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    • 专利摘要:
    A method and system for producing a quasi-static Stoneley slowness log. The method for producing a quasi-static Stoneley slowness log may include recording a pressure wave at a receiver; determining a slow-frequency range with an information processing system from the pressure wave, processing a frequency domain look-up, extracting a Stoneley dispersion, reducing the Minimum of a mismatch between the theoretical dispersion and the Stoneley dispersion, and the identification of the quasi-static Stoneley slowness from the Stoneley dispersion. The well measurement system for producing a quasi-static Stoneley slowness log may include a downhole tool, a vehicle, and an information processing system. Wherein the information processing system can operate to record a pressure wave at a receiver, determine a slowness-frequency range with an information processing system from the pressure wave, process a appearing in the frequency domain, extracting a Stoneley dispersion; minimize a mismatch between the theoretical dispersion and the Stoneley dispersion; and identify the quasi-static Stoneley slowness from the Stoneley dispersion.
    公开号:FR3061237A1
    申请号:FR1761193
    申请日:2017-11-27
    公开日:2018-06-29
    发明作者:Ruijia Wang；Chung Chang；Baichun Sun
    申请人:Halliburton Energy Services Inc；
    IPC主号:
    专利说明:

    Agent (s):
    GEVERS & ORES Public limited company.
    ® ESTIMATE OF THE SLAVE OF QUASI-STATIC STONELEY.
    (57) a method and system for producing a quasi-static Stoneley slowness diagram. The method of producing a quasistatic Stoneley slowness log may include recording a pressure wave at a receiver; the determination of a slow-frequency range with an information processing system from the pressure wave, the processing of a semblance of the frequency domain, the extraction of a Stoneley dispersion, the reduction to minimum of a mismatch between the theoretical dispersion and the Stoneley dispersion, and the identification of the quasistatic Stoneley slowness from the Stoneley dispersion. The well measurement system for producing a quasi-static Stoneley slowness log may include a downhole tool, a vehicle and an information processing system. In which the information processing system is operable to record a pressure wave at a receiver, determining a slow-frequency range with an information processing system from the pressure wave, processing a semblance of the frequency domain, extracting a Stoneley dispersion; minimize a mismatch between the theoretical dispersion and the Stoneley dispersion; and identify the quasi-static Stoneley slowness from the dispersion of Sto-

    ESTIMATING THE QUASI-STATIC STONELEY SLOW BACKGROUND For the exploration and production of oil and gas, a network of wells, facilities and other conduits can be established by connecting sections of metal pipe together. For example, a well installation can be completed, in part, by lowering multiple sections of metal pipe (i.e., a casing column) into a borehole, and cementing the casing column in place . In some well installations, multiple casing columns are used (for example, a concentric multiple column arrangement) to allow for different operations related to well completion, production or enhanced oil recovery (EOR) options .
    The development of underground formations like hydrocarbon reservoirs can be an ongoing process. In particular, the analysis of well logs can allow an operator to evaluate, as a function of depth, quantitative properties representative of formations. By estimating the quasi-static Stoneley slowness from unipolar waveforms with minimal human intervention, a real-time sound sink log of Stoneley slowness versus depth can be produced. Stoneley slowness could furthermore be adopted to estimate the formation shear slowness, the formation anisotropy or the formation permeability, by combining the results of dipole data. This can provide an operator with a picture of the oil tank in a formation.
    BRIEF DESCRIPTION OF THE DRAWINGS These drawings illustrate certain aspects of certain examples of the present invention, and should not be used to limit or define the invention.
    Figure 1 is a schematic illustration of a well measurement system;
    Figure 2 is a schematic illustration of a downhole tool;
    Figure 3 is a graph illustrating a Stoneley dispersion response;
    Figure 4 is a workflow diagram for processing the frequency domain and processing the time domain;
    Figure 5 is a work flow diagram for processing based on the time domain;
    Figure 6 is a graph illustrating the comparison between the exact Stoneley dispersions by direct modeling and the dispersion curves from the simplified Stoneley model;
    Figure 7 is a graph illustrating the difference between the input Stoneley data and the final Stoneley dispersion estimates;
    Figure 8 illustrates a sectional map of the objective function;
    Figure 9 is a graph showing different levels of anisotropy;
    Figure 10a illustrates a first unipolar low frequency trip;
    Figure 10b illustrates a second unipolar low frequency trigger;
    Figure 11 is an example of processing field data for a flexible training case in the form of logging; and [0016] FIG. 12 is a workflow for the calculations of the formation shear slowness and the shear slowness anisotropy.
    DETAILED DESCRIPTION The present invention can generally relate to well logging. More particularly, in certain examples, methods can be provided for determining a sound sink log in near real time by estimating the quasi-static Stoneley slowness from low frequency unipolar waveforms, which can be used for calculate the shear slowness, shear anisotropy or formation permeability by combining other logs, as well as calculated shear moduli, the Young's modulus and the Poisson's ratio with the slowness P of formation. These elastic moduli and the Poisson's ratio can be parameters used to characterize the mechanical properties of a rock formation. They can be used to estimate borehole characteristics which may include stability, sanding potential, fracture resistance and a number of other related parameters, which may determine a procedure for completion and well production. The mechanical properties can be a function of the acoustic wave velocities of compression (P) and shear (S) and the density of the rock. Without limitation, the production companies want to make decisions in terms of reservoir development, by providing precise acoustic well logs as a function of the reservoir depth in real time and / or in near real time on site at the well level with minimal human intervention which may be desirable.
