Velocity inversion method and system for acquiring perforation signals based on in-well DAS

Abstract

The invention provides a speed inversion method and system based on perforation signals acquired by a downhole DAS, and belongs to the field of oil and gas exploitation. The method comprises the following steps: firstly, setting a uniform velocity model, then uniformly segmenting DAS full-well-section acquired data in a well, and carrying out segmented velocity inversion from bottom to top based on perforation signal direct wave first arrival time information acquired in each section. According to the method, the advantages of DAS full-well-section collection in a well are utilized, the strategy of inversion from bottom to top one by one well section is adopted in the speed inversion process, the inversion result can be obtained without depending on an initial speed model, meanwhile, multiplicity of solutions is greatly reduced, and a high-precision speed model can be provided for DAS microseism phase recognition and seismic source positioning.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas exploitation, and in particular relates to a velocity inversion method and system based on DAS acquisition of perforation signals in a well. Background Art

[0002] In the field of oil and gas extraction, the application of microseismic monitoring technology is mainly to collect microseismic signals generated during hydraulic fracturing to monitor the fracturing process and evaluate the fracturing effect. Conventional in-well microseismic monitoring uses a dedicated three-component detector in the well to collect microseismic signals, and completes the processing of microseismic signals through methods such as filtering, phase identification and source location. However, due to the limitations of factors such as the number of detectors that can be deployed and the temperature resistance of the detectors, conventional in-well microseismic monitoring methods have a capacity limit in terms of effective monitoring distance and source location accuracy.

[0003] Distributed fiber acoustic sensing technology (hereinafter referred to as "DAS") is based on the principle of optical time domain reflectometry (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 signals. Microseismic monitoring in wells based on DAS not only has the advantages of high temperature resistance, high pressure resistance, and corrosion resistance, but also can achieve high spatial density sampling of vibration signals in the entire well section. It is a new type of fracturing microseismic monitoring technology.

[0004] The accuracy of microseismic phase identification and source location depends on the accuracy of the velocity model. The current conventional microseismic velocity inversion method is to first use acoustic logging to establish an initial layered velocity model, and then use the direct wave first arrival time information of the perforation signal to perform velocity inversion. This method relies on the initial velocity model, and because the layer velocity and layer interface must be inverted at the same time, it has strong multi-solution. Since DAS microseismic monitoring is a full-well acquisition, the direct wave first arrival time of the lower receiving point is only affected by the lower local formation velocity, which makes it possible to perform high-precision velocity inversion from bottom to top in each well section. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned difficulties in the prior art and to provide a velocity inversion method and system based on DAS acquisition of perforation signals in the well. In the velocity inversion process, a bottom-up well section inversion strategy is adopted, which is independent of the acquisition of the initial velocity model and greatly reduces the multi-solution problem.

[0006] One of the purposes of the present invention is to provide a velocity inversion method based on perforation signals collected by DAS in a well.

[0007] The second object of the present invention is to provide a velocity inversion system based on DAS acquisition of perforation signals in the well.

[0008] A third object of the present invention is to provide a computer-readable storage medium.

[0009] A fourth object of the present invention is to provide a computer device.

[0010] The present invention is achieved through the following technical solutions:

[0011] The first aspect of the present invention provides a velocity inversion method based on perforation signals collected by DAS in the well. First, a uniform velocity model is set, and then the data collected by DAS in the whole well section is evenly segmented, and based on the first arrival time information of the direct wave of the perforation signal collected in each section, segmented velocity inversion is performed from bottom to top.

[0012] A further improvement of the present invention is:

[0013] The method comprises the following steps:

[0014] Step 1, model setting;

[0015] Step 2: Perform segmented velocity inversion from bottom to top.

[0016] A further improvement of the present invention is:

[0017] The step 1 includes:

[0018] In DAS microseismic acquisition in wells, any point along the length of the optical fiber can be defined as a sensing point. Assuming that there are n sensing points defined along the optical fiber, the i-th sensing point is denoted as r. i (i=1,2,...,n); the perforation position is recorded as s, and the first arrival time of the perforation direct wave from s to the i-th sensor point is t i ;

[0019] Divide the n sensing points of the whole well section into m sections, and the number of sampling points in each section is floor(n / m), where floor() is a rounding operation;

[0020] Then the DAS sensing points contained in the jth segment are recorded as:

[0021] R j = {r n-(j-1)*floor(n / m) , r n-(j-1)*floor(n / m)-1 , ..., r n-j*floor(n / m)+1}

[0022] Among them, floor() represents rounding towards negative infinity;

[0023] The first arrival time of the perforation direct wave corresponding to the jth segment is Tj, and the specific formula is:

[0024] T j ={t n-(j-1)*floor(n / m), t n-(j-1)*floor(n / m)-1 , ..., t n-j*floor(n / m)+1}.

