Full-wavefield inversion of primaries and multiples in marine environment

Information

  • Patent Grant
  • 9702998
  • Patent Number
    9,702,998
  • Date Filed
    Friday, June 20, 2014
    10 years ago
  • Date Issued
    Tuesday, July 11, 2017
    7 years ago
Abstract
Method for using the full wavefield (primaries, internal multiples and free-surface multiples) in inversion of marine seismic data, including both pressure and vertical velocity data (21), to infer a subsurface model of acoustic velocity or other physical property. The marine seismic data are separated (22) into up-going (23) and down-going (24) wavefields, and both wavefields are inverted in a joint manner, in which the final model is impacted by both wavefields. This may be achieved by inverting both wavefields simultaneously (25), or one after the other, i.e. in a cascaded approach (35→37, or 45→47), for the subsurface properties (26, 38, 48).
Description
FIELD OF THE INVENTION

The invention relates generally to the field of geophysical prospecting, and more particularly to geophysical data processing. Specifically, the invention is a method to invert seismic data containing primaries and multiples in a marine environment.


BACKGROUND OF THE INVENTION

Full wavefield inversion (FWI) is a computer-implemented geophysical method that is recently being used to invert for subsurface properties such as velocity or acoustic impedance. FWI is known to estimate the subsurface properties more accurately than, for example, inversion of the recorded wavefield after being processed to eliminate multiple reflections. The crux of any FWI algorithm can be described as follows: using a starting subsurface property model, synthetic seismic data are generated, i.e. modeled or simulated, by solving the wave equation using a numerical scheme (e.g., finite-difference, finite-element etc.). The synthetic seismic data are compared with the field seismic data and using the difference between the two, an error or objective function is calculated. Using the objective function, a modified subsurface model is generated which is used to simulate a new set of synthetic seismic data. This new set of synthetic seismic data is compared with the field data to generate a new objective function. This process is repeated until the objective function is satisfactorily minimized and the final subsurface model is generated. A global or local optimization method is used to minimize the objective function and to update the subsurface model. The accuracy of any FWI method is in general dictated by its two important components: the numerical algorithm used for solving wave equation to generate synthetic seismic data and the optimization scheme. Depending on the type of optimization scheme employed, a FWI method may get stuck in a local minimum while updating the subsurface model.


There are several numerical methods such as finite-difference, finite-element etc. available for solving the wave equation. The finite-difference methods [1] which are the most popular numerical scheme for solving the wave equation suffer from the interface error generated by the misalignment between numerical grids and numerical interfaces [2]. Although all types of reflection (primaries, free-surface multiples, internal multiples etc.) suffer from the interface error, the free-surface multiples are affected the most due to multiple bounces between the free surface and reflectors in subsurface. Given that free-surface multiples are some of the strongest arrivals in a seismic record, including free-surface multiples in a FWI workflow may result in erroneous inverted subsurface properties.


Although in any seismic experiment, full wavefield (primaries, internal multiples and free-surface multiples) are acquired, due to inability of accurately modeling free-surface multiples, in most of the FWI methods only primaries and internal multiples are used to invert for subsurface models. Given that the free-surface multiples carry additional information about the subsurface model and complements to the information being carried by primaries and internal multiples, it is expected that including free-surface multiples in inversion will improve the accuracy of the inverted subsurface model. The present invention is a method that permits circumventing the direct modeling and subtraction of free-surface multiples.


SUMMARY OF THE INVENTION

In one embodiment, the invention is a method for inverting marine seismic data to infer a subsurface physical property model, said seismic data including pressure data and vertical velocity data, said method comprising (a) separating the pressure data and the vertical velocity data into an up-going wavefield and a down-going wavefield; and (b) inverting the up-going wavefield and the down-going wavefield together, either simultaneously or cascaded, to infer a subsurface physical property model; wherein the separating and the inverting are performed using a computer.


In a second embodiment, the invention is a method for inverting marine seismic data to infer a subsurface physical property model, said seismic data including pressure data and vertical velocity data, said method comprising: (a) separating the pressure data and the vertical velocity data into an up-going wavefield and a down-going wavefield; and (b) iteratively inverting the up-going wavefield and the down-going wavefield together, meaning that each iteration cycle inverts the up-going wavefield or the down-going wavefield or simultaneously inverts both up-going and down-going wavefields, with each iteration cycle resulting in a model update which is used to generate simulated data in a next iteration cycle, resulting finally in a final physical property model; wherein the separating and the inverting are performed using a computer.





BRIEF DESCRIPTION OF THE DRAWINGS

The advantages of the present invention are better understood by referring to the following detailed description and the attached drawings, in which:



FIG. 1 illustrates decomposition of pressure and vertical particle velocity into up-going and down-going wavefields, where the up-going wavefield contains primaries and associated internal multiples and the down-going wavefield carries free-surface multiples and associated internal multiples;



FIG. 2 is a flowchart showing basic steps in a simultaneous inversion embodiment of the present inventive method;



FIG. 3 is a flowchart showing basic steps in one cascaded inversion embodiment of the present inventive method;



FIG. 4 is a flowchart showing basic steps in another cascaded inversion embodiment of the present inventive method; and



FIGS. 5A-5C are data displays showing test results for the present inventive method.





The invention will be described in connection with example embodiments. However, to the extent that the following detailed description is specific to a particular embodiment or a particular use of the invention, this is intended to be illustrative only, and is not to be construed as limiting the scope of the invention. On the contrary, it is intended to cover all alternatives, modifications and equivalents that may be included within the scope of the invention, as defined by the appended claims.


DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

The invention is a method for using the full wavefield (primaries, internal multiples and free-surface multiples) in inversion. The marine seismic data are separated into up-going and down-going wavefields, which is possible for marine surveys because of the pressure data that can be collected underwater. Then, both wavefields are inverted in some joint manner, in which the final model is impacted by both wavefields. This may be achieved by inverting both wavefields simultaneously, or one after the other (in a cascaded approach) for the subsurface properties.


Wong et al. (2010) [3] disclosed a method for performing joint least-squares migration of up- and down-going wavefields. In contrast, the present invention inverts for the subsurface properties (by implementing a method of full waveform non-linear inversion). Inversion is quite different from migration. The objective in migration, i.e. imaging, is to move the reflectors to their correct subsurface positions, assuming a velocity model of the subsurface. The velocity model is not updated in migration. Inversion is a process, usually iterative, where the objective is to improve and update the initial assumed velocity model.


