High-resolution seismic experiments, employing arrays of closely spaced, four-component ocean-bottom seismic recorders, were conducted at a site off western Svalbard and a site on the northern margin of the Storegga slide, off Norway to investigate how well seismic data can be used to determine the concentration of methane hydrate beneath the seabed. Data from P-waves and from S-waves generated by P-S conversion on reflection were inverted for P-and S-wave velocity (Vp and Vs), using 3D travel-time tomography, 2D ray-tracing inversion and 1D waveform inversion. At the NW Svalbard site, positive Vp anomalies above a sea-bottomsimulating reflector (BSR) indicate the presence of gas hydrate. A zone containing free gas up to 150-m thick, lying immediately beneath the BSR, is indicated by a large reduction in Vp without significant reduction in Vs. At the Storegga site, the lateral and vertical variation in Vp and Vs and the variation in amplitude and polarity of reflectors indicate a heterogeneous distribution of hydrate that is related to a stratigraphically mediated distribution of free gas beneath the BSR. Derivation of hydrate content from Vp and Vs was evaluated, using different models for how hydrate affects the seismic properties of the sediment host and different approaches for estimating the background velocity of the sediment host. The error in the average Vp of an interval of 20-m thickness is about 2.5%, at 95% confidence, and yields a resolution of hydrate concentration of about 3%, if hydrate forms a connected framework, or about 7%, if it is both pore-filling and framework-forming. At NW Svalbard, in a zone about 90-m thick above the BSR, a Biot-theory-based method predicts hydrate concentrations of up to 11% of pore space, and an effective-medium-based method predicts concentrations of up to 6%, if hydrate forms a connected framework, or 12%, if hydrate is both pore-filling and frameworkforming. At Storegga, hydrate concentrations of up to 10% or 20% were predicted, depending on the hydrate model, in a zone about 120-m thick above a BSR. With seismic techniques alone, we can only estimate with any confidence the average hydrate content of broad intervals containing more than one layer, not only because of the uncertainty in the layer-by-layer variation in lithology, but also because of the negative correlation in the errors of estimation of velocity between adjacent layers. In this investigation, an interval of about 20-m thickness (equivalent to between 2 and 5 layers in the model used for waveform inversion) was the smallest within which one could sensibly estimate the hydrate content. If lithological layering much thinner than 20-m thickness controls hydrate content, then hydrate concentrations within layers could significantly exceed or fall below the average values derived from seismic data.

S U M M A R YThe presence of gas hydrate in oceanic sediments is mostly identified by bottom-simulating reflectors (BSRs), reflection events with reversed polarity following the trend of the seafloor. Attempts to quantify the amount of gas hydrate present in oceanic sediments have been based mainly on the presence or absence of a BSR and its relative amplitude. Recent studies have shown that a BSR is not a necessary criterion for the presence of gas hydrates, but rather its presence depends on the type of sediments and the in situ conditions. The influence of hydrate on the physical properties of sediments overlying the BSR is determined by the elastic properties of their constituents and on sediment microstructure. In this context several approaches have been developed to predict the physical properties of sediments, and thereby quantify the amount of gas/gas hydrate present from observed deviations of these properties from those predicted for sediments without gas hydrate.We tested four models: the empirical weighted equation (WE); the three-phase effectivemedium theory (TPEM); the three-phase Biot theory (TPB) and the differential effectivemedium theory (DEM). We compared these models for a range of variables (porosity and clay content) using standard values for physical parameters. The comparison shows that all the models predict sediment properties comparable to field values except for the WE model at lower porosities and the TPB model at higher porosities. The models differ in the variation of velocity with porosity and clay content. The variation of velocity with hydrate saturation is also different, although the range is similar. We have used these models to predict velocities for field data sets from sediment sections with and without gas hydrates. The first is from the Mallik 2L-38 well, Mackenzie Delta, Canada, and the second is from Ocean Drilling Program (ODP) Leg 164 on Blake Ridge. Both data sets have V p and V s information along with the composition and porosity of the matrix. Models are considered successful if predictions from both V p and V s match hydrate saturations inferred from other data. Three of the models predict consistent hydrate saturations of 60-80 per cent from both V p and V s from log and vertical seismic profiling data for the Mallik 2L-38 well data set, but the TPEM model predicts 20 per cent higher saturations, as does the DEM model with a clay-water starting medium. For the clay-rich sediments of Blake Ridge, the DEM, TPEM and WE models predict 10-20 per cent hydrate saturation from V p data, comparable to that inferred from resistivity data. The hydrate saturation predicted by the TPB model from V p is higher. Using V s data, the DEM and TPEM models predict very low or zero hydrate saturation while the TPB and WE models predict hydrate saturation very much higher than those predicted from V p data. Low hydrate saturations are observed to have little effect on V s . The hydrate phase appears to be connected within the sediment microstructure even at low saturations.

