Turning noise into geologic information: The next big step? A joint EAGE/SEG Forum

It is often said that one geophysicist's noise is another's data, but today it seems that it has never been more the case. Features of seismic records that once were considered noise are now routinely used to aid in imaging the Earth's interior and in deriving rock properties. Sacrosanct noise such as surface waves is now inverted to derive near-surface properties. Multiple reflections, once the interpreter's bane, have long been estimated and removed but now are being used in the imaging process. Even seismic interference is now actively pursued as a source of new data in the guise of simultaneous-source acquisition. And then there is the emerging use of passive seismic data, which once would have been considered as pure noise.ImPhys/Imaging PhysicsApplied Science

Estimation of primaries by sparse inversion incuding the ghost

Today, the problem of surface-related multiples, especially in shallow water, is not fully solved. Although surface-related multiple elimination (SRME) method has proved to be successful on a large number of data cases, the involved adaptive subtraction acts as a weak link in this methodology, where primaries can be distorted due to their interference with multiples. Therefore, recently, SRME has been redefined as a large-scale inversion process, called estimation of primaries by sparse inversion (EPSI). In this process the multi-dimensional primary impulse responses are considered as the unknowns in a largescale inversion process. By parameterizing these impulse responses as spikes in the space-time domain, and using a sparsity constraint in the update step, the algorithm looks for those primaries that, together with their associated multiples, explain the total input data. As the objective function in this minimization process truly goes to zero, the tendency for distorting primaries is greatly reduced. An additional advantage is that imperfections in the data can be included in the forward model and resolved simultaneously, such as the missing near offsets. In this paper it is demonstrated that the ghost effect can also be included in the EPSI formulation after which a ghost-free primary estimate can be obtained, even in the case the ghost notch is within the desired spectrum.IST/Imaging Science and TechnologyApplied Science

Surface-related multiple elimination, an inversion approach

Applied Science

Augmented Full Wavefield Modeling - An Iterative Directional Modeling Scheme for Inhomogeneous Media

We derive a representation theorem for modeling directional wavefields using reciprocity theorem of the convolution-type. A Neumann series expansion of the representation yields a series that is similar to that of Bremmer. A generalized Neumann series is also derived similar to that used for solving the non-directional Lippmann-Schwinger representation. An example shows how the series can model each scattering order separately for inhomogeneous media. This could potentially be useful in imaging and inverse problems

From surface seismic data to reservoir elastic parameters using a full-wavefield redatuming approach

Traditionally, reservoir elastic parameters inversion suffers from the overburden multiple scattering and transmission imprint in the local input data used for the target-oriented inversion. In this paper, we present a full-wavefield approach, called reservoir-oriented joint migration inversion (JMI-res), to estimate the high-resolution reservoir elastic parameters from surface seismic data.As a first step in JMI-res, we reconstruct the fully redatumed data (local impulse responses) at a suitable depth above the reservoir from the surface seismic data, while correctly accounting for the overburden interal multiples and transmission losses. Next, we apply a localized elastic full waveform inversion on the estimated impulse responses to get the elastic parameters. We show that JMI-res thus provides much more reliable local target impulse responses, thus yielding high-resolution elastic parameters, compared to a standard redatuming procedure based on time reversal of data. Moreover, by using this kind of approach we avoid the need to apply a full elastic full waveform inversion-type process for the whole subsurface, as within JMI-res elastic full waveform inversion is only restricted to the reservoir target domain.</p

AVP-preserving estimation of reservoir impulse responses

Estimating the reservoir properties from surface seismic data for a target below a complex overburden is a challenging problem. One of the approaches is to apply reservoir-oriented local inversion schemes on the redatumed local reflection response. In this paper, we propose a process to estimate the reservoir impulse responses (redatumed reflection response) in a complex overburden setting for realistic data with angledependent or angle vs ray parameter (AVP) characteristics. The impulse responses are estimated using Joint Migration Inversion (JMI) followed by sparsity constrained Proximity Transformation. It comprises a full wavefield approach in the sense that it correctly accounts for all internal multiples and transmission effects. As a result, the estimated impulse responses are free of interference related to internal multiples in the overburden. The process involves a noval procedure to estimate the propagation velocity model using the flexibility in the JMI parameterization. We finally show that this proposed JMI redatuming provides a much more reliable local reflection response, compared to standard redatuming based on time reversal of recorded data.</p

Double-blended Seismic Acquisition for High-resolution Imaging

In current seismic acquisition, the firing times between shots is sufficiently large to avoid temporal overlap between records. To economize on survey time, the current compromise is to keep the number of shots to an acceptable minimum. The result is a poorly sampled source domain. We propose to abandon the condition of non-overlapping shot records to allow densely sampled, wide-azimuth source distributions ( source blending ). The rationale is that interpolation is much harder than separation. Blending has significant implications for quality and economics. The blending concept can also be applied in the detector space ( detector blending ). Then, the recording channels consist of a superposition of detected signals, each signal with its own code. With detector blending, many more detectors can be used for the same number of recording channels. This is particularly beneficial when the number of channels is limited, like in wireless recording or OBS. The concept of double blending is defined as the case where both source blending and detector blending are applied. Double blending allows a significant data compression during acquisition. After a deblending procedure, existing processing schemes can be used. However, the challenge is to design new algorithms that do not require a deblending preprocessing step

Towards 3D near-surface correction without NMO: A rank-based approach

To avoid multiple iterations of normal moveout (NMO) velocity estimation followed by short-wavelength statics estimation usually performed on land data, and to also improve the accuracy and computational efficiency of the latter, a low-rank-based residuals statics (LR-ReS) estimation and correction framework has been recently proposed. The method iteratively promotes the low-rank structure in the midpoint-offset-frequency domain of 2D data as statics-free data can be approximated by low-rank matrices, while data influenced by the weathering layers exhibits slow singular values decay. For 3D data, there exist different options to organize it into 2D matrices to be able to compute the singular value decomposition (SVD) required for low-rank approximation. It is also essential to find an organization that reveals the rank structure. We examine the different organization options. Based on finding a suitable sorting domain, we extend the LR-ReS estimation and correction to 3D data. We demonstrate the performance of the method on simulated data and will show field data results during the presentation.ImPhys/Medical ImagingImPhys/Verschuur groupApplied Geophysics and Petrophysic