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WO2011071812A2 - Inversion simultanée et conjointe de données d'onde de surface et de réfraction - Google Patents

Inversion simultanée et conjointe de données d'onde de surface et de réfraction Download PDF

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Publication number
WO2011071812A2
WO2011071812A2 PCT/US2010/059088 US2010059088W WO2011071812A2 WO 2011071812 A2 WO2011071812 A2 WO 2011071812A2 US 2010059088 W US2010059088 W US 2010059088W WO 2011071812 A2 WO2011071812 A2 WO 2011071812A2
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Prior art keywords
wave
refracted
surface wave
computer
properties
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WO2011071812A3 (fr
Inventor
Massimo Virgilio
Claudio Strobbia
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Schlumberger Canada Ltd
Schlumberger Technology BV
Westerngeco LLC
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Schlumberger Canada Ltd
Geco Technology BV
Westerngeco LLC
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Priority to GB1209580.8A priority Critical patent/GB2490051B/en
Publication of WO2011071812A2 publication Critical patent/WO2011071812A2/fr
Publication of WO2011071812A3 publication Critical patent/WO2011071812A3/fr
Priority to EG2012061027A priority patent/EG26916A/xx
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/282—Application of seismic models, synthetic seismograms
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles

Definitions

  • This invention relates to data processing for geophysical exploration and is, more specifically, related to simultaneous joint inversion of surface wave and refraction data to obtain the near surface properties in three-dimensional (“3D”) and two-dimensional (“2D”) seismic surveys.
  • 3D three-dimensional
  • 2D two-dimensional
  • This coherent noise (often simply called ground roll in land seismic) can be made of different wave types, such as Rayleigh waves, with multiple modes of propagation, Lamb waves, P-guided waves, Love waves, Scholte waves.
  • the propagation properties of surface waves depend on the elastic properties of the so-called near-surface, the shallow portion of the earth which is responsible of most of the perturbation and degradation of the seismic signals.
  • the accurate identification of the properties of the different surface waves is a crucial point for the design of filters (adapted to the different properties), and can be used for the generation of noise models to be subtracted from data.
  • the analysis of surface wave allows the near surface characterization.
  • the dispersion curve can be inverted to get a velocity profile as demonstrated in Xia J., et ah, "Estimation of near-surface shear wave velocity by inversion of Rayleigh waves", 64 Geophysics 691-700 (1999).
  • the characterization techniques based on the analysis and inversion of the surface wave properties have been used in different disciplines, from the large scale of the earthquake seismology to the very small scale of ultrasonic non-destructive testing.
  • the surface wave method for the near surface characterization is a three-step process: seismic data are acquired with a linear array of receivers and an in-line source, data are processed to extract the propagation properties, usually the dispersion curve, which is finally inverted to get a single velocity profile associated to one location within the array.
  • Socco L.V. & Strobbia C "Surface-wave method for near- surface characterization: a tutorial, Near Surface Geophysics," 165-185 (2004).
  • the dispersion curve is often extracted tracking energy maxima in 2D wavefield transforms, in which the energy is mapped from T-X domain into F-K, F-V, F-p.
  • Alternative approaches use the phase difference analysis, such as that disclosed in Strobbia C. & Foti S., "Multi-offset phase analysis of surface wave data (MOPA),” 59/4 Journal of Applied Geophysics, 300-313 (2006), and can identify lateral variations.
  • refraction can be defined as the change in the direction of propagation of a wavefront, or the bending of a ray, as it passes from one medium to another. It is expressed mathematically by Snell's law and is consequence of changes in wavelength and velocity of propagation of a wave. It is produced by differences in refractive indices of the media. "Refracted waves” are also called “diving waves” ("DW”) in seismic exploration. Refraction surveys where the incident and reflected angles are critical can be useful for evaluating increasing velocity gradients and locating features that have anomalously high velocities. Currently refraction tomography provides a reliable near-surface velocity model for both structural depth imaging workflows and static corrections for time processing.
  • the refraction method for the near surface characterization is a three step process: seismic data are acquired with a linear array of receivers and an in line source, data are processed to extract the refraction properties, usually a set of picks of first arrivals on the shot gathers, and then inverted (tomography) to get velocity of the subsurface.
