Seismic Depth Imaging

Seismic_Depth_Imaging

Depth migration of seismic data is a wave equation-based echo-reconstruction technique for subsurface imaging. In the migration process, the recorded pressure waves are used as initial conditions for a wave field that propagates downward and in reverse time in an inhomogeneous medium. Any migration technique begins with an a priori estimate of the velocity field, i.e. a model of the earth's subsurface obtained from an empirical analysis. Traditionally, the efforts of the Imaging and Numerical Geophysics group have gone into the development of innovative migration methods, based on an accurate approximation of the wave equation in the frequency domain, so as to reduce the complexity of the computation while retaining the essential features of the signal propagation. More precisely, the ING team developed an effective 3D Phase Shift Plus Interpolation (PSPI) extrapolation kernel, combining it with an adaptive scheme, based on information theory concepts, for the choice of the reference velocities. The resulting software, a high-performance parallel tool for processing very large data sets, provides an accurate 3D data depth migration, especially in terms of reducing the uncertainties of the geological model during the exploration and development phase. This application, in production since its very first version, has progressively been enriched with new features, such as the management of anisotropy and the generation of angle gathers. Recently, the design of an innovative depth extrapolation operator has led to significantly better results than conventional methods, proving itself to be particularly effective for imaging steep dips in the presence of severe lateral velocity variations.

The aim of this project is to provide a reliable and fast imaging tool to improve the understanding of the subsurface geology through the determination of the sediment thick, the basement depth and the type of material.

Starting from observations of gravity anomalies, imaging and characterization are made possible by reconstructing the mass density distribution of the investigated medium. This basic limitation is brought about from the unavoidable fact that the governing physics and the direct problem formulation lead to the solution of a difficult ill-posed inverse problem. While the direct problem for finding the gravity effects of a given mass density distribution, which is the induced scalar gravitational field, is perfectly unique, the inversion solution is notoriously non-unique since the large number of degrees of freedom exceeds the number of measurements. As a matter of fact, many different geologic configurations can reproduce the same gravity measurements, although, many of them are not of any geophysical interest. To mitigate this difficulty, the role of the interpreter becomes of paramount importance to provide reliable information to shrink the null space of the inverse problem.

These anomalies can then be interpreted by a variety of analytical and computational methods to determine empirically depth, geometry and density that cause the gravity field variations. The inverse problem based on a finite-element Poisson solver as the numerical engine for the solution of the direct and the adjoint problem constitutes an important step forward for the subsurface characterization from zero to 10-50 km.

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