Hunt L.,Fairborne Energy Ltd |
Reynolds S.,Fairborne Energy Ltd |
Hadley M.,Fairborne Energy Ltd |
Hadley S.,Fairborne Energy Ltd |
And 2 more authors.
Leading Edge (Tulsa, OK) | Year: 2011
We investigated our ability to remove a specific short-period multiple from the Nisku and Blueridge formations in West Central Alberta, Canada. This problem is commercial in nature, and has persisted because it was believed that the multiple had too little moveout to be removed, rendering interpretation of the thin Blueridge zone impossible. Associated with this issue was the belief that the modern high-resolution Radon transforms do not materially affect the stack response of real data in this area despite their excellent performance on synthetics and on other data in the literature. Serious technical work seldom affords a discussion of "beliefs", but this work is concerned with the decision-making of the interpreter. We show that in order to address a specific, real, short-period multiple problem, the interpreter was required to challenge previously held technical assumptions. This required the interpreter to consider the nature of the multiple itself, the nature and limitations of the multiple suppression technology used, and to objectively measure the level of success in suppressing the multiple. © 2011 Society of Exploration Geophysicists. Source
Divestco Inc. and International Datashare Corporation | Date: 2002-01-04
DESKTOP SOFTWARE, NAMELY MAPPING AND ANALYSIS SOFTWARE USED WITHIN THE OIL AND GAS, ENERGY AND GEOGRAPHIC INFORMATION SYSTEMS SECTORS WHICH SOFTWARE USES INFORMATION THAT IS EITHER INTERNALLY BUNDLED OR EXTERNALLY SUPPLIED.
Ng M.,Divestco Inc. |
Zheng Y.,Divestco Inc.
SEG Technical Program Expanded Abstracts | Year: 2011
Several effective footprint removal filtering techniques assume that the footprint orientations are parallel to the co-ordinate axes of the filter; but when they are not, those techniques may fail. A direct rotation of the data volume in order to line up the footprint orientation with the co-ordinate axes for filter operation, and rotating it back to the original orientation will involve two re-binning processes. Data rotation introduces errors due to imperfect interpolation methods in practice. Given this fact, in this paper, we will try to minimize those errors by only estimating the footprint in the rotated co-ordinates, and rotating it back to be removed from the original unrotated input data. © 2011 Society of Exploration Geophysicists. Source
Divestco Inc. | Date: 2015-05-08
The present invention relates to a system and method that provides a user with an ability to use a secondary device to take a more detailed look at nuances within a captured seismic data set. The present invention allows the user to view a scaled image of the seismic data that is at a different scale than what is displayed on a primary device. Optionally, the secondary device is a mobile device that is wirelessly connected to the primary device. The present invention also enables the user to interpret the captured seismic data using the secondary device in real time while maintaining a macro view on the primary device. The user may annotate the scaled image regarding picked horizons and the information regarding the location of the annotations on the scaled image are then processed by the primary device and then scaled image on the secondary device is updated.
Wang J.,Divestco Inc. |
Ng M.,Divestco Inc. |
Perz M.,Divestco Inc.
Geophysics | Year: 2010
We propose a greedy inversion method for a spatially localized, high-resolution Radon transform. The kernel of the method is based on a conventional iterative algorithm, conjugate gradient (CG), but is utilized adaptively in amplitude-prioritized local model spaces. The adaptive inversion introduces a coherence-oriented mechanism to enhance focusing of significant model parameters, and hence increases the model resolution and convergence rate. We adopt the idea in a time-space domain local linear Radon transform for data interpolation. We find that the local Radon transform involves iteratively applying spatially localized forward and adjoint Radon operators to fit the input data. Optimal local Radon panels can be found via a subspace algorithm which promotes sparsity in the model, and the missing data can be predicted using the resulting local Radon panels. The subspacing strategy greatly reduces the cost of computing local Radon coefficients, thereby reducing the total cost for inversion. The method can handle irregular and regular geometries and significant spatial aliasing. We compare the performance of our method using three simple synthetic data sets with a popular interpolation method known as minimum weighted norm Fourier interpolation, and show the advantage of the new algorithm in interpolating spatially aliased data. We also test the algorithm on the 2D synthetic data and a field data set. Both tests show that the algorithm is a robust antialiasing tool, although it cannot completely recover missing strongly curved events. © 2010 Society of Exploration Geophysicists. Source