  • the tomography uses refracted first arrivals to compute a near-surface earth model by minimizing the difference between calculated and observed travel times. Because refracted energy samples the near surface with more redundancy and with a greater angular range than reflected waves, it converges robustly to the final velocity model. This approach is used today in land, marine, or OBC environments.
  • Two-dimensional Simultaneous Joint Inversion (“2D SJI”) is today a robust technology for structural imaging in the exploration framework, mainly used to improve the quality of the velocity models used for depth imaging by means of the integration with different domains (Seismic, Gravity, and Electromagnetic).
  • Two different patent submissions are currently running about SJI for integration of seismic and non seismic data for structural imaging. See U.S. Serial No. 1 1/829,551, entitled “Methods and Apparatus for Geophysical Exploration Via Joint Inversion", filed July 27, 2007, and International Patent Application No. PCT/IT2006/000636, entitled “Method for Building Velocity Models for Pre-Stack Depth Migration via the Simultaneous Joint Inversion of Seismic, Gravity and Magnetotelluric Data", filed April 9, 2006.
  • the data to be minimized consist of residuals from multiple geophysical domains, cross parameter constraints (empirical, physical, statistical), and external a-priori constraints (e.g., geometrical relations).
  • the objective function for the SJI problem contains the models of different geophysical domains (the unknowns), the data residuals, the single domain regularization and the links, that are simply the constraints between the domains involved.
  • the present invention is directed to resolving, or at least reducing, one or all of the problems mentioned above.
  • the present invention is a computer-implemented technique for use in geophysical exploration and is, more specifically, related to a processing technique including simultaneous joint inversion of surface wave and refraction data to obtain the near surface properties in three-dimensional ("3D") and two-dimensional (“2D”) seismic surveys.
  • 3D three-dimensional
  • 2D two-dimensional
  • the invention includes a computer-implemented method for use in exploring a subsurface geological formation, comprising: extracting the surface and refracted wave properties from a set of seismic data representing the subsurface geological formation; and simultaneously and jointly inverting the extracted surface and refracted wave properties to estimate the visco-elastic shear and compressional parameters in the near surface.
  • the invention includes a program storage medium encoded with instructions that, when executed by a computing device, performs a method such as that described above.
  • the invention includes a computing apparatus programmed to perform such a method.
  • FIG. 1 illustrates one embodiment of a computer-implemented method in accordance with one aspect of the present invention
  • FIG. 2 illustrates one particular implementation of the embodiment of FIG. 1
  • FIG. 3 is a block diagram of one particular embodiment of the present invention.
  • FIG. 4A - FIG. 4B present an analysis of a shot gather to identify coherent noise modes
  • FIG. 5 is an exemplary, continuous distribution of the phase velocity of the fundamental mode for a 2D line (surface wave velocity pseudosection), in which the vertical axis is the SW wavelength, the horizontal axis the position along the line, the color scale the phase velocity;
  • FIG. 6A and FIG. 6B to illustrate an exemplary shot gather and picked first break travel times, respectively;
  • FIG. 7 is an exemplary representation of refracted first-break wave travel time for a full 2D line
  • FIG. 8A - FIG. 8B illustrate two independent inversions for the same 2D line
  • FIG. 8A representing the shear wave velocity section obtained with the surface wave dispersion inversion and FIG. 8B representing the compression wave velocity section obtained via refracted travel time inversion;
  • FIG. 9A - FIG. 9B are sketches of the grids for the refraction and surface wave forward models.
  • FIG. 10 shows selected portions of the hardware and software architecture of a computing apparatus such as may be employed in some aspects of the present invention
  • FIG. 11 illustrates a computing system on which some aspects of the present invention may be practiced in some embodiments
  • the proposed method allows the estimation of the near surface properties in 3D and 2D seismic survey by inverting jointly the surface wave and the refracted wave properties.
  • the approach used herein consists of the integration of the surface wave method in the general data processing workflow for 3D data.
  • the analysis stage involves creating first a smooth spatial distribution of the propagation properties and then a detailed high- resolution image of the dispersive and dissipative properties of the surface wave modes.
  • Both the wave types can be analyzed and processed, with different techniques, to characterize the near surface, for instance to correct for the distortion that the near surface induces on the deeper image.
