Reverse time migration imaging method, device and computer equipment

Abstract

The present application discloses a reverse time migration imaging method, apparatus, and computer equipment, belonging to the field of seismic exploration technology. An embodiment of the present application provides a reverse time migration imaging method, which generates seismic waves based on source signal excitation within a preset frequency range, collects seismic data corresponding to the seismic waves, and determines the effective frequency range for imaging the seismic data at different depths based on a first pre-stack depth migration image of the seismic data. Because invalid frequency ranges are removed from the preset frequency range, reverse time migration processing is performed on the seismic data based on the effective frequency range, saving time required for reverse time migration processing of the seismic data through the invalid frequency range, thereby improving the processing efficiency of the seismic data.

Description

Technical Field

[0001] The present application relates to the field of seismic exploration technology, and in particular to a reverse time migration imaging method, device, and computer equipment. Background Art

[0002] In the field of seismic exploration, collected seismic data is processed to generate seismic images, from which the subsurface structure can be determined, facilitating well location exploration in the seismic area where the data was collected. Reverse time migration is a widely used imaging method.

[0003] In the related art, seismic waves are first excited by a source signal in a preset frequency range, and then seismic data is collected. The seismic data is reverse-time migrated based on the preset frequency range to obtain a reverse-time migrated image, also known as a seismic image.

[0004] However, the source signal attenuates as it penetrates deeper into the ground. Consequently, some frequencies may weaken or even disappear from the collected seismic data, narrowing the frequency range of the acquired seismic data. In this case, processing the seismic data within the pre-set frequency range increases processing time and results in low processing efficiency. Summary of the Invention

[0005] The present invention provides a reverse time migration imaging method, apparatus, and computer equipment to improve the processing efficiency of seismic data. The specific technical solution is as follows:

[0006] In one aspect, an embodiment of the present application provides a reverse time migration imaging method, the method comprising:

[0007] Acquire first seismic data, where the first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range;

[0008] performing prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image;

[0009] determining, based on the first pre-stack depth migration image, an effective frequency range for imaging the first seismic data at different depths;

[0010] Dividing the effective frequency range into a first number of sub-frequency ranges along the depth direction, where the first number is greater than 1 and does not exceed a preset number threshold;

[0011] Based on the preset frequency range and each sub-frequency range, performing reverse time migration processing on the first seismic data respectively to obtain a first number of reverse time migration sub-images;

[0012] The first number of reverse time migrated sub-images are fused to obtain a reverse time migrated image.

[0013] In a possible implementation, performing reverse time migration processing on the first seismic data based on the preset frequency range and each sub-frequency range to obtain a first number of reverse time migrated sub-images includes:

[0014] For each sub-frequency range, filtering the first seismic data based on the preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range;

[0015] determining an imaging frequency corresponding to the sub-frequency range, and determining an imaging depth of a depth range corresponding to the sub-frequency range;

[0016] Based on the imaging frequency and imaging depth corresponding to each sub-frequency range, reverse time migration processing is performed on the second seismic data corresponding to each sub-frequency range to obtain a first number of reverse time migration sub-images.

[0017] In another possible implementation, filtering the first seismic data based on the preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range includes:

[0018] Based on the preset frequency range and the sub-frequency range, determining an invalid frequency range corresponding to the sub-frequency range;

[0019] Seismic data corresponding to the invalid frequency range is filtered out from the first seismic data to obtain second seismic data.

[0020] In another possible implementation, if the first number is 2, dividing the effective frequency range into a first number of sub-frequency ranges along the depth direction includes:

[0021] The effective frequency range is divided into a first sub-frequency range and a second sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the first sub-frequency range is less than the maximum depth of the depth range corresponding to the second sub-frequency range, then the frequency range of the first sub-frequency range is wider than the frequency range of the second sub-frequency range.

