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    • 专利摘要:
    An acoustic logging system determines the slowness selections using the acoustic wave phase and the amplitude data. An amplitude-based first reception selection ("FAP") technique is applied to acquired waveforms to derive a first set of slowness selections, and a waveform phase coherence technique is also applied. to derive a second set of slowness selections. The first and second sets of slowness selections are then compared in various ways to determine a definitive set of slowness selections.
    公开号:FR3060049A1
    申请号:FR1760631
    申请日:2017-11-13
    公开日:2018-06-15
    发明作者:Baichun Sun；Ruijia Wang；Chung Chang
    申请人:Halliburton Energy Services Inc；
    IPC主号:
    专利说明:

    © Publication no .: 3,060,049 (to be used only for reproduction orders)
    ©) National registration number: 17 60631 ® FRENCH REPUBLIC
    NATIONAL INSTITUTE OF INDUSTRIAL PROPERTY
    COURBEVOIE
    ©) Int Cl 8 : E 21 B 47/00 (2017.01), G 01 V 1/28
    A1 PATENT APPLICATION
    ©) Date of filing: 13.11.17. © Applicant (s): HALLIBURTON ENERGY SERVICES, (30) Priority: 14.12.16 IB WOUS2016066582. INC. - US. (72) Inventor (s): SUN BAICHUN, WANG RUIJIA and CHANG CHUNG. (43) Date of public availability of the request: 15.06.18 Bulletin 18/24. (56) List of documents cited in the report preliminary research: The latter was not established on the date of publication of the request. (© References to other national documents ©) Holder (s): HALLIBURTON ENERGY SERVICES, related: INC .. ©) Extension request (s): ©) Agent (s): GEVERS & ORES Société anonyme.
    (34) PROCESSING ACOUSTIC LOGGING DATA USING AMPLITUDE AND WAVEFORM PHASE.
    FR 3 060 049 - A1
    An acoustic logging system determines the slowness selections using the acoustic wave phase and amplitude data. An amplitude-based first reception selection (“FAP”) technique is applied to the acquired waveforms to derive a first set of slowness selections, and a waveform phase consistency technique is also applied to derive a second set of slowness selections. The first and second sets of slowness selections are then compared in various ways to determine a final set of slowness selections.
    Time series
    d1 d3 d4 d5
    0.5 1.0 1.5 Z0
    Time (ms)
    Acoustic log data processing using waveform amplitude and phase
    AREA OF DISCLOSURE
    The present disclosure generally relates to downhole logging, and in particular to methods for determining acoustic slowness using jointly the amplitude and the waveform phase.
    CONTEXT
    The collection of information concerning the downhole conditions, commonly called "logging", can be carried out by several methods including "logging during drilling" (LWD) and wire logging. Acoustic well bottom logging tools are often used to acquire various characteristics of land formations traversed by the borehole. In such systems, the acoustic waves are generated using a transmitter and the acoustic responses are received using one or more networks of receivers. The acquired data is then used to determine the slowness (speeds) of the formation in order to obtain maximum slowness and minimum slowness; and processing the maximum and minimum slowness obtained to determine the horizontal transverse acoustic anisotropy and the angular direction of the maximum and minimum slowness of the formation. The level of anisotropy and direction can be helpful in planning wells and assessing cement or training; for example, to direct the cannons or to assess the stability of the wellbore.
    Drill waves generated by an acoustic pulse source consist of multiple complicated guided waves traveling along the borehole surrounded by rock. To extract measurements of the slowness of these mixed wave movements, such as compression slowness ("DTC") and shear slowness ("DTS"), or low shear screw wave shear in In LWD cases, a 2D coherence map is generally used for these purposes. However, identifying and correctly selecting these target wave modes from the 2D map is difficult, as it is often necessary to deal with complications including a low signal to noise ratio ("SNR"), interference from other wave modes, such as trailing P-waves, tool waves, Stoneley waves, road noise due to tool movements or distortions of these modes in the map 2D consistency. All of these reasons can contribute to a complex drilling wave field, thereby reducing the ability to make correct, simple, real-time automatic selections of slowness.