  • Refraction techniques have been traditionally used, for example for the computation of static corrections or shallow depth imaging, while surface wave methods have been introduced more recently in the data processing workflow.
  • Surface waves and refracted waves are normally present in surface seismic data, acquired with sources and receivers close to the Earth's surface. The two events have different characteristics and their joint use offers several synergies.
  • the seismic surface waves are more sensitive to the shear elastic parameters (velocity and attenuation) and their properties can be inverted to get, for example, a near surface distribution of the shear wave velocity.
  • the first arrivals are in general associated with P-wave refracted path, and the inversion of the refracted wave properties can generate, for instance, a near surface distribution of the compressional velocity.
  • the investigation depth of refraction based techniques tends to be larger, while SW gives a higher resolution in the shallow portion.
  • Surface wave methods are moreover more robust with respect to complex shallow structures, such as velocity inversions and hidden layers.
  • the surface waves are not affected by scarce penetration of the energy, a typical problem of the refraction propagations through vertical inversions of velocity.
  • the two methods can complement each other for a complete and robust near surface characterization.
  • a joint interpretation can exploit only part of the benefits, while the proposed simultaneous joint inversion uses all the available data and prior information for the determination of the elastic parameters of the near surface.
  • the joint inversion does not require a priori assumption about the Poisson ratio in the surface wave inversion.
  • the method 100 comprises of two stages 110, 120. Firstly, at 1 10, a single set of seismic data is processed to extract both the surface and refracted wave properties. Secondly, at 120, these properties are simultaneously and jointly inverted to estimate the (visco-) elastic parameters (shear and compressional) in the near surface. [0036]
  • the surface wave properties estimation can include the dispersion of the surface wave modes, their attenuation and frequency response.
  • the refracted wave properties include the travel-time for each pair of source and detector, as well as the amplitude and wavelet information.
  • the processing stage can involve the extraction of first break travel time for all pairs source-detector in a survey and the estimation of modal dispersion curves for all locations within the survey area simultaneously.
  • the data are analyzed to define the optimal model parameterization, for example the size and discretization of the domain.
  • the prior information (geological, petrophysical etc.) is formalized in terms of constitutive relationships and links between the two domains, and a-priori information used in the workflow.
  • the inversion stage consists of an optimization problem, where unknown near surface elastic properties are estimated matching modeled data to the extracted wave properties, and considering mutual and spatial correlation for both domains.
  • the surface wave and refraction properties would be inverted separately, and in case, just at the end of the inversion phase, they would be interpreted jointly.
  • the proposed technology inverts for surface and refraction properties simultaneously, providing a consistent and integrated parameterization obtained at inversion level, and therefore an improved workflow in terms of integration.
  • the novelty of the method is the complete integration of surface waves and refracted waves in terms of data and of inferred models, and the applicability to 3D large scale surveying.
  • the proposed method aims obtaining the spatial distribution of the elastic properties (V p , V s , attenuation) from seismic data with general 3D acquisition geometries, inverting jointly the properties of the surface waves and of the refracted compressional waves.
  • the recorded seismic data are processed to extract the propagation properties of the two wave phenomena, the surface waves and the refracted compressional waves.
  • multimodal dispersion and attenuation can be extracted from data with 3D geometries for the whole survey area covered with sources and detectors.
  • the travel time and wavelet properties can be extracted for each source-detector pair.
  • the method 100, of FIG. 1, can, in one particular embodiment, be broken into four main stages, as shown in FIG. 2.
  • the wave properties are identified (at 210). Seismic data is processed to extract the properties of the considered wave phenomena. The dispersion and attenuation curves are extracted continuously within the survey area, the first break ("FB") and the FB wavelet attributes are extracted for all pairs of sources and detectors of interest. This is followed by single domain inversions (at 220). The two data sets, or subsets of them corresponding to selected areas of interest, are first inverted independently. The results are compared and analyzed jointly, to evaluate their spatial and mutual correlation, to assess the sensitivity and limitations of the techniques for the area of study, and to validate and calibrate the links between the petrophysical parameters.
  • SJI simultaneous joint inversion
  • the parameters of the SJI are determined and tuned for the particular application.
  • the properties of the grids for the two forward problems, the regularizations and the physical links with the relative weights must be defined before proceeding with the SJI iterations.