[0022] In another possible implementation, performing prestack depth migration on the first seismic data to obtain a first prestack depth migration image includes:

[0023] Obtain prestack depth migration velocity model;

[0024] inputting the first seismic data into the prestack depth migration velocity model to obtain depth migration velocity;

[0025] Based on the depth migration velocity, prestack depth migration processing is performed on the first seismic data to obtain a first prestack depth migration image.

[0026] In another possible implementation, the first pre-stack depth migration image includes a plurality of second pre-stack depth migration images;

[0027] The determining, based on the first pre-stack depth migration image, an effective frequency range of imaging of the first seismic data at different depths includes:

[0028] determining a frequency range in which each second prestack depth migration image is imaged at different depths;

[0029] The frequency range corresponding to each second pre-stack depth migration image is combined into the effective frequency range.

[0030] In another possible implementation, obtaining the first seismic data includes:

[0031] Determine the seismic wave field corresponding to the seismic wave;

[0032] Acquiring third seismic data acquired based on the seismic wavefield;

[0033] The third seismic data is preprocessed to obtain the first seismic data.

[0034] In another possible implementation, fusing the first number of reverse time migrated sub-images to obtain a reverse time migrated image includes:

[0035] Based on the depth range corresponding to each sub-frequency range, the first number of reverse time migrated sub-images are spliced to obtain the reverse time migrated image.

[0036] On the other hand, an embodiment of the present application provides a reverse time migration imaging device, comprising:

[0037] An acquisition module, configured to acquire first seismic data, wherein the first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range;

[0038] a first processing module, configured to perform prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image;

[0039] a determination module, configured to determine, based on the first pre-stack depth migration image, an effective frequency range of imaging of the first seismic data at different depths;

[0040] a division module, configured to divide the effective frequency range into a first number of sub-frequency ranges along a depth direction, where the first number is greater than 1 and does not exceed a preset number threshold;

[0041] a second processing module, configured to perform reverse time migration processing on the first seismic data based on the preset frequency range and each sub-frequency range, to obtain a first number of reverse time migration sub-images;

[0042] A fusion module is used to fuse the first number of reverse time migrated sub-images to obtain a reverse time migrated image.

[0043] In one possible implementation, the second processing module is used to filter the first seismic data for each sub-frequency range based on the preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range; determine the imaging frequency corresponding to the sub-frequency range, and determine the imaging depth of the depth range corresponding to the sub-frequency range; and perform reverse time migration processing on the second seismic data corresponding to each sub-frequency range based on the imaging frequency and imaging depth corresponding to each sub-frequency range to obtain a first number of reverse time migration sub-images.

[0044] In another possible implementation, the second processing module is used to determine an invalid frequency range corresponding to the sub-frequency range based on the preset frequency range and the sub-frequency range; and filter the seismic data corresponding to the invalid frequency range from the first seismic data to obtain second seismic data.

[0045] In another possible implementation, if the first number is 2, the division module is used to divide the effective frequency range into a first sub-frequency range and a second sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the first sub-frequency range is less than the maximum depth of the depth range corresponding to the second sub-frequency range, then the frequency range of the first sub-frequency range is wider than the frequency range of the second sub-frequency range.

[0046] In another possible implementation, the first processing module is configured to obtain a pre-stack depth migration velocity model; input the first seismic data into the pre-stack depth migration velocity model to obtain depth migration velocity; and perform pre-stack depth migration processing on the first seismic data based on the depth migration velocity to obtain a first pre-stack depth migration image.

[0047] In another possible implementation, the first pre-stack depth migration image includes a plurality of second pre-stack depth migration images;

[0048] The determining module is configured to determine a frequency range in which each second pre-stack depth migration image is imaged at different depths; and to combine the frequency range corresponding to each second pre-stack depth migration image into the effective frequency range.

[0049] In another possible implementation, the acquisition module is configured to determine a seismic wave field corresponding to a seismic wave; acquire third seismic data collected based on the seismic wave field; and preprocess the third seismic data to obtain the first seismic data.