    BRIEF DESCRIPTION OF THE FIGURES
    Figure 1 illustrates a phase coherence map (bottom) derived from waveforms (top) which may include additional energy distortions or interference from other wave modes;
    Figure 2 illustrates a variable density layer derived from a 2D coherence map of Figure 1, in accordance with certain illustrative embodiments in the present disclosure;
    Figure 3 illustrates how a compression wave is incorrectly selected when strong interference appears in the selection time window, shown as spikes;
    FIG. 4 illustrates a window of time slowness, or a masking of time slowness, on a 2D coherence map in order to prevent the selections from jumping to an inadequate range of slowness, according to certain embodiments illustrated in the this disclosure;
    FIG. 5 illustrates a coherence in 2D, where the P-wave appears cut by the slowness-time mask;
    FIG. 6 shows examples of unipolar (upper) and dipolar (lower) waveforms acquired in a hard formation, according to certain methods illustrated in the present disclosure;
    FIG. 7 is a flow diagram of a method 700 for acoustic logging, so that the slowness of the acoustic wave is determined as a function of the joint estimation of the coherence and of the travel time, according to certain methods illustrated in this disclosure;
    FIG. 8 is an operation flow of a method for improving the selection of first reception 900 which can be carried out at block 706, according to certain alternative methods of the present disclosure;
    FIG. 9 shows a comparison of the improved slowness of the first reception selection with the original slowness of the first reception selection;
    FIG. 10 is a flow diagram of an alternative acoustic logging method 1100 in which the travel time and coherence techniques are applied sequentially, according to certain methods illustrative of the present disclosure;
    Figure 11 shows a graph defining a range of slowness providing a constraint for the computation of the coherence map, which helps to avoid selection peaks for subsequent receptions;
    Figure 12 illustrates the slowness selections which show how the use of first reception selection constraints eliminates the need for slowness-time masks in the search for slowness selections;
    FIG. 13A illustrates a sonic / acoustic logging tool used in an LWD application, which acquires acoustic waveforms and performs the determinations of slowness using the illustrated methods described here; and
    FIG. 13B illustrates an alternative embodiment of the present disclosure, allowing a wired acoustic logging tool to acquire and generate signals of slowness.
    DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
    Illustrative embodiments and related methods of this disclosure are described below, as they can be used in methods and systems for performing acoustic logging using amplitude and phase data of waveforms. acoustic. For the sake of clarity, all the characteristics of an embodiment or of a process are not described in this specification. It will of course be noted that in the development of any actual embodiment, many implementation-specific decisions must be made in order to achieve the specific objectives of the developers, such as compliance with system-related constraints or business considerations, which will vary from one materialization to another. In addition, it will be noted that such a development effort may be complex and time consuming, but would nevertheless be a routine undertaking for those skilled in the art who benefit from this disclosure. Other aspects and advantages of the various embodiments and related methods of the disclosure will become apparent from the following description and figures.
    As described herein, systems and methods illustrative of the present disclosure seek to accurately determine slowness selections using phase and acoustic waveform amplitude data. In a generalized process, the acoustic signals of a borehole are acquired. An amplitude-based first reception selection (“FAP”) technique is applied to the waveforms to obtain a first slowness selection set. A waveform phase consistency technique is also applied to derive a second set of slowness selection. The first and second slowness selection sets are then compared to determine a final slowness selection set, which forms the log. Thereafter, various drilling operations can be carried out using final slowness selections, including for example cement formation or evaluation. As a result, through the use of phase and amplitude information to constrain the selections, more precise and reliable logs are provided.
    As mentioned earlier, the acoustic waveforms of drilling consist of multiple complicated guided waves. To extract the selections for the slowness of these mixed wave movements, a 2D coherence map is generally used for these purposes. However, the precise selection of these targeted wave modes can be a challenge in the context of a varied phenomenon, including low SNR and interference from other wave modes. As a result, methods that apply only a 2D consistency map reduce the ability to make precise selections of slowness.
    To eliminate interference from unwanted mode or noise or its distortions, a slowness-time masking technique can be applied to the 2D coherence map to isolate unwanted modes or noise. In general, this process works well in homogeneous or weakly heterogeneous formations; however, in the case of complicated drilling conditions, for example, when the formation is highly heterogeneous, the time masking technique fails because it is designed to minimize interference based on the assumption that the source formation to the last receiver is homogeneous. Consequently, the imposed time mask could potentially partially or completely exclude the desired wave modes and lead to an imprecise selection of the slowness measurements. Since complicated waveforms are frequently found in the bottom of the well, the selection (or "selection") of the slowness of the targeted waveform using either of these methods in isolation presents many disadvantages, such as jumping to distortion or logging jitter.
    Accordingly, in the illustrated methods described herein, a robust approach is provided to improve the accuracy of real-time slow tracking of P or S waves or other waves in acoustic recording. Unlike the coherence measurement techniques alone, where only the phase component of the network waveforms is used for tracking the slowness, the present disclosure also uses waveform amplitude information to better constrain the slowness selections. As a result, complications from conventional approaches are ruled out, resulting in more precise and reliable selection of target slowness.
