3dgeo Development, Inc.

3dgeo Inc.

Dimitri Bevc

Alexander M Popovici

Ovidiu Feodorov

Biondo Biondi

Wei Liu

Sean E Crawley

Iulian Musat

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. The automatic generation of data-entry windows allows relatively simple integration of new seismic interpretation packages with a given graphical user interface.

Remote access and automated dialog building for remote processing

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.

Systems and methods for collaboratively viewing and editing seismic data

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. Similar methods can be applied with a narrow-azimuth downward continuation operator.

Seismic data processing systems and methods

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.

Typing picks to horizons in migration velocity analysis

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.

Output based azimuth moveout re-gridding of seismic data

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.

Velocity analysis using angle-domain common image gathers

Remote access and automated dialog building for seismic processing

A computationally efficient semi-recursive Kirchhoff migration algorithm is capable of obtaining accurate images of complex structures in complex geological environments which commonly give rise to multivalued arrivals. The method alternates wave-equation datuming (downward continuation) and Kirchhoff migration. Breaking up the complicated velocity structure into small depth regions allows traveltimes to be calculated in regions where the computation is well behaved and where the computation corresponds to energetic arrivals. Because traveltimes are computed for small depth domains, the effects of multivalued arrivals are implicitly accounted for in the migration and the adverse effects of caustics and headwaves do not develop. The invention can use any simple first-arrival traveltime algorithm, and thus benefits from the computational efficiency, robustness, and simplicity of such algorithms.

Growing community of inventors

Pleasanton, CA, United States of America

Dimitri Bevc