    Acoustic logging tools can trigger acoustic sources with different azimuthal symmetries to measure acoustic velocities. In fast isotropic formations, the P and S wave velocities can be estimated from refracted P and S acoustic waves excited by an axisymmetric (unipolar) source. These waves can be non-dispersive and can allow direct estimation of wave speeds (or slowness) using a variety of time-like or frequency-like techniques. Two guided wave modes can exist, the pseudo-Rayleigh mode and the Stoneley mode. Among them, the Stoneley drill hole mode can be essential in the interpretation of acoustic data as it provides several crucial applications for geoscientists and petroleum engineers. More precisely, the Stoneley mode may be the only wave mode sensitive to the elasticity module of Cee formation in a transversely isotropic vertical well (VTI), which can be represented by the degree of the difference between the wavelength of horizontal propagation shear (s S h) and vertical propagation shear wavelength (ssv), where ssh could be estimated from a quonistatic Stoneley wavelength and ssv could be estimated using data low frequency dipole.
    Figure 1 illustrates a cross-sectional view of a well measurement system 100. As illustrated, the well measurement system 100 may include a downhole tool 102 attached to a vehicle 104. In the examples , it should be noted that the downhole tool 102 cannot be attached to a vehicle 104. The downhole tool 102 can be supported by a platform 106 on the surface 108. The downhole tool downhole 102 can be fixed to the vehicle 104 by a means of transport 110. The means of transport 110 can be arranged around one or more pulley wheels 112 on the vehicle 104. The means of transport 110 can comprise any means suitable for providing mechanical transportation for the downhole tool 102, including, but not limited to, wire rope, smooth cable, coiled tubing, tubing, drill pipe, tractor downhole or similar. In some embodiments, the transport means 110 may provide mechanical suspension, as well as electrical connectivity, for the downhole tool 102. The transport means 110 may, in some cases, include a plurality of conductors electrical extending from the vehicle 104. The means of transport 110 may comprise an internal core of seven electrical conductors covered with an insulating envelope. An inner and outer steel shielding sheath can be wrapped in a helix in opposite directions around the conductors. The electrical conductors can be used to communicate power and telemetry between the vehicle 104 and the downhole tool 102. Information from the downhole tool 102 can be collected and / or processed by a Information processing 114. For example, signals recorded by the downhole tool 102 can be stored on a memory and then processed by the downhole tool 102. The processing can be carried out in real time during of the acquisition of data or after the recovery of the downhole tool 102. The processing can also occur at the bottom of the hole or can occur both at the bottom of the hole and at the surface. In some embodiments, signals recorded by the downhole tool 102 may be routed to the information processing system 114 through the transport means 110. The information processing system 114 may process the signals, and the information contained therein can be displayed for viewing by an operator and stored for further processing and reference. The information processing system 114 may also contain an apparatus for supplying control signals and power to the downhole tool 102.
    The systems and methods of the present invention can be implemented, at least in part, with the information processing system 114. The information processing system 114 can include any instrument or set of instruments capable of operating to calculate, estimate, classify, process, transmit, receive, retrieve, develop, change, store, display, manifest, detect, record, reproduce, process or use any form of information, intelligence or data to commercial, scientific, control or other purposes. For example, an information processing system 114 may be a personal computer 116, a network storage device or any other suitable device and may vary in size, shape, performance, functionality and price. The information processing system 114 may include a random access memory (RAM), one or more processing resources such as a central processing unit (CPU) or hardware or software control logic, a ROM and / or other types of non-volatile memory. Additional components of the information processing system 114 may include one or more disk drives, one or more network ports for communication with external devices, and various input and output (I / O) devices such as than a keyboard 118, a mouse and a video screen 120. The information processing system 114 may also include one or more buses that can operate to transmit communications between the various hardware components.
    Alternatively, the systems and methods of the present invention can be implemented, at least in part, with non-transient computer-readable media 122. Non-transient computer-readable media 122 can include any instrument or assembly instruments that can store data and / or instructions for a period of time. The non-transient computer readable media 122 may include, for example, storage media such as a direct access storage device (for example, a hard disk drive or a floppy drive), an access storage device sequential (for example, magnetic tape drive), compact disc, CD-ROM, DVD, RAM, ROM, electrically erasable programmable read-only memory (EEPROM) and / or flash memory; as well as communication media such as cables, optical fibers, microwaves, radio waves and other electromagnetic and / or optical media; and / or any combination of the above.
    In the examples, the platform 106 comprises a load cell (not shown) which can determine the amount of traction on the transport means 110 on the surface of the borehole 124. The information processing system 114 may include a safety valve which controls the hydraulic pressure which drives a drum 126 on the vehicle 104 which can wind up and / or release the transport means 110 which can move the downhole tool 102 upwards and / or down the borehole 124. The safety valve can be adjusted to a pressure such that the drum 126 can only transmit a small amount of tension to the conveyor 110 above and above the tension necessary for retrieve conveyor 110 and / or downhole tool 102 from borehole 124. The safety valve is usually set a few hundred pounds above the desired amount of safe traction on the means from trans port 110 so that once this limit is exceeded; additional traction on the transport means 110 is prevented.
