Marchenko-type integrals typically relate so-called focusing functions and Green's functions via the reflection response measured on the open surface of a volume of interest. Originating from one dimensional inverse scattering theory, the extension to two and three dimensions set in motion various new developments regarding imaging in complex materials. This extension, however, is based on wavefield decomposition inside the volume and a truncated medium state, i.e. a version of the medium that is reflection-free underneath the focusing location, suggesting that evanescent, refracted and diving waves cannot be included in the representation. We elaborate on a new derivation for Marchenko-like integrals that (i) extends the concept of wavefield focusing by using a generalised homogeneous Green's function, (ii) is based on partial differential equations and thereby allows for additional insights and a new physical intuition for Marchenko equations, (iii) unifies wavefield focusing for open and closed boundary systems, (iv) does not require wavefield decomposition or a truncated medium state, thus including the full wavefield Green's function, (v) enables using forward modelling to obtain, e.g., Marchenko-type, time-compact focusing functions. We place a particular focus on the latter point, illustrating and investigating how to solve the underlying partial differential equations for various types of focusing functions. This paves the way for a deeper understanding of focusing functions as well as advanced full wavefield Marchenko schemes. While the derivations are generally presented for the 3D case, we show numerical examples in 1D.

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Marchenko methods can retrieve both Green’s functions and focusing functions from single-sided reflection data and a smooth velocity model, as essential components of a redatuming process. Recent studies also show that a modified Marchenko scheme can reconstruct primary-only reflection responses directly from reflection data without requiring a priori model information. To provide insight into the artifacts that arise when input data are not ideally sampled, we study the effects of subsampling in both types of Marchenko methods in 2D earth and data — by analyzing the behaviour of Marchenko-based results on synthetic data subsampled in sources or receivers. We show with a layered model that for Marchenko redatuming, subsampling effects jointly depend on the choice of integration variable and the subsampling dimension, originated from the integrand gather in the multidimensional convolution process. When reflection data are subsampled in a single dimension, integrating on the other yields spatial gaps together with artifacts while integrating on the subsampled dimension produces aliasing artifacts but without spatial gaps. Our complex subsalt model shows the subsampling may lead to very strong artifacts, which can be further complicated by having limited apertures. For Marchenko-based primary estimation (MPE), subsampling below a certain fraction of the fully-sampled data can cause MPE iterations to diverge, which can to some extent be mitigated by using more robust iterative solvers, such as LSQR. Our results, covering redatuming and primary estimation in a range of subsampling scenarios, provide insights that can inform acquisition sampling choices as well as processing parameterization and quality control, e.g., to set up appropriate data filters and scaling to accommodate the effects of dipole fields, or to help ensuring that the data interpolation achieves the desired levels of reconstruction quality that minimize subsampling artifacts in Marchenko-derived fields and images.@en

The Marchenko methods can retrieve both Green's functions and focusing functions from single-sided reflection data and an initial focusing function. Recent studies also show that they can be applied to eliminating multiples directly from reflection data without requiring model information as the input. In this work, we study the effect of limited acquisition sampling on both the output focusing functions and the primary estimation results obtained from Marchenko methods. For focusing functions output from the coupled Marchenko system, downsampling in either source or receiver leads to absolute amplitude errors, with the addition of spatial aliasing brought by receiver subsampling. For the projected Marchenko system used in primary estimation, downsampling in these two dimensions can completely contaminate output primaries with multiples, with similar spatial gaps brought by receiver downsampling. Therefore, the acquisition geometry has a significant impact on results of the Marchenko methods, which must be taken into account in realistic acquisition scenarios.@en

The Marchenko method retrieves Green's functions between the acquisition surface and any arbitrary point in the medium. The process generally involves solving an inversion starting with an initial focusing function, e.g., a direct-wave Green's function from the desired subsurface position, typically obtained using an approximate velocity model. We have formulated the Marchenko method in the time-imaging domain. In that domain, we recognize that the traveltime of the direct-wave Green's function is related to the Cheop's traveltime pyramid commonly used in time-domain processing, which in turn can be readily obtained from the local slopes of the common-midpoint gathers. This observation allows us to substitute the velocity-model-based initial focusing operator with that from a data-driven slope estimation process. Moreover, we found that working in the time-imaging domain allows for the specification of the desired subsurface position in terms of vertical time, which is connected to the Cartesian depth position via the time-to-depth conversion. Our results suggest that the prior velocity model is only required when specifying the position in depth, but this requirement can be circumvented by making use of the time-imaging domain within its usual assumptions (e.g., mild lateral heterogeneity). Provided that those assumptions are satisfied, the estimated Green's functions from the proposed method have comparable quality to those obtained with the knowledge of a prior velocity model.

