Method and device for evaluating radial ductility of near-wellbore fractures

Abstract

The present application discloses a method and device for evaluating the radial ductility of near-wellbore fractures, which relates to the field of acoustic logging. The method comprises: collecting array acoustic wave full-wave train data before and after fracturing for the near-wellbore zone of the target well, wherein the array acoustic wave full-wave train data comprises: monopole full-wave data and dipole full-wave data; using longitudinal wave travel time tomography technology to process the monopole full-wave data before and after fracturing, and making a difference; using Gaussian beam offset imaging technology to process the dipole full-wave data before and after fracturing, and making a difference; using scattered wave radial energy imaging technology to process the dipole full-wave data before and after fracturing, and making a difference; based on the imaging results obtained by the above three technologies before and after fracturing, the radial ductility of the near-wellbore fractures is precisely evaluated. The present application can effectively improve the evaluation accuracy of the radial extension characteristics of the reservoir fracture network, has good application effect and high applicability, and at the same time provides a new idea for the evaluation of the fracturing effect of unconventional reservoirs.

Description

Technical Field

[0001] The present application relates to the field of acoustic well logging, and in particular to a method and device for evaluating radial ductility of near-wellbore pressure fractures. Background Art

[0002] In recent years, with the continuous deepening of offshore exploration and development, low-permeability reservoirs have become the key area for increasing oil and gas reserves and production in my country. Low-permeability reservoirs must be fractured to obtain industrial oil and gas flows. Therefore, fracturing is an inevitable way to assist the exploration and development of low-permeability reservoirs. How effective is the fracturing of low-permeability reservoirs and whether the expected effect of fracturing construction is achieved has become a difficult problem in the exploration and development of low-permeability reservoirs.

[0003] At present, the mainstream logging evaluation technologies for reservoir fracturing transformation effects mainly include well temperature method, radioactive tracer method, non-radioactive tracer method, optical fiber method, anisotropy analysis method, radial tomography method, etc. However, the above methods can only evaluate the height of the fracture, but not the radial extension characteristics of the fracture. Although the microseismic method can evaluate the length, height, width and other information of the fracture, due to the limited space for offshore fracturing operations, it is still difficult to implement microseismic technology offshore. Therefore, there is an urgent need for a solution with high applicability and the ability to accurately evaluate the radial extension of the fracture near the wellbore. Summary of the invention

[0004] In view of the above problems, the present application is proposed to provide a method and device for evaluating radial ductility of near-wellbore pressure fractures that overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of an embodiment of the present application, a method for evaluating radial ductility of a near-wellbore fracture is provided, wherein the method comprises:

[0006] Collecting array acoustic wave full wave train data before and after fracturing corresponding to the near-wellbore zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data;

[0007] The P-wave travel time tomography method is used to process the monopolar full wave data before fracturing and the monopolar full wave data after fracturing respectively, so as to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and the relative radial velocity profile difference is calculated according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing;

[0008] The Gaussian beam migration imaging method is used to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing, respectively, to obtain the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing, and the Gaussian beam migration imaging difference is calculated according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing;

[0009] The scattered wave radial energy imaging method is used to process the dipole full wave data before fracturing and the dipole full wave data after fracturing respectively, to obtain the energy envelope before fracturing and the energy envelope after fracturing, and the scattered wave energy difference is calculated according to the energy envelope before fracturing and the energy envelope after fracturing;

[0010] The radial ductility of the near-wellbore fracture is evaluated based on the relative radial velocity profile difference, Gaussian beam migration imaging difference and scattered wave energy difference, and the radial ductility evaluation result of the fracture is obtained.

[0011] Furthermore, the monopolar full-wave data is processed by using the P-wave travel time tomography method to obtain the formation P-wave relative radial velocity profile further including:

[0012] S1, determine the initial velocity model;

[0013] S2, based on the velocity model, forward calculation of the reference travel time using the ray tracing method;

[0014] S3, if the difference between the reference travel time and the measured travel time is greater than the preset difference, the velocity model is updated and the process jumps to S2;

[0015] S4, if the difference between the reference travel time and the measured travel time is less than or equal to a preset difference, determining the velocity model as a final velocity model;

[0016] S5, determining the velocity of the radial maximum penetration depth based on the monopole full-wave data, and calculating the relative radial velocity profile of the P-wave of the formation based on the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model.

[0017] Furthermore, calculating the relative radial velocity profile of the P-wave of the formation according to the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model further includes:

[0018] The relative radial velocity profile of the formation P-wave is calculated using the following formula:

[0019]

[0020] in, is the relative radial velocity profile of the formation P-wave, is the velocity at the maximum radial penetration depth, is the longitudinal wave velocity at different radial distances at any depth in the final velocity model.

