios were investigated resulting in a global mass of sub-seafloor gas hydrates of ~ 550 GtC. Overall, our systematic approach allows to clearly and quantitatively distinguish between the effect of biogenic methane generation from POC and fluid advection on the accumulation of gas hydrate, and hence, provides a simple prognostic tool for the estimation of large-scale and global gas hydrate inventories in marine sediments.

scholarly journals Estimation of the global inventory of methane hydrates in marine sediments using transfer functions

2012 ◽  
Vol 9 (1) ◽  
pp. 581-626 ◽  
Author(s):  
E. Piñero ◽  
M. Marquardt ◽  
C. Hensen ◽  
M. Haeckel ◽  
K. Wallmann
Keyword(s):  
Transfer Function ◽  
Organic Carbon ◽  
Marine Sediments ◽  
Gas Hydrates ◽  
Gas Hydrate ◽  
Large Scale ◽  
Transfer Functions ◽  
Carbon Accumulation ◽  
Methane Hydrates ◽  
Transport Reaction

Abstract. The accumulation of gas hydrates in marine sediments is essentially controlled by the accumulation of particulate organic carbon (POCar) which is microbially converted into methane, the thickness of the gas hydrate stability zone (GHSZ) where methane can be trapped, and the delivery of methane from deep-seated sediments by ascending pore fluids and gas into the GHSZ. Recently, Marquardt et al. (2010) developed a transfer function to predict the gas hydrate inventory in diffusion-controlled geological systems based on POCar and GHSZ. We present a new parameterization of this function and apply it to global datasets of bathymetry, heat flow, seafloor temperature and organic carbon accumulation estimating a global mass of only 91 Gt of carbon (GtC) stored in marine methane hydrates. Seepage of methane-rich fluids is known to have a pronounced effect on gas hydrate accumulation. Therefore, we carried out a set of systematic model runs with the transport-reaction code in order to derive an extended transfer function explicitly considering upward fluid advection. Using averaged fluid velocities for active and passive margins, which were derived from mass balance considerations, this extended transfer function predicts the formation of gas hydrates along the continental margins worldwide. Different scenarios were investigated resulting in a global mass of sub-seafloor gas hydrates of 400–1100 GtC. Overall, our systematic approach allows to clearly and quantitatively distinguish between the effect of biogenic methane generation from POC and fluid advection on the accumulation of gas hydrate and hence, provides a simple prognostic tool for the estimation of large-scale and global gas hydrate inventories in marine sediments.

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

2010 ◽  
Vol 7 (1) ◽  
pp. 1057-1099
Author(s):  
M. Marquardt ◽  
C. Hensen ◽  
E. Piñero ◽  
K. Wallmann ◽  
M. Haeckel
Keyword(s):  
Transfer Function ◽  
Marine Sediments ◽  
Gas Hydrate ◽  
Numerical Models ◽  
Accumulation Rate ◽  
Parameter Analysis ◽  
General Validity ◽  
Transport Reaction ◽  
Degradation Rates ◽  
Wide Range

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 biogenic CH4 formation. 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/cm2/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. Several tests indicate that the transfer function gives a realistic approximation of the minimum potential GH inventory of low gas flux (LGF) systems. The overall advantage of the presented function is its simplicity compared to complex numerical models: only two easily accessible parameters are needed.

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

2010 ◽  
Vol 7 (9) ◽  
pp. 2925-2941 ◽  
Author(s):  
M. Marquardt ◽  
C. Hensen ◽  
E. Piñero ◽  
K. Wallmann ◽  
M. Haeckel
Keyword(s):  
Transfer Function ◽  
Marine Sediments ◽  
Gas Hydrate ◽  
Numerical Models ◽  
Order Approximation ◽  
Parameter Analysis ◽  
General Validity ◽  
Transport Reaction ◽  
Degradation Rates ◽  
Wide Range

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.

scholarly journals Assessing the measurement transfer function of single-cell RNA sequencing

2016 ◽  
Author(s):  
Hannah R. Dueck ◽  
Rizi Ai ◽  
Adrian Camarena ◽  
Bo Ding ◽  
Reymundo Dominguez ◽  
...  
Keyword(s):  
Transfer Function ◽  
Single Cell ◽  
Rna Sequencing ◽  
Large Scale ◽  
Transfer Functions ◽  
Single Cells ◽  
Biological Information ◽  
Gene Detection ◽  
Single Cell Rna Sequencing ◽  
Scale Control

AbstractRecently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate the measurement transfer functions to be linear above ~5-10 molecules. Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.

Natural Gas Hydrates – A Review of the Resources Offshore Nigeria and around the Globe

2011 ◽  
Vol 4 ◽  
pp. 27-33
Author(s):  
U.P. Igboanusi ◽  
J.U. Okere
Keyword(s):  
Climate Change ◽  
Natural Gas ◽  
Geographical Distribution ◽  
Gas Hydrates ◽  
Co2 Sequestration ◽  
Large Scale ◽  
Continental Margins ◽  
Natural Gas Hydrates ◽  
Pure Methane ◽  
Permafrost Regions

Natural gas hydrates are ice-like materials which exist in permafrost regions and in the continental margins of oceans. They constitute a huge unconventional reservoir of natural gas around the globe including offshore Nigeria. The paper is a review of this important global resource with particular focus on the Nigerian deposits. The reasons for the interest on hydrates are discussed including the potential for the recovery of large quantities of methane, the climate change and ocean floor instability that may result from their dissociation. They may also be exploited for large-scale CO2 sequestration. The geographical distribution of hydrates deposits on earth, the thermodynamics of why they occur in those particular places and source of the methane gas that is eventually enchlathrated into hydrates are discussed. The natural gas in the Nigerian hydrate is essentially biogenic in origin and is almost pure methane (more than 99% methane). The hydrates exist in finely disseminated or massive aggregate forms within clay-rich sediment.