[0025] A further improvement of the present invention is:

[0026] The step 1 also includes:

[0027] Given the initial velocity model V for inversion 0 = {v 0 ,h 0},v 0 is the speed, h 0 is the depth of the velocity layer interface, the number of layers is l, and the velocity of the kth layer is The upper interface depth of the velocity layer is

[0028] The initial velocity model is set to a uniform velocity model, that is, l=1.

[0029] A further improvement of the present invention is:

[0030] The step 1 further includes:

[0031] Sets the threshold parameters used in subsequent inversions.

[0032] A further improvement of the present invention is:

[0033] The step 2 includes performing velocity inversion on the first segment, and the specific process is as follows:

[0034] (1) Set the initial velocity model to V 1 =V 0 ;

[0035] (2) Based on the velocity model V 1 , calculate the distance from s to R using the two-point ray tracing method 1 The theoretical first arrival time of the perforation direct wave is TT 1 ;

[0036] (3) Calculate the theoretical first arrival time TT 1 The actual first arrival time T 1 The residual between:

[0037] residual 1 =RMS(TT 1 -T 1 )

[0038] (4) If residual 1 <threshold, then set the speed model V 1 = {v 1 ,h 1}, where v1 =v 0 ,h 1 =h 0 , the first segment inversion is completed, and the subsequent second to floor (n / m) segment inversion process begins; if residual j >threshold, then go to step (5) to continue velocity inversion;

[0039] (5) Set v 1 Speed ​​scanning range V min :deltaV:V max , where V min and V max are the minimum and maximum scanning speeds, respectively. deltaV is the speed scanning step. For each scanning speed, repeat steps (2) and (3). After the scanning is completed, select the smallest residual 1 The corresponding velocity v is taken as the inversion result, and v 1 =v;

[0040] (6) Set V 1 = {v 1 ,h 1}.

[0041] A further improvement of the present invention is:

[0042] The step 2 also includes sequentially performing velocity model inversion on the 2nd to floor (n / m) segments, and the specific process is as follows:

[0043] For the jth segment:

[0044] (7) Set the initial velocity model to V j =V j-1 ;

[0045] (8) Based on the velocity model V j , calculate the distance from s to R using the two-point ray tracing method j The theoretical first arrival time of the perforation direct wave is TT j ;

[0046] (9) Calculate the theoretical first arrival time TT j The actual first arrival time T j The residual between:

[0047] residual j =RMS(TT j -T j )

[0048] (10) If residual j<threshold, then the current speed model V is not used. j Make the modification and return to step (7) to continue the inversion of the j+1th segment; if residual j >threshold, then go to step (11) to continue velocity inversion;

[0049] (11) Increase the number of speed layers l = l + 1, let R j The first sensing point in n-(j-1)*floor(n / m) The depth is assigned to And order against Set the speed scanning range V min :deltaV:V max , where V min and V max are the minimum and maximum scanning speeds respectively, deltaV is the speed scanning step size, for each Repeat steps (8) and (9) at the scanning speed. After the scanning is completed, select the smallest residual j The corresponding speed v is The final value of

[0050] After the velocity inversion calculations of the 1st to floor (n / m) segments are completed in sequence, the velocity inversion calculation based on the perforation signal collected by the DAS in the well is completed.

[0051] In a first aspect, the present invention provides a velocity inversion system based on DAS acquisition of perforation signals in a well, comprising:

[0052] Setting unit, used for model setting;

[0053] The inversion unit is used to perform segmented velocity inversion from bottom to top.

[0054] A third object of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the velocity inversion method based on the DAS acquisition of perforation signals in the well as described above.

[0055] A fourth aspect of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the velocity inversion method based on perforation signals collected by DAS in the well as described above.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention takes advantage of the full-section DAS acquisition in the well and adopts a bottom-up well section inversion strategy in the velocity inversion process. The inversion result is independent of the acquisition of the initial velocity model, and the multi-solution is greatly reduced, which can provide a high-precision velocity model for DAS microseismic phase identification and source location.