We present a new petro-elastical and numerical-simulation methodology to compute synthetic seismograms for reservoirs subject to CO 2 sequestration. The petro-elastical equations model the seismic properties of reservoir rocks saturated with CO 2 , methane, oil and brine. The gas properties are obtained from the van der Waals equation and we take into account the absorption of gas by oil and brine, as a function of the in situ pore pressure and temperature. The dry-rock bulk and shear moduli can be obtained either by calibration from real data or by using rock-physics models based on the Hertz-Mindlin and Hashin-Shtrikman theories. Mesoscopic attenuation due to fluids effects is quantified by using White's model of patchy saturation, and the wet-rock velocities are calculated with Gassmann equations by using an effective fluid modulus to describe the velocities predicted by White's model. The simulations are performed with a poro-viscoelastic modeling code based on Biot's theory, where viscoelasticity is described by generalizing the solid/fluid coupling modulus to a relaxation function. Using the pseudo-spectral method, which allows general material variability, a complete and accurate characterization of the reservoir can be obtained. A simulation, that considers the Utsira sand of the North Sea, illustrates the methodology.

We obtain the wave velocities and quality factors of gas‐hydrate‐bearing sediments as a function of pore pressure, temperature, frequency and partial saturation. The model is based on a Biot‐type three‐phase theory that considers the existence of two solids (grains and gas hydrate) and a fluid mixture. Attenuation is described with the constant‐Q model and viscodynamic functions to model the high‐frequency behaviour. We apply a uniform gas/water mixing law that satisfies Wood's and Voigt's averages at low and high frequencies, respectively. The acoustic model is calibrated to agree with the patchy‐saturation theory at high frequencies (White's model). Pressure effects are accounted by using an effective stress law for the dry‐rock moduli and permeabilities. The dry‐rock moduli of the sediment are calibrated with data from the Cascadia margin. Moreover, we calculate the depth of the bottom simulating reflector (BSR) below the sea floor as a function of sea‐floor depth, geothermal gradient below the sea floor, and temperature at the sea floor.

A B S T R A C TWe estimate the quality factor (Q) from seismic reflections by using a tomographic inversion algorithm based on the frequency-shift method. The algorithm is verified with a synthetic case and is applied to offshore data, acquired at western Svalbard, to detect the presence of bottom-simulating reflectors (BSR) and gas hydrates. An array of 20 ocean-bottom seismographs has been used.The combined use of traveltime and attenuation tomography provides a 3D velocity-Q cube, which can be used to map the spatial distribution of the gas-hydrate concentration and free-gas saturation. In general, high P-wave velocity and quality factor indicate the presence of solid hydrates and low P-wave velocity and quality factor correspond to free-gas bearing sediments.The Q-values vary between 200 and 25, with higher values (150-200) above the BSR and lower values below the BSR (25-40). These results seem to confirm that hydrates cement the grains, and attenuation decreases with increasing hydrate concentration.