Node continuous recording data-based inversion channel detection method, device and equipment

Abstract

The invention discloses an inversion channel detection method, device and equipment based on node continuous recording data, and belongs to the field of petroleum geophysical exploration. According to the method, by utilizing the characteristic that the continuous recorded data of the nodes in the adjacent areas are similar, the inversion channel condition in the continuous recorded data of the nodes is detected through a phase difference method; the invention further provides a device for implementing the method and computer equipment. According to the method, the detection time is shortened, the manual workload is reduced, and the blank of inversion channel detection of node continuous recording data is filled. The method can be applied to the seismic data processing technology.

Description

Technical Field

[0001] The present invention belongs to the field of petroleum geophysical exploration, relates to a seismic data processing technology, and specifically relates to a reverse trace detection method, device and equipment based on continuously recorded node data. Background Art

[0002] In the seismic exploration acquisition link, due to the situation of reverse connection of the positive and negative poles of the wiring inside the acquisition equipment, the reverse trace phenomenon often occurs, resulting in phase reversal, and the sine wave of the data is inverted into a cosine wave, which has a certain impact on data processing. Therefore, it is crucial to detect reverse traces in the data. The prior art often uses shot gathers or trace gathers for reverse trace detection. During the seismic exploration acquisition process, wired instrument acquisition equipment can generate shot gathers or trace gathers in real time to detect reverse traces in the data; while node instrument acquisition equipment cannot transmit the acquired seismic data in real time, and it takes a very long time to convert the time-series data generated by node instruments into shot gathers or trace gathers. Therefore, node instruments cannot detect reverse traces in time through shot gathers or trace gathers like wired instruments.

[0003] In recent years, with the development of the "two-width and one-high" technology and the complication of the surface types of exploration work areas, node instruments have been widely used. Node instruments have the characteristic of quickly converting time-series data into continuously recorded data. At present, there is no method in the industry that can directly detect reverse traces in the continuously recorded data of node instruments. Therefore, it is urgent to develop a method for detecting reverse traces using the continuously recorded data converted by node instruments to shorten the detection time and reduce the manual workload. Summary of the Invention

[0004] To solve the above-mentioned deficiencies in the prior art, one object of the present invention is to provide a reverse trace detection method, device and equipment based on continuously recorded node data, so as to achieve the purpose of detecting reverse traces using continuously recorded node data based on the phase difference method;

[0005] Another object of the present invention is to provide a device and a computer device for running the above method.

[0006] To achieve the above object, the technical solutions adopted by the present invention are as follows:

[0007] A reverse trace detection method based on continuously recorded node data is to perform cross-correlation operation on the continuously recorded data volume generated by node data, then perform fast Fourier transform, calculate the phase difference between subsets of the continuously recorded data volume to be checked, and determine whether the signals of the subsets of the continuously recorded data volume to be checked are reversed. If reversed, further detect whether the trace where the continuously recorded data volume to be checked is located is a reverse trace.

[0008] Further, it includes the following steps carried out in sequence:

[0009] S1. Data processing

[0010] Generate a continuous record data body to be searched for the node data received by the node instrument, defined as dx. According to the position information in the data body header, calculate the 2 data bodies adjacent to the left and right of dx respectively, and form an operation data set of the continuous record data body dx, defined as Dc = [dx-2, dx-1, dx, dx+1, dx+2];

[0011] According to the shot point information file, select m shot points adjacent to the side far from dx for each of the data bodies dx-2 and dx+2. For each shot point, intercept Dc through the excitation time and recording length of the shot point to form a subset of the continuous record data body, defined as Dcn = [dxn-2, dxn-1, dxn, dxn+1, dxn+2],

[0012] where dxn is a subset of the continuous record data body to be searched, and the others are 2 subsets of the continuous record data body adjacent to the left and right of dxn;

[0013] S2. Cross-correlation operation

[0014] Perform a cross-correlation operation on Dcn to obtain a set of subsets of the continuous record data body after cross-correlation, defined as Dr = [drn-2, drn-1, drn, drn+1, drn+2];

[0015] S3. Phase difference calculation

[0016] After performing a fast Fourier transform on Dr, calculate the phase differences between the subset drn of the continuous record data body to be searched and the other 4 subsets of the continuous record data body respectively, expressed in angular value θ, and the calculation formula is as follows:

[0017] θ = arctan(Im(drn(f) / Re(drn(f)))-arctan(Im(X(f)) / Re(X(f)))

[0018] In the formula: Im and Re are the imaginary part and real part respectively after performing a fast Fourier transform on Dr, drn(f) is the frequency domain representation of the subset drn of the continuous record data body to be searched, and X(f) is the frequency domain representation of the other subsets of the continuous record data body;

[0019] S4. Reverse trace detection

[0020] Judge whether the signal of the subset dxn of the continuous record data body to be searched is reversed according to the phase difference. If it is reversed, further detect whether the trace where the continuous record data body dx to be searched is located is a reverse trace.