[0021] Furthermore, the dipole full-wave data is processed by using a Gaussian beam migration imaging method to obtain Gaussian migration imaging results of the formation outside the well, which further includes:

[0022] Use dipole full-wave data and Green's function to construct direct sound field and reverse propagation sound field;

[0023] The Green's function is approximated by combining the superposition of Gaussian beams, and the cross-correlation between the direct sound field and the reverse propagation sound field is calculated based on the asymptotic result;

[0024] The geological structure outside the well is imaged based on the cross-correlation to obtain the Gaussian migration imaging result of the formation outside the well.

[0025] Furthermore, the dipole full-wave data is processed by using the scattered wave radial energy imaging method to obtain the energy envelope, which further includes:

[0026] Performing filtering processing on the dipole full-wave data to obtain filtered dipole full-wave data;

[0027] The filtered dipole full-wave data are normalized using the dipole direct wave amplitude to obtain normalized dipole full-wave data;

[0028] The normalized dipole full-wave data are Hilbert transformed to obtain the corresponding energy envelope.

[0029] Furthermore, before filtering the dipole full-wave data, the method further includes: converting the dipole full-wave data into an earth coordinate system using an instrument azimuth curve;

[0030] Filtering the dipole full-wave data to obtain filtered dipole full-wave data further includes: performing bandpass filtering and fk filtering on the converted waveform data.

[0031] According to another aspect of an embodiment of the present application, a device for evaluating radial ductility of a near-wellbore hydraulic fracture is provided, the device comprising:

[0032] The acquisition module is suitable for acquiring array acoustic wave full wave train data before fracturing and array acoustic wave full wave train data after fracturing corresponding to the near-well zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data;

[0033] The first processing module is suitable for using the P-wave travel time tomography method to process the monopolar full wave data before fracturing and the monopolar full wave data after fracturing, respectively, to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and to calculate the relative radial velocity profile difference according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing;

[0034] The second processing module is adapted to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing respectively by using a Gaussian beam migration imaging method to obtain Gaussian migration imaging results of the out-of-hole formation before fracturing and Gaussian migration imaging results of the out-of-hole formation after fracturing, and calculate the Gaussian beam migration imaging difference according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing;

[0035] The third processing module is suitable for using the scattered wave radial energy imaging method to process the dipole full wave data before fracturing and the dipole full wave data after fracturing, respectively, to obtain the energy envelope before fracturing and the energy envelope after fracturing, and to calculate the scattered wave energy difference according to the energy envelope before fracturing and the energy envelope after fracturing;

[0036] The evaluation module is suitable for evaluating the radial ductility of the near-wellbore fracture according to the relative radial velocity profile difference, Gaussian beam migration imaging difference and scattered wave energy difference, and obtaining the radial ductility evaluation result of the fracture.

[0037] According to another aspect of the embodiment of the present application, there is provided a computing device, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0038] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned radial ductility evaluation method of near-wellbore zone hydraulic fractures.

[0039] According to another aspect of the embodiments of the present application, a computer storage medium is provided, in which at least one executable instruction is stored, and the executable instruction enables a processor to perform operations corresponding to the above-mentioned method for evaluating radial ductility of near-wellbore zone hydraulic fractures.

[0040] According to another aspect of the present application, a computer program product is provided, comprising at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the above-mentioned method for evaluating radial ductility of near-wellbore zone hydraulic fractures.

[0041] According to the technical solution provided in the present application, based on the fact that fracturing causes the formation rock to break, generate a large number of cracks, and form rock expansion, the rock elastic wave velocity caused by rock expansion decreases, and the longitudinal wave tomography technology can reconstruct the rock elastic wave velocity changes near the wellbore wall (within 1m). At the same time, fracturing will enhance the formation heterogeneity. The near-wellbore reflection wave Gaussian beam migration imaging technology and the wellside scattered wave radial energy imaging technology can characterize the near-wellbore zone (within 2-30m) The heterogeneous wave impedance interface information, mainly by comparing the radial velocity profiles before and after fracturing, the near-wellbore reflection wave Gaussian beam migration imaging, and the wellside scattered wave radial energy imaging The difference in logging responses is used to evaluate the radial extension effect of the fracture in the near-wellbore range (within 1-30m). This application can solve the problem of evaluating the radial extension characteristics of fractures in the current evaluation of reservoir fracturing transformation effects. By comprehensively utilizing longitudinal wave tomography technology, near-wellbore reflected wave Gaussian beam migration imaging technology, and wellside scattered wave radial energy imaging technology, the radial extension of fractures near the wellbore zone can be evaluated, which can effectively improve the evaluation accuracy of the radial extension characteristics of the reservoir fracture network. The method of this application has good application effect and high applicability, and at the same time provides a new idea for the evaluation of unconventional reservoir fracturing effects.

