Method and apparatus

Abstract

A method and apparatus for performing the method are disclosed. The method comprises obtaining at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore. The method further comprises determining a quality metric of the fully or partially formed plug based on the obtained at least one signal and providing an indication of the determined quality metric.

Description

METHOD AND APPARATUSTECHNICAL FIELD

[0001] The present invention relates to methods and apparatus for determining a quality metric of a fully or partially formed plug in a wellbore, such as a wellbore of an oil or gas well. More particularly, the present invention relates to a method of determining a quality metric of a plug based on at least one obtained signal, where the at least one obtained signal is based on one or more acoustic signals relating to the plug in the wellbore, and an apparatus for performing the same. The method and apparatus disclosed herein may be useful during the formation, repair, or monitoring of plugs in wellbores and may, for example, be implemented for plugs formed from a variety of materials, including, but not limited to, cement-based materials, resin and metals, or metal alloys, that expand upon solidification.BACKGROUND

[0002] Once a wellbore of a well, such as an oil or gas well has been drilled, it may become necessary or beneficial to end or suspend oil or gas extraction. For example, when an oil or gas well, reaches the end of its useful lifespan it is usually abandoned, or, alternatively, if it is no longer used for efficient production, it may be suspended. In other examples, a previously abandoned or suspended well may be recovered for an alternate purpose. In such cases, before a well can be abandoned, suspended or recovered, the wellbore must be plugged to prevent materials, such as hydrocarbons, escaping from the wellbore.

[0003] Various methods are employed to plug wellbores. These methods include, but are not limited to, pouring cement-based material or resin into a wellbore so as to plug (or seal) the wellbore across its radial extent. In some examples, cement-based material or resin may be poured into the wellbore to fill the entire axial extent (i.e., depth) of the wellbore. Recently, an alternative approach has been developed that makes use of metals or metal alloys, such as a bismuth-containing alloy to plug (or form a seal) within a wellbore. These approaches, utilize the properties of metals or alloys that contract upon melting and expand again when they resolidify. When metals or alloys of this nature are used for plugging a wellbore the metals or alloys are provided or deployed into the wellbore in an initial form (such as in the form of plugforming material, such as beads) and once in-situ in the wellbore, are actively heated until the material melts. After melting, the metal or alloy is allowed to cool, expanding on solidification, and thereby plugging (or sealing) the wellbore.

[0004] As the plugs of oil and gas wellbores plug the bore to prevent the release or escape of materials, a need exists for the confirmation of successful plug formation and the monitoring of plug integrity during the plug lifetime. Such methods are particularly advantageous for plugs formed with the recently developed methods utilizing metals and alloys, where the plug integrity may depend on the conditions achieved during the active plug formation steps, such as the application of heat to melt the plug-forming material.SUMMARY OF INVENTION

[0005] Embodiments of the invention are set out in the appended claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Various features of the present disclosure will be apparent from the detailed description which follows, taken in conjunction with the accompanying drawings, which together illustrate features of the present disclosure, and wherein:

[0007] FIG. 1 is a schematic diagram of an example wellbore.

[0008] FIG. 2 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug.

[0009] FIG. 3 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug based on determining a signal propagation characteristic of one or more acoustic communication signals.

[0010] FIG. 4 is a flow chart illustrating optional example methods of determining a quality metric of a fully or partially formed plug based on determining a signal propagation characteristic of one or more acoustic communication signals.

[0011] FIG. 5 illustrates example results of a peaking and / or trough counting analysis.

[0012] FIG. 6 illustrates frequency responses of received acoustic communication signals.

[0013] FIG. 7 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug based on determining an axial length of the plug.

[0014] FIG. 8 illustrates a received acoustic communication signal comprising additional frequency components associated with the presence of a plug.

[0015] FIG. 9 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug based on at least of temperature and pressure data indicated by at least one acoustic communication signal.

[0016] FIG. 10 is a flow chart illustrating optional example methods of determining a quality metric of a fully or partially formed plug based on at least of temperature and pressure data indicated by at least one acoustic communication signal.

[0017] FIG. 11 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug based on detecting a change in at least one obtained environmental acoustic signal.

[0018] FIG. 12 is a flow chart illustrating an example method of providing a quality metric of a fully or partially formed plug based on a weighted combination of a plurality of quality metric indicators.

[0019] FIG. 13 is a schematic diagram of functional blocks of an example apparatus.

[0020] FIG. 14 is a schematic diagram of functional blocks of an example kit of parts.

[0021] FIG. 15 is a schematic diagram of machine readable instructions.

[0022] FIG. 16 is a schematic diagram of a machine readable medium having machine readable instructions stored thereon.DETAILED DESCRIPTION

[0023] The present disclosure describes methods and apparatus to determine a quality metric for a plug of a wellbore based on acoustic signals. The methods and apparatus described herein may improve the accuracy or reliability of plug quality metrics in an effort to improve the assessment of plug integrity, which may alert the existence of plug faults, thus preventing material from leaking, and / or may enable the life of functioning plugs to be prolonged.

[0024] The methods and apparatus disclosed herein may be applicable to any type of plugged wellbore, and specifically a wellbore plugged with any type of plug-forming material. In particular, the present disclosures may be advantageous for plugs formed via melting and cooling, leading to re-solidification.

[0025] The methods and apparatus described herein may be suitable for use with any wellbore, for example a wellbore of an oil or gas well.

[0026] The terms ‘above’ and ‘below’ are used herein to describe relative locations or positions along an axis parallel to the direction of gravity, such that a first position / location described as above a second position / location experiences a higher gravitational potential than the second position / location, and, conversely, a first position / location described as below a second position experiences a lower gravitational potential than the first position / location.

[0027] In the following description, for the purposes of explanation, numerous specific details of certain examples are set forth. Reference in the specification to "an example" or similar language means that a particular feature, structure, or characteristic described in connection with the example is included in at least that one example, but not necessarily in other examples. It should also be understood that examples may be combined in any combination where feasible.

[0028] In order to aid understanding, Figure 1 illustrates a wellbore 102, such as a wellbore provided for drilling or mining environments. It may be that the wellbore has been formed via drilling, such as by a drilling rig, or similar apparatus. As illustrated in Figure 1 , an acoustic conductor, such as a solid acoustic conductor 106 may be disposed internal to the wellbore 102. It may be that the solid acoustic conductor comprises a solid tubular acoustic conductor, such as one or more of a lining, tubing, and casing of the wellbore 102, or any wellbore tubular (such as any tubular component internal to a lining, tubing or casing of the wellbore). The solid acoustic conductor may be formed of metal. Although illustrated in Figure 1 as a single, integrally formed unit, the solid acoustic conductor 106 may comprise a part of a larger structure, or may comprise one or more sub-structures.

[0029] As illustrated in Figure 1 , the wellbore 102 extends from a surface or floor 104. The surface (of floor) 104 may be the ground, i.e., the surface may be a ground-level surface, or in the case of a sub-sea wellbore, the surface 104 may be the sea-floor. The wellbore 102extends from the surface 104 in a direction along a longitudinal axis 110. It may be that the longitudinal axis 110 is parallel, or substantially parallel to the direction of gravity. Alternatively, (not shown) it may be that the longitudinal axis 110 is inclined with respect to the direction of gravity.

[0030] The internal volume of the wellbore 102 may be defined along one or more axis, or dimensions 112, 114, 116. It may be that at least one of the axis (e.g., 114) is aligned with, or is the same as, the longitudinal axis 110 of the wellbore 102.

[0031] A fully or partially formed plug 108 may be disposed within the wellbore 102. As illustrated in Figure 1 , the plug 108 may seal at least a portion of the wellbore 102 from which material can escape. It may be that the plug 108 is configured to plug an internal volume of the wellbore and / or solid acoustic conductor thereof. For example, the plug 108 may be configured to plug an internal volume of a solid acoustic conductor (e.g., a liner etc.,) of a wellbore. It may be that the plug also extends through solid acoustic conductor (such as a liner etc.,) and optionally also beyond the solid acoustic conductor. For example, the plug may also plug (i.e., seal) an internal volume of the wellbore beyond (i.e., external to) the solid acoustic conductor.

[0032] It is noted that while the wellbore arrangement of Figure 1 illustrates space between the wellbore and the solid acoustic conductor thereof, this illustration is merely for ease of distinguishing the separate components, and when deployed, the solid acoustic conductor may be configured to be in mechanical contact with the wellbore, such that leakage therebetween is limited and / or prevented. Alternatively, the solid acoustic conductor may be disposed relative to the wellbore (or e.g., walls thereof) such that there is space (e.g., a cavity) between the solid acoustic conductor and e.g., the walls of, the wellbore.

[0033] It may be that the plug 108 is disposed relative to an existing plug (not shown) to plug or seal an existing damaged or otherwise leaking existing plug.

[0034] It may be that the plug 108 is fully formed (i.e., such that it plugs or seals the wellbore) as a result of the plug formation process (e.g., via the heating and re-solidification of a metal or alloy-based plug-forming material). Alternatively, it may be that the plug 108 is only partially formed (i.e., such that it does not seal the wellbore, or does not meet a sealing criterion or threshold) as a result of the process, for example if the plug-forming material is not fully, or optimally melted. This may result due to insufficient heating of the plug-forming material. For example, if a pre-determined temperature is not reached, or is not sustained or supplied for a time interval required to melt the plug-forming material, or for example if the heating is not applied uniformly to the plug-forming material, or is applied uniformly to an inhomogeneous distribution of plug-forming material. Additionally, or alternatively, the plug formed as a result of the forming process may deviate from an optimal location in the wellbore for plugging the wellbore, or may comprise cracks or other structural deformations, that allow the escape of materials therethrough. Additionally, or alternatively, the plug may become cracked, structurally deformed or dislodged from an optimal sealing location after the formation process, for example, as a result of degradation with age.

[0035] It may be that an acoustic communication node 120 is disposed in acoustic communication with the solid acoustic conductor 106. The acoustic communication node 120 may be configured to transmit an acoustic signal, such as an acoustic communication signal. It may be that an acoustic communication node 118 configured to receive an acoustic signal is disposed in acoustic communication with the solid acoustic conductor 106.

[0036] As illustrated in Figure 1 , the transmitting acoustic communication node 120 may be disposed relative to the wellbore 102 at a location along the longitudinal axis 110 of the wellbore 102 below the plug 108. The receiving acoustic communication node 118 may be disposed relative to the wellbore 102 at a location along the longitudinal axis 110 of the wellbore 102 above the plug 108, or at, or above the surface 104. However, the wellbore 102 may not be so limited and the relative locations of the acoustic communication node 118 and acoustic communication node 120 may be reversed.

[0037] Various methods are described below, which determine a quality metric of a fully or partially formed plug (e.g., plug 108) in a wellbore (e.g., wellbore 102), based on obtaining at least one signal based on one or more acoustic signals relating to the plug (e.g., plug 108).

[0038] The methods described herein may be computer-implemented methods. For example, the method disclosed herein may be methods to be performed by processing circuitry.

[0039] In the following description of the Figures, the methods of Figures 1 to 12 share several features in common. Corresponding features in Figures 1 to 12 are referred to using similar reference numerals.

[0040] Figure 2 is a flow chart illustrating an example method 200.

[0041] In block 202 the method 200 comprises obtaining at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore.

[0042] In block 204 the method 200 comprises determining a quality metric of the fully or partially formed plug based on the received at least one signal.

[0043] In block 206 the method 200 comprises providing an indication of the determined quality metric.

[0044] It may be that obtaining the at least one signal comprises obtaining the at least one signal by processing circuitry, for example by way of receiving the at least one signal by a receiver coupled to the processing circuitry.

[0045] It may be that the at least one signal is as signal configured to be processed by the processing circuitry, for example, the at least one signal may be an electrical signal such as an electrical signal generated by a receiver (coupled to the processing circuitry) in response to receiving the one or more acoustic signals relating to the fully or partially formed plug.

[0046] It may be that the quality metric is an indicator of how able the plug is to plug (or seal) the wellbore, e.g., to prevent the escape of solid or fluids from the wellbore below the plug (and potentially to the surface). For example, a plug that leaks and therefore has a low likelihood of sealing, or continuing to seal a wellbore may be considered to be of low quality, and the qualitymetric determined for such a plug may indicate a relatively low quality, (e.g., may have a relatively low quality score, or low probability or low probability score of providing or maintaining sealing), in comparison to a plug that does not leak, or vice versa.

[0047] The quality metric may be a quality score or e.g., a probability of likelihood of plug integrity, or conversely of plug leakage. It may be that the quality score is a score of a relative scale with one end of the scale associated with plug leakage and the opposite end of the scale associated with complete, or optimal, sealing. It may be that the quality score is a probability, or probability score indicating likelihood of plug leakage, or plug sealing.

[0048] It may be that provided indication of the quality metric enables determination of whether the plug is to be replaced or repaired, or whether additional steps of a plug-forming process are required (such as further heating of the plug-forming material).

[0049] It may be that providing the indication of the determined quality metric comprises providing the indication of the quality metric to a user or operator (such as a user or operator of the wellbore or of equipment thereof), for example by way of a user output or alert etc. It may be that providing the quality metric comprises providing a signal, such as an alert signal or control signal to a device, such as a device associated with the wellbore.

[0050] It may be that at least one of the state of formation of the plug (i.e., fully or partially formed), the plug formation material, structural integrity of the plug (e.g., lack of cracks or deformations) and location of the plug (i.e., with respect to the wellbore) may provide an indication of the plug integrity (or leakage), or the ability of the plug to form (or maintain) a seal. Thus, a plug quality metric may be based on, or depend on, at least one of these indicators.