  • the simultaneous joint inversion (at 240).
  • the experimental data are input to a joint optimization problem which estimates a unique near surface elastic model.
  • a single cost function is created, incorporating a collection of different misfits functions for the data and the link between the domains, relating the petrophysical parameter or the spatial gradients.
  • the illustrated implementation begins with a set of previously acquired seismic data 300. Because the seismic data 300 is previously acquired, it could be legacy data in some embodiments. It may also be acquired relatively contemporaneously and collected for processing at another location. This will be the typical scenario. The invention is not limited by the temporal relationship between acquisition and processing.
  • the seismic data 300 may be acquired in any suitable manner known to the art. For example, the seismic data 300 may be acquired through either a land survey or a seabed survey. In a seabed survey, the seismic data may be multi-component data or just pressure data.
  • the seismic data 300 then undergoes processing in both the surface wave domain 310 and the refracted wave domain 320.
  • the wave properties are identified (at 210) and the single domain inversions (at 220) are performed.
  • the results of the single domain processing 310, 320 are then used in the parameterization (at 230) and simultaneous joint inversion (at 240).
  • the wave properties are first identified (at 210). Some shot gathers spanning a large offset range are selected, in order to analyze and classify the near surface modes, with special care to the presence of multiple modes, their phase velocity and attenuation. Shot gathers can be analyzed using wavefield transforms such as f-k, followed by tracking of energy maxima. Events are identified, and the subsequent processing workflow is set-up. FIG. 4A - FIG. 4B are examples of shot gather and modal curves. The complete processing workflow extracts the dispersion curves and attenuation curves for the different surface wave modes present in the data, continuously within the survey area. An example of Rayleigh wave fundamental mode phase velocity along a receiver line is provided in FIG. 5.
  • the refracted wave domain processing 320 extracts the refracted wave properties after pre-processing and data conditioning in a manner known to the art.
  • the first break travel-time, the peak amplitude, the spectral properties of the wavelet can be extracted.
  • FIG. 6A and FIG. 6B a shot gather and the first-break travel-times extracted via first break picking are depicted.
  • the refracted wave properties are extracted for all source-detector pairs.
  • the picked first-break travel times for the considered 2D line are represented in terms of CMP location (horizontal axis), source- detector offset (vertical axis) and tangent velocity (gray scale).
  • This processing 322 yields a set of surface wave data 324.
  • the two datasets 314, 324 are inverted independently (at 220) before being used within the SJI framework.
  • the surface wave inversion 316 provides a shear wave velocity model 318, and a shear wave attenuation model (not shown).
  • the refraction inversion 326 provides a compressional wave velocity model 328 and a compressional attenuation model (also not shown).
  • the resolution of the two inverted models 318, 328 is assessed; the depth of investigation is evaluated considering the model covariances as well as respectively the Rayleigh wave eigenfunctions and the refraction illumination or ray coverage.
  • the relationship between the different physical parameters is observed and mapped, to evaluate the validity of assumed petrophysical relationships.
  • the technique embarks upon parameterization of the simultaneous joint inversion (at 230).
  • the geometries of the SJI iterations i.e. the grid dimension and extension, the position and the padding
  • Vs and Vp are resolved on different grids according to their specific resolution.
  • the SJI parameters to be defined for each SJI iteration include the regularization, the links, and the weights.
  • the regularization weight coming from the single domain analysis is generally too high since each refraction domain acts as regularization for the V s inversion (and vice versa). Therefore it is reduced and properly tuned for the specific application.
  • V p and V s have a common pattern in the shallow subsurface (see FIG. 8A - FIG. 8B) and so the geometrical link forcing the V p and V s to be inverted with similar shapes and variations is precious.
  • the general empirical equation V p 1.7 V s is used as empirical constrain within the cost function.
  • the weights, refraction and surface wave domain have the same weight, the empirical law is weighted the double when compared with the geometrical link.
  • the parameterization (at 230) is then followed by the simultaneous joint inversion (at 240) that extracts a unique SJI-V S model 330 and unique SJI-V P model 340, combining the information of the two datasets.
  • SJI improved the quality of the sections, defining better the near surface features and resolving the shallow anomalies.