[0042] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0044] Figure 1 A schematic flow chart of a method for evaluating radial ductility of near-wellbore zone hydraulic fractures according to an embodiment of the present application is shown;

[0045] Figure 2 This is a result diagram of radial ductility evaluation of hydraulic fractures in the near-wellbore zone of an offshore well to be evaluated;

[0046] Figure 3 A structural block diagram of a device for evaluating radial ductility of near-wellbore zone hydraulic fractures according to an embodiment of the present application is shown;

[0047] Figure 4 A schematic diagram of the structure of a computing device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] Figure 1 FIG. 1 is a flow chart of a method for evaluating radial ductility of near-wellbore fractures according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0050] Step S101, collecting array acoustic wave full wave train data before fracturing and array acoustic wave full wave train data after fracturing corresponding to the near-wellbore zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data.

[0051] Specifically, an acoustic logging instrument can be used to perform array acoustic logging in the near-well zone of the target well (for example, within a range of 1-30 meters, and of course other ranges) to obtain array acoustic full wave train data, wherein the array acoustic full wave train data includes: monopole full wave data and dipole full wave data. It should be noted that here, before the fracturing treatment, an array acoustic logging needs to be performed once, so that the array acoustic full wave train data before fracturing can be collected, and after the fracturing treatment, an array acoustic logging needs to be performed again, so that the array acoustic full wave train data after fracturing can be collected.

[0052] Step S102, using the P-wave travel time tomography method to process the monopolar full wave data before fracturing and the monopolar full wave data after fracturing, respectively, to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and calculate the relative radial velocity profile difference according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing.

[0053] Specifically, the P-wave travel time tomography method reconstructs the velocity distribution of the underground medium by analyzing the travel time data of seismic waves. The P-wave travel time tomography method is used to process the monopole full wave data before fracturing and the monopole full wave data after fracturing respectively to reconstruct the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing. In order to facilitate the analysis of the reservoir transformation caused by fracturing, the P-wave relative radial velocity profile of the formation before fracturing can be subtracted from the P-wave relative radial velocity profile of the formation after fracturing to obtain the difference between the P-wave relative radial velocity profiles of the formation before and after fracturing, that is, to obtain the relative radial velocity profile difference.

[0054] In an optional implementation, the monopolar full-wave data is processed by the P-wave travel time tomography method to obtain the formation P-wave relative radial velocity profile, which can be further achieved by the following method:

[0055] S1, determine the initial velocity model;

[0056] S2, based on the velocity model, forward calculation of the reference travel time using the ray tracing method;

[0057] S3, if the difference between the reference travel time and the measured travel time is greater than the preset difference, the velocity model is updated and the process jumps to S2;

[0058] S4, if the difference between the reference travel time and the measured travel time is less than or equal to a preset difference, determining the velocity model as a final velocity model;

[0059] S5, determining the velocity of the radial maximum penetration depth based on the monopole full-wave data, and calculating the relative radial velocity profile of the P-wave of the formation based on the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model.

[0060] Specifically, the whole processing idea is to use the ray tracing method to establish the longitudinal wave radial velocity profile and obtain the velocity model of the formation near the wellbore wall in the axial and radial directions. The following is a detailed description. The present invention uses a two-dimensional velocity profile to represent the velocity model. First, a two-dimensional velocity profile function v(r,z) is selected and the acoustic wave travel time is calculated by the ray tracing method, as shown in formula (1), which is defined as the reference travel time. , the formula is as follows:

[0061] (1)

[0062] Among them, z is the position along the well axis, r is the position along the radial direction of the wellbore, v(r,z) is the two-dimensional velocity profile function, and s is the shortest path traveled by the longitudinal wave in the monopole full wave in the formation.

[0063] The reference travel time calculated by formula (1) is compared with the measured travel time. For the formation with no radial change in v(r,z), the reference travel time is consistent with the measured travel time. The model with the velocity from 0m to infinity from the wellbore wall is v(z) (where v(z) is the formation longitudinal wave sound velocity curve obtained by processing the monopole full-wave data using the STC method, is the velocity at the maximum radial penetration depth, and is the velocity of the formation far from the wellbore) is the initial velocity model.

[0064] According to the initial velocity model, the reference travel time is forward calculated using the ray tracing method. If the difference between the reference travel time and the measured travel time is greater than the preset difference, that is, the measured travel time lags behind the reference travel time, the velocity model is updated to make the measured travel time coincide with or approach the reference travel time. For example, the following update processing can be performed: the velocity from 0m to drm near the well wall is reduced to v(z)-dv, and the velocities at other radial depths remain unchanged. The reference travel time is recalculated based on the updated velocity model; if the difference between the reference travel time and the measured travel time is greater than the preset difference, the velocity from 0m to drm near the well wall is reduced to v(z)-2dv, and the velocities at drm to 2dr The velocity at point m is reduced to v(z)-dv, and the velocities at other radial depths remain unchanged. The reference travel time is recalculated based on the updated velocity model, and so on. The velocity model is updated repeatedly until the difference between the reference travel time and the measured travel time is less than or equal to the preset difference, that is, the measured travel time coincides with or is close to the reference travel time. The velocity model at this time is the final velocity model v(r,z) required, and the velocity in this model is the absolute velocity.

