By evaluating the consistency of the Gassmann theory with various inclusion‐based effective medium theories, we investigate the impact of elastic interactions between ellipsoidal pores on the poroelasticity. To rule out any factors that can violate the Gassmann condition, other than elastic interactions, we first construct idealized models that contain only a single set of isolated, identical, and vertically aligned ellipsoidal pores. The numerical simulation suggests that the periodic distribution of ellipsoidal pores generate uniform pore pressure distribution, whereas random distribution of ellipsoidal pores generates heterogeneous pore pressure distributions. Then we analyze the precise conditions under which the underlying Gassmann relationship is valid for various inclusion‐based models. The results reveal the following: (1) Noninteracting effective medium theories are always consistent with the Gassmann prediction, simply because the elastic interactions are ignored. (2) The elastic interactions between randomly distributed pores cause heterogeneous pore pressure that violates the essential requirement of the Gassmann theory. The differential effective medium and self‐consistent approximation theories corresponding to this model thus are inconsistent with the Gassmann prediction. (3) The elastic interactions between periodically distributed pores cause uniform pore pressure; therefore, the Gassmann condition is fully satisfied. The T‐matrix approach explicitly takes into account such elastic interactions and thus is consistent with the Gassmann theory. It is interesting to notice that on top of other well‐known common types of heterogeneities, like pore structure or fluid heterogeneities, the distribution of pores and its associated elastic interactions can be a separate source of heterogeneity, and this makes Gassmann equations not valid anymore.

Diffractions caused by, e.g., faults, fractures, and small-scale heterogeneity localized near the surface are often used in ground-penetrating radar (GPR) reflection studies to constrain the subsurface velocity distribution using simple hyperbola fitting. Interference with reflected energy makes the identification of diffractions difficult. We have tailored and applied a diffraction imaging method to improve imaging for surface reflection GPR data. Based on a plane-wave destruction algorithm, the method can separate reflections from diffractions. Thereby, a better identification of diffractions facilitates an improved determination of GPR wave velocities and an optimized migration result. We determined the potential of this approach using synthetic and field data, and, for the field study, we also compare the estimated velocity structure with crosshole GPR results. For the field data example, we find that the velocity structure estimated using the diffraction-based process correlates well with results from crosshole GPR velocity estimation. Such improved velocity estimation may have important implications for using surface reflection GPR to map, e.g., porosity for fully saturated media or soil moisture changes in partially saturated media because these physical properties depend on the dielectric permittivity and thereby also the GPR wave velocity.

Conventional seismic analysis in partially saturated rocks normally lays emphasis on estimating pore fluid content and saturation, typically ignoring the effect of mobility, which decides the ability of fluids moving in the porous rocks. Deformation resulting from a seismic wave in heterogeneous partially saturated media can cause pore fluid pressure relaxation at mesoscopic scale, thereby making the fluid mobility inherently associated with poroelastic reflectivity. For two typical gas‐brine reservoir models, with the given rock and fluid properties, the numerical analysis suggests that variations of patchy fluid saturation, fluid compressibility contrast, and acoustic stiffness of rock frame collectively affect the seismic reflection dependence on mobility. In particular, the realistic compressibility contrast of fluid patches in shallow and deep reservoir environments plays an important role in determining the reflection sensitivity to mobility. We also use a time‐lapse seismic data set from a Steam‐Assisted Gravity Drainage producing heavy oil reservoir to demonstrate that mobility change coupled with patchy saturation possibly leads to seismic spectral energy shifting from the baseline to monitor line. Our workflow starts from performing seismic spectral analysis on the targeted reflectivity interface. Then, on the basis of mesoscopic fluid pressure diffusion between patches of steam and heavy oil, poroelastic reflectivity modeling is conducted to understand the shift of the central frequency toward low frequencies after the steam injection. The presented results open the possibility of monitoring mobility change of a partially saturated geological formation from dissipation‐related seismic attributes.

Sedimentary rocks are often heterogeneous porous media inherently containing complex distributions of heterogeneities (e.g., fluid patches and cracks). Understanding and modeling their frequency-dependent elastic and adsorption behaviors is of great interest for subsurface rock characterization from multiscale geophysical measurements. The physical parameter of dynamic volumetric strain (DVS) associated with wave-induced fluid flow is proposed to understand the common physics and connections behind known poroelastic models for modeling dispersion behaviors of heterogeneous rocks. We have derived the theoretical formulations of DVS for patchy saturated rock at the mesoscopic scale and cracked porous rock at microscopic grain scales, essentially embodying the wave-induced fluid-pressure relaxation process. By incorporating DVS into the classic Gassmann equation, a simple but practical “dynamic equivalent” modeling approach, the extended Gassmann equation, is developed to characterize the dispersion and attenuation of complex heterogeneous rocks at nonzero frequencies. Using the extended Gassmann equation, the effect of microscopic or mesoscopic heterogeneities with complex distributions on the wave dispersion and attenuation signatures can be captured. Our theoretical framework provides a simple and straightforward analytical methodology to calculate wave dispersion and attenuation in porous rocks with multiple sets of heterogeneities exhibiting complex characteristics. We also demonstrate that, with the appropriate consideration of multiple crack sets and complex fluid patches distribution, the modeling results can better interpret the experimental data sets of dispersion and attenuation for heterogeneous porous rocks.

Bitumen is a very important hydrocarbon resource, which exists in enormous amounts all over the world. Bitumen sands and bitumen carbonates have large percentages of bitumen content. However, the differences in lithology, porosity, and bitumen content cause them to have distinct properties, which can further lead to different production methods. Therefore, it is significant to study the different properties between bitumen sands and bitumen carbonates, so as to further analyze the factors causing the differences and to provide guidance for production. To study the basic properties of the bitumen rocks, we have developed a method to measure the rock samples’ true porosity, which can estimate the porosity even for “as is” samples. The method involves injecting water and can provide relatively accurate estimation of the porosity. Then, we compared the porosities and bitumen content of the bitumen sands and bitumen carbonates from the same area. Due to different rock formation mechanisms, mineral composition, and compaction, bitumen sands and bitumen carbonates show different porosity and bitumen saturation. Based on the differences in porosity and bitumen content, the responses of the bitumen sands and bitumen carbonates under different pressure and temperature conditions are also compared and analyzed. The bitumen sands are more sensitive to pressure and temperature than are the bitumen carbonates, owing to the larger porosities and higher bitumen content. Bitumen carbonates show distinct behaviors from bitumen sands — the velocities drop faster at the high temperature range. In the end, the waveforms of the signals of the bitumen sands and bitumen carbonates are also compared, and the attenuation is calculated. Bitumen sands and bitumen carbonates display stronger attenuation in the middle temperature range, which is related to the bitumen properties. Comparatively stronger attenuation occurs in bitumen sands because of its loose frame and higher bitumen content.