WO2018013390A1 - Procédé permettant de déterminer des profondeurs de capteurs et de contrôler la qualité de profondeurs de capteurs pour le traitement des données sismiques - Google Patents

Procédé permettant de déterminer des profondeurs de capteurs et de contrôler la qualité de profondeurs de capteurs pour le traitement des données sismiques Download PDF

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Publication number
WO2018013390A1
WO2018013390A1 PCT/US2017/040785 US2017040785W WO2018013390A1 WO 2018013390 A1 WO2018013390 A1 WO 2018013390A1 US 2017040785 W US2017040785 W US 2017040785W WO 2018013390 A1 WO2018013390 A1 WO 2018013390A1
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WO
WIPO (PCT)
Prior art keywords
seismic
depth
sensor
depths
measurements
Prior art date
Application number
PCT/US2017/040785
Other languages
English (en)
Inventor
Gary Hampson
Original Assignee
Downunder Geosolutions (America) Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Downunder Geosolutions (America) Llc filed Critical Downunder Geosolutions (America) Llc
Priority to MYPI2019000348A priority Critical patent/MY197512A/en
Priority to AU2017295827A priority patent/AU2017295827B2/en
Priority to GB1902042.9A priority patent/GB2567381B/en
Publication of WO2018013390A1 publication Critical patent/WO2018013390A1/fr
Priority to US16/243,496 priority patent/US11385373B2/en

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • 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. analysis, for interpretation, for correction
    • G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
    • G01V1/364—Seismic filtering
    • G01V1/366—Seismic filtering by correlation of seismic signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/38—Seismology; Seismic or acoustic prospecting or detecting specially adapted for water-covered areas
    • G01V1/3817—Positioning of seismic devices
    • G01V1/3835—Positioning of seismic devices measuring position, e.g. by GPS or acoustically
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/50—Corrections or adjustments related to wave propagation
    • G01V2210/56—De-ghosting; Reverberation compensation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/67—Wave propagation modeling
    • G01V2210/679—Reverse-time modeling or coalescence modelling, i.e. starting from receivers