The present invention is designed for marine seismic data and requires acquisition of at least two-components of wavefield namely pressure and particle velocity. Any marine seismic acquisition can be categorized into one of the following three categories: towed streamer acquisition, ocean bottom cable (OBC) acquisition and ocean bottom node (OBN) acquisition. Towed streamer acquisitions have traditionally been used to record only the pressure component of the wavefield. In the past few years, however, it has become increasingly common to record both pressure and velocity components of the wavefield using a towed streamer acquisition system. OBC and OBN acquisitions almost always record pressure and velocity components of the wavefield.


Both pressure (P) and vertical velocity components (Z) have primaries, internal multiples and free-surface multiples. In principle, pressure and velocity components can be used together in a FWI method to estimate subsurface properties. However, as mentioned previously, accurate numerical modeling of free-surface multiples is challenging. Hence, any FWI method that requires accurate modeling of seismic data is prone to error if the free-surface multiples are used in inversion. To circumvent this problem, instead of using field-recorded pressure and velocity components, the present inventive method uses up-going and down-going wavefields in inversion.


There are several published methods available for deriving up-going and down-going wavefields from pressure and vertical velocity components. Some of those are described in [4, 5]. The up-going wavefield contains primaries and associated internal multiples while the down-going wavefield contains free-surface multiples and the associated internal multiples. (The terms up-going and down-going refer to the direction of the wavefield as it arrives at the receiver.) In terms of seismic inversion, both wavefields have their own advantages and disadvantages. Reference may be had to the self-explanatory schematic diagrams of FIG. 1. The up-going wavefields have larger reflection angle and usually have better signal-to-noise ratio. Down-going wavefields provide larger aperture but have less fold than the up-going wavefield. Since the up-going wavefield does not contain free-surface multiples, free-surface multiples do not need to be modeled in order to perform FWI. The down-going wavefield, which contains the free-surface multiples, can be modeled by using mirror geometry [6, 7] without needing a free-surface condition on the top of the model. In mirror geometry, the top of the model is padded (see FIG. 1) with a water layer as thick as the water depth and the receiver location is moved upward (directly above the original location) with a distance 2 g, where g is the depth of the original receiver location.


Up-going and down-going wavefields are used to perform FWI to invert for subsurface parameters. FWI may be performed using, for example, any of the three following approaches which are all embodiments of the present inventive method. The first four steps (21-24) are the same in each approach.


Simultaneous inversion: FIG. 2 describes basic steps in the workflow. Pressure and vertical velocity components of marine seismic data, including towed streamer, OBC, OBN/OBS (21), are decomposed (22) into up-going (23) and down-going (24) wavefields. These two wavefields are simultaneously inverted (25) for subsurface properties (26). A simultaneous inversion can be characterized by the optimizing of a single, combined objective function measuring misfit between simulated and actual data of both wavefields, resulting in a single model update, which updated model is then used in the next iteration cycle to simulate the up-going and down-going wavefields, etc.


Cascaded Inversion I: FIG. 3 describes the workflow. Pressure and vertical velocity components of marine seismic data, including towed streamer, OBC, and OBN/OBS (21), are decomposed (22) into up-going (23) and down-going (24) wavefields. Next, FWI is performed on up-going wavefield (35) to invert for subsurface properties, which may be called intermediate subsurface properties (36). Thereafter, FWI is applied on down-going wavefield (37) to invert for final subsurface properties (38) and the intermediate subsurface properties is used as the starting model for FWI.


Cascaded Inversion II: FIG. 4 describes the workflow. Pressure and vertical velocity components of marine seismic data, including towed streamer, OBC, and OBN/OBS (21), are decomposed (22) into up-going (23) and down-going (24) wavefields. Next, FWI is performed on down-going wavefield (45) to invert for subsurface properties, which may be called the intermediate subsurface properties (46). Thereafter, FWI is applied on up-going wavefield (47) to invert for final subsurface properties (48) and the intermediate subsurface properties is used as the starting model for FWI.



FIGS. 5A-5C show test results for the present inventive method applied to actual data. FIG. 5A shows the initial velocity model used to start the iterative inversion process. For complex scenarios such as the high velocity geo-body of this example, a reasonably close starting model is important to successful inversion. FIG. 5B shows the inverted velocity model using the simultaneous inversion method of FIG. 2. FIG. 5C shows the inverted velocity model using the cascaded inversion I method of FIG. 3. Both inverted models show many details not present in the starting model.


An alternative to the cascaded inversion embodiments described above might be to invert the up-going wavefield and the down-going wavefield separately, and then reduce the two resulting models to a single, best model by some sort of averaging process or least-squares fitting.


The foregoing description is directed to particular embodiments of the present invention for the purpose of illustrating it. It will be apparent, however, to one skilled in the art, that many modifications and variations to the embodiments described herein are possible. For example, an iterative inversion cycle where in the first cycle the up-going wavefield is inverted resulting in a model update, then use the updated model to invert the down-going wavefield, update the model again, then use that updated model to invert the up-going wavefield, and so on alternating the two wavefields from one cycle of the iterative process to the next. All such modifications and variations are intended to be within the scope of the present invention, as defined by the appended claims.


References




  • 1. Virieux, J., “P-SV wave propagation in heterogenous media,” Geophysics 51, 889-901 (1986).

  • 2. Symes, W. W. and Vdovina, T., “Interface error analysis for numerical wave propagation,” Computational Geosciences 13, 363-371 (2009).

  • 3. Wong, M., Biondi, B., Ronen, S., “Joint least-squares inversion of up- and down-going signal for ocean bottom data sets,” SEG Expanded Abstracts 29, 2752 (2010).

  • 4. Barr, F. J. and Sanders, J. I., “Attenuation of water-column reverberations using pressure and velocity detectors in a water-bottom cable,” 59th annual SEG meeting, Expanded Abstracts, 653 (1989).

  • 5. Amundsen, L., “Elimination of free-surface related multiples with need of a source wavelet,” Geophysics 66, 327-341 (2001).

  • 6. Godfrey, R. P. K., Armstrong, B., Cooper, M. and Thorogood, E., “Imaging the Foinaven ghost,” SEG Expanded Abstracts, 1333-1335 (1998).

  • 7. Ronen, S., Comeaux, L. and Miao J., “Imaging downgoing waves from ocean bottom stations,” SEG Expanded Abstracts, 963-966 (2005).


