This invention relates to methods and systems for accurately estimating the speed and depth of an inspection tool within a pipe or conduit using an imaging device on the inspection tool. In particular, this technology applies to the real-time or post-processing of downhole images from surface or subsurface pipes in the oil and gas industry.
It is common practice in the oil and gas industry to make measurements of formation properties (‘Open Hole’) or pipe components (‘Cased Hole’) by lowering instruments down the well on cables or coiled tubing. The depth location of the objects being investigated is commonly estimated by determining the length of cable or tubing spooled into the hole.
Due to stretch of the cable or coiled tubing and variations in friction throughout the whole system, this depth estimate is often inaccurate.
It is also possible to estimate the depth of a tool by using data obtained from sensors such as accelerometers or head tension devices, which can provide information on the behaviour of the tool itself rather than the cable or coiled tubing. While the data from such sensors can be used to estimate the change in position of a tool over a relatively short distance, the accuracy of this approach tends to decrease with increasing distance.
Against that background, it would be desirable to provide methods and systems for estimating the velocity and depth of a downhole tool that offer increased accuracy compared to known methods and systems.
The methods and systems of the present invention provide a means to correct surface measurements of depth and tool speed which are prone to errors, for example from stretch of the cable or coiled tubing supporting the inspection tool or due to friction between the tool and the conduit causing stick/slip behaviour. The measurements obtained by the methods and systems of the present invention can provide precise depth locations of downhole components and pipe or conduit anomalies which may be used during production optimisation and for planning well interventions.
From a first aspect, the present invention provides a method for determining a corrected axial displacement parameter of a conduit inspection tool having an imaging device. The method comprises:
With this method, a corrected axial displacement parameter such as a displacement distance or velocity of the tool is obtained that has improved accuracy compared to prior art methods. In particular, by combining data derived from the images obtained by the tool and a displacement estimate derived from a different source, the corrected displacement parameter of the tool captures high-frequency changes in velocity due to friction between the tool and the conduit whilst remaining consistent with the displacement measured between the reference points.
The tool may be attached to a control module with a connecting line. In this case, determining the estimated axial displacement distance of the tool may comprise making a displacement measurement of the connecting line at the control module. The estimated axial displacement distance of the tool may be taken as the displacement distance of the connecting line or, alternatively, determining the estimated axial displacement distance of the tool may comprise determining, from the displacement measurement of the connecting line, an estimated axial velocity of the tool as a function of transit time and integrating the estimated axial velocity with respect to time over the interval of transit time.
In cases where the spacing between the reference features is known, the estimated axial displacement distance of the tool can be taken to equal a known spacing distance between the corresponding reference features.
In one embodiment, the displacement parameter is a velocity, and the total axial displacement distance of the tool within the interval of transit time is determined by integrating the corrected axial velocity with respect to time over the interval of transit time.
The observed axial velocity of the tool may be determined in units of image pixels per unit time. The method may comprise converting the observed axial velocity to units of distance per unit time before computing the corrected axial velocity of the tool. In an alternative approach, when the observed axial velocity of the tool is determined in units of image pixels per unit time, a conversion from pixels per unit time to distance per unit time can be incorporated into the correction factor. The correction factor may therefore have units of distance per unit pixel. With this approach, it is not necessary determine a conversion factor to convert the observed axial velocity to units of distance per unit time before computing the corrected axial velocity of the tool.
When the displacement parameter is velocity, the method may further comprise integrating the corrected axial velocity with respect to time to determine a corrected displacement distance of the tool as a function of time.
In another embodiment, the displacement parameter is a displacement distance. In this case, the total axial displacement distance of the tool within the interval of transit time can be determined as the difference in corrected axial displacement distance over the interval.
The observed axial displacement distance of the tool may be determined in units of image pixels. The method may comprise converting the observed axial displacement distance to units of distance by applying a conversion factor to the observed axial displacement distance before computing the corrected axial displacement distance of the tool. Alternatively, a conversion from pixels to distance units can be incorporated into the correction factor.