[0051] It may be that the fully or partially formed plug at least one of: acts on, or e.g., causes an effect on, or change of, the acoustic signal; or emits (or is a source of) the acoustic signal as a result of a change in the plug or a change in the wellbore surroundings as a result of a change in the plug.

[0052] It may be that the acoustic signal carries information relating to the plug, or relating to a wellbore environment parameter which is influenced by (or affected by) the plug.

[0053] It may be that the one or more acoustic signals (e.g., on which the at least one obtained signal is based) is transmitted by propagation via a solid acoustic conductor, such as solid acoustic conductor 106 in acoustic communication with the fully or partially formed plug.

[0054] For example, the solid acoustic conductor (e.g., solid acoustic conductor 106) may form at least part of an acoustic communication channel between the source of the acoustic signal (for example, the transmitting acoustic communication node 120, or other sources of the acoustic signal) and the point of reception of the acoustic communication channel (for example, the receiving acoustic communication node 118).

[0055] For example, it may be that the source of the acoustic signal (for example, the transmitting acoustic communication node 120) and / or the point at which the acoustic signal is received (for example, the receiving acoustic communication node 118) may be disposed in direct acoustic communication with the solid acoustic conductor (for example, solid acousticconductor 106), or in acoustic communication with at least one further acoustic conductor in direct acoustic communication with the solid acoustic conductor. For example, the source of the acoustic signal and / or the point at which the acoustic signal is received may be in direct physical or direct mechanical contact with the solid acoustic conductor, or may be in direct physical or direct mechanical contact with a further acoustic conductor in acoustic communication with the solid acoustic conductor.

[0056] As described above, the solid acoustic conductor (e.g., 106) may be disposed internal to the wellbore 102. The solid acoustic conductor may comprise a tubular solid acoustic conductor. For example, the solid acoustic conductor may comprise or may form one or more of a lining, tubing, and casing of the wellbore 102. The solid acoustic conductor may be formed of metal, but is not so limited.

[0057] It may be that the plug (e.g., plug 108) is disposed within, or relative to the solid acoustic conductor (e.g., solid acoustic conductor 106) and is configured to plug an internal volume of the wellbore or solid acoustic conductor thereof. Alternatively, the plug (e.g., plug 108) may replace or otherwise be integrated with at least a portion of the solid acoustic conductor and may further be configured to plug an internal volume of the wellbore or solid acoustic conductor thereof. For example, the plug may at least replace a portion of removed or e.g. damaged solid acoustic conductor. The plug may be acoustically conducting. It may be that the acoustic properties of the plug are different from the acoustic properties of the solid acoustic conductor. For example, the signal propagation characteristics of the acoustic signal propagating through the plug, or plug-forming material, may be different from the signal propagation characteristics of the acoustic signal propagating through the solid acoustic conductor. For example, the conductance or resonance of the plug may be different from the conductance or resonance of the solid acoustic conductor. It may also be that the signal propagation characteristics of the acoustic signal propagating through a fully formed plug may be different from the characteristics of the acoustic signal propagating through a partially formed plug.

[0058] It may be that the presence of the fully or partially formed plug (and for example, the material, state of formation (i.e., fully or partially formed), structure and / or location of the plug) may change the signal propagation characteristics of the acoustic signal propagating through the solid acoustic conductor in acoustic communication with the plug. For example, the presence of the plug (and for example, the material, state of formation, structure and / or location of the plug) may exert a damping (e.g., an additional damping) of the acoustic signal.

[0059] It may be that, as described herein, the at least one acoustic signal comprises an acoustic communication signal actively transmitted by an acoustic communications node (e.g., node 120), or at least one of the acoustic signals comprises an environmental acoustic signal. For example, it may be that an environmental acoustic signal is not actively transmitted by an acoustic communication node, and may be regarded as a passive acoustic signal. For example, it may be that an environmental acoustic signal relating to the plug originates from, or as aresult of, an event in the wellbore, such as cracking of the plug, movement of the plug, or other such mechanisms relating to the plug by which an acoustic signal arises. In contrast, it may be that an acoustic communication signal is actively transmitted, for example, by way of a powered transmission means or mechanism, such as by a powered transmitter. It may be that the acoustic communication signal comprises symbols by way of which data is transmitted (e.g., via encoding).

[0060] Figure 3 is a flow chart illustrating an example method 300. In block 304 of the example method 300, determining a quality metric of the fully or partially formed plug based on the received at least one signal comprises determining a respective signal propagation characteristic of at least one of one or more acoustic communication signals.

[0061] For example, as described above, it may be that at least the presence of the fully or partially formed plug in acoustic communication with the solid acoustic conductor may change the signal propagation characteristic of the acoustic signal. In particular, it may be that when at least one of the one or more acoustic signals is transmitted by propagation via a solid acoustic conductor in acoustic communication with the fully or partially formed plug, the plug changes a signal propagation characteristic of the acoustic signal obtained (e.g., by way of receiving) after propagation via (at least) the solid acoustic conductor.

[0062] It may be that when the at least one acoustic signal is an acoustic communication signal (actively) transmitted by an acoustic communications node, the signal propagation characteristics of the acoustic communication signal may be determined based at least on the signal characteristics of the transmitted acoustic communication signal, which may be predetermined or otherwise known. For example, may be known by, or communicated to processing circuitry configured to determine the respective signal propagation characteristics of the one or more acoustic communication signals.

[0063] It may be that the signal propagation characteristic is determined based on a comparison of one or more received acoustic communication signals with one or more known, or pre-determined transmitted acoustic communication signals and / or with known signal propagation characteristics associated with given solid acoustic conductors.

[0064] It may be that the signal propagation characteristic is determined based on, i.e. , derived from, one or more received acoustic communication signals. It may be that the signal propagation characteristic is determined based on a signal characteristic indicator detected, or identified, in one ore more received acoustic communication signals. It may be that the signal propagation characteristic is determined based on a reference signal, such as a reference received acoustic communication signal. It may be that the signal propagation characteristic is determined based on a relative comparison of signal characteristic indicators within one or more received acoustic communication signals, for example without requiring a reference signal.

[0065] It may be that a signal propagation characteristic of at least one of the one or more acoustic communication signals indicates information relating to the propagation medium, ormedia, along the acoustic communication channel between the respective acoustic communication signal transmission and receiving nodes, (e.g., nodes 120 and 118). For example, a signal propagation characteristic may be an effect (e.g., a measurable effect) on the transmitted acoustic communication signal caused by the propagation medium or media. For example an effect on the spectrum of the transmitted acoustic communication signal. For example, a signal propagation characteristic may be a change in shape of the spectrum e.g., due to attenuation, but it is not so limited.

[0066] A signal propagation characteristic may indicate a conductance, resonance or attenuation of at least one of the media. It may be that a signal propagation characteristic is an indicator of a damping of the solid acoustic conductor depending on the plug (i.e., depending on at least the presence of the plug). For example, it may be that the signal propagation characteristic is an indicator of a damping of the solid acoustic conductor as a result of at least a presence, and / or at least one of the material, state of formation (i.e., fully or partially formed), structure (i.e., intact or cracked) and / or location of the fully or partially formed plug.

[0067] For example, if the fully or partially formed plug is loose, i.e., if it has become dislodged and / or is not or is no longer forming a seal across the wellbore (i.e., it is not lodged in the wellbore and as a result is not held tightly), or, if for example, the plug is partially formed such that particles or beads of plug-forming material have not been melted and re-solidified into a single structure, then the plug and or components thereof may move.

[0068] More specifically, when an acoustic signal (such as an acoustic communication signal) propagates therethrough, the plug or components thereof may have a greater degree of movement than a fully formed or sealing (tightly held) plug. In this case, when the acoustic communication signal propagates therethrough, the energy of the acoustic signal is preferentially absorbed by the material with higher degrees of movement (i.e., the energy of the acoustic communication signal is absorbed more by the elements with higher degrees of movement), such as the partially formed or dislodged plug, as opposed to the fully formed or sealing plug, which may be considered to be stiffer. This is particularly the case for plugs formed of bismuth, where if the plug is stiff and fully formed the plug resonates at a particular frequency and allows other signals to pass without losing energy to free components (i.e., bismuth beads) of the plug. This effect provides a plurality of signal propagation characteristics that can be used to indicate the quality of the plug.

[0069] As illustrated in Figure 4, it may be that the signal propagation characteristic is based on (or is characterised depending on) at least one of: a peak and / or trough counting analysis of the acoustic communication signal; a determination of a Q-factor of the acoustic communication signal; and a frequency response of the acoustic communication signal. It may be that each of these determinations of the signal propagation characteristic are included in methods 300 or 400 alone, or in combination.

[0070] As illustrated in block 404a, it may be that the signal propagation characteristic of a respective acoustic communication signal is based on (or is characterised depending on) apeak and / or trough counting analysis of the acoustic communication signal. For example, a signal propagation characteristic of an acoustic communication signal may be based on a number of local minima and / or local maxima detected in the signal strength (i.e., amplitude) of a received acoustic communication signal as a function of frequency.

[0071] It may be that one or more local minima, and / or local maxima are determined (i.e., identified, or classified) within a given received acoustic communication signal. The term local maxima and local minima is used herein to differentiate from a global maxima or global minima, of which there can be only one.

[0072] For example, a local maxima may be identified (or e.g., classified) as a portion of the received signal associated with a local peak (i.e., a candidate local maxima) in signal amplitude (i.e., a continuous increase in amplitude followed by an continuous decrease in amplitude), if no other peaks or troughs (i.e., decreases in amplitude on the rising edge of the candidate local maxima or increases in amplitude on the falling edge of the candidate) are detected within a pre-determined frequency bandwidth centered on the local peak (of the candidate local maxima). For example, a local maxima may be identified (or e.g., classified) if the increase in amplitude of the candidate local maxima following a decrease in amplitude (i.e., the rising or leading edge), and the respective decrease in amplitude following the increase in amplitude (i.e., the falling or trailing edge), are continuous (i.e., the direction of the change in amplitude does not change, such that the amplitude of the signal is continuously increasing or continuously decreasing) over the pre-determined frequency bandwidth. It may be that the frequency bandwidth corresponds to a pre-determined range in (or e.g., change in) amplitude of the signal. For example, it may be that the frequency bandwidth, on each side of the peak, corresponds to 7dB in amplitude. For example, it may be that a local maxima may be identified (or e.g., classified) based on a candidate local maxima if no other peaks or troughs are detected within the received signal on either side of the candidate local maxima over a portion of the received signal that comprises a pre-determined range in amplitude (e.g., 7dB).

[0073] Alternatively, or additionally it may be that one or more local maxima are determined (i.e., identified, or classified) within a given received acoustic communication signal based on identifying a local peak (i.e., a candidate local maxima), identifying an associated local minima ( i.e., candidate local minima, e.g., an associated trough) on a first side of the candidate local maxima, and identifying an associated local minima ( i.e., candidate local minima, e.g., an associated trough ) on a second side of the candidate local maxima opposite the first side. It may be that the local maxima is further determined by determining a first respective amplitude difference between the amplitude of the local minima on the first side of the candidate local maxima, and the amplitude of the candidate local maxima (i.e., a peak to trough amplitude difference), and determining a second respective amplitude difference between the amplitude of the local minima on the second side of the candidate local maxima, and the amplitude of the candidate local maxima (i.e., a peak to trough amplitude difference).

[0074] It may be that the local maxima is further determined by identifying the candidate local maxima as a local maxima if both of the respective first and second amplitude differences meet a criteria based on a comparison with a threshold. For example, if both the first and second amplitude differences are equal to or greater than 7dB. It may be that the associated local minima is the nearest trough adjacent to the candidate local maxima or may be a local minima identified / classified from a candidate local minima.

[0075] It may be that one or more local minima are similarly determined with respect to a local trough (i.e., local minima candidate) in signal amplitude if no other peaks or troughs (i.e., increases in amplitude on the falling edge of the candidate local minima or decreases in amplitude on the rising edge of the candidate) are detected within a pre-determined frequency bandwidth. For example, it may be that one or more local minima are determined if the decrease in amplitude of the candidate local minima following an increase in amplitude (i.e., the falling or leading edge), and the respective increase in amplitude following the decrease in amplitude (i.e., the rising or trailing edge) are continuous (i.e., the direction of the change in amplitude does not change, such that the amplitude of the signal is continuously increasing or continuously decreasing) over the pre-determined frequency bandwidth, as described above. For example, it may be that a local minima may be identified (or e.g., classified) based on a candidate local minima if no other peaks or troughs are detected within the received signal on either side of the candidate local minima over a portion of the received signal that comprises a pre-determined range in amplitude (e.g., 7dB).

[0076] Alternatively, or additionally it may be that one or more local minima are determined (i.e., identified, or classified) within a given received acoustic communication signal based on identifying a local trough (i.e., a candidate local minima), identifying at least one associated local maxima ( i.e., candidate local maxima, e.g., an associated peak) on a first side of the candidate local minima, and identifying at least one associated local maxima ( i.e., candidate local maxima, e.g., an associated peak) on a second side of the candidate local minima opposite the first side.

[0077] It may be that the local minima is further determined by determining a first respective amplitude difference between the amplitude of the local maxima on the first side of the candidate local minima, and the amplitude of the candidate local minima (i.e., a peak to trough amplitude difference), and determining a second respective amplitude difference between the amplitude of the local maxima on the second side of the candidate local minima, and the amplitude of the candidate local minima (i.e., a peak to trough amplitude difference).

[0078] It may be that the local minima is further determined by identifying the candidate local minima as a local minima if both of the respective first and second amplitude differences meet a criteria based on a comparison with a threshold. For example, if the both amplitude differences are equal to or greater than 7dB. It may be that the associated local maxima is the nearest peak adjacent to the candidate local minima or may be a local maxima identified from a candidate local maxima.