Claims
  • 1. A computer-implemented method for inverting marine seismic data to infer a subsurface physical property model, said seismic data including pressure data and vertical velocity data, said method comprising: separating the pressure data and the vertical velocity data into an up-going wavefield and a down-going wavefield;inverting, with a full wavefield inversion, the up-going wavefield and the down-going wavefield together, either simultaneously or cascaded, to infer a subsurface physical property model; andprospecting for hydrocarbons with the subsurface physical property model, wherein the separating and the inverting are performed using a computer.
  • 2. The method of claim 1, wherein the inversion is cascaded, the up-going wavefield being inverted first to infer an intermediate physical property model, then, using the intermediate physical property model as an initial model, the down-going wavefield is inverted to infer a final physical property model.
  • 3. The method of claim 1, wherein the inversion is cascaded, the down-going wavefield being inverted first to infer an intermediate physical property model, then, using the intermediate physical property model as an initial model, the up-going wavefield is inverted to infer a final physical property model.
  • 4. The method of claim 1, wherein the physical property is velocity or acoustic impedance.
  • 5. The method of claim 1, wherein the down-going wavefield is simulated in the inversion using mirror geometry.
  • 6. A method of claim 1, wherein the pressure and vertical velocity data are full wavefield data, not processed to eliminate or reduce multiple reflections.
  • 7. The method of claim 1, displaying an image of the subsurface generated from the subsurface physical property model.
  • 8. The method of claim 1, displaying an image of the subsurface generated from the final physical property model.
  • 9. A computer-implemented method for inverting marine seismic data to infer a subsurface physical property model, said seismic data including pressure data and vertical velocity data, said method comprising: separating the pressure data and the vertical velocity data into an up-going wavefield and a down-going wavefield; anditeratively inverting, with a full wavefield inversion, the up-going wavefield and the down-going wavefield together, meaning that each iteration cycle inverts the up-going wavefield or the down-going wavefield or simultaneously inverts both up-going and down-going wavefields, with each iteration cycle resulting in a model update which is used to generate simulated data in a next iteration cycle, resulting finally in a final physical property model,wherein the separating and the inverting are performed using a computer.
  • 10. The method of claim 9, wherein each inversion comprises using a current physical property model to simulate data, comparing the simulated data to corresponding actual data, measuring a degree of misfit, and using the misfit to generate an update to the current physical property model; wherein the up-going wavefield and the down-going wavefield are separately simulated.
  • 11. The method of claim 10, wherein the down-going wavefield is simulated using mirror geometry.
CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Patent Application 61/843,622, filed Jul. 8, 2013, entitled FULL-WAVEFIELD INVERSION OF PRIMARIES AND MULTIPLES IN MARINE ENVIRONMENT, the entirety of which is incorporated by reference herein.