    FIG. 2 illustrates the downhole tool 102, in particular an acoustic dipole configuration. It should be noted that the downhole tool 102 may include any appropriate configuration operation described in the present invention. As illustrated, the downhole tool 102 may be disposed in the borehole 124 along a vertical axis. In the examples, the downhole tool 102 may include a single-pole transmitter 200. Without limitation, the single-pole transmitter 200 may be disposed along any surface of the downhole tool 102 and may be oriented in n no matter which direction. In addition, there can be any number of single pole transmitters 200 arranged in any pattern and / or location along the downhole tool 102. The downhole tool 102 can further comprising a receiver 202. Without limitation, the receiver 202 may be disposed along any surface of the downhole tool 102 and may be oriented in any direction. It should be noted that the receiver 202 can be unipolar, dipolar and / or the like. In addition, there may be a number of receivers 202 arranged in any pattern and / or location along the downhole tool 102. In the examples, receivers 202 may be arranged in an aligned array along the same azimuth of the downhole tool 102. In the examples, the unipolar transmitter 200 can generate an azimuthal asymmetric acoustic pressure wave (not shown) which can propagate through the drilling fluid in the hole 124. The sound pressure field can be converted into shear (not shown) at a borehole wall 132 and excite the bending mode (not shown) in formation 134. The bending mode can propagate down the borehole 124, transforming into a pressure wave at the borehole wall 132 and can touch the receivers 202. The pressure exerted on each receiver 202 can be recorded by the processing system information 114. In the borehole 124, the Stoneley waves can be a dominant wave for the processing of acoustic data, because it can provide various valuable information to geoscientists and petrophysicists. Low frequency Stoneley waves, which can also be called tube waves, may be the only wave movement sensitive to the shear wave module of horizontal propagation. Processing methods can extract the slow shear wave from low frequency Stoneley waves.
    In the examples, the Stoneley waves can be excited by the unipolar transmitter 200, which can be an axisymmetric acoustic source. Thus, the distribution of Stoneley wave pressure inside and outside of borehole 124 can be axisymmetric. FIG. 2 illustrates the downhole tool 102 which can generate and receive Stoneley waves in a drilling hole filled with fluid 124 which can be surrounded by a solid formation 206. The single-pole transmitter 200 can produce acoustic signals in fluid 208 with borehole 124, which can strike the wall of borehole 132 and generate Stoneley waves. The receivers 202 can be located equally along the axis of the borehole 124 to detect the wave pressure field in the borehole 124, which can be sent to the information processing system 114 for a further processing or analysis, and / or the like. Receivers 202 can be arranged in any order, with any spacing, and can be at any angle to each other. The acoustic energy of the Stoneley waves can be distributed both in the fluid 208 of the borehole 124 and / or in the formation 206 and can contain abundant information of the fluid 208 in the borehole 124 and the formation 206.
    The slowness of Stoneley at high frequency can approach the Scholte wave slowness, while its slowness (quasi-static) at zero frequency can be a fixed value, which can be mathematically described in the equation below. :
    (1) where ^ muû is the mass density of the borehole fluid (for example, the fluid 208 of FIG. 2) and X * is the effective compressibility module, which is given by, _ 1 t 1
    K (2) for an open borehole 124 without the presence of the downhole tool
    102, where denotes an effective training shear module. More specifically, refers to the elastic modulus Ce6 for a transversely isotropic vertical formation, VTI, in the borehole 124. Taking into account the downhole tool 102, the equation can be defined as follows:
    K *
    (3)
    Γ where , 0 ° l is the volume fraction of the downhole tool 102 with respect to the borehole 124, ^ 0 ° 1 is the effective tool module. In the examples, equations (1) and (2) cannot describe formation 206 and all the variants of formation 206 that it can include. For example, it is easily possible to extend the equations to cases of arbitrary anisotropy formation by evaluating the shear modulus of effective formation as indicated below:
    —— = —-— fu n ds'
    Pfm Pb ^ b ib 0)
    J <2 where * and represent the area and the circumference of the hole section of
    U drilling, respectively, and represents the displacement of normal fluid directed away from the column of fluid.
    A quasistatic Stoneley slowness log can be produced from the information and characteristics of the borehole 124. The quasistatic Stoneley slowness log may include measurements of the quasistatic Stoneley slowness at different depths in borehole 123. In some embodiments, the expression of quasistatic Stoneley slowness may have no dependence on the size of borehole 124, which can accurately model the quasi-Stoneley slowness static and / or reverse the training shear module 206 from the quasi-static Stoneley slowness. In addition, this quasi-static Stoneley slowness has no dependence on training parameters 206 except for the effective training shear module. Thus, the formation shear module 206 can be solved by equation (1) and / or (2) without formulating any hypothesis on the characteristics and / or the formation properties 206.
    As indicated above, the quasistatic Stoneley wavelength (zero frequency Stoneley wavelength) can include precise information from the shear modulus in the horizontal direction. However, it is not possible to directly measure the quasi-static Stoneley wave due to the limitation of the frequency transmitted from the downhole tool 102 and the influence of the waves produced by the downhole tool 102 at a very low frequency band. It may not be possible to excite and / or capture zero frequency Stoneley waves with current downhole tools and 0.5 kHz may not be low enough to replace the slow wave. Stoneley at zero frequency. Figure 3 is a graph illustrating Stoneley's dispersion responses for typical rapid formation and typical slow formation, respectively. The Stoneley slowness between 0.5-2 kHz can still be different from the zero frequency Stoneley wave slowness, which can be deeper when the formation 206 can be "flexible", which can be described as a formation referring to its slower shear slowness than the slowness of borehole fluid. This can cause a larger error if we take the Stoneley wavelength at low frequency (0.5 ~ 2 kHz) as the quasi-static Stoneley wavelength in Stoneley data processing. It can be difficult to use equation (1) to obtain a training shear modulus 206 because zero frequency Stoneley slowness cannot be obtained directly by downhole tools.