When a conversion factor for converting pixels to distance units is required, in some embodiments, the method may comprise disposing a reference marker of known dimension on or against the internal wall of the conduit within a field of view of the camera such that the reference marker is visible in one or more of the obtained images, identifying the reference marker in an image corresponding to a transit time, determining the number of image pixels occupied by the known dimension of the reference marker, and determining the conversion factor for that transit time based on the determined number of image pixels and the known dimension of the reference marker. The marker may be a physical member or a visual marker projected from the tool. The reference marker may be a blade or other structure of known width, where the width dimension of the reference marker extends circumferentially with respect to the conduit. Preferably, the tool comprises the reference marker.
The tool may comprise a further sensor offset axially with respect to the imaging device.
The method may then comprise determining a corrected displacement position of the further sensor by applying an axial offset to the corrected displacement distance of the tool.
The correction factor may be constant within each interval of transit time between successive reference points. Alternatively, the correction factor may vary according to the internal diameter of the conduit within each interval of transit time. For example, the method may comprise measuring the internal diameter of the conduit as a function of transit time, and the correction factor may vary within each interval of transit time as a function of the measured internal diameter. The internal diameter of the conduit is preferably measured during transit of the tool, for example with a suitable measuring device carried on the tool.
The imaging device preferably comprises a sideview camera arranged such that a centreline of the field of view of the camera is substantially perpendicular to a longitudinal axis of the inspection tool. The imaging device may comprise a plurality of such sideview cameras, arranged such that a centreline of the field of view of each of the cameras lies in a common plane. In another embodiment, the imaging device comprises a downview camera arranged such that a centreline of the field of view of the camera is substantially parallel to a longitudinal axis of the inspection tool.
The corrected axial displacement parameter determined by the method of the invention may be useful in interpreting the image data obtained by the imaging device and/or data from other sensors. In particular, the corrected axial velocity or corrected axial displacement distance can be used to obtain accurate values for the depth or position of images or other data points obtained during inspection.
A second aspect of the invention resides in a conduit inspection system comprising:
The conduit inspection system may comprise a control module and a connecting line attached to the imaging device, the control module being arranged to control movement of the connecting line to transit the tool axially along a conduit. In this case, the computer system may be arranged to determine the estimated axial displacement parameter of the tool by making a displacement measurement of the connecting line at the control module.
The imaging device may comprise one or more sideview cameras. Alternatively, or in addition, the imaging device may comprise a downview camera.
The inspection tool may comprise a reference marker of known dimension arranged to contact or lie on the internal wall of the conduit within a field of view of the camera, such that the reference marker is visible in one or more of the obtained images. The computer system may be arranged to:
The computer system may be disposed in whole or in part in the inspection tool, in the control module, and/or in one or more further modules of the system. The computer system may be configured to perform the method of the first aspect of the invention.
Preferred and/or optional steps and features of each aspect of the invention may also be used, alone or in appropriate combination, in the other aspects also.
Embodiments of the present invention will now be described with reference to the accompanying drawings, in which like reference signs are used for like features, and in which:
The tool 10 is shown in operation in a pipe or conduit 14 of a well or other downhole structure. In this example, the pipe 14 is vertically-oriented, but it will be appreciated that the pipe 14 could have any orientation and that the local orientation of the pipe may change over its length. The tool 10 is suspended on a connecting line or downhole line which in this case comprises a cable 16. The cable 16 is attached to a surface control module 18, which is shown schematically in
The control module 18 includes a winch for pulling in and paying out the cable 16, allowing the tool 10 to be moved axially along the pipe 14. By “axially”, it is meant that the tool 10 transits in a direction generally parallel to the longitudinal axis of the pipe. As is generally known in the art, operation of the winch is monitored and logged by the control module 18 so that the depth of the tool 10 as a function of time can be estimated from a displacement measurement of the cable 16. For example, the length of cable 16 payed out or pulled in may be measured directly or determined from the operating speed and direction of the winch, with the estimated depth of the tool 10 being equal to the length of cable 16 deployed at a given time. The velocity of the tool 10 can be estimated by differentiating the estimated depth as a function of time.