  • the workflow proceeds iteratively with a global tomography approach, which is inverting all the refraction residuals together as opposite of the layer stripping approach.
  • the total number of iterations of SJI to obtain the final V p and SJI-V S models is in general lower than 10.
  • the near surface velocity volume combines the greater penetration of refraction data with the higher vertical and lateral resolution of surface waves in the shallow section.
  • thin and sub-vertical low velocity fault zones can be resolved better with the contribution of SW.
  • shallow velocity inversions affect the effectiveness of refraction in that part of the model.
  • the final SJI-V P model 340 (incorporating both RW and SW data) can be used directly to compute parameters for the data processing.
  • the SJI-V P model 340 has been used to compute the time statics on the seismic data that now show an improved continuity and a better stacking power on the main events of the first few hundreds meters.
  • the technique presented herein allows obtaining a near surface model using all the information in seismic record, merging in a rational manner the contribution of surface wave and refracted waves.
  • Surface and refracted waves provide different advantages to the near surface investigation; the resolution, the penetration and therefore the depth range of investigation are different; merging refracted and surface waves properly means taking benefits from both of them and thus having a better definition of the shallow subsurface parameters.
  • the combination of the two techniques has therefore several synergies, which can be exploited using the simultaneous joint inversion.
  • the resolution and robustness of surface wave data is able to resolve better the shallow part of the model, and to solve the critical cases of complex near surface.
  • the refraction extends the investigation depth and provides the direct P-wave information which is essential to use the near surface model in the reflection data processing workflow.
  • the joint inversion will also contribute to improve the shear wave model reliability with Poisson's ratio anomalies: in these cases, the a priori assumption of the Poisson ratio may lead to model errors, Foti S., & Strobbia C, "Some Notes on Model Parameters for Surface Wave Data Inversion", Proc. SAGEEP, Las Vegas, USA,1 lpp. (2002), and the use of the refraction data avoids this pitfall.
  • the obtained model allows a lithological classification of the near-surface, and a more reliable estimation of other physical and petrophysical parameters, such as the absolute or relative mass density, used for instance in full wave inversions, elastic seismic migrations, and similar applications.
  • the data will reside on some type of program storage medium and will be transformed upon execution of the process. This will then physically alter the content of the program storage medium.
  • the physical alteration is a "physical transformation" in that it changes the physical state of the storage for the computing apparatus.
  • the software implemented aspects of the invention are typically encoded on some form of program storage medium or implemented over some type of transmission medium.
  • the program storage medium may be magnetic (e.g., a floppy disk or a hard drive) or optical (e.g., a compact disk read only memory, or "CD ROM"), and may be read only or random access.
  • the transmission medium may be twisted wire pairs, coaxial cable, optical fiber, or some other suitable transmission medium known to the art. The invention is not limited by these aspects of any given implementation.
  • FIG. 10 shows selected portions of the hardware and software architecture of a computing apparatus 1000 such as may be employed in one particular embodiment of some aspects of the present invention.
  • the computing apparatus " 000 includes a processor 1005 communicating with storage 1010 over a bus system 1015.
  • the storage 1010 may include all manner of program storage media such as a hard disk and/or random access memory (“RAM”) and/or removable storage such as a floppy magnetic disk 1017 and an optical disk 1020.
  • RAM random access memory
  • the storage 1010 is encoded with surface wave data 1025 and refraction data 1026.
  • the surface wave data 1025 and refraction data 1026 are acquired as discussed above.
  • the storage 1010 is also encoded with an operating system 1030, user interface software 1035, and an application 1065.
  • the user interface software 1035 in conjunction with a display 1040, implements a user interface 1045.
  • the user interface 1045 may include peripheral I/O devices such as a keypad or keyboard 1050, a mouse 1055, or a joystick 1060.
  • the processor 1005 runs under the control of the operating system 1030, which may be practically any operating system known to the art.
  • the application 1065 is invoked by the operating system 1030 upon power up, reset, or both, depending on the implementation of the operating system 1030.
  • the application 1065 when invoked, performs the method of the present invention as described above.
  • the user may invoke the application in conventional fashion through the user interface 1045.
  • surface wave data 1025 and refraction data 1026 may reside on the same computing apparatus 1000 as the application 1065 by which it is processed.