[0021] Further, the determination of whether the signal of the subset dxn of the to-be-checked continuous recorded data body in step S4 is reversed is made according to the angular value θ of the phase difference. If there is any angular value θ greater than 90 degrees, the signal of the subset dxn of the to-be-checked continuous recorded data body is reversed; if all angular values θ are less than 90 degrees, the signal of the subset dxn of the to-be-checked continuous recorded data body is not reversed.

[0022] Further, the detection of whether the trace where the to-be-checked continuous recorded data body dx is located is a reversed trace in step S4 is to separately determine the reversals of 2m subsets dxn of the to-be-checked continuous recorded data bodies corresponding to 2m selected shot points. If the number of subsets dxn of the to-be-checked continuous recorded data bodies that are reversed is greater than m + 1, the trace where the to-be-checked continuous recorded data body dx is located is a reversed trace; otherwise, it is a non-reversed trace.

[0023] The present invention also provides a reversed trace detection device based on node continuous recorded data, which is characterized by including:

[0024] A data processing unit: used to define the to-be-checked continuous recorded data body and the subset of the to-be-checked continuous recorded data body;

[0025] A cross-correlation operation unit: used to perform cross-correlation operations on the subsets of the continuous recorded data body;

[0026] A phase difference calculation unit: used to calculate the phase difference between subsets of the continuous recorded data body;

[0027] A reversed trace detection unit: used to detect whether the trace where the to-be-checked continuous recorded data body is located is a reversed trace.

[0028] The present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the reversed trace detection method based on node continuous recorded data described in any one of the above is implemented.

[0029] Due to the adoption of the above technical solution, compared with the prior art, the beneficial effects obtained by the present invention are:

[0030] (1) The reversed trace detection method, device, and equipment based on node continuous recorded data provided by the present invention utilize the characteristic that the continuous recorded data between nodes in adjacent regions have similarity, and detect the reversed trace situation in the node continuous recorded data through the phase difference method, thereby shortening the detection time, reducing the manual workload, and filling the blank of the reversed trace detection of node continuous recorded data;

[0031] (2) The reverse trace detection method, device, and equipment based on continuous node data recording provided by the present invention can timely detect the polarity problem of nodes during the construction process, help the field geophysical exploration team to perform rapid data detection, timely discover the problems existing in the collected data, and ensure the quality of node acquisition data and construction efficiency.

[0032] (3) The device and computer equipment provided by the present invention can quickly and effectively detect reverse traces. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0034] Figure 1 It is a schematic diagram of the selection of each parameter in Embodiment 1, where 1, all nodes; 2, shot point; 3, node to be checked; 4, two data bodies adjacent to the left and right of the node to be checked; 5, all nodes recovered by the node instrument.

[0035] Figure 2 It is a schematic diagram of intercepting the continuous node data body in Embodiment 1;

[0036] Figure 3 It is a schematic diagram of a normal trace in Embodiment 1;

[0037] Figure 4 It is a schematic diagram of a reverse trace in Embodiment 1;

[0038] Figure 5 It is a flowchart of the reverse trace detection device based on continuous node data recording in Embodiment 2, where 1, data processing unit; 2, cross-correlation operation unit; 3, phase difference calculation unit; 4, reverse trace detection unit. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The present invention will be further described in detail below through specific embodiments. It should be understood that the preferred embodiments described herein are only used to illustrate and understand the present invention, and are not used to limit the present invention.

[0040] Embodiment 1 A Reverse Trace Detection Method Based on Continuous Node Data Recording

[0041] This embodiment is a reverse trace detection method based on continuous node data recording, including the following steps carried out in sequence:

[0042] S1. Data processing

[0043] Load the node data of a detection line, a total of 527 nodes. Generate a continuous record data body for each node data, and the data format is segy. Define the set of continuous record data bodies generated from the 527 node data received by the node instrument as D = [d1, d2,..., dn]. Select a dx in D and define it as the continuous record data body to be searched. The node stake number is (2250, 1978). According to the position information in the data body trace header, calculate the 2 data bodies adjacent to the left and right of dx respectively, and form the operation data set of the continuous record data body dx, which is defined as Dc = [dx - 2, dx - 1, dx, dx + 1, dx + 2]; The start time of the data is recorded in the trace header, the data record length is 32.95 hours, and the sampling is 4 milliseconds. Therefore, Dc contains a total of 5 data, and each data includes 29,655,000 sample point values in digital form;