US Referenced Citations (207)
Number Name Date Kind
3812457 Weller May 1974 A
3864667 Bahjat Feb 1975 A
4159463 Silverman Jun 1979 A
4168485 Payton et al. Sep 1979 A
4545039 Savit Oct 1985 A
4562540 Devaney Dec 1985 A
4575830 Ingram et al. Mar 1986 A
4594662 Devaney Jun 1986 A
4636956 Vannier et al. Jan 1987 A
4675851 Savit et al. Jun 1987 A
4686654 Savit Aug 1987 A
4707812 Martinez Nov 1987 A
4715020 Landrum, Jr. Dec 1987 A
4766574 Whitmore et al. Aug 1988 A
4780856 Becquey Oct 1988 A
4823326 Ward Apr 1989 A
4924390 Parsons et al. May 1990 A
4953657 Edington Sep 1990 A
4969129 Currie Nov 1990 A
4982374 Edington et al. Jan 1991 A
5260911 Mason et al. Nov 1993 A
5469062 Meyer, Jr. Nov 1995 A
5583825 Carrazzone et al. Dec 1996 A
5677893 de Hoop et al. Oct 1997 A
5715213 Allen Feb 1998 A
5717655 Beasley Feb 1998 A
5719821 Sallas et al. Feb 1998 A
5721710 Sallas et al. Feb 1998 A
5790473 Allen Aug 1998 A
5798982 He et al. Aug 1998 A
5822269 Allen Oct 1998 A
5838634 Jones et al. Nov 1998 A
5852588 de Hoop et al. Dec 1998 A
5878372 Tabarovsky et al. Mar 1999 A
5920838 Mostow et al. Jul 1999 A
5924049 Beasley et al. Jul 1999 A
5999488 Smith Dec 1999 A
5999489 Lazaratos Dec 1999 A
6005916 Johnson et al. Dec 1999 A
6014342 Lazaratos Jan 2000 A
6021094 Ober et al. Feb 2000 A
6028818 Jeffryes Feb 2000 A
6058073 VerWest May 2000 A
6125330 Robertson et al. Sep 2000 A
6219621 Hornbostel Apr 2001 B1
6225803 Chen May 2001 B1
6311133 Lailly et al. Oct 2001 B1
6317695 Zhou et al. Nov 2001 B1
6327537 Ikelle Dec 2001 B1
6374201 Grizon et al. Apr 2002 B1
6381543 Guerillot et al. Apr 2002 B1
6388947 Washbourne et al. May 2002 B1
6480790 Calvert et al. Nov 2002 B1
6522973 Tonellot et al. Feb 2003 B1
6545944 de Kok Apr 2003 B2
6549854 Malinverno et al. Apr 2003 B1
6574564 Lailly et al. Jun 2003 B2
6593746 Stolarczyk Jul 2003 B2
6662147 Fournier et al. Dec 2003 B1
6665615 Van Riel et al. Dec 2003 B2
6687619 Moerig et al. Feb 2004 B2
6687659 Shen Feb 2004 B1
6704245 Becquey Mar 2004 B2
6714867 Meunier Mar 2004 B2
6735527 Levin May 2004 B1
6754590 Moldoveanu Jun 2004 B1
6766256 Jeffryes Jul 2004 B2
6826486 Malinverno Nov 2004 B1
6836448 Robertsson et al. Dec 2004 B2
6842701 Moerig et al. Jan 2005 B2
6859734 Bednar Feb 2005 B2
6865487 Charron Mar 2005 B2
6865488 Moerig et al. Mar 2005 B2
6876928 Van Riel et al. Apr 2005 B2
6882938 Vaage et al. Apr 2005 B2
6882958 Schmidt et al. Apr 2005 B2
6901333 Van Riel et al. May 2005 B2
6903999 Curtis et al. Jun 2005 B2
6906981 Vauge Jun 2005 B2
6927698 Stolarczyk Aug 2005 B2
6944546 Xiao et al. Sep 2005 B2
6947843 Fisher et al. Sep 2005 B2
6970397 Castagna et al. Nov 2005 B2
6977866 Huffman et al. Dec 2005 B2
6999880 Lee Feb 2006 B2
7046581 Calvert May 2006 B2
7050356 Jeffryes May 2006 B2
7069149 Goff et al. Jun 2006 B2
7072767 Routh et al. Jul 2006 B2
7092823 Lailly et al. Aug 2006 B2
7110900 Adler et al. Sep 2006 B2
7184367 Yin Feb 2007 B2
7230879 Herkenhoff et al. Jun 2007 B2
7271747 Baraniuk et al. Sep 2007 B2
7330799 Lefebvre et al. Feb 2008 B2
7337069 Masson et al. Feb 2008 B2
7373251 Hamman et al. May 2008 B2
7373252 Sherrill et al. May 2008 B2
7376046 Jeffryes May 2008 B2
7376539 Lecomte May 2008 B2
7400978 Langlais et al. Jul 2008 B2
7436734 Krohn Oct 2008 B2
7480206 Hill Jan 2009 B2
7584056 Koren Sep 2009 B2
7599798 Beasley et al. Oct 2009 B2
7602670 Jeffryes Oct 2009 B2
7616523 Tabti et al. Nov 2009 B1
7620534 Pita et al. Nov 2009 B2
7620536 Chow Nov 2009 B2
7646924 Donoho Jan 2010 B2
7672194 Jeffryes Mar 2010 B2
7672824 Dutta et al. Mar 2010 B2
7675815 Saenger et al. Mar 2010 B2
7679990 Herkenhoff et al. Mar 2010 B2
7684281 Vaage et al. Mar 2010 B2
7710821 Robertsson et al. May 2010 B2
7715985 Van Manen et al. May 2010 B2
7715986 Nemeth et al. May 2010 B2
7725266 Sirgue et al. May 2010 B2
7791980 Robertsson et al. Sep 2010 B2
7835072 Izumi Nov 2010 B2
7840625 Candes et al. Nov 2010 B2
7940601 Ghosh May 2011 B2
8121823 Krebs et al. Feb 2012 B2
8248886 Neelamani et al. Aug 2012 B2
8428925 Krebs et al. Apr 2013 B2
8437998 Routh et al. May 2013 B2
8688381 Routh et al. Apr 2014 B2
20020099504 Cross et al. Jul 2002 A1
20020120429 Ortoleva Aug 2002 A1
20020183980 Guillaume Dec 2002 A1
20040199330 Routh et al. Oct 2004 A1
20040225483 Okoniewski et al. Nov 2004 A1
20060235666 Assa et al. Oct 2006 A1
20070036030 Baumel et al. Feb 2007 A1
20070038691 Candes et al. Feb 2007 A1
20070274155 Ikelle Nov 2007 A1
20080175101 Saenger et al. Jul 2008 A1
20080306692 Singer et al. Dec 2008 A1
20090006054 Song Jan 2009 A1
20090067041 Izumi Mar 2009 A1
20090070042 Birchwood et al. Mar 2009 A1
20090083006 Mackie Mar 2009 A1
20090164186 Haase et al. Jun 2009 A1
20090164756 Dokken et al. Jun 2009 A1
20090187391 Wendt et al. Jul 2009 A1
20090248308 Luling Oct 2009 A1
20090254320 Lovatini et al. Oct 2009 A1
20090259406 Khadhraoui et al. Oct 2009 A1
20100008184 Hegna et al. Jan 2010 A1
20100018718 Krebs et al. Jan 2010 A1
20100039894 Abma et al. Feb 2010 A1
20100054082 McGarry et al. Mar 2010 A1
20100088035 Etgen et al. Apr 2010 A1
20100103772 Eick et al. Apr 2010 A1
20100118651 Liu et al. May 2010 A1
20100142316 Keers et al. Jun 2010 A1
20100161233 Saenger et al. Jun 2010 A1
20100161234 Saenger et al. Jun 2010 A1
20100161235 Ikelle Jun 2010 A1
20100185422 Hoversten Jul 2010 A1
20100208554 Chiu et al. Aug 2010 A1
20100212909 Baumstein et al. Aug 2010 A1
20100265797 Robertsson et al. Oct 2010 A1
20100270026 Lazaratos et al. Oct 2010 A1
20100286919 Lee et al. Nov 2010 A1
20100299070 Abma Nov 2010 A1
20110000678 Krebs et al. Jan 2011 A1
20110040926 Frost et al. Feb 2011 A1
20110051553 Scott et al. Mar 2011 A1
20110090760 Rickett et al. Apr 2011 A1
20110131020 Meng Jun 2011 A1
20110134722 Virgilio et al. Jun 2011 A1
20110182141 Zhamikov et al. Jul 2011 A1
20110182144 Gray Jul 2011 A1
20110191032 Moore Aug 2011 A1
20110194379 Lee et al. Aug 2011 A1
20110222370 Downton et al. Sep 2011 A1