    With an acoustic logging tool, the waves excited by a unipolar (omnidirectional) source move along the drilling fluid and the formation interface (i.e., the wall of the borehole) and are recorded by a network of compensated receivers. As will be described here, in order to obtain a compression slowness (the same process can be applied to the extraction of the Stoneley slowness, of the flexion slowness at low frequency, of the slowness of the screw at low frequency ), the processing of the recorded waveforms is based in part on monitoring the amplitude of the first wave receptions using the receivers positioned along the drilling axis. In addition, a 2D coherence map of slowness-time is produced from a processing of the time domain, which exploits the coherent phase component without taking into account the waveform amplitude component to process non-dispersive waves.
    To understand the lithologies of the formation, the porosity or the saturation of the fluids of the formation, the correct extraction of the slowness of the acoustic wave was an important subject in the exploration of hydrocarbons, because the table of forms of wave can be complicated in difficult areas. Figure 1 illustrates how a bottom phase coherence map (derived from the top waveforms) can include additional distortion energy or interference from other wave modes as indicated by arrows. As can be seen, the coherence map contains multiple coherent peaks. These coherent peaks include distortion and waveform interference. It is also generally common to see multiple peaks due to leakage P-waves, reflections, road noise, etc. In real-time logging and using only this data, the lack of human intervention makes correct and consistent selection at consecutive depths of the recording very difficult.
    Therefore, to carry out a successful, automatic and intelligent treatment, it is necessary to reject spikes of unwanted noise. A method to assist in the selection of slowness is based on a 2D map derived using the variable density layer ("VDL") technique. A VDL can be produced using various methods such as, for example, determining the maximum coherence values of the 2D map along the time axis for a specific time range. Here, the selection of the slowness can be carried out as a function of certain consistency thresholds in certain embodiments.
    Due to the complications of the different wave modes, it is common for the
    The resulting VDL contains several peaks, for example shown in Figure 2, which illustrates a VDL derived from the 2D coherence map of Figure 1. A certain criterion or threshold can be used consistently throughout the logging process to determine the slowness of the
    VDL, such as the maximum amplitude of the VDL. In certain difficult situations, however, the distortion of the unipolar waves may have the highest amplitude, but at a slower time, since an incorrect slowness based on a certain amplitude threshold can be chosen. For example, Figure 3 illustrates how a compression wave is incorrectly selected when strong interference / distortion appears in the selection time window. The coherence map shows that there is more than one peak around the time of reception of the P wave (~
    0.7 ms), and the amplitude at this level shows the highest slowness, then a selection is made (as indicated by the star). However, it will be clear to a person skilled in the art that the first reception is the right answer.
    An illustrative method for controlling spikes in slowness selection is to place a slowness-time window, or a slowness-time mask, on the 2D coherence map of slowness-time in order to prevent the selections from skipping. to an undesirable slow-time range. Figure 4 illustrates these phenomena based on the example in Figure 3, and shows the desired slowness-time range identified between the two lines. In some examples, in particular for real-time processing, the selection of a slowness-time window is based on the estimation of the slowness and of the travel time as a function of the transmitter and receiver positions, as well as the drilling and the relative positions of the tool. The slowness-time window can be very effective in defining the correct selection range for slowness-time. However, the design of the slowness-time window must be careful in order to avoid cropping (adjusting) the necessary coherent information. By comparing Figure 3 and Figure 4, the true slowness of the P-wave at about 75 feet / us is reduced by the slowness-time window. Another example of poor definition of the slowness-time window is shown in Figure 5.
    In addition to the process of masking the slowness-time, another solution includes the use of the slowness ratio of the P and S waves to control the selection of slowness. However, this solution only applies to wells in hard formations.
    Accordingly, in view of the above, illustrative methods and embodiments of the present disclosure present a joint method using both a 2D phase coherence map and the amplitude derived from the time and slowness of FAP . Thus, the methods are based on tracking large amplitude changes for each recorded signal, while maintaining the 2D and VDL coherence map from the receiver network. Figure 6 shows examples of unipolar (upper) and dipolar (lower) waveforms acquired in a hard formation. The first receptions of P waves on the left or the bending waves on the right are identified as lines on the table. The first reception normally has a good SNR and can be followed for the determination of slowness. The output of FAP can be followed throughout the acquisition depths during acoustic logging and the determination of the output slowness of the displacement of the corresponding wave modes. In contrast, the coherence technique uses coherence along the first reception waveforms for the selection of slowness, but it uses coherent phase information, such as the differential phase method. Thus, the amplitude information is missing, and although the distortions generally exist in the 2D map, the slowness of FAP does not contain any possibility of distortion. Therefore, the combination of these two methods in the present disclosure is closely related and, therefore, can be implemented simultaneously or sequentially to constrain the selection of the target wave modes.