The camera 12 of the tool 10 is arranged to capture successive images of the internal surface of the pipe 14 that lie within a field of view 20 of the camera 12. Conveniently, the successive images can be captured in the form of a video stream, in which successive images or frames are captured at intervals determined by the frame rate of the video stream.
In
As illustrated in
The pipe 14 includes a plurality of features, indicated generally at 24, that are spaced apart from one another. The features 24 may be at a known depth position within the pipe 14 or may be at known distances from one another, although it is not necessary that the absolute positions of the features 24 with respect to the surface are known. Examples of reference features 24 may include collars, joins and junctions, and downhole equipment of various types. These reference features 24 provide reference points during subsequent analysis of the images, as will be described in more detail below. The reference features 24 are visible in the images when they are within the field of view 20 of the camera 12. Accordingly, in the illustrated example, one such reference feature 24 would be visible in the third image 22c.
The image data obtained in this way may be logged in the tool 10 and retrieved after removal from the tool 10 from the pipe 14. Alternatively, or in addition, the image data may be transmitted to the control module 18 via the cable 16 for logging at the surface.
The present invention provides a method of using image data, such as can be obtained by the tool 10 as described above, to obtain a measure of the instantaneous axial velocity of the tool 10 during its transit along the pipe 14 that can provide a more accurate indication of the depth of the tool at a given transit time than can be obtained by monitoring the operation of the winch alone.
Referring to
In a second step 102, the overlapping images are analysed to determine, as a function of transit time t, an observed axial velocity of the tool VPimage(t), in units of image pixels per unit time (expressed as pixels per second in this example). In a third step 103, a conversion is applied to the observed axial velocity in pixels per second to obtain an observed axial velocity Vmimage(t) in units of distance per unit time (expressed as millimetres per second in this example).
In a fourth step 104, reference points x are identified in the images. As described above, the reference points are provided by features 24 of the pipe 14 that are spaced apart from one another in distance, and therefore appear at succeeding transit times in the image data as the tool 10 moves along the pipe 14. The transit times at which the reference points appear in the images (or, more accurately, intersect with a central part of the image) define the boundaries of reference transit time intervals, referred to as zones, in the image data.
In a fifth step 105, an estimated axial velocity of the tool Vmcable(t) in units of distance per unit time (expressed as millimetres per second in this example), is determined as a function of transit time from the behaviour of the cable 14 at the control module 18. For example, Vmcable(t) may be determined by measurement of the displacement of the as a function of transit time, or by direct or indirect measurement of the velocity of the cable.
In a sixth step 106, the estimated axial velocity determined from the control module in the fifth step 105, Vmcable(t), and the observed axial velocity determined from the image data in the third step 103, Vmimage(t), are both integrated with respect to time within each of the zones identified in the fourth step 104. This integration step provides two estimates of the distance traversed by the tool 10 between the reference points x, calculated from the behaviour of the cable 16 in the first case and the captured image data in the second case.
If Vmcable(t) and Vmimage(t) were both accurate measurements of the tool velocity, the respective distances estimated in step 106 would be equal. However, this is typically not the case. In particular, Vmcable(t) cannot account for variations in velocity of the tool 10 with respect to the uphole end of the cable 16. Such variations might for example come about through stretching or oscillation of the cable 16, and/or through friction between the tool 10 and the wall of the pipe 14 that acts to cause stick-slip behaviour of the tool 10. Vmimage(t), on the other hand, can accurately capture such high-frequency variations in the velocity of the tool 10, but typically provides a poorer estimate of average velocity of the tool over a relatively long distance compared to Vmcable(t) due to cumulative errors in the conversion of VPimage(t) to Vmimage(t), for example.
Referring back to
Vm
corr(t)=ax·Vmimage(t)
where ax is a dimensionless correction factor that is calculated for each zone between adjacent reference points x so that the condition:
∫Vmcorr(t)dt=∫Vmcable(t)dt
is satisfied for each zone.