[0050] In another possible implementation, the fusion module is configured to stitch the first number of reverse time migrated sub-images based on a depth range corresponding to each sub-frequency range to obtain the reverse time migrated image.

[0051] On the other hand, an embodiment of the present application provides a computer device, comprising a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the operations performed in the reverse time migration imaging method described in the embodiment of the present application.

[0052] On the other hand, an embodiment of the present application provides a computer-readable storage medium, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement the operations performed in the reverse time migration imaging method described in the embodiment of the present application.

[0053] In another aspect, embodiments of the present application provide a computer program product or computer program, comprising computer program code stored in a computer-readable storage medium. A processor of a computer device reads the computer program code from the computer-readable storage medium and executes the computer program code to implement the operations performed in the reverse time migration imaging method described in the embodiments of the present application.

[0054] The beneficial effects of the technical solution provided by the embodiments of the present application are:

[0055] An embodiment of the present application provides a reverse time migration imaging method, which generates seismic waves based on the excitation of a source signal within a preset frequency range, collects seismic data corresponding to the seismic waves, and determines the effective frequency range for imaging the seismic data at different depths based on a first pre-stack depth migration image of the seismic data. Since an invalid frequency range is removed from the preset frequency range, reverse time migration processing is performed on the seismic data based on the effective frequency range, saving time for reverse time migration processing of the seismic data through the invalid frequency range, thereby improving the processing efficiency of the seismic data. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a flow chart of a reverse time migration imaging method provided by an embodiment of the present application;

[0057] Figure 2This is a reverse time migration sub-image obtained by performing reverse time migration processing on a shallower stratum using a higher frequency of 45 Hz, as provided in an embodiment of the present application;

[0058] Figure 3 This is a reverse time migration sub-image obtained by performing reverse time migration processing on a deeper stratum using a lower frequency of 25 Hz, as provided in an embodiment of the present application;

[0059] Figure 4 This is a schematic diagram of performing reverse time migration processing on seismic data provided by an embodiment of the present application;

[0060] Figure 5 This embodiment of the present application provides a method of Figure 2 and Figure 3 Schematic diagram of the complete reverse time migration image obtained by fusing the reverse time migration sub-images obtained in ;

[0061] Figure 6 1 is a schematic structural diagram of a reverse time migration imaging device provided in an embodiment of the present application;

[0062] Figure 7 This is a structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the technical solutions and advantages of the present application clearer, the implementation methods of the present application are described in further detail below.

[0064] The present invention provides a reverse time migration imaging method, which is executed by a computer device. Figure 1 , the method comprising:

[0065] Step 101: A computer device acquires first seismic data.

[0066] The first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range.

[0067] In this step, the computer device can be implemented by the following steps (1) to (3), including:

[0068] (1) Computer equipment determines the seismic wave field corresponding to the seismic wave.

[0069] In this step, the computer device can record the seismic wave field through the detector and then obtain the seismic wave field. The seismic wave can be excited by an artificially controlled source signal.

[0070] (2) The computer device obtains third seismic data collected based on the seismic wave field.

[0071] (3) The computer device pre-processes the third seismic data to obtain the first seismic data.

[0072] In this step, the computer device can perform static correction processing, denoising processing, etc. on the third seismic data to obtain the first seismic data. In the embodiment of the present application, the computer device can also perform other preprocessing on the third seismic data, and the preprocessing is not specifically limited here.

[0073] Step 102: The computer device performs pre-stack depth migration processing on the first seismic data to obtain a first pre-stack depth migration image.

[0074] This step can be achieved by following the steps (1) to (3), including:

[0075] (1) Computer equipment obtains the pre-stack depth migration velocity model.

[0076] In this step, the computer device may obtain sample seismic data in advance, train an initial velocity model using the sample seismic data, and obtain a pre-stack depth migration velocity model.

