Fracturing low-frequency strain response signal extraction method and device based on distributed optical fibers

Abstract

The invention provides a fracturing low-frequency strain response signal extraction method and device based on distributed optical fibers. The corresponding method comprises the steps that a time domain filter of a target reservoir is generated according to reservoir rock physical property parameters of the target reservoir; according to pre-acquired distributed optical fiber acoustic wave data of a target reservoir and the time domain filter, generating an expected signal corresponding to the distributed optical fiber acoustic wave data; wherein the distributed optical fiber sound wave data is generated by fracturing the target reservoir stratum; and performing down-sampling on the expected signal according to the effective opening degree of the micro-crack of the target reservoir to extract a fracturing low-frequency strain response signal of the target reservoir. According to the method, the calculation amount in the process of extracting the fracturing low-frequency strain response signals is greatly reduced, in addition, the signal-to-noise ratio of data is improved while the data storage cost is reduced, the calculation process is simple and efficient, and effective technical support can be provided for the crack propagation and development process for optical fiber fracturing monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development using geophysics, in particular to the technical field of oil and gas field fracturing monitoring, and more particularly to a method and device for extracting fracturing low-frequency strain response signals based on distributed optical fiber. Background Art

[0002] Conventional reservoirs are relatively mature and developed earlier in the oil and gas field due to their shallow burial depth and easy excavation. Therefore, the remaining reserves of such reservoirs are relatively small. Unconventional reservoirs have large proven reserves, and with the advancement of exploration and development technology, existing technologies have the ability to explore and develop unconventional reservoirs, and unconventional reservoirs have gradually become the target of mainstream exploration and development. The economical and efficient development of unconventional reservoirs is inevitably inseparable from hydraulic fracturing technology. Fracturing technology is related to the production capacity of unconventional reservoirs, so there is an urgent need for a technology to evaluate the fracturing effect.

[0003] At present, commonly used fracturing monitoring technologies include microseismic, tracer, inclinometer, electromagnetic method, etc. Distributed optical fiber has the advantage of multi-physical quantity perception, which can realize vibration, temperature and strain sensing. Different from previous monitoring methods, based on distributed optical fiber vibration monitoring, formation strain response monitoring can be realized through appropriate processing.

[0004] The principle of distributed optical fiber based strain monitoring is to directly evaluate the changes in the formation stress state during the fracturing process; rather than indirectly evaluating the fracturing effect through information such as the location of underground fractures. Therefore, the study of distributed optical fiber strain response extraction is of great significance for the efficient development of unconventional reservoirs. However, the distributed optical fiber fracturing monitoring technology is still in the exploratory stage.

[0005] Since the frequency band of distributed fiber optic monitoring signals is wide, the lowest frequency can be close to 0Hz and the highest frequency can reach 4KHz. Therefore, the polarity of the DAS signal collected by the optical fiber needs to be processed in order to obtain data for evaluating the formation strain response. On the other hand, fracturing monitoring generally requires real-time display of monitoring results, and has high requirements for the timeliness of data processing and results display. Generally, it cannot be delayed for 30 seconds, that is, the current monitoring results must be displayed within 30 seconds. In summary, the existing methods for extracting low-frequency strain response signals of distributed fiber optic fracturing cannot process huge optical fiber signals in a timely manner, making the processing and display of optical fiber signals extremely difficult. Summary of the invention

[0006] One object of the present invention is to provide a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber. The method aims to reduce the storage cost of the low-frequency strain response signals of fracturing of distributed optical fiber, improve the signal-to-noise ratio of the data, and make the calculation process concise and efficient, thereby providing favorable technical support for the crack extension and development process for optical fiber fracturing monitoring.

[0007] Another object of the present invention is to provide a device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber. Another object of the present invention is to provide a computer device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber when executing the computer program. Another object of the present invention is to provide a readable medium, on which a computer program is stored, and when the computer program is executed by the processor, the steps of the above-mentioned method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber are implemented.

[0008] In order to achieve the above objectives, the present invention discloses a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber, comprising:

[0009] Generate a time domain filter of the target reservoir according to reservoir petrophysical parameters of the target reservoir;

[0010] Generate an expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0011] The expected signal is downsampled according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0012] In some embodiments of the invention, the step of generating a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir includes:

[0013] Setting a low-pass filter corresponding to the target reservoir according to the reservoir rock physical property parameters of the target reservoir;

[0014] The low-pass filter is inverse Fourier transformed to generate the time domain filter.

[0015] In some embodiments of the invention, generating the expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter includes:

[0016] extracting strain rate data from the distributed optical fiber acoustic wave data;

[0017] The strain rate data is convolved with the time domain filter to generate the desired signal.

