Abstract: In some embodiments, a seismic processing method comprises assembling a specularity gather by determining a specularity value at each of a plurality of subsurface locations, and summing trace amplitudes into a plurality of bins, each bin characterized by a range of specularity values. The specularity value at a subsurface location is computed according to an angle between a normal to a local reflector and a direction of a total (source+receiver) traveltime gradient. For example, the specularity may be proportional to (e.g. equal to) a magnitude of the cosine of the angle. A diffraction image may be generated by summing specularity gather data over specularity, with specular event amplitudes attenuated relative to diffractive event amplitudes.

Abstract: In some embodiments, a time migration diffraction imaging method includes computing a pseudo-depth characterizing a subsurface seismic event by scaling a vertical traveltime using a scaling velocity. A specularity value for a subsurface seismic event is determined according to the pseudo-depth, and a contribution weight for a corresponding seismic trace amplitude is determined according to the specularity value. The specularity value may be determined according to an angle between a traveltime gradient and a normal to a local reflector surface. A diffraction image is generated according to a weighted sum of seismic trace amplitudes. The weighted sum attenuates the contribution of specular events relative to diffraction events.

Abstract: In some embodiments, input seismic data is decomposed into Gaussian beams using plane wave destructor (PWD) filters. The beams are used in a fast beam migration method to generate a seismic image of a subsurface volume of interest. PWD filters are applied to groups of neighboring traces to generate a field of dips/curvatures that fit the input trace data. Beam wavelets are then formed according to the dip/curvature field. Multiple dips (PWD slopes) may be determined at each location in time/space in order to handle intersecting reflection events. Exemplary methods allow an improvement in processing speed by more than an order of magnitude as compared to standard industry techniques such as Kirchhoff migration.

Abstract: Geophysical data processing is remotely controlled and monitored over a wide-area network such as the Internet. A customer using a client computer builds geophysical data processing flows (concatenations of geophysical data processing modules or filters) and enters parameter values required for flow execution. The flow descriptions and associated parameter values are then transferred from the client to a geophysical data processing server, for example a parallel supercomputer. The flows (jobs) are executed on the server, typically over periods ranging from hours to weeks. Intermediate or partial results are made available to the customer for visualization before the processing of a flow is complete. The customer can then modify the flow before its complete execution. Data-entry windows are automatically generated for geophysical processing modules by parsing the source code of the modules.

Abstract: In one embodiment, a computer-implemented seismic viewing/editing collaboration method includes performing real-time collaborative cursor tracking, copaging, picking, and image manipulation in a distributed-display-processing, peer-to-peer architecture. A parameterized, minimal set of information required to update a display is transferred directly between different clients. A group state containing events generated by different clients is enforced to be synchronized on the different clients.

Abstract: In one embodiment, a computer-implemented common azimuth migration seismic data processing method comprises: providing a common-azimuth input data set for a geophysical data processing volume of interest; providing a velocity model for the volume; applying an offset antialiasing operator to the input data set; and performing a recursive downward-continuation of the common-azimuth input data set to a plurality of successive common-azimuth surfaces to generate an image of the volume of interest. In one embodiment, the present invention further provides for selecting a depth dependence of an offset range employed in the downward continuation; selecting a frequency-dependence of a depth step size employed in the downward continuation; selecting a frequency dependence of a cutoff depth employed in the downward continuation; and adding reciprocal traces to the data around zero offset, for reducing imaging artifacts introduced by data edge effects.

Abstract: A seismic velocity analysis method includes tying velocity parameter values such as residual velocity values to geological horizons (reflectors) within a seismic exploration volume. Common image gathers (CIGs) such a common reflection point (CRP) gathers or angle-domain common image gathers (ACIGs) are generated for a set of CIG grid points. Computed best-fit residual velocity values are then snapped to a neighboring horizon or vertically interpolated to the horizon, to generate residual velocity values along the horizon. The residual velocity values for points along the horizon are then selectively employed in updating the velocity model for the volume of interest.

Abstract: Input seismic data are re-gridded to an arbitrary output grid by output-based azimuth moveout. An input seismic data set corresponding to an input grid is used to generate an equivalent output seismic data set corresponding to an output grid different from the input grid. Preferably, the output grid is divided into blocks, and each output grid block is assigned to one of a plurality of independent parallel processors. For each output trace corresponding to an output location, the contributions of plural input traces to the output trace are computed according to an azimuth moveout operator. The contributions are then summed into the output trace.