[0065] The STC method is used to process the monopole full-wave data to obtain the formation P-wave velocity curve, from which the velocity of the maximum radial penetration depth can be determined. Then, the formation P-wave relative radial velocity profile is calculated based on the velocity of the maximum radial penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model. For example, the relative velocity change profile at any depth can be calculated according to formula (2), thereby calculating the formation P-wave relative radial velocity profile. Formula (2) is as follows:

[0066] (2)

[0067] in, is the relative radial velocity profile of the formation P-wave, is the velocity at the maximum radial penetration depth, The P-wave velocity at different radial distances at any depth in the final velocity model.

[0068] Here, the above method is used to process the monopole full-wave data before fracturing and the monopole full-wave data after fracturing, so as to obtain the relative radial velocity profile of the longitudinal wave of the formation before fracturing and the relative radial velocity profile of the longitudinal wave of the formation after fracturing.

[0069] Step S103, using the Gaussian beam migration imaging method to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing, respectively, to obtain the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing, and calculating the Gaussian beam migration imaging difference according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing.

[0070] Gaussian beam migration imaging is an advanced seismic imaging technique that uses Gaussian beam approximation to improve the accuracy and resolution of imaging. The Gaussian beam method is used to simulate the propagation of sound waves in the formation.

[0071] The Gaussian beam migration imaging technique is used to process the dipole full-wave data before and after fracturing, respectively, to obtain Gaussian migration imaging results of the out-of-hole formation before and after fracturing. In an optional implementation, the Gaussian beam migration imaging method is used to process the dipole full-wave data, and the Gaussian migration imaging results of the out-of-hole formation can be further achieved by the following method: using the dipole full-wave data and the Green's function to construct a direct sound field and a reverse propagation sound field;

[0072] The Green's function is approximated by combining the superposition of Gaussian beams, and the cross-correlation between the direct sound field and the reverse propagation sound field is calculated based on the asymptotic result;

[0073] The geological structure outside the well is imaged based on the cross-correlation to obtain the Gaussian migration imaging result of the formation outside the well.

[0074] Specifically, it can be achieved through the following process:

[0075] ① Input dipole full wave data, here use To represent, the dipole full-wave data is processed to obtain the velocity model in the offset domain .in, Represents the emission point The waveform data at is the well axis position The recorded waveform changes over time.

[0076] ② First calculate the dynamic parameters obtained from the sound source position: Rays are emitted at different angles, and then kinematic and dynamic tracing are performed using formula (3) to evaluate the ray path and dynamic parameters. p and q .

[0077]

[0078] in, s is the arc length of the ray; is the distance from a point outside the ray to the ray; is the exit angle of the Gaussian beam.

[0079] ③ Calculate the propagation sound field of the direct sound field: Calculate the imaging point through the sound source excitation ray traced in step ② Then, the direct wave field is calculated by formula (4).

[0080]

[0081] Where Re represents the real part of a complex number; is the frequency domain excitation function of the sound source of the logging tool, which is generally a Ricker wavelet. ω represents the angular frequency; Reason Point (sound source point) emission, point on the ray path The direct wave field calculated at t change; for The velocity of the offset domain at the point; u ( s , n , ω ) is the frequency domain expression of the Gaussian beam.

[0082] ④ Calculate the reverse propagation sound field emitted from the imaging point near the well: Rays are emitted at different angles and the same method as in ② is used for ray tracing. Then, the effective amplitude of the Gaussian beam is calculated using formula (5), and the Green's function is evaluated using formula (6). Finally, the reverse propagation sound field is obtained using formula (7).

[0083]

[0084] in, is the arrival time on the central ray; The exit angle is The initial amplitude of the Gaussian beam; is the velocity on the central ray; i is an imaginary unit; ω is the angular frequency, is any point in the Gaussian ray beam The waveform at is a point in the offset domain obtained at z = 0, time t and T The sound field is propagated in reverse at time t0.

[0085] ⑤ Using the direct wave field and reverse propagation sound field calculated by the above processes ③ and ④, the correlation value between the direct wave field and the reverse propagation wave field is calculated using formula (8): To image the geological structure outside the well, and finally obtain the wellside point imaging results.

[0086] (8)

[0087] in, is the correlation value between the direct wavefield and the reverse propagation wavefield, that is, the Gaussian beam migration imaging expression.

[0088] Assumptions If there is a reflector at that point, the two wave fields are in phase with each other at that point and have a higher coherence value after superposition.

[0089] ⑥ Repeat steps ③-⑤ for the dipole full-wave data at all depth points to obtain the Gaussian migration imaging results of the formation outside the well.