[0018] In some embodiments of the invention, before downsampling the expected signal according to the effective aperture of the microfractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, the method further includes:

[0019] Divide the desired signal into blocks to generate a plurality of block data;

[0020] The expected signal is divided into blocks, comprising:

[0021] Determine a sampling time window according to the length of the expected signal;

[0022] Calculating the average value of the expected signal within the sampling time window;

[0023] Determine the number of sampling points in each block of data according to the average value;

[0024] The desired signal is divided into blocks according to the number of sampling points in each block of data.

[0025] In some embodiments of the invention, downsampling the expected signal according to the effective aperture of the microfractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir includes:

[0026] Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir;

[0027] The expected signal is downsampled according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

[0028] In some embodiments of the invention, the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further includes:

[0029] determining a maximum frequency of the desired signal;

[0030] Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency;

[0031] Downsampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, further comprising:

[0032] Determining a sampling time of the downsampling according to the sampling frequency;

[0033] The expected signal is downsampled according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

[0034] In some embodiments of the invention, the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further includes:

[0035] Determining the influence weights of different throats in the target reservoir on the permeability;

[0036] Determining the effective permeability of the target reservoir according to the impact weight;

[0037] The effective opening of the microcracks is determined according to the effective permeability.

[0038] The present invention also discloses a distributed optical fiber-based fracturing low-frequency strain response signal extraction device, comprising:

[0039] A time domain filter generation module, used to generate a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir;

[0040] An expected signal generating module, used for generating an expected signal corresponding to the distributed optical fiber acoustic wave data of the target reservoir according to the pre-acquired distributed optical fiber acoustic wave data and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0041] The expected signal downsampling module is used to downsample the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0042] In some embodiments of the invention, the time domain filter generation module includes:

[0043] A low-pass filter setting unit, used for setting a low-pass filter corresponding to the target reservoir according to the reservoir petrophysical parameters of the target reservoir;

[0044] The time domain filter generating unit is used to perform inverse Fourier transform on the low pass filter to generate the time domain filter.

[0045] In some embodiments of the invention, the expected signal generation module includes:

[0046] A strain rate data extraction unit, used to extract strain rate data from the distributed optical fiber acoustic wave data;

[0047] The expected signal generating unit is used to convolve the strain rate data with the time domain filter to generate the expected signal.

[0048] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0049] An expected signal block module, used for dividing the expected signal into blocks to generate a plurality of block data;

[0050] The desired signal block module comprises:

[0051] A sampling time window determining unit, used to determine the sampling time window according to the length of the expected signal;

[0052] An average value calculation unit, used to calculate the average value of the expected signal within the sampling time window;

[0053] a sampling point determination unit, configured to determine the number of sampling points in each block of data according to the average value;

[0054] The expected signal blocking unit blocks the expected signal according to the number of sampling points in each block of data.

[0055] In some embodiments of the invention, the desired signal downsampling module includes:

[0056] A sampling frequency determination unit, used to determine the sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir;

[0057] The expected signal down-sampling unit is used to down-sample the expected signal according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

[0058] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0059] A maximum frequency determination module, used to determine the maximum frequency of the expected signal;

[0060] A sampling frequency determination module, used to determine the sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency;

[0061] The expected signal downsampling module also includes:

[0062] A sampling time determining unit, used to determine the sampling time of the downsampling according to the sampling frequency;

[0063] The strain response signal extraction unit is used to downsample the expected signal according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

[0064] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0065] An influence weight determination module, used to determine the influence weights of different throats in the target reservoir on the permeability;

[0066] An effective permeability determination module, used to determine the effective permeability of the target reservoir according to the impact weight;

[0067] The effective opening determination module is used to determine the effective opening of the microcrack according to the effective permeability.

[0068] The present invention also discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0069] When the processor executes the program, the method described above is implemented.

[0070] The present invention also discloses a computer readable medium having a computer program stored thereon.

[0071] When the program is executed by a processor, the method described above is implemented.

[0072] From the above description, it can be seen that the method and device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber provided in an embodiment of the present invention first generate a time domain filter of the target reservoir according to the reservoir rock physical property parameters of the target reservoir; then, based on the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter, an expected signal corresponding to the distributed optical fiber acoustic wave data is generated; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; finally, the expected signal is downsampled according to the effective aperture of the microcracks of the target reservoir to extract the low-frequency strain response signal of fracturing of the target reservoir.