Definitions

  • This disclosure relates to the field of seismic surveying. More specifically the disclosure relates to seismic surveying for the purpose of geophysical exploration.
  • Geophysical exploration for and exploitation of subsurface hydrocarbon reserves includes reflection seismic surveying.
  • Reflection seismic surveys can be acquired both onshore (land) and offshore (marine).
  • the Earth's surface (land or water) that is in contact with the air is hereinafter referred to as the "free-surface".
  • a seismic source or sources typically one or more air gun arrays, may also towed directly behind the boat or by another vessel, also at a selected depth below the free-surface.
  • the seismic source when actuated generates an acoustic signal that propagates through the water column (the distance in the water between the free-surface and the water bottom) and into the geological strata (formations) below the water bottom.
  • the acoustic signal is refracted and reflected by acoustic impedance boundaries, e.g., at boundaries between the various formation layers, travelling back upwardly where it is ultimately detected by the sensors or sensor arrays in the streamer.
  • a linear array of sensors may include a selected number of seismic sensors spaced apart from each other at a relatively small distance (e.g., 1 ⁇ 4 of the shortest wavelength of seismic energy detected in the acoustic signal) and the output of such sensors may be combined electrically or otherwise to produce a single detected signal that has reduced effects of horizontally propagating noise.
  • the seismic source is typically actuated at selected time intervals (each actuation being called a "shot") as the boat travels along a survey line or "sail line.”
  • shots Each sensor or array of sensors detects upwardly traveling (i.e., reflected and/or refracted) signals and the detected signals are recorded with respect to time.
  • the recording time may be referenced or indexed, e.g., to the actuation time of the seismic source.
  • Such signal recording produces a single seismic "trace” for each sensor or array of sensors.
  • a collection of recorded traces from all sensors or sensor arrays along a single streamer is called a shot record.
  • a seismic survey is made up of a plurality of shot records recorded along a single sail line or many parallel sail lines covering a selected area of the subsurface.
  • Raw (pre-stack) shot records undergo sophisticated processing in order to create a final (post-stack) seismic volume for interpretation of geophysical characteristics of the subsurface formations.
  • An objective of seismic surveying is to record the response of the earth to imparted seismic signals.
  • Vertical resolution is related to bandwidth, or the range of frequencies that are present in the detected seismic signals.
  • Many parameters related to the acquisition and the physics of the propagating acoustic signal act to limit the bandwidth that can be detected by the sensors and recorded.
  • a well-known factor that limits bandwidth in marine seismic acquisition relates to reflections from the free-surface. Acoustic signals travelling upwardly in the water layer will be reflected with opposite polarity from the free-surface. Such reflected signals are termed “ghost” reflections.
  • the sensors in the streamer record, for each shot, not only the desired "primary reflection” wave field, i.e., a single, upwardly traveling wave field representing reflections of the original seismic signal from subsurface acoustic impedance boundaries, but also the ghost reflections.
  • ghost reflections destructively interfere with the primary reflection of interest resulting in "notches" in the spectrum of the detected acoustic signal at particular frequencies. These notches limit the useable bandwidth of the seismic data and are thus undesirable.
  • Methods known in the art for reducing the effect of ghost reflections are termed "deghosting.”
  • Deterministic deghosting methods known in the art require an accurate description of the reflectivity function of the free-surface and require accurate knowledge of the source and sensor depths. Methods to check the quality of determined sensor depths are therefore desired.
  • FIG. 1 shows an example of marine seismic data acquisition.
  • FIG. 2 shows extrapolated up-going and down-going wavefields.
  • FIG. 3 shows one way in which the up-going wavefield may be upwardly continued and depicts its coincidence with the down-going wavefield of unprocessed measured seismic data.
  • the scan may be performed in discrete increments of depth.
  • FIG. 5 shows a shot record used for an example embodiment of a method according to the present disclosure.
  • FIG. 6 shows the amplitude spectrum of the /-x-transform of the data record in
  • FIG. 5 is a diagrammatic representation of FIG. 5.
  • FIG. 7 shows the result of performing the wave equation autocorrelation. Positive lags from 0 - 26 meters sensor depth equivalent are displayed.
  • FIG. 8 shows the k ⁇ x spectrum of the autocorrelation.
  • FIG. 9 shows a flow chart of an example implementation of a method according to the present disclosure.
  • FIG. 10 shows an example computer system that may be used in some embodiments.
  • FIG. 1 shows an example of a system and method for acquiring marine seismic data that can be used with methods according to the present disclosure.
