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74th EAGE Conference and Exhibition - Workshops
- Conference date: 04 Jun 2012 - 07 Jun 2012
- Location: Copenhagen, Denmark
- ISBN: 978-90-73834-28-6
- Published: 04 July 2012
41 - 60 of 156 results
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Quick-clay Landslide-prone Grounds in Norway and Sweden:A Complex Problem Requiring a Combined Geophysical and Geotechnical Approach
Quick-clay sliding occurs in formerly glaciated coastal areas in, e.g., Norway, Sweden and Canada. The soil was originally deposited in shallow marine environments which emerged following isostatic rebound and fall of the relative sea level since the last glacial maximum. Long-term leaching of salt, due to groundwater flow and percolating surface water, affects clay-particles bonding and makes the soil highly susceptible to failure when disturbed. We review the properties of quick-clays in order to define a suitable, integrated and multi-disciplinary approach to improve identification and mapping of quick-clay areas. Though electrical resistivity tomography is actually the geophysical method of choice, it is paramount to combine a range of geophysical and geotechnical approaches for a better assessment of a given quick-clay site. The discussed integrated approach is here presented for 2 Norwegian and 1 Swedish quick-clay sites. The collected data and preliminary site characterization will illustrate the high diversity of quick-clay grounds as well as the complexity related to an integrated approach.
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A Multidisciplinary Study of Near-shore Landslides in the Trondheim Harbour, Mid Norway
The geological and historical record in the bay of Trondheim, mid Norway, illustrates that landslides are recurrent phenomena. Recent and ongoing development of the area, including land reclamation and extension of harbour facilities, have increased concerns about the stability of the shoreline slopes and highlighted the need for better understanding of these mass-movement processes. Herein, we summarize previous and ongoing work in the area that shed new light on the origin and development of mass wasting processes in the bay of Trondheim. Intergration of geotechnical and geophysical data (including shear wave reflection profiling) from both on- and off-shore shows that the presence of softer and more sensitive laminated clay-rich beds facilitates translational slope failure, by acting as slip planes. Additional pre-conditioning factors promoting instability include the loading of weaker clay-rich beds by delta progradation, over-steepening from erosion and/or sediment accumulation and artesian groundwater pressure at different stratigraphic levels. For the more recent landslides, anthropogenic factors like embankment fillings and vibrations from construction work are considered the most important triggering mechanisms. Finally, the results presented illustrate the importance of detailed morphological analyses, combined with a geological model including the physical/geotechnical characteristics of sediments on- and off-shore, in order to perform proper shoreline slope stability assessment.
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Ray Based Approaches for Velocity Model Building: Past Present and Future
More LessBy mid 2000’s emergence of full waveform inversion (Virieux and Operto, 2009) has somehow occulted the progresses and perspectives of ray based velocity model building. Whatever by now velocity model building in industry remains still largely done using ray based approaches. Moreover, if breakthroughs have not been strongly put forwards for these techniques, they provide now solutions with unexpected resolution and accuracy. My aim here is to review this approaches and to investigate their future. The success and power of ray based approaches is strongly connected to a theoretical and numerical frame, which has been built around ray theory, and which offers a so powerful frame for the physical understanding of velocity model building. I first recall them before reviewing the various ray based velocity model building tools. Finally I discuss their connection with full waveform inversion approaches and discuss the perspectives.
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Objective Functions for Full Waveform Inversion
More LessSeismic full waveform inversion as conventionally formulated imposes very strict constraints on data acquisition: high signal-to-noise at very low frequencies and/or very long offsets. In this workshop presentation, I will explain how some of these constraints arise in the mathematics of wave propagation, and describe some alternative optimization formulations of seismic inversion, which may allow fitting of less constrained data. The extreme heterogeneity of the earth’s sedimentary crust still poses many unresolved challenges for inversion.
