# US 10,768,327 B2 · Method and device for deblending seismic data using self-adapting and/or selective radon interpolation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,768,327 B2 - Document ID: US10768327B2 - Status: Granted - Kind: B2 - Application number: 14/651,382 - Filed: 2014-10-31 - Published: 2015-11-19 - Granted: 2020-09-08 - Earliest claimed: 2013-11-01 - Assignees: Cgg Services SAS - Applicants: Cgg Services SA - Inventors: Ross Haacke; Gordon Poole; Margherita Maraschini - Web page: https://patentgrep.com/patent/US10768327B2 ## CPC - G01V 1/36: Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy - G01V 1/282: {Application of seismic models, synthetic seismograms} - G01V 1/364: {Seismic filtering (G01V1/37 takes precedence)} - G01V 2210/20: Trace signal pre-filtering to select, remove or transform specific events or signal components, i.e. trace-in/trace-out - G01V 2210/32: Noise reduction - G01V 2210/57: Trace interpolation or extrapolation, e.g. for virtual receiver; Anti-aliasing for missing receivers - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) ## Abstract Methods (700) and devices (600) for seismic data processing estimate (720) signal-to-noise ratios of data in a spatio-temporal block of data, determine (730) data-domain weights associated to the data based on the estimated signal-to-noise ratios, and then generate (740) a model of the signal and/or a model of the noise using the data-domain weights. ## Claims ### Claim 1 A method for removing noise from seismic data recorded by receivers over an underground formation, the data representing overlapping signals carrying structural information, the method comprising: selecting a spatio-temporal block of data focusing on one of the overlapping signals at a specific location, from the seismic data; estimating signal-to-noise ratios of data in the spatio-temporal block of data, for the one of the overlapping signals that is coherent with first seismic waves used to explore the underground formation and the noise that includes other of the overlapping signals; determining data-domain weights associated to the data, the data-domain weights being determined based on the estimated signal-to-noise ratios; generating a model of the one of the overlapping signals and/or a model of the noise from the seismic data using the data-domain weights thereby separating the one of the signals from the overlapping signals; and creating an image of the underground formation using the model of the one of the overlapping signals and/or the model of the noise to search and evaluate subterranean hydrocarbon deposits. ### Claim 2 (depends on 1) The method of claim 1, wherein the data-domain weights are used to derive a model of the data. ### Claim 3 (depends on 2) The method of claim 2, wherein the model is an anti-leakage Radon transform. ### Claim 4 (depends on 3) The method of claim 3, further comprising: determining an order used when applying the anti-leakage Radon transform to the spatio-temporal block of data, the order being determined based on the data-domain weights. ### Claim 5 (depends on 2) The method of claim 2, wherein a model-domain signal is obtained using an inversion. ### Claim 6 (depends on 5) The method of claim 5, wherein the data domain weights are used as constraints for the inversion. ### Claim 7 (depends on 1) The method of claim 1, further comprising: re-estimating the signal-to-noise ratios based on the model of the one of the overlapping signals and/or the model of the noise; recalculating the data-domain weights based on the re-estimated signal-to-noise ratios; and updating the model of the one of the overlapping signals and/or the model of the noise using the recalculated data-domain weights. ### Claim 8 (depends on 7) The method of claim 7 wherein the re-estimating, the recalculating and the updating are performed iteratively until a predetermined criterion is met. ### Claim 9 (depends on 1) The method of claim 1, further comprising: decreasing at least one weight among the data-domain weights, the at least one weight being selected based on a statistical analysis of the data. ### Claim 10 (depends on 1) The method of claim 1, further comprising: attenuating the noise in the spatio-temporal block of data using the model of the one of the overlapping signals and/or the model of the noise. ### Claim 11 (depends on 1) The method of claim 1, further comprising: evaluating the signal for seismic data other than data included in the spatio-temporal block of data, using the model of the signal. ### Claim 12 (depends on 1) The method of claim 1, further comprising: excluding one or more weights corresponding to a subset of the spatio-temporal block of data, from the data-domain weights used to generate the model of the one of the overlapping signals and/or the model of the noise; and interpolating the one of the overlapping signals and/or the noise for the subset of the spatio-temporal block of data using the model of the one of the overlapping signals and/or the model of the noise. ### Claim 13 (depends on 1) The method of claim 1, further comprising: estimating second signal-to-noise ratios of the data in the spatio-temporal block of data, for a second one of the overlapping signals that is coherent with second seismic waves used to explore the underground formation and a second