  • a seismic vessel 101 moves along the surface 108 of a body of water 102 above a portion 103 of the subsurface that is to be surveyed. Beneath the water bottom 104, a portion 103 of the subsurface contains formations of interest such as a layer 105 positioned between an upper boundary 106 and lower boundary 107 thereof.
  • the seismic vessel 101 contains seismic acquisition control equipment, designated generally at 109.
  • the seismic acquisition control equipment 109 includes navigation control, seismic energy source control, seismic sensor control, and signal recording equipment, all of which can be of types well known in the art.
  • the seismic acquisition control equipment 109 causes a seismic source 110 towed in the body of water 102 by the seismic vessel 101 (or by a different vessel) to actuate at selected times.
  • the seismic source 110 may be of any type well known in the art of seismic acquisition, including air guns or water guns, or particularly, arrays of air guns.
  • Seismic streamers 111 are also towed in the body of water 102 by the seismic vessel 101 (or by a different vessel) to detect the acoustic wave fields initiated by the seismic source 110 and reflected from interfaces in the environment. Although only one seismic streamer 111 is shown in FIG. 1 for illustrative purposes, typically a plurality of laterally spaced apart seismic streamers 111 are towed behind the seismic vessel 101.
  • the seismic streamers 111 contain sensors to detect the reflected wave fields initiated by the seismic source 110.
  • the seismic streamers 111 contain pressure responsive sensors such as hydrophones 112.
  • the hydrophones 112 are typically disposed in multiple sensor arrays at regular intervals along the seismic streamers 111.
  • the type of sensors and their particular locations along the seismic streamers 111 are not intended to be limitations on the present disclosure.
  • an acoustic wave field travels in spherically expanding wave fronts.
  • the propagation of the wave fronts will be illustrated herein by ray paths which are perpendicular to the wave fronts.
  • An upwardly traveling wave field designated by ray path 114, will reflect off the free-surface 108 and then travel downwardly, as in ray path 115, where the wave field may be detected by the hydrophones 112 in the seismic streamers 111.
  • Such a reflection from the free-surface 108, as in ray path 115 contains no useful information about the subsurface formations of interest.
  • free-surface reflections also known as ghosts, act as secondary seismic sources with a time delay from initiation of the seismic source 110.
  • the downwardly traveling wave field, in ray path 116, will reflect off the earth- water interface at the water bottom 104 and then travel upwardly, as in ray path 117, where the wave field may be detected by the hydrophones 112.
  • a reflection at the water bottom 104, as in ray path 117, contains information about the water bottom 104.
  • Ray path 117 is an example of a "primary" reflection, that is, a reflection originating from a boundary in the subsurface.
  • the downwardly traveling wave field, as in ray path 116, may transmit through the water bottom 104 as in ray path 118, reflect off a layer boundary, such as 107, of a layer, such as 105, and then travel upwardly, as in ray path 119.
  • the upwardly traveling wave field, ray path 119 may then be detected by the hydrophones 112.
  • Such a reflection off a layer boundary 107 contains useful information about a formation of interest 105 and is also an example of a primary reflection.
  • the acoustic wave fields will continue to reflect off interfaces such as the water bottom 104, free-surface 108, and layer boundaries 106, 107 in combinations.
  • the upwardly traveling wave field in ray path 117 will reflect off the free- surface 108, continue traveling downwardly in ray path 120, may reflect off the water bottom 104, and continue traveling upwardly again in ray path 121, where the wave field may be detected by the hydrophones 112.
  • Ray path 121 is an example of a multiple reflection, also called simply a "multiple", having multiple reflections from interfaces.
  • the upwardly traveling wave field in ray path 119 will reflect off the free- surface 108, continue traveling downwardly in ray path 122.
  • Such reflected energy as in ray path 122 may be detected by one or more of the hydrophones 112, thus creating a ghost referred to as a "sensor side ghost", the effects of which on the desired seismic signal are similar in nature to the previously described ghost.
  • the seismic energy may reflect off a layer boundary 106 and continue traveling upwardly again in ray path 123, where the wave field may be detected by the hydrophones 112.
  • Ray path 123 is another example of a multiple reflection, also having multiple reflections in the subsurface.
  • One or more seismic energy sources may be disposed at the surface, or, for example, in one or more wellbores drilled to a selected depth below the free-surface.
  • the seismic sensors may be buried at a selected depth below the free-surface, or may be deployed in one or more spaced apart wellbores at selected depths or within a selected range of depths below the free-surface.
  • W +Zy is a one way wave extrapolator to downward extrapolate an up- going wavefield across the depth interval 0— » z r and the symbol * denotes convolution in
  • Eq. (1) is a depth extrapolation of a time-dependent scalar wavefield.
  • the foregoing operator reduces the time of seismic events in a wave-consistent manner.