Abstract: Geophysical data processing is remotely controlled and monitored over a wide-area network such as the Internet. A customer using a client computer builds geophysical data processing flows (concatenations of geophysical data processing modules or filters) and enters parameter values required for flow execution. The flow descriptions and associated parameter values are then transferred from the client to a geophysical data processing server, for example a parallel supercomputer. The flows (jobs) are executed on the server, typically over periods ranging from hours to weeks. Intermediate or partial results are made available to the customer for visualization before the processing of a flow is complete. The customer can then modify the flow before its complete execution. Data-entry windows are automatically generated for geophysical processing modules by parsing the source code of the modules.

Abstract: Migration velocity analysis is performed using Angle-Domain Common Image Gathers (ACIGs). When the correct velocity model is employed for migration, all ACIG events corresponding to a subsurface location are aligned along a horizontal line. Residual moveout can be performed on each ACIG with a suite of trial residual velocity values, according to an angle-domain residual moveout equation. A best-fit residual velocity value that leads to horizontally-aligned events upon moveout can be selected by generating a distribution of semblance (amplitude summed over a given depth) over residual velocity. Best-fit residual velocity values corresponding to selected subsurface points can be employed to update the initial velocity model using a vertical update, normal ray update, or tomographic update method.

Abstract: Geophysical data processing is remotely controlled and monitored over a wide-area network such as the Internet. A customer using a client computer builds geophysical data processing flows (concatenations of geophysical data processing modules or filters) and enters parameter values required for flow execution. The flow descriptions and associated parameter values are then transferred from the client to a geophysical data processing server, for example a parallel supercomputer. The flows (jobs) are executed on the server, typically over periods ranging from hours to weeks. Intermediate or partial results are made available to the customer for visualization before the processing of a flow is complete. The customer can then modify the flow before its complete execution. Data-entry windows are automatically generated for geophysical processing modules by parsing the source code of the modules.

Abstract: Migration velocity analysis is performed using Angle-Domain Common Image Gathers (ACIGs). When the correct velocity model is employed for migration, all ACIG events corresponding to a subsurface location are aligned along a horizontal line. Residual moveout can be performed on each ACIG with a suite of trial residual velocity values, according to an angle-domain residual moveout equation. A best-fit residual velocity value that leads to horizontally-aligned events upon moveout can be selected by generating a distribution of semblance (amplitude summed over a given depth) over residual velocity. Best-fit residual velocity values corresponding to selected subsurface points can be employed to update the initial velocity model using a vertical update, normal ray update, or tomographic update method.

Abstract: A seismic velocity analysis method includes tying velocity parameter values such as residual velocity values to geological horizons (reflectors) within a seismic exploration volume. Common image gathers (CIGs) such a common reflection point (CRP) gathers or angle-domain common image gathers (ACIGs) are generated for a set of CIG grid points. Computed best-fit residual velocity values are then snapped to a neighboring horizon or vertically interpolated to the horizon, to generate residual velocity values along the horizon. The residual velocity values for points along the horizon are then selectively employed in updating the velocity model for the volume of interest.

Abstract: Seismic traveltimes are computed using a conditional high-order method: the traveltime computation operator is second- or higher-order if enough suitable upwind traveltimes are available, and first-order otherwise. Typically, a first-order operator is employed only around singularities, e.g. corners and cusps; a high-order operator is employed for the vast majority of grid points in the target volume. Selectively switching to first-order makes the method relatively simple and computationally efficient, as compared to a pure high-order method. At the same time, most traveltimes are computed to high-order accuracy. In the preferred embodiment, the traveltime front is selectively advanced at its minimum traveltime grid point, using a finite-difference approximation to the eikonal equation. A narrow band propagation zone is used to advance the finite-difference stencil. Tentative traveltimes for the narrow band adjacent to the traveltime front are computed using the eikonal equation and arranged on a heap.

Abstract: Accurate and reliable traveltimes for a seismic exploration volume having a complex velocity structure are generated by selectively advancing a traveltime front at its minimum traveltime grid point, using an entropy-satisfying finite-difference approximation to the eikonal equation. A narrow band propagation zone is used to advance the finite difference stencil. Tentative traveltimes for the narrow band adjacent to the traveltime front are computed using the eikonal equation and arranged on a heap. The minimum traveltime (top of the heap) is selected as an accepted traveltime, saved in the output table, and removed from the heap. Tentative traveltimes for all non-accepted grid points neighboring the selected point are then computed/recomputed and put on the heap. The traveltime computation is fast, unconditionally stable, resolves any overturning propagation wavefronts, and ensures that the eikonal equation is globally solved for each point of the 3-D grid.