Patent Application
20090164756
The present invention relates to the field of geological imaging. Specifically it relates to the application of stream processor based computational devices to convert geological data obtained by seismic acquisition to images.
Geological data are gathered by methods such as seismic reflection, ultrasound, magnetic resonance, etc., and processed to create an image of underground structures. The computer processing of the data is complex and contains a succession of filters (deconvolution, wavelets methods, statistic methods), migration (pre-stack or post-stack with Kirchhoff migration, wave equation methods . . . ) and imaging methods (see
Looking away from input and output operations, transformations to specific data formats and other tasks of pre- or post-processing type, one can isolate a group of instructions that perform the main calculation—name this group of instructions the core calculation. It usually involves discreet Fourier transforms, convolutions or some other type of filtering, or it may involve numerical integration or the application of a differential operator. Unless the application is bound by I/O-operations, improving the speed of the core calculation can benefit the overall time usage.
A so-called stream processor applies a defined set of instructions to each element of its input stream (the input data), producing an output stream. The defined set of instructions, call it the kernel, stays fixed for the elements of the stream, i.e., the kernel can be changed on the stream level. A stream processor might also allow for multiple kernels. The kernel's data usage is local and independent of the processing of other elements in the stream, and this allows the stream processor to execute its kernel significantly faster than an analogue set of instructions would execute on a central processing unit (CPU). A prime example of a stream processor is the (programmable) graphics processor unit (GPU). Another example is the cell processor, which can be seen as a tight integration of several stream processors (called Synergistic Processing Elements in the context of the cell processor). Stream processing hardware is well suited to the execution of the abovementioned kernel of geological data processing.
The present invention is a method and a corresponding system to convert geological response data to graphical raw data which involves a number of steps.
The geological response data is preprocessed by at least one CPU and the resulting preprocessed geological response data is fed into at least one stream processor. The preprocessed geological response data is further processed inside at least one stream processor and the processing results from this step are received at the at least one CPU from said at least one stream processor. Further post-processing of the processing results are performed by said at least one CPU. The at least one stream processor performs on said geological response data at least one of deconvolution, corrections and filtering comprising noise filtering, multiple suppression, NMO correction, spherical divergence correction, sorting, time-to-depth conversion comprising velocity analysis, post-stack image processing, pre-stack image processing and migration. Said sorting can be coupled to said time-to-depth conversion. The method/system can involve manual checking of the computational results after each stage and re-iterating with a reduced latency on critical tasks. The noise filtering can be based on local statistical methods and ultra fast calculations, and the stream processor (s) can be used to compare n (n>1) geological images derived from n sets of geological raw data taken at different times ti (2≦i≦n). Said at least one stream processor is one of at least one programmable Graphical Processing Unit (GPU), a cluster of nodes with CPU's with at least one core and at least one GPU, a cell processor, a processor derived from a cell processor, a cluster of cell processor nodes, a massively parallel computer with stream processors attached to at least one of its CPU's, a game computer and a cluster of game computers.
In detail the invention is characterized by the attached patent claims.
The invention will be described in the following section with reference to the. attached drawings, where
In the following, preferred embodiments of the invention are described in detail with reference to the attached drawings.
The idea is to use one or more stream processors (also called “Parallel computing nodes” in the drawings 205, 302, 405) in conjunction with one or more CPUs, and to organize the application such that the CPUs handle the data input and all preparations of the input streams to the kernels, and all post-processing of the kernel's output stream and output to files or similar tasks. The stream processors are invoked by the CPUs, and execute the core calculation. Examples of computer architectures that can be used to implement such an application include:
Using both CPUs and stream processors, software applications for the processing of geological response data can be implemented with the stream processors as coprocessors doing the core calculation. The enhanced computational speed within the stream paradigm is thus made available to this very demanding type of applications.
The stage “Noise filtering and correction” 105 corresponds to a large amount of mathematical calculations, usually costly and without any possible iteration. By using a stream processor the user can control, modify and re-iterate all these operations.
“Sorting of data” 106 is a necessary step; it can be immediately coupled to the depth conversion phase (from milliseconds, acquisition time to meters, geological unit) thanks to the advanced calculations facilities of the stream processor.
Then there are two choices to manipulate the seismic image: either by a classical post-stack imaging process 101 where the stack allows compression of the amount of data or directly in a pre-stack imaging process 102. This second alternative is recognized as much more accurate for low quality data (bad signal/noise ratio, bad illuminations, complex geology) but has to handle a higher volume of data (no stacking of the data) and therefore is not always possible with current technologies.
After the migration and time-to-depth conversion, one has obtained a geological image of the data. Additionally a new step is now possible. Comparing the obtained image with the image obtained from the same place but acquired at a different time 104 (time-lapse processing). Indeed the stream processor allows handling of multiple datasets, calculations, comparison and feature recognition process 107.
The user is checking the result after each stage 203 and can re-iterate the operations with a reduced latency on critical tasks. Using advantages of stream processors for fast sorting of data 204 (traditionally into CommonDepthPoint gathers) this step is no longer a hindrance in the speed of the workflow.
A user-controlled process allowing iterations is suggested here for both alternatives. In addition instantaneous attribute calculations can be performed.
Having described preferred embodiments of the invention it will be apparent to those skilled in the art that other embodiments incorporating the concepts may be used. These and other examples of the invention illustrated above are intended by way of example only and the actual scope of the invention is to be determined from the following claims.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/NO2006/000364 | 10/18/2006 | WO | 00 | 11/4/2008 |
| Number | Date | Country | |
|---|---|---|---|
| 60727502 | Oct 2005 | US |
