CO2 time shift analysis method and system based on zero offset DAS-VSP data

Abstract

The invention relates to the technical field of oil exploration and development, and discloses a zero-offset DAS-VSP data acquisition method, which comprises the following steps: acquiring zero-offset DAS-VSP data in different periods, the zero-offset DAS-VSP data comprising basic data and monitoring data in different periods; respectively selecting data of a depth section with a data signal-to-noise ratio higher than a first threshold value from the basic data and the monitoring data as first intermediate data and second intermediate data; respectively separating the first intermediate data and the second intermediate data to obtain corresponding uplink reflection wave field data; first uplink reflected wave field first arrival time and second uplink reflected wave field first arrival time at different positions are picked up by using the uplink reflected wave field data of the basic data and the monitoring data respectively; correspondingly carrying out cross-correlation time difference calculation processing on the first arrival time of the first uplink reflected wave field at different positions and the first arrival time of the second uplink reflected wave field at different periods, and finally carrying out CO2 time shift analysis. The method can analyze and monitor the distribution and dynamic change of underground carbon dioxide.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum exploration and development, and in particular to a CO2 time-shift analysis method and system based on zero-bias DAS-VSP data. Background Art

[0002] In recent years, time-lapse seismic monitoring technology has developed rapidly, the country's requirements for low carbon, and green development have accelerated CO2 and promoted the development of CCS technology. The so-called "carbon capture" is to capture carbon dioxide released into the atmosphere, compress it, and seal it in depleted oil fields or other safe underground places. Vigorously developing a corresponding long-term and stable carbon dioxide geological storage monitoring system is an important application field for geophysics to open up new markets. With the help of the deep learning wave, the comprehensive use of multiple geophysical methods to monitor carbon dioxide geological storage projects is a future development trend.

[0003] Therefore, it is urgent to design a fast and simple CO2 time-shift analysis method. Summary of the invention

[0004] The present invention provides a CO2 time-shift analysis method and system based on zero-bias DAS-VSP data, so as to realize fast and simple CO2 time-shift analysis.

[0005] The present invention is achieved through the following technical solutions:

[0006] A CO2 time-shift analysis method based on zero-bias DAS-VSP data, comprising:

[0007] Collect zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected;

[0008] Selecting data of a depth segment having a data signal-to-noise ratio higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data respectively;

[0009] Separating the first intermediate data and the second intermediate data respectively to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data;

[0010] picking up upgoing reflection wavefield first arrival times at different positions from the first upgoing reflection wavefield data and the second upgoing reflection wavefield data respectively, setting the upgoing reflection wavefield first arrival time corresponding to the first upgoing reflection wavefield data as the first upgoing reflection wavefield first arrival time, and setting the upgoing reflection wavefield first arrival time corresponding to the second upgoing reflection wavefield data as the second upgoing reflection wavefield first arrival time;

[0011] The first arrival times of the first upgoing reflection wave field at different positions and the first arrival times of the second upgoing reflection wave field at different periods are processed by cross-correlation time difference, and finally the pre-stack time difference analysis results of different periods are obtained. The time shift analysis of CO2 is performed based on the pre-stack time difference analysis results of different periods.

[0012] As an optimization, when performing the direct wave first arrival picking operation from the basic data and the monitoring data, a depth segment with a data signal-to-noise ratio higher than a set first threshold is selected to pick the direct wave first arrival.

[0013] As an optimization, the specific process of separating the first intermediate data to obtain the first uplink reflection wavefield data is:

[0014] Performing deconvolution processing on the first intermediate data to eliminate the influence of multiple waves on upgoing wavefield analysis, thereby obtaining third intermediate data;

[0015] Wavefield separation is performed on the third intermediate data to remove the downlink wavefield data, thereby obtaining first uplink reflected wavefield data.

[0016] As an optimization, the specific process of separating and obtaining the second uplink reflection wavefield data from the second intermediate data is as follows:

[0017] performing deconvolution processing on the second intermediate data to eliminate the influence of multiple waves on upgoing wavefield analysis, thereby obtaining fourth intermediate data;

[0018] The fourth intermediate data is subjected to wavefield separation to remove the downlink wavefield data, thereby obtaining second uplink reflected wavefield data.