    The graph in FIG. 3 can be an example of construction of an advanced and data-based method for predicting the quasistatic Stoneley wavelength from the Stoneley wave data for a typical well at frequencies between 0.5 and 2.0 kHz. The method can be flexible and reliable, and it can be adapted to complicated conditions in borehole 124 without special assumption of borehole 124 and formation 206. The estimated quasi-static Stoneley wavelength can then be used to calculate the effective shear modulus of formation 206, and can further be combined with dipole measurements, which can produce the observed Stoneley anisotropy for any type of formation 206.
    To extract the quasi-static Stoneley wavelength, an operator can choose an approach based on the frequency domain and / or a method based on the time domain. As illustrated in Figure 4, a workflow 400 for processing the frequency domain and processing the time domain is illustrated. In block 402, the waveforms captured by the receivers 202 placed equally along the borehole axis can be entered into the information processing system 114. In block 404, the range of Slowness-frequency of the Stoneley modes can be determined using an automatic slow-frequency range selection process. In block 406, a frequency domain semblance processing can be performed and, in block 408, the measured Stoneley dispersion can be extracted by choosing the maximum semblance / coherence value at each frequency. During this processing, in block 410, prior information of borehole characteristics may be entered (for example, sluggish flow of sludge, density of mud) in the information processing system 114. In the block 412, the preliminary information can be processed to carry out a direct simulation of the Stoneley wave at low frequency in an advanced model. Low-frequency Stoneley generally refers to Stoneley waves below 2 kHz in sound log data. In block 414, a simplified theoretical low frequency Stoneley dispersion model can be produced. The theoretical low frequency Stoneley dispersion model refers to a data set which can be calculated by theoretically direct modeling with known parameters. After obtaining both the theoretical dispersion model and the measured Stoneley dispersion curves, in block 416, an optimization procedure to extract the Stoneley dispersion and the quasistatic Stoneley wavelength can be performed. . The optimization procedure can be performed by minimizing the mismatch between the theoretical and measured Stoneley dispersion. In block 418, the quasi-static Stoneley wavelength is estimated by the value of slowness at zero frequency of the predicted Stoneley dispersion.
    Figure 5 illustrates a workflow for a time domain based processing workflow 500 for estimating quasistatic Stoneley wavelength from low frequency Stoneley waveform data. In block 502, a theoretical Stoneley dispersion model can be constructed with prior information, similar to the workflow 400 in Figure 4. In block 504, an advanced realized model can be used, as being similar to the method of frequency domain 400 of Figure 4. In block 506, a dispersion model, similar to the frequency domain method 400 of Figure 4, can be prepared. In block 508, the waveforms can propagate from a first receiver to an additional receiver (for example, from receiver 202 in Figure 2) by the dispersion model with test parameters. In block 510, the dispersion model test parameters can be found by minimizing the mismatch between the measured Stoneley waveform data and the predicted Stoneley waveform data, by increasing the maximum the consistency value between the measured and predicted Stoneley waveform data, and / or by maximizing the energy of the stacked waveform of all of the predicted and measured Stoneley waveform data . In block 512, the Stoneley dispersion estimates can be obtained once the test parameters can be optimized. An operator can choose the quonistatic Stoneley wavelength from the estimated Stoneley dispersion at zero frequency.
    As shown in Figures 4 and 5, a procedure in workflows can include constructions of the theoretical Stoneley dispersion model. In the examples, a Stoneley model which explains all the types of formation 206, the fluid in the borehole 124 (for example, the fluid 208 in FIG. 2) and / or the factors coming from the bottom tool of hole 102 can be complex and therefore it is unlikely to introduce a complex Stoneley dispersion model for practical field data processing. Introducing an advanced model into the workflows in Figure 3 and Figure 4 can allow an operator to make full use of information known from other logs.
    In the examples, the Stoneley dispersion can be solved by the dispersion equation and / or the characteristic equation with a digital process,
    TMp ^ DTÇDTSip, „, ANimVn = 0 where f represents the frequency, R denotes the radius of the borehole, and denotes the mass density of the mud and of the formation respectively; DTS and DTC denote the slow shear and compression compression; DTM represents the slow flow of sludge; ANI represents all the anisotropy parameters of the formation; INV designates all the invasion parameters; TL designates the parameters of the tool model. By solving equation (5) with a numerical process, the Stoneley dispersion model can be written as shown below, equation (6) can have many parameters which can increase the amount of time in which to process l 'equation (6). Thus, a simplified Stoneley dispersion model can be used in place of equation (6) to decrease the processing time. The simplified Stoneley dispersion model can be written as shown below:
    r ^ f, R, D TMp ^ DTÇp ^ s im a, b, TI ^, ( ) £
    where feature denotes a characteristic point in the dispersion curve at a point y specific frequency a and b j are newly introduced parameters that can explain the effect of anisotropy and invasion. In the Stoneley dispersion simplified model of equation (7), p t had replace the parameters (DTS, ANI, INV) ^ η5 equation (6). This simplified Stoneley dispersion model can be obtained from a Stoneley dispersion model to surround the borehole 124 by a formation 206 which can be isotropic without the mud invasion described in equation (8) ci below:
    Λν (/, R, DTM, p mud , DTC, ps {eatun , a, b, TL) = bD sr (af, R, DTM, p mud , DTC, p fm , s feature , 1,1,77. ) + (1 - b) SfiatuK noted that the basic dispersion library can be generated with g a set of parameters in the cases in which the formation 206 may be without anisotropy and mud invasion. For practical application, it may be possible to further decrease the amount of direct modeling parameters. The combination of ^ S f ea, ursa '^ can compensate for the influence of more parameters in equation (6). For example, in an extreme case, the combination of can compensate for the influences of all the parameters in equation (6) except the DTM, which can create a new equation below:
    £> ότ (/, DTM, 5 featuK , a, b) = bD ST (af, DTM, s feature , 1,1) + (1 - b) s feature y (9) although this simplification can reduce the precision of the model. Note that in equation (9), the basic library can be generated by a set of standard field data parameters. Note also that the characteristic point £ f (featw ^ featur ^ | a dj S p ers j on j e Stoneley can be selected on the dispersion curves according to the precision of the downhole tool 102.
