Underground fracture identification method and device, electronic equipment and computer storage medium

Abstract

The present application relates to a kind of underground fracture identification method, device, electronic equipment and computer storage medium, belong to acoustic wave detection technical field, wherein, the underground fracture identification method includes: extracting three borehole mode waves in full wave train waveform in acoustic logging, and the time difference and energy amplitude of each borehole mode wave are calculated;Determine the time difference envelope area of each borehole mode wave at time difference mutation place based on the time difference of each borehole mode wave, calculate the average energy amplitude and cooperative attenuation index of the borehole mode wave based on the energy amplitude of the borehole mode wave;Based on the time difference envelope area, average energy amplitude and cooperative attenuation index of each borehole mode wave, the three-dimensional parameter atlas of underground fracture to be identified is constructed, the three-dimensional parameter atlas is analyzed, and the comprehensive indication curve of underground fracture to be identified is determined.The present application can accurately identify underground fracture.

Description

Technical Field

[0001] This invention relates to the field of acoustic wave detection technology, and in particular to a method, device, electronic equipment, and computer storage medium for identifying underground cracks. Background Technology

[0002] As the exploration and development of unconventional oil and gas resources continues to deepen, low-permeability reservoirs such as tight sandstone are gradually becoming the focus of exploration and development. In these reservoirs, fracture systems play a crucial role in improving reservoir permeability and controlling fluid migration. Therefore, in geological evaluation and oil and gas field development, fracture-developed areas are often considered favorable reservoir targets. Accurately identifying and locating underground fractures is a core element in improving reservoir evaluation accuracy and optimizing development plans.

[0003] Currently, underground fracture identification technologies in the oil and gas sector mainly include electrical imaging logging, conventional logging, and seismic inversion. Among these, seismic and conventional logging generally have low accuracy in identifying fractures in tight formations, while electrical imaging logging is limited by its cost and cannot be widely adopted. Furthermore, many development wells in actual oilfields lack imaging logging data.

[0004] This shows that existing technologies are either not accurate enough in identifying underground fissures, or too costly. Summary of the Invention

[0005] In view of this, it is necessary to provide a method, device, electronic device and computer storage medium for identifying underground cracks, so as to solve the problems of low accuracy or high cost of existing technologies for identifying underground cracks.

[0006] To address the aforementioned problems, in a first aspect, the present invention provides a method for identifying underground cracks, comprising:

[0007] Three borehole mode waves were extracted from the full wave train waveform in acoustic logging, and the time difference and energy amplitude of each borehole mode wave were calculated.

[0008] The time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change is determined based on the time difference of each wellbore mode wave, and the average energy amplitude and cooperative attenuation index of the wellbore mode wave are calculated based on the energy amplitude of the wellbore mode wave.

[0009] A three-dimensional parameter map of the underground fracture to be identified is constructed based on the time difference envelope area, average energy amplitude and cooperative attenuation index of the mode waves of each well. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified.

[0010] In one possible implementation, determining the time difference envelope area of ​​each wellbore mode wave at the point of abrupt change in time difference based on the time difference of each wellbore mode wave includes:

[0011] The original time difference curve of the wellbore mode wave is sampled based on the sliding window to determine the local minimum point in each sliding window;

[0012] A preset linear interpolation function is used to connect all local minima to obtain the interpolation floating baseline;

[0013] Calculate the area of ​​the time envelope between the original time difference curve and the interpolated floating baseline.

[0014] In one possible implementation, the average energy amplitude and co-attenuation index of the wellbore mode wave are calculated based on the energy amplitude of the wellbore mode wave, including:

[0015] The second average energy amplitude of all wellbore mode waves and the cooperative attenuation index of wellbore mode waves are calculated based on the first average energy amplitude of each wellbore mode wave and the preset energy attenuation function; wherein, the preset energy attenuation function is a function of the energy attenuation of the wellbore mode wave and the fracture width and fracture dip angle.

[0016] In one possible implementation, the process of obtaining the preset energy decay function includes:

[0017] Obtain the amplitude sequence of the borehole mode wave and the preset reference amplitude sequence. The amplitude sequence represents the amplitude of the borehole mode wave at different depths, and the preset reference amplitude sequence is the amplitude of the borehole mode wave at different depths corresponding to the known fracture width.

[0018] The amplitude difference sequence is calculated based on the amplitude sequence and the preset reference amplitude sequence, and the correlation coefficient of each sequence value in the amplitude difference sequence is calculated based on the maximum and minimum differences in the amplitude difference sequence.

[0019] The energy attenuation function of the wellbore mode wave is determined based on the correlation coefficients corresponding to each wellbore mode wave.

[0020] In one possible implementation, a three-dimensional parameter map of the subsurface fractures to be identified is constructed based on the time-difference envelope area, average energy amplitude, and cooperative attenuation index of the mode waves from each well, including:

[0021] A three-dimensional parameter map of the underground fracture to be identified is constructed using the difference envelope area, average energy amplitude, and co-attenuation index of each wellbore mode wave as the first coordinate axis, the detection depth corresponding to the wellbore mode wave as the second coordinate axis, and the values ​​corresponding to the difference envelope area, average energy amplitude, and co-attenuation index of each wellbore mode wave as the third coordinate axis.