Accordingly, Vmcorr(t) is based on the velocity derived from the image data with a correction factor that ensures that, within each zone between adjacent reference points, Vmcorr(t) provides an estimate of the total displacement distance traversed by the tool as it passes through the zone that is equal to the displacement distance which can be derived from Vmcable(t). In this way, Vmcorr(t) provides a more accurate estimate of the velocity of the tool 10 than either Vmimage(t) or Vmcable(t) alone.
Once Vmcorr(t) has been calculated, an accurate estimate for the displacement distance of the tool 10 along the pipe between two time intervals can be obtained by integrating Vmcorr(t) with respect to time between those time intervals. It will be appreciated that Vmcorr(t), and therefore the position estimates that can be derived by integrating Vmcorr(t), relate specifically to the position of the camera 12 of the tool 10.
Accordingly, in an optional eighth step 108, an accurate estimate of the downhole position of the camera 12 at a given transit time, relative to a given reference position, can be determined by integrating Vmcorr(t) with respect to time between the transit time at the reference position and the transit time of interest.
Where the tool 10 includes further sensors disposed above or below the position of the camera 12 or is coupled to other tools with further sensors in a toolstring, an accurate estimate of the depth of those sensors can be obtained, in an optional ninth step 109, by applying a suitable offset to the calculated depth of the camera. The offset to be applied can be readily determined from knowledge of the geometry of the tool 10 (or the toolstring).
In this way, the images and data from other sensors obtained from the tool 10 can be ascribed accurately to a depth or position within the pipe 14 for further analysis.
Examples of how the steps of the method illustrated in
The second image 202 is obtained subsequent to the first image 201, so that the second image 202 captures a field of view that is shifted downwards in the pipe 14 with respect to the first image 201. The axial extent of the two images 201, 202 overlaps. In this example, a reference feature 24, such as a collar, is visible in both images. Another surface feature 28 is also visible in both images 201, 202.
First, in step 301, the captured images 201, 202 can be adjusted to correct for different lighting conditions, geometrical distortions caused by viewing geometry and other distortions and effects, and to apply a lens calibration to account for individual lens properties.
Then, in step 302, the corrected images 201, 202 are pre-processed for subsequent image analysis, as is generally known in the art. Such pre-processing may include contrast enhancement, noise reduction, colour correction, and so on.
In step 303, the pre-processed images 201, 202 are analysed by suitable image analysis techniques to determine the shift in the axial (y) direction between the two images 201, 202, Δy (see
In step 304, the observed axial velocity of the tool in pixels per second, VPimage, is calculated for the pair of images 201, 202 by dividing the y-shift Δy by the time interval Δt between the images 201, 202. Repeating this calculation for successive pairs of overlapping images provides the observed axial velocity VPimage(t) as a function of transit time, where the transit time assigned to each value of VPimage is preferably taken as the mid-point between the capture times of each image 201, 202.
If the images are captured as part of a video stream with frame rate F (in units of frames per second), the observed axial velocity VPimage (in units of pixels per second) can be calculated as VPimage=Δy. F.
To convert VPimage(t) to Vmimage(t) (step 103 of
First, in step 401, image analysis is used to identify the pixels in the corrected images 201, 202 that are occupied by the reference blade 26. Then, in step 402, the width of the reference blade 26 in pixels is measured from the images. Then, in step 403, a conversion factor Qref in millimetres per pixel is determined, based on the known width of the reference blade 26. Finally, in step 404, Vmimage(t) can be calculated as:
Vm
image(t)=Qref·VPimage(t).