  • Some embodiments of the present invention may therefore be implemented on a computing system, e.g., the computing system 1 100 in FIG. 11, comprising more than one computing apparatus.
  • surface wave data 1025 and refraction data 1026 may reside in a data structure residing on a server 1 103 and the application 1065 by which it is processed on a workstation 1106 where the computing system 1100 employs a networked client/server architecture.
  • the surface wave data set 1026 is shown residing on the server 1103, there is no requirement that surface wave data 1025 and refraction data 1026 reside together.
  • the computing system 1 100 may be networked.
  • Alternative embodiments may employ, for instance, a peer-to-peer architecture or some hybrid of a peer-to-peer and client/server architecture.
  • the size and geographic scope of the computing system 1 100 is not material to the practice of the invention. The size and scope may range anywhere from just a few machines of a Local Area Network ("LAN") located in the same room to many hundreds or thousands of machines globally distributed in an enterprise computing system.
  • LAN Local Area Network
  • the apparatus is described as being “capable of performing a one or more particular functions.
  • the phrase "capable of as used herein is a recognition of the fact that some functions described for the various parts of the disclosed apparatus are performed only when the apparatus is powered and/or in operation.
  • the embodiments illustrated herein include a number of electronic or electro-mechanical parts that, to operate, require electrical power. Even when provided with power, some functions described herein only occur when in operation.
  • some embodiments of the apparatus of the invention are "capable of performing the recited functions even when they are not actually performing them— i.e., when there is no power or when they are powered but not in operation.
  • Socco L.V. & Strobbia C "Surface-wave method for near-surface characterization: a tutorial, Near Surface Geophysics," 165-185 (2004);

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Abstract

La présente invention concerne une technique comprenant un procédé et un appareil destinés à l'inversion simultanée et conjointe de données d'onde de surface et de réfraction afin d'identifier des propriétés géophysiques et géologiques à proximité de la surface.
PCT/US2010/059088 2009-12-07 2010-12-06 Inversion simultanée et conjointe de données d'onde de surface et de réfraction Ceased WO2011071812A2 (fr)

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GB1209580.8A GB2490051B (en) 2009-12-07 2010-12-06 Simultaneous joint inversion of surface wave and refraction data
EG2012061027A EG26916A (en) 2009-12-07 2012-06-06 Simultaneous joint inversion of surface wave and refraction data

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US26722309P 2009-12-07 2009-12-07
US61/267,223 2009-12-07
US12/960,703 US8861308B2 (en) 2009-12-07 2010-12-06 Simultaneous joint inversion of surface wave and refraction data
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US8694299B2 (en) 2010-05-07 2014-04-08 Exxonmobil Upstream Research Company Artifact reduction in iterative inversion of geophysical data
US8995223B2 (en) * 2010-10-13 2015-03-31 The Petroleum Institute Method for removing Scholte waves and similar ground roll type waves from seismic sea bottom data shallow waters
US9134442B2 (en) * 2010-12-16 2015-09-15 Bp Corporation North America Inc. Seismic acquisition using narrowband seismic sources
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CA2839277C (fr) 2011-09-02 2018-02-27 Exxonmobil Upstream Research Company Utilisation d'une projection sur des ensembles convexes pour limiter l'inversion du champ d'ondes complet
GB2495906A (en) * 2011-10-17 2013-05-01 Seg Squared Ltd Identifying objects buried close to the surface from surface wave and p-wave data extracted from seismic survey data
US9176930B2 (en) 2011-11-29 2015-11-03 Exxonmobil Upstream Research Company Methods for approximating hessian times vector operation in full wavefield inversion
WO2013116099A1 (fr) * 2012-01-30 2013-08-08 Schlumberger Canada Limited Amélioration de l'efficacité d'algorithmes d'inversion à base de pixels
AU2013230789B2 (en) 2012-03-08 2016-02-11 Exxonmobil Upstream Research Company Orthogonal source and receiver encoding
EP2926170A4 (fr) 2012-11-28 2016-07-13 Exxonmobil Upstream Res Co Tomographie fondée sur le facteur de qualité q de données sismiques de réflexion
US9626463B2 (en) 2012-12-28 2017-04-18 Dassault Systemes Simulia Corp. Accelerated algorithm for modal frequency response calculation
US20140200816A1 (en) * 2013-01-14 2014-07-17 Westerngeco L.L.C. Seismic data processing
CA2909105C (fr) 2013-05-24 2018-08-28 Ke Wang Inversion multiparametrique par fwi elastique dependante au decalage
US10459117B2 (en) 2013-06-03 2019-10-29 Exxonmobil Upstream Research Company Extended subspace method for cross-talk mitigation in multi-parameter inversion
US9702998B2 (en) 2013-07-08 2017-07-11 Exxonmobil Upstream Research Company Full-wavefield inversion of primaries and multiples in marine environment
MX359179B (es) 2013-08-23 2018-09-18 Exxonmobil Upstream Res Co Adquisicion de fuentes simultanea durante adquisicion sismica e inversion sismica.