[0077] It should be noted that in addition to the prestack depth migration velocity model, computer equipment can also obtain other medium models, such as density models.

[0078] (2) The computer device inputs the first seismic data into the pre-stack depth migration velocity model to obtain the depth migration velocity.

[0079] The depth migration velocity is the velocity of seismic wave propagation. The first seismic data and the sample seismic data for training the pre-stack depth migration velocity model are seismic data collected from different areas of the same seismic work area.

[0080] If the computer device also obtains other medium models in step (1), then in this step, the computer device also inputs the first seismic data into the other medium models to obtain corresponding depth migration parameters.

[0081] (3) The computer device performs pre-stack depth migration processing on the first seismic data based on the depth migration velocity to obtain a first pre-stack depth migration image.

[0082] In this step, the computer device may perform pre-stack depth migration processing on the first seismic data based on the depth migration velocity to obtain a first pre-stack depth migration image.

[0083] If the computer device also determines other depth migration parameters in step (2), then in this step, the computer device may be: the computer device performs prestack depth migration processing on the first seismic data based on the depth migration velocity and other depth migration parameters to obtain a first prestack depth migration image.

[0084] In one possible implementation, the first pre-stack depth migration image includes multiple second pre-stack depth migration images, that is, the computer device can perform pre-stack depth migration processing on the first seismic data using multiple pre-stack depth migration methods to obtain multiple second pre-stack depth migration images.

[0085] In this implementation, a variety of pre-stack depth migration methods can be selected as needed. For example, the multiple pre-stack depth migration methods include the Kirchhoff integral method pre-stack depth migration method and the Beam pre-stack depth migration method.

[0086] For example, if the multiple pre-stack depth migration methods are the Kirchhoff integration method and the Beam pre-stack depth migration method, the computer device performs pre-stack depth migration processing on the first seismic data using the Kirchhoff integration method based on the depth migration velocity to obtain a second pre-stack depth migration image. The computer device performs pre-stack depth migration processing on the first seismic data using the Beam pre-stack depth migration method based on the depth migration velocity to obtain a second pre-stack depth migration image.

[0087] Step 103: The computer device determines an effective frequency range of the first seismic data at different depths based on the first pre-stack depth migration image.

[0088] As can be seen from step 102, the computer device obtains multiple second pre-stack depth migration images. In this step, the computer device determines the frequency range in which each second pre-stack depth migration image is imaged at different depths based on the imaging effect of each second pre-stack depth migration image. The frequency range corresponding to each second pre-stack depth migration image is then combined into an effective frequency range.

[0089] Step 104: The computer device divides the effective frequency range into a first number of sub-frequency ranges along the depth direction.

[0090] In this step, the computer may determine a first number of sub-frequency ranges into which the effective frequency range is divided along the depth direction by using a spectrum analysis method or other methods. The first number is greater than 1 and does not exceed a preset threshold value. The preset threshold value may be set and modified as needed. While improving the efficiency of seismic data processing, the preset threshold value may be lowered. For example, the preset threshold value may be 2 or 3, and accordingly, the first number may be 2 or 3.

[0091] In one possible implementation, if the first number is 2, this step may be: the computer device divides the effective frequency range into a first sub-frequency range and a second sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the first sub-frequency range is less than the maximum depth of the depth range corresponding to the second sub-frequency range, then the frequency range of the first sub-frequency range is wider than the frequency range of the second sub-frequency range.

[0092] For example, consider a work area with a depth range of 0 to 2200 m. Based on the imaging results of multiple second prestack depth migration images, it is shown that most frequencies within the depth range of 0 to 1500 m do not significantly attenuate, while some frequencies within the depth range of 1500 to 2200 m experience significant attenuation. Therefore, the effective frequency range with no significant attenuation within the depth range of 0 to 1500 m can be used as the first sub-frequency range, and the effective frequency range with no significant attenuation within the depth range of 1500 to 2200 m can be used as the second sub-frequency range. Because high frequencies gradually attenuate with increasing depth, the effective frequency range corresponding to the depth range of 0 to 1500 m is wider, while the effective frequency range corresponding to the depth range of 1500 to 2200 m is narrower and primarily low-frequency.