[0090] The Gaussian migration imaging result of the out-of-hole formation after fracturing is subtracted from the Gaussian migration imaging result of the out-of-hole formation before fracturing to obtain the difference between the Gaussian migration imaging before and after fracturing, that is, the calculated Gaussian beam migration imaging difference.

[0091] Step S104, using the scattered wave radial energy imaging method to process the dipole full wave data before fracturing and the dipole full wave data after fracturing, respectively, to obtain the energy envelope before fracturing and the energy envelope after fracturing, and calculate the scattered wave energy difference according to the energy envelope before fracturing and the energy envelope after fracturing.

[0092] Specifically, the dipole full-wave data is converted to the earth coordinate system using the instrument azimuth curve, and the converted waveform data is subjected to bandpass filtering and fk filtering to eliminate the random noise in the logging and the reflection interference from the layer interface, and the filtered dipole full-wave data is obtained. In order to facilitate the comparison of the energy difference of the dipole scattered wave before and after fracturing, the dipole direct wave amplitude is used to normalize the filtered data to obtain the normalized dipole full-wave data, as shown in formula (9):

[0093] (9)

[0094] in, is the normalized dipole full-wave data, is the dipole direct wave amplitude, is the filtered dipole full-wave data.

[0095] The energy envelope of the normalized dipole acoustic logging data is obtained by performing Hilbert transform. For example, the energy envelope of the data can be obtained by performing Hilbert transform using formula (10):

[0096] (10)

[0097] Wherein: Hilbert {·} is the Hilbert transform of the data in brackets {·}; B(z, t) is the energy envelope of the dipole acoustic wave data after the Hilbert transform.

[0098] According to the above calculation principle, the dipole full waves before and after fracturing are processed respectively to obtain the energy envelopes before and after fracturing. The difference between the energy envelopes before and after fracturing at each depth point is calculated respectively to obtain the scattered wave energy difference.

[0099] It should be noted that this embodiment does not limit the execution order of step S102 to step S104.

[0100] Step S105, evaluating the radial ductility of the near-wellbore fracture according to the relative radial velocity profile difference, the Gaussian beam migration imaging difference and the scattered wave energy difference, and obtaining the radial ductility evaluation result of the fracture.

[0101] The P-wave travel time tomography technology mainly reflects the radial velocity change of the formation direct P-wave within 1-2m near the wellbore wall. By comparing the radial velocity profile change before and after fracturing, the reservoir transformation within 1-2m near the wellbore wall can be evaluated. The Gaussian beam migration imaging technology mainly reflects the imaging of the formation reflection wave within 2-6m near the wellbore. By comparing the Gaussian beam migration imaging change before and after fracturing, the reservoir transformation within 2-6m near the wellbore wall can be evaluated. The scattered wave radial energy imaging technology mainly reflects the energy change of the scattered wave radiated by the dipole sound source within 6-30m far from the wellbore due to the formation heterogeneity. By comparing the scattered wave imaging change before and after fracturing, the reservoir transformation within 6-30m far from the wellbore can be evaluated. The above three technologies are applied in combination to accurately evaluate the radial ductility of the fracture within 1-30m near the wellbore.

[0102] Figure 2This is a result diagram of radial ductility evaluation of fractures in the near-well zone of an offshore well to be evaluated. In the figure, the first track is the lithology curve, the second track is the resistivity curve, the third track is the porosity curve, the fourth track is the fracturing section, the fifth track is the depth track, the sixth track is the difference between the relative radial velocity profiles before and after fracturing, the seventh track is the difference between the Gaussian beam migration imaging before and after fracturing, and the eighth track is the difference in scattered wave energy before and after fracturing. The fracturing sections of this well are 3031-3032m, 3037-3038m, and 3048-3049m. According to the difference in relative radial velocity profiles before and after fracturing, the difference in Gaussian beam migration imaging, and the difference in scattered wave energy, it is shown that the areas where the reservoir in this section undergoes significant changes before and after fracturing are mainly concentrated in 3027-3034.5m (section 1), 3036-3040m (section 2), and 3045-3055m (section 3). The relative radial velocity profiles in these three sections after fracturing change significantly. The obvious change indicates that the longitudinal wave velocity of the formation has obviously decreased in the radial direction, indicating that the reservoir has been affected by the fracturing operation, and fractures and micro fractures have been generated within 1m from the wellbore wall. At the same time, the Gaussian beam offset imaging and scattered wave energy imaging after fracturing show obvious reflection information next to the well, indicating that the fractures generated by the reservoir under the influence of the fracturing operation have further extended radially, and obvious fractures have been generated within 1-14m from the wellbore wall. In summary, this well has formed an obvious fracturing volume transformation within a range of at least 14m around the wellbore. This well had no production capacity before fracturing, and after fracturing, it produced 19.5 cubic meters of oil per day and 1589 cubic meters of gas per day. Combined with the production information, the evaluation of the fracturing effect by the above method is further verified, and finally the correctness and effectiveness of the method proposed in the present invention for finely evaluating the radial ductility of fractures in the near-wellbore zone is explained.

