Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
Results
ABSTRACT We implement multiparameter full-waveform inversion (FWI) in the isotropic acoustic media with the nonlinear conjugate gradient (CG) method. The performance of the FWI is evaluated using di erent combinations of acoustic parameters, including velocity, density and acoustic impedance. Simultaneous inversion of velocity and density leads to smoother results than simultaneous inversion of velocity and acoustic impedance. We apply FWI to a time-lapse (4D) seismic inverse problem, and show gradient based methods cannot e ciently resolve velocity and density change simultaneously because of the crosstalk between parameters. We show a second order method is promising in time-lapse FWI by applying the approximated inverse of the Hessian to the gradient. Presentation Date: Monday, October 17, 2016 Start Time: 4:35:00 PM Location: Lobby D/C Presentation Type: POSTER
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Four-dimensional and four-component seismic (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (0.88)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Seismic (four dimensional) monitoring (0.72)
ABSTRACT Interpretation of sharp salt boundaries can be achieved by using level sets to define the boundary as an isocontour of a higher dimensional implicit surface. Using shape optimization, we can evolve this surface and the boundary it represents. We derive an update for the implicit surface that uses second-order information in the Hessian of the FWI objective function, taking into account the effects of the acquisition, as well as scattering and transmission energy. This approach helps us avoid local minima and more effectively converges on the true model, both in terms of the data and model residual norms. We demonstrate this idea using a Gauss-Newton approximation of the Hessian on synthetic examples. Presentation Date: Tuesday, October 18, 2016 Start Time: 9:15:00 AM Location: Lobby D/C Presentation Type: POSTER
ABSTRACT The imaging condition usually adopted for reverse time migration gives good results when applied to acoustic data. However, when dealing with multi-component data, it is important to take into account the vectorial nature of the wave fields recorded. We show how the imaging condition can be formulated to include these vector wave fields. We also apply this formulation to the 2D Marmousi 2 synthetic model and obtain multi-parameter images that can be applied for structural interpretation or as a part of a multi-parameter inversion scheme. Presentation Date: Monday, October 17, 2016 Start Time: 3:45:00 PM Location: 171/173 Presentation Type: ORAL
Integrated VTI model building with seismic data, geologic information, and rock-physics modeling โ Part 2: Field data test
Li, Yunyue (Stanford University, Massachusetts Institute of Technology) | Biondi, Biondo (Stanford University) | Clapp, Robert (Stanford University) | Nichols, Dave (Schlumberger)
ABSTRACT Velocity model building is the first step of seismic inversion and the foundation of the subsequent processing and interpretation workflow. Velocity model building from surface seismic data only becomes severely underdetermined and nonunique when more than one parameter is needed to characterize the velocity anisotropy. The traditional seismic processing workflow sequentially performs seismic velocity model building, structural imaging/interpretation, and lithologic inversion, modifying the subsurface model in each step without verifications against the previously used data. We have developed an integrated model building scheme that uses all available information: seismic data, geologic structural information, well logs, and rock-physics knowledge. We have evaluated the accuracy of the anisotropic model in the image space, in which structural information is estimated. The lithologic inversion results from well logs and the dynamic seismic information (amplitude versus angle) are also fed back to the kinematic seismic inversion via a cross-parameter covariance matrix, which is a multivariate Gaussian approximation to the numerical distribution modeled from stochastic rock-physics modeling. The procedure of building the rock-physics prior information and the improvements using these extra constraints were tested on a Gulf of Mexico data set. The inverted vertical transverse isotropic model not only better focused the seismic image, but it also satisfied the geologic and rock-physics principles.
