System and method for seismic amplitude analysis
US-2024125956-A1 · Apr 18, 2024 · US
US2016341835A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016341835-A1 |
| Application number | US-201515111011-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jan 13, 2015 |
| Priority date | Jan 13, 2014 |
| Publication date | Nov 24, 2016 |
| Grant date | — |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
Methods and systems for processing seismic data are presented. Primary wave (P) seismic data (PP data) and shear wave (P) seismic data (PS data) are jointly inverted as part of a nonlinear tomography process which adheres to one or more co-depthing constraints.
Opening claim text (preview).
1 . A method for processing seismic data comprising: jointly inverting primary wave (P) seismic data (PP data) and shear wave (S) seismic data (PS data) as part of a nonlinear tomography process which adheres to one or more co-depthing constraints. 2 . The method of claim 1 , wherein the one or more co-depthing constraints includes a volumetric constraint. 3 . The method of claim 2 , wherein the volumetric constraint is based on a Vp/Vs ratio. 4 . The method of claim 3 , wherein the Vp/Vs ratio is determined by: Iteratively filtering PS and PP images associated with the seismic data until a misalignment criterion is satisfied. 5 . The method of claim 1 , wherein the one or more co-depthing constraints includes a reflector constraint which minimizes discrepancies between kinematically re-migrated seismic reflectors in PP and PS domains. 6 . The method of claim 1 , wherein the step of jointly inverting primary wave (PP) and shear wave (PS) seismic data as part of the nonlinear tomography process which adheres to one or more co-depthing constraints further comprises: kinematically re-migrating the seismic data using PP and PS residual moveout (RMO) invariants and at least one of P or S horizon invariants; evaluating a cost function which includes at least one term associated with the one or more co-depthing constraints; performing a linear update of multi-layer velocity attributes using an output of the evaluating step which is constrained by co-depthing; and repositioning the at least one of the P or S horizons. 7 . The method of claim 6 , wherein the four steps are iterated as part of an update loop until an exit criterion is satisfied. 8 . The method of claim 7 , further comprising: outputting final pre-stack depth migrated seismic data when the exit criterion is satisfied; and generating an image of a subsurface using the final pre-stack depth migrated seismic data. 9 . A computer system for processing seismic data comprising: an interface configured to receive seismic data; and at least one processor configured to jointly invert primary wave (P) seismic data (PP data) and shear wave (S) seismic data (PS data) as part of a nonlinear tomography process which adheres to one or more co-depthing constraints. 10 . The system of claim 9 , wherein the one or more co-depthing constraints includes a volumetric constraint. 11 . The system of claim 10 , wherein the volumetric constraint is based on a Vp/Vs ratio. 12 . The system of claim 11 , wherein the Vp/Vs ratio is determined by the at least one processor being configured to iteratively filtering PS and PP images associated with the seismic data until a misalignment criterion is satisfied. 13 . The system of claim 9 , wherein the one or more co-depthing constraints includes a reflector constraint which minimizes discrepancies between kinematically re-migrated seismic reflectors in PP and PS domains. 14 . The system of claim 9 , wherein the at least one processor is configured to jointly invert primary wave (PP) and shear wave (PS) seismic data as part of the nonlinear tomography process which adheres to one or more co-depthing constraints by: kinematically re-migrating the seismic data using PP and PS residual moveout (RMO) invariants and at least one of P or S horizon invariants; evaluating a cost function which includes at least one term associated with the one or more co-depthing constraints; performing a linear update of multi-layer velocity attributes using an output of the evaluating step which is constrained by co-depthing; and repositioning the at least one of the P or S horizons. 15 . The system of claim 14 , wherein the at last one processor is configured to iterate the steps of kinematically re-migrating, evaluating, performing and repositioning as part of an update loop until an exit criterion is satisfied. 16 . The system of claim 15 , wherein the at least one processor is further configured to output final pre-stack depth migrated seismic data when the exit criterion is satisfied; and wherein the at least one processor and the interface are configured to generate an image of a subsurface using the final pre-stack depth migrated seismic data. 17 . A method for updating parameters associated with seismic data which includes pressure wave (PP) data and shear wave (PS) data, the method comprising: computing matching filters between a PP image and a PS image at a plurality of lateral positions of the seismic data; and minimizing an objective function of non-zero lag coefficients of the matching filters. 18 . The method of claim 17 , further comprising: updating at least one of a P-velocity model (Vp) and an S-velocity model (Vs) based on the steps of computing and minimizing. 19 . The method of claim 17 , further comprising: preconditioning at least one of the PP image and the PS image to increase an initial similarity between the PP image and the PS image in terms of frequency content. 20 . The method of claim 17 , further comprising: computing a gradient of the objective function; and performing a local gradient-based optimization using the gradient to iteratively update an S-wave velocity model associated with the seismic data.
Related publications grouped by family.
Answers are generated from the same data shown on this page.