scholarly journals Behavioral Analysis of Various Techniques of Model Order Reduction Used in the Reduction of Large Scale Control System

2019 ◽  
Vol 9 (2) ◽  
pp. 4894-4899
Keyword(s):  
Transfer Function ◽  
Model Order Reduction ◽  
Large Scale ◽  
Transfer Functions ◽  
Order Approximation ◽  
Order Reduction ◽  
Higher Order ◽  
Reduction Technique ◽  
Order System ◽  
Model Order

It is very important task to study the behavior of the processes occurring in the industry. To attain this task, the knowledge of the transfer function of the system should be there. When working in robust environment, these transfer functions becomes so tedious that it becomes very difficult to obtain these transfer functions and hence affects the study of the behavior of these system. Due to this, the requirement for reduction of these transfer function becomes a necessity to analyze the behavior of foresaid systems and it becomes easy to do the desired modifications in the system i.e addition of any feature, desired changes in the behavior etc., furthermore the thing to be kept in consideration while doing the reduction in transfer function that the behavior viz. peak overshoot, settling time, steady state error of the two systems (reduced and the original system) should be approximately same, so it is prime importance that the applied model order reduction technique should provide a more accurate approximation of original higher order system. The paper presents here the different categories of model order reduction techniques that can be applied to achieve the motto of model order reduction of higher order systems. The techniques presented are categorized into the four different categories to understand them and their merits and demerits and these will help in proper selection of the model order reduction technique to obtain the most accurate reduced order approximation of large scale system.

Formation of Natural Gas Hydrates in Marine Sediments: Gas Hydrate Growth and Stability Conditioned by Host Sediment Properties

2006 ◽  
Vol 912 (1) ◽  
pp. 887-896 ◽  
Author(s):  
M. BEN CLENNELL ◽  
PIERRE HENRY ◽  
MARTIN HOVLAND ◽  
JAMES S. BOOTH ◽  
WILLIAM J. WINTERS ◽  
...  
Keyword(s):  
Natural Gas ◽  
Marine Sediments ◽  
Gas Hydrates ◽  
Gas Hydrate ◽  
Sediment Properties ◽  
Natural Gas Hydrates ◽  
Host Sediment

The nucleation of gas hydrates near silica surfaces

2015 ◽  
Vol 93 (8) ◽  
pp. 791-798 ◽  
Author(s):  
Shuai Liang ◽  
Peter G. Kusalik
Keyword(s):  
Gas Hydrates ◽  
Gas Hydrate ◽  
Dynamics Simulation ◽  
Methane Hydrates ◽  
Mineral Surfaces ◽  
Methane Recovery ◽  
Nucleation Behavior ◽  
Silica Surfaces ◽  
Energy Penalty ◽  
Hydrate Reservoirs

Understanding the nucleation and crystal growth of gas hydrates near mineral surfaces and in confinement are critical to the methane recovery from gas hydrate reservoirs. In this work, through molecular dynamics simulation studies, we present an exploration of the nucleation behavior of methane hydrates near model hydroxylated silica surfaces. Our simulation results indicate that the nucleation of methane hydrates can initiate from the silica surfaces despite of the structural mismatch of the two solid phases. A layer of intermediate half-cage structures was observed between the gas hydrate and silica surfaces, apparently helping to minimize the free energy penalty. These results have important implications to our understanding of the effects of solid surfaces on hydrate nucleation processes.

scholarly journals Evidences for Paleo-Gas Hydrate Occurrence: What We Can Infer for the Miocene of the Northern Apennines (Italy)

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 134 ◽  
Author(s):  
Claudio Argentino ◽  
Stefano Conti ◽  
Chiara Fioroni ◽  
Daniela Fontana
Keyword(s):  
Gas Hydrates ◽  
Gas Hydrate ◽  
Northern Apennines ◽  
Stability Field ◽  
Continental Margins ◽  
Shallow Gas ◽  
Hydrate Decomposition ◽  
Oxygen Isotopic ◽  
The Stability ◽  
Seep Carbonate

The occurrence of seep-carbonates associated with shallow gas hydrates is increasingly documented in modern continental margins but in fossil sediments the recognition of gas hydrates is still challenging for the lack of unequivocal proxies. Here, we combined multiple field and geochemical indicators for paleo-gas hydrate occurrence based on present-day analogues to investigate fossil seeps located in the northern Apennines. We recognized clathrite-like structures such as thin-layered, spongy and vuggy textures and microbreccias. Non-gravitational cementation fabrics and pinch-out terminations in cavities within the seep-carbonate deposits are ascribed to irregularly oriented dissociation of gas hydrates. Additional evidences for paleo-gas hydrates are provided by the large dimensions of seep-carbonate masses and by the association with sedimentary instability in the host sediments. We report heavy oxygen isotopic values in the examined seep-carbonates up to +6‰ that are indicative of a contribution of isotopically heavier fluids released by gas hydrate decomposition. The calculation of the stability field of methane hydrates for the northern Apennine wedge-foredeep system during the Miocene indicated the potential occurrence of shallow gas hydrates in the upper few tens of meters of sedimentary column.

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