[0058] The method of the present invention utilizes the characteristic that the entire well section of the optical fiber is collected, and performs segmented inversion from bottom to top. In this way, the velocity inversion result of the lower part is not affected by the travel time of the upper received signal. Therefore, compared with the overall one-time inversion in the existing method, the stability of the segmented inversion from bottom to top is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a technical flow chart of a velocity inversion method based on DAS acquisition of perforation signals in a well in an embodiment of the present invention;

[0060] Figure 2 is a schematic diagram of the perforation source position and the optical fiber sensor position;

[0061] Figure 3 is a schematic diagram of the true velocity model;

[0062] Figure 4 It is the direct wave synthetic record of perforation signal;

[0063] Figure 5 is the first arrival time of the direct wave of the perforation signal;

[0064] Figure 6 is the initial velocity model;

[0065] Figure 7 is the layered velocity model obtained by inversion. DETAILED DESCRIPTION

[0066] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0067] In order to provide a high-precision velocity model for DAS microseismic phase identification and source location, the present invention takes advantage of the full-well section acquisition of DAS in the well and proposes a velocity inversion method based on the perforation signal acquired by DAS in the well. This method adopts a bottom-up well section inversion strategy in the velocity inversion process, which is independent of the acquisition of the initial velocity model and greatly reduces the multi-solution problem.

[0068] The present invention first sets an arbitrary uniform velocity model, then uniformly segments the DAS full-section acquisition data in the well, and performs segmented velocity inversion from bottom to top based on the first arrival time information of the direct wave of the perforation signal acquired in each section. When each section velocity is inverted, only the layer velocity and layer velocity interface at the depth of the current section are updated.

[0069] [Example 1]

[0070] The embodiment of the present invention provides a velocity inversion method based on DAS acquisition of perforation signals in a well. The technical implementation process is as follows: Figure 1 As shown, the specific steps include:

[0071] Step 1: Model setup

[0072] In DAS microseismic acquisition in wells, any point along the length of the optical fiber can be defined as a sensing point, such as Figure 2 As shown in the figure, it is assumed that there are n sensing points defined along the optical fiber, and the i-th sensing point is denoted as r i (i=1,2,...,n); the perforation position is recorded as s, and the first arrival time of the perforation direct wave from s to the i-th sensor point is t i ;

[0073] Divide the n sensing points of the whole well section into m sections, and the number of sampling points in each section is floor(n / m), where floor() is a rounding operation;

[0074] Then the DAS sensing points contained in the jth segment are recorded as:

[0075] R j = {r n-(j-1)*floor(n / m) , r n-(j-1)*floor(n / m)-1 , ..., r n-j*floor(n / m)+1}

[0076] Among them, floor() represents rounding towards negative infinity;

[0077] The first arrival time of the perforation direct wave corresponding to the jth segment is Tj, and the specific formula is:

[0078] T j ={t n-(j-1)*floor(n / m) , t n-(j-1)*floor(n / m)-1 , ..., t n-j*floor(n / m)+1}

[0079] Given the initial velocity model V for inversion 0 = {v 0 ,h 0},v 0 is the speed, h 0 is the depth of the velocity layer interface, which can be given any value. The number of layers is recorded as l, where the velocity of the kth layer is The upper interface depth of the velocity layer is The present invention sets the initial velocity model to be a uniform velocity model, that is, l=1.

[0080] Set the threshold parameter threshold used in subsequent inversion. Theoretically, the threshold parameter can be greater than 0. However, the lower the threshold, the higher the inversion accuracy but the worse the stability. The higher the threshold, the lower the inversion accuracy but the better the stability. It is an empirical value.

[0081] Step 2, perform segmented velocity inversion from bottom to top;

[0082] Specific operations include:

[0083] For the first segment:

[0084] (1) Set the initial velocity model to V 1 =V 0 ;

[0085] (2) Based on the velocity model V 1 , calculate the distance from s to R using the two-point ray tracing method 1 The theoretical first arrival time of the perforation direct wave is TT 1 ;

[0086] (3) Calculate the theoretical first arrival time TT 1 The actual first arrival time T 1 The residual between:

[0087] residual 1 =RMS(TT 1 -T 1 )

[0088] (4) If residual 1 <threshold, then set the speed model V 1 = {v 1 ,h 1}, where v 1 =v 0 ,h 1 =h 0 , the first segment inversion is completed, and the subsequent second to floor (n / m) segment inversion process begins; if residual j >threshold, then go to step (5) to continue velocity inversion;

[0089] (5) Set v 1 Speed ​​scanning range V min :deltaV:V max , where V min and V max The minimum and maximum scanning speeds (V min and V maxare all artificially set parameters, empirical values), deltaV is the speed scanning step, for each scanning speed, repeat steps (2) and (3), after the scanning is completed, select the smallest residual 1 The corresponding velocity v is taken as the inversion result, and v 1 =v;

[0090] (6) Set V 1 = {v 1 ,h 1}.