[0073] The present invention is aimed at the distributed optical fiber strain response monitoring scenario during hydraulic fracturing, and proposes a method and device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber based on time domain convolution and block processing. The method and device extract strain response signals from distributed optical fiber acoustic sensing data. On the one hand, the method extracts strain response signals through the time domain convolution operator, avoiding forward and inverse Fourier transforms for each channel, and reducing the amount of calculation; on the other hand, the amount of data is reduced through block processing, which reduces the data storage cost and improves the signal-to-noise ratio of the data. The calculation process is simple and efficient, which can provide effective technical support for the crack expansion and development process for optical fiber fracturing monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 It is a schematic diagram of a flow chart of a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in Embodiment 1 of the present invention;

[0076] Figure 2 1 is a flow chart of step 100 in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0077] Figure 3 This is a flow chart of step 200 in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0078] Figure 4 It is another schematic diagram of the process of extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0079] Figure 5 4 is a flow chart of step 400 in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0080] Figure 6 It is a flow chart of step 300 in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0081] Figure 7 This is a third flow chart of the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0082] Figure 8 Another flowchart diagram of step 300 in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0083] Fig. 9 This is a fourth flow chart of the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the first embodiment of the present invention;

[0084] Fig.10 It is a schematic diagram of the flow of a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the second embodiment of the present invention;

[0085] Fig.11 This is a schematic diagram of DAS raw data in Embodiment 2 of the present invention;

[0086] Fig.12 This is a schematic diagram of a frequency domain filter in Embodiment 2 of the present invention;

[0087] Fig.13 Schematic diagram of a time domain filtering operator in Embodiment 2 of the present invention;

[0088] Fig.14 This is a schematic diagram of a high signal-to-noise ratio extraction result of a low-frequency strain response in the second embodiment of the present invention;

[0089] Fig.15 It is a schematic diagram of the structure of a device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in Embodiment 3 of the present invention;

[0090] Fig.16 It is a schematic diagram of the structure of an electronic device in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0091] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0092] It should be noted that the terms "including" and "having" in the specification and claims of the present application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. In the absence of conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0093] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of laws and regulations.

[0094] Embodiment 1

[0095] In this embodiment, Figure 1 As shown, a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber is provided, which comprises:

[0096] Step 100: generating a time domain filter of the target reservoir according to reservoir petrophysical parameters of the target reservoir;

[0097] Specifically, the amplitude and phase of the fracturing low-frequency strain response signal in time are adjusted according to the reservoir rock physical parameters of the target reservoir to achieve control of different frequency components. A set of filter coefficients or filter functions are usually used to filter the input fracturing low-frequency strain response signal and output the signal result after filtering. Common time domain filters include low-pass filters, high-pass filters, band-pass filters, and band-stop filters. Preferably, the time domain filter generated in step 100 is a band-stop filter.

[0098] It should be noted that the time domain filter is a linear time-invariant system (LTI), and its filtering effect is affected by the frequency response of the signal, the characteristics of the filter, and the filter parameters. When selecting and designing the time domain filter, it is necessary to make reasonable selections and adjustments based on the reservoir rock physical parameters of the target reservoir.

[0099] Preferably, the reservoir rock physical property parameters in step 100 include: porosity, permeability, saturation, porosity distribution, pore structure, saturation distribution, rock density and rock elastic modulus, specifically:

[0100] Porosity refers to the proportion of pore space in reservoir rock, usually expressed as a percentage. The higher the porosity, the greater the storage capacity of the reservoir.

[0101] Permeability is a measure of the ability of rock to support fluid flow and describes the degree of pore connectivity in reservoir rock. The higher the permeability, the greater the fluid flow capacity.

[0102] Saturation refers to the degree to which the pore space in the reservoir rock is filled with fluid, and is usually expressed in terms of water saturation, oil saturation, gas saturation, etc.

[0103] Porosity distribution is used to describe the changes in the spatial distribution of reservoir porosity. Different porosity distributions have different effects on fluid mobility.

[0104] Pore ​​structure is used to describe the shape, size, connectivity and other characteristics of reservoir pores, which affects the flow pattern of fluid in the reservoir.

[0105] Saturation distribution is used to describe the spatial distribution of different fluid saturations in a reservoir and is of great significance to reservoir development and evaluation.

[0106] Rock density is used to characterize the density of reservoir rocks and can be used to calculate the volume of fluid in the reservoir.

[0107] Rock elastic modulus is used to describe the elastic properties of reservoir rocks and is used to determine the in-situ stress of reservoirs.

