Application of the redundant‐lifting scheme for ground‐roll attenuation in near‐surface characterization using full‐waveform inversion on P‐wave seismic data

2020 ◽  
Vol 68 (7) ◽  
pp. 2078-2093
Author(s):  
Md Iftekhar Alam ◽  
Khemraj Shukla
Keyword(s):  
Seismic Data ◽  
Surface Characterization ◽  
Waveform Inversion ◽  
Lifting Scheme ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Full Waveform ◽  
Ground Roll

Full Waveform Inversion for the Near Surface Characterization, Onshore UAE, Case Study

2021 ◽  
Author(s):  
Rahul Dixit ◽  
Pavel Vasilyev ◽  
Ivica Mihaljevic ◽  
Michelle Tham ◽  
Denes Vigh ◽  
...  
Keyword(s):  
Seismic Data ◽  
Surface Characterization ◽  
Waveform Inversion ◽  
Surface Modeling ◽  
Surface Model ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Seismic Responses ◽  
Near Surface ◽  
Full Waveform

Abstract Full-waveform inversion (FWI) has become a well-established method for obtaining a detailed earth model suitable for improved imaging, near-surface characterization and pore-pressure prediction. FWI for onshore data has always been challenging and has seen limited application (Vigh et al, 2018). It requires a dedicated data processing approach related to the lower signal-to-noise ratio, accounting for variable topography and complex near-surface related effects. During the past few years, ADNOC has been acquiring and processing one of the world's largest combined 3D onshore and offshore seismic surveys in the Emirate of Abu Dhabi. The modern acquisition parameters that were implemented enabled the acquisition of broadband onshore seismic data rich in low frequencies that could benefit the initial stages of the FWI workflow. Sand dunes and sabkha layers at the surface, and high-velocity carbonate and dolomite layers in the subsurface pose a significant challenge for near-surface modeling in the UAE. The purpose of this work is to evaluate FWI application onshore UAE for near-surface characterization. We will compare the FWI results with conventional approaches for the near-surface model building that has been used routinely on land datasets in UAE, such as data-driven image-based statics (DIBS, Zarubov et al, 2019). One of the main challenges is data preconditioning, as onshore seismic data typically exhibits high levels of noise. It is imperative to denoise gathers sufficiently prior to the FWI process. A well sonic velocity function with large smoothing was used to build the starting velocity model for FWI. The process aims to minimize the least-squared difference between predicted and observed seismic responses by means of updating the model on which the prediction is based. As the predicted and seismic responses are functions of model parameters as well as source signature, a good estimate of the source wavelet is important for update and convergence in FWI. During this FWI work, source wavelet inversion was done as a separate step and used in subsequent FWI passes. FWI inversion started with adjustive FWI (Kun et al, 2015) on lower frequencies, moving to higher frequencies where both adjustive and least square objective functions were used. We will further show assessment of the anisotropy, initial conditions, usage of geological constraints, and comparisons to the conventional solutions. A comparison of results shows that FWI has successfully added velocity details to the near-surface model that follow the geological trend and conforms to well information while producing a plausible static solution. We have demonstrated the application of FWI onshore UAE for near-surface modeling. Although turnaround time (TAT) has increased compared to the conventional approach, the learning that was gained during this trial will decrease TAT for the future FWI work.

scholarly journals Full waveform inversion of short-offset, band-limited seismic data inthe Alboran basin (SE Iberia)

2019 ◽  
Author(s):  
Clàudia Gras ◽  
Valentí Sallarès ◽  
Daniel Dagnino ◽  
C. Estela Jiménez ◽  
Adrià Meléndez ◽  
...  
Keyword(s):  
Travel Time ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Time Inversion ◽  
Full Waveform ◽  
Travel Time Tomography ◽  
Band Limited