[0103] In summary, the present application is based on the fact that fracturing causes the formation rock to break, generate a large number of cracks, and form rock expansion. The rock elastic wave velocity caused by rock expansion decreases, and the longitudinal wave tomography technology can reconstruct the rock elastic wave velocity changes near the wellbore wall (within 1m). At the same time, fracturing will enhance the formation heterogeneity. The near-wellbore reflection wave Gaussian beam migration imaging technology and the wellside scattered wave radial energy imaging technology can characterize the near-wellbore zone (within 2-30m) The heterogeneous wave impedance interface information, mainly by comparing the radial velocity profiles before and after fracturing, the near-wellbore reflection wave Gaussian beam migration imaging, and the wellside scattered wave radial energy imaging The difference in logging responses is used to evaluate the radial extension effect of the fracture in the near-wellbore range (within 1-30m). This application can solve the problem of evaluating the radial extension characteristics of fractures in the current evaluation of reservoir fracturing transformation effects. By comprehensively utilizing longitudinal wave tomography technology, near-wellbore reflected wave Gaussian beam migration imaging technology, and wellside scattered wave radial energy imaging technology, the radial extension of fractures near the wellbore zone can be evaluated, which can effectively improve the evaluation accuracy of the radial extension characteristics of the reservoir fracture network. The method of this application has good application effect and high applicability, and at the same time provides a new idea for the evaluation of unconventional reservoir fracturing effects.

[0104] Figure 3 FIG. 4 shows a structural block diagram of a device for evaluating radial ductility of near-wellbore fractures according to an embodiment of the present application. Figure 3 As shown, the device comprises:

[0105] The acquisition module 301 is suitable for acquiring array acoustic wave full wave train data before fracturing and array acoustic wave full wave train data after fracturing corresponding to the near-wellbore zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data;

[0106] The first processing module 302 is adapted to process the monopolar full-wave data before fracturing and the monopolar full-wave data after fracturing respectively by using the P-wave travel time tomography method, to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and to calculate the relative radial velocity profile difference according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing;

[0107] The second processing module 303 is adapted to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing respectively by using a Gaussian beam migration imaging method to obtain Gaussian migration imaging results of the out-of-hole formation before fracturing and Gaussian migration imaging results of the out-of-hole formation after fracturing, and calculate the Gaussian beam migration imaging difference according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing;

[0108] The third processing module 304 is adapted to process the dipole full wave data before fracturing and the dipole full wave data after fracturing respectively by using the scattered wave radial energy imaging method to obtain the energy envelope before fracturing and the energy envelope after fracturing, and calculate the scattered wave energy difference according to the energy envelope before fracturing and the energy envelope after fracturing;

[0109] The evaluation module 305 is adapted to evaluate the radial ductility of the near-wellbore fracture according to the relative radial velocity profile difference, Gaussian beam migration imaging difference and scattered wave energy difference, and obtain the radial ductility evaluation result of the fracture.

[0110] Optionally, the first processing module is further adapted to: S1, determine an initial velocity model;

[0111] S2, based on the velocity model, forward calculation of the reference travel time using the ray tracing method;

[0112] S3, if the difference between the reference travel time and the measured travel time is greater than the preset difference, the velocity model is updated and the process jumps to S2;

[0113] S4, if the difference between the reference travel time and the measured travel time is less than or equal to a preset difference, determining the velocity model as a final velocity model;

[0114] S5, determining the velocity of the radial maximum penetration depth based on the monopole full-wave data, and calculating the relative radial velocity profile of the P-wave of the formation based on the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model.

[0115] Optionally, the first processing module is further adapted to: calculate the relative radial velocity profile of the formation compressional wave using the following formula:

[0116]

[0117] in, is the relative radial velocity profile of the formation P-wave, is the velocity at the maximum radial penetration depth, is the longitudinal wave velocity at different radial distances at any depth in the final velocity model.

[0118] Optionally, the second processing module is further adapted to: construct a direct sound field and a reverse propagation sound field using dipole full-wave data and Green's function;

[0119] The Green's function is approximated by combining the superposition of Gaussian beams, and the cross-correlation between the direct sound field and the reverse propagation sound field is calculated based on the asymptotic result;

[0120] The geological structure outside the well is imaged based on the cross-correlation to obtain the Gaussian migration imaging result of the formation outside the well.

[0121] Optionally, the third processing module is further adapted to: filter the dipole full-wave data to obtain filtered dipole full-wave data;

[0122] The filtered dipole full-wave data are normalized using the dipole direct wave amplitude to obtain normalized dipole full-wave data;

[0123] The normalized dipole full-wave data are Hilbert transformed to obtain the corresponding energy envelope.

