Publications
197 results found
Warner M, Guasch L, 2015, Robust adaptive waveform inversion, Pages: 1059-1063, ISSN: 1052-3812
Adaptive Waveform Inversion (AWI) was introduced by Warner & Guasch (2014) as a means to avoid cycle skipping during full-waveform inversion. Here we demonstrate the robustness of this new method by applying it to three challenging problems: a 3D field dataset without an accurate velocity model to start the inversion; a highly realistic blind synthetic dataset that contains elastic effects, attenuation, an unknown density model and ambient noise; and a simple synthetic dataset where the inversion proceeds using the wrong source wavelet. AWI outperforms conventional FWI in each of these applications, and remains stable and accurate throughout.
Yao G, Warner M, 2015, Bootstrapped waveform inversion: Longwavelength velocities from pure reflection data, Pages: 4067-4071
Conventional FWI cannot successfully invert pure reflection data to recover the long-wavelength velocity model. We present an FWI methodology that can solve this problem, and demonstrate its success inverting data from a simple but difficult-to-invert synthetic model. The method proceeds by modifying the FWI objective function, and by interleaving a migration-like form of FWI with a tomography-like form. Starting from a constant-velocity, this FWI approach produces a full-bandwidth velocity model that accurately depth migrates the reflection data.
Esser E, Herrmann F, Guasch L, et al., 2015, Constrained waveform inversion in salt-affected datasets, Pages: 1086-1090, ISSN: 1052-3812
We have developed an accurate and robust methodology that is capable of inverting seismic data in salt-affected environments, to obtain a highly resolved velocity model, without the use of travel-time tomography or explicit salt flooding, in circumstances where conventional full-waveform inversion (FWI) and similar approaches fail. A reflection-driven inversion, in combination with total variation (TV) constraints applied to the adaptive waveform inversion (AWI) objective function, provides the building blocks required to recover both long and short-wavelength velocity models in such environments.
Yao G, Debens HA, Umpleby A, et al., 2015, Adaptive finite difference for seismic wavefield modelling, Pages: 650-654
We present an alternative scheme for calculating finite difference coefficients in seismic wavefield modelling. This novel technique seeks to minimise the difference between the accurate value of spatial derivatives and the value calculated by the finite difference operator over all propagation angles. Since the coefficients vary adaptively with different velocities and source wavelet bandwidths, the method maximises the accuracy of the finite difference operator. Numerical examples demonstrate that this method is superior to standard finite difference methods whilst comparable to Zhang's optimised finite difference method.
Debens HA, Warner M, Umpleby A, et al., 2015, Global anisotropic 3D FWI, Pages: 1193-1197, ISSN: 1052-3812
Seismic anisotropy influences both the kinematics and dynamics of seismic waveforms. If anisotropy is not adequately taken into account during full-waveform seismic inversion (FWI), then inadequacies in the anisotropy model are likely to manifest as significant error in the recovered P-wave velocity model. Conventionally, anisotropic FWI uses either a fixed anisotropy model derived from tomography or such, or it uses a local inversion scheme to recover the anisotropy as part of the FWI; both of these methods can be problematic. In this paper, we show that global rather than local FWI can be used to recover the long-wavelength anisotropy model, and that this can then be followed by more-conventional local FWI to recover the detailed model. We demonstrate this approach on a full 3D field dataset, and show that it avoids problems associated to cross-talk that can bedevil local inversion schemes. Although our method provides a global inversion of anisotropy, it is nonetheless affordable and practical for 3D field data.
Warner M, Guasch L, 2015, Adaptive waveform inversion using incomplete physics, imperfect data, and an incorrect source, Pages: 4057-4061
Adaptive waveform inversion (AWI) provides a means of performing full-waveform inversion (FWI) that appears to be immune to the effects of cycle skipping. However, the form of the AWI algorithm suggests that it could have increased sensitivity to errors in the assumed source wavelet, to noise in the field data, and to inadequacies in the physics used to simulate wave propagation. We examine each of these for a synthetic model. We show that AWI is in fact less sensitive than FWI to errors in the source wavelet, and is no more sensitive to errors in the data and in the modelling than is FWI. It appears likely that the immunity that AWI displays to cycle skipping also contributes to its reduced sensitivity to errors in the assumed source wavelet.