[0022] In one possible implementation, after constructing a three-dimensional parametric map of the underground fractures to be identified, the process includes:

[0023] By continuously interpolating the three-dimensional parameter spectrum of the detection depth based on the difference envelope area, average energy amplitude, and cooperative attenuation index of the borehole mode waves corresponding to different detection depths, a continuous spectrum of the underground fracture to be identified is constructed.

[0024] The continuous map is smoothed and filtered to obtain a three-dimensional parameter map of the underground fissure to be identified.

[0025] In one possible implementation, the three-dimensional parametric map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified, including:

[0026] The volume of the three-dimensional parameter map of each window is obtained by integrating the three-dimensional parameter map in the direction of the detection depth using a sliding window of preset length.

[0027] By combining the volume of the three-dimensional parameter maps of each window, a comprehensive indicator curve for the underground fissures to be identified is obtained.

[0028] Secondly, the present invention also provides an apparatus for identifying underground cracks, comprising:

[0029] The waveform extraction module is used to extract three wellbore mode waves from the full wave train waveform in acoustic logging, and to calculate the time difference and energy amplitude of each wellbore mode wave.

[0030] The parameter calculation module is used to determine the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change based on the time difference of each wellbore mode wave, and to calculate the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave.

[0031] The fracture identification module is used to construct a three-dimensional parameter map of the underground fracture to be identified based on the time difference envelope area, average energy amplitude and cooperative attenuation index of the mode wave of each well. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified.

[0032] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein,

[0033] Memory, used to store programs;

[0034] A processor, coupled to a memory, is used to execute a program stored in the memory to implement the steps in the underground crack identification method of any of the above embodiments.

[0035] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instructions, which, when executed by a processor, can implement the steps in the underground crack identification method of any of the above embodiments.

[0036] The beneficial effects of this invention are as follows: The subsurface fracture identification method provided by this invention extracts three borehole mode waves from the full wave train waveform in acoustic logging and calculates the time difference and energy amplitude of each borehole mode wave. Considering the propagation time difference and energy amplitude of multiple borehole mode waves, it can fully exploit the information in array acoustic logging data. When encountering complex strata with many interfering factors, such as tight strata, strongly anisotropic strata, or complex lithological strata, it can more accurately reflect the development of rock fractures. Based on the time difference of each borehole mode wave, the time difference envelope area at the time difference abrupt change is determined. Based on the energy amplitude of the borehole mode waves, the average energy amplitude and co-attenuation index of the borehole mode waves are calculated. Five parameters are then combined to construct a three-dimensional parameter map of the subsurface fracture to be identified. A set of tight strata fracture location methods integrating the time difference and energy response characteristics of borehole mode waves at fracture development locations has been developed. This solves the shortcomings of previous methods, which considered only one factor and had strong limitations. By calculating the volume of the three-dimensional map, a comprehensive fracture indicator parameter is extracted through dimensionality reduction, resulting in accurate subsurface fracture identification at a low cost. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A schematic flowchart of a method for identifying underground cracks provided in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of wellbore mode wave extraction provided in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of an underground crack identification process provided in an embodiment of the present invention;

[0041] Figure 4 A flowchart illustrating a method for calculating the time difference envelope area provided in an embodiment of the present invention;

[0042] Figure 5 An acoustic wave time difference envelope area map provided in an embodiment of the present invention;

[0043] Figure 6 A flowchart illustrating a method for obtaining an energy decay function according to an embodiment of the present invention;

[0044] Figure 7 A schematic diagram of average amplitude energy and cooperative decay index provided for an embodiment of the present invention;

[0045] Figure 8 A three-dimensional parametric map provided in an embodiment of the present invention;

[0046] Figure 9 A flowchart illustrating a three-dimensional parametric map optimization method provided in an embodiment of the present invention;

[0047] Figure 10 An optimized three-dimensional parametric map is provided in an embodiment of the present invention;

[0048] Figure 11 A flowchart illustrating a comprehensive indicator curve calculation method provided in an embodiment of the present invention;

[0049] Figure 12 This is a result diagram of a crack comprehensive indicator curve processing provided in an embodiment of the present invention;

[0050] Figure 13 This is a schematic diagram of the structure of an underground crack identification device provided in an embodiment of the present invention;

[0051] Figure 14 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0052] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0053] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0054] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0055] A specific embodiment of the present invention, such as Figure 1 As shown, a method for identifying underground cracks is disclosed, including:

[0056] S101, extract the three wellbore mode waves from the full wave train waveform in acoustic logging, and calculate the time difference and energy amplitude of each wellbore mode wave.