US10036818B2 (en) 2013-09-06 2018-07-31 Exxonmobil Upstream Research Company Accelerating full wavefield inversion with nonstationary point-spread functions
US11614554B2 (en) * 2014-01-13 2023-03-28 Cgg Services Sas Velocity model building for seismic data processing using PP-PS tomography with co-depthing constraint
US9910189B2 (en) 2014-04-09 2018-03-06 Exxonmobil Upstream Research Company Method for fast line search in frequency domain FWI
RU2649214C1 (ru) 2014-05-09 2018-03-30 Эксонмобил Апстрим Рисерч Компани Эффективные способы линейного поиска при многопараметрической инверсии полного волнового поля
US10185046B2 (en) 2014-06-09 2019-01-22 Exxonmobil Upstream Research Company Method for temporal dispersion correction for seismic simulation, RTM and FWI
CA2947410A1 (fr) 2014-06-17 2015-12-30 Exxonmobil Upstream Research Company Inversion de champ d'ondes complet viscoacoustique et viscoelastique rapide
US10838092B2 (en) 2014-07-24 2020-11-17 Exxonmobil Upstream Research Company Estimating multiple subsurface parameters by cascaded inversion of wavefield components
US10422899B2 (en) 2014-07-30 2019-09-24 Exxonmobil Upstream Research Company Harmonic encoding for FWI
US10386511B2 (en) 2014-10-03 2019-08-20 Exxonmobil Upstream Research Company Seismic survey design using full wavefield inversion
WO2016064462A1 (fr) 2014-10-20 2016-04-28 Exxonmobil Upstream Research Company Tomographie de vitesse utilisant des balayages de propriété
WO2016099747A1 (fr) 2014-12-18 2016-06-23 Exxonmobil Upstream Research Company Planification évolutive de travaux sismiques itératifs parallèles
US10520618B2 (en) 2015-02-04 2019-12-31 ExxohnMobil Upstream Research Company Poynting vector minimal reflection boundary conditions
CA2972028C (fr) 2015-02-13 2019-08-13 Exxonmobil Upstream Research Company Condition de limite d'absorption efficace et stable dans des calculs a difference finie
WO2016133561A1 (fr) 2015-02-17 2016-08-25 Exxonmobil Upstream Research Company Procédé d'inversion de champ d'ondes complet à plusieurs étages qui génère un ensemble de données sans multiples
US20160320507A1 (en) * 2015-04-28 2016-11-03 Westerngeco, Llc Time lapse seismic data processing
WO2016187252A1 (fr) * 2015-05-20 2016-11-24 Conocophillips Company Tomographie en ondes de surface utilisant l'acquisition de données éparses
SG11201708665VA (en) 2015-06-04 2017-12-28 Exxonmobil Upstream Res Co Method for generating multiple free seismic images
US10838093B2 (en) 2015-07-02 2020-11-17 Exxonmobil Upstream Research Company Krylov-space-based quasi-newton preconditioner for full-wavefield inversion
RU2693495C1 (ru) 2015-10-02 2019-07-03 Эксонмобил Апстрим Рисерч Компани Полная инверсия волнового поля с компенсацией показателя качества
CA2998519A1 (fr) 2015-10-15 2017-04-20 Exxonmobil Upstream Research Company Empilements d'angles de domaine de modele d'inversion des formes d'onde complete (fwi) a preservation d'amplitude
US10768324B2 (en) 2016-05-19 2020-09-08 Exxonmobil Upstream Research Company Method to predict pore pressure and seal integrity using full wavefield inversion
US10605937B2 (en) * 2016-05-26 2020-03-31 Cgg Services Sas Device and method for smart picking surface waves dispersion curves