Yao G, Warner M, Silverton A, 2014, Reflection FWI for both Reflectivity and Background Velocity, 76th EAGE Conference and Exhibition 2014
Guasch L, Warner M, 2014, Adaptive waveform inversion -FWI without cycle skipping -Applications, Pages: 3970-3974
Conventional FWI suffers from cycle skipping if the starting model is inadequate at the lowest frequencies present in a dataset. The newly developed technique of adaptive FWI overcomes cycle skipping, and is able to invert normal bandwidth data beginning from an inaccurate velocity model. Here we apply the method to data extracted from a 3D field model, and show that the new method outperforms conventional FWI when starting at higher frequencies than have previously been used to invert this field dataset. We also apply the new methodology to a synthetic dataset that is not cycle skipped, but that is dominated by reflected rather than refracted arrivals. In this case, we show that adaptive FWI also produces a superior result because it has enhanced sensitivity to reflection data, and is able to update the velocity macro-model successfully using reflection-only data.
Warner M, Guasch L, 2014, Adaptive waveform inversion -FWI without cycle skipping -Theory, Pages: 3965-3969
Conventional FWI minimises the direct differences between observed and predicted seismic datasets. Because seismic data are oscillatory, this approach will suffer from the detrimental effects of cycle skipping if the starting model is inaccurate. We reformulate FWI so that it instead adapts the predicted data to the observed data using Wiener filters, and then iterates to improve the model by forcing the Wiener filters towards zero-lag delta functions. This adaptive FWI scheme is demonstrated on synthetic data where it is shown to be immune to cycle skipping, and is able to invert successfully data for which conventional FWI fails entirely. The new method does not require low frequencies or a highly accurate starting model to be successful. Adaptive FWI has some features in common with wave-equation migration velocity analysis, but it works for all types of arrivals including multiples and refractions, and it does not have the high computational costs of WEMVA in 3D.
Yoon K, Moghaddam P, Vlad I, et al., 2014, Full waveform inversion on Jackdaw ocean bottom nodes data in North Sea, Pages: 392-396
A FWI workflow for Jackdaw Ocean Bottom Node (OBN) dataset is described. Small receiver coverage, large receiver crossline spacing and no well information make it challengeable to apply FWI against this dataset. Improved shallow velocities and increasing offset, depth and traveltime enable us to get high resolution shallow FWI velocity model. Source estimation using near offset direct waves is a good approach for shallow sea bottom data. Convergence of FWI was confirmed by shallow depth slices of velocity model, seismogram comparison and phase residual between observed and synthetic seismograms.
Silverton A, Warner M, Umpleby A, et al., 2014, Non-physical water density as a proxy to improve data fit during acoustic FWI, Pages: 4135-4139
Major uplift in imaging is evident when migration is performed with a FWI velocity model for a North Sea hydrocarbon field. However, a small but significant, systematic mismatch in travel-time remains between the field data and synthetic data predicted using the final FWI model. However we perturb the model, the source, the number of iterations, the end result invariably returns to give the same final mismatch in which the predicted data are late. We know that both the synthetic and field data contain strong water-bottom multiples, and these affect the duration, bandwidth and amplitude decay of the coda. However, the finitedifference representation of the velocity model does not contain the seabed explicitly. We propose changing the assumed density of the water layer, which changes the seabed reflection amplitudes without affecting other aspects of the data, thereby properly modelling the seabed reflectivity. The wave-train is in reality an interference pattern between several arrivals, and as the relative strength of those arrivals changes, the interference pattern changes, thereby better fitting the travel-times. We find that decreasing the density of seawater improves the fit to the field data, and that we have to reduce the density by a greater factor as offset increases.
Warner M, Guasch L, 2014, Adaptive waveform inversion: Theory, Pages: 1089-1093, ISSN: 1052-3812
We present a new method for performing full-waveform inversion that appears to be immune to the effects of cycle skipping - Adaptive Waveform Inversion (AWI). The method uses Wiener filters to match observed and predicted data. The inversion is formulated so that the model is updated in the direction that drives these Wiener filters towards delta functions at zero lag, at which point the true model has been recovered. The method is computationally efficient, it appears to be universally applicable, and it recovers the correct model when conventional FWI fails entirely.