[0124] Optionally, the first processing module is further adapted to: transform the dipole full-wave data into an earth coordinate system using an instrument azimuth curve;

[0125] The converted waveform data is subjected to bandpass filtering and fk filtering.

[0126] In summary, the present application is based on the fact that fracturing causes the formation rock to break, generate a large number of cracks, and form rock expansion. The rock elastic wave velocity caused by rock expansion decreases, and the longitudinal wave tomography technology can reconstruct the rock elastic wave velocity changes near the wellbore wall (within 1m). At the same time, fracturing will enhance the formation heterogeneity. The near-wellbore reflection wave Gaussian beam migration imaging technology and the wellside scattered wave radial energy imaging technology can characterize the near-wellbore zone (within 2-30m) The heterogeneous wave impedance interface information, mainly by comparing the radial velocity profiles before and after fracturing, the near-wellbore reflection wave Gaussian beam migration imaging, and the wellside scattered wave radial energy imaging The difference in logging responses is used to evaluate the radial extension effect of the fracture in the near-wellbore range (within 1-30m). This application can solve the problem of evaluating the radial extension characteristics of fractures in the current evaluation of reservoir fracturing transformation effects. By comprehensively utilizing longitudinal wave tomography technology, near-wellbore reflected wave Gaussian beam migration imaging technology, and wellside scattered wave radial energy imaging technology, the radial extension of fractures near the wellbore zone can be evaluated, which can effectively improve the evaluation accuracy of the radial extension characteristics of the reservoir fracture network. The method of this application has good application effect and high applicability, and at the same time provides a new idea for the evaluation of unconventional reservoir fracturing effects.

[0127] An embodiment of the present application provides a non-volatile computer storage medium, which stores at least one executable instruction or computer program, which enables a processor to execute operations corresponding to the method for evaluating radial ductility of near-wellbore pressure fractures in any of the above method embodiments.

[0128] An embodiment of the present application provides a computer program product, which includes at least one executable instruction or computer program, which can enable a processor to perform operations corresponding to the method for evaluating radial ductility of near-wellbore fractures in any of the above method embodiments.

[0129] Figure 4 A schematic diagram of the structure of a computing device according to an embodiment of the present application is shown. The specific embodiment of the present application does not limit the specific implementation of the computing device.

[0130] like Figure 4 As shown, the computing device may include: a processor 402 , a communication interface 404 , a memory 406 , and a communication bus 408 .

[0131] The processor 402 , the communication interface 404 , and the memory 406 communicate with each other via a communication bus 408 .

[0132] The communication interface 404 is used to communicate with other devices such as clients or other servers.

[0133] The processor 402 is used to execute the program 410, and specifically can execute the relevant steps in the above-mentioned embodiment of the method for evaluating radial ductility of hydraulic fractures in the near-wellbore zone.

[0134] Specifically, the program 410 may include program codes, which include computer operation instructions.

[0135] The processor 402 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0136] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0137] The program 410 can be specifically used to enable the processor 402 to execute the radial ductility evaluation method of the near-wellbore pressure fracture in any of the above-mentioned method embodiments. The specific implementation of each step in the program 410 can refer to the corresponding descriptions in the corresponding steps and units in the above-mentioned method embodiment for evaluating radial ductility of pressure fractures near the wellbore, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-mentioned equipment and modules can refer to the corresponding process description in the above-mentioned method embodiment, which will not be repeated here.

[0138] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the application is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the application described herein, and the description of the specific language above is for the purpose of disclosing the best mode of implementation of the application.

[0139] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0140] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the following intention: the claimed application requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims, the inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present application.

[0141] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device so disclosed may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0142] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0143] The various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the embodiments of the present application. The present application may also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals. Such a signal may be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0144] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets should not be constructed as a limitation to the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names.

Claims

1. A method for evaluating radial ductility of near-wellbore fractures, characterized in that: The method comprises: Collecting array acoustic wave full wave train data before and after fracturing corresponding to the near-wellbore zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data; The P-wave travel time tomography method is used to process the monopolar full wave data before fracturing and the monopolar full wave data after fracturing respectively, so as to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and the relative radial velocity profile difference is calculated according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing; The Gaussian beam migration imaging method is used to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing, respectively, to obtain the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing, and the Gaussian beam migration imaging difference is calculated according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing; The scattered wave radial energy imaging method is used to process the dipole full wave data before fracturing and the dipole full wave data after fracturing respectively, to obtain the energy envelope before fracturing and the energy envelope after fracturing, and the scattered wave energy difference is calculated according to the energy envelope before fracturing and the energy envelope after fracturing; The radial ductility of the near-wellbore fracture is evaluated based on the relative radial velocity profile difference, Gaussian beam migration imaging difference and scattered wave energy difference, and the radial ductility evaluation result of the fracture is obtained.

