Efficient seismic attribute gather generation with data synthesis and expectation method
A method for generating seismic attribute gathers, the method including: computing, with a computer, seismic images with a field dataset; generating, with a computer, synthetic data corresponding to the seismic images; computing, with a computer, an attribute volume by applying an expectation method to the synthetic data; mapping, with a computer, the attribute volume to the seismic images; and generating, with a computer, seismic attribute gathers by stacking the seismic images mapped to the attribute volume.
1. A method for generating seismic attribute gathers, the method comprising:
computing, with a computer, seismic images with a field dataset;
generating, with a computer, synthetic data corresponding to the seismic images, using a forward simulation method that omits surface-related multiples;
computing, with a computer, an attribute volume by applying an expectation method to the synthetic data, wherein applying the expectation method to the synthetic data comprises;
applying a migration process to the synthetic data to generate a subsurface image volume;
applying a migration process to the synthetic data, wherein seismic traces of the synthetic data are weighted by multiplying the seismic traces by a function of a value of an attribute, and generating an attribute weighted subsurface image volume; and
computing the attribute volume by applying a division process to the subsurface image volume and the attribute weighted subsurface image volume;
mapping, with a computer, the attribute volume to the seismic images; and
generating, with a computer, seismic attribute gathers by stacking the seismic images mapped to the attribute volume.
2. The method of claim 1 , wherein the computing seismic images further comprises:
dividing the field dataset into bins, wherein binned data have similar values of an attribute;
performing seismic imaging for the binned data using a known Earth model and one of Kirchhoff migration, one-way wave equation migration, or reverse time migration; and
forming a subsurface Earth image by summing outputs from the seismic imaging of the binned data.
3. The method of claim 2 , wherein the attribute is surface offset.
4. The method of claim 1 , wherein the synthetic data is generated using a reflectivity model.
5. The method of claim 4 , wherein the reflectivity model is generated using seismic interpretation software.
6. The method of claim 4 , wherein the reflectivity model is generated by a computerized painting or picking program.
7. The method of claim 6 , wherein the method includes using a dip field to populate the reflectivity model.
8. The method of claim 1 , wherein the synthetic data is generated using a prestack demigration process.
9. The method of claim 1 , wherein the synthetic data is based on an acquisition geometry substantially similar to that of the field dataset set in both surface density and time sampling.
10. The method of claim 1 , wherein the synthetic data has a sparser surface acquisition geometry and time sampling than the field dataset.
11. The method of claim 1 , wherein the synthetic data has a regular acquisition pattern.
12. The method of claim 1 , wherein the synthetic data has an irregular acquisition pattern.
13. The method of claim 1 , wherein the synthetic data has a substantially similar acquisition area relative to the field dataset.
14. The method of claim 1 , wherein the synthetic data has a wider acquisition area relative to the field dataset.
15. The method of claim 1 , wherein the mapping the seismic images to bins using the attribute volume, wherein the bins define attribute values.
16. The method of claim 1 , further comprising using the seismic attribute gathers to improve a velocity model, using the improved velocity model to generate a subsurface image, and extracting hydrocarbons from a location determined at least in part from the subsurface image.