- North America > United States > California (0.28)
- North America > United States > Massachusetts (0.28)
- North America > United States > Texas (0.28)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.51)
Integrated VTI model building with seismic data, geologic information, and rock-physics modeling โ Part 1: Theory and synthetic test
Li, Yunyue (Stanford University, Massachusetts Institute of Technology) | Biondi, Biondo (Stanford Univeristy) | Clapp, Robert (Stanford Univeristy) | Nichols, Dave (Schlumberger)
ABSTRACT Seismic anisotropy plays an important role in structural imaging and lithologic interpretation. However, anisotropic model building is a challenging underdetermined inverse problem. It is well-understood that single component pressure wave seismic data recorded on the upper surface are insufficient to resolve a unique solution for velocity and anisotropy parameters. To overcome the limitations of seismic data, we have developed an integrated model building scheme based on Bayesian inference to consider seismic data, geologic information, and rock-physics knowledge simultaneously. We have performed the prestack seismic inversion using wave-equation migration velocity analysis (WEMVA) for vertical transverse isotropic (VTI) models. This image-space method enabled automatic geologic interpretation. We have integrated the geologic information as spatial model correlations, applied on each parameter individually. We integrate the rock-physics information as lithologic model correlations, bringing additional information, so that the parameters weakly constrained by seismic are updated as well as the strongly constrained parameters. The constraints provided by the additional information help the inversion converge faster, mitigate the ambiguities among the parameters, and yield VTI models that were consistent with the underlying geologic and lithologic assumptions. We have developed the theoretical framework for the proposed integrated WEMVA for VTI models and determined the added information contained in the regularization terms, especially the rock-physics constraints.
- North America > United States > California (0.28)
- North America > United States > Massachusetts (0.28)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.49)
- Geophysics > Seismic Surveying > Seismic Processing > Seismic Migration (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
Abstract Velocity-model building is the first task of seismic inversion and the foundation of the subsequent data-processing workflow. When the earth velocity becomes multivalued with respect to the propagating direction of the waves, velocity-model building becomes severely underdetermined and nonunique. The traditional workflow separates velocity-model building from lithologic inversion, which hampers both processing steps. An integrated model-building scheme is demonstrated to simultaneously consider prestack seismic data and its structural and lithologic inversion results from a previous iteration. The prestack seismic inversion is performed using wave-equation migration velocity analysis (WEMVA) for vertical transverse isotropic (VTI) models. To constrain the seismic inversion, the geologic information is integrated as spatial-model correlations, and the rock-physics information as lithologic-model correlations. This feedback step completes the loop from seismic imaging to lithologic-model building, where previous rock-physics estimations and geologic interpretations can be validated further and updated in order to constrain the next WEMVA iteration. Improvements from the integrated inversion scheme are shown on a Gulf of Mexico field data set.
- Geology > Geological Subdiscipline > Geomechanics (0.62)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.31)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (1.00)
5. Diffraction Imaging (Seismic Diffraction)
Hubral, P., Landa, E., Shtivelman, V., Gelchinsky, B., Kanasewich, Ernest R., Phadke, Suhas M., Keydar, Shemer, Zavalishin, B. R., Khaidukov, V., Moser, T. J., Grasmueck, Mark, Weger, Ralf, Horstmeyer, Heinrich, Bansal, Reeshidev, Imhof, Matthias G., Sava, Paul C., Biondi, Biondo, Etgen, John, Fomel, Sergey, Taner, M. Turhan, Howard, C. B., Reshef, Moshe, Berkovitch, Alex, Belfer, Igor, Hassin, Yehuda, Bachrach, Ran
Chapter 5, the final section in this volume, focuses on the separation and imaging of diffractions, starting with pioneering work in the 1970s and proceeding to the current state. The separation process removes the reflection data and retains the lower-energy diffraction data. The imaging process focuses the diffraction energy at the surface locations from which the diffractions originated. Synthetic and real data examples are included. The objective of diffraction imaging is to locate the discontinuities in the subsurface that give rise to diffraction energy. Papers in this section detail a progression of different approaches to this problem.
- Europe (1.00)
- Asia (1.00)
- North America > United States > Texas > Travis County > Austin (0.27)
- Geology > Structural Geology > Tectonics (1.00)
- Geology > Structural Geology > Fault (1.00)
- Geology > Sedimentary Geology (1.00)
- (2 more...)
- Energy > Oil & Gas > Upstream (1.00)
- Leisure & Entertainment (0.67)
- North America > United States > New Mexico > San Juan Basin (0.99)
- North America > United States > Colorado > San Juan Basin (0.99)
- North America > United States > Arizona > San Juan Basin (0.99)