[0079] It may be that a number of local minima and / or a number of local maxima are determined with respect to a single received acoustic communication signal ( e.g., a single received broad-band signal, chirp or sweep). It may be that a number of local minima and / or a number of local maxima are a number of local minima and / or a number of local maxima are determined with respect to (e.g., summed over) a plurality of received acoustic communication signals ( e.g., more than one received broad-band signal, chirp or sweep)

[0080] It may be that a higher number of determined (or identified / detected) local maxima indicates a plug with relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) and that a lower number of local maxima indicates a plug with a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality). It may be that a higher number of determined (or identified / detected) local minima indicates a plug with relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) and that a lower number of local minima indicates a plug with a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality).

[0081] It may be that the determined quality metric depends on the determined number of local minima and / or local maxima. For example, the quality metric may be determined (or e.g., assigned) depending on the value of the number of local minima and / or local maxima. For example, the quality metric may based on (or depends on) a comparison of the number of local minima and / or local maxima with respect to a threshold value (and further optionally with respect to a pre-determined deviation from a threshold value). For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the difference is within a pre-determined deviation from a threshold value. For example, if the number of local minima and / or local maxima is greater than or equal to a threshold value. It may be that the threshold value is greater than 8 and less than 16, as discussed below with respect to Figure 5.

[0082] It may be that the number of determined local minima and number of determined local maxima are independent quality metric indicators. For example, it may be a quality metric indicating that the plug has a higher likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively higher quality) is determined if both the number of local minima and the number of local maxima meet respective threshold criteria, for example, in comparison to a quality metric determined with respect to a threshold comparison based on either a number of local minima or local maxima alone.

[0083] As illustrated in block 404b, it may be that the signal propagation characteristic of a respective acoustic communication signal is based on (or is characterised depending on) a determination of at least one Q-factor of the acoustic communication signal. The Q-factor is a dimensionless indicator of the damping of a resonator (or oscillator). The Q-factor is a function of the energy stored in a resonator divided by the energy dissipated in a resonator per cycle ofoscillation, where a larger Q denotes a less damped resonator. Thus, it may be that a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined ( or e.g., assigned) based on a lower value of Q, for example, a value of Q less than a predetermined threshold, and vice versa.

[0084] The Q-factor may be given by equation 1 :. bandwidth

[0085] The resonance frequency is a frequency for the resonator (for example, the solid acoustic conductor in acoustic communication with the plug) at which peak gain occurs. The bandwidth may be, or may be derived from, the 3dB bandwidth, i.e., the half-power bandwidth or the full width half maximum value. Alternatively, the bandwidth may be, or may be derived from, the 6dB bandwidth, i.e., the quarter-power bandwidth.

[0086] It may be that a resonance frequency is determined (e.g., measured) from the obtained signal based on the one or more acoustic communication signals. For example, a resonance frequency may be based on the peak and / or trough counting analysis. For example, a resonance frequency may be (i.e., may equal) a frequency corresponding to a detected peak.

[0087] For example, it may be that a respective Q-factor value is determined for each local maxima detected in a received acoustic communication signal. It may be that a respective Q- factor value is determined for each local maxima detected in each of a plurality of received acoustic communication signals ( e.g., more than one received broad-band signal, chirp or sweep), for example where each received acoustic communication signal is received separated in time within a pre-determined time interval.

[0088] It may be that the respective 3dB bandwidth or 6dB bandwidth for a respective resonance frequency is determined (e.g., measured) from the obtained signal based on the one or more acoustic communication signals. For example, a respective 3dB bandwidth or 6dB bandwidth may be based on the peak and / or trough counting analysis. For example, the 3dB bandwidth or 6dB bandwidth may be based on the detected peak associated with the resonance frequency. For example, the 3dB bandwidth may be the half-power bandwidth or the full width half maximum value of the detected peak associated with the resonance frequency. Alternatively, the 6dB bandwidth may be the quarter-power bandwidth or the full width quarter maximum value of the detected peak associated with the resonance frequency.

[0089] It may be that the determined quality metric depends on the one or more determined Q-factor values. For example, the quality metric may be determined (or e.g., assigned) depending on the one or more values of the determined Q-factor.

[0090] For example, the quality metric may based on (or depends on) a comparison of at least one Q-factor value, for example a single (e.g., maximum) Q-factor value or e.g., a sum of Q-factor values, with respect to a threshold value (and further optionally with respect to a predetermined deviation from a threshold value). For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the difference iswithin a pre-determined deviation from a threshold value. Alternatively, it may be that a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined ( or e.g., assigned) if the difference is outside or beyond a pre-determined deviation from a threshold value, or vice versa.

[0091] It may be that respective Q-factor values, based on respective resonance frequencies (i.e., detected local maxima) and respective 3dB or 6dB bandwidths are determined for a plurality of detected peaks (e.g., from a single received acoustic communication signal or from a plurality of received acoustic communication signals). It may be that a histogram of the respective Q-factor values is determined. The quality metric may be determined (or e.g., assigned) depending on at least one characteristic (or descriptor) of the determined Q-factor value histogram, or a distribution fitted thereto. For example, based on at least one of a maximum amplitude, mean, median, mode, standard deviation, variance, mean absolute deviation, median absolute deviation, skew, kurtosis etc.,. For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined ( or e.g., assigned) based on a higher value of maximum amplitude of the histogram of Q-factor values and / or based on a shape of the distribution, e.g., based on a narrowly peaked distribution of Q-factor values, and vice versa.

[0092] It may be that the quality metric may be determined (or e.g., assigned) depending on a change of at least one characteristic (or descriptor) of Q-factor value histograms (or a distribution fitted thereto) determined as a function of time. For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined ( or e.g., assigned) based on a larger change in at least one characteristic (or descriptor, e.g., maximum amplitude and / or width of distribution) between respective Q-factor value histograms determined based on respective acoustic communication signals received separated in time from an initial starting point (e.g., from the start of the plug formation process) and vice versa. For example, it may be that as plug-forming material is formed (e.g., cured and / or heated) respective histograms of Q- factor values determined from acoustic communication signals received at progressively later times after the start of the plug-formation progress may display increasingly narrow and higher peaks if a plug-formation process proceeds successfully to form a good plug. However, if the plug formation process is not successful, i.e., does not fully form a plug, or forms a plug with low likelihood of sealing the wellbore (i.e., if the plug-forming material is not sufficiently melted and re-solidified), respective Q-factor values histograms may have characteristics that do not change, or change less, with time, e.g., the peak and width of the respective histograms may remain low and wide.

[0093] The above histograms and analysis thereof have been described as being representations of (e.g., comprising) Q-factor values. However, the above presented analysis may instead be performed with respect to histograms of values of first derivatives of the spectrum (i.e., the gradient of the slope of the spectrum) of one or more received acousticcommunication signal in portions of the spectrum associated with (i.e., comprising and / or adjacent to) determined (i.e., identified) local maxima or local minima.

[0094] It may be that the values of the first derivatives of the spectrum of the received signals at (or close to) the local maxima, indicates the shape, e.g., the width of the peak of the spectrum of the received signal, which may also (e.g., similarly to the Q-factor) indicate the damping of the resonance of the solid acoustic conductor.

[0095] It may be that the histograms comprise values of first derivatives of the spectrum on a first side (e.g., the rising or leading edge for a local maxima), or a second side (e.g., the falling or trailing edge for a local maxima, or vice versa for a local minima) of the local maxima or minima. It may be that, as above, the quality metric is determined (or e.g., assigned) depending on at least one characteristic (or descriptor) of at least one determined first derivative value histogram, or a distribution fitted thereto. For example, it may be that the quality metric is determined (or e.g., assigned) depending on at least one characteristic (or descriptor) of a plurality of respective first derivative value histograms.

[0096] It may be that the respective histograms representing the first derivatives of the spectrum on the first side and on the second side of the local maxima (or local minima) provide different (and e.g., independent) indications of the damping of the solid acoustic conductor. It may be that the determination of the quality metric based on the combination of quality metric indicators determined, respectively, from the different histograms comprising values derived from the different first and second sides of the local maxima (or minima) may increase the accuracy and / or reliability of the quality metric. For example, the quality metric may be determined (or e.g., assigned) depending on at least one characteristic (or descriptor) of a histogram representing (e.g., comprising) first derivative values determined on the first side of respective local maxima (or minima), and based on at least one characteristic (or descriptor) of a histogram representing (e.g., comprising) first derivative values determined on the second side of the respective local maxima (or minima).

[0097] Another effect that may be detected on an acoustic signal as a result of free moving (i.e., not stiff) components of a partially formed plug (e.g., beads of plug-forming material), or of a non-sealing (i.e., dislodged) plug is the increase in attenuation of the acoustic signal (e.g., the acoustic communication signal) with increasing frequency. In particular, the attenuation of frequencies above 10kHz by bismuth beads.

[0098] As illustrated in block 404c it may be that the signal propagation characteristic of a respective acoustic communication signal is based on (or is characterised depending on) a frequency response of the acoustic communication signal. For example, the signal propagation characteristic of a respective acoustic communication signal may be based on a relative comparison of signal strengths of a received acoustic communication signal between at least two frequency bands of the received signal, or based on a comparison of received versus transmitted signal strengths in two different frequency bands. It may be that the comparison is further with respect to a threshold, such as a threshold in determined difference.

[0099] For example the first frequency band may be less than 5kHz, and the second frequency band may be greater than 5kHz. Alternatively, the first frequency band may be less than 10kHz, and the second frequency band may be greater than 10kHz. Alternatively, the first frequency band may be less than 20kHz, and the second frequency band may be greater than 20kHz.

[0100] It may be that a determination of higher attenuation (i.e. , more reduction in signal strength) at higher frequencies than at lower frequencies indicates that a plug is partially formed or is or has become dislodged, and is therefore has a lower likelihood of successfully, and sustainably, sealing the wellbore. It may be that the determined quality metric depends on the determined frequency response, and in particular, the determined attenuation at higher frequencies. For example, the quality metric may be determined (or e.g., assigned) depending on a value of the determined frequency-dependent attenuation.

[0101] For example, it may be that the signal propagation characteristic is determined based on an attenuation gradient, or roll-off rate (i.e., slope of the received spectrum (amplitude as a function of frequency)), at a frequency above 5kHz, 10kHz, or 20kHz. It may be that the attenuation gradient is determined based on a smoothed, or filtered received acoustic communication signal.

[0102] It may be that the quality metric is based on (or depends on) a comparison of the determined attenuation gradient, beyond a pre-determined frequency, with respect to a threshold value (and further optionally with respect to a pre-determined deviation from a threshold value). For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the difference is within a pre-determined deviation from a threshold value, or vice versa. For example, it may be that quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the attenuation gradient beyond a pre-determined frequency (e.g., 5kHz, 10kHz or 20kHz) is relatively flat, i.e., changes by less than 10dB per octave.

[0103] Alternatively, it may be that a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined ( or e.g., assigned) if the difference is outside or beyond a pre-determined deviation from a threshold value, or vice versa. For example, it may be that quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined (or e.g., assigned) if the attenuation gradient is relatively steep, i.e., changes by more than 10dB, or 20dB, per octave.

[0104] It may be that the quality metric is determined based on (or depending on) a single signal propagation characteristic determination based on a single indicator, such as a single value of Q-factor, a single value of counted peaks and / or troughs, or a singe value indicating a frequency response of the acoustic communication signal. It may be that the quality metric isdetermined based on (or depending on) a plurality of signal propagation characteristic determinations based on a single indicator, such as a plurality of signal propagation characteristic values (e.g., Q-factor values, number of local minima / maxima or frequencydependent attenuation values). For example, a plurality of signal propagation characteristic values based on a single indicator as a function of time, or based on a statistical analysis identifying a descriptor of a plurality (or distribution) of signal propagation characteristic values based on a single indicator (e.g., Q-factor values, number of local minima / maxima or frequency-dependent attenuation values) such as a minimum, maximum, mean, median, mode, standard deviation, sum etc.

[0105] It may also be that the quality metric is determined based on a combination of a plurality of quality metric indicators, as will be discussed in more detail below. It may be that the respective quality metric indicators are different (or independent) indicators. It may be that determining the quality metric based on plurality of different quality metric indicators increases the accuracy and / or reliability of the quality metric. It may be that the combination of each additional quality metric indicator in the quality metric determination increases the accuracy and / or reliability of the quality metric.

[0106] It may be that each respective quality metric indictor is based on (depends on) a specific signal propagation characteristic indictor, and that different signal propagation characteristic indicators are combined via respective quality metric indicators. For example a signal propagation characteristic indictor may be: one or more Q-values, one or more peak and / or trough counting values, or one or more frequency response values indicative of frequency-dependent attenuation.

[0107] For example, a first quality metric indicator may be based on one or more Q-factor values, a second quality metric indicator may be based on one or more peak and / or trough counting values, and a third quality metric indicator may be based on one or more frequency response values etc.,. Although three quality metric indictors are described above, the methods disclosed herein are not so limited and the quality metric may be based on more or fewer quality metric indicators, which may be combined in any combination.

[0108] Figure 5 illustrates example results of determined quality metric indicators for a plurality of received acoustic communication signals associated with respective plugs.

[0109] It is known from independent verification (within an experimental environment) that plugs 1 and 4 are good plugs with a high likelihood of sealing, or continuing to seal a wellbore and can be considered to be of high (or higher) quality, whereas it is known that plug 3 is a bad plug with a lower likelihood of sealing, or continuing to seal a wellbore and can be considered to be of low (or lower) quality. It is also known that plug 2 is a low quality plug as it is a plug with short (or shorter) axial length.

[0110] The plots in Figure 5 show representations of a plurality of different quality metric indicators as a function of time, in increments of time following the start of the plug-formation process, i.e., 'start of setting' of the plug-forming material.