[0044] According to the shot point information file, select 5 shot points adjacent to the side far from dx for each of the data bodies dx - 2 and dx + 2. For each shot point, intercept Dc according to the firing time and record length of the shot point to form a subset of the continuous record data body, which is defined as Dcn = [dxn - 2, dxn - 1, dxn, dxn + 1, dxn + 2],

[0045] where dxn is the subset of the continuous record data body to be searched, and the others are the 2 subsets of the continuous record data bodies adjacent to the left and right of dxn respectively;

[0046] Randomly select a firing time. According to the start time in the trace header, find the position of the firing time in the data. The construction uses a 9 - second scanning length and a 7 - second record length. Therefore, it is necessary to intercept 15 - second - long data starting from the firing time, that is, intercept 3750 sample point values starting from the firing time, and finally generate 5 data, each data including 3750 sample point values in digital form;

[0047] The selection of each parameter is as Figure 1 shown, Figure 1 In the figure, black dot 1 represents all the nodes deployed in the field, and the 5 black dots in the box are the 527 nodes received by the node instrument. Select any node 3 to be searched and define it as the continuous record data body to be searched. According to the position information in the data body trace header, calculate the 2 data bodies adjacent to the left and right of the node to be searched, which are shown as the 4 nearest black dots 4 to 3 in the figure. According to the shot point information file, select 5 shot points adjacent to the side far from dx for each of the data bodies dx - 2 and dx + 2, as shown by 2 in the figure;

[0048] Generate a continuous record data body for each recovered node, as Figure 2 shown, Figure 2A scatter plot is drawn for the continuous recorded data body generated for a node. The excitation time of the shot point closest to the node to be searched is selected. The excitation time is an instantaneous moment, representing a time point. Starting from the excitation time, the recording length is intercepted to form a subset of the operation set.

[0049] S2. Cross-correlation operation

[0050] Perform cross-correlation operation on Dcn using the scanning signal to obtain the set of subsets of the continuous recorded data body after cross-correlation, defined as Dr = [drn-2, drn-1, drn, drn+1, drn+2];

[0051] The length of the scanning signal is 9 seconds. After cross-correlation operation, within 5 data, the length of each data becomes 1750 sample point values.

[0052] S3. Phase difference calculation

[0053] After performing the fast Fourier transform on Dr, calculate the phase differences between the subset drn of the continuous recorded data body to be searched and the other 4 subsets of the continuous recorded data body respectively, represented by the angular value θ. The calculation formula is as follows:

[0054] θ = arctan(Im(drn(f) / Re(drn(f)))-arctan(Im(X(f)) / Re(X(f))

[0055] In the formula: Im and Re are the imaginary part and real part respectively after performing the fast Fourier transform on Dr. drn(f) is the frequency domain representation of the subset drn of the continuous recorded data body to be searched, and X(f) is the frequency domain representation of the other subsets of the continuous recorded data body;

[0056] S4. Reverse trace detection

[0057] Judge whether the subset dxn of the continuous recorded data body to be searched has reversed according to the phase difference, and then detect whether the trace where the continuous recorded data body dx to be searched is located is a reverse trace;

[0058] Perform reverse detection on the 10 subsets dxn of the continuous recorded data body to be searched corresponding to the 10 selected shot points respectively. Among them, there are 7 subsets dxn of the continuous recorded data body to be searched where the angular value θ is greater than 90 degrees. Then the trace where the continuous recorded data body dx to be searched is located is a reverse trace.

[0059] It can also be seen from the schematic diagram of the data after cross-correlation that the data reversal situation of the node to be searched is as Figure 3 and Figure 4 shown. The third data in the figure is the data of the node to be searched. Figure 3 It is a schematic diagram of a normal trace. It can be seen from the figure that the data extrema are almost in the same position; Figure 4It is a schematic diagram of an inverted track. As can be seen from the figure, near the extreme values of other nodes, the node to be checked shows a negative extreme value, that is, the phase difference is more than 90 degrees.

[0060] Perform the above operations on the remaining 526 nodes respectively to obtain the corresponding inverted track conditions.

[0061] Embodiment 2 An inverted track detection device based on continuously recorded data of nodes

[0062] Figure 5 The flowchart of an inverted track detection device based on continuously recorded data of nodes according to an embodiment of the present invention is shown, including:

[0063] Data processing unit 1: used to define the continuously recorded data body to be checked and the subset of the continuously recorded data body to be checked;

[0064] Cross-correlation operation unit 2: used to perform cross-correlation operations on the subset of the continuously recorded data body;

[0065] Phase difference calculation unit 3: used to calculate the phase difference between subsets of the continuously recorded data body;

[0066] Inverted track detection unit 4: used to detect whether the track where the continuously recorded data body to be checked is located is an inverted track.