[0057] In this embodiment of the invention, acoustic logging is a logging technology that utilizes a logging system composed of multiple receivers and multiple frequency sound sources. It acquires and analyzes the acoustic propagation characteristics at multiple spatial locations to obtain elastic parameters and structural information of underground rock formations. Underground fractures are fracture or shear surfaces generated in formation rocks under stress, often exhibiting open or closed linear structures. Based on their spatial orientation and strike, they can be classified into high-angle fractures (such as tensile fractures) and low-angle fractures (such as interlayer slip fractures). In tight sandstone formations, due to strong compaction and cementation and poor matrix properties, acoustic transit time usually does not change significantly. However, at fracture sites, the increased heterogeneity of the medium leads to prolonged acoustic propagation paths or diffraction, resulting in increased transit times for P-waves, S-waves, and Stoneley waves. Under different fracture orientations, the increase in time difference of the three waves varies. The P-wave responds significantly to horizontal or low-angle dip fractures, the S-wave responds noticeably to high-angle fractures, while the Stoneley wave's time difference increase is sensitive to fracture opening and is influenced by fracture width and fluid properties, reflecting formation permeability changes to some extent. Quantifying the increase in time difference of the three waves can reflect the degree of fracture development in tight formations. Therefore, in this embodiment of the invention, by extracting the three wellbore mode waves—P-wave, S-wave, and Stoneley wave—from the full wave train waveform in sonic logging, specifically, as... Figure 2 As shown, taking a tight sandstone gas well (Well A) as an example, the wellbore mode wave energy (amplitude) and time difference (slowness) are first extracted from the measured full-waveform acoustic wave. The first track in the figure is the logging depth (m); the second track is the acoustic variable density waveform imaging diagram; the third to fifth tracks are eight curves each for the P-wave, S-wave, and Stoneley wave energies; and the sixth to eighth tracks are the time differences for the P-wave, S-wave, and Stoneley wave.

[0058] S102, determine the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change based on the time difference of each wellbore mode wave, and calculate the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave.

[0059] In this embodiment of the invention, the time difference value of the rock matrix is ​​artificially set as the background baseline. Overlaying this baseline with the original time difference curve can show the magnitude of time difference variation at fracture sites. However, due to lithological influences, a fixed baseline cannot adapt to formations of different strata or lithologies throughout the well section. Therefore, this invention employs a floating baseline, which uses a sliding window with a window length of three sampling points to mark the minimum value points within each depth window. Then, linear interpolation is used to connect the minimum value points, and finally, the difference between the original time difference curve and the interpolated floating baseline is calculated, i.e., the time difference envelope area.

[0060] Furthermore, in dense strata, fractures, as heterogeneous geological anomalies, significantly interfere with sound wave propagation. The presence of fractures leads to abrupt changes in wave impedance, variations in the elastic modulus of the medium, and enhanced local anisotropy, causing sound waves to undergo reflection, refraction, scattering, and mode conversion during propagation, ultimately resulting in attenuation of the measured waveform energy. Therefore, this invention proposes using the average amplitude of three waves to reflect the energy attenuation caused by fractures, i.e., the average energy amplitude; simultaneously considering the synergistic attenuation of the three waves, a nonlinear model characterizing the degree of attenuation of the three waves at the fracture site is established, i.e., the synergistic attenuation index.

[0061] S103. Based on the time difference envelope area, average energy amplitude and cooperative attenuation index of the mode waves of each well, a three-dimensional parameter map of the underground fracture to be identified is constructed. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified.

[0062] In this invention, a three-dimensional coordinate system is constructed using the time difference envelope area, average energy amplitude, and cooperative attenuation index. A three-dimensional parameter map of the underground fissure to be identified is then plotted. The map is analyzed to determine the comprehensive indicator curve of the fissure. The specific plotting method and subsequent analysis process for the three-dimensional parameter map will be described in detail later in this invention.

[0063] Furthermore, such as Figure 3 As shown, this invention first extracts the time difference (slowness) and energy (amplitude) of three wellbore mode waves—P-wave, S-wave, and Stoneley wave—from the full wave train waveform. Then, a parallel strategy is employed: for time difference, a curve interpolation reconstruction method is used for wave detection, calculating the envelope area between the original curve and the interpolation baseline at points of abrupt (increased) time difference to indicate time difference increases or cycle jumps caused by fractures. Secondly, for energy, the average energy amplitude and co-attenuation index of the three waves are calculated as dual parameters. High- and low-dip fractures are distinguished by the P-wave / S-wave velocity ratio. Using a classification modeling approach, grey relational analysis is employed to calibrate the dual-parameter attenuation weights of the three waves under different orientation modes using imaging logging or core fracture width scales. Further, the three parameters of time difference envelope area and energy are interpolated and synthesized into a multi-parameter matrix, and a three-dimensional fracture parameter fusion map is generated through interpolation and smoothing filtering. Finally, a dynamic sliding window is used to calculate the image volume integral within the window, and the resulting value is the final comprehensive fracture indicator curve.

[0064] The subsurface fracture identification method provided by this invention extracts three borehole mode waves from the full wave train waveform in acoustic logging and calculates the time difference and energy amplitude of each borehole mode wave. By considering the propagation time difference and energy amplitude of multiple borehole mode waves, it can fully exploit the information in array acoustic logging data. When encountering complex strata with many interfering factors, such as tight strata, highly anisotropic strata, or complex lithological strata, it can more accurately reflect the development of rock fractures. Based on the time difference of each borehole mode wave, the time difference envelope area at the time difference abrupt change is determined. Based on the energy amplitude of the borehole mode waves, the average energy amplitude and cooperative attenuation index of the borehole mode waves are calculated. Five parameters are then combined to construct a three-dimensional parameter map of the subsurface fracture to be identified. A method for locating fractures in tight strata by integrating the time difference and energy response characteristics of borehole mode waves at the fracture development location has been developed. This method overcomes the shortcomings of previous methods, which considered only one factor and had strong limitations. By calculating the volume of the three-dimensional map, a comprehensive fracture indicator parameter is extracted through dimensionality reduction, resulting in accurate subsurface fracture identification at a low cost.