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Challenges and Value of Applying FWI to Depth Imaging Projects
Authors Laurent Sirgue, Bertrand Denel and Fuchun Gaol Waveform Inversion (FWI) has now been established a few decades ago (Lailly 1983; Tarantola 1984; Pratt et al. 1996). Until recently however, the application of the technique on full scale 3D seismic was made impossible due to the computational requirements of modeling thousands of shot. Recent advances in high performance computers along with the development of efficient 3D modeling algorithms has lead to the first successfull full scale application on field data (Plessix et al. 2009, Sirgue et al. 2009, Vigh and Star 2009). However, the added value of performing FWI to Prestack Depth Imaging Projects is yet to be clearly defined by the industry. This task is particularly challenging since the type of seismic acquisition largely varies from one asset to the other; along with the geophysical environment (presence of salt, water depth etc…). In this workshop, we will present a wide range of application of FWI to streamer data in both deep offshore and shallow water environments. We will show that FWI may be applied to a wide range of seismic data: from an isotropic application in the Caspian Sea to more complex application such as deep offshore of Gulf of Guinea.
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Full-waveform Inversion Aided Depth Imaging
By Denes VighFull-waveform inversion based on the finite difference approach was originally introduced in the time–space domain (e.g.Tarantola, 1984, Pica et al., 1990, Sun & McMechan, 1992). Inversion can also be implemented in the frequency-domain (Pratt et al., 1998, 1999, Ben-Hadj-ali et al., 2008). The advancement in hardware over the past few years has allowed us to execute 3D FWI on real datasets in marine (Plessix,2009, Sirgue at al.,2009,Vigh et al.,2009,2010) and in land (Plessix,2010) environments. They demonstrate that FWI can be used for velocity updates if the acquired data has adequate low frequency signal and long offsets. The shallow section of the model could be significantly enhanced by the use of FWI, which can result in a much improved depth image over all. One of the challenges with FWI is converging to the local minima, which makes the technique very sensitive to the starting velocity model especially when 3D is considered. To lessen the sensitivity of the initial velocity field, the implementation of FWI at low frequencies using long offsets is required (Bunks et al., 1995, Pratt, 1999).
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A Priori Model Estimation for FWI from Constrained Kinematic Inverse Problem
Authors Christophe Barnes and Marwan ChararaExploration inverse methods such as Monte Carlo could provide the general solution for the fullwaveform inversion (FWI) inverse problem allowing incorporating complex a priori information and data with arbitrary noise distributions. Such an approach applied directly to the FWI problem is computationally not tractable. The alternative is to solve the highly non-linear part of the problem with a fast forward problem such as traveltime with a constrained random exploration. The obtained a priori models and uncertainties help greatly in solving the FWI. This approach was successfully applied to an offset vertical seismic profile (OVSP) case.
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Investigating the Differential Waveform Inversion
Authors Herve Chauris and Ren-douard PlessixIn the context of velocity estimation, we propose the Differential Waveform Inversion approach defined in the data domain. For reflected data, it first consists of migrating a single shot. From the updated velocity model, we then compute the data at the next shot position and compare it with the observed data. The minimization of the misfit appears to be equivalent to the Differential Semblance Optimization approach formulated in the depth migrated domain, at least for reflected data.
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Traveltime Inversion, an Integration Tool in Complex Structures: Lessons from Case Studies in Thrust Belt Setting
Authors Anne Jardin and Karine BrotoWe have developed a traveltime tomography software whose flexibility enables to tackle complex subsurfaces. Applications of this software in thrust belt setting are presented. The role of geology and seismic data integration to validate the final model is analyzed.
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Sensitivity Analysis of Joint Diving Wave+Reflection Tomography in Anisotropic Media
Authors Jacopo Panizzardi and Nicola BienatiIt is more and more evident that the transmitted component of the wavefield recorded by reflection acquisitions does contain precious information about velocity. Indeed, the results obtained from firstarrival traveltime tomography, and in general those obtained by the various works recently presented on Full Waveform Inversion are motivating an increasing interest for transmitted waves, i.e. refractions and diving waves.
