Matteo Ravasi

Nonlinear scattering based imaging in elastic media

With the more widespread introduction of multicomponent recording devices in land and marine ocean-bottom seismic acquisition, elastic imaging may become mainstream in coming years. We have derived new, nonlinear, elastic imaging conditions. A correlation-type representation theorem for perturbed elastic media, commonly used in seismic interferometry to explain how a scattered wave response between two receivers/ sources may be predicted given a boundary of sources/receivers, can be considered as a starting point for the derivation. Here, we use this theorem to derive and interpret imaging conditions for elastic migration by wavefield extrapolation (e.g., elastic reverse-time migration). Some approximations lead to a known, heuristically derived imaging condition that crosscorrelates P- and S-wave potentials that are separated in the subsurface after full-wavefield extrapolation. This formal connection reveals that the nonapproximated correlation-type representation theorem can be interpreted as a nonlinear imaging condition, that accounts also for multiply scattered and multiply converted waves, properly focusing such energy at each image point. We present a synthetic data example using either an ideal (acquisition on a full, closed boundary) or a real (partial boundary) seismic exploration survey, and we demonstrate the importance of nonlinearities in pure- and converted-mode imaging. In PP imaging, they result in better illumination and artifact reduction, whereas in PS imaging they show how zero time-lag and zero space-lag crosscorrelation imaging conditions are not ideal for imaging of converted-mode waves because no conversion arises from zero-offset experiments.

Marchenko Imaging of Volve Field, North Sea

Marchenko redatuming estimates the full response (including internal multiples) from a virtual source inside of an medium, using only reflection measurements at the Earth’s surface and a smooth estimate of the velocity model. As such, it forms a new way to obtain full field propagators to form images of target zones in the subsurface by means of Marchenko imaging, without necessarily have to create detailed models of overburden structure. One of the main obstacles to the application of such novel techniques to field datasets is the set of requirements of the reflection response: it should be wideband, acquired with wide aperture, densely sampled arrays of co-located sources and receivers, and should have undergone removal of direct waves, source and receiver ghosts and free-surface multiples. We use a wave-equation approach to jointly redatum, demultiple, and source designature to transform data recorded using ocean-bottom acquisition systems into a suitable proxy of the reflection response required by the Marchenko scheme. We briefly review the Marchenko redatuming scheme, and present the first encouraging field results of 2D target-oriented imaging of an ocean-bottom cable dataset, acquired over the Volve field. We further discuss the ‘challenge of convergence’ of the Marchenko redatuming scheme for real data.

Robust Marchenko Focusing - Calibrating Surface Reflection with VSP Data

reflection measurements at the Earths surface and an estimate of the direct wave from a focusing point in the subsurface to the acquisition level in order to retrieve the Green’s function between the two. However, the method suffers when an erroneous scaling of the amplitudes and/or a constant phase-shift is introduced to the reflection response, and artifacts caused by internal multiples are not fully suppressed in the retrieved subsurface wave fields. We propose a workflow to calibrate the reflection response, prior to Greens function retrieval via Marchenko focusing, using additional information in the form of a VSP dataset. First a virtual VSP dataset is estimated via Marchenko focusing, to subsequently compare its upgoing component to the upgoing part of the recorded VSP. Thereby, making it possible to correct for a constant phase shift applied to the reflection data. By identifying the minimum residual energy between the virtual VSP and the recorded VSP wave fields, an erroneous scaling of the reflection response can also be corrected. This workflow leads to a more robust Marchenko focusing, where the reflection response can be redatumed to a target zone in the subsurface and used for ghost-free imaging.

Vector-acoustic Reverse-time Migration of Volve OBC Dataset without Up/Down Decomposed Wavefields

Wavefield separation based on the combination of pressure and particle velocity data is generally used to extract the up- and down-going components from multi-component seabed or towed marine seismic recordings prior to imaging. By carefully combining vector-acoustic (VA) data in the extrapolation of shot gathers in reverse-time migration (RTM) we show that wavefield separation (deghosting) can be performed ‘on-the-fly’ at no extra cost. We call such a strategy VARTM and we successfully apply it to a North Sea OBC field dataset, acquired in the Volve field. We also discuss additional advantages of VARTM over standard RTM of up-going only waves such as improved handling of directivity information contained in the acquired vector-acoustic data for clearer shallow sections and imaging of the down-going component of the recorded field (mirror VARTM) without the need for an additional finite difference modelling.

Imaging Strategies Using Marchenko Focusing Functions

The development of Marchenko methods for seismic data has enabled the creation of an array of new imaging, redatuming, and multiple or primary estimation methods. Most of these methods make use of the subsurface up- and down-going Green’s functions produced by the Marchenko scheme. However, equally important outputs are the so-called focusing functions. Here, we establish a novel interpretation of these focusing functions and use it to develop new methods to image the data. One of our methods can be used to image reflectors individually, which demonstrate on two experiments: a synthetic model and a field dataset from the North Sea. Our methods are computationally cheaper than standard Marchenko imaging and is shown to provide more continuous images with fewer artifacts than standard RTM. In addition they show the first individually imaged reflector using a Marchenko method on field data.