[0093] In another possible implementation, if the first number is 3, this step may be: the computer device divides the effective frequency range into a third sub-frequency range, a fourth sub-frequency range and a fifth sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the third sub-frequency range is less than the maximum depth of the depth range corresponding to the fourth sub-frequency range, and the maximum depth of the depth range corresponding to the fourth sub-frequency range is less than the maximum depth of the depth range corresponding to the fifth sub-frequency range, then the frequency range of the third sub-frequency range is wider than the frequency range of the fourth sub-frequency range, and the frequency range of the fourth sub-frequency range is wider than the frequency range of the fifth sub-frequency range.

[0094] For another example, the working area depth is still 0-2200 m. According to the imaging effects of multiple second pre-stack depth migration images, it is concluded that most frequencies in the depth range of 0-1000 m do not attenuate significantly, some frequencies in the depth range of 1000-1500 m attenuate significantly, and some frequencies in the depth range of 1500-2200 m also attenuate significantly. In this case, the effective frequency range corresponding to the depth range of 0-1000 m can be used as the third sub-frequency range, the effective frequency range corresponding to the depth range of 1000-1500 m can be used as the fourth sub-frequency range, and the effective frequency range corresponding to the depth range of 1500-2200 m can be used as the fifth sub-frequency range. The frequency ranges corresponding to the third sub-frequency range, the fourth sub-frequency range, and the fifth sub-frequency range are narrowed in sequence.

[0095] Step 105: For each sub-frequency range, the computer device performs filtering processing on the first seismic data based on the preset frequency range and each sub-frequency range to obtain second seismic data corresponding to the sub-frequency range.

[0096] This step can be achieved by following the steps (1) to (2), including:

[0097] (1) The computer device determines an invalid frequency range corresponding to the sub-frequency range based on the preset frequency range and the sub-frequency range.

[0098] For each sub-frequency range, the computer device may remove the sub-frequency range from the preset frequency range to obtain an invalid frequency range.

[0099] For example, a computer device divides a valid frequency range into a first sub-frequency range and a second sub-frequency range. The preset frequency range is 10-60 Hz, the first sub-frequency range is 10-50 Hz, and the second sub-frequency range is 10-30 Hz. For the first sub-frequency range, the computer device removes the first sub-frequency range of 10-50 Hz from the preset frequency range of 10-60 Hz, resulting in an invalid frequency range of 51-60 Hz corresponding to the first sub-frequency range. For the second sub-frequency range, the computer device removes the second sub-frequency range of 10-30 Hz from the preset frequency range of 10-60 Hz, resulting in an invalid frequency range of 31-60 Hz.

[0100] (2) The computer device filters the seismic data corresponding to the invalid frequency range from the first seismic data to obtain the second seismic data.

[0101] In this step, for each sub-frequency range, the computer device removes the seismic data corresponding to the invalid sub-frequency range from the first seismic data to obtain the second seismic data corresponding to the sub-frequency range.

[0102] For example, for shallower formations between 0 and 1500 meters, the computer removes data in the invalid frequency range from the first seismic data, retaining the seismic data in the dominant frequency range of the target formation to generate the corresponding second seismic data. For deeper formations between 1500 and 2200 meters, the computer removes data in the high-frequency range from the first seismic data, essentially reducing the frequency band of data outside the target formation to generate the corresponding second seismic data.

[0103] Step 106: The computer device determines the imaging frequency corresponding to the sub-frequency range.

[0104] In this step, for each sub-frequency range, the computer device may use the maximum value or the minimum value of the sub-frequency range as the imaging frequency of the sub-frequency range.