[0111] The plots of the number of local maxima 502, number of local minima 504 and the sum of determined Q-factor values 508, as a function of time, show that these quality metrics can be used to distinguish a bad plug (of lower quality), e.g., plug 3, from good plugs (of higher quality), e.g., at least plugs 1 and 4.

[0112] It may be that the thresholds described above for determining the quality metric may be set based on the results illustrated in Figure 5.

[0113] For example, it may be that, as described above, a threshold for determining a quality metric based on a number of local maxima may be set at, or around 10, for example at 8, 9, 10 or 11 . It may be that, as described above, a threshold for determining a quality metric based on a number of local minima may be set at, or around 15, for example at 13, 14 or 15.

[0114] It may be that, as described above, a threshold for determining a quality metric based on a determination of Q-factor values, and for example based on a sum of a determined number of Q-factor values, may be set at, or around 3000, for example between 2500 and 3500.

[0115] As shown in Figure 5, it may be that quality metric indicator of the maximum value of the determined Q-factor values in a spectrum 506, i.e., peak determined Q-factor value, may provide additional information on plug quality.

[0116] Figure 6 illustrates respective frequency responses of acoustic communication signals associated with respective plugs.

[0117] As discussed above, it is seen from Figure 6 that a received acoustic communication signal 602 associated with plug of low likelihood of sealing, or continuing to seal a wellbore and can be considered to be of low (or lower) or bad quality, has a higher attenuation at higher frequencies, as compared with a received acoustic communication signal 604 associated with plug of high likelihood of sealing, or continuing to seal a wellbore and can be considered to be of high (or higher) or good quality.

[0118] As illustrated in Figure 6, the received acoustic communication signal 602 associated with plug of low likelihood of sealing, or continuing to seal a wellbore and can be considered to be of low (or lower) or bad quality, is preferentially attenuated, i.e., has a steeper attenuation gradient above 20kHz than the received acoustic communication signal 604 associated with plug of high likelihood of sealing, or continuing to seal a wellbore and can be considered to be of high quality.

[0119] It can also bee seen from Figure 6, that a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) may be determined (or e.g., assigned) if the attenuation gradient changes by more than 10dB, or 20dB, per octave beyond (i.e., above) 20kHz.

[0120] It may be that in addition to e.g., the state of formation, material, structural integrity (e.g., lack of cracks or deformations) and location of the plug, the length (e.g., the axial length) of the plug (e.g., plug 108) may provide a quality indication of the plug. For example, a plug of longer axial length may provide more robust sealing, or may be more robust to changes overtime that may prevent the plug eroding and or otherwise deforming to allow (unwanted) leakage therethrough.

[0121] It may be that when a plug is excited by an acoustic signal, it will resonate at a natural frequency that is based on (e.g., is defined by) by its axial length. It may be that in comparison to an acoustic signal transmitted via the solid acoustic conductor when the plug is not present (e.g., before the plug is formed or disposed in the wellbore), an acoustic signal received via the solid acoustic conductor in communication with the plug may additionally comprise a frequency component associated with the natural resonant frequency of the plug.

[0122] Figure 7 is a flow chart illustrating an example method 700. In block 704 of the example method 700, determining a quality metric of the fully or partially formed plug based on the received at least one signal comprises determining an axial length of the fully or partially formed plug based on determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals.

[0123] The axial length of the plug (e.g., plug 108) is parallel to the longitudinal axis (e.g., 110) of the wellbore (e.g., 102).

[0124] It may be that, as described above, the signal propagation characteristic is determined based on a comparison of a signal propagation characteristic of a received acoustic communication signal with a signal propagation characteristic of a known, or pre-determined transmitted acoustic communication signal modified with a plurality of transmission functions based on a respective plurality of modelled plugs, for example with a plurality of different axial lengths.

[0125] It may be that an axial length of the plug is determined based on a signal propagation characteristic of a received acoustic communication signal.

[0126] It may be the signal propagation characteristic is the addition of at least one frequency component in the received acoustic communication signal (for example, with respect to the transmitted acoustic communication signal). For example, the addition of at least one frequency component at the natural resonant frequency of the plug. It may be that block 704 further comprises identifying and isolating (or e.g., extracting) the at least one additional frequency component and analysing the at least one frequency component.

[0127] It may be that the axial length of the plug (and therefore the quality metric) is determined based on at least the frequency of the at least one additional frequency component. For example, it may be that the axial length of the plug may be estimated by way of the relationship between the wave speed (i.e., speed of sound in a given material), frequency and wavelength of the additional frequency component. For example, it may be that the wave speed of the additional frequency component is based on (or equals) the frequency of the additional frequency component multiplied by the wavelength of the additional frequency component. It may be that the wave speed is known. It may be that the wave speed depends on the plugforming material (for example, as a result of the density of the plug). It may be that the plugforming material is known and the wave speed for the plug-forming material is known. It may bethat the frequency is determined, e.g., from the identification of the at least one additional frequency component in received acoustic communication signal. It may be that the wavelength is determined from the known wave speed and the determined frequency. It may be that the wavelength is a function of the plug length, thus the axial length of the plug may be determined based on the determined wavelength of the additional frequency component. For example, the axial length of the plug may correspond (e.g., directly correspond) to the determined wavelength of the additional frequency component. For example, the axial length of the plug may equal the determined wavelength of the additional frequency component.

[0128] It may be that identifying and isolating (or e.g., extracting) the additional frequency component comprises determining (e.g., confirming) that the additional frequency component has at least one periodic counterpart. For example, it may be that the presence of the plug introduces a plurality of resonances (i.e., additional peaks in the spectrum of the received signal) spaced periodically in the received acoustic communication signal. For example, it may be that the first resonance introduced as a result of the presence of the plug may occur at frequency equal to 1 / n multiplied the wave speed divided by the length of the plug, where n is an integer. It may be that additional resonances in the received acoustic communication signal occur at integer multiples (m) of the first resonance, i.e., at frequencies equal to m / n multiplied the wave speed divided by the length of the plug. For example, the first resonance may occur at one quarter of the wave speed divided by the length of the plug, i.e., 1 / 4 multiplied by the wave speed divided by the length of the plug. Additional resonances may occur in the received acoustic communication signal at frequencies equal to m / 4 multiplied by the wave speed divided by the length of the plug. For example, each additional resonance may be spaced apart (periodically) in the frequency domain at frequencies corresponding to 1 / n (e.g., 1 / 4) wavelength intervals.

[0129] It may be that the periodicity of a plurality of additional frequency components is an indictor of a (genuine or verified) additional frequency component associated with the plug, and for example, may distinguish a candidate additional frequency component associated with the plug from noise.

[0130] It may be that the length of the plug corresponds to the wavelength of at least one of the identified additional frequency components. For example, the length of the plug may equal the corresponding wavelength of the additional frequency component, divided by m. For example, the length of the plug may equal the corresponding wavelength of the first, (e.g., lowest frequency) resonance (e.g., one quarter of the wave speed divided by the lowest resonance frequency).

[0131] It may be that the quality metric depends on the determined axial length. For example, the quality metric may be determined (or e.g., assigned) depending on the determined axial length of the plug. It may be that quality metric indicating a higher likelihood of plug stability, integrity or ability to prevent leakage, is determined for (or e.g., assigned to) a plug with a determined longer axial length, and vice versa.

[0132] It may be that in the methods described above, methods, 200 to 700, the one or more acoustic signals originate (e.g., are transmitted or arise) from below the plug. For example, it may be that the one or more acoustic signals comprise at least one acoustic communication signal transmitted by an acoustic communications node located in the wellbore below the plug, i.e., located in an axial direction parallel to the longitudinal axis of the wellbore below the plug. It may also be that at least one acoustic signal is received at a location above the plug i.e., located in an axial direction parallel to the longitudinal axis of the wellbore above the plug.

[0133] It may be that the methods 200, 300, 400 and 700 further comprise in blocks 202, 302, 402, 702 receiving the one or more acoustic signals. However, the methods disclosed herein are not so limited.

[0134] It may be that any of the above determinations of, or methods for determining (or assigning), the quality metric may be combined. For example, it may be that the quality metric is further determined based on a combination of quality metric indictors determined based on the axial length determination of the plug described above and at least one quality metric indicator determined based on a respective signal propagation characteristic of a received acoustic communication signal described above with respect to Figure 3 and 4.

[0135] For example, it may be that the accuracy, or reliability of the quality metric may be improved by assigning the quality metric based on more than one of the determinations (or methods) described above with respect to any of Figures 3, 4 and 7.

[0136] Figure 8 illustrates example respective received acoustic communication signals associated with different wellbore scenarios.

[0137] The received signal represented by 802 is associated with acoustic communication via a wellbore without a plug therein. The received signal represented by 804 is associated with acoustic communication via the same wellbore with a fully or partially formed plug formed therein.

[0138] The received acoustic communication signal represented by 804 illustrates that in comparison to a signal associated with a wellbore with no plug, a plurality of additional frequency components 806a, 806b are present, and detectable in the received signal associated with acoustic communication via the same wellbore with a fully or partially formed plug formed therein. It is also shown in Figure 8, that the additional frequency components 806a, 806b are periodic, i.e., they are spaced at periodic intervals (e.g., one quarter wavelengths).

[0139] It may be that an acoustic communication signal, such as any of the acoustic communication signals described above, indicates (e.g., communicates) data relating to an environmental property of the wellbore. For example, it may be that an acoustic communication signal, indicates (e.g., communicates) at least one of temperature and pressure data, such as at least one of temperature and pressure data detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore. The at least one of temperature and pressure data may provide an indication the integrity of the plug. Forexample, the presence of the plug may affect the temperature and / or pressure in the wellbore, for example, by partially or fully sealing (e.g., thermally and / or hydraulically sealing) the wellbore environment below the plug.

[0140] Figure 9 is a flow chart illustrating an example method 900. In block 904 of the example method 900, determining the quality metric comprises obtaining at least one of temperature and pressure data indicated by the at least one acoustic communication signal. The at least one of the temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore, i.e., the temperature and pressure data is detected by at least one sensor external to the plug.

[0141] It may be that the temperature and / or pressure data is indicated (or communicated) by at least one acoustic communication signal via one or more symbols. For example, the temperature and / or pressure data may be represented by (e.g., encoded in) at least one symbol of the acoustic communication signal.

[0142] It may be that obtaining the temperature and / or pressure data comprises obtaining the date from the one or more acoustic communication signals, for example, by decoding the one or more acoustic communication signals and further optionally may comprise receiving the acoustic communication signal.

[0143] It may be that determining the quality metric comprises determining the quality metric based on the temperature and / ore pressure data, e.g., based on the decoded temperature and / or pressure data.

[0144] It may be that the at least one sensor spaced apart from the plug is above or below the plug. For example, it may be that if the plug seals the wellbore, there may be a difference in temperature and pressure below the plug, as opposed to above the plug, which may provide an indication of plug quality (or integrity). For example, as a result of a plug sealing the wellbore, the temperature and / or pressure in the wellbore may be wholly or partially insulated (e.g., thermally and / or hydraulically insulated) from the temperature and / or pressure above the plug, which may vary in response to changes in temperature and / or pressure at the surface etc. The insulation by the plug may be detectable as a change in temperature and / or pressure above and below the plug. The change may be detectable as a discreet change, or as a gradient etc.

[0145] It may also be that monitoring a temperature and / or pressure either above or below the plug with time may indicate a quality of the plug, because changes with temperature and / or pressure in time below the plug, or above and proximate to the plug may indicate leakage by the plug.

[0146] As illustrated in Figure 10, it may be that the quality metric is determined based on at least one of: a single temperature or pressure data value; temperature or pressure data detected by a single sensor; a comparison of two or more temperature or pressure data values detected by a respective two or more sensors, where at least one or the sensors is disposed in the wellbore below the plug and at least one of the sensors is disposed in the wellbore above the plug, or disposed at the surface; and at least one estimate of the temperature which theplug-forming material reaches during or after the plug-formation heating process. It may be that each of these determinations for the signal propagation characteristic are included in methods 900 or 1000 alone, or in combination.

[0147] As illustrated in block 1004a the quality metric may be determined based on a single temperature or pressure data value. For example, the quality metric may be determined based on comparing a single temperature or pressure data value to a threshold value. It may be that the quality metric depends on the comparison. For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the single data value is within a pre-determined deviation from a threshold value, and a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined (or e.g., assigned) if the single data value is outside (or beyond) a pre-determined deviation from a threshold value, or vice versa.

[0148] As illustrated in block 1004b, it may be that the quality metric is determined based on temperature or pressure data detected by a single sensor. For example, it may be that a plurality of temperature or pressure data values detected from a single sensor detected at intervals separated in time may be analysed to identify a trend in the temperature or pressure in the environment surrounding the location of the sensor. It may be that the quality metric is determined based on whether a trend is detected. For example, the detected data may be analysed to identify a change or trend in time associated with a leaking plug, such as an increase or decrease in temperature or an increase or decrease in pressure. In such a case, the quality metric may depend on the identification (i.e., positive or affirmative identification) of the trend in the detected data. For example, in response to a positive identification of a change or trend associated with a leaking plug, a quality metric indicating a high likelihood of leaking, or low likelihood of sealing (i.e., a quality metric indicating a low quality plug) may be determined (or e.g., assigned). It may be that, in response to the lack of a positive identification of the change or trend, a quality metric indicating a low likelihood of leaking, or high likelihood of sealing (i.e., a quality metric indicating a high quality plug) may be determined (or e.g., assigned).

