WO2015026997A1 - Calcul d'un gradient sur la base de différences entre plusieurs paires de capteurs de mouvement de particules - Google Patents

Calcul d'un gradient sur la base de différences entre plusieurs paires de capteurs de mouvement de particules Download PDF

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Publication number
WO2015026997A1
WO2015026997A1 PCT/US2014/051971 US2014051971W WO2015026997A1 WO 2015026997 A1 WO2015026997 A1 WO 2015026997A1 US 2014051971 W US2014051971 W US 2014051971W WO 2015026997 A1 WO2015026997 A1 WO 2015026997A1
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WIPO (PCT)
Prior art keywords
motion sensors
particle motion
sensor device
longitudinal axis
plural pairs
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PCT/US2014/051971
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English (en)
Inventor
Nicolas Goujon
Pascal Edme
Artem KASHUBIN
Everhard Johan MIUJZERT
Claudio Bagaini
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Westerngeco Llc
Schlumberger Canada Limited
Westerngeco Seismic Holdings Limited
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Priority claimed from US14/158,193 external-priority patent/US10048395B2/en
Application filed by Westerngeco Llc, Schlumberger Canada Limited, Westerngeco Seismic Holdings Limited filed Critical Westerngeco Llc
Publication of WO2015026997A1 publication Critical patent/WO2015026997A1/fr

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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
    • G01V1/16—Receiving elements for seismic signals; Arrangements or adaptations of receiving elements
    • G01V1/20—Arrangements of receiving elements, e.g. geophone pattern
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P13/00—Indicating or recording presence, absence, or direction, of movement
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/10—Aspects of acoustic signal generation or detection
    • G01V2210/14—Signal detection
    • G01V2210/142—Receiver location
    • G01V2210/1425—Land surface