[0019] As an optimization, the first arrival times of the upgoing reflected wave fields at different positions are picked up, and the different positions include above the gas injection layer, the gas injection layer and below the gas injection layer.

[0020] As an optimization, the first threshold is 20 decibels.

[0021] As an optimization, after removing the downlink wavefield data, the waveform of the depth segment with a data signal-to-noise ratio higher than the second threshold is selected as the uplink reflection wavefield data.

[0022] As an optimization, the second threshold is 30 decibels.

[0023] As an optimization, the gas injection layer, the upper gas injection layer, and the lower gas injection layer are all located in a depth segment where the data signal-to-noise ratio is higher than a set first threshold.

[0024] As an optimization, the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods are cross-correlated and processed to obtain the time difference. The specific process of finally obtaining the pre-stack time difference analysis results at different periods is as follows:

[0025] A1. For the first arrival times of the second upgoing reflected wave field at different positions corresponding to the monitoring data of a certain period, the first arrival time of the first upgoing reflected wave field at the corresponding position and the first arrival time of the second upgoing reflected wave field are cross-correlated and processed to obtain the time difference analysis results of the different positions in the period;

[0026] A2. Change a monitoring period and repeat A1 until the number of monitoring periods required for analysis is reached.

[0027] The present invention also discloses a CO2 time-shift analysis system based on zero-bias DAS-VSP data, which is used to implement the aforementioned CO2 time-shift analysis method based on zero-bias DAS-VSP data, including:

[0028] An acquisition module, used for acquiring zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected;

[0029] A selection module, used to select data of a depth segment having a data signal-to-noise ratio higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data;

[0030] A separation module, used to separate the first intermediate data and the second intermediate data to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data;

[0031] an uplink reflection wavefield first arrival picking module, used to pick up uplink reflection wavefield first arrival times at different positions from the first uplink reflection wavefield data and the second uplink reflection wavefield data, and set the uplink reflection wavefield first arrival time corresponding to the first uplink reflection wavefield data as the first uplink reflection wavefield first arrival time, and set the uplink reflection wavefield first arrival time corresponding to the second uplink reflection wavefield data as the second uplink reflection wavefield first arrival time;

[0032] The analysis module is used to perform cross-correlation time difference processing on the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods, and finally obtain the pre-stack time difference analysis results of different periods, and perform time shift analysis of CO2 through the pre-stack time difference analysis results of different periods.

[0033] The present invention also discloses an electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a CO2 time-shift analysis method based on zero-bias DAS-VSP data as described above.

[0034] The present invention also discloses a storage medium storing a computer program, wherein when the computer program is executed by a processor, the method for analyzing CO2 time shift based on zero-bias DAS-VSP data is implemented.

[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0036] The present invention can perform pre-stack time difference analysis using the monitoring data of zero-bias DAS VSP at different periods, and evaluate whether the subsequent CO2 is effectively sealed as expected by monitoring the distribution and dynamic changes of underground carbon dioxide, which reflects the practicality of the method. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0038] Figure 1 The present invention is a process flow chart of the method described in the present invention.

[0039] Figure 2 This is a schematic diagram of the input vertical seismic profile zero-bias DAS VSP data collected at different times displayed in the loaded observation system. The horizontal axis is depth (unit: meter); the vertical axis is time (unit: milliseconds).

[0040] Figure 3 In order to select the data collected at different periods, the depth segment of 600-850m was selected. The data before and after deconvolution are shown in the figure. The horizontal axis is the depth (unit: meter) and the vertical axis is the time (unit: milliseconds).

[0041] Figure 4 The upgoing reflection wave field in the depth segment of 600-850m is selected for acquisition at different periods; the horizontal axis is depth (unit: meter) and the vertical axis is time (unit: millisecond).

[0042] Figure 5 This is the time difference analysis of zero deviation in different periods; the horizontal axis of the upper figure is time (unit: milliseconds), and the vertical axis of the upper figure is time (unit: meters); the horizontal axis of the lower figure is time (unit: milliseconds), and the vertical axis of the lower figure is time (unit: meters). DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0044] Generally, DAS-VSP is used for fine velocity and reservoir research near wells. It has the advantages of high resolution and facing the reservoir. In recent years, many time-lapse monitoring projects have been implemented at home and abroad. For time-lapse VSP, it is a seismic exploration technology that monitors the changes of underground geological structure or fluid properties over time by repeatedly performing VSP measurements at different time points.