[0108] Step 200: generating an expected signal corresponding to the distributed optical fiber acoustic wave data of the target reservoir according to the pre-acquired distributed optical fiber acoustic wave data and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0109] Distributed Acoustic Sensing (DAS) is based on the principle of optical time-domain reflectometer (OTDR). It sends laser pulses to the connected detection optical cable through a high-power laser transmitter, and collects and analyzes the Rayleigh scattered light in the backscattered light, thereby realizing distributed perception of vibration or acoustic wave signals. In-well fracturing monitoring based on DAS not only has the advantages of high temperature resistance, high pressure resistance, and corrosion resistance, but also can achieve high-density sampling in space in the entire well section. It is a new type of fracturing monitoring technology. There is a certain functional relationship between distributed fiber optic acoustic wave data and reservoir rock strain (generated by fracturing of the reservoir). By determining this functional relationship, the rock strain of the target reservoir can be predicted based on distributed fiber optic acoustic wave data. The reservoir rock strain here is the relative change in length or volume of the reservoir rock under stress (fracturing). Its meaning is the ratio of the changed shape or volume to the original.

[0110] When step 200 is implemented, the distributed fiber acoustic wave data and the time domain filter are convolved to generate the desired signal in step 200 .

[0111] Step 300: down-sampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0112] As we all know, the amount of optical fiber signal data is large, so the optical fiber data processing requires high computer computing power. At the same time, the display of processing results requires high computer graphics cards. In short, on the basis of extracting strain data, downsampling processing is also required to improve the calculation effect and display capability. In addition, due to the influence of environmental noise and internal impurities, the optical fiber measurement data of distributed optical fiber monitoring has noise, resulting in a low signal-to-noise ratio of the data. Therefore, while performing downsampling processing, it is also necessary to improve the signal-to-noise ratio of the extracted low-frequency strain response signal of fracturing.

[0113] From the above description, it can be seen that the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber provided in an embodiment of the present invention first generates a time domain filter of the target reservoir according to the reservoir rock physical property parameters of the target reservoir; then, based on the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter, an expected signal corresponding to the distributed optical fiber acoustic wave data is generated; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; finally, the expected signal is downsampled according to the effective aperture of the microcracks of the target reservoir to extract the low-frequency strain response signal of fracturing of the target reservoir.

[0114] The present invention is aimed at the distributed optical fiber strain response monitoring scenario during hydraulic fracturing, and proposes a method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber based on time domain convolution and block processing. The method extracts strain response signals from distributed optical fiber acoustic sensing data. On the one hand, the method extracts strain response signals through the time domain convolution operator, avoiding forward and inverse Fourier transforms for each channel and reducing the amount of calculation; on the other hand, the block processing reduces the amount of data, reduces the data storage cost, and improves the signal-to-noise ratio of the data. The calculation process is simple and efficient, which can provide effective technical support for the crack expansion and development process for optical fiber fracturing monitoring.

[0115] In some embodiments of the present invention, see Figure 2 , step 100 comprises:

[0116] Step 101: setting a low-pass filter corresponding to the target reservoir according to reservoir petrophysical parameters of the target reservoir;

[0117] First, the cutoff frequency F is determined according to the porosity, permeability, saturation, porosity distribution, pore structure, saturation distribution, rock density and rock elastic modulus of the target reservoir to filter out the part of the low-frequency strain response signal of fracturing with a frequency higher than F (Hz).

[0118] Step 102: Perform inverse Fourier transform on the low-pass filter to generate the time domain filter.

[0119] In step 102, the mathematical expression of the inverse Fourier transform is:

[0120] f(t)=(1 / 2π)∫F(ω)e^(jωt)dω

[0121] Among them, f(t) is the representation of the function (low-pass filter) in the time domain, F(ω) is the representation of the function (low-pass filter) in the frequency domain, t is time, and ω is the angular frequency.

[0122] The role of the inverse Fourier transform is to convert the function in the frequency domain back to the time domain, thereby obtaining the temporal representation of the low-pass filter. When performing the inverse Fourier transform, it is necessary to pay attention to the sampling rate and truncation effect of the signal according to the reservoir rock physical parameters, and reasonably select the appropriate inverse Fourier transform algorithm and parameters to ensure accurate time domain representation.

[0123] In some embodiments of the present invention, see Figure 3 , step 200 comprises:

[0124] Step 201: extracting strain rate data from the distributed optical fiber acoustic wave data;

[0125] First, use the matlab function H5disp to read the information of "RawDataUnit" in "Group' / Acquisition / Raw[0]" of the HDF5 file in the distributed fiber acoustic wave data to determine the physical meaning of the stored data. If the value of this tag is "rad", the type of DAS data is strain rate, and then the strain rate data is extracted.

[0126] In addition, if the tag value is "nε", the type of DAS data is strain data. It is necessary to perform time difference on the strain data to obtain the strain rate data.

[0127] Step 202: Convolve the strain rate data with the time domain filter to generate the desired signal.