    FIG. 7 is a flow diagram of a method 700 for acoustic logging, in which the slowness of the acoustic wave is determined as a function of the joint phase coherence and the estimation of the travel time defined by the amplitude, according to certain methods illustrative of the present disclosure. In FIG. 7, the process flow of this illustrative method of simultaneous selection is presented. In block 702, a set of waveforms from unipolar or dipolar shots is acquired and supplied to the acoustic logging system as input. At block 704, the preprocessing of the waveforms is carried out to better condition the data, for example the elimination of the DC, the filtering of the waves to suppress the noises and to preserve the frequency band of the unipolar shooting and the interpolation waveforms, all of which can be applied when improving the accuracy and consistency of the first reception is important. In this illustrative method, an efficient filter can suppress the energy of the very low frequency band in order to improve the accuracy of the FAP to be used in subsequent blocks. Once the signals are prepared at block 704, they are transmitted in two simultaneous / parallel selection methods starting at blocks 706 and 710, including selecting the first reception waveforms using amplitude break and the calculation of a 2D coherence map for VDL calculation, as will be discussed in detail below.
    In block 706, the appearance of the first indices of the travel times are selected for the target wave mode. For modern acoustic logging tools, the selection of target wave modes based on amplitude breaks can be achieved with different methods. For example, in some illustrative methods, the time of reception of the waves is determined using two consecutive sliding windows, and the ratio of energy, entropy, etc., can be calculated for each window to indicate the abrupt variation in the 'time axis. Alternatively, the correlation of the window waveform method can be used for the same purpose. In block 706, the receiver-to-receiver FAP is followed to ensure that the process does not introduce any significant bias.
    Once the FAP of all waveforms in the receiving network is determined in block 706, the slowness of the target wave is derived for the specific wave mode in block 708. In some methods, determining the slowness at block 708 is accomplished using a linear data adjustment method corresponding to reception times. Equation (1) below, namely:
    t = t 0 + sx Δχ Equation 1, demonstrates the relationship between the travel time t, the initial reception time to and the offset of the receiver Δχ, and how the slowness s can be determined using this method d 'linear adjustment. In some examples, multiple iterations of linear fit are needed to reject outliers if necessary. Thereafter, the slope of the linear regression is the slowness of exit from block 708.
    In some illustrative methods, the accuracy of the delay between receivers can be improved depending on the initial selection of the FAP. In one example, the improvements are obtained by correlating the sinusoidal waveforms according to the initial FAP in block 706. Figure 8 is a process flow of a method for improving the FAP 800 which can be performed at level of block 706, according to certain alternative methods of this disclosure. From the first reception time selected at block 706 and the network input of block 702, predefined window waveforms are extracted from the FAP at block 802, which include the waveforms of the first reception wave mode. Then, in block 804, half or the full period of the first signal is extracted using a zero crossing method and the values of the window waveforms are replaced by trailing zeros.
    Then, at block 806, to find the delay between the window waveforms delimited in the receivers, the cross-correlation is performed either with the extracted wavelet or with one of the window waveforms. In block 806, wavelet extraction can be achieved by shifting and aligning window waveforms and deriving the average or median waveform. Finally, in block 808, these time delays against the reference waveform are used to update the initial estimate of the first reception time. In some methods, the improved reception time can be used to perform the same linear regression process to derive the slowness at block 708, or the slowness can be estimated based on the distance between the source and the receiver and the time of move to block 708. In addition, to block 708, the delay can be checked to eliminate outliers in some illustrative methods. The improved treatment will generally lead to a more precise estimation of the slowness at block 708. For example, Figure 9 shows a comparison of the improved FAP slowness and the initial slowness of the FAP. As can be seen, the slowness from the original APF is less than the improved APF, because the improved APF has a correspondence very close to the apparent peak (VDL).
    Returning to Figure 7, while the FAP technique is applied, to the block
    710, a coherence technique is used simultaneously for the slowness selections in block 710. In this example, a 2D map coherent in the time domain is useful because of the separations of the reception time of the different modes. Different methods can be used to calculate the coherence map, for example, the time domain differential phase method.
    In block 712, a VDL ID (eg, Figure 2) is derived from the consistency map and used to make the selection. As mentioned earlier, it is common to see multiple peaks in the VDL, including distortions. In the absence of any other constraints, conventionally, the slowness corresponding to the maximum coherence is selected. However, in the illustrative methods described here, all the candidate selections are delivered to block 714 on the basis of a predefined coherence threshold such as, for example, 0.2. The attributes of all the results include their consistency, their travel time and their information on the slowness values.