Definitions

  • Seismic surveying is used for identifying subterranean elements of interest, such as hydrocarbon reservoirs, freshwater aquifers, gas injection zones, and so forth.
  • seismic sources are activated to generate seismic waves directed into a subterranean structure.
  • seismic waves generated by a seismic source travel into the subterranean structure, with a portion of the seismic waves reflected back to the surface for receipt by seismic sensors (e.g., geophones, accelerometers, etc.). These seismic sensors produce signals that represent detected seismic waves. Signals from the seismic sensors are processed to yield information about the content and characteristics of the subterranean structure.
  • seismic sensors e.g., geophones, accelerometers, etc.
  • a land-based seismic survey arrangement can include a deployment of an array of seismic sensors on the ground.
  • a marine survey arrangement can include placing a seabed cable or other arrangement of seismic sensors on the seafloor.
  • a seismic sensor device includes an elongated housing for placement at least partially into an earth surface.
  • a plurality of particle motion sensors are contained in the elongated housing to measure translational data in a first direction, where plural pairs of the particle motion sensors are spaced apart along a second, different direction along a longitudinal axis of the elongated housing.
  • a communication interface communicates the measured translational data to a computer system configured to compute a gradient based on respective differences of the measured translational data of the corresponding plural pairs of the particle motion sensors, and compute one or more of rotation data and divergence data using the gradient.
  • Fig. 1 is a schematic diagram of a sensor device according to some implementations .
  • FIGs. 2A-2C are schematic diagrams of a sensor device according to various implementations .
  • FIGs. 3 and 4 are schematic diagrams of sensor devices according to further implementations .
  • Fig. 5 is a flow diagram of a process according to some implementations.
  • Fig. 6 is a schematic diagram of a sensor device according to other implementations .
  • Fig. 7 is a schematic diagram of an example survey arrangement including sensor devices according to some implementations.
  • seismic sensors are used to measure seismic data, such as displacement, velocity, or acceleration.
  • Seismic sensors can include geophones, accelerometers, microelectromechanical systems (MEMS) sensors, or any other type of sensors that measure translational motion of the surface in one or more directions.
  • MEMS microelectromechanical systems
  • a seismic sensor that measures translational motion is referred to as a particle motion sensor.
  • a particle motion sensor can refer to any of the sensors listed above.
  • An arrangement of particle motion sensors can be provided at (or proximate) a ground surface or earth surface (land surface or bottom surface of a body of water, such as a seafloor) to measure seismic waves reflected from a subterranean structure, in response to seismic waves (or impulses) produced by one or more seismic sources and propagated into an earth subsurface.
  • a particle motion sensor provided at (or proximate) a ground surface can refer to a particle motion sensor that is placed in contact with the ground surface, partially buried in the ground surface, or completely buried in the ground surface up to a predetermined depth (e.g., up to a depth of less than 5 meters).
  • a particle motion sensor at (or proximate) the earth surface can record the vectorial part of an elastic wavefield just below the free surface (i.e., ground surface).
  • rotation data can be combined with translational data measured by particle motion sensors to eliminate or attenuate noise from the measured translational data.
  • noise include ground-roll noise or another type of noise (such as ambient noise) that can travel along the earth' s surface.
  • Ground-roll noise can be produced by a seismic source or other source, such as cars, engines, pumps, and natural phenomena such as wind and ocean waves.
  • the ground-roll noise travels generally horizontally along an earth surface towards seismic receivers.
  • the horizontally traveling seismic waves, such as Rayleigh waves or Love waves, are undesirable components that can contaminate seismic survey data.
  • rotation data can be used for other purposes, whether in the context of a land-based survey acquisition or marine -based survey acquisition in which a seabed cable or other arrangement of seismic sensors is placed on the seafloor.
  • rotation data and translational data can be used in performing various seismic data processing algorithms, including, among others, wavefield interpolation, wavefield extrapolation, wavefield reconstruction, wavefield regularization, P- and S-wave separation, apparent velocity estimation, near-surface characterization, seismic sensor calibration, and seismic imaging.
  • Wavefield interpolation refers to estimating (interpolating) wavefields at locations where seismic sensors are not provided.
  • P- and S-wave separation refers to separating compressional (P) waves from shear (S) waves in measured seismic survey data.
  • Apparent velocity estimation refers to estimating a characteristic of the seismic wavefield known as ray parameter or horizontal slowness, from which seismic wave velocities at various points in a subterranean structure can be retrieved.
  • Near-surface characterization refers to estimating the shallow earth elastic properties.
  • Seismic sensor calibration refers to calibrating a seismic sensor to compensate for any non-ideal characteristic of the seismic sensor.
