# US 9,435,906 B2 · Simultaneous wavelet extraction and deconvolution processing in the time domain > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,435,906 B2 - Document ID: US9435906B2 - Status: Granted - Kind: B2 - Application number: 14/224,217 - Filed: 2014-03-25 - Published: 2014-07-24 - Granted: 2016-09-06 - Earliest claimed: 2011-03-25 - Assignees: Saudi Arabian Oil Company - Applicants: Saudi Arabian Oil Company - Inventors: Saleh Al-Dossary; Jinsong Wang - Web page: https://patentgrep.com/patent/US9435906B2 ## CPC - G01V 1/364: {Seismic filtering (G01V1/37 takes precedence)} - G01V 1/28: Processing seismic data, e.g. for interpretation or for event detection (G01V1/48 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: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) ## Abstract Blind wavelet extraction and de-convolution is performed on seismic data to enable its practical usage in seismic processing and to provide quality control of data obtained in areas where data from wells are not available. The wavelet extraction and deconvolution are realized in the time domain by iteration, producing a mixed phase wavelet with minimal prior knowledge of the actual nature of the wavelet. As a result of the processing, the de-convolved seismic reflectivity is obtained simultaneously. ## Claims ### Claim 1 A computer implemented method of processing seismic data obtained in the form of seismic traces from a reflection seismic survey of subsurface portions of the earth for analysis of subsurface features of interest, the computer implemented method comprising the computer implemented processing steps of: forming a wavelet from the seismic survey data; resolving a time of occurrence of maximum energy in the wavelet from the seismic survey data; forming a normalized amplitude of energy for the wavelet from traces in the seismic survey data; forming a composite trace at the resolved time of occurrence and normalized amplitude from an ensemble of the traces in the seismic survey data; applying a time filter to the wavelet based on the composite trace to form a resultant deconvolution wavelet having a main frequency in the seismic frequency band; performing a deconvolution operation on the seismic traces by applying the resultant deconvolution wavelet to the seismic data for analysis of subsurface features of interest; migration processing the seismic data, after the step of performing a deconvolution operation on the seismic traces, to move reflections in the data to their correct spatial locations; and forming displays of the migrated seismic data for analysis of subsurface features of interest. ### Claim 2 (depends on 1) The computer implemented method of claim 1, wherein the step of forming a normalized amplitude of energy for the wavelet comprises the steps of: forming an estimate of amplitude of the wavelet amplitude; adjusting the estimate of the wavelet amplitude to minimize a total error function; and forming an average of the adjusted estimate of the wavelet amplitude. ### Claim 3 (depends on 1) The computer implemented method of claim 1, wherein the step of forming a composite trace comprises the step of: forming a composite trace at the resolved time of occurrence and normalized amplitude from a selected group of the traces in the seismic survey data. ### Claim 4 (depends on 3) The computer implemented method of claim 3, wherein the selected group of traces comprises a common depth point gather of the traces in the seismic survey data. ### Claim 5 (depends on 3) The computer implemented method of claim 3, wherein the selected group of traces comprises a shot point gather of the traces in the seismic survey data. ### Claim 6 (depends on 1) The computer implemented method of claim 1, wherein the step of applying a time filter to the wavelet comprises the steps of: forming a measure of the average power spectrum of the composite trace; determining a seismic main frequency of the presence of average power in the composite trace; and forming the resultant deconvolution wavelet at the determined seismic main frequency. ### Claim 7 (depends on 1) The computer implemented method of claim 1, wherein the step of performing a deconvolution operation on the seismic traces comprises the steps of: performing a deconvolution operation on the seismic traces to remove the effects of the resultant deconvolution wavelet on the recorded data. ### Claim 8 (depends on 1) The computer implemented method of claim 1, wherein the seismic data represents reflected energy resulting from acoustic impedance changes in the earth due to the location and presence of subsurface structure of interest. ### Claim 9 A computer implemented method of processing seismic data obtained in the form of seismic traces from a reflection seismic survey of subsurface portions of the earth for analysis of subsurface features of interest, the computer implemented method comprising the computer implemented processing steps of: forming in the computer a wavelet from the seismic survey data; resolving in the computer a time of occurrence of maximum energy in the wavelet from the seismic survey data; forming in the computer a normalized amplitude of energy for the wavelet from traces in the seismic survey data; forming in the computer a composite trace at the resolved time of occurrence and normalized amplitude from an ensemble of the traces in the seismic survey data; applying in the computer a time filter to the wavelet based on the composite trace to form a resultant deconvolution wavelet having a main frequency in the seismic frequency band; and performing in the computer a deconvolution operation on the seismic traces by applying the resultant deconvolution wavelet to the seismic data for analysis of subsurface features of interest; migration processing the seismic data in the computer, after the step of performing a deconvolution operation on the seismic traces, to move reflections in the data to their correct spatial locations; and forming with the computer displays of the migrated seismic data for analysis of subsurface features of interest. ### Claim 10 (depends on 9) The computer implemented method of claim 9, wherein the step of forming a normalized amplitude of energy for the wavelet comprises the steps of: forming in the computer an estimate of amplitude of the wavelet amplitude; adjusting in the computer the estimate of the wavelet amplitude to minimize a total error function; and forming in the computer an average of the adjusted estimate of the wavelet amplitude. ### Claim 11 (depends on 9) The computer implemented method of claim 9, wherein the step of forming a composite trace comprises the step of: forming in the computer a composite trace at the resolved time of occurrence and normalized amplitude from a selected group of the traces in the seismic survey data. ### Claim 12 (depends on 11) The computer implemented method of claim 11, wherein the selected group of traces comprises a common depth point gather of the traces in the seismic survey data. ### Claim 13 (depends on 11) The computer implemented method of claim 11, wherein the selected group of traces comprises a shot point gather of the traces in the seismic survey data. ### Claim 14 (depends on 9) The computer implemented method of claim 9, wherein the step of applying a time filter to the wavelet comprises the steps of: forming in the computer a measure of the average power spectrum of the composite trace; determining in the computer a seismic main frequency of the presence of average power in the composite trace; and forming the resultant deconvolution wavelet at the determined seismic main frequency. ### Claim 15 (depends on 9) The computer implemented method of claim 9, wherein the step of performing a deconvolution operation on the seismic traces comprises the steps of: performing in the computer a deconvolution operation on the seismic traces to remove the effects of the resultant deconvolution wavelet on the recorded data. ### Claim 16 (depends on 9) The computer implemented method of claim 9, wherein the seismic data represents reflected energy resulting from acoustic impedance changes in the earth due to the location and presence of subsurface structure of interest. ### Claim 17 A computer implemented method of processing seismic data obtained in the form of seismic traces from a reflection seismic survey of subsurface portions of the earth for analysis of subsurface features of interest, the computer implemented method comprising the computer implemented processing steps of: forming a wavelet from the seismic survey data; resolving a time of occurrence of maximum energy in the wavelet from the seismic survey data; forming a normalized amplitude of energy for the wavelet from traces in the seismic survey data; forming a composite trace at the resolved time of occurrence and normalized amplitude from an ensemble of the traces in the seismic survey data; applying a time filter to the wavelet based on the composite trace to form a resultant deconvolution wavelet having a main frequency in the seismic frequency band; and performing a deconvolution operation on the seismic traces by applying the resultant deconvolution wavelet to the seismic data; velocity analysis processing the seismic traces to determine a seismic velocity function represents the velocity of energy travel through the earth as a function of depth; summing the individual seismic trace to improve the signal-to-noise ratio of the data in the seismic traces; migration processing the seismic data, after the step of performing a deconvolution operation on the seismic traces, to move reflections in the data to their correct spatial locations; and forming displays of the migrated seismic data for analysis of subsurface features of interest. ### Claim 18 (depends on 17) The computer implemented method of claim 17, further including the step of: applying moveout correction to adjust for differences in signal arrival time in the seismic data. ### Claim 19 (depends on 17) The computer implemented method of claim 17, further including the step of: applying data filtering to the seismic data to remove undesirable portions of the data. ### Claim 20 (depends on 17) The computer implemented method of claim 17, wherein the step of forming a normalized amplitude of energy for the wavelet comprises the steps of: forming an estimate of amplitude of the wavelet amplitude; adjusting the estimate of the wavelet amplitude to minimize a total error function; and forming an average of the adjusted estimate of the wavelet amplitude. ### Claim 21 (depends on 17) The computer implemented method of claim 17, wherein the step of forming a composite trace comprises the step of: forming a composite trace at the resolved time of occurrence and normalized amplitude from a selected group of the traces in the seismic survey data. ### Claim 22 (depends on 17) The computer implemented method of claim 17, wherein the step of applying a time filter to the wavelet comprises the steps of: forming a measure of the average power spectrum of the composite trace; determining a seismic main frequency of the presence of average power in the composite trace; and forming the resultant deconvolution wavelet at the determined seismic main frequency. ### Claim 23 (depends on 17) The computer implemented method of claim 17, wherein the step of performing a deconvolution operation on the seismic traces comprises the steps of: performing a deconvolution operation on the seismic traces to remove the effects of the resultant deconvolution wavelet on the recorded data. ### Claim 24 (depends on 17) The computer implemented method of claim 17, wherein the seismic data represents reflected energy resulting from acoustic impedance changes in the earth due to the location and presence of subsurface structure of interest. ### Claim 25 (depends on 17) The computer implemented method of claim 17, further including the steps of: migration processing the seismic data, after the step of performing a deconvolution operation on the seismic traces, to move reflections in the data to their correct spatial locations; and forming displays of the migrated seismic data for analysis of subsurface features of interest.