[0067] Embodiment 3 A computer device

[0068] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor to implement the above-mentioned inverted track detection method based on continuously recorded data of nodes.

[0069] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0070] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is used to run the computer-readable instructions stored in the memory.

[0071] Those skilled in the art should be able to understand that, in order to solve the technical problem of how to obtain good user experience effects, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included in the protection scope of this disclosure.

[0072] For the detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details are not repeated here.

[0073] It should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or perform equivalent replacements on some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An inverted trace detection method based on continuously recording data at nodes, characterized in that, after performing cross-correlation operation on the continuously recorded data body generated from node data, perform fast Fourier transform, calculate the phase difference between subsets of the continuously recorded data body to be searched, and determine whether the signal of the subset of the continuously recorded data body to be searched is inverted. If it is inverted, further detect whether the trace where the continuously recorded data body to be searched is located is an inverted trace.

2. The inverted trace detection method based on continuously recording data at nodes according to claim 1, characterized in that, comprises the following steps carried out in sequence: S1. Data processing Generate a continuously recorded data body to be searched from the node data received by the node instrument, defined as dx. According to the position information in the trace header of the data body, calculate the 2 data bodies adjacent to the left and right of dx respectively, and form an operation data set of the continuously recorded data body dx, defined as Dc = [dx - 2, dx - 1, dx, dx + 1, dx + 2]; According to the shot point information file, select m shot points adjacent to the sides far from dx of the data bodies dx - 2 and dx + 2 respectively. For each shot point, intercept Dc through the excitation time and recording length of the shot point to form a subset of the continuously recorded data body, defined as Dcn = [dxn - 2, dxn - 1, dxn, dxn + 1, dxn + 2], wherein, dxn is the subset of the continuously recorded data body to be searched, and the others are 2 subsets of the continuously recorded data bodies adjacent to the left and right of dxn; S2. Cross-correlation operation Perform cross-correlation operation on Dcn to obtain a set of subsets of the continuously recorded data body after cross-correlation, defined as Dr = [drn - 2, drn - 1, drn, drn + 1, drn + 2]; S3. Phase difference calculation After performing fast Fourier transform on Dr, calculate the phase difference between the subset drn of the continuously recorded data body to be searched and the other 4 subsets of the continuously recorded data bodies respectively, represented by the angle value θ. The calculation formula is as follows: θ = arctan(Im(drn(f) / Re(drn(f)))-arctan(Im(X(f)) / Re(X(f)) In the formula: Im and Re are respectively the imaginary part and the real part after performing fast Fourier transform on Dr, drn(f) is the frequency domain representation of the subset drn of the continuously recorded data body to be searched, and X(f) is the frequency domain representation of the other subsets of the continuously recorded data bodies; S4. Inverted trace detection Judge whether the signal of the subset dxn of the continuously recorded data body to be searched is inverted according to the phase difference. If it is inverted, further detect whether the trace where the continuously recorded data body dx to be searched is located is an inverted trace.

3. The inverted trace detection method based on continuously recording data at nodes according to claim 2, characterized in that, the judgment of whether the signal of the subset dxn of the continuously recorded data body to be searched in step S4 is inverted is made according to the angle value θ of the phase difference. If there is any angle value θ greater than 90 degrees, the signal of the subset dxn of the continuously recorded data body to be searched is inverted; if all the angle values θ are less than 90 degrees, the signal of the subset dxn of the continuously recorded data body to be searched is not inverted.

4. The reverse track detection method based on continuously recording data of nodes according to claim 3, characterized in that, for the detection of whether the track where the to-be-checked continuously recorded data body dx in step S4 is a reverse track, it is to respectively judge the reversals of 2m subsets dxn of the to-be-checked continuously recorded data bodies corresponding to 2m shot points selected. If the number of subsets dxn of the to-be-checked continuously recorded data bodies that undergo reversal is greater than m + 1, then the track where the to-be-checked continuously recorded data body dx is located is a reverse track; otherwise, it is a non-reverse track.

5. A reverse track detection device based on continuously recording data of nodes according to any one of claims 1 to 4, characterized in that, comprising: A data processing unit: used to define the to-be-checked continuously recorded data body and the subsets of the to-be-checked continuously recorded data bodies; A cross-correlation operation unit: used to perform cross-correlation operations on the subsets of the continuously recorded data bodies; A phase difference calculation unit: used to calculate the phase differences between the subsets of the continuously recorded data bodies; A reverse track detection unit: used to detect whether the track where the to-be-checked continuously recorded data body is located is a reverse track.

6. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the reverse track detection method based on continuously recording data of nodes according to any one of claims 1 to 4.

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