Morgan JV, Warner MR, Bell R, et al., 2013, Next-generation seismic experiments: wide-angle, multi-azimuth,three-dimensional, full-waveform inversion, Geophysical Journal International, Vol: in press
Full-waveform inversion (FWI) is an advanced seismic imaging technique that has recentlybecome computationally feasible in three dimensions, and that is being widely adopted andapplied by the oil and gas industry. Here we explore the potential for 3-D FWI, when combinedwith appropriate marine seismic acquisition, to recover high-resolution high-fidelity P-wavevelocity models for subsedimentary targets within the crystalline crust and uppermost mantle.We demonstrate that FWI is able to recover detailed 3-D structural information within aradially faulted dome using a field data set acquired with a standard 3-D petroleum-industrymarine acquisition system. Acquiring low-frequency seismic data is important for successfulFWI; we show that current acquisition techniques can routinely acquire field data from airgunsat frequencies as low as 2 Hz, and that 1 Hz acquisition is likely to be achievable using oceanbottomhydrophones in deep water. Using existing geological and geophysical models, weconstruct P-wave velocity models over three potential subsedimentary targets: the Soufri`ereHills Volcano on Montserrat and its associated crustal magmatic system, the crust and uppermostmantle across the continent–ocean transition beneath the Campos Basin offshore Brazil,and the oceanic crust and uppermost mantle beneath the East Pacific Rise mid-ocean ridge.Weuse these models to generate realistic multi-azimuth 3-D synthetic seismic data, and attempt toinvert these data to recover the original models.We explore resolution and accuracy, sensitivityto noise and acquisition geometry, ability to invert elastic data using acoustic inversion codes,and the trade-off between low frequencies and starting velocity model accuracy.We show thatFWI applied to multi-azimuth, refracted, wide-angle, low-frequency data can resolve featuresin the deep crust and uppermost mantle on scales that are significantly better than can beachieved by any other geophysical technique, and that these results ca
Warner M, Ratcliffe A, Nangoo T, et al., 2013, Anisotropic 3D full-waveform inversion, Geophysics, Vol: 78, Pages: R59-R80
We have developed and implemented a robust and practical scheme for anisotropic 3D acoustic full-waveform inversion (FWI). We demonstrate this scheme on a field data set, applying it to a 4C ocean-bottom survey over the Tommeliten Alpha field in the North Sea. This shallow-water data set provides good azimuthal coverage to offsets of 7 km, with reduced coverage to a maximum offset of about 11 km. The reservoir lies at the crest of a high-velocity antiformal chalk section, overlain by about 3000 m of clastics within which a low-velocity gas cloud produces a seismic obscured area. We inverted only the hydrophone data, and we retained free-surface multiples and ghosts within the field data. We invert in six narrow frequency bands, in the range 3 to 6.5 Hz. At each iteration, we selected only a subset of sources, using a different subset at each iteration; this strategy is more efficient than inverting all the data every iteration. Our starting velocity model was obtained using standard PSDM model building including anisotropic reflection tomography, and contained epsilon values as high as 20%. The final FWI velocity model shows a network of shallow high-velocity channels that match similar features in the reflection data. Deeper in the section, the FWI velocity model reveals a sharper and more-intense low-velocity region associated with the gas cloud in which low-velocity fingers match the location of gas-filled faults visible in the reflection data. The resulting velocity model provides a better match to well logs, and better flattens common-image gathers, than does the starting model. Reverse-time migration, using the FWI velocity model, provides significant uplift to the migrated image, simplifying the planform of the reservoir section at depth. The workflows, inversion strategy, and algorithms that we have used have broad application to invert a wide-range of analogous data sets.
Warner M, Nangoo T, Shah N, 2013, Full-waveform inversion of cycle-skipped seismic data by frequency down-shifting, Pages: 903-907, ISSN: 1052-3812
Full-waveform inversion can be severely compromised by problems of cycle skipping; this occurs when predicted and observed data differ by more than half a cycle, and it leads the inversion to recover a local rather than the global minimum model. Overcoming cycle skipping normally requires both a good starting model and low-frequency content in the field data. Here we present a scheme that uses a non-linear extrapolation to add missing low-frequencies into the field data. We demonstrate the scheme using a 3D OBC field dataset, and show that it can invert to recover the global minimum model even when the original un-extrapolated field dataset is significantly cycle skipped.