  • Rotation data refers to a rate of rotation (or change in rotation over time) about a specific axis, such as about the x axis (which can also be referred to as a horizontal inline axis) and/or about the y axis (which can also be referred to as a horizontal crossline axis).
  • rotation data can be derived based on translational data measured by particle motion sensors. In this way, a separate rotational sensor would not have to be provided in survey equipment for the purpose of measuring rotation data.
  • Fig. 1 depicts an example seismic sensor device 100 that includes a first sensor component 102A and a second sensor component 102B.
  • the sensor components 102A and 102B are included inside a single housing 106 of the sensor device 100.
  • the seismic sensor device 100 can also include a power source, such as a battery, a solar cell, and so forth.
  • the housing 106 can be sealed to protect the sensor components 102A and 102B.
  • the housing 106 generally has an elongated shape that allows the sensor components 102A and 102B to be spaced apart along a longitudinal axis 108, by a distance D, of the sensor device 100.
  • the sensor components 102A and 102B are co-axial along the longitudinal axis of the housing 106.
  • the elongated housing 106 can be in the form of a hollow tube, stick, or other elongated structure.
  • the longitudinal axis 108 is the axis along a dimension of the sensor device 100 which is longer than other dimensions of the sensor device 100, such as a width dimension 110 or a depth dimension (not shown) that corresponds to a thickness of the housing 106.
  • the sensor device 100 having the elongated housing 106 can be referred to as a spike-shaped sensor device.
  • the housing 106 can be made out of a material, such as plastic, metal, and so forth. According to an example embodiment, the housing 106 may not resonate within a bandwidth of interest for target signals to be measured. In some examples, the bandwidth of interest can be in the range between 1 to 250 Hertz (Hz). In other examples, the housing 106 may exhibit resonance; in such examples, the resonance can be removed by processing, or the resonance can be compensated for by processing.
  • Hz Hertz
  • the sensor components 102A and 102B are spaced apart along just the longitudinal axis 108.
  • the sensor device 100 does not include sensor components that are spaced apart in any other direction (other than a direction parallel to the longitudinal axis).
  • Fig. 1 shows a portion of the sensor device 100 (not to scale) being below the ground surface 120, and a portion of the sensor device 100 being above the ground surface 120.
  • the configuration can include a sensor 102B below the ground surface and a sensor 102A above the ground surface.
  • a sensor can also be positioned at or proximate the ground surface 120.
  • a majority of the sensor device 100 can be below the ground surface 120.
  • a majority of the sensor device 100 can be above the ground surface 120.
  • Another embodiment can have approximately half the sensor device 100 above and half the sensor device 100 below the ground surface 120.
  • two vertically spaced horizontal orientated particle motion sensors can be provided in the sensor device 100.
  • the sensor device 100 can then be vertically arranged at or near the ground surface 120. It should be understood that additional sensors to 102A and 102B can be located along the length of the sensor device 100 to provide redundancy for failed sensors and/or additional measurements.
  • the sensor device 100 can include a communication interface circuit 101, which is connected to a communications medium 103 (e.g., electrical cable, fiber optic cable, etc.).
  • the communications medium 103 can be a wireless medium over which data can be communicated.
  • the communication interface circuit 101 is connected to the sensor components 102A and 102B. Data acquired by the sensor components 102A and 102B are transferred to the communication interface circuit 101, such as over an electrical, optical, or wireless link.
  • the communication interface circuit 101 in turn transmits the acquired data over the communications medium 103 to a remote station, which can be a recording station, a computer, and so forth.
  • a memory can be provided and incorporated with the sensor device 100.
  • the memory can also be separate from the sensor device 100 and connected by wire, or short range wireless technology such as Wi-Fi or Bluetooth.
  • An arrangement where memory is included can be referred to in the commercial art as a "blind" node arrangement.
  • a communications interface circuit 101 may not have to be present. It should also be appreciated that a combination of a "blind" node arrangement and a wired node and a wireless node arrangement can be used.
  • the sensor device 100 may contain a sensing element (or sensing elements) to measure a tilt and/or an azimuth of the sensor device 100, where tilt is measured with respect to the z axis.
  • This sensing element(s) can be part of the sensor components 102A and 102B that measure translation and rotation.
  • the sensor components 102A and 102B include MEMS accelerometers that measure down to DC, then the MEMS accelerometers can provide tilt data. If the sensor components 102A and 102B include geophones, then a tilt meter can be added.
  • An azimuth sensor e.g., magnetometer, compass
  • measured horizontal components e.g., translational data or rotation data in the x or y axis
  • control circuitry can be included in the sensor device 100 to control the particle motion sensors.
  • an analog-to-digital converter and other components may be included, such as in the communication interface circuit 101, to convert signals measured by the particle motions sensors into digital form.
  • the components in the sensor device 100 may be powered by a battery, a solar panel, or through a wired or wireless connection.