[0149] Alternatively, the data may be analysed for a trend in time associated with a sealing plug (e.g., a plug of high quality), such as a lack of change in temperature or pressure (e.g., to within a pre-determined threshold of deviation). In response to a positive identification of a trend associated with a sealing plug, a quality metric indicating a low likelihood of leaking, or high likelihood of sealing (i.e., a quality metric indicating a high quality plug) may be determined (or e.g., assigned). It may be that, in response to the lack of a positive identification of the trend, a quality metric indicating a high likelihood of leaking, or low likelihood of sealing (i.e., a quality metric indicating a low quality plug) may be determined (or e.g., assigned).

[0150] In the preceding examples relating to the determination of the quality metric based on temperature or pressure data detected by a single sensor, it may be that the single sensor islocated in the wellbore above or below the plug. Alternatively, the single sensor may be located at the surface ( e.g., 104).

[0151] As illustrated in block 1004c, it may be that the quality metric is determined based on a comparison of two or more temperature or pressure data values detected by a respective two or more sensors.

[0152] It may be that at least one of the sensors is disposed in the wellbore below the plug and at least one of the sensors is disposed in the wellbore above the plug, or disposed at the surface. For example, where at least one of the two or more sensors (i.e., plurality of sensors) is disposed in the wellbore relative to a receiver of the acoustic communication signal (e.g., node 118) such that the plug is located therebetween in an axial direction parallel to the longitudinal axis (e.g., 110) of the wellbore, the plug being above the at least one of the plurality of sensors and beneath the receiver. However, the method of block 1004c is not so limited.

[0153] It may be that as a result of a plug sealing the wellbore, a detectable pressure or temperature difference (or differential) exists in the wellbore environment across the plug.

[0154] It may be that the quality metric may be determined based on difference determined between the data detected by the respective sensors above and below the plug. It may be that the determined difference is a difference between temperature data values, or a difference between pressure data values. For example, the quality metric may depend on a measured temperature or pressure differential.

[0155] It may be that the quality metric is based on (or depends on) a comparison of the difference with respect to a threshold value (and further optionally with respect to a predetermined deviation from a threshold value). For example, it may be that a quality metric indicating that the plug has a relatively high likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively high quality) is determined (or e.g., assigned) if the difference is within a pre-determined deviation from a threshold value. Alternatively, it may be that a quality metric indicating that the plug has a relatively low likelihood of sealing or continuing to seal the wellbore (i.e., is of relatively low quality) is determined ( or e.g., assigned) if the difference is outside or beyond a pre-determined deviation from a threshold value, or vice versa.

[0156] It may be that the quality metric is determined further based on the difference determined between the data detected by the respective sensors (as described above) as a function of time. For example, it may be that the quality metric is determined based on (or depends on) whether a change or trend in the difference is identified, as described above.

[0157] It may be that the determination described above with respect to block 1004c is based on a plurality of temperature and / or pressure data values detected by a respective plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis (e.g., 110) of the wellbore. For example, respective sensors of at least a subset of the plurality of sensors may be located at increasing distances spaced apart from the plug, i.e., along the longitudinal axis of the wellbore.

[0158] It may be that the determination based on a plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore may increase the accuracy or reliability of the determination of the quality metric. For example, it may be that the plurality of temperature and / or pressure data values detected by the respective plurality of sensors distributed at different distances spaced apart from the plug provides information on a temperature or pressure gradient sensed with respect to distance from the plug (i.e., along the axial direction of the wellbore parallel to the longitudinal axis). It may be that the comparison of the two or more temperature and / or pressure data values is assessed with respect to (e.g., compared to) a pre-determined (or expected) gradient associated with a plug sealing the wellbore.

[0159] It may be that at least one of the sensors of the plurality of sensors distributed at different distances spaced apart from the plug is disposed above the below, and / or at least one of the sensors of the plurality of sensors is disposed below the plug. It may be that each of the plurality of sensors is disposed above the plug, or each of the plurality of sensors is disposed below the plug.

[0160] It may be that during the formation of the plug, heat (or thermal energy) is provided to the plug-forming material, for example by way of one or more heating elements disposed within a plug-forming material volume. The applied heat may melt the plug-forming material, such as metal or alloy (e.g., bismuth alloy) based plug-forming material, in a step of the plug-forming process. It may be that in order to fully melt the plug-forming material (i.e., to fully melt each bead or element of provided plug-forming material) such that an optimal plug is formed (for example in order to ensure a fully-formed plug, or a plug without defects or deformations is formed), the plug-forming material must be heated to a particular temperature, and for example, for a particular period of time. By estimating the temperature to which the plug-forming material is heated (i.e., the temperature which the plug-forming material reaches during the heating process), and / or estimating the thermal energy that is imparted to the plug-forming material during the heating process, a determination can be made as to whether the formation requirements of the plug have been met. A quality metric of the fully or partially formed plug may be based on (depend on) this determination, as the degree of formation achieved for the plug may impact the ability of the plug to seal the wellbore.

[0161] As illustrated in block 1004d, it may be that the quality metric is determined based on at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process based on temperature data detected by at least one temperature sensor (such as a temperature sensor disposed spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore).

[0162] It may be that the quality metric is determined based on (depending on) an estimate of the thermal energy imparted to (or gained by) the plug-forming material during or after the heating process. For example, the estimate of the thermal energy imparted to the plug-forming material may be based on (depend on) the estimate of the temperature reached by the plug-forming material during or after the heating process, the mass of the plug-forming material, and a specific heat capacity of the plug-forming material. For example, the estimate of the thermal energy imparted to the plug-forming material may be given by equation 2:

[0163] Q = Mass x Specific Heat Capacity x ^Temperature , where Q is the estimate of thermal energy gained by the plug forming material, Mass is the mass of the plug-forming material, Specific Heat Capacity is the specific heat capacity of the plug-forming material, or the specific heat capacity of the majority of the plug-forming material (if more than one material is used) and ATemperature is an estimate of a change in temperature of the plug, which may be based on at least the estimate of the temperature of the plug-forming material during or after the heating process.

[0164] It may be that ATemperature is based on (or e.g., equals) a difference between a first estimate of the temperature of the plug-forming material prior to the heating process (e.g., a background temperature estimate), and a second estimate of the temperature of the plugforming material during or after the heating process (e.g., when the maximum temperature of the plug-forming material has been reached). It may be that each of the first and second estimates is based on (e.g., equals) temperature data (values) detected by at least one sensor (and for example, the same sensor) disposed above or below the plug. It may be that the at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process, and optionally also the temperature estimate of the plugforming material before the heating process, are determined based on (depending on) a proximity of the respective sensors to the plug -forming material. For example, the temperature which the plug-forming material reaches during or after the plug-formation heating process, and optionally also the temperature estimate of the plug-forming material before the heating process, may be extrapolated from temperature data from one or more sensors disposed relative to, and spaced apart from, the plug. Alternatively, the temperature which the plugforming material reaches during or after the plug-formation heating process, and optionally also the temperature estimate of the plug-forming material before the heating process, may be interpolated from temperature data from one or more sensors disposed with the plug therebetween.

[0165] It may be that the quality metric is based on (depends on) a comparison (e.g., difference) of the estimate of the thermal energy gained by plug-forming material with a predetermined gain in thermal energy or an indication of thermal energy intended to be provided to the plug-forming material. For example, it may be that the comparison is based on (depends on) a pre-determined gain in thermal energy known (for example, from experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments) to melt (i.e. , completely melt) the plug-forming material present in the wellbore . It may be that the comparison is based on (depends on) an indication of an intended thermal energy gain based on an intended temperature which theplug-forming material is to reach that is obtained, e.g., by way of signalling (e.g., from the heating element disposed within the plug-forming material, or a controller thereof).

[0166] It may be that the quality metric of the plug is determined based on (depends on) the comparison further with respect to a threshold value and deviation therefrom. For example, it may be that if the difference between the estimated gain in thermal energy and the predetermined gain in thermal energy deviates from a threshold value by more than a predetermined deviation value, a quality metric indicating that the plug is partially formed, for example as a result of not being sufficiently heated to melt the plug-forming material, may be determined (or e.g., assigned).

[0167] It may be that the quality metric is determined based on (depends on) the estimate of the temperature reached by the plug-forming material, or the gain in thermal energy of the plugforming material as a function of time. For example, it may be that the quality metric of the plug is determined depending on how long the plug-forming material is heated.

[0168] It may be that determining the quality metric further comprises utilising a Thermal Finite Element Analysis (FEA) for estimating the thermal energy gained by the plug-forming material based on the estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process. A Thermal FEA analysis may be performed when the plug-forming material comprises a plurality of materials having different one or more of different specific heat capacities or mass contributions to the total mass of the plug-forming material.

[0169] It may be that the quality metric is determined based on (depending on) at least one estimate of the temperature which the plug-forming material reaches during or after the plugformation heating process based on temperature data detected by a single temperature sensor (such as a temperature sensor disposed spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore). Additionally, it may be that the first estimate of the temperature of the plug-forming material prior to the heating process (e.g., a background temperature estimate), and a second estimate of the temperature of the plug-forming material during or after the heating process may be based on (depend on) temperature data from a single sensor.

[0170] Alternatively, it may be that the accuracy or reliability of the at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process, and thus the estimate of the thermal energy gained by the plug-forming material may be improved by determining the estimate of the temperature reached by the plugforming material (and optionally, additionally the estimate of the temperature of the plugforming material prior to the heating process) based on (depending on) temperature data detected (or sensed) by a plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis (e.g., 110) of the wellbore. For example, respective sensors of at least a subset of the plurality of sensors may be located at increasing distances spaced apart from the plug, i.e., along the longitudinal axis of thewellbore. It may be that the plurality of temperature data values detected by the respective plurality of sensors distributed at different distances spaced apart from the plug provides information on a temperature gradient sensed with respect to distance from the plug (i.e. , along the axial direction of the wellbore parallel to the longitudinal axis).

[0171] It may be that at least one of the sensors of the plurality of sensors is disposed above the below, and / or at least one of the sensors of the plurality of sensors is disposed below the plug. It may be that each of the plurality of sensors is disposed above the plug, or each of the plurality of sensors is disposed below the plug.

[0172] It may be that the plurality of temperature data values (and e.g., temperature gradient information) improves the accuracy of the interpolation or extrapolation of the temperature of the plug-forming material from the detected temperature data. It may be that the number of sensors distributed along the longitudinal axis of the wellbore is greater than one, and for example, not more than 100. It may be that at least 5, 10, 12, 15 or 20 sensors are distributed along the longitudinal axis of the wellbore.

[0173] It may be that the response of each of the plurality of sensors to a given (predetermined) thermal energy input (e.g., from a heating element disposed within the plugforming material, or for at least one further heating element disposed within the wellbore, for example, spaced apart from the plug) may be used to form a model (e.g., based on a response function) of the thermodynamic properties of the wellbore environment, e.g., the wellbore environment surrounding, or proximate to, the plug. It may be that the estimate of the temperature reached by the plug-forming material based on the detected temperature data, and / or the estimate of the thermal energy gained by the plug-forming material based on the temperature estimate of the plug-forming material reached during or after the heating process of the plug-formation process may be further based on the determined model. For example, the estimate of the temperature of the plug-forming material reached during or after the heating process from the temperature sensor data may depend on the temperature sensor data and the model of the thermodynamic properties of the wellbore environment.

[0174] It may be that at least one of the plurality of sensors distributed at different distances spaced apart from the plug is positioned spaced apart from at least a second sensor of the plurality of sensors in a second dimension of the wellbore different to the dimension defined by (e.g., aligned with) the longitudinal axis (e.g., 110) of the wellbore (e.g., 102).

[0175] For example, the at least one sensor may be spaced apart from at least a second sensor of the plurality of sensors along a further axis (e.g., 112, 116) of the wellbore, different to the longitudinal axis (e.g., 110, 114) of the wellbore (e.g., 102).

[0176] It may be that distributing at least one of the plurality of sensors spaced apart in an additional dimension with respect to the remaining plurality of sensors provides at least 2- dimensional information relating to the wellbore volume and the thermodynamic properties thereof, which may increase the accuracy or reliability of the plug-forming material temperature and thermal energy gain estimate.

[0177] It may be that the number of sensors distributed along the longitudinal axis of the wellbore is greater than one, and for example, not more than 100 and the number of sensors distributed along a second axis of the wellbore is greater than one, and for example, not more than 100.

[0178] It may be that at least 5, 10, 12, 15 or 20 sensors are distributed along the longitudinal axis (e.g., 114) of the wellbore and at least 1 , 2, 5, 10, 12, 15 or 20 sensors are distributed along a second or third axis (e.g., 112, 116) of the wellbore.

[0179] It may be that at least a first sensor of the plurality of sensors distributed at different distances spaced apart from the plug is positioned spaced apart from at least a second sensor of the plurality of sensors in a second dimension of the wellbore different to the dimension defined by (e.g., aligned with) the longitudinal axis (e.g., 110) of the wellbore (e.g., 102), and a third sensor of the plurality of sensors is spaced apart from at least the first and second sensor in a third dimension different from the first and second dimensions.

[0180] For example, it may be that at least a subset of the plurality of sensor is distributed spaced apart in three (different) dimensions (or along 3 different axes, e.g., 112, 114, 116) of the wellbore. It may be that the three-dimensional spacing of the plurality of sensors provides 3-dimensional information relating to the wellbore volume and the thermodynamic properties thereof, which may further increase the accuracy or reliability of the plug-forming material temperature and thermal energy gain estimate.

[0181] It may be that the number of sensors distributed along the longitudinal axis of the wellbore is greater than one, and for example, not more than 100, the number of sensors distributed along a second axis of the wellbore is greater than one, and for example, not more than 100 and the number of sensors distributed along a third axis of the wellbore is greater than one, and for example, not more than 100 .