[0045] Therefore, the present invention designs a CO2 time-shift analysis method, which performs time-shift analysis on CO2 through the DAS-VSP data gap before and after CO2 injection. The method picks up the direct wave first arrival from the zero-bias DAS-VSP data, uses median filtering to separate the reflected wave field, obtains the upgoing reflected wave field, picks up the first arrival of the reflected wave at different depths, and then performs multi-period time-difference time-shift analysis, thereby realizing CO2 monitoring time-shift analysis from the upgoing and downgoing wave field time difference results in the multi-period zero-bias DAS-VSP data.

[0046] Next, the method of the present invention is described in detail.

[0047] This embodiment 1 provides a CO2 time-shift analysis method based on zero-bias DAS-VSP data, such as Figure 1 As shown, including:

[0048] S1. Collect zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected;

[0049] Input the DASVSP data (including basic data Basedata and monitoring data Monitordata) collected at different zero bias periods into the loading observation system, where the basic data Basedata and monitoring data Monitordata are recorded as data DATA_B and DATA_M respectively.

[0050] S2. Selecting data of a depth segment whose data signal-to-noise ratio is higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data; the first intermediate data is marked as DATA_B ′ , the second intermediate data is marked as

[0051] DATA_M′.

[0052] In this embodiment, data of a depth segment whose data signal-to-noise ratio is higher than a first threshold value is selected from the basic data and the monitoring data as the first intermediate data and the second intermediate data. In this embodiment, the first threshold value is 20 decibels.

[0053] For example, if the depth segment is 600 to 800 m and the data signal-to-noise ratio is higher than 20 decibels, then this depth segment is selected.

[0054] S3, separating the first intermediate data and the second intermediate data respectively to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data;

[0055] In this embodiment, the specific process of separating the first intermediate data to obtain the first uplink reflected wavefield data is:

[0056] Performing deconvolution processing on the first intermediate data to eliminate the influence of multiple waves on the first upgoing wave field analysis, thereby obtaining third intermediate data;

[0057] 1) Use the data DATA_B selected in step S2 ′ Deconvolution processing is performed to eliminate the influence of multiple waves on the upgoing wavefield analysis.

[0058] DATA1_B=Decon(DATA_B′);

[0059] Wherein, Decon is to perform deconvolution processing on the data to obtain the deconvolution data, and DATA1_B represents the third intermediate data.

[0060] Wavefield separation is performed on the third intermediate data to remove the downlink wavefield data, thereby obtaining first uplink reflected wavefield data.

[0061] Using the deconvolved data in step 1), it is necessary to perform wave field separation on the deconvolved data, remove the downlink wave field, obtain the uplink reflection wave field data, and intercept the depth segment with high data signal-to-noise ratio and relatively stable waveform.

[0062] DATA2_B=Median(DATA1_B)

[0063] Among them, Median performs wave field separation on the data to obtain uplink reflection wave field data, and DATA2_B is the first uplink reflection wave field data.

[0064] In this embodiment, the specific process of separating and obtaining the second uplink reflected wavefield data from the second intermediate data is as follows:

[0065] performing deconvolution processing on the second intermediate data to eliminate the influence of multiple waves on upgoing wavefield analysis, thereby obtaining fourth intermediate data;

[0066] 2) Use the data DATA_M selected in step S2 ′ Deconvolution processing is performed to eliminate the influence of multiple waves on the upgoing wavefield analysis.

[0067] DATA1_M=Decon(DATA_M′)

[0068] Wherein, Decon is to perform deconvolution processing on the data to obtain the deconvolution data, and DATA1_M represents the fourth intermediate data.

[0069] The fourth intermediate data is subjected to wavefield separation to remove the downlink wavefield data, thereby obtaining second uplink reflected wavefield data.

[0070] Using the deconvolved data in step 2), it is necessary to perform wavefield separation on the deconvolved data to remove the downlink wavefield and obtain the uplink reflection wavefield data.