    In block 716, the slowness selections from the linear regression derived from the slowness of the FAP (block 708) and candidate slowness selections from the 2D consistency map (block 714) are joined (e.g., compared) to determine selection of slowness of the final result. Joint determination can be done in a number of ways. In some illustrative methods, a conical function is applied based on selections of slowness of the linear regression of block 708. The conical function is applied to candidate VDL selections (block 714) to suppress coherent peaks according to their distances by compared to the slowness derived from linear regression (block 708). Once the conical function is applied, the remaining coherence peak (s) (X) is (are) compared with the selection of slowness of FAP s FAP to define the final result of slowness in l equation 2 in block 718.
    s = Min {} x - s FAP Q, x -e X, Equation (2),
    In an alternative method, selections for slowness from linear regression (block 708) are compared sequentially to (or used to constrain) all candidate selections for slowness VDL (block 714) in order to locate the slowness with the minimum distance from the slow linear regression. If there are more than one candidate remaining, the consistency value is normally used as the critical criterion for determining the final slowness selections. In some unusual situations, if there are still comparable consistency peaks on the 2D consistency map, the candidate selections will still be compared based on their travel time and slowness. If there are reference values, such as the previous acquisition result, or the known slowness or travel time of the other corresponding wave modes, this information can be used to help infer the final result. When a branch result is not valid, such as unrealistic slowness or speed, the result can be evaluated based on the consistency of the cached value of slowness from previous acquisitions. However, after the final slowness selections are produced in block 718, they can be applied to perform various downhole operations, including, for example, cement formation or evaluation.
    FIG. 10 is a flow diagram of an alternative acoustic logging method 1000 in which the travel time and the coherence techniques are applied sequentially, according to certain methods illustrative of the present disclosure. The difference from the operation flow in Figure 7 is that the result of the slowness selections from the FAP technique is directly used to define a narrow range of coherence calculation. At block 1002, the waveform table is entered and preprocessed at block 1004 as previously described. At blocks 1006 and 1008, the estimation of the travel time and of the slowness is carried out. In block 1010, depending on the determined results of the slowness and the displacement time of the amplitude processing of the waveform, on the coherence map of the slowness-time, the time and the slowness can be restricted to limit the selection and calculation range, and a limited search range for the slowness is determined for the coherence calculation using a threshold of slowness and time range. For example, Figure 11 shows a graph that illustrates a defined slowness range providing a constraint for calculating the coherence map, which helps to avoid selection peaks for slower noises or distortions. Only the FAP slowness range of the 2D map is required for the calculation, and selections will be made within this range. Thereafter, the coherence map is calculated in block 1012, the VDL is derived from block 1014 and the final slowness selections are delivered to block 1016, as described previously here. The merit of this operation flow is that it reduces the scope and the computation time, as compared to this one, the operation flow of figure 7.
    It is remarkable that the slowness selections from the FAP according to the amplitude treatment is the slowness of the group. In addition, for non-dispersive or weakly dispersive waves, the slowness of the group is identical to or close to the phase slowness. Therefore, in some illustrative methods, a slowness response can be used to validate or constrain the other response, in order to provide a converging result.
    Figure 12 illustrates a comparison of the treatment of slowness between Figure 3 and the illustrative methods described here. In Figure 12 (1), the raw VDL data from the slowness-time map is displayed and is superimposed by the slowness derived from FAP shown in vertical line. The final selection is obtained by comparing the peaks of the VDL with the vertical line. In Figure 12 (2), it illustrates here an alternative method where the slowness derived from FAP is used to define a slowness selection range, indicated by the horizontal lines, then the consistency map is calculated and the final selection y is carried out. In Figure 12 (3), the last selection (denoted by "x") on the final slowness-time map is illustrated. The correct selection is made according to the constraint of the FAP slowness. At the same time, the reduction in VDL is eliminated by rejecting the slowness-time mask using this method. Obviously, the slowness FAP is closely correlated with the final selection, and compared to the conventional method of semblance only, the spikes or jumps will be considerably reduced.
    Illustrative methods of the present disclosure can be used in a variety of logging applications, including, for example, LWD or MWD applications. Figure 13A illustrates a sonic / acoustic logging tool used in an LWD application, which acquires acoustic waveforms and performs slowness determinations using the illustrative methods described here. The methods described here can be carried out by a system control center located on the logging tool or can be carried out by a processing unit at a remote location such as, for example, at the surface.