[0091] Carry out velocity model inversion for the 2nd to floor (n / m) segments in turn:

[0092] For the jth segment:

[0093] (7) Set the initial velocity model to V j =V j-1 ;

[0094] (8) Based on the velocity model V j , calculate the distance from s to R using the two-point ray tracing method j The theoretical first arrival time of the perforation direct wave is TT j ;

[0095] (9) Calculate the theoretical first arrival time TT j The actual first arrival time T j The residual between:

[0096] residual j =RMS(TT j -T j )

[0097] (10) If residual i <threshold, then the current speed model V is not used. j Make the modification and return to step (7) to continue the inversion of the j+1th segment; if residual i >threshold, then go to step (11) to continue velocity inversion;

[0098] (11) Increase the number of speed layers l = l + 1, let R j The first sensing point in n-(j-1)*floor(n / m) The depth is assigned to And order against Set the speed scanning range V min :deltaV:V max , where V min and Vmax are the minimum and maximum scanning speeds respectively, deltaV is the speed scanning step size, for each Repeat steps (8) and (9) at the scanning speed. After the scanning is completed, select the smallest residual j The corresponding speed v is The final value of .

[0099] After the velocity inversion calculations of the above-mentioned 1st to floor (n / m) segments are completed in sequence, the velocity inversion calculation based on the perforation signal collected by the DAS in the well is completed.

[0100] The maximum length of the optical fiber in the well is set to 5555 meters. Starting from the 100-meter length of the optical fiber at the wellhead, there is a sensing point every 5 meters, for a total of 1092 optical fiber sensing points. Figure 4 According to Table 1 and Figure 3 The direct wave record of the perforation signal obtained by the formation velocity model shown in the figure is Figure 5 is the first arrival time corresponding to the direct wave record. Figure 6 The velocity model obtained by inversion using the method of the present invention is shown in Table 3 and Figure 7 This embodiment shows that the velocity inversion method based on the DAS acquisition of perforation signals in the well proposed by the present invention has a high inversion accuracy.

[0101] Table 1 Design parameters of true velocity model

[0102] Speed ​​layer number Depth of velocity layer upper interface (m) Speed ​​(m / s) 1 0 1000 2 1000 2000 3 2000 3000 4 3000 4000

[0103] Table 2 Initial velocity model parameters

[0104] Speed ​​layer number Depth of velocity layer upper interface (m) Speed ​​(m / s) 1 0 3000

[0105] Table 3 Velocity model parameters obtained by inversion

[0106] Speed ​​layer number Depth of velocity layer upper interface (m) Speed ​​(m / s) 1 0 1000 2 955 1080 3 1005 2110 4 2005 3120 5 3005 4000

[0107] [Example 2]

[0108] The embodiment of the present invention provides a velocity inversion system based on DAS acquisition of perforation signals in a well, comprising:

[0109] To set the unit for model setting, perform the following operations:

[0110] In DAS microseismic acquisition in wells, any point along the length of the optical fiber can be defined as a sensing point, such as Figure 2 As shown in the figure, it is assumed that there are n sensing points defined along the optical fiber, and the i-th sensing point is denoted as r i (i=1,2,...,n); the perforation position is recorded as s, and the first arrival time of the perforation direct wave from s to the i-th sensor point is ti ;

[0111] Divide the n sensing points of the whole well section into m sections, and the number of sampling points in each section is floor(n / m), where floor() is a rounding operation;

[0112] Then the DAS sensing points contained in the jth segment are recorded as:

[0113] R j = {r n-(j-1)*floor(n / m) , r n-(j-1)*floor(n / m)-1， ..., r n-j*floor(n / m)+1}

[0114] Among them, floor() represents rounding towards negative infinity;

[0115] The first arrival time of the perforation direct wave corresponding to the jth segment is Tj, and the specific formula is:

[0116] T j ={t n-(j-1)*floor(n / m) , t n-(j-1)+floor(n / m)-1 , ..., t n-j*floor(n / m)+1}

[0117] Given the initial velocity model V for inversion 0 = {v 0 ,h 0},v 0 is the speed, h 0 is the depth of the velocity layer interface, which can be given any value. The number of layers is recorded as l, where the velocity of the kth layer is The upper interface depth of the velocity layer is The present invention sets the initial velocity model to be a uniform velocity model, that is, l=1.