[0128] Specifically, the strain rate data is slid over the time filter, and a product operation is performed at each position, and all the product results are added together. In this way, a new function, the expected signal, is obtained, which describes the interaction between the strain rate data and the time domain filter.

[0129] Assume that the time domain filter is h(t), which is obtained by inverse Fourier transform of the low-pass filter H(f):

[0130]

[0131] In some embodiments of the present invention, see Figure 4 The method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further includes, before step 300:

[0132] Step 400: Divide the desired signal into blocks to generate a plurality of block data;

[0133] Further, see Figure 5 , step 400 further comprises:

[0134] Step 401: Determine a sampling window according to the length of the expected signal;

[0135] Step 402: Calculate the average value of the expected signal within the sampling time window;

[0136] Step 403: determining the number of sampling points in each block of data according to the average value;

[0137] Step 404: Divide the desired signal into blocks according to the number of sampling points in each block of data.

[0138] In step 401 to step 404, the DAS seismic data is cut into N / K blocks, each block of data is K sampling points. The data in the time window determined by the length of the expected signal is averaged:

[0139]

[0140] Next, the average As the number of sampling points in the time window, N / K sampling points are finally obtained, thereby dividing the desired signal into blocks.

[0141] In some embodiments of the present invention, see Figure 6 , step 300 comprises:

[0142] Step 301: determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir;

[0143] Through a large amount of experimental data and actual production data, the applicant found that the effective aperture of the microfractures of the target reservoir has a very obvious indicative effect on the sampling frequency. Therefore, the sampling frequency in the process of downsampling the low-frequency strain response signal of the fracturing can be effectively determined according to the effective aperture of the microfractures.

[0144] Step 302: down-sampling the expected signal according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

[0145] In some embodiments of the present invention, see Figure 7 , the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber also includes:

[0146] Step 500: Determine the highest frequency of the desired signal;

[0147] Step 600: determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency;

[0148] Based on the sampling theorem, the sampling frequency F c Must satisfy the following formula

[0149] F c ≥2×F

[0150] Where F is the highest frequency in the target signal frequency band.

[0151] In some embodiments of the present invention, see Figure 8 , step 300 further includes:

[0152] Step 303: Determine the sampling time of the downsampling according to the sampling frequency;

[0153] Based on the following formula, it can be inferred that the maximum time sampling interval △t is:

[0154] △t=1 / F c ≤2×F

[0155] Step 304: down-sample the expected signal according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

[0156] By downsampling the filtered desired signal using the above sampling interval, the purpose of efficiently extracting the low-frequency strain response signal of fracturing from DAS records can be achieved. Specifically, assuming that the time sampling interval of the original DAS record is △tt, and the time sampling interval of the downsampling is △t, the downsampling rate is

[0157]

[0158] In some embodiments of the present invention, see Fig. 9 , the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber also includes:

[0159] Step 700: Determine the influence weights of different throats in the target reservoir on the permeability;

[0160] Core analysis is performed on the core of the target reservoir to obtain its corresponding full-scale throat distribution curve, and then the relationship between the average throat radius and the permeability is determined according to the full-scale throat distribution curve. Specifically:

[0161] The full-scale throat distribution is normalized and the average throat radius is calculated using the following formula;

[0162]

[0163] Where: represents the average throat radius;

[0164] r i represents the throat radius corresponding to the i-th point;

[0165] n represents the number of data points;

[0166] α iRepresents the normalized distribution frequency of the throat radius.

[0167] Next, the average throat radius of all samples is obtained; a correlation curve (scatter plot) between the average throat radius and the permeability is drawn, and a correlation function between the average throat radius and the permeability is obtained.

[0168] Finally, the influence weight of throats with different radii on permeability is calculated using the following formula:

[0169]

[0170] Where: △K i Represents the impact weight of permeability.

[0171] Step 800: determining the effective permeability of the target reservoir according to the impact weight;

[0172] Establish a distribution curve with the throat radius as the horizontal axis and the cumulative influence weight of permeability as the vertical axis to determine the throat radius when the sample permeability contribution reaches 99.99%, which is the lower limit of the effective throat radius K. L .

[0173] Step 900: Determine the effective opening of the microcracks according to the effective permeability.

[0174] Specifically, the casting thin sections and scanning electron microscope of all samples were measured to obtain the maximum value of the microcrack spacing D MAX , and record the corresponding effective permeability; the effective microcrack opening e is calculated using the following formula L .