Nangoo T, Warner M, O'Brien GS, et al., 2013, The application of full waveform seismic inversion to a narrow-azimuth marine dataset, Pages: 4422-4426
We apply 3D anisotropic acoustic full-waveform inversion to a North Sea narrow-azimuth, marine-streamer dataset. We use a windowed strategy, with 3 stages, first focusing on mainly refracted arrivals with offsets up to (a) 1 km, (b) 2 km and then (c) 3 km with increasing iterations. We demonstrate that our recovered velocity model is realistic.
Al-Yaqoobi A, Warner M, 2013, Full waveform inversion - dealing with limitations of 3D onshore seismic data, Pages: 934-938, ISSN: 1052-3812
Full-waveform inversion is a promising technique to produce high-resolution, interpretable velocity images of the subsurface. We present one of the first results from application of full waveform inversion to a vibrator seismic land data. The results verify that full waveform inversion can be successfully applied to land seismic data after certain preconditioning procedures and with a good a priori velocity model. Updates of the shallow part of the velocity model will have an impact on better recovering of the deeper part of the migration image.
Al Yaqoobi A, Warner M, 2013, Full waveform inversion - A strategy to invert cycle-skipped 3D onshore seismic data, Pages: 3638-3642
Building a velocity model for onshore subsurface is a nontrivial problem. Full-waveform inversion is a technique that seeks to find a high-resolution high-fidelity model of the Earth's subsurface that is capable of matching individual seismic waveforms, within an original raw field dataset, trace by trace. We have developed an inversion scheme in which only data from the shorter offsets are initially inverted since these represent the subset of the data that is not cycle skipped. The offset range is then gradually extended as the model improves. The final 3D model contains a strongly developed low-velocity layer in the shallow section. The results from this inversion appear to match p-wave logs from a shallow drill hole, better flatten the gathers, and better stack and migrate the reflection data. The inversion scheme is generic, and should have applications to other similar difficult datasets.
Christeson GL, Morgan JV, Warner MR, 2012, Shallow oceanic crust: Full waveform tomographic images of the seismic layer 2A/2B boundary, Journal of Geophysical Research, Vol: 117
We present results of full-waveform tomographic inversions of four profiles acquired over young intermediate- and fast spreading rate oceanic crust. The mean velocity-depth functions from our study include a 0.25–0.30 km-thick low-velocity, low-gradient region beneath the seafloor overlying a 0.24–0.28-km-thick high-gradient region; together these regions compose seismic layer 2A. Mean layer 2A interval velocities are 3.0–3.2 km/s. The mean depth to the layer 2A/2B boundary is 0.49–0.54 km, and mean velocities within the upper 0.25 km of layer 2B are 4.7–4.9 km/s. Previous velocity analyses of the study areas using 1-D ray tracing underestimate the thickness of the high-gradient region at the base of layer 2A. We observe differences in the waveform inversion velocity models that correspond to imaging of the layer 2A event; regions with a layer 2A event have higher velocity gradients at the base of layer 2A. Intermittent high velocities, which we interpret as massive flows, are observed in the waveform inversion velocity models at 0.05–0.10 km below the seafloor (bsf) over 10–25% of the intermediate-spreading profiles and 20–45% of the fast spreading profiles. The high-gradient region located 0.25–0.54 km bsf at the base of layer 2A may be associated with an increased prevalence of massive flows, the first appearance of dikes (lava-dike transition zone), or with increased crack sealing by hydrothermal products. The upper portion of layer 2B, which begins at 0.49–0.54 km bsf, may correspond to sheeted dikes or the top of the transition zone of lavas and dikes.
Vieira Da Silva N, Morgan J, Warner M, et al., 2012, 3D constrained inversion of CSEM data with acoustic velocity using full waveform inversion, Pages: 605-609
The marine Controlled Source Electromagnetic Method (CSEM) has been used as exploration technology in the oil and gas industry. Inversion is the most widely used technique for interpretation of electromagnetic data. Nonetheless, resistivity images obtained from CSEM data generally have low resolution creating difficulties in the accurate characterization of geological reservoirs (containing hydrocarbons or for CO2 storage for example). Here is shown that by integrating a velocity field to guide the CSEM inversion leads to better focused resistivity images reducing ambiguities and source-receiver footprint. The proposed method integrates velocity models obtained through seismic full waveform inversion, in a constrained inversion algorithm for controlled source electromagnetic data. A synthetic example using a modified version of the Marmousi model is presented to validate the proposed methodology.