    The introduction of adjustable parameters a and can make the treatment independent of the model hypothesis on the anisotropy and the invasion of the formation. In addition, the adjustable parameters "and ^ can be optimized using the measured Stoneley dispersion data.
    Figure 6 shows a comparison between the dispersions of
    Stoneley exact by direct modeling (solid line) and dispersion curves from the simplified Stoneley model (dotted lines). Cases of formations with a different level of anisotropy can be illustrated to reflect the accuracy of the model for formations with a different level of anisotropy. As shown in Figure 6, at frequencies below 2 kHz, the simplified model corresponds well to the exact model, while the simplified model differs from the exact model at frequencies above 2 kHz. This may suggest that the simplified dispersion model may be precise for low-frequency (<2 kHz) Stoneley waves. Furthermore, the proposed method of the present invention can process low frequency Stoneley signals; therefore, this simplified Stoneley dispersion model can make the inversion objective more precise.
    The simplified dispersion model and the Stoneley dispersion curve can be optimized to obtain the parameters ^ S f eaturia ' 1 ^ in equation (8) by minimizing the mismatch between estimated Stoneley data and measured Stoneley data. For example, the objective optimization function in the method based on the fféquential domain can be written as indicated below:
    feature ’
    fashion!
    f
    , R, DTM, p tnwi , DTQp ^, s feature , a, b,
    -D “(/) | 2
    where parameters that minimize the objective function can be used in subsequent equations. Optimization and / or inversion methods can be used. Once the optimal parameters ^ S f eaturêa '' can be obtained, an operator can calculate the estimated dispersion with equation (8), and the quasi-static Stoneley slowness can be chosen at zero frequency from the estimated dispersion curve.
    In an example of the optimization procedure for estimating the Stoneley dispersion in the frequency domain, the synthetic data for formation 206 with an anisotropy level of 0.1 as the dispersion data of entry can be used. The working frequency band selected can be 0.5 ~ 2 kHz with the downhole tool 102. The processing results are illustrated in Figure 7, where Figure 7 shows a comparison between the Stoneley data from input and final Stoneley dispersion estimates, and Figure 8 shows the cross-section of the objective function. The comparison shows that the estimate of the Stoneley dispersion corresponds well to the input Stoneley data, and the estimated quasi-static Stoneley slowness is 272.27 ps / ft, and may be close to the almost Stoneley slowness -static input of 273.34 ps / ft. In the examples, an inversion error is 0.38% and may be acceptable for processing acoustic log data.
    A visualization of the inverted results can be produced with the values of the objective function. The objective function can first be normalized as shown below:
    o min ^ Ofeature ^) (11) where denotes the global minimum of the objective function, and a sectioned figure can display the value of the function of interest with color. Note that equation (11) normalized the value of as between 0 and 1, where the higher the values, the closer the data can to the optimized response. This display process can be considered a qualitative process to monitor the optimization process and the accuracy of the estimates. Note that, in Figure 8, the image of the object function shows a single clear peak with a smooth edge, which suggests that the objective function cannot be poorly conditioned and, therefore, that inversion can be stable and reliable.
    Several examples at different levels of anisotropy are presented in FIG. 9. The synthetic Stoneley data between 0.5 kHz and 2 kHz can be processed to reach the quasi-static Stoneley wavelength. Figure 9 suggests that the estimated Stoneley dispersions may be equal to the input Stoneley data and that the mean error for the estimation of the quasi-static Stoneley wavelength is 0.192%. The processing of synthetic data suggests that the simplified Stoneley dispersion model can be precise and that the new method can provide an accurate quasi-static Stoneley wavelength.
    Figures 10a and 10b illustrate two unipolar low frequency trips of adjacent depths. It can be noted that the two triggers can be very close in terms of. depth; the quasi-static Stoneley wavelength may be close, due to the fact that the sound data can actually contribute to an average of the training section around the receivers 202. The Stoneley data in Figure 10a illustrates the high quality frequencies up to 0.15 kHz, while the Stoneley data in Figure 10b can only be read at 0.4 kHz. For the two figures 10a and 10b, the estimated Stoneley dispersions correspond to the measured Stoneley dispersions, and the quasi-static Stoneley slowness estimated for the two cases may be close to both, which suggests that the Stoneley dispersions and the slowness quasi-static can be both correctly estimated.