[0118] Set the threshold parameter threshold used in subsequent inversion. Theoretically, the threshold parameter can be greater than 0. However, the lower the threshold, the higher the inversion accuracy but the worse the stability. The higher the threshold, the lower the inversion accuracy but the better the stability. It is an empirical value.

[0119] The inversion unit is used to perform segmented velocity inversion from bottom to top and performs the following operations:

[0120] For the first segment:

[0121] (1) Set the initial velocity model to V 1 =V 0 ;

[0122] (2) Based on the velocity model V 1 , calculate the distance from s to R using the two-point ray tracing method 1 The theoretical first arrival time of the perforation direct wave is TT 1 ;

[0123] (3) Calculate the theoretical first arrival time TT 1 The actual first arrival time T 1 The residual between:

[0124] residual 1 =RMS(TT 1 -T 1 )

[0125] (4) If residual 1 <threshold, then set the speed model V 1 = {v 1 ,h 1}, where v 1 =v 0 ,h 1 =h 0 , the first segment inversion is completed, and the subsequent second to floor (n / m) segment inversion process begins; if residual j >threshold, then go to step (5) to continue velocity inversion;

[0126] (5) Set v 1 Speed ​​scanning range V min :deltaV:V max , where V min and V max The minimum and maximum scanning speeds (V min and V max are all artificially set parameters, empirical values), deltaV is the speed scanning step, for each scanning speed, repeat steps (2) and (3), after the scanning is completed, select the smallest residual 1 The corresponding velocity v is taken as the inversion result, and v 1 =v;

[0127] (6) Set V 1 = {v 1 ,h 1}.

[0128] Carry out velocity model inversion for the 2nd to floor (n / m) segments in turn:

[0129] For the jth segment:

[0130] (7) Set the initial velocity model to V j =V j-1 ;

[0131] (8) Based on the velocity model V j , calculate the distance from s to R using the two-point ray tracing methodj The theoretical first arrival time of the perforation direct wave is TT j ;

[0132] (9) Calculate the theoretical first arrival time TT j The actual first arrival time T j The residual between:

[0133] residual j =RMS(TT j -T j )

[0134] (10) If residual i <threshold, then the current speed model V is not used. j Make the modification and return to step (7) to continue the inversion of the j+1th segment; if residual i >threshold, then go to step (11) to continue velocity inversion;

[0135] (11) Increase the number of speed layers l = l + 1, let R j The first sensing point in n-(j-1)*floor(n / m) The depth is assigned to And order against Set the speed scanning range V min :deltaV:V max , where V min and V max are the minimum and maximum scanning speeds respectively, deltaV is the speed scanning step size, for each Repeat steps (8) and (9) at the scanning speed. After the scanning is completed, select the smallest residual j The corresponding speed v is The final value of .

[0136] After the velocity inversion calculations of the above-mentioned 1st to floor (n / m) segments are completed in sequence, the velocity inversion calculation based on the perforation signal collected by the DAS in the well is completed.

[0137] [Example 3]

[0138] An embodiment of the present invention provides a computer-readable storage medium, which stores at least one computer-executable program. When the at least one program is executed by the computer, the computer executes the steps in the velocity inversion method based on DAS acquisition of perforation signals in the well as described in Example 1.

[0139] [Example 4]

[0140] An embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the velocity inversion method based on DAS acquisition of perforation signals in the well as described in Example 1.

[0141] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0142] The above technical solution is only one implementation mode of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the principles disclosed in the present invention, and it is not limited to the technical solution described in the above specific embodiments of the present invention. Therefore, the above description is only preferred and does not have a restrictive meaning.

Claims

1. A velocity inversion method based on DAS acquisition of perforation signals in a well, characterized in that: Firstly, a uniform velocity model is set, and then the DAS full-section acquisition data in the well is evenly segmented. Based on the first arrival time information of the direct wave of the perforation signal acquired in each section, the segmented velocity inversion is performed from bottom to top.

2. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 1 is characterized in that: The method comprises the following steps: Step 1, model setting; Step 2: Perform segmented velocity inversion from bottom to top.

3. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 2 is characterized in that: The step 1 includes: In DAS microseismic acquisition in wells, any point on the length of the optical fiber can be defined as a sensing point. Assuming that there are n sensing points defined along the optical fiber, the i-th sensing point is denoted as r i (i=1,2,...,n); the perforation position is recorded as s, and the first arrival time of the perforation direct wave from s to the i-th sensor point is t i ; Divide the n sensing points of the whole well section into m sections, and the number of sampling points in each section is floor(n / m), where floor() is a rounding operation; Then the DAS sensing points contained in the jth segment are recorded as: R j = {r n-(j-1)*floor(n / m) , r n-(j-1)*floor(n / m)-1 , ..., r n-j*floor(n / m)+1 }Wherein, floor() represents rounding towards negative infinity; The first arrival time of the perforation direct wave corresponding to the jth segment is Tj, and the specific formula is: T j ={t n-(j-1)*floor(n / m) ,t n-(j-1)*floor(n / m)-1 ,...,t n-j*floor(n / m)+1 }。 4. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 3 is characterized in that: The step 1 also includes: Given the initial velocity model of inversion V0 = {v0, h0}, v0 is the velocity, h0 is the depth of the velocity layer interface, the number of layers is l, and the velocity of the kth layer is The upper interface depth of the velocity layer is The initial velocity model is set to a uniform velocity model, that is, l=1.

5. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 4 is characterized in that: The step 1 further includes: Sets the threshold parameters used in subsequent inversions.

6. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 5 is characterized in that: The step 2 includes performing velocity inversion on the first segment, and the specific process is as follows: (1) Set the initial velocity model to V1 = V0; (2) Based on the velocity model V1, the theoretical first arrival time of the perforation direct wave from s to R1 is calculated by using the two-point ray tracing method as TT1; (3) Calculate the residual between the theoretical first arrival time TT1 and the actual first arrival time T1: residual1=RMS(TT1-T1) (4) If residual1 < threshold, set the velocity model V1 = {v1, h1}, where v1 = v0 and h1 = h0. The first-segment inversion ends, and the subsequent inversion process for the 2nd to floor(n / m) segments is entered; if residual j > threshold, go to step (5) to continue the velocity inversion; (5) Set the speed scanning range V of v1 min :deltaV:V max , where V min and V max are the minimum and maximum scanning speeds, respectively, deltaV is the speed scanning step size, and for each scanning speed, steps (2) and (3) are repeated. After the scanning is completed, the speed v corresponding to the minimum residual1 is selected as the inversion result, and v1=v is set; (6) Set V1 = {v1, h1}.

7. The velocity inversion method based on DAS acquisition of perforation signals in a well according to claim 6 is characterized in that: The step 2 also includes sequentially performing velocity model inversion on the 2nd to floor (n / m) segments, and the specific process is as follows: For the jth segment: (7) Set the initial velocity model to V j =V j-1 ; (8) Based on the velocity model V j , calculate the distance from s to R using the two-point ray tracing method j The theoretical first arrival time of the perforation direct wave is TT j ; (9) Calculate the theoretical first arrival time TT j The actual first arrival time T j The residual between: residual j =RMS(TT j -T j ) (10) If residual j < threshold, the current velocity model V j will not be modified, and return to step (7) to continue the inversion of the (j + 1)-th segment; if residual j > threshold, enter step (11) to continue the velocity inversion; (11) Increase the number of speed layers l = l + 1, let R j The first sensing point in n-(j-1)*floor(n / m) The depth is assigned to And order against Set the speed scanning range V min :deltaV:V max , where V min and V max are the minimum and maximum scanning speeds respectively, deltaV is the speed scanning step size, for each Repeat steps (8) and (9) at the scanning speed. After the scanning is completed, select the smallest residual j The corresponding speed v is The final value of After the velocity inversion calculations of the 1st to floor (n / m) segments are completed in sequence, the velocity inversion calculation based on the perforation signal collected by the DAS in the well is completed.

8. A velocity inversion system based on DAS acquisition of perforation signals in a well, characterized in that: include: Setting unit, used for model setting; The inversion unit is used to perform segmented velocity inversion from bottom to top.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps of the velocity inversion method based on DAS acquisition of perforation signals in a well as described in any one of claims 1 to 7.

10. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the velocity inversion method based on the DAS acquisition of perforation signals in the well as described in any one of claims 1 to 7.

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