  • the bottom portion of the sensor device 100 may include a spike 112 for driving the sensor device 100 into the ground surface 120.
  • the spike 112 has a generally sharp tip 113 that allows for easier insertion of the sensor device 100 into the ground surface 120 to form a connection between the earth and the sensor device 100.
  • a user or machine can push the spike 112 into the ground surface 120 to cause at least a portion of the sensor device 100 to be buried in the earth beneath the ground surface 120.
  • the sensor device 100 can be driven into the ground surface using a hammer, either by a user or in an automated manner by a machine.
  • the sensor device 100 can be screwed into the ground by a wrench or planted in a prepared borehole with reduced disturbance of the surrounding earth.
  • a borehole may be dug and the sensor device 100 may be placed therein.
  • the borehole may be refilled after positioning the sensor device 100.
  • the housing 106 of the sensor device 100 can have a V or screw shape to facilitate planting into the ground surface 120 (protrusions can be formed on the outer wall of the housing 106 in the form of a helical screw).
  • the sensor device 100 is partially buried beneath the ground surface 120, with a portion of the sensor device 100 protruding above the ground surface 120. In other cases, the sensor device 100 can be completely buried in the ground surface, up to a predetermined depth (as discussed above).
  • Fig. 1 shows the seismic sensor device 100 being arranged vertically, it is noted that in alternative examples, the seismic sensor device 100 can be arranged horizontally (in other words, the seismic sensor device 100 lies on its side).
  • the sensor components 102A and 102B are sensor chips.
  • a sensor chip refers to an integrated circuit device that includes a substrate (e.g., semiconductor substrate) on which particle motion sensors can be provided.
  • the particle motion sensors that can be provided in the sensor chip 102A or 102B can include MEMS particle motion sensors, such as MEMS accelerometers.
  • MEMS particle motion sensor can include a micro element (e.g., a micro cantilever) that is moveable in response to particle motion, where the movement of the micro element can be detected by a sensing element.
  • the sensor components 102A and 102B can include other types of particle motion sensors. It should be noted that the MEMS particle motion sensors do not have to be on the "chip," but that is an option.
  • An example of a MEMS and electronics configuration is disclosed in U.S. Patent Application Publication No. 2013/0315036.
  • the particle motion sensors that are provided in the sensor component 102A or 102B can measure translational data in multiple directions, such as the x, y and z directions. Examples of such arrangements are shown in Figs. 2A and 2B, where the sensor component 102A or 102B includes a respective z sensor 202A or 202B (for measuring translational data along the z axis), a respective x sensor 204A or 204B (for measuring translational data along the x axis), and a respective y sensor 206A or 206B (for measuring translational data along the y axis).
  • the sensor component 102A or 102B can include just a respective x sensor 204A or 204B and a respective y sensor 206A or 206B.
  • a separate z sensor 210 can be provided for measuring translational data along the z direction.
  • the z sensor 210 can be positioned in the middle between sensor components 102A and 102B. In other examples, the z sensor 210 can be positioned elsewhere, such as in either 102A or 102B.
  • a pair of sensors e.g., 204A and 204B, or 206A and 206B, or 202A and 202B
  • the sum can help reduce the non- correlated noise (between the elements of a pair) and the difference provides a gradient.
  • the sensor component 102A can include particle motion sensors to measure in the x, y, and z axes, while the sensor component 102B can include particle motion sensors to measure in just the x and y axes.
  • the particle motion sensors in a given component (e.g., 102A) within the same sensor device 100 do not have to be orientated in the same direction as the other sensor component (e.g., 102B). If the relative angle between the sensor components 102A and 102B is known, then the measured data by the pair of particle motion sensors can be corrected using vector rotation.
  • the gradient - ⁇ represents a spatial derivative of v with respect to the j axis
  • the particle velocity measurements can be made at or just under the ground surface 120 (Fig. 1). At or just under the ground surface 120, the following relationships for deriving rotation data along the x and y axis may apply:
  • a characteristic of providing the sensor device 100 at the ground surface 120 is that a spatial gradient and rotation become equivalent to one another, as expressed by Eq. 2 or 3.
  • a vertical gradient refers to a gradient taken with respect to the z axis.
  • Horizontal translation data refers to translational data along the x or y axis.
  • the foregoing vertical gradients of horizontal translational data can be obtained using measurements of closely spaced apart x sensors 204A and 204B, or closely spaced apart y sensors 206A and 206B.
  • divergence data can also be derived using the translational data, in accordance with further implementations.
  • V ⁇ V The divergence of a wavefield, V ⁇ V, can be represented as:
  • Eq. 4 (x, y, z) represent the three orthogonal axes. At the free surface, Eq. 4 is expressed as:
  • Eq. 5 indicates that, at the free surface, the divergence of a wavefield can be measured by just one partial derivative term
  • the parameters ⁇ and ⁇ are Lame parameters.