CN106772575A (zh) * 2016-11-28 2017-05-31 安徽理工大学 一种基于折射波与面波联合反演剩余煤层厚度的方法
CN108646288B (zh) * 2018-02-27 2020-03-10 中国石油天然气集团有限公司 近地表模型的建立方法和装置
CN109061731B (zh) * 2018-09-18 2019-10-25 中国地震局地壳应力研究所 面波频散与体波谱比联合反演浅层速度的全局优化方法
CN113093279B (zh) * 2020-01-08 2024-05-28 中国石油天然气集团有限公司 转换波静校正方法及装置
US11754744B2 (en) * 2020-03-04 2023-09-12 Southern University Of Science And Technology Surface wave prospecting method for jointly extracting Rayleigh wave frequency dispersion characteristics by seismoelectric field
CN112904407B (zh) * 2020-10-14 2023-05-30 东华理工大学 复杂地形与干扰条件下的微动勘探方法
CN112285767B (zh) * 2020-10-14 2021-04-23 中国科学院地质与地球物理研究所 海底地震仪四分量海洋面波多阶频散能量成像装置及方法
US12449561B2 (en) 2020-12-14 2025-10-21 Saudi Arabian Oil Company Physics-driven deep learning inversion coupled to fluid flow simulators
US11846740B2 (en) 2022-01-31 2023-12-19 Saudi Arabian Oil Company First break picking for full wavefield travel-time inversion
US12517272B2 (en) 2022-12-21 2026-01-06 Saudi Arabian Oil Company Near surface modeling and drilling hazard identification for a subterranean formation
CN116660974B (zh) * 2023-04-11 2024-02-23 中国地震局地球物理研究所 一种基于结构耦合约束的体波和面波三维联合反演方法
CN116520402B (zh) * 2023-06-02 2023-11-28 大连理工大学 岩石半空间场地下考虑体波与面波的多震相波场反演方法
US20250003327A1 (en) * 2023-06-30 2025-01-02 Aramco Services Company Adaptive non-dispersive and direction-dependent attenuation of artifacts in seismic wave propagation
CN116819622B (zh) * 2023-08-30 2023-11-21 北京工业大学 土层三维速度结构的背景噪声水平竖向谱比联合反演方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7330799B2 (en) * 2001-12-21 2008-02-12 Société de commercialisation des produits de la recherche appliquée-Socpra Sciences et Génie s.e.c. Method and algorithm for using surface waves
WO2008029420A1 (fr) 2006-09-04 2008-03-13 Geosystem S.R.L. Procédé de construction de modèles de vitesse pour la migration en profondeur après sommation via l'inversion conjointe, simultanée, de données sismiques, gravimétriques et magnétotelluriques
US9015014B2 (en) * 2007-05-24 2015-04-21 Westerngeco L.L.C. Near surface layer modeling
US20090070042A1 (en) 2007-09-11 2009-03-12 Richard Birchwood Joint inversion of borehole acoustic radial profiles for in situ stresses as well as third-order nonlinear dynamic moduli, linear dynamic elastic moduli, and static elastic moduli in an isotropically stressed reference state
US8509027B2 (en) 2008-11-26 2013-08-13 Westerngeco L.L.C. Continuous adaptive surface wave analysis for three-dimensional seismic data

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11204350B2 (en) 2013-03-15 2021-12-21 Ancera, Llc Systems and methods for bead-based assays in ferrofluids
US11383247B2 (en) 2013-03-15 2022-07-12 Ancera, Llc Systems and methods for active particle separation
US11285490B2 (en) 2015-06-26 2022-03-29 Ancera, Llc Background defocusing and clearing in ferrofluid-based capture assays
US11833526B2 (en) 2015-06-26 2023-12-05 Ancera Inc. Background defocusing and clearing in ferrofluid-based capture assays
CN110687602A (zh) * 2019-10-31 2020-01-14 山东电力工程咨询院有限公司 浅层地震多波联合勘探方法

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