Abstract. We present a high-resolution P-wave velocity model of the sedimentary cover and the uppermost basement until ~ 3 km depth obtained by full-waveform inversion of multichannel seismic data acquired with a 6 km-long streamer in the Alboran Sea (SE Iberia). The inherent non-linearity of the method, especially for short-offset, band-limited seismic data as this one, is circumvented by applying a data processing/modeling sequence consisting of three steps: (1) data re-datuming by back-propagation of the recorded seismograms to the seafloor; (2) joint refraction and reflection travel-time tomography combining the original and the re-datumed shot gathers; and (3) FWI of the original shot gathers using the model obtained by travel-time tomography as initial reference. The final velocity model shows a number of geological structures that cannot be identified in the travel-time tomography models or easily interpreted from seismic reflection images alone. A sharp strong velocity contrast accurately defines the geometry of the top of the basement. Several low-velocity zones that may correspond to the abrupt velocity change across steeply dipping normal faults are observed at the flanks of the basin. A 200–300 m thick, high-velocity layer embedded within lower velocity sediment may correspond to evaporites deposited during the Messinian crisis. The results confirm that the combination of data re-datuming and joint refraction and reflection travel-time inversion provides reference models that are accurate enough to apply full-waveform inversion to relatively short offset streamer data in deep water settings starting at field-data standard low frequency content of 6 Hz.

scholarly journals Semiglobal viscoacoustic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R271-R293 ◽  
Author(s):  
Nuno V. da Silva ◽  
Gang Yao ◽  
Michael Warner
Keyword(s):  
Physical Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Intrinsic Attenuation ◽  
Full Waveform ◽  
P Wave Velocity

Full-waveform inversion deals with estimating physical properties of the earth’s subsurface by matching simulated to recorded seismic data. Intrinsic attenuation in the medium leads to the dispersion of propagating waves and the absorption of energy — media with this type of rheology are not perfectly elastic. Accounting for that effect is necessary to simulate wave propagation in realistic geologic media, leading to the need to estimate intrinsic attenuation from the seismic data. That increases the complexity of the constitutive laws leading to additional issues related to the ill-posed nature of the inverse problem. In particular, the joint estimation of several physical properties increases the null space of the parameter space, leading to a larger domain of ambiguity and increasing the number of different models that can equally well explain the data. We have evaluated a method for the joint inversion of velocity and intrinsic attenuation using semiglobal inversion; this combines quantum particle-swarm optimization for the estimation of the intrinsic attenuation with nested gradient-descent iterations for the estimation of the P-wave velocity. This approach takes advantage of the fact that some physical properties, and in particular the intrinsic attenuation, can be represented using a reduced basis, substantially decreasing the dimension of the search space. We determine the feasibility of the method and its robustness to ambiguity with 2D synthetic examples. The 3D inversion of a field data set for a geologic medium with transversely isotropic anisotropy in velocity indicates the feasibility of the method for inverting large-scale real seismic data and improving the data fitting. The principal benefits of the semiglobal multiparameter inversion are the recovery of the intrinsic attenuation from the data and the recovery of the true undispersed infinite-frequency P-wave velocity, while mitigating ambiguity between the estimated parameters.

Near-surface full-waveform inversion in a transmission surface-consistent scheme

Geophysics ◽  
2020 ◽  
pp. 1-57
Author(s):  
Daniele Colombo ◽  
Ernesto Sandoval ◽  
Diego Rovetta ◽  
Apostolos Kontakis
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Velocity Mapping ◽  
Signal To Noise ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform

Land seismic velocity modeling is a difficult task largely related to the description of the near surface complexities. Full waveform inversion is the method of choice for achieving high-resolution velocity mapping but its application to land seismic data faces difficulties related to complex physics, unknown and spatially varying source signatures, and low signal-to-noise ratio in the data. Large parameter variations occur in the near surface at various scales causing severe kinematic and dynamic distortions of the recorded wavefield. Some of the parameters can be incorporated in the inversion model while others, due to sub-resolution dimensions or unmodeled physics, need to be corrected through data preconditioning; a topic not well described for land data full waveform inversion applications. We have developed novel algorithms and workflows for surface-consistent data preconditioning utilizing the transmitted portion of the wavefield, signal-to-noise enhancement by generation of CMP-based virtual super shot gathers, and robust 1.5D Laplace-Fourier full waveform inversion. Our surface-consistent scheme solves residual kinematic corrections and amplitude anomalies via scalar compensation or deconvolution of the near surface response. Signal-to-noise enhancement is obtained through the statistical evaluation of volumetric prestack responses at the CMP position, or virtual super (shot) gathers. These are inverted via a novel 1.5D acoustic Laplace-Fourier full waveform inversion scheme using the Helmholtz wave equation and Hankel domain forward modeling. Inversion is performed with nonlinear conjugate gradients. The method is applied to a complex structure-controlled wadi area exhibiting faults, dissolution, collapse, and subsidence where the high resolution FWI velocity modeling helps clarifying the geological interpretation. The developed algorithms and automated workflows provide an effective solution for massive full waveform inversion of land seismic data that can be embedded in typical near surface velocity analysis procedures.