  • the partial derivative in the right-hand side of Eqs. 2, 3, and 5 can be measured by differentiating measurements from closely spaced apart particle motion sensors, such as closely spaced apart particle motion sensors depicted in Fig. 1.
  • the particle motion sensors are spaced apart along the longitudinal axis 108 by a distance D that is less than or equal to about 0.3 times a wavelength of a target signal for measurement by the sensor device 100.
  • the particle motion sensors are spaced apart along the longitudinal axis 108 by a distance D that is less than or equal to about 0.1 times a wavelength of a target signal for measurement by the sensor device 100. Note that the foregoing distances D between the particle motion sensors are applicable to computing the rotation data according to Eqs. 2 and 3 and/or the divergence data according to Eq. 5.
  • the particle motion sensors are selected or configured such that the impulse responses of the particle motions sensors within the same sensor device 100 are similar to one other to within a specified threshold difference of one other. This may be achieved by selecting matching pairs of particle motion sensors, or by applying calibration coefficients to measurement data acquired by the particle motion sensors.
  • wavelengths of signals in seismic exploration may be much larger than the spacing between particle motion sensors within a sensor device (such as sensor device 100).
  • a vertical gradient (computed with respect to the z axis) of a horizontal wavefield may not be accurate.
  • the computation of the vertical gradient may be affected by factors such as different sensitivities of the particle motion sensors, electronic noise, and vibrations that affect the particle motion sensors.
  • the different particle motion sensors may be affected differently by vibrations caused by the surrounding mechanical elements of a sensor device.
  • the effect of these perturbations may not be negligible because the difference of the measured signals is expected to be relatively small with respect to the signals themselves.
  • the signal wavelength is 50 meters. In other examples, other signal wavelengths are possible.
  • one or more additional sensor components can be provided in the housing of a seismic sensor device. Combining the measurements of the one or more additional sensor components with the other sensor components, as described further below, can reduce the detrimental effects of perturbations and additive noise on the gradient computed using techniques or mechanisms according to some implementations.
  • providing the additional sensor components in a seismic sensor device may not add too much to the telemetry load relating to communications between the seismic sensor device and another system, since measurements can be combined at the seismic sensor device prior to communicating to the other system. For example, compression can be applied to differences of measured signals as computed at the seismic sensor device, and the compressed differences can be transmitted.
  • the vertical gradient of the x translational data with respect to the z axis can be represented as g ⁇ z .
  • the vertical gradient - ⁇ - of the y translational data with respect to the z axis can be represented as g yZ .
  • the vertical gradient of the x translational data can be approximated (with an accuracy to 0(L) ) with Eq. 7: where L is the vertical distance between sensor components (e.g., shown as D in Fig. 1 between sensor components 102A and 102B), u x (z) is the actual horizontal ground displacement at depth z, and n(z) is the additive noise that takes into account that the actual displacements are different than the measured displacements.
  • the measured displacement at the sensor component 102A is u x (0) + n(0)
  • the measured displacement at the sensor component 102B is u x (L) + n(L).
  • the depth of the shallowest sensor component e.g., 102A in Fig.
  • Eq. 8 highlights how a reduced distance between sensor components can boost the noise.
  • Fig. 3 shows a sensor device 300 according to further implementations, in which an additional sensor component 102C has been added in a housing 301 of the sensor device 300, in addition to the sensor components 102A and 102B that are also contained within the housing 301.
  • Elements of the sensor device 300 that are similar to elements of the sensor device 100 are assigned the same reference numerals.
  • the sensor device 300 can be considered to be an "augmented" sensor device, since it includes additional sensor component(s) than arrangements depicted in Figs. 1 and 2A-2C.
  • the sensor component 102C can include particle motion sensors for measuring translational data in multiple directions, including at least the horizontal directions (x and y), and possibly also the vertical direction (z direction).
  • the additional sensor component 102C is at a distance ⁇ (which can be a relatively small distance) above the sensor component 102B.
  • the computation of the vertical gradient g ⁇ z can be modified and is performed according to Eq. 9 below.
  • the variance (represented by Eq. 10) of the vertical gradient computed according to Eq. 9 is less than the variance (represented by Eq. 8) of the vertical gradient computed according to Eq. 7.
  • u x (L-z) is the actual horizontal ground displacement at the vertical depth (L- ⁇ ) corresponding to the sensor component 102C
  • n(L-z) is the additive noise at the vertical depth (L- ⁇ ).
  • a first gradient is computed based on the translational data measured by a first pair of sensor components (102A, 102B), and a second gradient is computed based on the translational data measured by a second pair of the sensor components 102A, 102C).
  • the gradient g ⁇ z is an aggregate (e.g., average) of the first and second gradients.