Retrieving Reservoir-only Reflection and Transmission Responses from Target-enclosing Extended Images

The Marchenko redatuming approach reconstructs wavefields at depth that contain not only primary reflections, but also multiply-scattered waves. While such fields in principle contain additional subsurface information, conventional imaging approaches cannot tap into the information encoded in internal multiples in a trivial manner. We discuss a new approach that uses the full information contained in Marchenko-redatumed fields, whose output are local reflection and transmission responses that fully enclose a target volume at depth, without contributions from over- or under-burden structures. To obtain the Target-Enclosing Extended Images (TEEIs) we solve a multi-dimensional deconvolution (MDD) problem that can be severely ill-posed, so we offer stable estimates to the MDD problem that rely on the physics of the Marchenko scheme. We validate our method on ocean-bottom field data from the North Sea. In our field data example, we show that the TEEIs can be used for reservoir-targeted imaging using reflection and, for the first time, local transmission responses, shown to be the direct by-product of using internal multiples in the redatuming scheme. Finally, we present local, TEEI-derived reflection and transmission images of the target volume at depth that are structurally consistent with a benchmark image from conventional migration of surface data.

Multi-dimensional Free-surface Multiple Elimination and Source Deblending of Volve OBC Data

The wave-equation approach to signature deconvolution and free-surface related multiple elimination of multi-component ocean-bottom data of Amundsen (2001) has recently been linked to seismic interferometry by multi-dimensional deconvolution (MDD). When applied to simultaneous-source data this method can also unravel and reorganise blended data into sequential source responses. We have generated two blended versions of the Volve OBC dataset and compared the ability of MDD to deblend different types of simultaneous-source acquisitions together with suppressing free-surface multiples. Reverse-time migration of the deblended responses produces seismic images of similar quality to those from truly sequential source data.

Using Sparsity to Improve the Accuracy of Marchenko Imaging of Single and Time-Lapse Seismic Given Imperfect Acquisitiont

Summary Marchenko focusing and imaging are novel methods for processing seismic data while correctly handling multiply scattered energy. Strict requirements in the acquisition geometry, specifically co-location of sources and receivers as well as dense and regular sampling, currently constrain their practical applicability. We reformulate the Marchenko equations to handle the case where there are gaps in the source geometry while receiver sampling remains regular. Comparing different solvers for the newly formulated inversion problem, we find that sparse Marchenko inversion enhances the recovery of focusing functions, filling the gaps caused by the missing sources. This does, however, not translate into a significant improvement in the subsequently produced images, as both least-squares and sparse inversion struggle to eliminate overburden effects in the presence of gaps. Further, we develop a method for co-processing two time-lapse datasets with different source geometries using sparse Marchenko inversion to image 4D effects. Sparse joint Marchenko inversion of multiple datasets results in clear time-lapse images, despite non-repeated source geometries and large fractions of missing sources.

Internal Multiple Prediction - A New Approach Based on Seismic Interferometry and Marchenko Autofocusing

Standard seismic processing steps such as velocity analysis and reverse time migration (imaging) usually assume that all reflections are primaries: multiples represent a source of coherent noise and must be suppressed to avoid imaging artefacts. Suppressions methods are relatively ineffective for internal multiples. We show how to predict and remove internal multiples using Marchenko autofocusing and seismic interferometry. We first show how internal multiples can theoretically be reconstructed in convolutional interferometry by combining purely reflected, up- and down- going Green’s functions from virtual sources in the subsurface. We then generate the relevant up- and down-going wavefields at virtual sources along discrete subsurface boundaries using autofocusing. Then, we convolve purely scattered components of up- and down-going Green’s functions to reconstruct only the internal multiple field which is adaptively subtracted from the measured data. Crucially, this is all possible without detailed modelled information about the Earth’s subsurface. The method only requires surface reflection data and estimates of direct (non-reflected) arrivals between subsurface sources and the acquisition surface. The method is demonstrated on a stratified synclinal model and is particularly robust against errors in the velocity model used.

Beyond Conventional Migration - Nonlinear Subsalt Imaging with Transmissions and Two-sided Illumination

Conventional (linear) migration algorithms use only a small portion of recorded seismic data (primary reflections) because they rely on single-scattering assumptions. Nonlinear imaging methods also use reflected multiply-scattered waves, benefiting from their additional illumination and sensitivity to the model. Primary and multiple reflections are, however, just part of the energy generated during a seismic experiment - transmitted waves are also generated but are usually not recorded by one-sided (surface seismic) acquisition systems. In theory only two-sided illumination of the imaging target would allow this energy to be recorded and used in migration. Here we use a synthetic example of subsalt imaging to show the nature of improvements to the seismic image (and extended image) from the use of multiples and transmitted waves. We then suggest a practical approach to construct the additional fields required by nonlinear two-sided imaging without the need of a velocity model with sharp contrasts and receivers (and/or sources) in the subsurface.