[0065] In some possible embodiments of the present invention, such as Figure 4 As shown, the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change is determined based on the time difference of each wellbore mode wave, including:

[0066] S401, Based on the sliding window, the original time difference curve of the wellbore mode wave is sampled to determine the local minimum point in each sliding window;

[0067] S402, a preset linear interpolation function is used to connect all local minimum points to obtain the interpolation floating baseline;

[0068] S403 calculates the area of ​​the time envelope between the original time difference curve and the interpolated floating baseline.

[0069] In this embodiment of the invention, the original time difference curves of the three wellbore mode waves are... A sliding window with a length of 3 sampling intervals (well logging data is usually recorded at fixed sampling intervals and is discrete) is set up, and local minimum points are marked in each window unit to form a minimum value sequence:

[0070] (1)

[0071] in, For the first i One detection depth point.

[0072] Assuming the current depth point satisfy: Connecting the minimum points using a linear interpolation function generates a floating baseline that adapts to different rock matrix background values.

[0073] (2)

[0074] in, The current depth point that needs interpolation; , These are the depths of two adjacent minimum points near the current depth point. , These are the time differences of the corresponding local minimum points; This is the interpolated floating baseline value.

[0075] The difference between the original time difference of the three wellbore mode waves and the floating baseline is calculated to obtain the time difference envelope area at the current depth point, which is represented by the well logging curve as follows:

[0076] (3)

[0077] (4)

[0078] (5)

[0079] in, , , Time differences for longitudinal waves, transverse waves, and Stoneley waves, respectively. ; , , Interpolation floating baselines for P-waves, S-waves, and Stoneley waves, respectively. ; , , These are the calculated envelope areas of the longitudinal wave, transverse wave, and Stoneley wave, respectively.

[0080] Specifically, such as Figure 5 As shown, the calculation function of the sonic transit time envelope area is mainly implemented by a computer program. The first channel represents the logging depth (m); the second to fourth channels represent the original transit time curves of P-wave, S-wave, and Stoneley wave, and the floating baseline (BL) obtained by interpolation reconstruction, respectively; the fifth to seventh channels represent the calculated transit time envelope areas of P-wave, S-wave, and Stoneley wave (normalized). In practical applications, lithological factors such as clay content, ash interlayers, carbonaceous debris, or coal seams can cause abnormal increases or decreases in transit time. Therefore, a threshold can be set according to the mineral content. For the portion exceeding the threshold, the floating baseline is made to coincide with the original curve to avoid misjudgment caused by the influence of lithological factors.

[0081] In some possible embodiments of the present invention, the calculation of the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave includes:

[0082] The second average energy amplitude of all wellbore mode waves and the cooperative attenuation index of wellbore mode waves are calculated based on the first average energy amplitude of each wellbore mode wave and the preset energy attenuation function; wherein, the preset energy attenuation function is a function of the energy attenuation of the wellbore mode wave and the fracture width and fracture dip angle.

[0083] In this embodiment of the invention, in tight formations, fractures, as heterogeneous anomalous geological bodies, significantly interfere with the propagation of acoustic waves. The presence of fractures leads to abrupt changes in wave impedance, variations in the elastic modulus of the medium, and enhanced local anisotropy, causing acoustic waves to undergo reflection, refraction, scattering, and mode conversion during propagation, ultimately resulting in attenuation of the measured waveform energy. Therefore, this invention proposes to use the average amplitude of the three waves to reflect the energy attenuation caused by fractures, i.e., the average energy amplitude, as shown in formula (6); at the same time, considering the synergistic effect of the superimposed attenuation of the three waves, a nonlinear model characterizing the degree of attenuation of the three waves at the fracture is established, i.e., the synergistic attenuation index, as shown in formula (7). Numerous physical experiments and numerical simulation studies have shown that the energy attenuation of borehole mode waves at fractures is mainly related to the fracture orientation and fracture width. Therefore, the two parameters can be expressed as functions of fracture dip angle and fracture width:

[0084] (6)

[0085] (7)

[0086] in, The average energy amplitude; The co-attenuation index; and These are functions of crack width and crack inclination angle, respectively. , , These represent the average energy amplitudes of the longitudinal wave, transverse wave, and Stoneley wave of the receiver array, respectively, calculated using the following formulas:

[0087] (8)

[0088] (9)

[0089] (10)

[0090] in, , , These represent the average energy amplitudes of the longitudinal wave, transverse wave, and Stoneley wave of the receiver array, respectively. m This refers to the total number of receivers (array acoustic logging instruments typically carry multiple receivers). n This is the current receiver number.