  • the vertical distance or spacing between sensor components 102A and 102C is different from the vertical distance between sensor components 102C and 102B. In other examples, the vertical distance between sensor components 102A and 102C is the same as the vertical distance between sensor components 102C and 102B.
  • another augmented sensor device 400 including a different arrangement of sensor components can be used. Elements of the sensor device 400 that are similar to elements of the sensor device 100 are assigned the same reference numerals.
  • the sensor device 400 includes four sensor components 402A, 402B, 402C, and 402D within an elongated housing 401 of the sensor device 400.
  • the sensor components 402A-402D can include similar arrangements of particle motion sensors as depicted for sensor components 102A and 102B in Figs. 2A-2C, in some examples.
  • a center longitudinal axis of the sensor device 400 is represented as 404.
  • the sensor components 402A and 402B are at the same depth, and are placed on either side of the center longitudinal axis 404.
  • the sensor component 402A is on the left of the center longitudinal axis 404, and the sensor component 402A is offset from the center longitudinal axis 404 by -Ax.
  • the sensor component 402B is on the right of the center longitudinal axis 404, and the sensor component 402B is offset from the center longitudinal axis 404 by +Ax.
  • the sensor components 402C and 402D are at the same depth (a different depth than the depth of the sensor components 402A and 402B), and the sensor components 402C and 402D are placed on either side of the center longitudinal axis 404.
  • the sensor component 402C is on the left of the center longitudinal axis 404, and the sensor component 402C is offset from the center longitudinal axis 404 by -Ax.
  • the sensor component 402D is on the right of the center longitudinal axis 404, and the sensor component 402D is offset from the center longitudinal axis 404 by +Ax.
  • the value of Ax is much smaller than the vertical spacing L between the sensor components 402A, B and sensor components 402C, D.
  • the value of Ax can be less than 10% of L.
  • the vertical gradient g ⁇ z can be computed as follows (in which the depth of the sensor components 402A, B is assumed to be 0, and the terms relating to the additive noise have been omitted for simplicity): u x (L,Ax) -u x (0, Ax) u x (L,Ax) - u x (0, -Ax) u x (L,-Ax) -u x (0,Ax) u x (L,-Ax) - u x (0,-Ax) u x (L,-Ax) - u x (0,-Ax)
  • sensor components (402B, 402D, (402A,
  • the same variance of Eq. 12 for the sensor device 400 of Fig. 4 can be obtained by first summing the measured translational data recorded at each depth before performing a gradient computation by taking a difference of the sums.
  • the measured translational data of the sensor components 402A and 402B can be summed (or otherwise aggregated), and the measured translational data of the sensor components 402C and 402D can be summed (or otherwise aggregated).
  • the gradient can be computed based on a difference of the sums divided by the distance (L) between the sensor component pairs.
  • A, B, C and D represent the locations of the sensor components 402A, 402B, 402C and 402D, respectively.
  • W is a weighting matrix (which can be based on a noise covariance matrix that represents the noise experienced by the sensor device 400)
  • u x is a vector of the measured translational data
  • W is multiplied by an identity (I) made up of "l"s.
  • the gradient g %z can be computed according to Eq. 15:
  • the weighting matrix W is the inverse of the noise covariance matrix N. If the noise statistics at the sensor components are uncorrelated, N is diagonal.
  • the elements of the noise covariance matrix can be constant, frequency-dependent or (in the case of non- stationary) time-frequency dependent.
  • the estimation of the noise covariance matrix can be carried out using time windows extracted when the seismic sources are activated.
  • Fig. 5 is a flow diagram of a process according to some implementations. The process receives (at 502) translational data in a first direction (e.g., x or y direction) measured by particle motion sensors contained in an elongated housing of a seismic sensor device (e.g., 300 or 400) provided proximate the earth surface.
  • a first direction e.g., x or y direction
  • a seismic sensor device e.g., 300 or 400
  • Plural pairs of the particle motion sensors are spaced apart along a second, different direction (e.g., z direction) along a longitudinal axis of the elongated housing of the seismic sensor device.
  • the plural pairs of sensors can include a first pair of sensor components 102A and 102B, and a second pair of sensor components 102A and 102C.
  • the plural pairs of sensors can include the following pairs of sensor components: (402B, 402D, (402A, 402D), (402B, 402C), and (402A, 402C).
  • the process computes (at 504) a gradient based on respective differences of the corresponding plural pairs of particle motions sensors.
  • the process then computes (at 506) at least one of a rotation data and divergence data based on the computed gradient, such as according to Eqs. 2, 3, and 5.
  • the estimation of a gradient may also be affected by perturbations due to the vibration of the sensor housing containing the sensor components, and different sensitivities of the sensor components. These perturbations can be approximated with (frequency- and depth-dependent) multiplicative factors.
  • a model of a two-sensor gradient estimation is:
  • the augmented sensor device configurations discussed above can reduce the variance of the estimated gradient in the presence of amplitude perturbations.
  • the representation of perturbations with statistics that do not depend on deployment depth may be used for modeling the different sensitivities of the sensor components.