[0105] For example, for the first sub-frequency range and the second sub-frequency range, if the first sub-frequency range is wider than the second sub-frequency range, then under the condition that the imaging requirements are met, the computer device can use the minimum frequency in the first sub-frequency range as the imaging frequency of the first sub-frequency range and the maximum frequency in the second sub-frequency range as the imaging frequency of the second sub-frequency range.

[0106] Step 107: The computer device determines the imaging depth of the depth range corresponding to the sub-frequency range.

[0107] In this step, for each sub-frequency range, the computer device determines that, under the condition that the imaging depth meets the imaging requirement, the maximum value or minimum value of the depth range corresponding to the sub-frequency range can be used as its imaging depth.

[0108] For example, for the first sub-frequency range and the second sub-frequency range, if the maximum depth of the depth range corresponding to the first sub-frequency range is smaller than the maximum depth of the depth range corresponding to the second sub-frequency range, the computer device may use the maximum depth of the depth range corresponding to the first sub-frequency range as the imaging depth of the first sub-frequency range, and use the maximum depth of the depth range corresponding to the second sub-frequency range as the imaging depth of the second sub-frequency range.

[0109] Step 108: The computer device performs reverse time migration processing on the second seismic data corresponding to each sub-frequency range based on the imaging frequency and imaging depth corresponding to each sub-frequency range to obtain a first number of reverse time migration sub-images.

[0110] In this step, for each sub-frequency range, the computer device performs reverse time migration processing on the second seismic data corresponding to the sub-frequency range based on the imaging frequency and imaging depth corresponding to the sub-frequency range to obtain a reverse time migration sub-image corresponding to the sub-frequency range.

[0111] The computer device may perform reverse time migration processing on the second seismic data by any method, such as a finite difference method, which is not specifically limited in the embodiments of the present application.

[0112] See respectively Figure 2 and Figure 3 , Figure 2 This is an image obtained by reverse time migration processing of seismic data with a shallow depth range at a higher frequency of 45Hz. Figure 3 This image is obtained by performing reverse time migration processing on seismic data with a deeper depth range at a lower frequency of 25 Hz.

[0113] Step 109: The computer device fuses the first number of reverse time migrated sub-images to obtain a reverse time migrated image.

[0114] In this step, the computer device may stitch the first number of reverse time migrated sub-images based on the depth range corresponding to each sub-frequency range to obtain a reverse time migrated image.

[0115] One thing that needs to be explained is that in the related art, variable depth gridding technology is used to solve the problem of processing efficiency of seismic data. However, this method requires interpolation and exchange of the wave field at the interface of variable grid density, and requires the use of the same time step, which makes the implementation process complicated. In the embodiment of the present application, the high-frequency components of the data in the deep area of seismic exploration have been greatly attenuated, and there are no effective high-frequency components for imaging. The seismic data is segmented along the depth for reverse time migration processing. A wider frequency band is used in the shallow area, and a narrower frequency band is used in the deep area. The results of each part are then fused to obtain a complete reverse time migration image. This method solves the problem that the frequency coefficient of the finite difference decomposition of the wave equation in the reverse time migration imaging method has a large impact on the amount of calculation, and does not require the use of complex variable depth gridding. The implementation method is simple, saving processing time, thereby improving processing efficiency.

[0116] See also Figure 4 ,from Figure 4 It can be seen that the computer equipment first pre-processes the collected third seismic data to obtain the first seismic data, then obtains the pre-stack depth migration velocity model and other medium models, and performs pre-stack depth migration based on the first seismic data, pre-stack depth migration velocity model and other medium models to obtain a pre-stack depth migration image. Based on the dominant and inferior frequency bands of the pre-stack depth migration image, the segmented sub-frequency range is determined. The first seismic data is filtered to retain the dominant frequency band of the target layer to obtain a reverse time migration sub-image, and reduce the frequency band of non-target layer data to obtain a reverse time migration sub-image. Multiple reverse time migration sub-images are fused to obtain a complete reverse time migration image. See Figure 5 , Figure 5 It will Figure 2 and Figure 3 The reverse time migration sub-images are fused to obtain the complete reverse time migration image. Figure 5 It can be seen from the figure that the reverse time migration image has good imaging effect at all depths.