20110227577 Zhang et al. Sep 2011 A1
20110235464 Brittan et al. Sep 2011 A1
20110238390 Krebs et al. Sep 2011 A1
20110246140 Abubakar et al. Oct 2011 A1
20110267921 Mortel et al. Nov 2011 A1
20110267923 Shin Nov 2011 A1
20110276320 Krebs et al. Nov 2011 A1
20110288831 Tan et al. Nov 2011 A1
20110299361 Shin Dec 2011 A1
20110320180 Al-Saleh Dec 2011 A1
20120010862 Costen Jan 2012 A1
20120014215 Saenger et al. Jan 2012 A1
20120014216 Saenger et al. Jan 2012 A1
20120051176 Liu Mar 2012 A1
20120073824 Routh Mar 2012 A1
20120073825 Routh Mar 2012 A1
20120082344 Donoho Apr 2012 A1
20120143506 Routh et al. Jun 2012 A1
20120215506 Rickett et al. Aug 2012 A1
20120275264 Kostov et al. Nov 2012 A1
20120275267 Neelamani et al. Nov 2012 A1
20120290214 Huo et al. Nov 2012 A1
20120314538 Washbourne et al. Dec 2012 A1
20120316790 Washbourne et al. Dec 2012 A1
20120316844 Shah et al. Dec 2012 A1
20130081752 Kurimura et al. Apr 2013 A1
20130238246 Krebs et al. Sep 2013 A1
20130311149 Tang et al. Nov 2013 A1
20130311151 Plessix Nov 2013 A1
Foreign Referenced Citations (20)
Number Date Country
2 796 631 Nov 2011 CA
1 094 338 Apr 2001 EP
1 746 443 Jan 2007 EP
2 390 712 Jan 2004 GB
2 391 665 Feb 2004 GB
WO 2006037815 Apr 2006 WO
WO 2007046711 Apr 2007 WO
WO 2008042081 Apr 2008 WO
WO 2008123920 Oct 2008 WO
WO 2009067041 May 2009 WO
WO 2009117174 Sep 2009 WO
WO 2011040926 Apr 2011 WO
WO 2011091216 Jul 2011 WO
WO 2011093945 Aug 2011 WO
WO 2012024025 Feb 2012 WO
WO 2012041834 Apr 2012 WO
WO 2012083234 Jun 2012 WO
WO 2012134621 Oct 2012 WO
WO 2012170201 Dec 2012 WO
WO 2013081752 Jun 2013 WO
Non-Patent Literature Citations (162)
Entry
Abt, D.L. et al. (2010), “North American lithospheric discontinuity structured imaged by Ps and Sp receiver functions”, J. Geophys. Res., 24 pgs.
Akerberg, P., et al. (2008), “Simultaneous source separation by sparse radon transform,” 78th SEG Annual International Meeting, Expanded Abstracts, pp. 2801-2805.
Aki, K. et al. (1980), “Quantitative Seismology: Theory and Methods vol. I—Chapter 7—Surface Waves in a Vertically Heterogenous Medium,” W.H. Freeman and Co., pp. 259-318.
Aki, K. et al. (1980), “Quantitative Seismology: Theory and Methods vol. I,” W.H. Freeman and Co., p. 173.
Aki et al. (1980), “Quantitative Seismology, Theory and Methods,” Chapter 5.20, W.H. Freeman & Co., pp. 133-155.
Amundsen, L. (2001), “Elimination of free-surface related multiples without need of the source wavelet,” Geophysics 60(1), pp. 327-341.
Anderson, J.E. et al. (2008), “Sources Near the Free-Surface Boundary: Pitfalls for Elastic Finite-Difference Seismic Simulation and Multi-Grid Waveform Inversion,” 70th EAGE Conf. & Exh., 4 pgs.
Barr, F.J. et al. (1989), “Attenuation of Water-Column Reverberations Using Pressure and Velocity Detectors in a Water-Bottom Cable,” 59th Annual SEG meeting, Expanded Abstracts, pp. 653-656.
Baumstein, A. et al. (2009), “Scaling of the Objective Function Gradient for Full Wavefield Inversion,” SEG Houston 2009 Int'l. Expo and Annual Meeting, pp. 224-2247.
Beasley, C. (2008), “A new look at marine simultaneous sources,” The Leading Edge 27(7), pp. 914-917.
Beasley, C. (2012), “A 3D simultaneous source field test processed using alternating projections: a new active separation method,” Geophsyical Prospecting 60, pp. 591-601.
Beaty, K.S. et al. (2003), “Repeatability of multimode Rayleigh-wave dispersion studies,” Geophysics 68(3), pp. 782-790.
Beaty, K.S. et al. (2002), “Simulated annealing inversion of multimode Rayleigh wave dispersion waves for geological structure,” Geophys. J. Int. 151, pp. 622-631.
Becquey, M. et al. (2002), “Pseudo-Random Coded Simultaneous Vibroseismics,” SEG Int'l. Exposition and 72th Annl. Mtg., 4 pgs.
Ben-Hadj-Ali, H. et al. (2009), “Three-dimensional frequency-domain full waveform inversion with phase encoding,” SEG Expanded Abstracts, pp. 2288-2292.
Ben-Hadj-Ali, H. et al. (2011), “An efficient frequency-domain full waveform inversion method using simultaneous encoded sources,” Geophysics 76(4), pp. R109-R124.
Benitez, D. et al. (2001), “The use of the Hilbert transform in ECG signal analysis,” Computers in Biology and Medicine 31, pp. 399-406.
Berenger, J-P. (1994), “A Perfectly Matched Layer for the Absorption of Electromagnetic Waves,” J. of Computational Physics 114, pp. 185-200.
Berkhout, A.J. (1987), “Applied Seismic Wave Theory,” Elsevier Science Publishers, p. 142.
Berkhout, A.J. (1992), “Areal shot record technology,” Journal of Seismic Exploration 1, pp. 251-264.
Berkhout, A.J. (2008), “Changing the mindset in seismic data acquisition,” The Leading Edge 27(7), pp. 924-938.
Beylkin, G. (1985), “Imaging of discontinuities in the inverse scattring problem by inversion of a causal generalized Radon transform,” J. Math. Phys. 26, pp. 99-108.
Biondi, B. (1992), “Velocity estimation by beam stack,” Geophysics 57(8), pp. 1034-1047.
Bonomi, E. et al. (2006), “Wavefield Migration plus Monte Carlo Imaging of 3D Prestack Seismic Data,” Geophysical Prospecting 54, pp. 505-514.
Boonyasiriwat, C. et al. (2010), 3D Multisource Full-Waveform using Dynamic Random Phase Encoding, SEG Denver 2010 Annual Meeting, pp. 1044-1049.
Boonyasiriwat, C. et al. (2010), 3D Multisource Full-Waveform using Dynamic Random Phase Encoding, SEG Denver 2010 Annual Meeting, pp. 3120-3124.
Bunks, C., et al. (1995), “Multiscale seismic waveform inversion,” Geophysics 60, pp. 1457-1473.
Burstedde, G. et al. (2009), “Algorithmic strategies for full waveform inversion: 1D experiments,” Geophysics 74(6), pp. WCC17-WCC46.
Chavent, G. et al. (1999), “An optimal true-amplitude least-squares prestack depth-migration operator,” Geophysics 64(2), pp. 508-515.
Choi, Y. et al. (2011), “Application of encoded multisource waveform inversion to marine-streamer acquisition based on the global correlation,” 73rd EAGE Conference, Abstract, pp. F026.