[0175]

[0176] From the above description, it can be seen that the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber provided in the embodiment of the present invention first generates a time domain filter of the target reservoir according to the reservoir rock physical property parameters of the target reservoir; then, the expected signal corresponding to the distributed optical fiber acoustic wave data is generated according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; finally, the expected signal is downsampled according to the effective aperture of the micro-fractures of the target reservoir to extract the low-frequency strain response signal of the fracturing of the target reservoir. Specifically, the present invention has the following beneficial effects:

[0177] The present invention extracts strain response signals from DAS data through a time domain convolution operator, avoiding the forward and inverse Fourier transforms of each channel in frequency domain processing, thereby greatly reducing the amount of calculation; while downsampling, the signal-to-noise ratio of strain is improved by processing the desired signal in blocks. It not only ensures the acquisition of effective signals, but also reduces the amount of data required for calculation. In summary, the method for extracting low-frequency strain response signals based on distributed optical fiber fracturing provided by the present invention can meet the requirements of real-time on-site monitoring during fracturing, while improving the accuracy of the results. The calculation process is concise and efficient. It can provide technical support for using strain to describe crack extension characteristics in real time during distributed optical fiber fracturing monitoring.

[0178] Embodiment 2

[0179] In order to further illustrate the solution, the present invention also provides a specific application example of the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber, specifically, as follows Fig.10 As shown, the specific application example includes the following steps:

[0180] S1: Acquire the DAS signal monitored during fracturing.

[0181] like Fig.11 As shown, the DAS recording time sampling interval is 2KHz.

[0182] S2: Build a low-pass filter.

[0183] First, we need to set a cutoff frequency F to filter out the components in the signal with a frequency higher than F (Hz). Assuming that the original DAS recording time sampling interval is △t and the number of time sampling points is N, the frequency sampling interval △f of the filter is,

[0184]

[0185] Based on the filtering principle, in order to avoid the Gibbs phenomenon caused by filtering, it is necessary to set a high cutoff frequency f of the low-pass filter. h , set as follows

[0186] f h =0.9×F

[0187] Based on this, the mathematical expression of the low-pass filter H(f) is:

[0188]

[0189] Among them, f k = k × △f. Here, F is selected as 1Hz, and the spectrum of the low-pass filter is as follows Fig.12 shown.

[0190] S3: Construct a time domain filter.

[0191] Let the time domain filter be h(t), which is obtained by inverse Fourier transform of H(f).

[0192]

[0193] S4: Generate expected signal.

[0194] Strain rate data for distributed fiber acoustic sensing (DAS) monitoring With the time domain filter h(t n ) is convolved to obtain the desired signal y(t n ,x m ).

[0195]

[0196] The expected signal generated is Fig.13 shown.

[0197] S5: Down-sample the desired signal.

[0198] First, set the time sampling interval required for downsampling. Based on the sampling theorem, the sampling frequency F c Must satisfy the following formula

[0199] F c ≥2×F

[0200] Where F is the highest frequency in the target signal frequency band.

[0201] Based on the following formula, it can be inferred that the maximum time sampling interval △t is:

[0202] △t=1 / F c ≤2×F

[0203] By using the above sampling interval (to downsample the filtered desired signal, the purpose of efficiently extracting the low-frequency strain response signal of fracturing from DAS records can be achieved. Assuming that the time sampling interval of the original DAS record is △tt, and the time sampling interval of the downsampled signal is △t, the downsampling rate is

[0204]

[0205] The original signal record length T is:

[0206] T=△tt×N

[0207] The seismic data is divided into N / K blocks, each block of data has K sampling points. The data in the time window is averaged

[0208]

[0209] The average As the sampling points in the time window, N / K sampling points are obtained to downsample the desired signal.

[0210] The above formula is used to calculate the time sampling interval after downsampling to be 0.5ms and the downsampling rate K to be 1000, and the downsampling of the ultra-low frequency fracturing strain response signal is completed through the above formula. The data after downsampling is as follows Fig.14 shown.

[0211] From the above description, it can be seen that the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber provided in an embodiment of the present invention first determines the frequency range of the low-pass filter and sets the filter; then, the low-pass filter is inverse Fourier transformed to obtain a time domain filter; then, the original record is convolved with the time domain filter, and finally, the data in the time window is downsampled using a block processing method, thereby achieving the purpose of extracting high signal-to-noise ratio strain response from distributed acoustic wave monitoring.

