ALBERT

Description: We have developed a procedure for estimating the effective elastic properties of various mixtures of smectite and kaolinite over a range of confining pressures, based on the individual effective elastic properties of pure porous smectite and kaolinite. Experimental data for the pure samples are used as input to various rock physics models, and the predictions are compared with experimental data for the mixed samples. We have evaluated three strategies for choosing the initial properties in various rock physics models: (1) input values have the same porosity, (2) input values have the same pressure, and (3) an average of (1) and (2). The best results are obtained when the elastic moduli of the two porous constituents are defined at the same pressure and when their volumetric fractions are adjusted based on different compaction rates with pressure. Furthermore, our strategy makes the modeling results less sensitive to the actual rock physics model. The method can help obtain the elastic properties of mixed unconsolidated clays as a function of mechanical compaction. The more common procedure for estimating effective elastic properties requires knowledge about volume fractions, elastic properties of individual constituents, and geometric details of the composition. However, these data are often uncertain, e.g., large variations in the mineral elastic properties of clays have been reported in the literature, which makes our procedure a viable alternative.

Description: Compaction of siliciclastic sediments leads to an increase in their stiffness parameters and seismic velocities. Although mechanical compaction implies a reduction of porosity and closing of compliant pores, chemical compaction may alter the mineral properties, the cementing of grain contacts, and the pore volume. The ability of rock physics models to quantify such effects on seismic observables will aid hydrocarbon exploration. A framework was designed for modeling compaction effects by use of a so-called coated inclusion model that eliminates the need of using a hybrid approach through combining different theories. A basic feature of the model is that the inclusion is defined by a kernel representing the pore, which is surrounded by shells that may individually have different elastic properties from those of the pore-filling material and the background matrix. The modeling can be designed to explore seismic effects of various texture perturbations, including contact cementing and pore-filling processes. The numerical modelings seem to be consistent with the results obtained from other rock physics models. The model allows for the possibility of including small-scale heterogeneities within the rock texture and estimating frequency dispersion together with attenuation due to pore fluid flow. A basic weakness of the method is the relatively large number of parameters needed to describe a porous rock, which will always limit its practical usage. However, its basic physical foundation may provide a reference for understanding the qualitative and quantitative effects of various cementation scenarios on seismic parameters.

Description: To reveal the extent of freezing in subglacial sediments, we estimated S-wave velocity along a glacier using surface-wave analysis. Because the S-wave velocity varies significantly with the degree of freezing of the pore fluid in the sediments, this information is useful for identifying unfrozen zones within subglacial sediments, which again is important for glacier dynamics. We used active-source multichannel seismic data originally acquired for reflection analysis along a glacier at Spitsbergen in the Norwegian Arctic and proposed an effective approach of multichannel analysis of surface waves (MASW) in a glacier environment. Common-midpoint crosscorrelation gathers were used for the MASW to improve lateral resolution because the glacier bed has a rough topology. We used multimode analysis with a genetic algorithm inversion to estimate the S-wave velocity due to the potential existence of a low-velocity layer beneath the glacier ice and the observation of higher modes in the dispersion curves. In the inversion, we included information of ice thickness derived from high-resolution ground-penetrating radar data because a simulation study demonstrated that the ice thickness was necessary to estimate accurate S-wave velocity distribution of deep subglacial sediment. The estimated S-wave velocity distribution along the seismic line indicated that low velocities occurred below the glacier, especially beneath thick ice (∼1300  m/s for ice thicknesses larger than 50 m). Because this velocity was much lower than the velocity in pure ice (∼1800  m/s), the pore fluid was partially melted at the ice–sediment interface. At the shallower subglacial sediments (ice thickness less than 50 m), the S-wave velocity was similar to that of the pure ice, suggesting that shallow subglacial sediments are more frozen than sediments beneath thick ice.