Choi, Y et al. (2012), “Application of multi-source waveform inversion to marine stream data using the global correlation norm,” Geophysical Prospecting 60, pp. 748-758.
Clapp, R.G. (2009), “Reverse time migration with random boundaries,” SEG International Exposition and Meeting, Expanded Abstracts, pp. 2809-2813.
Dai, W. et al. (2010), “3D Multi-source Least-squares Reverse Time Migration,” SEG Denver 2010 Annual Meeting, pp. 3120-3124.
Delprat-Jannuad, F. et al. (2005), “A fundamental limitation for the reconstruction of impedance profiles from seismic data,” Geophysics 70(1), pp. R1-R14.
Dickens, T.A. et al. (2011), RTM angle gathers using Poynting vectors, SEG Expanded Abstracts 30, pp. 3109-3113.
Donerici, B. et al. (1005), “Improved FDTD Subgridding Algorithms Via Digital Filtering and Domain Overriding,” IEEE Transactions on Antennas and Propagation 53(9), pp. 2938-2951.
Downey, N. et al. (2011), “Random-Beam Full-Wavefield Inversion,” 2011 San Antonio Annual Meeting, pp. 2423-2427.
Dunkin, J.W. et al. (1973), “Effect of Normal Moveout on a Seismic Pluse,” Geophysics 38(4), pp. 635-642.
Dziewonski A. et al. (1981), “Preliminary Reference Earth Model”, Phys. Earth Planet. Int. 25(4), pp. 297-356.
Ernst, F.E. et al. (2000), “Tomography of dispersive media,” J. Acoust. Soc. Am 108(1), pp. 105-116.
Ernst, F.E. et al. (2002), “Removal of scattered guided waves from seismic data,” Geophysics 67(4), pp. 1240-1248.
Esmersoy, C. (1990), “Inversion of P and SV waves from multicomponent offset vertical seismic profiles”, Geophysics 55(1), pp. 39-50.
Etgen, J.T. et al. (2007), “Computational methods for large-scale 3D acoustic finite-difference modeling: A tutorial,” Geophysics 72(5), pp. SM223-SM230.
Fallat, M.R. et al. (1999), “Geoacoustic inversion via local, global, and hybrid algorithms,” Journal of the Acoustical Society of America 105, pp. 3219-3230.
Fichtner, A. et al. (2006), “The adjoint method in seismology I. Theory,” Physics of the Earth and Planetary Interiors 157, pp. 86-104.
Forbriger, T. (2003), “Inversion of shallow-seismic wavefields: I. Wavefield transformation,” Geophys. J Int. 153, pp. 719-734.
Mora, P. (1987), “Elastic Wavefield Inversion,” PhD Thesis, Stanford University, pp. 22-25.
Mora, P. (1989), “Inversion = migration + tomography,” Geophysics 64, pp. 888-901.
Nazarian, S. et al. (1983), “Use of spectral analysis of surface waves method for determination of moduli and thickness of pavement systems,” Transport Res. Record 930, pp. 38-45.
Neelamani, R., (2008), “Simultaneous sourcing without compromise,” 70th Annual Int'l. Conf. and Exh., EAGE, 5 pgs.
Neelamani, R. (2009), “Efficient seismic forward modeling using simultaneous sources and sparsity,” SEG Expanded Abstracts, pp. 2107-2111.
Nocedal, J. et al. (2006), “Numerical Optimization, Chapt. 7—Large-Scale Unconstrained Optimization,” Springer, New York, 2nd Edition, pp. 165-176.
Nocedal, J. et al. (2000), “Numerical Optimization—Calculating Derivatives,” Chapter 8, Springer Verlag, pp. 194-199.
Ostmo, S. et al. (2002), “Finite-difference iterative migration by linearized waveform inversion in the frequency domain,” SEG Int'l. Expo. & 72nd Ann. Meeting, 4 pgs.
Park, C.B. et al. (1999), “Multichannel analysis of surface waves,” Geophysics 64(3), pp. 800-808.
Park, C.B. et al. (2007), “Multichannel analysis of surface waves (MASW)—active and passive methods,” The Leading Edge, pp. 60-64.
Pica, A. et al. (2005), “3D Surface-Related Multiple Modeling, Principles and Results,” 2005 SEG Ann. Meeting, SEG Expanded Abstracts 24, pp. 2080-2083.
Plessix, R.E. et al. (2004), “Frequency-domain finite-difference amplitude preserving migration,” Geophys. J. Int. 157, pp. 975-987.
Porter, R.P. (1989), “Generalized holography with application to inverse scattering and inverse source problems,” In E. Wolf, editor, Progress in Optics XXVII, Elsevier, pp. 317-397.
Pratt, R.G. et al. (1998), “Gauss-Newton and full Newton methods in frequency-space seismic waveform inversion,” Geophys. J. Int. 133, pp. 341-362.
Pratt, R.G. (1999), “Seismic waveform inversion in the frequency domain, Part 1: Theory and verification in a physical scale model,” Geophysics 64, pp. 888-901.
Rawlinson, N. et al. (2008), “A dynamic objective function technique for generating multiple solution models in seismic tomography,” Geophys. J. Int. 178, pp. 295-308.
Rayleigh, J.W.S. (1899), “On the transmission of light through an atmosphere containing small particles in suspension, and on the origin of the blue of the sky,” Phil. Mag. 47, pp. 375-384.
Romero, L.A. et al. (2000), Phase encoding of shot records in prestack migration, Geophysics 65, pp. 426-436.
Ronen S. et al. (2005), “Imaging Downgoing waves from Ocean Bottom Stations,” SEG Expanded Abstracts, pp. 963-967.
Routh, P. et al. (2011), “Encoded Simultaneous Source Full-Wavefield Inversion for Spectrally-Shaped Marine Streamer Data,” SEG San Antonio 2011 Ann. Meeting, pp. 2433-2438.
Ryden, N. et al. (2006), “Fast simulated annealing inversion of surface waves on pavement using phase-velocity spectra,” Geophysics 71(4), pp. R49-R58.
Sambridge, M.S. et al. (1991), “An Alternative Strategy for Non-Linear Inversion of Seismic Waveforms,” Geophysical Prospecting 39, pp. 723-736.
Schoenberg, M. et al. (1989), “A calculus for finely layered anisotropic media,” Geophysics 54, pp. 581-589.
Schuster, G.T. et al. (2010), “Theory of Multisource Crosstalk Reduction by Phase-Encoded Statics,” SEG Denver 2010 Ann. Meeting, pp. 3110-3114.
Sears, T.J. et al. (2008), “Elastic full waveform inversion of multi-component OBC seismic data,” Geophysical Prospecting 56, pp. 843-862.
Sheen, D-H. et al. (2006), “Time domain Gauss-Newton seismic waveform inversion in elastic media,” Geophysics J. Int. 167, pp. 1373-1384.