    FIG. 13A illustrates a drilling platform 1302 equipped with a derrick 1304 which supports a winch 1306 for raising and lowering a drilling column 1308. The winch 1306 suspends an upper drive 1310 capable of rotating the drilling column 1308 and to lower it through the well head 1312. Linked to the lower end of the drill string 1308 is a drill bit 1314. When the drill bit 1314 rotates, it digs a borehole 1316 which passes through various layers of formation 1318. A pump 1320 circulates drilling fluid through a supply pipe 1322 to the upper transmission 1310, descending through the interior of the drilling column 1308, through orifices in the drill bit. drill 1314, and back to the surface through the ring around the drill string 1308, and into a retention basin 1324. The drilling fluid carries the cuttings from the borehole into the retention basin 1324 and has ide to maintain the integrity of borehole 1316. Various materials can be used for the drilling fluid, including, but not limited to, a conductive mud based on salt water.
    An acoustic logging tool 1326 is integrated into the assembly of the lower hole near the drill bit 1314. In this illustrative embodiment, the logging tool 1326 is an LWD sonic tool; however, in other illustrated embodiments, the 1326 logging tool can be used in a directional or wired tube logging application. If the logging tool is used in an application that does not rotate the downhole assembly, the logging tool can be equipped with azimuthal position sensors that acquire the measurement of the slowness around the borehole. In certain other illustrative embodiments, the acoustic logging tool 1326 can be adapted to perform logging operations in environments with open holes and cased wells.
    In this example, the acoustic logging tool 1326 will include multi-pole transmitters and receiver networks (not shown) which generate acoustic waves in geological formations and record their transmission. In some embodiments, the transmitters can direct their energies in substantially opposite directions, while in others, a single transmitter can be used and rotated accordingly. The frequency, magnitude, angle and time of transmission of energy from the transmitter can also be controlled, if necessary. In other embodiments, the collected slowness measurements can be stored and processed by the tool itself, while in other embodiments, the measurements can be communicated to remote processing circuits to perform the treatment of slowness.
    The acoustic logging tool 1326 is used to acquire data for measuring slowness at many azimuths. As such, some embodiments may also include a directional sensor for determining the orientation of the tool. The illustrative methods described herein can be used in a variety of propagation modes, including, for example, compression, shear, low frequency bending, low frequency screw, quadrupole or Stoneley modes, for example example.
    Still referring to FIG. 13A, when the drill bit 1314 extends the wellbore 1316 through the formations 1318, the logging tool 1326 collects slowness measurement signals relating to various formation properties, as well as the tool orientation and various other drilling conditions. In some embodiments, the 1326 logging tool may take the form of a drill collar, i.e., a thick-walled tubular that provides weight and rigidity to facilitate the drilling process . A telemetry module 1328 can be included to transfer slow images and data or measurement signals to a surface receiver 1330 and to receive commands from the surface. In some embodiments, the telemetry module 1328 does not communicate with the surface, but rather stores slowness measurement data for later retrieval at the surface when the logging set is retrieved.
    In some embodiments, the acoustic logging tool 1326 includes a system control center ("SCC"), as well as a necessary processing / storage / communication circuit, which is communicatively coupled to one or more transmitters. / receivers (not shown) used to acquire slowness measurement signals. In some embodiments, once the acoustic waveforms are acquired, the system control center calibrates the signals, performs the methods of calculating the slowness described here, and then reports the data upstream of the well and / or other assembly components by the telemetry module 1328. In another embodiment, the system control center may be located at a remote location away from the logging tool 1326, such as on the surface or in a different borehole, and performs statistical processing accordingly. These and other variations in the present disclosure will readily appear to those ordinarily skilled in the art and benefit from this disclosure.
    FIG. 13B illustrates an alternative embodiment of the present disclosure, allowing a wired acoustic logging tool to acquire and generate signals of slowness. At various times during the drilling process, the drill string 1308 can be removed from the borehole as shown in Figure 13B. Once the drill string 1308 is removed, the logging operations can be performed using a wired acoustic logging probe 1334, i.e., an acoustic probe suspended by a cable 1341 having conductors for transport energy to the probe and to the telemetry from the probe to the surface. A wired acoustic logging probe 1334 may include buffers and / or centralizing springs to hold the tool close to the axis of the borehole when the tool is pulled upstream from the well. The 1334 acoustic logging probe can include a variety of transceivers to measure acoustic anisotropy. A logging facility 1343 collects measurements from the logging probe 1334 and includes a computer system 1345 for processing and storing the slowness measurements collected by the sensors, as described here.