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Wavelet Estimation and Multiple Modeling in Full-Waveform Inversion
Authors Ivan Chikichev, Ke Wang and Spyros LazaratosFull-waveform inversion (FWI) has the potential to extract information not only from primary reflections, but also from multiples. We show that accurate modeling of multiples provides strong constraints on the amplitude, frequency spectrum and phase of the seismic wavelet. Thus the method presented here leads to a very robust estimation of the wavelet without relying upon well control. As a consequence, it is applicable to and could be particularly beneficial to the early stages of exploration.
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Resolution in Seismic Inversion- Spectral Gap or Spectral Overlap, Which is Harder to Handle?
By Dave NicholsEarly methods that combined kinematic inversion with amplitude inversion have a gap in the resolved wavenumbers between those resolved by the amplitudes of the scattered field and those resolved by the kinematics. This gap required us to add extra constraints to the problem to recover a model that spans the full wavenumber spectrum. Three advances have brought us to a situation where that gap is often closed. 1) Modern seismic acquisition techniques with lower frequency sources and wider offsets have broadened the spectrum of wavenumbers resolved by single scattering inversions. 2) Full wave inversion using the two way wave equation data provides an accurate treatment of multiply scattered data and can accurately treat the low frequency part of the spectrum. 3) Improved tomography techniques now provide kinematic inversions that resolve more detail of the smooth background. This closing of the gap provides us with a new challenge. We have multiple measurements contributing to resolution of the same parts of the model. We must be careful to combine them in a way that honours the accuracy of each of the measurements.
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Waveform Inversion Using Blocky Parameterization in the Laplace Domain
Authors Changsoo Shin and Hong LeeThe Laplace-domain waveform inversion yields realistic smooth velocity models. By exploiting the inversion’s merits, we developed a cost-effective inversion algorithm by reducing the number of inversion parameters. To develop the idea, we adopted the blocky parameterization method. Then, we applied the Gauss-Newton method combined with the CGLS method to accelerate and stabilize the convergence process. Through numerical tests, we confirmed that the simultaneous inversion of both velocity and interface was feasible, and the smoothed inversion results are comparable to those of the conventional Laplace-domain inversion. The resolution of the inverted velocity models depends on the block size. Therefore, the block size should be carefully determined by tessellating the rough subsurface structure. In our tests on synthetic and field data, the total number of inversion parameters was reduced to less than one-hundredth of the conventional Laplace-domain inversion. The proposed algorithm maintains the robustness of the Laplace domain inversion, and the results are acceptable for use as initial velocity models for consequent inversions, such as the frequency-domain waveform inversion.
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Challenges in the Full Waveform Inversion Regarding Data, Model and Optimisation
Authors Jean Virieux, Romain Brossier, Ludovic Mtivier, Vincent Etienne and Stphane OpertoFull waveform inversion has been proposed in the early eighties and we now find various illustrations of this high resolution seismic imaging technique on both synthetic and real data. We investigate the different issues one may address regarding the three elements of this technique. The optimisation formulation should move towards more complete Newton-like methods. The hierarchical data sampling strategy should prevent the local optimisation approach to be trapped into a local minimum. The model description should keep the number of degrees of freedom as low as possible while prior information should be integrated into a regularisation term moving the full waveform inversion from a data-driven approach to a more balanced data and model contributions when available.
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Full Waveform Inversion by Iterative Depth Migration and Impedance Estimation Using Well Control
Authors Gary F. Margrave, Robert J. Ferguson and Chad M. HoganWe relate full waveform inversion (FWI) to processes familiar to practicing geophysicists. A key theoretical result behind FWI is that a linear update to a migration velocity model is proportional to a prestack reverse-time migration of the data residual (the difference between the actual data and data predicted by the model) where the proportionality factor must be estimated. We argue that in most real-world cases this factor will be frequency dependent, or in the time domain, it will be a convolutional wavelet. The estimation of the velocity update from the migrated section and the common process of impedance inversion are analogous, and we view FWI as a practical cycle of data modeling, migration of the data residual, and "calibration" of this migration to deduce the velocity update. The calibration step can be accomplished like a conventional impedance inversion where the migrated data residual is tied to the velocity residual (the difference between actual velocity and migration velocity) at a well. As there are a great many established algorithms for impedance inversion, so there are a plethora of possibilities for calibration. We present an extended example using the Marmousi model in which we use wave-equation migration (e.g. depth stepping) of the data residual and a simple least-squares amplitude scaling and constant phase rotation, determined at a simulated well, to calibrate the migration. We find that our approach produces a much improved velocity model in only a few iterations.
