Diffractions always need more advertising. It is true that conventional seismic processing and migration are usually successful in using specular reflections to estimate subsurface velocities and reconstruct the geometry and strength of continuous and pronounced reflectors. However, correct identification of geological discontinuities, such as faults, pinch‐outs, and small‐size scattering objects, is one of the main objectives of seismic interpretation. The seismic response from these structural elements is encoded in diffractions, and diffractions are essentially lost during the conventional processing/migration sequence. Hence, we advocate a diffraction‐based, data‐oriented approach to enhance image resolution—as opposed to the traditional image‐oriented techniques, which operate on the image after processing and migration. Even more: it can be shown that, at least in principle, processing of diffractions can lead to superresolution and the recovery of details smaller than the seismic wavelength. The so‐called reflection stack is capable of effectively separating diffracted and reflected energy on a prestack shot gather by focusing the reflection to a point while the diffraction remains unfocused over a large area. Muting the reflection focus and defocusing the residual wavefield result in a shot gather that contains mostly diffractions. Diffraction imaging applies the classical (isotropic) diffraction stack to these diffraction shot gathers. This focusing‐muting‐defocusing approach can successfully image faults, small‐size scattering objects, and diffracting edges. It can be implemented both in model‐independent and model‐dependent contexts. The resulting diffraction images can greatly assist the interpreter when used as a standard supplement to full‐wave images.

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A B S T R A C TWe review the multifocusing method for traveltime moveout approximation of multicoverage seismic data. Multifocusing constructs the moveout based on two notional spherical waves at each source and receiver point, respectively. These two waves are mutually related by a focusing quantity. We clarify the role of this focusing quantity and emphasize that it is a function of the source and receiver location, rather than a fixed parameter for a given multicoverage gather. The focusing function can be designed to make the traveltime moveout exact in certain generic cases that have practical importance in seismic processing and interpretation. The case of a plane dipping reflector (planar multifocusing) has been the subject of all publications so far. We show that the focusing function can be generalized to other surfaces, most importantly to the spherical reflector (spherical multifocusing). At the same time, the generalization implies a simplification of the multifocusing method. The exact traveltime moveout on spherical surfaces is a very versatile and robust formula, which is valid for a wide range of offsets and locations of source and receiver, even on rugged topography. In two-dimensional surveys, it depends on the same three parameters that are commonly used in planar multifocusing and the common-reflection surface (CRS) stack method: the radii of curvature of the normal and normal-incidence-point waves and the emergence angle. In three dimensions the exact traveltime moveout on spherical surfaces depends on only one additional parameter, the inclination of the plane containing the source, receiver and reflection point. Comparison of the planar and spherical multifocusing with the CRS moveout expression for a range of reflectors with increasing curvature shows that the planar multifocusing can be remarkably accurate but the CRS becomes increasingly inaccurate. This can be attributed to the fact that the CRS formula is based on a Taylor expansion, whereas the multifocusing formulae are double-square root formulae. As a result, planar and spherical multifocusing are better suited to model the moveout of diffracted waves. high-quality time imaging can provide a basis for interpretation in the processing sequence and often a useful one, even in case of poor data quality or strong structural complexity. Time imaging is basically model independent and does not require estimation or construction of a velocity model of the subsurface which is a crucial problem of seismic imaging. In the process of constructing a time image, useful additional products such as an root-mean-square (RMS) velocity and several important wavefield attributes can be obtained. Time-domain

A B S T R A C THigh resolution imaging is of great value to an interpreter, for instance to enable identification of small scale faults, and to locate formation pinch-out positions. Standard approaches to obtain high-resolution information, such as coherency analysis and structure-oriented filters, derive attributes from stacked, migrated images. Since they are image-driven, these techniques are sensitive to artifacts due to an inadequate migration velocity; in fact the attribute derivation is not based on the physics of wave propagation. Diffracted waves on the other hand have been recognized as physically reliable carriers of high-or even super-resolution structural information. However, high-resolution information, encoded in diffractions, is generally lost during the conventional processing sequence, indeed migration kernels in current migration algorithms are biased against diffractions. We propose here methods for a diffractionbased, data-oriented approach to image resolution. We also demonstrate the different behaviour of diffractions compared to specular reflections and how this can be leveraged to assess characteristics of subsurface features. In this way a rough surface such as a fault plane or unconformity may be distinguishable on a diffraction image and not on a traditional reflection image.We outline some characteristic properties of diffractions and diffraction imaging, and present two novel approaches to diffraction imaging in the depth domain. The first technique is based on reflection focusing in the depth domain and subsequent filtering of reflections from prestack data. The second technique modifies the migration kernel and consists of a reverse application of stationary-phase migration to suppress contributions from specular reflections to the diffraction image. Both techniques are proposed as a complement to conventional full-wave pre-stack depth migration, and both assume the existence of an accurate migration velocity.

We study the stability of source mechanisms inverted from data acquired at surface and near‐surface monitoring arrays. The study is focused on P‐wave data acquired on vertical components, as this is the most common type of acquisition. We apply ray modelling on three models: a fully homogeneous isotropic model, a laterally homogeneous isotropic model and a laterally homogeneous anisotropic model to simulate three commonly used models in inversion. We use geometries of real arrays, one consisting in surface receivers and one consisting in ‘buried’ geophones at the near‐surface. Stability was tested for two of the frequently observed source mechanisms: strike‐slip and dip‐slip and was evaluated by comparing the parameters of correct and inverted mechanisms. We assume these double‐couple source mechanisms and use quantitatively the inversion allowing non‐double‐couple components to measure stability of the inversion. To test the robustness we inverted synthetic amplitudes computed for a laterally homogeneous isotropic model and contaminated with noise using a fully homogeneous model in the inversion. Analogously amplitudes computed in a laterally homogeneous anisotropic model were inverted in all three models. We show that a star‐like surface acquisition array provides very stable inversion up to a very high level of noise in data. Furthermore, we reveal that strike‐slip inversion is more stable than dip‐slip inversion for the receiver geometries considered here. We show that noise and an incorrect velocity model may result in narrow bands of source mechanisms in Hudson's plots.