  • W ⁇ Zr is an upward extrapolation of an up-going wavefield across the depth interval 0— » z_ r .
  • the foregoing operator of Eq. (2) increases the times of seismic events in a wave consistent manner.
  • the operators W +Zy and W ⁇ Zy may be referred to as redatuming operators or wave extrapolation operators.
  • the foregoing redatuming operators may be expressed in one, two or three dimensions (ID, 2D or 3D).
  • ID the wave extrapolation operators represent values of time delay.
  • 2D and 3D the operators represent plane-wave dependent time delays.
  • the foregoing redatuming operators may be applied in a variety of domains, each with corresponding advantages and disadvantages.
  • Eq. (3) may be rewritten in the discrete notation of linear algebra, where upper case bold symbols represent matrices and lower case bold symbols denote column vectors:
  • FIG. 3 shows one way in which the up-going wavefield may be upwardly continued and depicts its coincidence with the down-going wavefield of unprocessed measured seismic data.
  • each seismic sensor or sensor array may be digitized, i.e., converted to a set of number pairs wherein one number represents the time (usually indexed to the actuation time of the source) and the other represents signal amplitude.
  • correlation troughs may be picked or determined to very high precision.
  • the wave equation based autocorrelation may also be Fourier transformed to the wavenumber-offset domain k z , x and the locations of the notches directly observed at each offset.
  • the correlation may be used to detect z r by picking the correlation trough location. If suitable digital sampling has been used in the construction of the autocorrelation, then the correlation trough may be located to arbitrarily high precision using appropriate interpolation methods, including, but not limited to, interpolation by trigonometric methods. The detection of z r is shown later in an example.
  • autocorrelation may be used to detect how well a particular set of deghosting parameters has performed. Negative correlation of the ghost should ideally be perfectly removed by deghosting. Metrics that may be used on the autocorrelation to detect how well the deghosting has been performed include, without limitation:
  • Using one or more metrics on the autocorrelation enables a range of parameters to be used as input and the results evaluated.
  • the first three example metrics listed above typically require minimizing the parameter value or a cost function based on the parameter value, while the Kurtosis requires maximising.
  • One or a mixture of these metrics may be used.
  • the depth samples in the depth scan are fine (closely spaced) enough to satisfy sampling theory, but not so fine as to create more computational burden than is necessary.
  • FIG. 5 shows a shot record used for an example embodiment of a method according to the present disclosure.
  • the seismic sensors (FIG. 1) are nominally disposed at a depth of 15 meters.
  • the amplitude spectrum of the /-x-transform of the data record in FIG. 5 is shown in FIG. 6 where the ghost notches are quite clearly observable but they change with offset and dip.
  • FIG. 7 shows the result of performing the wave equation autocorrelation. Positive lags from 0 - 26 meters sensor depth equivalent are displayed.
  • the sensor depths taken from the trace headers are plotted as discrete points indicated by numeral 140.
  • the locations of the troughs' minima are also shows as discrete points at reference numeral 142. It may be interpreted that fluctuations in the trough picks relates to fluctuations in the height of the free-surface.
  • FIG. 8 shows the k z -x spectrum of the autocorrelation. The locations of the notches from the headers are shown at the top of the figure. The locations picked from the autocorrelation are shown at 144 and 146. There appears to be good notch representation determined in the k z -x domain. FIG. 8 may also be compared to FIG. 6 to illustrate the absence of the effects of dip in the present example method.
  • FIG. 9 shows a flow chart of an example embodiment of sensor depth determination according to the present disclosure.
  • acquired data may be input to a computer or computer system (see FIG. 10).
  • the input data may include measured seismic data (FIG. 1), observers' logs from the seismic survey, measurement(s) of the water acoustic velocity and measurement(s) of seismic sensor depths.
  • Seismic sensor depths may be measured, for example using a pressure sensor associated with each seismic sensor, or in the case where the seismic sensors (112 in FIG. 1) are absolute pressure hydrophones rather than pressure time gradient hydrophones, the DC component of the seismic sensor measurements may be used to measure sensor depth.
  • a range of seismic sensor depths over which to perform the correlation analysis based upon an expected range of sensor depths may be defined.
  • the depth lag sample interval for the extrapolation depth increment may be defined so as to properly satisfy sampling theory.
  • the range of sensor depths may be estimated based on, for example, measurements of sensor depths made using, e.g., pressure sensors, or depths to which the streamers are moved using lateral force and depth (LFD) control devices coupled into the streamers.
  • LFD lateral force and depth
  • the depth extrapolation of the input seismic data to each depth lag of interest i.e., to each depth in the range of depths defined at 132 is performed.