[0182] It may be that at least 5, 10, 12, 15 or 20 sensors are distributed along the longitudinal axis (e.g., 114) of the wellbore, at least 1 , 2, 5, 10, 12, 15 or 20 sensors are distributed along a second axis (e.g., 112) of the wellbore and at least 1 , 2, 5, 10, 12, 15 or 20 sensors are distributed along a third axis (e.g.,116) of the wellbore.

[0183] It may be that each of the respective sensors is spaced apart in a respective dimension (or along a respective axis) of the wellbore. It may be that one or more sensors distributed spaced apart in a first dimension may be overlapping in a second and / or in a third dimension.

[0184] It may be that respective sensors of the plurality of sensors are uniformly spaced apart in at least one dimension of the wellbore (e.g., along the longitudinal axis). It may be that the distribution of respective sensors is one sensor per cubic inch (1 sensor per cubic 2.5 centimeters) of the wellbore volume.

[0185] It may be that the density of sensors in at least one dimension of the wellbore may be higherwith increasing proximity to the plug.

[0186] It may be that the determination of the quality metric based on at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process illustrated in block 1004d, further comprises determining a mass of plugforming material present in the wellbore. For example, determining a mass of the plug-forming material (prior to the plug-forming process) based on data obtained from e.g., a force sensor. It may be that the determination of the mass is more accurate than an expected mass of plugforming material, for example it may be that an expected mass of plug-forming material is not fully disposed down the wellbore, for example due to loss of material during the depositing etc.,. It may be that using a determined mass for the calculation shown in equation 2, e.g., as opposed to a pre-determined or expected mass, may provide a more accurate estimate of the thermal energy transferred to the plug-forming material and may provide a more accurate quality metric.

[0187] The mass of the plug-forming material may be determined based on data obtained from a force sensor, such as any force sensor known in the art, including but not limited to a resistive force sensor, strain gauge (such as a metal-based strain gauge, or a semiconductorbased strain gauge), quartz force sensor etc. It may be that a resistive force sensor or strain gauge is advantageous for sensing a static force or forces, and a quartz force sensor is advantageous for sensing non-static or quasi-static forces, e.g., oscillating forces, and compression or tension under varying conditions, such as high speed impact compression.

[0188] It may be that determining the quality metric comprises determining a mass of plugforming material based on data obtained from a force sensor and determining an estimate of the thermal energy gained by the plug forming material, i.e. , Q in equation 2, based on the mass determined based on data obtained from a force sensor.

[0189] It may be that the mass is determined further based on an estimate of the inclination of the longitudinal axis of the wellbore. For example, it may be that the determination of the quality metric based on at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process illustrated in block 1004d, further comprises determining an inclination of the wellbore. For example, determining an inclination based on data obtained from an inclinometer. For example, determining an inclination of the longitudinal axis (e.g., 110) of the wellbore with respect to the direction of gravity.

[0190] For example, it may be that if the longitudinal axis of the wellbore is inclined with respect to gravity, the mass determined based on a data from a force sensor (i.e., the mass determined from a sensed force associated with depositing of the plug-forming material), may not be accurate.

[0191] It may be that mass determined based on a data obtained from a force sensor (i.e., the mass determined from a sensed force associated with depositing of the plug-forming material) is further based on a sensed inclination (from an inclinometer). For example, the determined mass (used in equation 2) may equal the sensed force divided by an acceleration, where theacceleration is equal to the acceleration under gravity multiplied by the cosine of the sensed inclination, i.e. , F = ma anda“ Scos(i), where F is the force sensed by the force sensor, m is the mass of the plug-forming material deposited in the wellbore, g is the acceleration due to gravity ( given by the standard value of 9.8 m / s2) and i is the detected (or sensed) inclination of the longitudinal axis of the wellbore with respect to gravity.

[0192] It may be that the quality metric, and / or estimate of the thermal energy gain, for example based on equation 2, is alternatively, or additionally modified in respect of a force profile sensed by the force sensor.

[0193] For example, the quality metric may be based on a sensed force profile across at least a portion of the force sensor to account for an uneven distribution of mass of plug-forming material in the wellbore, which may affect how the plug-forming material is heated and subsequently re-solidified. For example, the quality metric may be determined ( e.g., assigned) based on a sensed force profile in combination with at least one reference measurement and an estimate of the thermal energy gained by the plug forming material (using equation 2). For example, it may be that a quality metric indicating a lower plug quality is assigned to a plug when the sensed force profile indicates a more uneven distribution of plug-forming material, as opposed to an even distribution of material, for a given determined Q. This may take into account that an uneven distribution of plug-forming material has a lower likelihood of being evenly melted and fully formed, and may thus form a plug of lower quality.

[0194] Alternatively, it may be that the quality metric of a cement-based plug, or plug formed of any other suitable material that does not require heating, may be determined based on the force sensor and / or inclinometer data as described above but without the calculation of thermal energy. For example it may be that a quality metric indicator of such a plug is the mass determination and / or inclination determination alone. It may be that the quality metric is assigned based on a deviation of a determined mass and / or inclination from an expected value. For example, to take into account the effects of plug formation (e.g., curing) of plug-forming material that deviates from an expected mass, or an expected, e.g., uniform distribution of plugforming material.

[0195] It may be that method 900 or method 1000 further comprises, responsive to the determined quality metric, generating a control signal. For example, generating a control signal based on (depending on) the determined quality metric, the control signal to be provided to a controller associated with the plug or plug-forming material thereof.

[0196] It may be that the control signal is configured to be provided to at least one heating element disposed within the plug-forming material, or partially formed plug, or a controller thereof. The control signal may be configured to provide further heating by the at least one heating element, or to terminate heating by the at least one heating element. Alternatively, the control signal may be configured to be provided to second (back-up) heating element disposed within the plug-forming material of the plug, or partially formed plug, or within additional plugforming material disposed above the plug (e.g., for repairing the plug), or a controller thereof.The control signal may be configured to provide further heating by the at least second heating element.

[0197] It may be that the method 900 or 1000 further comprises providing the control signal to a controller associated with the plug or plug-forming material. For example, by providing the control signal by way of a transmitter.

[0198] The methods disclosed above may be particularly beneficial for establishing plug quality, for example during or shortly after plug formation. However, they are not so limited, and may also be beneficial for monitoring plug quality or for initiating plug repair.

[0199] It may be that any of the above determinations of, or methods for determining (or assigning), the quality metric may be combined. For example, it may be that any of the methods for determining the quality metric based on one of temperature and pressure data indicated by at least one acoustic communication signal described with respect to Figures 9 and 10 may be combined. It may be that the quality metric is determined based on a combination of quality metric indictors determined based on one of temperature and pressure data indicated by at least one acoustic communication signal and at least one of the axial length determination of the plug described above with respect to Figure 7 and / or at least one quality metric indicator determined based on a respective signal propagation characteristic of a received acoustic communication signal described above with respect to Figure 3 and 4.

[0200] For example, it may be that the accuracy, or reliability of the quality metric may be improved by assigning the quality metric based on more than one of the determinations (or methods) described above with respect to any of Figures 3, 4, 7, 9 and 10.

[0201] As described above, it may be that the one or more acoustic signals relating to a fully or partially formed plug in a wellbore, on which the obtained at least one signal is based, comprises an environmental acoustic signal. It may be that the environmental acoustic signal is not actively transmitted by an acoustic communication node, and may originate from, or as a result of, an event in the wellbore, such as cracking of the plug, movement of the plug, or other such mechanisms relating to the plug by which an acoustic signal arises, or is emitted.

[0202] It may be that determining the quality metric based on at least one environmental acoustic signal has the advantage that it does not require power for the transmission of the acoustic signal upon which the determination is based, for example, as opposed to a determination based on an acoustic communication signal. It may be that a determination of the quality metric based on an environmental acoustic signal is advantageous when power to an acoustic communications node (e.g., node 118) configured to transmit an acoustic communication signal is limited or depleted. This may be the case for nodes disposed in the wellbore below the plug, which may become depleted over time, and close to, or at the end of their lifetime may no longer have sufficient power to transmit an acoustic communication signal. Thus, the methods disclosed below may be particularly beneficial for monitoring (e.g., long-term monitoring) plug quality.

[0203] Figure 11 is a flow chart illustrating an example method 1100. In block 1100 of the example method 1100, determining the quality metric based on the received at least one signal comprises detecting a change in at least one environmental acoustic signal that is a indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug. It may be that the change in a structural property comprises a change in the structural integrity of the plug, for example, a formation or expansion of a crack or deformation in the plug.

[0204] It may be that the detected indicator is a direct indicator of change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug. For example, the detection of the indicator, i.e., the presence of the indicator, may directly indicate the change in a structural property of change in location of the plug, i.e., without requiring an inference of the change from the presence of the indicator. For example, the indicator my be a primary indicator of the change, as opposed to a secondary indicator of the change.

[0205] It may be that the environmental acoustic signal is detected by at least one accelerometer. For example, at least one accelerometer disposed in the wellbore above the plug, or at the surface.

[0206] It may be that the at least one accelerometer is configured to detect vibration resulting from the propagation of the environmental acoustic signal. For example, the accelerometer may be disposed in the wellbore to detect a vibration (i.e., resonance of) a solid acoustic conductor (such as solid acoustic conductor 106), or to detect a vibration in a fluid acoustic conductor such as a liquid (e.g., a liquid disposed in the wellbore above the plug, such as water) or a gas (e.g., air).

[0207] As described above, it may be that the quality metric is determined based on data detected by a plurality of acoustic conductors, such as acoustic conductors distributed along at least one axis of the wellbore, or along more than one axis (i.e., distributed along at least 2 axes, or along 3 axes) of the wellbore.

[0208] It may be that determining the quality metric based on (depending on) detecting a change in the at least one environmental acoustic signal comprises detecting a pre-defined signature in the environmental acoustic signal, wherein the pre-defined signature relates to plug movement or a change in a plug structural property. For example, it may be that the detected environmental acoustic signal, or at least a portion thereof, is compared to a library of environmental acoustic signals comprising pre-defined signatures, or portions of environmental acoustic signals comprising pre-defined signatures to detect the pre-defined signature. For example, the pre-defined signature may be an environmental acoustic signal signature captured responsive to a known plug movement event or a known change in a plug structural property event. For example, it may be that the pre-defined signature and library thereof are acquired from experimental results (such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments), such as viadetection of an acoustic signal emitted in response to a triggered, predicted or otherwise expected or monitored plug movement or change in a structural property of a plug event.

[0209] It may be that the identification of the pre-defined signature in the environmental acoustic signal comprises performing a cross-correlation with the library of pre-defined signatures, or at least a subset of the library.

[0210] Alternatively, it may be that the pre-defined signature is identified by a machine learning algorithm (e.g., a trained machine learning algorithm, for example with trained weights and / or hyper-parameters). For example, a machine learning algorithm trained based on training data to identify a signature from within an environmental acoustic signal associated with a plug movement event, or a change in plug structural property event.

[0211] It may be that the method further comprises associating the environmental acoustic signal, or portion thereof, with a specific event (such as a specific plug movement or specific change in plug structural property) or type of event based on the identification of the predefined signature, and a pre-defined mapping between the signature and at least one specific event, or type thereof.

[0212] It may be that a machine learning algorithm provides as output one or more respective probabilities of an environmental acoustic signal comprising one or more pre-defined signatures associated with specific events, or types of events.

[0213] It may be that the method further comprises training the machine learning algorithm. For example, training the machine learning algorithm based on experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments.

[0214] It may be that the quality metric is determined (or assigned) depending on the whether one of the pre-defined signatures is detected, and / or on an association of an identified signature in the signal with a specific event or type of event.

[0215] It may be that any of the above determinations of, or methods for determining (or assigning), the quality metric may be combined. For example, it may be that any of the methods for determining the quality metric based on an environmental acoustic signal may be combined. It may be that the quality metric is determined based on a combination of quality metric indictors determined based on an environmental acoustic signal described above with respect to Figure 11 and any of the methods for determining the quality metric based on one of temperature and pressure data indicated by at least one acoustic communication signal described with respect to Figures 9 and 10 may be combined, and / or any of the methods for determining the quality metric based at least one of the axial length determinations of the plug described above with respect to Figure 7 and / or at least one quality metric indicator determined based on a respective signal propagation characteristic of a received acoustic communication signal described above with respect to Figure 3 and 4.

[0216] For example, it may be that the accuracy, or reliability of the quality metric may be improved by assigning the quality metric based on more than one of the determinations (or methods) described above with respect to any of Figures 3, 4, 7, 9, 10 and 11 .

[0217] It may be that any of the above determinations of, or methods for determining (or assigning), the quality metric may be combined. For example, it may be that the accuracy, or reliability of the quality metric may be improved by assigning the quality metric based on more than one of the determinations (or methods) described above. For example, it may be that the accuracy and / or reliability of the quality metric is improved by combining a plurality of different, and for example, independent, quality metric indicators.

[0218] Figure 12 is a flow chart illustrating an example method 1200. In block 1204 of the example method 1200, determining the quality metric based on the received at least one signal is based on a weighted combination of a plurality of quality metric indicators determined based on one or more of the acoustic signals.

[0219] It may be that the quality metric indicators comprise any of the determinations (or methods) described above with respect to Figures 3, 4, 7, 9, 10 and 11.

[0220] It may be that at least one of the quality metric indicators may be based on any of the determinations (or methods) described herein based on an acoustic communication signal. For example, any of the determinations described above with respect to Figures 3, 4, 7, 9 or 10.

[0221] It may be that at least one of the quality metric indicators may be based on any of the determinations (or methods) described herein based on an environmental acoustic signal. For example, any of the determinations (or methods) described above with respect to Figure 11 .

[0222] It may be that the weighted combinations of quality metric indicators comprises any combination of the determinations (or methods) described herein based on an acoustic communication signal, for example, any combination of the determinations (or methods) described above with respect to Figures 3, 4, 7, 9 or 10.