[0091] Furthermore, since the acoustic energy attenuation trend of cracks with increasing width is approximately the same for different dip angle modes, that is, under the same type of crack dip angle conditions, the physical response law of the three waves is relatively stable, and its attenuation mechanism has repeatability and statistical regularity in specific geological environments, the weights can be simplified to a constant value to enhance the model's universality and stability and avoid noise interference caused by local measurement point fluctuations. Therefore, formulas (6) and (7) can be simplified to:

[0092] (11)

[0093] (12)

[0094] in, , as well as These are the weighting coefficients for the changes in fracture width for P-waves, S-waves, and Stoneley waves, respectively. Furthermore, in the absence of logging data such as electrical imaging, fracture dip angle cannot be accurately characterized, but the P-wave / S-wave velocity ratio can, to some extent, distinguish between relatively high and low dip angle fracture patterns. In elastic wave propagation theory, the velocity ratio of P-waves to S-waves in isotropic media is mainly determined by the Poisson's ratio of the medium. However, in actual formations, fracture development often causes local anisotropy, especially when fractures are densely packed or have a specific dip angle distribution, which significantly affects the propagation velocities of different wave types. For low-dip fractures, P-waves are more likely to penetrate the fracture surface perpendicularly, resulting in greater energy loss and a more significant increase in slowness; while for high-dip fractures, P-waves are more likely to diffract around the fracture, with less impact, while the S-wave velocity decreases significantly with the fracture surface direction. Therefore, the P-wave / S-wave velocity ratio, as an auxiliary factor distinguishing between high and low dip angle fractures, can be replaced by the S-wave / P-wave time difference ratio in practical applications.

[0095] (13)

[0096] Therefore, by distinguishing between high- and low-angle crack modes using the P-wave and S-wave velocity ratios, classification modeling is performed, and the attenuation coefficients of the three modes under different dip angles are combined into a single weighted constant using the width constant and the dip angle function:

[0097] (14)

[0098] (15)

[0099] in, , , These are the energy weighting coefficients for P-waves, S-waves, and Stoneley waves in low-dip fractured formations, respectively. , , These are the energy weighting coefficients for P-waves, S-waves, and Stoneley waves in high-dipping fractured formations, respectively. It is a regional empirical constant, serving as a threshold for distinguishing high and low dip angles of cracks by the ratio of P-wave and S-wave velocities.

[0100] Furthermore, such as Figure 6 As shown, the process of obtaining the preset energy decay function includes:

[0101] S601, acquire the amplitude sequence of the borehole mode wave and the preset reference amplitude sequence. The amplitude sequence represents the amplitude of the borehole mode wave at different depths, and the preset reference amplitude sequence is the amplitude of the borehole mode wave at different depths corresponding to the known fracture width.

[0102] S602, calculate the amplitude difference sequence based on the amplitude sequence and the preset reference amplitude sequence, and calculate the correlation coefficient of each sequence value in the amplitude difference sequence based on the maximum difference and minimum difference in the amplitude difference sequence;

[0103] S603, determine the energy attenuation function of the wellbore mode wave based on the correlation coefficients corresponding to each wellbore mode wave.

[0104] In this embodiment of the invention, grey relational analysis is used, with the fracture width measured from the core as the energy attenuation weight for the three waves in the calibration scale. First, the fracture width obtained from the core measurement (or, depending on the actual situation, a relatively reliable fracture width calculated by electrical imaging logging or other methods can be used as the calibration) is extracted as a reference sequence, denoted as... The energy amplitudes of the three borehole mode waves extracted from the corresponding depth segments of the core depth were used as a comparison sequence, denoted as... For each depth point Calculate the difference between the reference sequence and the comparison sequence: The maximum and minimum differences are defined as follows: , Calculate the correlation coefficient:

[0105] (16)

[0106] Among them, the resolution coefficient It is usually taken as 0.5.

[0107] For each comparison sequence, the grey relational degree is further calculated as follows:

[0108] (17)

[0109] Finally, the weighting coefficients are determined, and the normalized correlation ratio is calculated:

[0110] (18)

[0111] in, For the first i The energy attenuation of borehole mode waves is a function of fracture width and fracture dip angle.

[0112] Specifically, when calculating the average energy amplitude and the synergistic attenuation index, it is necessary to calibrate the threshold for distinguishing high and low dip modes of fractures based on the core data of the target block, and then use the grey relational analysis method to calibrate the three-wave weighting coefficients. By statistically analyzing the core and imaging data of the block where well A is located, the corresponding P-wave and S-wave velocity ratios are extracted, and the threshold is determined. ,Right now If the angle is less than 0.5, it is considered a low tilt angle, and the first set of formulas is used for calculation; An angle greater than 0.5 is considered a high inclination angle, and the second set of formulas is used for calculation. The weight coefficients calculated based on grey relational analysis are shown in Table 1, and the formula can be expressed as:

[0113] (19)

[0114] (20)

[0115] like Figure 7 As shown, the first track represents the logging depth (m); the second to fourth tracks represent the array energy amplitudes of P-waves, S-waves, and Stoneley waves, respectively; the fifth to seventh tracks represent the average array energy amplitudes of P-waves, S-waves, and Stoneley waves, respectively; the eighth to tenth tracks represent the normalized average energy amplitudes of P-waves, S-waves, and Stoneley waves (0~1); the eleventh track represents the P-wave / S-wave velocity ratio (S-wave / P-wave time difference ratio); and the last two tracks represent the calculated average energy amplitudes. and co-decay index .