Shen, P. et al. (2003), “Differential semblance velocity analysis by wave-equation migration,” 73rd Ann. Meeting of Society of Exploration Geophysicists, 4 pgs.
Sheng, J. et al. (2006), “Early arrival waveform tomography on near-surface refraction data,” Geophysics 71, pp. U47-U57.
Sheriff, R.E.et al. (1982), “Exploration Seismology”, pp. 134-135.
Shih, R-C. et al. (1996), “Iterative pre-stack depth migration with velocity analysis,” Terrestrial, Atmospheric & Oceanic Sciences 7(2), pp. 149-158.
Shin, C. et al. (2001), “Waveform inversion using a logarithmic wavefield,” Geophysics 49, pp. 597-606.
Simard, P.Y. et al. (1990), “Vector Field Restoration by the Method of Convex Projections,” Computer Vision, Graphics and Image Processing 52, pp. 360-385.
Sirgue, L. (2004), “Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies,” Geophysics 69, pp. 231-248.
Soubaras, R. et al. (2007), “Velocity model building by semblance maximization of modulated-shot gathers,” Geophysics 72(5), pp. U67-U73.
Spitz, S. (2008), “Simultaneous source separation: a prediction-subtraction approach,” 78th Annual Int'l. Meeting, SEG Expanded Abstracts, pp. 2811-2815.
Stefani, J. (2007), “Acquisition using simultaneous sources,” 69th Annual Conf. and Exh., EAGE Extended Abstracts, 5 pgs.
Symes, W.W. (2007), “Reverse time migration with optimal checkpointing,” Geophysics 72(5), pp. P.SM213-SM221.
Symes, W.W. (2009), “Interface error analysis for numerical wave propagation,” Compu. Geosci. 13, pp. 363-371.
Tang, Y. (2008), “Wave-equation Hessian by phase encoding,” SEG Expanded Abstracts 27, pp. 2201-2205.
Tang, Y. (2009), “Target-oriented wave-equation least-squares migration/inversion with phase-encoded Hessian,” Geophysics 74, pp. WCA95-WCA107.
Tang, Y. et al. (2010), “Preconditioning full waveform inversion with phase-encoded Hessian,” SEG Expanded Abstracts 29, pp. 1034-1037.
Gao, H. et al. (2008), “Implementation of perfectly matched layers in an arbitrary geometrical boundary for leastic wave modeling,” Geophysics J. Int. 174, pp. 1029-1036.
Gibson, B. et al. (1984), “Predictive deconvolution and the zero-phase source,” Geophysics 49(4), pp. 379-397.
Godfrey, R. J. et al. (1998), “Imaging the Foiaven Ghost,” SEG Expanded Abstracts, 4 pgs.
Griewank, A. (1992), “Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation,” 1 Optimization Methods and Software, pp. 35-54.
Griewank, A. (2000), Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, Society for Industrial and Applied Mathematics, 49 pgs.
Griewank, A. et al. (2000), “Algorithm 799: An implementation of checkpointing for the reverse or adjoint mode of computational differentiation,” 26 ACM Transactions on Mathematical Software, pp. 19-45.
Griewank, A. et al. (1996), “Algorithm 755: A package for the automatic differentiation of algorithms written in C/C++,” ACM Transactions on Mathematical Software 22(2), pp. 131-167.
Haber, E. et al. (2010), “An effective method for parameter estimation with PDE constraints with multiple right hand sides,” Preprint—UBC http://www.math.ubc.ca/˜haber/pubs/PdeOptStochV5.pdf.
Hampson, D.P. et al. (2005), “Simultaneous inversion of pre-stack seismic data,” SEG 75th Annual Int'l. Meeting, Expanded Abstracts, pp. 1633-1637.
Heinkenschloss, M. (2008), :“Numerical Solution of Implicity Constrained Optimization Problems,” CAAM Technical Report TR08-05, 25 pgs.
Helbig, K. (1994), “Foundations of Anisotropy for Exploration Seismics,” Chapter 5, pp. 185-194.
Herrmann, F.J. (2010), “Randomized dimensionality reduction for full-waveform inversion,” EAGE abstract G001, EAGE Barcelona meeting, 5 pgs.
Holschneider, J. et al. (2005), “Characterization of dispersive surface waves using continuous wavelet transforms,” Geophys. J. Int. 163, pp. 463-478.
Hu, L.Z. et al. (1987), “Wave-field transformations of vertical seismic profiles,” Geophysics 52, pp. 307-321.
Huang, Y. et al. (2012), “Multisource least-squares migration of marine streamer and land data with frequency-division encoding,” Geophysical Prospecting 60, pp. 663-680.
Igel, H. et al. (1996), “Waveform inversion of marine reflection seismograms for P impedance and Poisson's ratio,” Geophys. J. Int. 124, pp. 363-371.
Ikelle, L.T. (2007), “Coding and decoding: Seismic data modeling, acquisition, and processing,” 77th Annual Int'l. Meeting, SEG Expanded Abstracts, pp. 66-70.
Jackson, D.R. et al. (1991), “Phase conjugation in underwater acoustics,” J. Acoust. Soc. Am. 89(1), pp. 171-181.
Jing, X. et al. (2000), “Encoding multiple shot gathers in prestack migration,” SEG International Exposition and 70th Annual Meeting Expanded Abstracts, pp. 786-789.
Kennett, B.L.N. (1991), “The removal of free surface interactions from three-component seismograms”, Geophys. J. Int. 104, pp. 153-163.
Kennett, B.L.N. et al. (1988), “Subspace methods for large inverse problems with multiple parameter classes,” Geophysical J. 94, pp. 237-247.
Krebs, J.R. (2008), “Fast Full-wavefield seismic inversion using encoded sources,” Geophysics 74(6), pp. WCC177-WCC188.
Krohn, C.E. (1984), “Geophone ground coupling,” Geophysics 49(6), pp. 722-731.
Kroode, F.T. et al. (2009), “Wave Equation Based Model Building and Imaging in Complex Settings,” OTC 20215, 2009 Offshore Technology Conf., Houston, TX, May 4-7, 2009, 8 pgs.
Kulesh, M. et al. (2008), “Modeling of Wave Dispersion Using Continuous Wavelet Transforms II: Wavelet-based Frequency-velocity Analysis,” Pure Applied Geophysics 165, pp. 255-270.
Lancaster, S. et al. (2000), “Fast-track ‘colored’ inversion,” 70th SEG Ann. Meeting, Expanded Abstracts, pp. 1572-1575.
Lazaratos, S. et al. (2009), “Inversion of Pre-migration Spectral Shaping,” 2009 SEG Houston Int'l. Expo. & Ann. Meeting, Expanded Abstracts, pp. 2383-2387.
Lazaratos, S. (2006), “Spectral Shaping Inversion for Elastic and Rock Property Estimation,” Research Disclosure, Issue 511, pp. 1453-1459.