[0071] DATA2_M=Median(DATA1_M)

[0072] Among them, Median performs wave field separation on the data to obtain uplink reflection wave field data, and DATA2_M is the second uplink reflection wave field data.

[0073] S4, picking up uplink reflection wavefield first arrival times at different positions from the first uplink reflection wavefield data and the second uplink reflection wavefield data respectively, setting the uplink reflection wavefield first arrival time corresponding to the first uplink reflection wavefield data as the first uplink reflection wavefield first arrival time, and setting the uplink reflection wavefield first arrival time corresponding to the second uplink reflection wavefield data as the second uplink reflection wavefield first arrival time;

[0074] In this embodiment, the first arrival times of the upgoing reflected wave fields at different positions are picked up, and the different positions include above the gas injection layer, the gas injection layer, and below the gas injection layer.

[0075] The injection layer is where the carbon dioxide is injected, and it has an accurate depth location.

[0076] Specifically, the first arrival time of the upward reflection wavefield on the gas injection layer of the basic data is defined as FB1_B, the first arrival time of the upward reflection wavefield on the gas injection layer is defined as FB2_B, and the first arrival time of the upward reflection wavefield below the gas injection layer is defined as FB3_B. Similarly, the first arrival time of the upward reflection wavefield on the gas injection layer of the monitoring data is defined as FB1_M, the first arrival time of the upward reflection wavefield on the gas injection layer is defined as FB2_M, and the first arrival time of the upward reflection wavefield below the gas injection layer is defined as FB3_M.

[0077] DATA2 data (DATA2_B, DATA2_M) is used to pick the first arrival of the reflection wave field at different positions and save them in the data headers at different positions. The positions of reflection wave picking can be divided into above the gas injection layer, the gas injection layer and below the gas injection layer, respectively recorded as FB1 (FB1_B, FB1_M), FB2 (FB2_B, FB2_M), FB3 (FB3_B, FB3_M).

[0078] S5. Perform cross-correlation time difference processing on the first arrival times of the first upgoing reflection wave field at different positions and the first arrival times of the second upgoing reflection wave field at different periods, and finally obtain pre-stack time difference analysis results of different periods, and perform time shift analysis of CO2 based on the pre-stack time difference analysis results of different periods.

[0079] The specific process of performing cross-correlation time difference processing on the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods, and finally obtaining the pre-stack time difference analysis results at different periods is as follows:

[0080] A1. For the first arrival times of the second upgoing reflected wave field at different positions corresponding to the monitoring data of a certain period, the first arrival time of the first upgoing reflected wave field at the corresponding position and the first arrival time of the second upgoing reflected wave field are cross-correlated and processed to obtain the time difference analysis results of the different positions in the period;

[0081] A2. Change a monitoring period and repeat A1 until the number of monitoring periods required for analysis is reached.

[0082] Since the injection speed of CO2 into the formation will change, the arrival time of the reflected wave field of the data collected at different times will be different. This difference is used to determine the time difference caused by CO2 injection, and the size of the time difference is used to determine whether CO2 is sealed in the formation.

[0083] The size of the time difference can determine whether there is a risk of leakage in the analysis of the injected CO2. Since CO2 injection will affect the velocity of the formation, the velocity will affect the arrival time of the reflected wave of each data acquisition. By analyzing the time difference, it can be determined that the CO2 injection has an impact on the data. If CO2 is not within this range (if the two time differences are equal or unchanged, it means that CO2 has not been injected into the formation), there will be no difference in wave field time difference.

[0084] For example, for the first arrival time of the second upgoing reflection wave field of the first monitoring data, the time difference analysis results at different positions (above the gas injection layer, the gas injection layer, and below the gas injection layer) can be obtained, as follows:

[0085] Time1=Corrlate(FB1_B,FB1_M);

[0086] Time2=Corrlate(FB2_B,FB2_M);

[0087] Time3=Corrlate(FB3_B,FB3_M);

[0088] Time1, Time2, and Time3 are the time difference analysis results of the first monitoring data and the basic data above the gas injection layer, the gas injection layer, and below the gas injection layer, respectively, that is, the time difference analysis results of three different depth sections.