Seismic characterization of submarine gas-hydrate deposits in the Western Black Sea by acoustic full-waveform inversion of ocean-bottom seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. B311-B324 ◽  
Author(s):  
Laura Gassner ◽  
Tobias Gerach ◽  
Thomas Hertweck ◽  
Thomas Bohlen
Keyword(s):  
Wave Velocity ◽  
Black Sea ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Field Data ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Full Waveform

Evidence for gas-hydrate occurrence in the Western Black Sea is found from seismic measurements revealing bottom-simulating reflectors (BSRs) of varying distinctness. From an ocean-bottom seismic data set, low-resolution traveltime-tomography models of P-wave velocity [Formula: see text] are constructed. They serve as input for acoustic full-waveform inversion (FWI), which we apply to derive high-resolution parameter models aiding the interpretation of the seismic data for potential hydrate and gas deposits. Synthetic tests indicate the applicability of the FWI approach to robustly reconstruct [Formula: see text] models with a typical hydrate and gas signature. Models of S-wave velocity [Formula: see text] containing a hydrate signature can only be reconstructed when the parameter distribution of [Formula: see text] is already well-known. When we add noise to the modeled data to simulate field-data conditions, it prevents the reconstruction of [Formula: see text] completely, justifying the application of an acoustic approach. We invert for [Formula: see text] models from field data of two parallel profiles of 14 km length with a distance of 1 km. Results indicate a characteristic velocity trend for hydrate and gas occurrence at BSR depth in the first of the analyzed profiles. We find no indications for gas accumulations below the BSR on the second profile and only weak indications for hydrate. These differences in the [Formula: see text] signature are consistent with the reflectivity behavior of the migrated seismic streamer data of both profiles in which a zone of high-reflectivity amplitudes is coincident with the potential gas zone derived from the FWI result. Calculating saturation estimates for the potential hydrate and gas zones yields values of up to 30% and 1.2%, respectively.

Optimal transport for mitigating cycle skipping in full-waveform inversion: A graph-space transform approach

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R515-R540 ◽  
Author(s):  
Ludovic Métivier ◽  
Aude Allain ◽  
Romain Brossier ◽  
Quentin Mérigot ◽  
Edouard Oudet ◽  
...  
Keyword(s):  
Seismic Data ◽  
Optimal Transport ◽  
Waveform Inversion ◽  
P Wave ◽  
Imaging Method ◽  
Convexity Property ◽  
Full Waveform Inversion ◽  
Low Frequencies ◽  
Transport Distance ◽  
Full Waveform

Optimal transport distance has been recently promoted as a tool to measure the discrepancy between observed and seismic data within the full-waveform-inversion strategy. This high-resolution seismic imaging method, based on a data-fitting procedure, suffers from the nonconvexity of the standard least-squares discrepancy measure, an issue commonly referred to as cycle skipping. The convexity of the optimal transport distance with respect to time shifts makes it a good candidate to provide a more convex misfit function. However, the optimal transport distance is defined only for the comparison of positive functions, while seismic data are oscillatory. A review of the different attempts proposed in the literature to overcome this difficulty is proposed. Their limitations are illustrated: Basically, the proposed strategies are either not applicable to real data, or they lose the convexity property of optimal transport. On this basis, we introduce a novel strategy based on the interpretation of the seismic data in the graph space. Each individual trace is considered, after discretization, as a set of Dirac points in a 2D space, where the amplitude becomes a geometric attribute of the data. This ensures the positivity of the data, while preserving the geometry of the signal. The differentiability of the misfit function is obtained by approximating the Dirac distributions through 2D Gaussian functions. The interest of this approach is illustrated numerically by computing misfit-function maps in schematic examples before moving to more realistic synthetic full-waveform exercises, including the Marmousi model. The better convexity of the graph-based optimal transport distance is shown. On the Marmousi model, starting from a 1D linearly increasing initial model, with data without low frequencies (no energy less than 3 Hz), a meaningful estimation of the P-wave velocity model is recovered, outperforming previously proposed optimal-transport-based misfit functions.

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