    In some illustrative embodiments, the system control centers used by the acoustic logging tools described here include at least one processor incorporated into the system control center and non-transient, computer-readable storage, all interconnected by a bus. system. The software instructions executable by the processor for implementing the illustrative processing methods described herein can be stored in local storage or other computer readable media. It will also be recognized that the instructions of the statistical processing software can also be loaded into the storage from a CD-ROM or other suitable storage medium by wired or wireless methods.
    In addition, those skilled in the art will appreciate that this disclosure can be practiced with a variety of computer system configurations, including portable devices, multiprocessor systems, and user programmable or microprocessor based electronic devices, mini- computers, mainframe computers, etc. Any number of computer systems and computer networks are acceptable for use with this disclosure. Disclosure can be practiced in networked computing environments in which tasks are performed by remotely controlled devices which are connected across a telecommunications network. In a networked computing environment, program modules can be located on both local and remote computer storage media, including memory storage devices. This disclosure may therefore be made in connection with various hardware, software, or a combination thereof in a computer system or other processing system.
    Accordingly, the illustrative methods described herein provide new methods using both the amplitude and the phase information of the waveforms of the receiving network to constrain the slowness peaks. The methods eliminate the need to use time masking techniques for the selection of slowness, which can cause inaccurate peaks, if defined as inappropriate. The illustrative methods can be used in the extraction of Stoneley slowness, low frequency bending slowness, low frequency screw slowness and slow refracted drilling compression waves. In addition, the selection of the previous slowness or the existing slowness selections from other wave modes can be used to validate the slowness selections and eliminate the aberrant noises for the slowness estimates. The processes can be applied in real time or after treatment or planning.
    The embodiments and methods of this disclosure described herein also relate to any one or more of the following paragraphs:
    1. A method of acoustic downhole logging, comprising the acquisition of acoustic drilling waveforms; the application of a first reception technique (“FAP”) to derive the first slowness measurements of the acquired acoustic forms, the FAP technique being based on the amplitude of the waveform; the application of a waveform phase coherence technique to derive second selections of slowness from the acquired acoustic forms; comparing the first and second slowness selection; determining final slowness selections based on the comparison; and performing a drilling operation using the final slowness selections.
    2. The method as defined in paragraph 1, in which the FAP consistency and waveform phase techniques are applied simultaneously.
    3. The method as defined in paragraphs 1 or 2, in which the FAP coherence and waveform phase techniques are applied sequentially.
    4. The method as defined in any one of paragraphs 1 to 3, in which the sequential application comprises the application of the FAP technique before the waveform phase consistency technique so as to choose the first selections slowness; determining a slowness search range based on the first slowness selections; and applying the slowness search range to the waveform phase consistency technique to constrain the second slowness selections.
    5. The method as defined in any one of paragraphs 1 to 4, wherein determining final slowness selections comprises determining a distance of the second slowness selections from the first slowness selections; and selecting a maximum coherence peak of the second slowness selections as a function of distance, wherein the second slowness selections having the maximum coherence peak or the most consistent slowness and travel times are the final values of slowness.
    The method as defined in any one of paragraphs 1 to 5, wherein determining the final slow selections comprises sequentially determining a distance of the second slow selections from the first slow selections; and selecting the second slowness selections as a function of distance, wherein the second slowness selections having a minimum distance from the first slowness selections are the final slowness values.
    7. The method as defined in any one of paragraphs 1 to 6, in which the acoustic waveforms are acquired using an acoustic logging tool placed along a wire line or a drilling set.
    8. The process as defined in any one of paragraphs 1 to 7, wherein the drilling operation includes good planning or evaluation of the training.
    9. A method of acoustic logging of the bottom of the well, comprising the acquisition of acoustic waveforms in a borehole; and using the amplitude and phase data of the acquired acoustic waveform to determine the slowness selections.
    10. The method as defined in paragraph 9, in which the use of amplitude data includes the application of a first reception selection technique ("FAP") to the acquired acoustic waveforms; and the use of phase data includes applying a waveform phase coherence technique to the acquired acoustic forms.
    11. The method as defined in paragraphs 9 or 10, in which the techniques of FAP coherence and waveform phase are applied simultaneously.
    12. The method as defined in any one of paragraphs 9 to 11, in which the FAP coherence and waveform phase techniques are applied sequentially.
    13. The method as defined in any one of paragraphs 9 to 12, further comprising performing a downhole operation using the slowness selections.
    14. A downhole acoustic logging system, comprising a logging tool; and a processor coupled in communication with the logging tool so that the system can carry out any of the methods of paragraphs 1 to 13.
    Furthermore, the foregoing paragraphs and the other methods described herein can be performed in a system comprising a processing circuit for implementing any of the methods, or a non-transient computer readable medium comprising instructions which, when they are executed by at least one processor, cause the processor to perform one of the methods described here.