[0089] Since the observation data of different periods are collected, the time difference analysis results of the gas injection layer, the gas injection layer and the gas injection layer at different periods can be obtained, that is, Time1, Time2, Time3 at different periods, so as to obtain the pre-stack time difference analysis results of multi-period data.

[0090] Next, the present invention is described through specific implementation examples.

[0091] 1) Input the DAS-VSP zero bias data DATA monitored at different times for multiple periods, and load the observation system as follows Figure 2 .

[0092] 2) Use the data (DATA_B) from step 1) to pick the first arrival of the direct wave of the data, save the picking result in the data header, and select the depth segment with high data signal-to-noise ratio to pick the first arrival of the direct wave and record it as FB_B.

[0093] 3)DATA1_B=Decon(DATA_B ′ ),

[0094] Among them, Decon is to perform deconvolution processing on the data to obtain the deconvoluted data and eliminate the influence of multiple waves on the time difference analysis.

[0095] 4) DATA2_B = Median(DATA1_B)

[0096] Among them, Median performs wave field separation on the data to obtain the upgoing reflection wave field, obtains the upgoing reflection wave field data, performs the first arrival picking of the upgoing reflection wave field and intercepts the depth segment with high data signal-to-noise ratio and relatively stable waveform, such as Figure 3 .

[0097] 5) Use the DATA2_B data in step 4) to pick up the first arrival of the reflection wave field at different positions and save them to the data headers at different positions. The positions of reflection wave picking can be divided into the upper gas injection layer, the gas injection layer and the lower gas injection layer, which are respectively recorded as FB1_B, FB2_B and FB3_B. Figure 4 , Figure 4 Where FB_B is the first arrival time of the direct wave.

[0098] 6) Use the first arrival of the reflected wave to calculate the time difference of the data in different periods, repeat the above steps 1-5 to calculate the time difference of the monitoring data, and then analyze the time shift and time difference of the monitoring data and the basic data. Figure 5 It can be obtained that the influence of the time difference on the data of different periods is further expanded due to the continuous increase of CO2 injection volume. Through two different time difference analyses, it can be concluded that the influence of the time difference on the time difference is further expanded due to the continuous increase of CO2 injection volume, indicating that there is no risk of leakage in CO2 injection.

[0099] In summary, the present invention provides a method for analyzing time-lapse earthquakes, which can monitor the changes caused by CO2 injection through earthquakes, and provide a scientific basis for the safe monitoring and operation of CO2 injection underground.

[0100] Example 2 also discloses a CO2 time-shift analysis system based on zero-bias DAS-VSP data, which is used to execute the method of Example 1, including:

[0101] An acquisition module, used for acquiring zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected;

[0102] A selection module, used to select data of a depth segment having a data signal-to-noise ratio higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data;

[0103] A separation module, used to separate the first intermediate data and the second intermediate data to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data;

[0104] an uplink reflection wavefield first arrival picking module, used to pick up uplink reflection wavefield first arrival times at different positions from the first uplink reflection wavefield data and the second uplink reflection wavefield data, and set the uplink reflection wavefield first arrival time corresponding to the first uplink reflection wavefield data as the first uplink reflection wavefield first arrival time, and set the uplink reflection wavefield first arrival time corresponding to the second uplink reflection wavefield data as the second uplink reflection wavefield first arrival time;

[0105] The analysis module is used to perform cross-correlation time difference processing on the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods, and finally obtain the pre-stack time difference analysis results of different periods, and perform time shift analysis of CO2 through the pre-stack time difference analysis results of different periods.

[0106] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A CO2 time-shift analysis method based on zero-bias DAS-VSP data, characterized in that: include: Collect zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected; Selecting data of a depth segment having a data signal-to-noise ratio higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data respectively; Separating the first intermediate data and the second intermediate data respectively to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data; picking up upgoing reflection wavefield first arrival times at different positions from the first upgoing reflection wavefield data and the second upgoing reflection wavefield data respectively, setting the upgoing reflection wavefield first arrival time corresponding to the first upgoing reflection wavefield data as the first upgoing reflection wavefield first arrival time, and setting the upgoing reflection wavefield first arrival time corresponding to the second upgoing reflection wavefield data as the second upgoing reflection wavefield first arrival time; The first arrival times of the first upgoing reflection wave field at different positions and the first arrival times of the second upgoing reflection wave field at different periods are processed by cross-correlation time difference, and finally the pre-stack time difference analysis results of different periods are obtained. The time shift analysis of CO2 is performed based on the pre-stack time difference analysis results of different periods.