[0116] Table 1: Energy Weighting Coefficients for Borehole Mode Waves

[0117]

[0118] In some possible embodiments of the present invention, a three-dimensional parameter map of the subsurface fracture to be identified is constructed based on the time difference envelope area, average energy amplitude, and cooperative attenuation index of the mode waves of each well, including:

[0119] A three-dimensional parameter map of the underground fracture to be identified is constructed using the difference envelope area, average energy amplitude, and co-attenuation index of each wellbore mode wave as the first coordinate axis, the detection depth corresponding to the wellbore mode wave as the second coordinate axis, and the values ​​corresponding to the difference envelope area, average energy amplitude, and co-attenuation index of each wellbore mode wave as the third coordinate axis.

[0120] In this embodiment of the invention, to eliminate dimensional differences and overall differences in instrument measurements across different well runs, the time difference envelope area, average energy amplitude, and cooperative attenuation index of the three waves are normalized:

[0121] (twenty one)

[0122] in, These are the normalized parameter values; This is the current depth parameter value; , These represent the maximum and minimum values ​​of parameters for the entire well section, respectively.

[0123] For tight sandstone formations, clay minerals exhibit significant energy absorption and scattering effects on sound wave propagation, and increased clay content leads to energy attenuation. Formations with high clay content typically have low elastic modulus and discontinuous rock skeletons, making sound waves prone to deformation and dissipation during propagation. Especially when sound waves pass through mudstone interlayers, reflection, dispersion, and refraction occur at the layer interfaces, causing energy attenuation, which is similar to the response caused by fractures. Therefore, correcting the energy system parameters for clay content to shield against energy attenuation due to increased clay content is a crucial step. This invention employs the classic volumetric model approach, simplifying the sound wave energy attenuation caused by clay content into a linear relationship. Parameter values ​​calculated from relatively pure mudstone sections within the block are used as pure clay response values ​​for correction. After normalization in the previous step, the average sound wave energy of pure mudstone sections can be considered 0, and the co-attenuation index can be considered 1. Simultaneously, the average energy amplitude is positively correlated with the other parameters. The following steps use… replace:

[0124] (twenty two)

[0125] (twenty three)

[0126] in, and These are the average energy amplitude and synergistic attenuation index of the sound waves after the elimination of the mud's influence, respectively. The average energy amplitude; The co-attenuation index; The average energy amplitude of the acoustic waves in the pure mudstone section is taken as 0. The synergistic attenuation index for the pure mudstone section is set to 1. This refers to the mud content.

[0127] In this embodiment of the invention, after parameter normalization and interference factor correction, a multidimensional fracture parameter fusion map is constructed. First, the five fracture parameters are combined into a 5-column array according to the logging sampling depth. These five fracture parameters represent the time differences of three wellbore mode waves, including area, average energy amplitude, and co-attenuation index. To construct a continuous three-dimensional map, an interpolation method is used to horizontally (in the direction of parameter numbering) expand the five normalized parameters, constructing a dense parameter matrix. Assuming at any depth... Five parameter values ​​have been obtained at this location. At parameter position The continuous spectral values ​​are interpolated using the following formula:

[0128] (twenty four)

[0129] Among them, weight The definition of is:

[0130] (25)

[0131] in, For the first The horizontal coordinates of the original parameters; This is a power parameter that controls the smoothness of the interpolation; it is typically set to 1 to 3.

[0132] Using depth as the Y-axis, column number as the X-axis, and parameter values ​​as the Z-axis, a 3D atlas is generated. An uninterpolated image within a window length is shown below. Figure 8 As shown.

[0133] In some possible embodiments of the present invention, such as Figure 9 As shown, after constructing the three-dimensional parameter map of the underground fissures to be identified, it includes:

[0134] S901 continuously interpolates the three-dimensional parameter spectrum of the detection depth based on the difference envelope area, average energy amplitude and cooperative attenuation index of the borehole mode waves corresponding to different detection depths, and constructs a continuous spectrum of the underground fracture to be identified.

[0135] S902, smoothing and filtering the continuous map to obtain the three-dimensional parameter map of the underground fissure to be identified.

[0136] In this embodiment of the invention, to further reduce the impact of noise and improve image continuity, the image spectrum is... Apply a smoothing filter by convolution smoothing the original spectrum using a Gaussian filter:

[0137] (26)

[0138] in, It is a two-dimensional Gaussian kernel function; This represents a two-dimensional convolution operation; This is the final smoothed 3D crack parameter map. The 2D Gaussian kernel function expression is as follows:

[0139] (27)

[0140] in, For logging depth; For the x-axis (parameter number); The core center (current pre-smoothed position); To control the standard deviation of the smoothing range; This represents the weight value at the current kernel center.

[0141] like Figure 10 As shown, this is a three-dimensional crack parameter fusion map within a window range after interpolation smoothing, which can intuitively display the degree of crack development and the response of multiple parameters.

[0142] In some possible embodiments of the present invention, such as Figure 11 As shown, the three-dimensional parametric map is analyzed to determine the comprehensive indicator curve of the underground fissure to be identified, including:

[0143] S1101, the three-dimensional parameter map is integrated in the direction of detection depth using a sliding window of preset length to obtain the volume of the three-dimensional parameter map of each window;

[0144] S1102, combining the volume of the three-dimensional parameter map of each window, a comprehensive indicator curve of the underground fissure to be identified is obtained.