Shah NK, Warner MR, Washbourne JK, et al., 2012, A phase-unwrapped solution for overcoming a poor starting model in full-wavefield inversion, Pages: 251-255
We present a new phase-unwrapped full-wavefield inversion (FWI) methodology for applying the technique to seismic data directly from a poor or simple starting model in an automated, robust manner. The well-known difficulty that arises with a poor starting model is a 'cycle-skipped' relationship between predicted and observed data at useable inversion frequencies. The local minimum convergence of cycleskipped data is one of the root causes for inaccurately recovered models in practical applications of FWI. Further it is why practical applications to date have focussed on favourable datasets possessing very low frequencies and an accurate velocity model already known prior to applying FWI. Here we tackle the cycle-skipping problem by inverting the lowest useable frequency of the data using an unwrapped phase-only objective function. We minimise a smooth, phase-unwrapped residual, extracted from the data by exploiting the spatial continuity existing between adjacent traces. The majority of field datasets acquired today are spatially well enough sampled to be manipulated in this way. An application to highly cycle-skipped synthetic data from the Marmousi model shows the benefit of applying phaseunwrapped inversion to a dataset prior to starting conventional FWI.
Nangoo T, Warner M, Morgan J, et al., 2012, Full-waveform seismic inversion at reservoir depths, Pages: 1117-1121
We apply 3D anisotropic acoustic full-waveform tomographic seismic inversion to a North Sea wide-Angle OBC dataset, and demonstrate that our recovered velocity model is realistic within the chalk reservoir sequence to depths of up to 4000 m. Because we use predominantly wide-Angle refracted arrivals in the inversion, we are able to undershoot and image within the otherwise seismic obscured area beneath a shallow gas cloud that overlies the reservoir. Wide-Angle FWI techniques using similar datasets have not previously been used to image successfully at these depths.
Warner M, Morgan J, Umpleby A, et al., 2012, Which physics for full-wavefield seismic inversion?, Pages: 2994-2998
Full waveform seismic inversion, as currently commercially available in 3D, uses the acoustic approximation to the wave equation, and generally ignores the effects of elasticity, attenuation and anomalous density variations. We examine the consequences of these practical compromises by inverting 3D synthetic seismic data using different approximations to the physics of wave propagation in the forward and inverse modelling. We also invert using different portions of the data, and examine the effects of data amplitudes. We conclude that current FWI practice works well if amplitudes and reflected energy are suppressed in the inversion, but that a more-complete description of the physics is required in order to extract quantitative physical properties from amplitudes and reflections.
Shah N, Warner M, Nangoo T, et al., 2012, Quality assured full-waveform inversion: Ensuring starting model adequacy, Pages: 2562-2566
Successful full-waveform inversion (FWI) of 3D seismic data typically requires low-frequency content in the field data coupled with an accurate starting velocity model. In these circumstances, two fundamental questions always arise: (1) is the starting model sufficiently accurate given the data that are available, and (2) will the inversion iterate towards the global minimum, or will it instead become trapped locally leading to an erroneous final model? We present a robust and objective means to answer both these questions. The diagnostic feature that we use to achieve this is the spatial continuity of the phase difference between the predicted and observed field data, extracted at a single low frequency, after windowing in time around early arrivals. We show proof of principle on a simple 2D synthetic example, and demonstrate the application of quality assured full-waveform inversion (QA-FWI) to a full 3D field dataset that shows significant velocity anisotropy.
Liu F, Guasch L, Morton SA, et al., 2012, 3-D Time-domain Full Waveform Inversion of a Valhall OBC dataset, Pages: 2520-2524
By minimizing the difference between synthetic and field data sets, full waveform inversion (FWI) can produce high resolution and high fidelity earth model parameters that are not resolvable by commonly used ray-based tomography. In this paper, we share our experience on applying 3-D acoustic time-domain full waveform inversion to an OBC data set collected over Valhall field in North Sea.