    Although various embodiments and methods have been illustrated and described, the disclosure is not limited to such embodiments and methods and it will be understood that it encompasses all modifications and variations which will be apparent to a specialist in the field . Therefore, it should be understood that the disclosure is not intended to be limited to the particular forms disclosed. Instead, the disclosure must cover all modifications, equivalences and alternatives that are within the spirit and scope of the disclosure, as defined in the appended claims.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. Method for acoustic logging of the bottom of the well, comprising:
    acquire acoustic waveforms from a borehole;
    applying a first reception technique (“FAP”) to derive the first selections of slowness of the acquired acoustic waveforms, the FAP technique being based on the amplitude of the waveform;
    applying a waveform phase consistency technique to derive second selections of slowness from the acquired acoustic waveforms;
    compare the first and second selections of slowness;
    determine the final slowness selections based on the comparison; and perform a drilling operation using the final slowness selections.
    [2" id="c-fr-0002]
    2. Method according to claim 1, in which the techniques of FAP coherence and of waveform phase are applied simultaneously.
    [3" id="c-fr-0003]
    3. The method of claim 1, wherein the techniques of FAP coherence and waveform phase are applied sequentially.
    [4" id="c-fr-0004]
    4. Method according to claim 3, in which the sequential application comprises:
    apply the FAP technique before the coherence technique of the waveform phase to thus select the first selections of slowness;
    determining a slowness search range based on the first slowness selections; and applying the slowness search range to the waveform phase consistency technique to constrain the second slowness selections.
    [5" id="c-fr-0005]
    5. Method according to claim any one of claims 1 to 4, in which the determination of the final slowness selections comprises:
    determining a distance of the second slowness selections from the first slowness selections; and selecting a maximum consistency peak of the second slowness selections as a function of distance, wherein the second slowness selections having the maximum coherence peak or the most consistent slowness and travel time are the final slowness values.
    [6" id="c-fr-0006]
    6. Method according to any one of claims 1 to 4, in which the determination of the final slowness selections comprises:
    sequentially determining a distance of the second slowness selections from the first slowness selections; and choosing the second selections of slowness as a function of distance, wherein the second selections of slowness having a minimum distance from the first selections of slowness are the final values of slowness.
    [7" id="c-fr-0007]
    7. Method according to any one of claims 1 to 6, in which the acoustic waveforms are acquired using an acoustic logging tool positioned along a wired or drilling assembly.
    [8" id="c-fr-0008]
    The method according to any of claims 1 to 7, wherein the drilling operation includes good well planning or training evaluation.
    [9" id="c-fr-0009]
    9. Method of acoustic logging of the bottom of the well, comprising:
    acquire acoustic waveforms from a borehole; and using amplitude and phase data of the acquired acoustic form to determine the slowness selections.
    [10" id="c-fr-0010]
    10. The method according to claim 9, in which:
    the use of amplitude data includes the application of a first reception selection technique (“FAP”) to the acquired acoustic waveforms; and the use of phase data includes applying a waveform phase coherence technique to the acquired acoustic waveforms.
    [11" id="c-fr-0011]
    11. The method of claim 10, wherein the techniques of FAP coherence and waveform phase are applied simultaneously.
    [12" id="c-fr-0012]
    The method of claim 10, wherein the FAP coherence and waveform phase techniques are applied sequentially.
    [13" id="c-fr-0013]
    13. The method of any of claims 9 to 12, further comprising performing a downhole operation using the slowness selections.
    [14" id="c-fr-0014]
    14. Downhole acoustic logging system, comprising:
    a logging tool; and a processor coupled in communication with the logging tool to cause the system to perform any of the methods of claims 1 to 13.
    [15" id="c-fr-0015]
    15. A non-transient computer-readable medium comprising instructions which, when executed by at least one processor, cause the processor to execute any of the methods according to claims 1 to 13.
    1/13
    Time series i, i I d1 d2 d3 d4 d5
    0.5 1.0 1.5 2.0
    Time (ms)
    Time Consistency Editor view
    Slowness (pspf)
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    法律状态:
    2018-09-28| PLFP| Fee payment|Year of fee payment: 2 |
    2019-11-29| PLFP| Fee payment|Year of fee payment: 3 |
    2020-06-19| PLSC| Search report ready|Effective date: 20200619 |
    2021-09-24| RX| Complete rejection|Effective date: 20210818 |
    优先权:
    申请号 | 申请日 | 专利标题
    IBWOUS2016066582|2016-12-14|
    PCT/US2016/066582|WO2018111256A1|2016-12-14|2016-12-14|Acoustic logging data processing using waveform amplitude and phase|
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