[0145] In this embodiment of the invention, after constructing and smoothing the multi-parameter three-dimensional map, to further quantify the comprehensive response of fracture parameters, this invention proposes a three-dimensional map volume calculation method based on a sliding window. Specifically, a length of [value missing] is set in the logging depth direction. A sliding window is used, with a sliding step size equal to the original sampling interval of the array acoustic logging data. The window covers all parameter spectrum dimensions within the current depth range. The total volume of the parameter spectrum within each sliding window's defined region is obtained by integrating the data. This volume value is the final fracture composite indicator parameter. The depth corresponding to the center of the window is the logging depth index for the fracture composite indicator parameter. The calculation formula is as follows:

[0146] (28)

[0147] in, The comprehensive crack indication parameter indicates the current depth; This represents the parameter value after final smoothing of the current depth; For the x-axis (parameter number); and These represent the start and end positions of the parameter dimensions after interpolation and filtering; For logging depth; The length of the sliding window.

[0148] In practical applications, due to the discrete sampling characteristics of well logging data, the above integral form can be approximated in engineering implementation using a weighted summation method as follows:

[0149] (29)

[0150] in, This refers to the logging sampling interval, which is generally a fixed value and can be ignored.

[0151] Specifically, such as Figure 12 As shown, this is the final result of the multi-dimensional parameter fusion map and fracture comprehensive indicator curve processing. The first track represents the logging depth (m); the second to fourth tracks represent the time difference envelope area parameters of P-wave, S-wave, and Stoneley wave, respectively. , , The fifth and sixth channels represent the average energy amplitude and the co-attenuation index, respectively. , The seventh line is a 3D map generated by fusing the above five crack parameters. The map values ​​are mapped to a gradient color scale from blue to red. The warmer the color of the map, the larger the crack parameter value, indicating that the crack development is more significant at this location. The eighth line is the comprehensive crack indicator parameter finally extracted from the fused map. The high and low values ​​of the comprehensive parameters directly indicate the degree of fracture development; the ninth line is a tadpole-shaped image of the fracture morphology and orientation outlined by electro-imaging, used to verify the reliability of the invention; the last two lines are, respectively, a static electro-imaging image and a mineral content profile. From the results, the final fracture indication parameters basically match the fracture development location shown by the electro-imaging, confirming the reliability of the invention.

[0152] To better implement the underground crack identification method in the embodiments of the present invention, based on the underground crack identification method, correspondingly, as follows: Figure 13 As shown, this embodiment of the invention also provides an underground crack identification device, the underground crack identification device 1300 comprising:

[0153] The waveform extraction module 1301 is used to extract three wellbore mode waves from the full wave train waveform in acoustic logging, and to calculate the time difference and energy amplitude of each wellbore mode wave.

[0154] The parameter calculation module 1302 is used to determine the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change based on the time difference of each wellbore mode wave, and to calculate the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave.

[0155] The fracture identification module 1303 is used to construct a three-dimensional parameter map of the underground fracture to be identified based on the time difference envelope area, average energy amplitude and cooperative attenuation index of the mode wave of each well. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified.

[0156] The underground crack identification device 1300 provided in the above embodiments can realize the technical solutions described in the above underground crack identification method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content of the above underground crack identification method embodiments, which will not be repeated here.

[0157] like Figure 14 As shown, the present invention also provides an electronic device 1400. The electronic device 1400 includes a processor 1401, a memory 1402, and a display 1403. Figure 14 Only some components of the electronic device 1400 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0158] In some embodiments, processor 1401 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 1402 or process data, such as the underground crack identification method of the present invention.

[0159] In some embodiments, processor 1401 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 1401 may be local or remote. In some embodiments, processor 1401 may be implemented on a cloud platform. In some embodiments, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, or any combination thereof.

[0160] In some embodiments, memory 1402 may be an internal storage unit of electronic device 1400, such as a hard disk or memory of electronic device 1400. In other embodiments, memory 1402 may also be an external storage device of electronic device 1400, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on electronic device 1400.

[0161] Furthermore, the memory 1402 may include both internal storage units of the electronic device 1400 and external storage devices. The memory 1402 is used to store application software and various types of data installed on the electronic device 1400.

[0162] In some embodiments, display 1403 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 1403 is used to display information from electronic device 1400 and to display a visual user interface. Components 1401-1403 of electronic device 1400 communicate with each other via a system bus.

[0163] In some embodiments, when the processor 1401 executes the underground fissure identification program in the memory 1402, the following steps may be performed:

[0164] Three borehole mode waves were extracted from the full wave train waveform in acoustic logging, and the time difference and energy amplitude of each borehole mode wave were calculated.

[0165] The time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change is determined based on the time difference of each wellbore mode wave, and the average energy amplitude and cooperative attenuation index of the wellbore mode wave are calculated based on the energy amplitude of the wellbore mode wave.

[0166] A three-dimensional parameter map of the underground fracture to be identified is constructed based on the time difference envelope area, average energy amplitude and cooperative attenuation index of the mode waves of each well. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified.