Lazaratos, S. et al. (2011), “Improving the convergence rate of full wavefield inversion using spectral shaping,” SEG Expanded Abstracts 30, pp. 2428-2432.
Lecomte, I. (2008), “Resolution and illumination analyses in PSDM: A ray-based approach,” The Leading Edge, pp. 650-663.
Lee, S. et al. (2010), “Subsurface parameter estimation in full wavefield inversion and reverse time migration,” SEG Denver 2010 Annual Meeting, pp. 1065-1069.
Levanon, N. (1988), “Radar Principles,” Chpt. 1, John Whiley & Sons, New York, pp. 1-18.
Liao, Q. et al. (1995), “2.5D full-wavefield viscoacoustic inversion,” Geophysical Prospecting 43, pp. 1043-1059.
Liu, F. et al. (2007), “Reverse-time migration using one-way wavefield imaging condition,” SEG Expanded Abstracts 26, pp. 2170-2174.
Liu, F. et al. (2011), “An effective imaging condition for reverse-time migration using wavefield decomposition,” Geophysics 76, pp. S29-S39.
Maharramov, M. et al. (2007) , “Localized image-difference wave-equation tomography,” SEG Annual Meeting, Expanded Abstracts, pp. 3009-3013.
Malmedy, V. et al. (2009), “Approximating Hessians in unconstrained optimization arising from discretized problems,” Computational Optimization and Applications, pp. 1-16.
Marcinkovich, C. et al. (2003), “On the implementation of perfectly matched layers in a three-dimensional fourth-order velocity-stress finite difference scheme,” J. of Geophysical Research 108(B5), 2276.
Martin, G.S. et al. (2006), “Marmousi2: An elastic upgrade for Marmousi,” The Leading Edge, pp. 156-166.
Meier, M.A. et al. (2009), “Converted wave resolution,” Geophysics, 74(2):doi:10.1190/1.3074303, pp. Q1-Q16.
Moghaddam, P.P. et al. (2010), “Randomized full-waveform inversion: a dimenstionality-reduction approach,” 80th SEG Ann. Meeting, Expanded Abstracts, pp. 977-982.
Mora, P. (1987), “Nonlinear two-dimensional elastic inversion of multi-offset seismic data,” Geophysics 52, pp. 1211-1228.
Virieus, J. (1986), “P-SV wave propagation in heterogeneous media,” Geophysics 51, pp. 889-901.
Tarantola, A. (1986), “A strategy for nonlinear elastic inversion of seismic reflection data,” Geophysics 51(10), pp. 1893-1903.
Tarantola, A. (1988), “Theoretical background for the inversion of seismic waveforms, including elasticity and attenuation,” Pure and Applied Geophysics 128, pp. 365-399.
Tarantola, A. (2005), “Inverse Problem Theory and Methods for Model Parameter Estimation,” SIAM, pp. 79.
Tarantola, A. (1984), “Inversion of seismic reflection data in the acoustic approximation,” Geophysics 49, pp. 1259-1266.
Trantham, E.C. (1994), “Controlled-phase acquisition and processing,” SEG Expanded Abstracts 13, pp. 890-894.
Tsvankin, I. (2001), “Seismic Signatures and Analysis of Reflection Data in Anisotropic Media,” Elsevier Science, p. 8.
Valenciano, A.A. (2008), “Imaging by Wave-Equation Inversion,” A Dissertation, Stanford University, 138 pgs.
van Groenestijn, G.J.A. et al. (2009), “Estimating primaries by sparse inversion and application to near-offset reconstruction,” Geophyhsics 74(3), pp. A23-A28.
van Manen, D.J. (2005), “Making wave by time reversal,” SEG International Exposition and 75th Annual Meeting, Expanded Abstracts, pp. 1763-1766.
Verschuur, D.J. (2009), Target-oriented, least-squares imaging of blended data, 79th Annual Int'l. Meeting, SEG Expanded Abstracts, pp. 2889-2893.
Verschuur, D.J. et al. (1992), “Adaptive surface-related multiple elimination,” Geophysics 57(9), pp. 1166-1177.
Verschuur, D.J. (1989), “Wavelet Estimation by Prestack Multiple Elimination,” SEG Expanded Abstracts 8, pp. 1129-1132.
Versteeg, R. (1994), “The Marmousi experience: Velocity model determination on a synthetic complex data set,” The Leading Edge, pp. 927-936.
Vigh, D. et al. (2008), “3D prestack plane-wave, full-waveform inversion,” Geophysics 73(5), pp. VE135-VE144.
Wang, Y. (2007), “Multiple prediction through inversion: Theoretical advancements and real data application,” Geophysics 72(2), pp. V33-V39.
Wang, K. et al. (2009), “Simultaneous full-waveform inversion for source wavelet and earth model,” SEG Int'l. Expo. & Ann. Meeting, Expanded Abstracts, pp. 2537-2541.
Weglein, A.B. (2003), “Inverse scattering series and seismic exploration,” Inverse Problems 19, pp. R27-R83.
Wong, M. et al. (2010), “Joint least-squares inversion of up- and down-going signal for ocean bottom data sets,” SEG Expanded Abstracts 29, pp. 2752-2756.
Wu R-S. et al. (2006), “Directional illumination analysis using beamlet decomposition and propagation,” Geophysics 71(4), pp. S147-S159.
Xia, J. et al. (2004), “Utilization of high-frequency Rayleigh waves in near-surface geophysics,” The Leading Edge, pp. 753-759.
Xie, X. et al. (2002), “Extracting angle domain information from migrated wavefield,” SEG Expanded Abstracts21, pp. 1360-1363.
Xie, X.-B. et al. (2006), “Wave-equation-based seismic illumination analysis,” Geophysics 71(5), pp. S169-S177.
Yang, K. et al. (2000), “Quasi-Orthogonal Sequences for Code-Division Multiple-Access Systems,” IEEE Transactions on Information Theory 46(3), pp. 982-993.
Yoon, K. et al. (2004), “Challenges in reverse-time migration,” SEG Expanded Abstracts 23, pp. 1057-1060.
Young, J. et al. (2011), “An application of random projection to parameter estimation in partial differential equations,” SIAM, 20 pgs.
Zhang, Y. (2005), “Delayed-shot 3D depth migration,” Geophysics 70, pp. E21-E28.
Ziolkowski, A. (1991), “Why don't we measure seismic signatures?,” Geophysics 56(2), pp. 190-201.
U.S. Appl. No. 14/272,020, filed May 7, 2014, Wang et al.
U.S. Appl. No. 14/286,107, filed May 23, 2014, Hu et al.
U.S. Appl. No. 14/272,827, filed May 8, 2014, Baumstein et al.
U.S. Appl. No. 14/329,431, filed Jul. 11, 2014, Krohn et al.
U.S. Appl. No. 14/330,767, filed Jul. 14, 2014, Tang et al.
Related Publications (1)
Number Date Country
20150012221 A1 Jan 2015 US
Provisional Applications (1)
Number Date Country
61843622 Jul 2013 US