noise; determining second data-domain weights associated to the data, the second data-domain weights being determined based on the estimated second signal-to-noise ratios; and generating a second model of the second one of the overlapping signals and/or a second model of the second noise using the second data-domain weights, wherein at least some of the receivers detected simultaneously the one of the overlapping signals coherent with the first waves and the second one of the overlapping signals coherent with the second seismic waves. ### Claim 14 (depends on 13) The method of claim 13, further comprising: re-estimating the signal-to-noise ratios and/or the second signal-to-noise ratios based on the model of the one of the overlapping signals, the model of the noise, the second model of the second one of the overlapping signals and/or the second model of the second noise, respectively; recalculating the data-domain weights and/or the second data-domain weights based on the re-estimated signal-to-noise ratios and/or the re-estimated second signal-to-noise ratios, respectively; and updating the model of the one of the overlapping signals, the model of the noise, the second model of the second one of the overlapping signals and/or the second model of the second noise using the recalculated data-domain weights and/or the recalculated second data-domain weights. ### Claim 15 (depends on 14) The method of claim 14, the re-estimating, the recalculating and the updating are performed iteratively until one or more predetermined criteria are met. ### Claim 16 (depends on 15) The method of claim 15, further comprising: determining a first level of similarity between the model of the one of the overlapping signals and the second model of the noise and/or a second level of similarity between the second model of the second one of the overlapping signals and the model of the noise, wherein the one or more predetermined criteria are related to the first and/or second levels of similarity. ### Claim 17 (depends on 13) The method of claim 13, further comprising: deblending the spatio-temporal block of data into first data focusing on the one of the overlapping signals and second data focusing on the second one of the overlapping signals based on the model of the one of the overlapping signals, the second model of the second one of the overlapping signals, the model of the noise and/or the second model of the second noise. ### Claim 18 (depends on 1) The method of claim 1, further comprising: calculating a changemap associating a noise measure to each data on a trace; identifying at least one noise-dominated point based on the changemap; and adjusting at least one of the data-domain weights associated to the at least one noise-dominated point. ### Claim 19 An apparatus configured to remove noise from seismic data recorded by receivers over an underground formation, the data representing overlapping signals carrying structural information, the apparatus comprising: an input/output interface configured to receive the seismic data and/or to output an image of the explored underground formation; and a data processing unit configured to select a spatio-temporal block of data focusing on one of the overlapping signals at a specific location, from the seismic data; to estimate signal-to-noise ratios of data in the spatio-temporal block of data, for the one of the overlapping signals that is coherent with first seismic waves used to explore the underground formation and the noise that includes other of the overlapping signals; to determine data-domain weights associated to the data, the data-domain weights being determined based on the estimated signal-to-noise ratios; to generate a model of the one of the overlapping signals and/or a model of the noise from the seismic data using the data-domain weights thereby separating the one of the overlapping signals; and to create the image of the explored underground formation using the model of the one of the overlapping signals signal and/or the model of the noise to search and evaluate subterranean hydrocarbon deposits. ### Claim 20 A non-transitory computer readable medium storing executable codes which when executed by a computer make the computer to perform a method for removing noise from seismic data recorded by receivers over an underground formation, the data representing overlapping signals carrying structural information, the method comprising: selecting a spatio-temporal block of data focusing on one of the overlapping signals at a specific location, from the seismic data; estimating signal-to-noise ratios for data in the spatio-temporal block of data, for the one of the overlapping signals that is coherent with first seismic waves used to explore the underground formation and a noise that includes other of the overlapping signals; determining data-domain weights associated to the data, the data-domain weights being determined based on the estimated signal-to-noise ratios; generating a model of the one of the overlapping signals and/or a model of the noise from the seismic data using the data-domain weights thereby separating the one of the overlapping signals; and creating an image of the underground formation using the model of the one of the overlapping signals and/or the model of the noise to search and evaluate subterranean hydrocarbon deposits.