[0167] It should be understood that when the processor 1401 executes the underground crack identification program in the memory 1402, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.

[0168] Furthermore, the embodiments of the present invention do not specifically limit the type of the electronic device 1400 mentioned. The electronic device 1400 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 1400 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0169] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the underground crack identification methods provided in the above-described method embodiments.

[0170] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0171] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying underground cracks, characterized in that, include: Three wellbore mode waves were extracted from the full wave train waveform in acoustic logging, and the time difference and energy amplitude of each wellbore mode wave were calculated. Based on the time difference of each wellbore mode wave, the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change is determined, and the average energy amplitude and cooperative attenuation index of the wellbore mode wave are calculated based on the energy amplitude of the wellbore mode wave. Based on the time difference envelope area, average energy amplitude and cooperative attenuation index of each wellbore mode wave, a three-dimensional parameter map of the underground fracture to be identified is constructed. The three-dimensional parameter map is analyzed to determine the comprehensive indicator curve of the underground fracture to be identified. The determination of the time difference envelope area of ​​each wellbore mode wave at the point of abrupt change in time difference based on the time difference of each wellbore mode wave includes: The original time difference curves of the wellbore mode waves are sampled based on sliding windows to determine the local minimum points in each sliding window. A preset linear interpolation function is used to connect all local minima to obtain the interpolation floating baseline; Calculate the area of ​​the time difference envelope between the original time difference curve and the interpolated floating baseline; The calculation of the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave includes: Based on the first average energy amplitude of each wellbore mode wave and a preset energy attenuation function, the second average energy amplitude of all wellbore mode waves and the cooperative attenuation index of the wellbore mode waves are calculated; wherein, the preset energy attenuation function is a function of the energy attenuation of the wellbore mode waves and the fracture width and fracture dip angle; the formula for calculating the second average energy amplitude of all wellbore mode waves is as follows: in, The second average energy amplitude of all wellbore mode waves. , , These represent the first average energy amplitudes of the longitudinal wave, transverse wave, and Stoneley wave of the receiver array, respectively. and These are functions of crack width and crack inclination angle, respectively. The construction of a three-dimensional parameter map of the subsurface fracture to be identified based on the time difference envelope area, average energy amplitude, and cooperative attenuation index of each wellbore mode wave includes: A three-dimensional parameter map of the underground fracture to be identified is constructed using the time difference envelope area, average energy amplitude, and cooperative attenuation index of each wellbore mode wave as the first coordinate axis, the detection depth corresponding to the wellbore mode wave as the second coordinate axis, and the values ​​corresponding to the difference envelope area, average energy amplitude, and cooperative attenuation index of each wellbore mode wave as the third coordinate axis.

2. The method for identifying underground cracks according to claim 1, characterized in that, The process of obtaining the preset energy decay function includes: The amplitude sequence of the wellbore mode wave and a preset reference amplitude sequence are obtained. The amplitude sequence represents the amplitude of the wellbore mode wave at different depths, and the preset reference amplitude sequence is the amplitude of the wellbore mode wave at different depths corresponding to a known fracture width. An amplitude difference sequence is calculated based on the amplitude sequence and the preset reference amplitude sequence, and the correlation coefficient of each sequence value in the amplitude difference sequence is calculated based on the maximum and minimum differences in the amplitude difference sequence. The energy attenuation function of the wellbore mode wave is determined based on the correlation coefficient corresponding to each of the wellbore mode waves.

3. The method for identifying underground cracks according to claim 1, characterized in that, After constructing the three-dimensional parametric map of the underground fissures to be identified, the following steps are included: For each well mode wave corresponding to different detection depths, the three-dimensional parameter spectrum of the detection depth is continuously interpolated to construct a continuous spectrum of the underground fracture to be identified. The continuous map is smoothed and filtered to obtain a three-dimensional parameter map of the underground fissure to be identified.

4. The method for identifying underground cracks according to claim 3, characterized in that, The analysis of the three-dimensional parameter map to determine the comprehensive indicator curve of the underground fissure to be identified includes: The volume of the three-dimensional parameter map of each window is obtained by integrating the three-dimensional parameter map along the detection depth direction using a sliding window of preset length. By combining the volume of the three-dimensional parameter maps of each window, a comprehensive indicator curve for the underground fissures to be identified is obtained.

5. A device for identifying underground cracks, applicable to the method for identifying underground cracks as described in any one of claims 1 to 4, characterized in that, include: The waveform extraction module is used to extract three wellbore mode waves from the full wave train waveform in acoustic logging, and to calculate the time difference and energy amplitude of each wellbore mode wave. The parameter calculation module is used to determine the time difference envelope area of ​​each wellbore mode wave at the time difference abrupt change based on the time difference of each wellbore mode wave, and to calculate the average energy amplitude and cooperative attenuation index of the wellbore mode wave based on the energy amplitude of the wellbore mode wave. The fracture identification module is used to construct a three-dimensional parameter map of the underground fracture to be identified based on the time difference envelope area, average energy amplitude and cooperative attenuation index of each wellbore mode wave, and to analyze the three-dimensional parameter map to determine the comprehensive indicator curve of the underground fracture to be identified.

6. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the underground crack identification method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the underground crack identification method according to any one of claims 1 to 4.

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