Guasch L, Warner M, Nangoo T, et al., 2012, Elastic 3D full-waveform inversion, Pages: 2567-2571
We demonstrate the application of elastic 3D full-waveform inversion (FWI) to a field dataset. We first analyze and validate its performance using synthetic data generated from a 3D version of the Marmousi model. We show that elastic FWI can recover both p-wave and shear-wave velocity models using only single-component hydrophone data. We then apply elastic FWI to a 3D multi-component OBC air-gun dataset from the North Sea, and show that it successfully recovers both the p-wave and shear-wave velocity structure of shallow channels.
Viera da Silva N, Morgan JV, MacGregor L, et al., 2012, A finite element multifrontal method for 3D CSEM modeling in the frequency domain, Geophysics, Vol: 77, Pages: E101-E115
There has been a recent increase in the use of controlled-source electromagnetic (CSEM) surveys in the exploration for oil and gas. We developed a modeling scheme for 3D CSEM modeling in the frequency domain. The electric field was decomposed in primary and secondary components to eliminate the singularity originated by the source term. The primary field was calculated using a closed form solution, and the secondary field was computed discretizing a second-order partial differential equation for the electric field with the edge finite element. The solution to the linear system of equations was obtained using a massive parallel multifrontal solver, because such solvers are robust for indefinite and ill-conditioned linear systems. Recent trends in parallel computing were investigated for their use in mitigating the computational overburden associated with the use of a direct solver, and of its feasibility for 3D CSEM forward modeling with the edge finite element. The computation of the primary field was parallelized, over the computational domain and the number of sources, using a hybrid model of parallelism. When using a direct solver, the attainment of multisource solutions was only competitive if the same factors are used to achieve a solution for multi right-hand sides. This aspect was also investigated using the presented methodology. We tested our proposed approach using 1D and 3D synthetic models, and they demonstrated that it is robust and suitable for 3D CSEM modeling using a distributed memory system. The codes could thus be used to help design new surveys, as well to estimate subsurface conductivities through the implementation of an appropriate inversion scheme.
Vieira da Silva N, Morgan JV, MacGregor L, et al., 2012, A finite element multifrontal method for 3D CSEM modeling in the frequency domain, Geophysics, Vol: 77, Pages: E101-E115
There has been a recent increase in the use of controlled-source electromagnetic (CSEM) surveys in the exploration for oil and gas. We developed a modeling scheme for 3D CSEM modeling in the frequency domain. The electric field was decomposed in primary and secondary components to eliminate the singularity originated by the source term. The primary field was calculated using a closed form solution, and the secondary field was computed discretizing a second-order partial differential equation for the electric field with the edge finite element. The solution to the linear system of equations was obtained using a massive parallel multifrontal solver, because such solvers are robust for indefinite and ill-conditioned linear systems. Recent trends in parallel computing were investigated for their use in mitigating the computational overburden associated with the use of a direct solver, and of its feasibility for 3D CSEM forward modeling with the edge finite element. The computation of the primary field was parallelized, over the computational domain and the number of sources, using a hybrid model of parallelism. When using a direct solver, the attainment of multisource solutions was only competitive if the same factors are used to achieve a solution for multi right-hand sides. This aspect was also investigated using the presented methodology. We tested our proposed approach using 1D and 3D synthetic models, and they demonstrated that it is robust and suitable for 3D CSEM modeling using a distributed memory system. The codes could thus be used to help design new surveys, as well to estimate subsurface conductivities through the implementation of an appropriate inversion scheme.
Cobden LJ, Tong CH, Warner MR, 2011, INVERSION OF FULL ACOUSTIC WAVEFIELD IN LOCAL HELIOSEISMOLOGY: A STUDY WITH SYNTHETIC DATA, ASTROPHYSICAL JOURNAL, Vol: 727, ISSN: 0004-637X
Al-Yaqoobi A, Warner M, Stekl I, 2011, Full-wavefield seismic tomography of vibrator data on land, Pages: 3986-3990
Application of full wavefield tomography has been proved to work well on marine seismic data. However, it still suffers some problems when applied to land seismic data. Few examples of land application have been shown for explosive sources and very low vibrator data. We present an application of the method on vibrator data acquired with normal frequency bandwidth.
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