[0223] It may be that the weighted combinations of quality metric indicators comprises any combination of the determinations (or methods) described herein based on an environmental acoustic signal, for example, any combination of the determinations (or methods) described above with respect to Figure 11 .

[0224] It may be that the he weighted combinations of quality metric indicators comprises any combination of the determinations (or methods) described herein based on an acoustic communication signal with the determinations described herein based on an environmental acoustic signal. For example, any combination of the determinations described above with respect to Figures 3, 4, 7, 9 or 10 in combination with any of the determinations described above with respect to Figure 11 .

[0225] It may be that the combination of quality metric indicators is determined by a machine learning algorithm. For example, it may be that the selection of the determinations (or methods) for quality metrics to be combined is determined by a machine learning algorithm.

[0226] It may be that respective weightings of the quality metric indictors of the combination of quality metric indicators is determined by a machine learning algorithm.

[0227] It may be that the method further comprises training the machine learning algorithm. For example, training the machine learning algorithm based on experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments.

[0228] As used herein the term machine learning algorithm may include, but is not limited to, e.g., supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning. The machine learning algorithm may be an artificial intelligence model, such as an artificial neural network including a plurality of artificial neural network layers. The artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), deep Q-network or a combination of two or more thereof but is not limited thereto. The machine learning algorithm, or artificial intelligence model, may be trained based on training data. For example, based on experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments.

[0229] An apparatus comprising processing circuitry configured to perform any of, or any combination of the methods disclosed herein is illustrated in Figure 13.

[0230] The apparatus 1302 comprises processing circuitry 1304 configured to obtain at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore, determine a quality metric of the fully or partially formed plug based on the received at least one signal and provide an indication of the determined quality metric.

[0231] As described above, it may be that at least one of the one or more acoustic signals is transmitted by propagation via a solid acoustic conductor in acoustic communication with the fully or partially formed plug.

[0232] As also described above, it may be that at least one of the acoustic signals comprises an acoustic communication signal actively transmitted by an acoustic communications node, or at least one of the acoustic signals comprises an environmental acoustic signal.

[0233] It may be that the processing circuitry is configured to determine a respective signal propagation characteristic of at least one of the one or more acoustic communication signals. For example, the determined signal propagation characteristic may be an indicator of a damping of the acoustic conductor depending on the plug, as described above.

[0234] It may be that the processing circuitry is configured to determine the signal propagation characteristic based on at least one of: a peak and / or trough counting analysis of the acoustic communication signal; a determination of a Q-factor of the acoustic communication signal; and a frequency response of the acoustic communication signal. It may be that the processing circuitry is configured to perform a determination of the signal propagation characteristic as described above with respect to Figures 3 and 4.

[0235] It may be that the processing circuitry is configured to determine an axial length of the fully or partially formed plug based on determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals, wherein the axial length is parallel to a longitudinal axis of the wellbore. For example, it may be that the processing circuitry is configured to perform a determination of the axial length of the plug as described above with respect to Figure 7.

[0236] It may be that the processing circuitry is configured to determine the quality metric based on at least one of temperature and pressure data indicated by the at least one acoustic communication signal, wherein the at least one of temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore. For example, it may be that the processing circuitry is configured to perform a determination of quality metric based on at least one of temperature and pressure data indicated by the at least one acoustic communication signal, as described above with respect to Figure 9 or 10. For example, it may be that the at least one of temperature and pressure data comprises a plurality of temperature and / or pressure data detected by a respective plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore. It may be that at least one of the plurality of sensors is disposed in the wellbore relative to a receiver of the acoustic communication signal such that the plug is located therebetween in an axial direction parallel to the longitudinal axis of the wellbore, the plug being above the at least one of the plurality of sensors and beneath the receiver.

[0237] It may be that the processing circuitry is configured to determine the quality metric based on detecting a change in at least one environmental acoustic signal that is an indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug. For example, it may be that the processing circuitry is configured to perform a determination of quality metric based on detecting a change in at least one environmental acoustic signal that is an indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug, as described above with respect to Figure 11 .

[0238] For example, it may be that the indicator is a direct indicator of change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug. It may be that the processing circuitry is configured to determine the quality metric based on detecting a change in at least one environmental acoustic signal, where the environmental acoustic signal is detected by at least one accelerometer.

[0239] For example, it may be that the processing circuitry is configured to detect a predefined signature in the environmental acoustic signal, wherein the pre-defined signature relates to plug movement.

[0240] It may be that processing circuitry is configured to determine the quality metric based on, or based on generating, a weighted combination of a plurality of quality metric indicatorsdetermined based on one or more of the acoustic signals. For example, it may be that the processing circuitry is configured to determine quality metric based on a weighted combination of a plurality of quality metric indicators as described above with respect to Figure 12.

[0241] It may be that the apparatus further comprises at least one of receiving circuitry (e.g., a receiver) and transmitting circuitry (i.e., a transmitter). For example, a receiver configured to receive the at least one acoustic signal. For example, a transmitter, to transmit a generated control signal.

[0242] It may be that at least one of the transmitting or receiving circuitry is further configured to communicate with one or more servers.

[0243] It may be that the processing circuitry include a main processor (e.g., a central processing unit (CPU) or an application processor (AP)), and optionally an auxiliary processor (e.g., a graphics processing unit (GPU), a neural processing unit (NPU) that is operable independently from, or in conjunction with, the main processor. For example, when the processing circuity includes the main processor and the auxiliary processor, the auxiliary processor may be adapted to consume less power than the main processor, or to be specific to a specified function. The auxiliary processor may be implemented as separate from, or as part of the main processor. For example, the processing circuitry (for example, the auxiliary processor) (or e.g., a neural processing unit thereof) may include a hardware structure configured to perform machine learning. Such learning may be performed by the processing circuitry, or performed via a separate server with which the processing circuitry is configured to communicate.

[0244] It may be that a trained machine learning algorithm is stored in memory coupled to the processing circuitry of the apparatus disclosed herein (e.g., apparatus 1302). It may be that the apparatus further comprises the memory. Alternatively, the memory may be remote from but communicatively coupled to the apparatus, or the processing circuity thereof. It may be that the processing circuitry is configured to execute the trained machine learning algorithm. Alternatively, it may be that the processing circuitry is configured to communicate with a server (such a centralized server) having the trained machine learning model stored and / or executable thereon, such that inputs to the trained algorithm are sent from the processing circuitry to the server, and outputs from the trained algorithm executed on the inputs are sent from the server to the processing circuitry.

[0245] A kit of parts is illustrated in Figure 14. The kit of parts 1400 comprises the apparatus described above (apparatus 1302) and at least one of: an acoustic communication node configured to at least receive acoustic signals 1402, an acoustic communication node configured to at least transmit acoustic communication signals 1404, a pressure and / or temperature 1406, an accelerometer 1408, an inclinometer 1410, a force sensor 1412.

[0246] The various methods and operations performed by the apparatus disclosed herein can be implemented in various forms, or combinations of hardware, software, firmware, and / or special purpose processors. For example, it may be that the methods disclosed herein may beimplemented by processing circuitry. It may be that the processing circuitry described herein may be general purpose processing circuitry (e.g., at least one processor or microprocessor) configured to implement software, gate level logic such as a field-programmable gate array (FPGA), a purpose-built semiconductor such as an application-specific integrated circuit (ASIC), integrated circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), logic gates, registers, semiconductor devices and the like.

[0247] Configuration of the processing circuitry to perform a specified function may be entirely in hardware, entirely in software or using a combination of hardware modification and software execution.

[0248] Instructions (such as program instructions) may be used to configure logic gates of general purpose or special-purpose processing circuitry to perform a processing function. For example, the methods disclosed herein may be implemented as machine (or computer) 1502 as illustrated in Figure 15.

[0249] The aforementioned instructions may be provided on at least one machine (or computer) readable medium. For example, as illustrated in Figure 16, machine readable instructions 1604 may be provided, or stored, on machine (or computer) readable medium 1602.

[0250] For example, at least one machine (or computer) readable medium may comprise instructions which, when executed, implement the methods disclosed herein. For example, the at least one machine (or computer) readable medium may comprise instructions which, when executed by processing circuitry (e.g., at least one processor), cause the processing circuitry to implement the methods disclosed herein.

[0251] It may be that the medium is a transitory, e.g., transmission medium, or non-transitory, e.g., storage medium.

[0252] The aforementioned machine readable medium may be any suitable medium for storing digital information, such as a hard drive, a server, a flash memory, and / or randomaccess memory (RAM), a compact disc read only memory (CD-ROM), or a combination of memories.

[0253] It may be that an apparatus disclosed herein comprises processing circuitry and memory coupled to the processing circuitry. It may be that the memory stores the machine readable instructions disclosed herein.

[0254] In the preceding, it has been disclosed that the acoustic signal may be an acoustic communication signal. It may be that the acoustic communication signal comprises symbols representing, or encoding, data. For example, representing or encoding the detected temperature and / or pressure data, data relating to other wellbore environment parameters, or pre-determined data (e.g., calibration data). It may be that the methods disclosed above comprising determining a signal propagation characteristic are performed on one or more acoustic communication signals communicating temperature and / or pressure data, data relating to other wellbore environment parameter or calibration data.

[0255] It may be that the acoustic communication signal is a frequency varying signal. For example, the acoustic communication signal may comprise one or more symbols represented by a tone, sweep or chirp within a frequency passband. It may be that the acoustic communication signal is generated via a spread spectrum technique. It may be that the frequency passband of the acoustic communication signal is between 1 Hz and 100kHz. For example, the frequency passband of the acoustic communication signal may be between 400Hz and 4kHz. It may be that the acoustic communication signal has a duration in time of between 1 second and 10 seconds, for example 6 seconds.

[0256] It may be that the acoustic communication signal comprises one or more symbols (or tones) spaced apart in a frequency interval, i.e. , spaced apart so as to be discrete. It may be that the one or more symbols are located in the frequency passband (i.e., over a relatively wide frequency range) in an un-correlated manner with respect to frequency and time, for example randomly or pseudo-randomly with respect to frequency and time (e.g., the acoustic communication signal is a broad-band signal).

[0257] It may be that the one or more symbols are periodically sequentially (i.e., as a function of time and frequency) located in the frequency passband (e.g., the acoustic communication signal is a chirp signal or a sweep signal) . It may be that the sequence is linear (i.e., the rate of change in frequency of the signal is linear with time) or it may be that the sequence is stepped (i.e., the rate of change in frequency of the signal is stepped with time).

[0258] It may be advantageous for the methods described above based on communication of temperature and / or pressure data to be performed with respect to (i.e., performed on) a broadband acoustic communication signal. It may also be advantageous for the signal propagation characteristic methods disclosed herein to be performed with respect to (i.e., performed on) chirp or sweep acoustic communication signals. However, the methods disclosed herein are not so limited.

[0259] In this application, the phrase “at least one of A or B” and the phrase “at least one of A and B” should be interpreted to mean any one or more of the plurality of listed items A, B, etc., taken jointly and severally in any and all permutations.

[0260] It is not intended that the order in which the methods are described in this application is to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the methods or an alternate method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein.

[0261] Within the scope of this application it is expressly intended that the various examples and alternatives set out in the preceding paragraphs, in the claims and / or in the description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all examples and / or features of any example can be combined in any way and / or combination, for example it may be that apparatus features correspond to method features or vice versa, unless such features are incompatible.

[0262] In the above description, for purposes of explanation, specific examples and details thereof are set forth in order to better explain the present invention, as claimed. It is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed examples, but, on the contrary, are intended to cover modifications and equivalents that are within the scope of the disclosed examples.

[0263] It will be apparent to one skilled in the art that the claimed invention may be practiced using different details than the exemplary ones described herein. Other examples may incorporate structural, logical, method, and other changes. Portions and features of some examples may be included in, or substituted for, those of other examples. In other instances, well-known features are omitted or simplified to clarify the description of the examples.

[0264] The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and / or incorporate any feature of any other claim although not originally claimed in that manner.

[0265] The disclosure also extends to the following examples.

[0266] Example 1 . A method comprising: obtaining at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore; determining a quality metric of the fully or partially formed plug based on the received at least one signal; and providing an indication of the determined quality metric.

[0267] Example 2. The method of example 1 , wherein at least one of the one or more acoustic signals is transmitted by propagation via at least a solid acoustic conductor in acoustic communication with the fully or partially formed plug.

[0268] Example 3. The method of example 1 or example 2, wherein at least one of the acoustic signals comprises an acoustic communication signal actively transmitted by an acoustic communications node, or at least one of the acoustic signals comprises an environmental acoustic signal.

[0269] Example 4. The method of example 2 and example 3, wherein determining the quality metric comprises determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals.

[0270] Example 5. The method of example 4, wherein the determined signal propagation characteristic is an indicator of a damping of the acoustic conductor depending on the plug.

[0271] Example 6. The method of example 4 or example 5, wherein the signal propagation characteristic is based on at least one of: a peak and / or trough counting analysis of the acoustic communication signal; a determination of a Q-factor of the acoustic communication signal; a frequency response of the acoustic communication signal.

[0272] Example 7. The method of example 4, wherein determining the quality metric comprises determining an axial length of the fully or partially formed plug based on determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals, wherein the axial length is parallel to a longitudinal axis of the wellbore.

[0273] Example 8. The method of example 3, wherein determining the quality metric comprises obtaining at least one of temperature and pressure data indicated by the at least one acoustic communication signal, wherein the at least one of temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

[0274] Example 9. The method of example 8, wherein determining the quality metric comprises at least one of: a single temperature or pressure data value; temperature or pressure data detected by a single sensor; a comparison of two or more temperature or pressure data values detected by a respective two or more sensors, where at least one or the sensors is disposed in the wellbore below the plug and at least one of the sensors is disposed in the wellbore above the plug, or disposed at the surface; and at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process.