[0212] Embodiment 3

[0213] Based on the same principle, this embodiment also discloses a device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber. Fig.15 As shown, the device comprises:

[0214] A time domain filter generation module 10, used to generate a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir;

[0215] The expected signal generating module 20 is used to generate an expected signal corresponding to the distributed optical fiber acoustic wave data of the target reservoir according to the pre-acquired distributed optical fiber acoustic wave data and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0216] The expected signal downsampling module 30 is used to downsample the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0217] In some embodiments of the invention, the time domain filter generation module includes:

[0218] A low-pass filter setting unit, used for setting a low-pass filter corresponding to the target reservoir according to the reservoir petrophysical parameters of the target reservoir;

[0219] The time domain filter generating unit is used to perform inverse Fourier transform on the low pass filter to generate the time domain filter.

[0220] In some embodiments of the invention, the expected signal generation module includes:

[0221] A strain rate data extraction unit, used to extract strain rate data from the distributed optical fiber acoustic wave data;

[0222] The expected signal generating unit is used to convolve the strain rate data with the time domain filter to generate the expected signal.

[0223] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0224] An expected signal block module, used for dividing the expected signal into blocks to generate a plurality of block data;

[0225] The desired signal block module comprises:

[0226] A sampling time window determining unit, used to determine the sampling time window according to the length of the expected signal;

[0227] An average value calculation unit, used to calculate the average value of the expected signal within the sampling time window;

[0228] a sampling point determination unit, configured to determine the number of sampling points in each block of data according to the average value;

[0229] The expected signal blocking unit blocks the expected signal according to the number of sampling points in each block of data.

[0230] In some embodiments of the invention, the desired signal downsampling module includes:

[0231] A sampling frequency determination unit, used to determine the sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir;

[0232] The expected signal down-sampling unit is used to down-sample the expected signal according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

[0233] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0234] A maximum frequency determination module, used to determine the maximum frequency of the expected signal;

[0235] A sampling frequency determination module, used to determine the sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency;

[0236] The expected signal downsampling module also includes:

[0237] A sampling time determining unit, used to determine the sampling time of the downsampling according to the sampling frequency;

[0238] The strain response signal extraction unit is used to downsample the expected signal according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

[0239] In some embodiments of the invention, the device for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further comprises:

[0240] An influence weight determination module, used to determine the influence weights of different throats in the target reservoir on the permeability;

[0241] An effective permeability determination module, used to determine the effective permeability of the target reservoir according to the impact weight;

[0242] The effective opening determination module is used to determine the effective opening of the microcrack according to the effective permeability.

[0243] From the above description, it can be seen that the distributed optical fiber-based fracturing low-frequency strain response signal extraction device provided in an embodiment of the present invention first generates a time domain filter for the target reservoir according to the reservoir rock physical property parameters of the target reservoir; then, based on the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter, an expected signal corresponding to the distributed optical fiber acoustic wave data is generated; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; finally, the expected signal is downsampled according to the effective aperture of the microcracks of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0244] In the process of using distributed acoustic sensing signals DAS to describe the strain changes of underground formations during fracturing, the present invention processes the collected original DAS signals as described above, so as to avoid forward and reverse Fourier transforms one by one when obtaining the expected signal, reduce the amount of calculation, improve efficiency, and based on convolution operation and block processing, have the beneficial effects of simple and clear calculation process, high signal-to-noise ratio of the extracted signal, etc.

[0245] Embodiment 4

[0246] The embodiments of the present application also provide a specific implementation of an electronic device capable of implementing all steps in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the above embodiments, see Fig.16 , electronic equipment specifically includes the following:

[0247] Processor (processor) 1201, memory (memory) 1202, communication interface (CommunicationsInterface) 1203 and bus 1204;

[0248] The processor 1201, the memory 1202, and the communication interface 1203 communicate with each other via the bus 1204; the communication interface 1203 is used to realize information transmission between related devices such as server-side devices, computing units, and client devices.

[0249] The processor 1201 is used to call the computer program in the memory 1202. When the processor executes the computer program, all the steps in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0250] Generate a time domain filter of the target reservoir according to reservoir petrophysical parameters of the target reservoir;

[0251] Generate an expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0252] The expected signal is downsampled according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0253] In some embodiments of the invention, the step of generating a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir includes:

[0254] Setting a low-pass filter corresponding to the target reservoir according to the reservoir rock physical property parameters of the target reservoir;

[0255] The low-pass filter is inverse Fourier transformed to generate the time domain filter.

[0256] In some embodiments of the invention, generating the expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter includes:

[0257] extracting strain rate data from the distributed optical fiber acoustic wave data;

[0258] The strain rate data is convolved with the time domain filter to generate the desired signal.

[0259] In some embodiments of the invention, before downsampling the expected signal according to the effective aperture of the microfractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, the method further includes:

[0260] Divide the desired signal into blocks to generate a plurality of block data;

[0261] The expected signal is divided into blocks, comprising:

[0262] Determine a sampling time window according to the length of the expected signal;

[0263] Calculating the average value of the expected signal within the sampling time window;

[0264] Determine the number of sampling points in each block of data according to the average value;

[0265] The desired signal is divided into blocks according to the number of sampling points in each block of data.