    Figure 11 illustrates an example of field data processing for a flexible training case in the form of logging. The quasi-static Stoneley wavelength can be superimposed on the VDL of the normalized slowness density log (NSDL) which shows the intensity of the dispersion curves at each slowness grid. In the examples, the Stoneley modes can be positively dispersive for the cases of flexible formation, the estimated quasi-static Stoneley slowness can be superimposed on the leading edge of the first local maximum on the VDL. The Stoneley estimates in Figure 11 may correspond to the leading edge of the first local maximum, which may suggest that the quasi-static Stoneley waves may be well evaluated.
    In the examples, once the quasi-static Stoneley wavelength can be extracted, the formation shear slowness and the shear slowness anisotropy can be calculated by the workflow illustrated in the figure. 12. In block 1200, the quasi-static Stoneley slowness can be obtained as described above. In block 1202, the effective Stoneley effective training shear modulus can be obtained by the equation below:
    ~ ~ DTM 2 ) ( 1 ~ r tool) hool
    X ^ mud Atool ζ J 2) without limitation, the observed anonisotropy of Stoneley can be obtained by,
    AsT AqSV ^ AqSV (13) where represents the observed Stoneley anisotropy, ^ sv represents the calculated shear modulus, block 1204, from the formation density and the vertical propagation shear wave slowness (SV ) or the quasi-vertical propagation shear slowness (quasi-SV) from the processing of dipole data,
    (14) here represents the apparent formation shear anisotropy observed by Stoneley waves. More precisely, for a case of VTI formation in a vertical well, may be the anisotropy of final shear slowness. In block 1206, the shear slowness for the case of a VTI and / or transversely isotropic inclined (TTI) formation in a deviated and / or vertical well combined with the results of data processing of crossed dipole if known the angle & between the transversely isotropic symmetrical axis (TI) and the borehole axis using equation (15):
    (15) where, Ά denotes the real shear slow anisotropy of the rock formation, ‘is the apparent shear slow anisotropy obtained from dipole treatment. Without limitation:
    AsH AqSV ^ AqSV (16) where represents the shear modulus in the axis of the borehole.
    In addition, note that equation (16) is simplified as being = when, and ^ -7 when θ = 90 °, which is consistent with the physics behind the measurements.
    These systems and methods may include any of the various features of the compositions, methods and system described in the present invention, including one or more of the following claims.
    Claim 1: method for producing a quasi-static Stoneley slowness log comprising: recording a pressure wave at a receiver; determining a slow-frequency range with an information processing system from the pressure wave; the treatment of a semblance of the frequency domain; extracting a Stoneley dispersion; minimization of a mismatch between the theoretical dispersion and the Stoneley dispersion; and the identification of the quasi-static Stoneley slowness from the Stoneley dispersion.
    Claim 2: Method according to claim 1, further comprising: the discovery of borehole characteristics; the realization of an advanced model with borehole characteristics; and the construction of a low-frequency Stoneley dispersion model.
    Claim 3: Method according to claim 2 or claim 1, in which the borehole characteristics include the slowness of the sludge or the density of the mud.
    Statement 4: method according to any preceding statement, in which the Stoneley dispersion model at low frequency is created from W , R, DT ^ DTCDTSp ^ UNV, TP θ. f | a frR es (a radius d <j borehole, is the mass density of the mud, represents the formation respectively; DTS is the shear of formation, DTC is the slow compression wave, DTM is the slow d 'sludge flow, ANI are the parameters of anisotropy of the formation, INV are the parameters of invasion, and TL are the parameters of a tool model.
    Affirmation 5: method according to any preceding assertion, in which the extraction of the Stoneley dispersion comprises the identification of a maximum semblance / coherence value at a frequency.
    Statement 6: Method according to any preceding statement, in which the minimization of a mismatch between the theoretical dispersion and the Stoneley dispersion comprises the comparison of the extracted Stoneley dispersion with the Stoneley dispersion model at low frequency.
    Claim 7: method according to any preceding claim, further comprising the display of the quasi-static slowness in a log.
    Claim 8: method for producing a quasi-static Stoneley slowness log comprising: recording a pressure wave at a first receiver; the entry of borehole characteristics into an information processing system; the realization of an advanced model with the information processing system;
    the construction of a low-frequency Stoneley dispersion model; propagation of a waveform to a second receiver; minimizing a mismatch between predicted and measured Stoneley waveform data to estimate the final Stoneley dispersion; and the identification of the quasi-static Stoneley slowness from the estimate of the final Stoneley dispersion.
    Claim 9: Method according to claim 8, in which the characteristics of the borehole include the slowness of the sludge or the density of the mud.
    Claim 10: method according to claim 8 or claim 9, in which the construction of a low frequency Stoneley dispersion model is created from yj at frequency, R is a borehole radius , ^ mua is the mass density of the mud, represents the formation respectively; DTS is the shear of formation, DTC is the slowness of compression wave, DTM is the slowness of sludge flow, ANI are the parameters of anisotropy of the formation, INV are the parameters of invasion, and TL are the parameters of a tool model, feature is a characteristic point in a dispersion curve at a point of specific frequency, ° and 5 are parameters which explain the effect of anisotropy and invasion.
    Affirmation 11: method according to any preceding assertion, in which the propagation of a waveform towards a second receiver is carried out with at least one test parameter.
    Affirmation 12: Method according to any preceding assertion, in which the minimization of the mismatch between predicted and measured Stoneley waveform data comprises the maximum increase of a coherence value between the predicted and measured Stoneley waveform data.
