Patrice Guillaume

A 3D subsalt tomography based on wave-equation migration-perturbation scans

We have developed a simple but practical methodology for updating subsalt velocities using wave-equation, migration-perturbation scans. For the sake of economy and scalability (with respect to full source-receiver migration) and accuracy (with respect to common-azimuth migration), we use shot-profile, wave-equation migration. As input for subsalt-velocity analysis, we provide wave-equation migration scans with velocity scanning limited to the subsalt sediments. Throughout the migration-scan sections, we look for the best focusing or structural positioning of characteristic seismic events. The picking on the migration stacks selects the value of the best perturbation attribute (alpha-scaling factor) along with the corresponding position and local dip for the chosen seismic events. The associated, locally coherent events are then demigrated to the base of the salt horizon. Our key observation is that this process is theoretically equivalent to performing a datuming to a base of salt followed by subsalt migr...

Kinematic invariants: an efficient and flexible approach for velocity model building

We present a fast turnaround strategy for building depth velocity models from kinematic invariants. Our approach is based on the concept of kinematic invariants describing locally coherent events by their position and slopes in the un-migrated pre-stack domain. 3D slope tomography can be based on kinematic invariants that fully characterize the events in terms of positioning and focusing. Kinematic invariants offer a versatile tool for velocity model building as they can be derived from dip and move-out picks made either in pre-stack depth migrated (preSDM) or pre-stack time migrated (preSTM) domains, or even in the unmigrated domain. Since the invariants are in the unmigrated domain, they only need to be picked once. The classical iterative velocity update made of several iterations of RMO picking, pre-stack migration and velocity update can thus be replaced by a more efficient sequential approach involving a single preSDM and a single residual move-out (RMO) picking followed by a non-linear tomographic inversion, should the quality of the initial PreSDM be appropriate for an automated volumetric picking.

Geologically consistent velocities obtained by high definition tomography

Velocity model building remains a crucial step in seismic depth imaging. Advances in residual move-out picking, which can now be performed very densely in 5D, and in applied mathematics (solvers can now apply to huge linear systems) make it possible to fine-tune the tomography with the view of improving the definition of the estimated velocity models. By carefully choosing velocity model parameters and by tailoring inversion criterion to locally coherent events picked with maximum density, data term in cost function can be maximized with respect to smoothing term, and high definition velocity models can be obtained. We illustrate the method on both synthetic and real examples involving structural complexities.

3D Finite Angle Tomography Based On Focusing Analysis

We have developed a new 3D finite angle tomography based on the analysis of focusing errors. The seismic input to this new velocity analysis is a set of migration panels that are stacked images formed at various imaging conditions, zerotime or non zero-time. By comparing these different common focusing error panels the best focused events and their corresponding focusing errors are picked. The picked focusing errors and associated local reflector attributes (position and dip) are then fed into the existing 3D finite angle tomography to update the velocity model. This new technique complements the input to our existing 3D tomography based on either residual curvature analysis or migration scan, and is a cost effective alternative to the latter. It is particularly appropriate in subsalt areas where migrated seismic data have poor signal to noise ratio.

3D Finite-offset Depth Tomography Model Building: Green Canyon, Gulf of Mexico

A more detailed velocity analysis is required for successful pre-stack depth migration model building and tomographic methods offer a potential solution. However, migration velocity analysis is often a underdetermined problem. We present a new finite-offset depth tomography scheme that overcomes the problems of non-linearity and allows us to perform automatic dense velocity analysis in structurally complex areas were classical linear methods fail. We demonstrate the advantage of the new tomography scheme on a deep offshore Gulf of Mexico dataset from the Green Canyon area.

Automatic, dense and volumetric picking for high‐resolution 3D tomographic model building

Summary As survey sizes are steadily increasing, 3D tomogra phy as the key component of today’s velocity model buildin g workflows has to be performed on large data volumes within acceptable turnaround times. To provide high resolution velocity models, dense volumetric pickin g is required. This leads to even larger data volumes. I t is therefore paramount to automate as many processing steps as possible to free the time of the geophysicist fo r the necessary QC. In this paper we present a modified workflow for high-resolution 3D tomography addressing the need for process automation. We are putting the emphasis of this paper on data preparation and the quality control of the inversion phase. The presented workf low allows performance of high-resolution tomography work on large data volumes over a significantly reduced cyc le time.

Non-linear Slope Tomography From RTM And Kirchhoff Angle Domain Common-image Gathers

In Montel and Lambare (2011), we put in evidence the pitfalls when using angle domain common-image gathers (ADCIGs) for velocity model building and the ways to solve for them. Using non-linear slope tomography, we show here through a complex synthetic example the critical role of a good understanding of the kinematic observed in the ADCIGs. We show what happens when handling things the “wrong” and the “right” way to get a good quantitative idea of the improvement we can expect from an accurate theoretical analysis of the kinematics of ADCIGs.

Can we correct for azimuthal variations of residual move-out in land WAZ context, using depth non-linear slope tomography? An imaging case history.

Summary High-density wide azimuth (WAZ) land surface acquisitions have demonstrated superior imaging capabilities. However, processing of such data exhibits several challenges related to the traditionally poor signal-to-noise ratio of land data and the necessity of reconciling the kinematics of the various azimuths. In this paper, we present an imaging case history involving WAZ non-linear slope tomography. Using the concept of kinematic invariants, velocity model update is performed both in depth and time based on the same picking. Our dense automated dip and residual move-out (RMO) picking is done on an initial pre-stack time migrated (PreSTM) dataset after application of a structurally consistent filtering that greatly improves the signal-to-noise ratio. Our case study demonstrates that non-linear slope tomography in the depth domain greatly improves the imaging of the structures when compared to the initial PreSTM result. We observe that even if tomography in the time domain significantly enhances imaging, it cannot successfully honour the kinematics of the various azimuths within the constraints of time imaging assumptions. On the contrary, WAZ nonlinear slope tomography in the depth domain offers an efficient way to reconcile these kinematics, thus promoting the use of depth imaging when processing high-density WAZ data, even in the context of mild geological complexity.

Non-linear slope tomography: extension to MAZ and WAZ.

An optimal velocity model building in depth requires combining various types of information. This can be expressed and solved efficiently as a non-linear optimization problem. Among the various non-linear tomography methods proposed for velocity model building in depth, non-linear slope tomography copes ideally with kinematic information obtained from a dense volumetric picking that yields a high-density resolution of the velocity model. We show how non-linear slope tomography has been extended to Multi-Azimuth and Wide-azimuth acquisitions resulting in improved velocity model resolution due to wave path redundancy and complementary information. We address both picking and velocity update aspects and, in particular, the kinematic migration and demigration processes.

From Time to Depth Imaging: an Accurate Workflow

We present a new strategy for depth velocity model building from pre-stack time migrated gathers. It is based on a dense volumetric dip and residual move-out (RMO) picking in the prestack time migrated domain. The kinematic information is demigrated to compute multioffset un-migrated attributes – called seismic invariants – used as input data for a multi-offset depth tomography. Compared to the corresponding existing strategy based on picking in the depth migrated domain, our new strategy allows to fully take advantage of a previous time imaging project. It bypasses the initial depth model building and initial prestack depth migration required for picking RMO in depth. Furthermore it takes advantage of the quality of a picking phase carried out on already reasonably focused time migrated dataset, with no compromise on the accuracy. We demonstrate the relevance of the approach on a real dataset.