[0275] Example 10. The method of example 9, wherein the determining the quality metric comprises estimating a thermal energy gained by the plug-forming material (e.g., imparted to the plug-forming material during the heating process) based at least on the at least one estimate of the temperature which the plug-forming material reaches during or after the plugformation heating process.

[0276] Example 11 . The method of example 10, wherein the estimate of the thermal energy gained by the plug-forming material is further based on at least one of: an estimate of the mass of plug-forming material in the wellbore and an inclination of longitudinal axis of the wellbore with respect to the direction of gravity.

[0277] Example 12. The method of any one of examples 8 to 11 , wherein the at least one of temperature and pressure data comprises a plurality of temperature and / or pressure data detected by a respective plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

[0278] Example 13. The method of example 12, wherein at least one of the plurality of sensors is disposed in the wellbore relative to a receiver of the acoustic communication signal such that the plug is located therebetween in an axial direction parallel to the longitudinal axis of the wellbore, the plug being above the at least one of the plurality of sensors and beneath the receiver.

[0279] Example 14. The method of example 3, wherein determining the quality metric based on the received at least one signal comprises detecting a change in at least one environmental acoustic signal that is a indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

[0280] Example 15. The method of example 14, wherein the indicator is a direct indicator of change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

[0281] Example 16. The method of example 14 or example 15, wherein the environmental acoustic signal is detected by at least one accelerometer.

[0282] Example 17. The method of any of the examples 14 to 16, wherein determining the quality metric comprises detecting a pre-defined signature in the environmental acoustic signal, wherein the pre-defined signature relates to plug movement or a change in a plug structural property.

[0283] Example 18. The method of example 17, wherein the detecting of the pre-defined signature in the environmental acoustic signal is performed by a machine learning algorithm.

[0284] Example 19. The method of any of the preceding examples, wherein determining the quality metric based on the received at least one signal is based on a weighted combination of a plurality of quality metric indicators determined based on one or more of the acoustic signals.

[0285] Example 20. The method of example 19, wherein at least one of the plurality of quality metric indicators is determined based on at least one acoustic communication signal and the quality metric indicator is determined according to any one of examples 4 to 13.

[0286] Example 21 . The method of example 19 or example 20, wherein at least one of the plurality of quality metric indicators is determined based on at least one environmental acoustic signal and the quality metric indicator is determined according to any one of examples 14 to 18.

[0287] Example 22. The method of any one of examples 19 to 21 , wherein the selection of the combination of quality metric indicators and / or the determination of the weightings of the respective quality metric indicators of the combination of quality metric indicators is performed by a trained machine learning algorithm.

[0288] Example 23. The method of example 18 or example 22, wherein the method further comprises training the machine learning algorithm. For example, training the machine learning algorithm based on experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments.

[0289] Example 24. The method of any of the preceding examples, wherein the method further comprises generating a control signal based on the determined quality metric, the control signal to be provided to a controller associated with the plug or plug-forming material thereof.

[0290] Example 25. Machine readable instructions, which when executed by processing circuitry cause the processing circuitry to perform the method of any one of claims 1 to 24.

[0291] Example 26. A machine readable medium having the machine readable instructions of example 25 stored thereon.

[0292] Example 27. An apparatus comprising processing circuitry, the processing circuitry configured to: obtain at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore, determine a quality metric of the fully or partially formed plug based on the received at least one signal, and provide an indication of the determined quality metric.

[0293] Example 28. The apparatus of example 27, wherein at least one of the one or more acoustic signals is transmitted by propagation via at least a solid acoustic conductor in acoustic communication with the fully or partially formed plug.

[0294] Example 29. The apparatus of example 27 or 28, wherein at least one of the acoustic signals comprises an acoustic communication signal actively transmitted by an acoustic communications node, or at least one of the acoustic signals comprises an environmental acoustic signal.

[0295] Example 30. The apparatus of example 28 and example 29, wherein the processing circuitry is configured to determine a respective signal propagation characteristic of at least one of the one or more acoustic communication signals.

[0296] Example 31 . The apparatus of example 30, wherein the determined signal propagation characteristic is an indicator of a damping of the acoustic conductor depending on the plug.

[0297] Example 32. The apparatus of example 30 or example 31 , wherein the signal propagation characteristic is based on at least one of: a peak and / or trough counting analysis of the acoustic communication signal; a determination of a Q-factor of the acoustic communication signal; a frequency response of the acoustic communication signal.

[0298] Example 33. The apparatus of example 30, wherein the processing circuitry is configured to determine an axial length of the fully or partially formed plug based on determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals, wherein the axial length is parallel to a longitudinal axis of the wellbore.

[0299] Example 34. The apparatus of example 29, wherein the processing circuitry is configured to determine the quality metric based on obtaining at least one of temperature and pressure data indicated by the at least one acoustic communication signal, wherein the at least one of temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

[0300] Example 35. The apparatus of example 34, wherein the processing circuitry is configured to determine the quality metric based on at least one of: a single temperature or pressure data value; temperature or pressure data detected by a single sensor; a comparison of two or more temperature or pressure data values detected by a respective two or more sensors, where at least one or the sensors is disposed in the wellbore below the plug and at least one of the sensors is disposed in the wellbore above the plug, or disposed at the surface; and at least one estimate of the temperature which the plug-forming material reaches during or after the plug-formation heating process.

[0301] Example 36. The apparatus of example 35, wherein the processing circuitry is configured to estimate a thermal energy gained by the plug-forming material (e.g., imparted to the plug-forming material during the heating process) based at least on the at least one estimate of the temperature which the plug-forming material reaches during or after the plugformation heating process.

[0302] Example 37. The apparatus of example 36, wherein the estimate of the thermal energy gained by the plug-forming material is further based on at least one of: an estimate of the mass of plug-forming material in the wellbore and an inclination of longitudinal axis of the wellbore with respect to the direction of gravity.

[0303] Example 38. The apparatus of any one of examples 34 to 37, wherein the at least one of temperature and pressure data comprises a plurality of temperature and / or pressure data detected by a respective plurality of sensors distributed at different distances spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

[0304] Example 39. The apparatus of example 38, wherein at least one of the plurality of sensors is disposed in the wellbore relative to a receiver of the acoustic communication signal such that the plug is located therebetween in an axial direction parallel to the longitudinal axis of the wellbore, the plug being above the at least one of the plurality of sensors and beneath the receiver.

[0305] Example 40. The apparatus of example 29, wherein the processing circuitry is configured to detect a change in at least one environmental acoustic signal that is a indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

[0306] Example 41 . The apparatus of example 40, wherein the indicator is a direct indicator of change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

[0307] Example 42. The apparatus of example 40 or example 41 , wherein the environmental acoustic signal is detected by at least one accelerometer.

[0308] Example 43. The apparatus of any of the examples 40 to 42, wherein the processing circuitry is configured detect a pre-defined signature in the environmental acoustic signal, wherein the pre-defined signature relates to plug movement or a change in a plug structural property.

[0309] Example 44. The apparatus of example 43, wherein the processing circuitry is configured to detect the pre-defined signature in the environmental acoustic signal is by way of a machine learning algorithm. For example, the processing circuitry may be configured to communicate with a server having stored thereon a trained machine learning algorithm, or the processing circuitry may be configured to execute a trained machine learning algorithm stored in a memory coupled to the processing circuitry.

[0310] Example 45. The apparatus of any of examples 27 to 44, wherein the processing circuitry is configured to determine the quality metric based on a weighted combination of a plurality of quality metric indicators determined based on one or more of the acoustic signals.

[0311] Example 46. The apparatus of example 45, wherein at least one of the plurality of quality metric indicators is determined based on at least one acoustic communication signal and the quality metric indicator is determined according to any one of examples 30 to 39 .

[0312] Example 47. The apparatus of example 45 or example 46, wherein at least one of the plurality of quality metric indicators is determined based on at least one environmental acoustic signal and the quality metric indicator is determined according to any one of examples 40 to 44.

[0313] Example 48. The apparatus of any one of examples 45 to 47, wherein the processing circuitry is configured to select of the combination of quality metric indicators and / or the determine the weightings of the respective quality metric indicators of the combination of quality metric indicators is performed by way of a trained machine learning algorithm.

[0314] Example 49. The apparatus of example 44 or example 48, wherein the processing circuitry is further configured to train the machine learning algorithm. For example, the processing circuitry is configured to train the machine learning algorithm based on experimental results, such as results from plugs formed in wellbores under test conditions or in laboratory environments simulating wellbore environments.

[0315] Example 50. The apparatus of any of examples 27 to 49, wherein the processing circuitry is configured to generate a control signal based on the determined quality metric, the control signal to be provided to a controller associated with the plug or plug-forming material thereof.

[0316] Example 51 . The apparatus of any of examples 27 to 50 further comprising at least one of transmitting and receiving circuitry.

[0317] Example 52. An apparatus comprising processing circuitry and memory coupled to the processing circuitry, the memory having the machine readable instructions of example 25 stored thereon.

[0318] Example 53. A kit of parts comprising: the apparatus of any one of examples 27 to 52 and at least one of: an acoustic communication node configured to at least receive acoustic signals, an acoustic communication node configured to at least transmit acoustic communication signals, a pressure and / or temperature, an accelerometer, an inclinometer, a force sensor.

Claims

CLAIMSWhat is claimed is:

1. A method comprising: obtaining at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore; determining a quality metric of the fully or partially formed plug based on the obtained at least one signal; and providing an indication of the determined quality metric.

2. The method of claim 1 , wherein at least one of the one or more acoustic signals is transmitted by propagation via at least a solid acoustic conductor in acoustic communication with the fully or partially formed plug.

3. The method of claim 1 or 2, wherein at least one of the acoustic signals comprises an acoustic communication signal actively transmitted by an acoustic communications node, or at least one of the acoustic signals comprises an environmental acoustic signal.

4. The method of claim 2 or 3, wherein determining the quality metric comprises determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals.

5. The method of claim 4, wherein the determined signal propagation characteristic is an indicator of a damping of the solid acoustic conductor depending on the plug.

6. The method of claim 4 or 5, wherein the signal propagation characteristic is based on at least one of: a peak and / or trough counting analysis of the acoustic communication signal; a determination of a Q-factor of the acoustic communication signal; a frequency response of the acoustic communication signal7. The method of claim 4, wherein determining the quality metric comprises determining an axial length of the fully or partially formed plug based on determining a respective signal propagation characteristic of at least one of the one or more acoustic communication signals, wherein the axial length is parallel to a longitudinal axis of the wellbore.

8. The method of claim 3, wherein determining the quality metric comprises obtaining at least one of temperature and pressure data indicated by the at least one acoustic communication signal, wherein the at least one of temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

9. The method of claim 8, wherein the at least one of temperature and pressure data comprises a plurality of temperature and / or pressure data detected by a respective plurality of sensors distributed at different distances spaced apart from the plug.

10. The method of claim 9, wherein at least one of the plurality of sensors is disposed in the wellbore relative to a receiver of the acoustic communication signal such that the plug is located therebetween in an axial direction parallel to the longitudinal axis of the wellbore, the plug being above the at least one of the plurality of sensors and beneath the receiver.11 . The method of claim 3, wherein determining the quality metric based on the received at least one signal comprises detecting a change in at least one environmental acoustic signal that is a indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug12. The method of claim 11 , wherein the indicator is a direct indicator of change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

13. The method of claim 11 or 12, wherein the environmental acoustic signal is detected by at least one accelerometer.

14. The method of any one of claims 11 to 13, wherein determining the quality metric comprises detecting a pre-defined signature in the environmental acoustic signal, wherein the pre-defined signature relates to plug movement.

15. The method of any one of claims 1 to 14, wherein determining the quality metric based on the received at least one signal is based on a weighted combination of a plurality of quality metric indicators determined based on one or more of the acoustic signals.

16. The method of claim 15, wherein at least one of the plurality of quality metric indicators is determined based on at least one acoustic communication signal.

17. The method of any one of claims 1 to 16, wherein the method further comprises generating a control signal based on the determined quality metric, the control signal to be provided to a controller associated with the plug or plug-forming material.

18. Machine readable instructions, which when executed by processing circuitry cause the processing circuitry to perform the method of any one of claims 1 to 17.

19. A machine readable medium having the machine readable instructions of claim 18 stored thereon.

20. An apparatus comprising: processing circuitry configured to:obtain at least one signal based on one or more acoustic signals relating to a fully or partially formed plug in a wellbore; determine a quality metric of the fully or partially formed plug based on the obtained at least one signal; provide an indication of the determined quality metric.21 . The apparatus of claim 20, wherein at least one of the one or more acoustic signals is transmitted by propagation via a solid acoustic conductor in acoustic communication with the fully or partially formed plug.

22. The apparatus of claim 20 or 21 , wherein at least one of the acoustic signals comprises an acoustic communication signal actively transmitted by an acoustic communications node, or at least one of the acoustic signals comprises an environmental acoustic signal.

23. The apparatus of claim 22, wherein the processing circuitry is configured to determine a respective signal propagation characteristic of at least one of the one or more acoustic communication signals.

24. The apparatus of claim 22, wherein the processing circuitry is configured to obtain at least one of temperature and pressure data indicated by the at least one acoustic communication signal, wherein the at least one of temperature and pressure data is detected by at least one sensor spaced apart from the plug in an axial direction parallel to the longitudinal axis of the wellbore.

25. The apparatus of claim 22, wherein the processing circuitry is configured to detect a change in at least one environmental acoustic signal that is a indicator of a change in a structural property or a change in a location relative to the wellbore of the fully or partially formed plug.

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