Once Vmimage(t) has been calculated in this way, the corrected axial velocity of the tool Vmcorr(t) can be determined, along with the corrected position of the camera and further sensors as described above with reference to steps 105 to 109 of
The conversion factor Qref will vary as a function of transit time if the diameter of the pipe is not constant. Preferably, therefore, the method of
A variant of the method of
In step 501 of the method of
In step 502, the observed axial displacement distance of the tool in pixels as a function of transit time, XPimage(t), is determined from the overlapping images. Referring back to
In step 503, a conversion factor is applied to the observed axial displacement distance in pixels to obtain an observed axial displacement distance Xmimage(t) in units of distance (millimetres in this example). Xmimage(t) can be calculated as:
Xm
image(t)=Qref·XPimage(t)
where the conversion factor Qref can calculated in the same way as described above with reference to steps 401 to 403 of
In step 504, reference points x and corresponding zones are identified in the images, as described above with reference to step 104 of
In step 505, an estimated axial displacement distance of the tool Xmref, in units of distance (millimetres this example), is determined for each zone. Xmref is an estimate of the total distance moved by the tool as it passes from the start to the end of each zone. Xmref may for example be obtained from direct measurement of the displacement of the cable, or by integrating the measured velocity of the cable Vmcable(t) with respect to time within each zone. Alternatively, if the spacing between reference features 24 is known, this spacing can be taken as the estimated axial displacement distance Xmref of the tool as it passes through the corresponding zone.
In step 506, the corrected axial displacement distance of the tool as a function of time, Xmcorr(t), is determined. Xmcorr(t) is also in units of distance and is given by:
Xm
corr(t)=ax·Xmimage(t)
The correction factor ax is calculated for each zone between adjacent reference points x so that, within each zone, the total axial displacement distance traversed by the tool within that zone, computed from Xmcorr(t), equals the estimated axial displacement distance Xmref for that zone.
In optional step 507, an accurate estimate of the position of further sensors on the tool or toolstring can be obtained by applying a suitable offset to the corrected axial displacement distance of the tool determined in step 506.
It will be appreciated that, in the case where a known spacing between reference features is used as the estimated axial displacement distance of the tool Xmref in step 505 of
The method of
The methods described above, in which reference blades 26 are used to determine the conversion factor Qref, can be used when the tool 10 includes a single sideways-facing camera 12, or when the tool 10 includes multiple sideways-facing cameras.
Where multiple sideways-facing cameras are provided, they are preferably arranged to capture the whole circumference of the pipe 14 in a plurality of successive sets of circumferentially-overlapping images. The cameras are preferably disposed in a single plane that extends perpendicular to a longitudinal axis of the tool. Accordingly, each of the cameras is disposed at the same distance from an end of the tool.
The multiple (e.g. 4) cameras are mounted symmetrically or equidistantly around the inspection tool and are arranged such that, within a certain range of pipe sizes, there is an overlap in the fields of view of neighbouring cameras. There is, therefore, a corresponding overlap in the captured images from neighbouring cameras.
When image data from multiple cameras is available, one approach is to calculate the observed axial displacement distance or velocity of the tool using the axially-overlapping images from each camera separately, as described with reference to
An alternative approach is to perform a circumferential stitching of the synchronised circumferentially-overlapping images from the set of cameras to provide, at each image time interval, a composite image covering the whole circumference of the pipe. The observed axial velocity of the tool VPimage as a function of time or the observed axial displacement distance of the tool XPimage(t) as a function of time can then be obtained by analysis of successive composite images in the manner described above with reference to
When the inspection tool 10 does not include reference blades 26, a conversion factor from pixels to distance units cannot be obtained by the method of
Steps 603 (identification of reference points and zones in the images) and 504 (determination of the estimated axial velocity of the tool, Vmcable(t), in units of distance per unit time) of the method of
In the method of
Vm
corr(t)=kx·VPimage(t)
where kx is a correction factor (with units of distance per image pixel) that is calculated for each zone between adjacent reference points x so that the condition:
∫Vmcorr(t)dt=∫Vmcable(t)dt
is satisfied within each zone. Again, this condition requires that, for each zone, the total displacement distance of the tool derived from the corrected axial velocity equals the estimated displacement distance of the tool over the same zone when calculated from the tool velocity determined from the cable measurements.
The corrected depth of the camera and of other sensors can be calculated from Vmcorr(t) as previously described.
In this way, Vmcorr(t) and corrected depth data for the tool can be determined without knowledge of the internal diameter of the pipe 14 and without a reference measurement of the distance per pixel in the images. In doing so, it is assumed that the internal diameter of the pipe 14 is constant between each adjacent pair of reference points.