  • the correlation or other measure of similarity between the extrapolated data and the input seismic data is calculated for each depth at each sensor within the defined range of depths. Then the correlation extrema and their associated depth lags are automatically selected by the computer or computer system.
  • the depths determined by correlation extrema (at 134) may be used in to quality check the results of the depths input at 130, for example, measured depths.
  • the wave equation autocorrelation could be used to match primary reflections to multiple reflections.
  • the method may also be used to perform trim adjustments to a given multiple model in order to optimize them for further processing.
  • FIG. 10 shows an example computing system 200 in accordance with some embodiments.
  • the computing system 200 may be an individual computer system 201A or an arrangement of distributed computer systems.
  • the individual computer system 201A may include one or more analysis modules 202 that may be configured to perform various tasks according to some embodiments, such as the tasks explained with reference to FIGS 2-9. To perform these various tasks, the analysis module 202 may operate independently or in coordination with one or more processors 204, which may be connected to one or more storage media 206.
  • a display device 205 such as a graphic user interface of any known type may be in signal communication with the processor 204 to enable user entry of commands and/or data and to display results of execution of a set of instructions according to the present disclosure.
  • the processor(s) 204 may also be connected to a network interface 208 to allow the individual computer system 201 A to communicate over a data network 210 with one or more additional individual computer systems and/or computing systems, such as 20 IB, 201C, and/or 20 ID (note that computer systems 20 IB, 201C and/or 20 ID may or may not share the same architecture as computer system 201 A, and may be located in different physical locations, for example, computer systems 201A and 201B may be at a well drilling location, while in communication with one or more computer systems such as 201C and/or 20 ID that may be located in one or more data centers on shore, aboard ships, and/or located in varying countries on different continents).
  • 20 IB, 201C, and/or 20 ID may or may not share the same architecture as computer system 201 A, and may be located in different physical locations, for example, computer systems 201A and 201B may be at a well drilling location, while in communication with one or more computer systems such as 201C and/or 20 ID
  • a processor may include, without limitation, a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.
  • the storage media 206 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of FIG. 10 the storage media 206 are shown as being disposed within the individual computer system 201A, in some embodiments, the storage media 206 may be distributed within and/or across multiple internal and/or external enclosures of the individual computing system 201A and/or additional computing systems, e.g., 201B, 201C, 201D.
  • Storage media 106 may include, without limitation, one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories; magnetic disks such as fixed, floppy and removable disks; other magnetic media including tape; optical media such as compact disks (CDs) or digital video disks (DVDs); or other types of storage devices.
  • semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories
  • magnetic disks such as fixed, floppy and removable disks
  • optical media such as compact disks (CDs) or digital video disks (DVDs); or other types of storage devices.
  • computer instructions to cause any individual computer system or a computing system to perform the tasks described above may be provided on one computer-readable or machine-readable storage medium, or may be provided on multiple computer-readable or machine-readable storage media distributed in a multiple component computing system having one or more nodes.
  • Such computer-readable or machine-readable storage medium or media may be considered to be part of an article (or article of manufacture).
  • An article or article of manufacture can refer to any manufactured single component or multiple components.
  • the storage medium or media can be located either in the machine running the machine- readable instructions, or located at a remote site from which machine-readable instructions can be downloaded over a network for execution.
  • computing system 200 is only one example of a computing system, and that any other embodiment of a computing system may have more or fewer components than shown, may combine additional components not shown in the example embodiment of FIG. 10, and/or the computing system 200 may have a different configuration or arrangement of the components shown in FIG. 10.
  • the various components shown in FIG. 10 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits.
  • the acts of the processing methods described above may be implemented by running one or more functional modules in information processing apparatus such as general purpose processors or application specific chips, such as ASICs, FPGAs, PLDs, GPUs, coprocessers or other appropriate devices. These modules, combinations of these modules, and/or their combination with general hardware are all included within the scope of the present disclosure.