  • Other perturbations, such as those due to rocking motion of the sensor device may be represented using a different model that depends on the size of the augmented sensor device, the weight distribution of the augmented sensor device, and the frequency of the measured wavefield.
  • the augmented sensor device rotates about a fulcrum (e.g., 113 shown in Fig. 3 or 4) located at the bottom of the augmented sensor device, the amplitude perturbations increase for shallower sensor deployments. This perturbation increase can be taken into account by modeling the amplitude perturbation with a zero-mean random variable whose variance varies with depth as: where ⁇ ⁇ ⁇ is the standard deviation of the amplitude perturbation at depth z
  • Eq. 20 implies that in the case of signals with smaller amplitudes, the dominant term is the additive noise and its variance.
  • the shallowest sensor component can therefore be located as close as possible to the surface (e.g., less than or equal to a depth of 1 centimeter
  • the shallower sensor component can be located at an intermediate location (e.g., between a depth of 1 and 20 cm, for example).
  • the frequency also plays a role in the optimal location of the sensor components. Higher frequencies generate higher angular acceleration. If sensor components for different frequency ranges are used, the lower frequency sensor component can be located closer to the earth surface, whereas the higher frequency sensor components can be located at an intermediate depth.
  • Fig. 6 shows a sensor device 600 according to further implementations.
  • a distributed sensing device 602 is used instead.
  • the distributed sensing device 602 is contained within an elongated housing 601 of the sensor device 600.
  • the distributed sensing device 602 is a continuous sensor that measures translational data continuously along a length of the continuous sensor.
  • the distributed sensing device 602 includes an optical fiber in which optical signals (light) can propagate.
  • the sensor device 600 includes an optical control arrangement 604 that includes a light source 606 and an interrogator 608.
  • the light source 606 emits light (e.g., laser light) into the optical fiber.
  • Backscattered light responsive to the emitted light is received by the interrogator 608.
  • the presence of seismic signals and other signals e.g., noise signals and other perturbations
  • At least one characteristic e.g., strain
  • the continuous measurements (including measured translational data) at various points along the optical fiber can be communicated by a communication interface 610 (which is part of the control arrangement 604) over the communication medium 103.
  • the measured optical signals (as acquired by the interrogator 608) can be communicated as optical signals over the communication medium.
  • the measured optical signals can be converted into electrical format for communication as electrical signals over the communication medium 103.
  • a gradient can be computed based on respective differences of corresponding plural pairs of the measurements, in similar fashion as described above in connection with Eqs. 9 and 11.
  • One or more of rotation data and divergence data can be computed using the gradient.
  • the computation of the gradient can be performed by a processor in the control arrangement 604, in some implementations.
  • the gradient is computed by a computer system that is remotely located from the sensor device.
  • Fig. 7 is a schematic diagram of a land-based survey arrangement (including a seismic sensor system) that includes sensor devices 700 (e.g., 100, 300, 400, or 600) according to some implementations.
  • the sensor devices 700 can be deployed in a marine survey arrangement.
  • Measurements acquired by the sensor devices 700 are transmitted to a computer system 701, where the measurements are recorded (stored in a storage medium or storage media 710).
  • each sensor device 700 (or at least one of the sensor devices 700) can include the computer system 701, or at least one or more processors 708 and storage medium (or storage media) 710.
  • the measurements are made by the sensor devices 700 in response to seismic waves produced by one or more seismic sources (not shown).
  • the seismic waves are propagated into a subterranean structure 702, and reflected from a subterranean element 704 of interest.
  • the reflected waves are detected by the sensor devices 700.
  • the computer system 701 includes a rotation and divergence data computation module 706, which can be implemented with machine-readable instructions that are executable on one or more processors 708.
  • a processor can include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.
  • the rotation and divergence data computation module 706 can compute rotation data and divergence data as discussed above.
  • the processor(s) 708 can be coupled to the storage medium (or storage media) 710, which can store data, such as translational data received from the sensor devices 700.
  • the storage medium (or storage media) 710 can be implemented as one or more computer-readable or machine-readable storage media.
  • the storage media include 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.
  • DRAMs or SRAMs dynamic or static random access memories
  • EPROMs erasable and programmable read-only memories
  • EEPROMs electrically erasable and programmable read-only memories
  • flash memories magnetic disks such as fixed, floppy
  • the instructions discussed above can be provided on one computer-readable or machine-readable storage medium, or alternatively, can be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes.
  • Such computer-readable or machine-readable storage medium or media is (are) 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.