2. A CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1, characterized in that: The specific process of separating the first intermediate data to obtain the first uplink reflected wavefield data is as follows: Performing deconvolution processing on the first intermediate data to eliminate the influence of multiple waves on upgoing wavefield analysis, thereby obtaining third intermediate data; Wavefield separation is performed on the third intermediate data to remove the downlink wavefield data, thereby obtaining first uplink reflected wavefield data.

3. The CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1 is characterized in that: The specific process of separating and obtaining the second uplink reflected wavefield data from the second intermediate data is as follows: performing deconvolution processing on the second intermediate data to eliminate the influence of multiple waves on upgoing wavefield analysis, thereby obtaining fourth intermediate data; The fourth intermediate data is subjected to wavefield separation to remove the downlink wavefield data, thereby obtaining second uplink reflected wavefield data.

4. The CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1 is characterized in that: The first arrival times of the upgoing reflected wave fields at different positions are picked up, and the different positions include above the gas injection layer, the gas injection layer and below the gas injection layer.

5. The CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1, characterized in that: The first threshold is 20 decibels.

6. The CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1, characterized in that: The gas injection layer, the upper gas injection layer, and the lower gas injection layer are all located in a depth section where the data signal-to-noise ratio is higher than a set first threshold.

7. The CO2 time-shift analysis method based on zero-bias DAS-VSP data according to claim 1, characterized in that: The specific process of performing cross-correlation time difference processing on the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods, and finally obtaining the pre-stack time difference analysis results at different periods is as follows: A1. For the first arrival times of the second upgoing reflected wave field at different positions corresponding to the monitoring data of a certain period, the first arrival time of the first upgoing reflected wave field at the corresponding position and the first arrival time of the second upgoing reflected wave field are cross-correlated and processed to obtain the time difference analysis results of the different positions in the period; A2. Change a monitoring period and repeat A1 until the number of monitoring periods required for analysis is reached.

8. A CO2 time-shift analysis system based on zero-bias DAS-VSP data, used to implement a CO2 time-shift analysis method based on zero-bias DAS-VSP data according to any one of claims 1 to 7, characterized in that: include: An acquisition module, used for acquiring zero-bias DAS-VSP data of different periods, wherein the zero-bias DAS-VSP data includes basic data and monitoring data of different periods, wherein the basic data includes VSP data detected when CO2 is not injected, and the monitoring data includes VSP data after CO2 is injected; A selection module, used to select data of a depth segment having a data signal-to-noise ratio higher than a first threshold from the basic data and the monitoring data as first intermediate data and second intermediate data; A separation module, used to separate the first intermediate data and the second intermediate data to obtain corresponding first uplink reflection wavefield data and second uplink reflection wavefield data; an uplink reflection wavefield first arrival picking module, used to pick up uplink reflection wavefield first arrival times at different positions from the first uplink reflection wavefield data and the second uplink reflection wavefield data, and set the uplink reflection wavefield first arrival time corresponding to the first uplink reflection wavefield data as the first uplink reflection wavefield first arrival time, and set the uplink reflection wavefield first arrival time corresponding to the second uplink reflection wavefield data as the second uplink reflection wavefield first arrival time; The analysis module is used to perform cross-correlation time difference processing on the first arrival time of the first upgoing reflection wave field at different positions and the first arrival time of the second upgoing reflection wave field at different periods, and finally obtain the pre-stack time difference analysis results of different periods, and perform time shift analysis of CO2 through the pre-stack time difference analysis results of different periods.

9. An electronic device, characterized in that: The invention comprises at least one processor and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform a CO2 time-shift analysis method based on zero-bias DAS-VSP data according to any one of claims 1 to 7.

10. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a CO2 time-shift analysis method based on zero-bias DAS-VSP data according to any one of claims 1 to 7 is implemented.

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