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Understanding Uncertainty and Managing Risk with Geophysics
More LessUncertainty in Geophysics starts with uncertainties in the measurements. It continues with the uncertainties in the models, explicit or implicit, that are used for processing. Modelling, calibration, optimisation and interpretation are mixed to produce numerical models of the subsurface that are the basis for decision making. All these aspects are illustrated in several examples.
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Incorporating Fault Uncertainties Into the Reservoir Model and Evaluating their Impact on the Fluid Flow
Authors Cecilie Otterlei, Oddvar Lia, Judithvan Hagen, Paul Gillespie and Signe OttesenSeismic imaging can be very challenging for some reservoirs, like sub-salt and deep structures, and also for structurally complex fields there can be significant uncertainty associated with the seismic interpretation. A workflow that incorporates the fault uncertainties into the reservoir model has been created, and their impact on the fluid flow is evaluated. Uncertainties in compartmentalization, fault location, fault displacement, sub-seismic faults and fault sealing have all been considered. The workflow is fully automatic and contains the complete chain from structural modelling to flow simulations. It can be extended to also take uncertainties in horizons and properties into account. The field case application is a sub-salt structure with poor quality seismic, and where pressure and PVT data indicate that the reservoir is compartmentalized. The economics are marginal, but large in-place volumes provide a high potential for the field. The uncertainties related to the faults are believed to be among the most important factors contributing to the total uncertainty in the in-place volumes and the recovery factor, and the uncertainty workflow allows a robust field development plan to be created that reduces the investment risk.
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Quantifying Petrophysical Uncertainty to Help Reduce Risk
More LessThe goal of formation evaluation is to identify the nature and volume of fluids contained in a given formation. Traditionally, single values for these parameters are presented though in reality each is subject to uncertainty. If we quantify the uncertainty associated with our analysis, our evaluations become more useful in the process of deciding whether or not a field is an economic prospect. Here we will consider the nature of petrophysical uncertainties and discuss approaches that can be used to quantify, understand and reduce them.
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Decision Making in the Presence of Uncertainty
By Peter KingUncertainty is intrinsic to all aspects of modelling reservoirs and their performance. It arises from several sources i) many key data have to be interpreted from data using incomplete or imperfect physical models ii) data are only taken at very sparse intervals which have to be interpolated between iii) the intrinsic non-linearity of the flow makes forward prediction inherently unstable and therefore non-deterministic. It is a widely held view in the industry that gathering more data, such as production history, will reduce uncertainty. However, history matching (inferring reservoir properties from production history) is an inverse problem which is inherently unstable so good history matches do not necessarily produce good forecasts. Moreover reservoir modelling is carried out to support reservoir management decisions. Decision making in the presence of high levels of uncertainty can be complicated. The aim of this talk is to highlight the sources of uncertainty inherent in reservoir modeling and to indicate some modern ways by which optimal reservoir management decisions can be made in the presence of such uncertainty.
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Integration of Stimulation into Field Development Planning
By Kevin MauthField development planning has occasionally included stimulation treatments as a contingency rather than as a key component of the plan, if stimulation was included in the planning process at all. Except in tight reservoirs, stimulation has been considered a means of last resort to establish or maintain production from wells that produce less than expectations. By leaving stimulation as a contingency, operators have missed opportunities to collect the data needed to enable successful stimulation. Often, completed well architechture requires compromise in stimulation practices, which makes optimization impossible. As the quality or accessibility of new reservoirs available for development continues to decline, the importance of incorporating stimulation and the associated data collection requirements into field development planning has never been greater. This presentation will discuss some common pitfalls associated with considering stimulation as a contingency as well as the integration of new disciplines to the planning process which increase the probability of success for stimulation treatments. Field examples will also be provided to emphasize the benefits of an expanded field development plan (FDP) workflow for different types of reservoirs.
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