5. Laboratory/Scaled Geophysics -Invited-
Seismic Methods to Detect Gas-hydrate Bearing Sediments
Jose' M. Carcione
Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Italy.
Abstract
Gas hydrate is composed of water and natural gas, mainly methane, which forms under conditions of low temperature, high pressure, and proper gas concentration (1 m3 hydrate is equal 164 m3 free gas plus 0.8 m3 water). Joseph Priestley is believed to have produced oxygen hydrate in 1778, and Humphrey Davy in 1810 and Michael Faraday in 1823 synthesised chlorine hydrate. Methane hydrate occurs in two types of geologic settings: on land in permafrost regions, and beneath the ocean floor at water depths greater than about 500 m where conditions of low temperature, high pressure, and proper gas concentration dominate. Gas hydrate is a potential energy resource, and can be the cause of slope failure offshore (a submarine geohazard) and an important issue in global warming (greenhouse effect). Bottom Simulating Reflectors (BSRs) on seismic profiles are interpreted to represent the seismic signature of the base of gas-hydrate formation; a free gas zone may be present just below the BSR. Where no direct measurements are available, detailed knowledge of the seismic properties is essential for quantitative estimations of gas hydrate and free gas in sediments.The discrepancies between the velocity profile and the velocity for water-filled, normally compacted, marine sediments are interpreted as due to the presence of gas hydrate (positive anomalies) and free gas (negative anomalies). These anomalies can be translated in terms of concentration of clathrate and free gas, knowing the velocity trend versus gas hydrate and free gas content.We first present a theory to 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 behavior. 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 BSR below the sea floor as a function of sea-floor depth, geothermal gradient below the sea floor, and temperature at the sea floor.Then, we propose a modeling algorithm for wave simulation in a three-phase porous medium composed of sand grains, ice (or hydrate) and water. We first obtain the time-domain stress-strain relations for non-uniform porosity and the corresponding differential equations based on the Lagrangian.The displacements of the rock and ice frames and the variation of fluid content are the generalized coordinates, and the stress components and fluid pressure are the generalized forces. An example shows the simulation wave propagation in a frozen porous medium with fractal variations of porosity and, therefore, realistic freezing conditions. The low-frequency limit yields the generalized Gassmann modulus, used to estimate the hydrate concentration.
We present two field examples. First, an area located at the western Svalbard margin. The method is based on P-wave velocities computed by reflection tomography applied to multi-component ocean-bottom seismometer (OBS) data. The tomographic velocity field is fitted to theoretical velocities obtained from the poroelastic model based on the Biot-type approach. Next, we estimate the concentration of gas hydrate at the Mallik 2L-38 research site using P- and S-wave velocities obtained from well logging and vertical seismic profiles (VSP). The dry-rock moduli are estimated from the log profiles, in sections where the rock is assumed to be fully saturated with water. In the Svalbard case, the quality factor is also estimated from the data by using attenuation tomography based on the frequency-shift method.
Last modified: Wed May 03 00:40:48 2006