In some cases, a measurement of the internal diameter of the pipe 14 can obtained during data acquisition by including suitable apparatus on the tool 10 (or on a toolstring coupled to the tool). Examples of apparatus that can be used to measure the internal diameter include multi-finger caliper devices, laser rangefinders, sonic rangefinders, infra-red rangefinders and so on.
When an independent internal diameter measurement is available, this can be taken into account by adjusting the value of kx in step 605 of the method of
k
xAv
·∫VP
image
dt=∫Vm
cable
dt
is satisfied within each zone. Then, the value of the correction factor as a function of time within each zone, kx(t), can be calculated as:
k
x(t)=(kxAv/DxAv)·D(t)
where DxAv is the average distance between the camera and the wall in that zone.
If the spacing between reference features is known, the method of
In step 701 of the method of
Steps 703 (identification of reference points and zones in the images) and 704 (determination of the estimated axial displacement distance of the tool, Xmref, in units of distance) of the method of
In step 705, the corrected axial displacement distance of the tool Xmcorr(t) is calculated as:
Xm
corr(t)=kx·XPimage(t)
where the correction factor kx is calculated for each zone between adjacent reference points x so that the total axial displacement distance over that zone, calculated from Xmcorr(t), is equal to the estimated axial displacement distance Xmref determined in step 704.
Successive overlapping images of the internal surface of the pipe 14 captured with a downview camera tool 50 can also be used to calculate Vmcorr(t) or Xmcorr(t), for example by following the methods described above with reference to
It will be appreciated, however, that the images acquired by a downview camera include highly distorted regions, and so care must be taken to correct for such distortions.
For example, the determination of the observed axial velocity may be performed on images that are cropped to an effective field of view within which the geometric distortion is relatively small (i.e. not too close to the camera 52) and within which each pixel corresponds to a reasonably small distance on the pipe wall (i.e. not too far from the camera 52).
Also, the geometrical correction applied to the images (for example in step 301 of
After suitable geometrical correction, the images obtained from a downview camera tool 50, as illustrated in
The tool may connected to the control module by any suitable connecting line. The above examples refer to arrangements in which the connecting line comprises a cable. Such a cable could be of any suitable type, and may for example be a slickline or electric line. The connecting line may instead be in the form of tubing, such as coiled tubing or drill pipe. The connecting line may allow communication between the tool and the control module, through electrical, fibre optic or other communication routes, or instead the connecting line may simply support the tool (in which case the data acquired by the tool may be stored by a logging device of the tool and downloaded after retrieval of the tool).
It is also possible that the inspection tool could be of a type in which no connecting line is present. For example, the inspection tool could be a self-propelled robotic tool.
It will be appreciated that, while in the above-referenced examples the imaging device is a visible light camera, other suitable imaging devices may be used in the methods and systems of the invention. Substantially any imaging device that can provide time-indexed, a really-extending data from the internal surface of the conduit could be used. For example, suitable alternative imaging devices include non-visible light cameras, such as infra-red cameras, and acoustic sensors.
The devices and/or components described herein can perform one or more processes and/or methods described herein. For example, the devices and/or components can perform at least a portion of such processes and/or methods based on a processor executing software instructions stored by a computer-readable medium, such as memory and/or storage component. A computer-readable medium (e.g., a non-transitory computer-readable medium) is defined herein as a non-transitory memory device. A memory device includes memory space located inside of a single physical storage device or memory space spread across multiple physical storage devices. When executed, software instructions stored in a computer-readable medium may cause a processor to perform one or more processes and/or methods described herein. Additionally, or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes and/or methods described herein. Thus, embodiments described herein are not limited to any specific combination of hardware circuitry and software.
Further modifications and variations of the invention not explicitly described above may also be made without departing from the scope of the invention as defined in the appended claims.
Number | Date | Country | Kind |
---|---|---|---|
1802808.4 | Feb 2018 | GB | national |
Filing Document | Filing Date | Country | Kind |
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PCT/GB2019/050289 | 2/4/2019 | WO | 00 |