[0266] In some embodiments of the invention, downsampling the expected signal according to the effective aperture of the microfractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir includes:

[0267] Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir;

[0268] The expected signal is downsampled according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

[0269] In some embodiments of the invention, the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further includes:

[0270] determining a maximum frequency of the desired signal;

[0271] Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency;

[0272] Downsampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, further comprising:

[0273] Determining a sampling time of the downsampling according to the sampling frequency;

[0274] The expected signal is downsampled according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

[0275] In some embodiments of the invention, the method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber further includes:

[0276] Determining the influence weights of different throats in the target reservoir on the permeability;

[0277] Determining the effective permeability of the target reservoir according to the impact weight;

[0278] The effective opening of the microcracks is determined according to the effective permeability.

[0279] Embodiment 5

[0280] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fibers in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps in the method for extracting low-frequency strain response signals of fracturing based on distributed optical fibers in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0281] Step 100: generating a time domain filter of the target reservoir according to reservoir petrophysical parameters of the target reservoir;

[0282] Step 200: generating an expected signal corresponding to the distributed optical fiber acoustic wave data of the target reservoir according to the pre-acquired distributed optical fiber acoustic wave data and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir;

[0283] Step 300: down-sampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

[0284] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0285] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0286] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0287] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0288] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0289] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0290] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for extracting low-frequency strain response signals of fracturing based on distributed optical fiber, characterized in that: include: Generate a time domain filter of the target reservoir according to reservoir petrophysical parameters of the target reservoir; Generate an expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; The expected signal is downsampled according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

2. The method for extracting low-frequency strain response signals of fracturing according to claim 1, characterized in that: The step of generating a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir comprises: Setting a low-pass filter corresponding to the target reservoir according to the reservoir rock physical property parameters of the target reservoir; The low-pass filter is inverse Fourier transformed to generate the time domain filter.

3. The method for extracting low-frequency strain response signals of fracturing according to claim 1, characterized in that: The method of generating an expected signal corresponding to the distributed optical fiber acoustic wave data according to the pre-acquired distributed optical fiber acoustic wave data of the target reservoir and the time domain filter comprises: extracting strain rate data from the distributed optical fiber acoustic wave data; The strain rate data is convolved with the time domain filter to generate the desired signal.

4. The method for extracting low-frequency strain response signals of fracturing according to any one of claims 1 to 3, characterized in that: Before downsampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, the method further includes: Divide the desired signal into blocks to generate a plurality of block data; The expected signal is divided into blocks, comprising: Determine a sampling time window according to the length of the expected signal; Calculating the average value of the expected signal within the sampling time window; Determine the number of sampling points in each block of data according to the average value; The desired signal is divided into blocks according to the number of sampling points in each block of data.

5. The method for extracting low-frequency strain response signals of fracturing according to claim 1, characterized in that: Downsampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir includes: Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir; The expected signal is downsampled according to the sampling frequency to extract the fracturing low-frequency strain response signal of the target reservoir.

6. The method for extracting low-frequency strain response signals of fracturing according to claim 5, characterized in that: Also includes: determining a maximum frequency of the desired signal; Determining a sampling frequency corresponding to the downsampling according to the effective aperture of the microfractures of the target reservoir and the maximum frequency; Downsampling the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir, further comprising: Determining a sampling time of the downsampling according to the sampling frequency; The expected signal is downsampled according to the sampling time to extract the fracturing low-frequency strain response signal of the target reservoir.

7. The method for extracting low-frequency strain response signals of fracturing according to claim 1, characterized in that: Also includes: Determining the influence weights of different throats in the target reservoir on the permeability; Determining the effective permeability of the target reservoir according to the impact weight; The effective opening of the microcracks is determined according to the effective permeability.

8. A distributed optical fiber-based fracturing low-frequency strain response signal extraction device, characterized in that: include: A time domain filter generation module, used to generate a time domain filter of the target reservoir according to the reservoir petrophysical parameters of the target reservoir; An expected signal generation module, used to generate an expected signal corresponding to the distributed optical fiber acoustic wave data of the target reservoir according to the pre-acquired distributed optical fiber acoustic wave data and the time domain filter; wherein the distributed optical fiber acoustic wave data is generated by fracturing the target reservoir; The expected signal downsampling module is used to downsample the expected signal according to the effective aperture of the micro-fractures of the target reservoir to extract the fracturing low-frequency strain response signal of the target reservoir.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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