    Statement 13: Method according to any preceding claim, wherein minimizing the mismatch between predicted and measured Stoneley waveform data includes maximizing the energy of a shape wave stack of predicted and measured Stoneley waveform data.
    Claim 14: method according to any preceding claim, comprising the display of the quasi-static Stoneley slowness on a log.
    Statement 15: Well measurement system for the production of a quasi-static Stoneley slowness log and a shear slowness anisotropy for a transversely isotropic vertical formation comprising: a downhole tool; a vehicle, in which the downhole tool is attached by means of transportation to the downhole tool; and an information processing system operable to record a pressure wave at a receiver; determining a slow-frequency range with an information processing system from the pressure wave; the treatment of a semblance of the frequency domain; extracting a Stoneley dispersion; minimization of a mismatch between the theoretical dispersion and the Stoneley dispersion; and the identification of the quasi-static Stoneley slowness from the Stoneley dispersion.
    Claim 16: Method according to claim 15, in which the information processing system can operate to obtain anisisropropia of slow formation shear for a transversely isotropic inclined formation.
    Affirmation 17: procedure according to affirmation 15 or Γ affirmation
    16, wherein the formation density and a layer tilt angle is calculated from fïïh "_ cosJ s | + icos ^
    UJ λ = 4 (1 + 277) cos 4 Θ - (1 + 2 £) cos 2 0sin 2 Θ + S - --— where 4 is the slowness anisotropy of
    T real shear of the rock formation, 1 is the apparent shear anisotropy obtained from dipole treatment and is the shear anisotropy of apparent formation observed by Stoneley waves.
    Claim 18: method according to any preceding claim, in which an anisotropy of apparent shear slowness is detected with
    AsH AqSV ^ AqSV where 1 is the anisotropy of apparent shear slowness obtained from a dipole treatment, ^ sv is a shear modulus for vertically polarized shear waves and is the shear modulus for propagation of Shear waves polarized horizontally in the axis of the borehole.
    Statement 19: Method according to any preceding statement, in which the information processing system can operate to calculate a shear modulus of effective Stoneley formation and is detected with, is
    A1SV Statement 20: Method according to any preceding statement, in which the information processing system can operate to calculate pour _ AsT ~ AqSV a shear anisotropy of formation and is detected with 2 // qSV the anisotropy of apparent formation shear observed by Stoneley waves, a shear modulus for vertically polarized shear waves calculated from a dipole data processing, and is the effective Stoneley formation shear module.
    The preceding description provides different examples of the systems and methods of use described in the present invention which may contain different process steps and alternative combinations of components. It should be understood that, although individual examples may be described in the present invention, it covers all combinations of the examples described, including, without limitation, the different combinations of components, the combinations of process steps and the system properties. It should be understood that the compositions and methods described by the terms "comprising", "containing" or "including" describe various components or steps, the compositions and methods may also "consist essentially of" or "consist" of the different components and steps. In addition, the indefinite articles "a" or "an", as used in the description, are defined in the present invention as designating one or more of the elements which they introduce.
    For reasons of brevity, only certain ranges are explicitly described in the present invention. However, ranges from any lower limit can be combined with any upper limit to describe a range not explicitly described, just as ranges from any lower limit can be combined with any other lower limit to describe a range not explicitly described, and similarly, ranges from any upper limit can be combined with any other upper limit to describe a range not explicitly described. In addition, whenever a numeric range with a lower limit and an upper limit is described, any number and any range included in the range is specifically described. In particular, any range of values (of the form, "from about a to about b", or, equivalently, "from about a to b", or, equivalently, "from about ab") described in the present invention is to be understood as stating all the numbers and all the ranges included in the widest range of values, even if it is not explicitly described. Thus, each point or individual value can serve as its own lower or upper limit combined with any other point or individual value or with any other lower or upper limit, to describe a range not explicitly described.
    Therefore, the present examples are well suited to achieve the ends and advantages mentioned as well as those inherent therein. The particular examples described above are only illustrative examples, and can be modified and practiced in different but equivalent ways, obvious to those skilled in the art having the advantage of the teachings presented in the present invention. Although individual examples are described, the invention covers all combinations of all 10 examples. Furthermore, there is no limitation to the construction or design details presented in the present invention, except in the cases described in the claims below. Furthermore, the terms in the claims have their clear and ordinary meaning, unless they are explicitly and clearly defined in any other way by the patent owner. It is therefore obvious that the particular illustrative examples described above can be altered or modified and all these variations are considered within the scope and spirit of these examples. In case of conflict in the use of a word or term in this description and one or more patents or other documents, the definitions in accordance with this description must be adopted.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. Method (400; 500) for producing a quasi-static Stoneley slowness log comprising:
    recording a pressure wave (402) at a receiver (202);
    determining a slow-frequency range (404) with an information processing system (114) from the pressure wave;
    processing a semblance of the frequency domain (406); extracting a Stoneley dispersion (408);
    minimization of a mismatch between the theoretical dispersion and the Stoneley dispersion (416; 510); and the identification of the quasi-static Stoneley slowness from the Stoneley dispersion (418; 512).
    [2" id="c-fr-0002]
    2. Method (400; 500) according to claim 1, further comprising:
    discovering borehole features (410; 502);
    making an advanced model with borehole characteristics (412; 504);
    the construction of a low-frequency Stoneley dispersion model (414; 506); and the optional display of quasi-static slowness in a log.