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  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Environmental & Geological Engineering (AREA)
  • Geology (AREA)
  • Remote Sensing (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Geophysics (AREA)
  • Geophysics And Detection Of Objects (AREA)

Abstract

La présente invention concerne un dispositif de capteur sismique comprenant un logement allongé pouvant être installé au moins en partie dans une surface de la terre. Une pluralité de capteurs de mouvement de particules est contenue dans le logement allongé pour mesurer des données de translation dans une première direction, plusieurs paires des capteurs de mouvement de particules étant espacées le long d'une seconde direction, différente, le long d'un axe longitudinal du logement allongé. Une interface de communication communique les données de translation mesurées à un système informatique configuré pour calculer un gradient sur la base des différences respectives des données de translation mesurées des plusieurs paires correspondantes des capteurs de mouvement de particules, et calculer une ou plusieurs données de rotation et données de divergence en utilisant le gradient.
PCT/US2014/051971 2013-08-21 2014-08-21 Calcul d'un gradient sur la base de différences entre plusieurs paires de capteurs de mouvement de particules WO2015026997A1 (fr)

Applications Claiming Priority (4)

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US201361868429P 2013-08-21 2013-08-21
US61/868,429 2013-08-21
US14/158,193 US10048395B2 (en) 2013-02-01 2014-01-17 Computing a gradient based on differences of plural pairs of particle motion sensors
US14/158,193 2014-01-17

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11822032B2 (en) * 2018-11-08 2023-11-21 Baker Hughes, A Ge Company, Llc Casing wall thickness detection from higher order shear-horizontal mode signals

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070265786A1 (en) * 2006-05-11 2007-11-15 Ozdemir Ahmet K Method and apparatus for marine seismic data acquisition
US20080049551A1 (en) * 2006-07-12 2008-02-28 Everhard Johan Muyzert Workflow for processing streamer seismic data
US20100195439A1 (en) * 2009-02-05 2010-08-05 Everhard Muyzert Seismic acquisition system and technique
EP2293116A2 (fr) * 2009-08-27 2011-03-09 PGS Geophysical AS Regroupement de capteur pour flûte sismique marine à double capteur et procédé d'étude sismique

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070265786A1 (en) * 2006-05-11 2007-11-15 Ozdemir Ahmet K Method and apparatus for marine seismic data acquisition
US20080049551A1 (en) * 2006-07-12 2008-02-28 Everhard Johan Muyzert Workflow for processing streamer seismic data
US20100195439A1 (en) * 2009-02-05 2010-08-05 Everhard Muyzert Seismic acquisition system and technique
EP2293116A2 (fr) * 2009-08-27 2011-03-09 PGS Geophysical AS Regroupement de capteur pour flûte sismique marine à double capteur et procédé d'étude sismique

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11822032B2 (en) * 2018-11-08 2023-11-21 Baker Hughes, A Ge Company, Llc Casing wall thickness detection from higher order shear-horizontal mode signals

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