Stereotomography: a semi‐automatic approach for velocity macromodel estimation

Abstract

A B S T R A C TMost methods for velocity macromodel estimation require considerable operator input, mainly concerning the regularization and the picking of events in the data set or in the migrated images. For both these aspects, slope tomography methods offer interesting solutions. They consider locally coherent events characterized by their slopes in the data cube. Picking is then much easier and consequently denser than in standard traveltime tomography. Stereotomography is the latest slope tomography method. In recent years it has been improved significantly, both from an algorithmic point of view and in terms of practical use. Robust and fast procedures are now available for 2D stereotomographic picking and optimization.Concerning the picking, we propose simple criteria for the selection of relevant data among the automatically picked events. This enables an accurate smooth velocity macromodel to be estimated quite rapidly and with very limited operator intervention. We demonstrate the method using a 2D line extracted from the Oseberg NH8906 data set. I N T R O D U C T I O NPrestack depth migration remains the best way of imaging the subsurface, in particular in areas of complex geology. This process is, however, very sensitive to the velocity macromodel and therefore great care must be taken at this very important step (Fagin 1998). Since standard approaches based on Dix's formula are not acceptable in complex media, two main types of method remain available: migration-based velocity analysis (MVA) and traveltime tomography. Tomography is particularly interesting in the case of 3D applications for which MVA is expensive, although traveltime picking in 3D tomography is a difficult and time-consuming process, requiring significant expertise.In order to facilitate the picking, a slope tomography method, known as stereotomography, was proposed for es-

Comparison of prestack stereotomography and NIP wave tomography for velocity model building: Instances from the Messinian evaporites

“…frame of this section, the preprocessing again consisted of multiple suppression using f-k filtering and t 3 gain control to ensure amplification of later events as well as in applying a so-called stereotomographic mute to focus the automatic input data selection on the most relevant traces ͑for details, see Lambaré et al, 2004͒. After preprocessing, semblance was estimated every 50 m using eight traces for calculating local slant stack. The initial thresholds for a pick to be accepted were set to a minimum semblance of 0.6 in each common-shot and common-receiver gather, respectively.…”

A review of the adjoint-state method for computing the gradient of a functional with geophysical applications

“…This example shows the power of the adjoint‐state technique. The third example is the stereotomography, Billette & Lambaré (1998) and Lambaré et al (2004). The link between the adjoint‐state variables and the propagator of the differential equation defining the ray trajectory perturbations, Cervený (2001) and Farra & Madariaga (1987), is established.…”

Residual stereotomographic inversion

“…Although several numerical implementations ͑e.g., Chauris et al, 2002;Billette et al, 2003;Lambaré et al, 2004͒ of the stereotomographic velocity inversion are illustrated in practical applications, automatic picking of locally coherent events in prestack time domain remains a critical point for stereotomography. Lavaud et al ͑2004͒ proposed picking locally coherent events in poststack rather than in prestack domain.…”