2. The method for evaluating radial ductility of near-wellbore fractures according to claim 1, characterized in that: The P-wave travel time tomography method is used to process the monopolar full wave data to obtain the formation P-wave relative radial velocity profile, which further includes: S1, determine the initial velocity model; S2, forward calculating the reference travel time using a ray tracing method according to the velocity model; S3, if the difference between the reference travel time and the measured travel time is greater than a preset difference, the velocity model is updated and the process jumps to S2; S4, if the difference between the reference travel time and the measured travel time is less than or equal to a preset difference, determining the velocity model as a final velocity model; S5, determining the velocity of the radial maximum penetration depth according to the monopole full-wave data, and calculating the relative radial velocity profile of the P-wave of the formation according to the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model.

3. The method for evaluating radial ductility of near-wellbore fractures according to claim 2, characterized in that: The step of calculating the relative radial velocity profile of the P-wave of the formation according to the velocity of the radial maximum penetration depth and the P-wave velocity at different radial distances at any depth on the final velocity model further comprises: The relative radial velocity profile of the formation P-wave is calculated using the following formula: in, is the relative radial velocity profile of the formation P-wave, is the velocity at the maximum radial penetration depth, is the longitudinal wave velocity at different radial distances at any depth in the final velocity model.

4. The method for evaluating radial ductility of near-wellbore fractures according to any one of claims 1 to 3, characterized in that: The Gaussian beam migration imaging method is used to process the dipole full-wave data to obtain the Gaussian migration imaging results of the out-of-hole formation, which further include: Use dipole full-wave data and Green's function to construct direct sound field and reverse propagation sound field; The Green's function is approximated by combining the superposition of Gaussian beams, and the cross-correlation between the direct sound field and the reverse propagation sound field is calculated based on the asymptotic result; The geological structure outside the well is imaged according to the cross-correlation to obtain Gaussian migration imaging results of the formation outside the well.

5. The method for evaluating radial ductility of near-wellbore fractures according to any one of claims 1 to 3, characterized in that: The dipole full-wave data is processed by the scattered wave radial energy imaging method to obtain the energy envelope, which further includes: Performing filtering on the dipole full-wave data to obtain filtered dipole full-wave data; Normalizing the filtered dipole full-wave data using the dipole direct wave amplitude to obtain normalized dipole full-wave data; The normalized dipole full-wave data is subjected to Hilbert transformation to obtain a corresponding energy envelope.

6. The method for evaluating radial ductility of near-wellbore fractures according to claim 5, characterized in that: Before filtering the dipole full-wave data, the method further comprises: converting the dipole full-wave data into an earth coordinate system using an instrument azimuth curve; The filtering process of the dipole full-wave data to obtain filtered dipole full-wave data further includes: performing bandpass filtering and fk filtering on the converted waveform data.

7. A device for evaluating radial ductility of near-wellbore fractures, characterized in that: The device comprises: The acquisition module is suitable for acquiring array acoustic wave full wave train data before fracturing and array acoustic wave full wave train data after fracturing corresponding to the near-well zone of the target well, wherein the array acoustic wave full wave train data includes: monopole full wave data and dipole full wave data; The first processing module is suitable for using the P-wave travel time tomography method to process the monopolar full wave data before fracturing and the monopolar full wave data after fracturing, respectively, to obtain the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing, and to calculate the relative radial velocity profile difference according to the P-wave relative radial velocity profile of the formation before fracturing and the P-wave relative radial velocity profile of the formation after fracturing; The second processing module is adapted to process the dipole full-wave data before fracturing and the dipole full-wave data after fracturing respectively by using a Gaussian beam migration imaging method to obtain Gaussian migration imaging results of the out-of-hole formation before fracturing and Gaussian migration imaging results of the out-of-hole formation after fracturing, and calculate the Gaussian beam migration imaging difference according to the Gaussian migration imaging results of the out-of-hole formation before fracturing and the Gaussian migration imaging results of the out-of-hole formation after fracturing; The third processing module is suitable for using the scattered wave radial energy imaging method to process the dipole full wave data before fracturing and the dipole full wave data after fracturing, respectively, to obtain the energy envelope before fracturing and the energy envelope after fracturing, and to calculate the scattered wave energy difference according to the energy envelope before fracturing and the energy envelope after fracturing; The evaluation module is suitable for evaluating the radial ductility of the near-wellbore fracture according to the relative radial velocity profile difference, Gaussian beam migration imaging difference and scattered wave energy difference, and obtaining the radial ductility evaluation result of the fracture.

8. A computing device, characterized in that include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the method for evaluating radial ductility of near-wellbore fractures according to any one of claims 1-6.

9. A computer storage medium, characterized in that The computer storage medium stores at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the method for evaluating radial ductility of near-wellbore zone hydraulic fractures according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises at least one executable instruction, wherein the executable instruction enables the processor to execute operations corresponding to the method for evaluating radial ductility of near-wellbore fractures according to any one of claims 1 to 6.

Images