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Marchenko redatuming can retrieve the impulse response to a subsurface virtual source from the single-sided surface reflection data with limited knowledge of the medium. We illustrate the concepts and practical aspects of Marchenko redatuming on a simple 1D acoustic lossless medium in which the coupled Marchenko equations are exact. Defined in a truncated version of the actual medium, the Marchenko focusing functions focus the wavefields at the virtual source location and are responsible for the subsequent retrieval of the downgoing and upgoing components of the medium's impulse response. In real seismic exploration, where we have no access to the truncated medium, we solve the coupled Marchenko equations by iterative substitution, relying on the causality relations between the focusing functions and the desired Green's functions along with an initial estimate of the downgoing focusing function. We show that the amplitude accuracy of the initial focusing function influences that of the retrieved Green's functions. During each iteration, propagating an updated focusing function into the actual medium can be approximated by explicit convolution with the broadband reflection seismic data after appropriate processing, which acts as a proxy for the true medium's reflection response.

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The characterisation of complex overburden structures can be key for seismic imaging in many geologic settings. To this end, one of the main challenges can be the separation of overburden signals from those coming from deeper structures. Here, we present a data-driven, focusing-based approach to extract full-waveform overburden-only transmission responses from surface-acquired reflection seismic data. Our approach builds on the Marchenko redatuming framework, which is capable of retrieving subsurface fields at depth, containing all internal multiples, from surface reflection data. Intrinsic to the Marchenko scheme is the retrieval of focusing functions, which by definition are sensitive only to overburden properties. Here, we show that the overburden-only transmission can be obtained directly by combining the focusing coda, a by-product of Marchenko redatuming, with a model-based reference transmission. Our transmission estimate can be obtained by inversion of the focusing operator, as well as by a numerically stable, series-based iterative scheme. We present our transmission estimation approach for acoustic and elastic media, and validate both cases using numerical examples. Our examples show that, within its domain of validity, our series-based transmission estimates quickly converge to the desired transmission responses, with good accuracy both in terms of kinematics and absolute amplitudes.@en

The Marchenko method represents a constructive technique toobtain Green�s functions between the acquisition surface andany arbitrary point in the medium. The process generally involvessolving an inversion starting with a direct-wave Green's function from the desired subsurface position, which is typicallyobtained using an approximate velocity model. In thisstudy, we first propose to formulate the Marchenko method inthe time-imaging domain. We recognize that the traveltimeof the direct-wave Green�s function is related to the Cheop�straveltime pyramid commonly used in time-domain processingand can be readily obtained from the local slopes of thecommon-midpoint (CMP) gathers. This observation allowsus to substitute the need for a prior velocity model with thedata-driven slope estimation process. Moreover, we show thatworking in the time-imaging domain allows for the specificationof the desired subsurface position in terms of vertical time,which is connected to the Cartesian depth position via the timeto-depth conversion. Our results suggest that the prior velocitymodel is only required when specifying the position in depthbut this requirement can be circumvented by making use of thetime-imaging domain and its usual assumptions. Provided thatthose assumptions are satisfied, the estimated Green�s functionsfrom the proposed method have comparable quality tothose obtained with the knowledge of a prior velocity@en

Seismic reflection data can be redatumed to a specified boundary in the subsurface by solving an inverse (or multidimensional deconvolution) problem. The redatumed data can be interpreted as an extended image of the subsurface at the redatuming boundary, depending on the subsurface offset and time. We retrieve targetenclosed extended images by using two redatuming boundaries, which are selected above and below a specified target volume. As input, we require the upgoing and downgoing wavefields at both redatuming boundaries due to impulsive sources at the earth's surface. These wavefields can be obtained from actual measurements in the subsurface, they can be numerically modeled, or they can be retrieved by solving a multidimensional Marchenko equation. As output, we retrieved virtual reflection and transmission responses as if sources and receivers were located at the two target-enclosing boundaries. These data contain all orders of reflections inside the target volume but exclude all interactions with the part of the medium outside this volume. The retrieved reflection responses can be used to image the target volume from above or from below. We found that the images from above and below are similar (given that the Marchenko equation is used for wavefield retrieval). If a model with sharp boundaries in the target volume is available, the redatumed data can also be used for two-sided imaging, where the retrieved reflection and transmission responses are exploited. Because multiple reflections are used by this strategy, seismic resolution can be improved significantly. Because target-enclosed extended images are independent on the part of the medium outside the target volume, our methodology is also beneficial to reduce the computational burden of localized inversion, which can now be applied inside the target volume only, without suffering from interactions with other parts of the medium.

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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.@en