    [3" id="c-fr-0003]
    The method (400; 500) according to claim 2, wherein the borehole characteristics include the slowness of the sludge or the density of the sludge.
    [4" id="c-fr-0004]
    The method (400; 500) of claim 2, wherein the low frequency Stoneley dispersion model is created from o . f Kt la R es [k κγοη & hole drilling, is the mass density of the mud, represents the formation respectively; DTS is the shear of formation, DTC is the slowness of compression wave, DTM is the slowness of sludge flow, ANI are the anisotropy parameters of the formation, INV are the parameters of invasion and TL are the parameters of a tool model.
    [5" id="c-fr-0005]
    5. Method (400; 500) according to any one of claims 2 to 4, in which the extraction of the Stoneley dispersion (408) comprises the identification of a maximum semblance / coherence value at a frequency and optionally wherein minimizing a mismatch between the theoretical dispersion and the Stoneley dispersion (416; 510) includes comparing the extracted Stoneley dispersion with the low frequency Stoneley dispersion model.
    [6" id="c-fr-0006]
    The method (400; 500) according to any preceding claim, further comprising propagating a waveform to a second receiver (508).
    [7" id="c-fr-0007]
    The method (400; 500) of claim 6, further comprising propagating a waveform, wherein the borehole characteristics include slowness of sludge flow or density of mud, and optionally wherein the propagation of a waveform to a second receiver (508) is effected with at least one test parameter.
    [8" id="c-fr-0008]
    8. Method (400; 500) according to claim 6 or 7, in which the construction of a low frequency Stoneley dispersion model is created from / -W (/ & DTtyp m ^ DTÇPfa, Sfe ^ e affi, TL) o ù y frequency, R is the borehole radius, MUU ^ is the mass density of the mud, represents the formation respectively; DTS is the shear of formation, DTC is the slowness of compression wave, DTM is the slowness of the mud, ANI are the parameters of anisotropy of the formation, INV are the parameters of invasion, and TL are the parameters d 'a tool model, feature is a characteristic point in a dispersion curve at a point of specific frequency, a and are the parameters which explain the effect of anisotropy and invasion.
    [9" id="c-fr-0009]
    The method (400; 500) according to any one of claims 6 to 8, wherein minimizing the mismatch between predicted and measured Stoneley waveform data (416; 510) includes the maximizing a consistency value between the predicted and measured Stoneley waveform data, or optionally wherein minimizing the mismatch between the predicted and measured Stoneley waveform data includes maximizing the energy of a stacked waveform to the maximum of the predicted and measured Stoneley waveform data.
    [10" id="c-fr-0010]
    10. Method (400; 500) according to any one of claims 6 to 9, comprising the display of the quasi-static Stoneley slowness in a log.
    [11" id="c-fr-0011]
    11. Well measurement system (100) for the production of a quasi-static Stoneley slowness log and a shear slowness anisotropy for a transversely vertical isotropic formation comprising:
    a downhole tool (102);
    a vehicle (104), in which the downhole tool is attached by a means of transport (110) to the vehicle; and an information processing system (114) operable to record a pressure wave at a receiver (202); determine a slow-frequency range with an information processing system from a pressure wave; treat a semblance of the frequency domain; extract a Stoneley dispersion; minimize a mismatch between the theoretical dispersion and the Stoneley dispersion; and identify the quasi-static Stoneley slowness from the Stoneley dispersion.
    [12" id="c-fr-0012]
    The well measurement system (100) of claim 11, wherein the information processing system (114) is operable to obtain anisisropropia of formation shear slowness for transversely isotropic inclined formation, and optionally in which the formation density and a layer tilt angle are calculated at ^ sin 2 # 2 /) ® 2 x.
    --cos Θ + ccos Θ l 8 J
    2 = · 4 (1 + 277) cos 4 # - (l + 2 £) cos 2 6 Sin 2 0 + ^ ——.
    from & where is the real shear slow shear anisotropy, is the apparent shear slow anisotropy obtained from dipole treatment and is the apparent shear anisotropy observed by the Stoneley waves.
    [13" id="c-fr-0013]
    13. Well measurement system (100) according to claim 12, wherein an anisotropy _ ASH ~ AqSV
    2 LL T of apparent shear slowness is detected with ^ qSV where 1 is the anisotropy of apparent shear slowness obtained from a dipole treatment, ^ sv is a shear modulus for vertically polarized shear waves and is the shear module for the propagation of horizontally polarized shear waves in the borehole axis.
    [14" id="c-fr-0014]
    The well measurement system (100) according to any of claims 11 to 13, wherein the information processing system (114) can operate to compute a shear modulus of effective Stoneley formation and is detected. by AsT hr 2 --p ™ 2 h-ûo 01 ) r tool
    UdOl
    [15" id="c-fr-0015]
    15. Well measurement system (100) according to any one of claims 11 to 14, in which the information processing system (114) can operate to calculate a ξ _ AsT AqSV
    15 shear formation anisotropy and is detected by 2 // qSV . ξ egt i ' an i so rO pi e apparent formation shear observed by Stoneley waves, ^ sv is a shear modulus for the vertically polarized shear waves calculated from the processing of dipole data and is the modulus of effective Stoneley formation shear.
    ί / 7
    132
    217
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    优先权:
    申请号 | 申请日 | 专利标题
    IBWOUS2016068745|2016-12-27|
    PCT/US2016/068745|WO2018125058A1|2016-12-27|2016-12-27|Quasi-static stoneley slowness estimation|
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