Heavy oils are important unconventional hydrocarbon resources with huge reserves. Seismic monitoring of thermal recovery processes makes study of their shear properties important. We measure, within the seismic band, the complex shear modulus (and thus also the attenuation) of a heavy-oil rock, and the oil extracted from it. The modulus and quality factor (Q) of the heavy-oil saturated rock shows a moderate dependence on frequency, but is strongly influenced by temperature. At room temperatures, the extracted heavy oil supports a shear wave, but with increase in temperature, its shear modulus decreases rapidly, which translates to a rapid drop in the shear modulus of the rock as well. At these low to intermediate temperatures (30 • C-100 • C), an attenuation peak corresponding to the viscous relaxation of the heavy oil is encountered.
Recent work on retrieving the Green’s function with the Marchenko equation shows how these functions for a virtual source in the subsurface can be obtained from reflection data. The response to the virtual source is the Green’s function from the location of the virtual source to the surface. The Green’s function is retrieved using only the reflection response of the medium and an estimate of the first arrival at the surface from the virtual source. Current techniques, however, only include primaries and internal multiples. Therefore, all surface-related multiples must be removed from the reflection response prior to Green’s function retrieval. We have extended the Marchenko equation to retrieve the Green’s function that includes primaries, internal multiples, and free-surface multiples. In other words, we have retrieved the Green’s function in the presence of a free surface. The information needed for the retrieval is the same as the current techniques, with the only difference being that the reflection response now also includes free-surface multiples. The inclusion of these multiples makes it possible to include them in the imaging operator, and it obviates the need for surface-related multiple elimination. This type of imaging with Green’s functions is called Marchenko imaging.
Conventional imaging algorithms assume single scattering and therefore cannot image multiply scattered waves correctly. The multiply scattered events in the data are imaged at incorrect locations resulting in spurious subsurface structures and erroneous interpretation. This drawback of current migration/imaging algorithms is especially problematic for regions where illumination is poor (e.g., subsalt), in which the spurious events can mask true structure. Here we discuss an imaging technique that not only images primaries but also internal multiples accurately. Using only surfacereflection data and direct-arrivals, we generate the up-and down-going wavefields at every image point in the subsurface. An imaging condition is applied to these up-and downgoing wavefields directly to generate the image. Because the above algorithm is based on inverse-scattering theory, the reconstructed wavefields are accurate and contain multiply scattered energy in addition to the primary event. As corroborated by our synthetic examples, imaging of these multiply scattered energy helps eliminate spurious reflectors in the image. Other advantages of this imaging algorithm over existing imaging algorithms include more accurate amplitudes, target-oriented imaging, and a highly parallelizable algorithm.
Knowledge of interval attenuation can be highly beneficial in reservoir characterization and lithology discrimination. We combine the spectral-ratio method with velocity-independent layer stripping to develop a technique for the estimation of the interval attenuation coefficient from reflection seismic data. The layer-stripping procedure is based on identifying the reflections from the top and bottom of the target layer that share the same ray segments in the overburden. The algorithm is designed for heterogeneous, arbitrarily anisotropic target layers, but the overburden is assumed to be laterally homogeneous with a horizontal symmetry plane. Although no velocity information about the overburden is needed, interpretation of the computed anisotropic attenuation coefficient involves the phase angle in the target layer. Tests on synthetic P-wave data from layered transversely isotropic and orthorhombic media confirm the high accuracy of 2D and 3D versions of the algorithm. We also demonstrate that the interval attenuation estimates are independent of the inhomogeneity angle of the incident and reflected waves.
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