Abstract

L'invention concerne un procédé permettant de déterminer des profondeurs de capteurs sismiques dans un corps d'eau. Le procédé consiste à accepter, en tant qu'entrée, des mesures informatiques de signaux sismiques prises par une pluralité de capteurs sismiques placés dans un corps d'eau. Un incrément de profondeur et une plage de profondeurs de capteurs sont définis pour corréler des signaux provenant de chacun de la pluralité de capteurs sismiques. Dans l'ordinateur, les mesures sismiques d'entrée sont extrapolées à chaque incrément de profondeur de la plage. Une profondeur de chaque capteur sismique est déterminée en corrélant les mesures de signaux sismiques avec des mesures extrapolées en profondeur des mesures de signaux sismiques.
PCT/US2017/040785 2016-07-11 2017-07-06 Procédé permettant de déterminer des profondeurs de capteurs et de contrôler la qualité de profondeurs de capteurs pour le traitement des données sismiques WO2018013390A1 (fr)

Priority Applications (4)

Application Number Priority Date Filing Date Title
MYPI2019000348A MY197512A (en) 2016-07-11 2017-07-06 Method for determining sensor depths and quality control of sensor depths for seismic data processing
AU2017295827A AU2017295827B2 (en) 2016-07-11 2017-07-06 Method for determining sensor depths and quality control of sensor depths for seismic data processing
GB1902042.9A GB2567381B (en) 2016-07-11 2017-07-06 Method for determing sensor depths and quality control of sensor depths for seismic data processing
US16/243,496 US11385373B2 (en) 2016-07-11 2019-01-09 Method for determining sensor depths and quality control of sensor depths for seismic data processing

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201662360665P 2016-07-11 2016-07-11
US62/360,665 2016-07-11

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100135113A1 (en) * 2008-12-03 2010-06-03 Guillaume Cambois Method for determining signal quality in dual sensor seismic streamer signals
US20100211321A1 (en) * 2009-02-13 2010-08-19 Ahmet Kemal Ozdemir Deghosting and reconstructing a seismic wavefield
US20130028049A1 (en) * 2011-07-25 2013-01-31 Naide Pan Method for handling rough sea and irregular recording conditions in multi-sensor towed streamer data
US20130322208A1 (en) * 2012-05-31 2013-12-05 Pgs Geophysical As Methods and systems for imaging subterranean formations with primary and multiple reflections
US20160139283A1 (en) * 2013-06-25 2016-05-19 Westerngeco L.L.C. Seismic wavefield deghosting and noise attenuation

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10317553B2 (en) * 2014-08-13 2019-06-11 Pgs Geophysical As Methods and systems of wavefield separation applied to near-continuously recorded wavefields

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100135113A1 (en) * 2008-12-03 2010-06-03 Guillaume Cambois Method for determining signal quality in dual sensor seismic streamer signals
US20100211321A1 (en) * 2009-02-13 2010-08-19 Ahmet Kemal Ozdemir Deghosting and reconstructing a seismic wavefield
US20130028049A1 (en) * 2011-07-25 2013-01-31 Naide Pan Method for handling rough sea and irregular recording conditions in multi-sensor towed streamer data
US20130322208A1 (en) * 2012-05-31 2013-12-05 Pgs Geophysical As Methods and systems for imaging subterranean formations with primary and multiple reflections
US20160139283A1 (en) * 2013-06-25 2016-05-19 Westerngeco L.L.C. Seismic wavefield deghosting and noise attenuation

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GB2567381B (en) 2021-12-01
GB2567381A (en) 2019-04-10
AU2017295827B2 (en) 2020-11-05
MY197512A (en) 2023-06-19
GB201902042D0 (en) 2019-04-03
AU2017295827A1 (en) 2019-02-28

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