[0117] See Table 1, which compares the working efficiency of the method provided by the embodiment of the present application with that of the method in the related art. As can be seen from Table 1, under the conditions of the same total number of shots of seismic data and the same number of GPUs (graphics processing units), the method in the related art processes each shot at a high frequency of 45 Hz, with a processing time of 2 hours for each shot, and a total processing time of 11 days. However, the embodiment of the present application processes seismic data using both a high frequency of 45 Hz and a low frequency of 25 Hz. It can be seen that when the shot is processed at a low frequency of 25 Hz, the processing time for each shot is reduced to 0.5 hours, thereby shortening the total processing time to 8 days, and improving the processing efficiency by approximately 30%. This shows that the method provided by the embodiment of the present application can improve the processing efficiency of seismic data.

[0118] Table 1 Comparison of work efficiency

[0119] Imaging methods Total number of guns efficiency Number of GPUs frequency Spend time Related technical methods 21058 2h / gun 160 45Hz 11 days This application method 21058 2h / gun or 0.5h / gun 160 45Hz / 25Hz 8 days

[0120] The reverse time migration imaging method provided in an embodiment of the present application generates seismic waves based on the excitation of a source signal within a preset frequency range, collects seismic data corresponding to the seismic waves, and determines the effective frequency range for imaging the seismic data at different depths based on a first pre-stack depth migration image of the seismic data. Since the invalid frequency range is removed from the preset frequency range, reverse time migration processing is performed on the seismic data based on the effective frequency range, saving time for reverse time migration processing of the seismic data through the invalid frequency range, thereby improving the processing efficiency of the seismic data.

[0121] The present invention provides a reverse time migration imaging device. Figure 6 , the device comprises:

[0122] An acquisition module 601 is configured to acquire first seismic data, where the first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range;

[0123] A first processing module 602 is configured to perform prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image;

[0124] A determination module 603 is configured to determine an effective frequency range of the first seismic data at different depths based on the first pre-stack depth migration image;

[0125] A division module 604 is configured to divide the effective frequency range into a first number of sub-frequency ranges along the depth direction, where the first number is greater than 1 and does not exceed a preset number threshold;

[0126] A second processing module 605 is configured to perform reverse time migration processing on the first seismic data based on the preset frequency range and each sub-frequency range to obtain a first number of reverse time migration sub-images;

[0127] The fusion module 606 is configured to fuse the first number of reverse time migrated sub-images to obtain a reverse time migrated image.

[0128] In one possible implementation, the second processing module 605 is used to filter the first seismic data for each sub-frequency range based on a preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range; determine the imaging frequency corresponding to the sub-frequency range, and determine the imaging depth of the depth range corresponding to the sub-frequency range; and perform reverse time migration processing on the second seismic data corresponding to each sub-frequency range based on the imaging frequency and imaging depth corresponding to each sub-frequency range to obtain a first number of reverse time migration sub-images.

[0129] In another possible implementation, the second processing module 605 is configured to determine an invalid frequency range corresponding to the sub-frequency range based on the preset frequency range and the sub-frequency range; and filter the seismic data corresponding to the invalid frequency range from the first seismic data to obtain second seismic data.

[0130] In another possible implementation, if the first number is 2, the division module 604 is used to divide the effective frequency range into a first sub-frequency range and a second sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the first sub-frequency range is less than the maximum depth of the depth range corresponding to the second sub-frequency range, then the frequency range of the first sub-frequency range is wider than the frequency range of the second sub-frequency range.

[0131] In another possible implementation, the first processing module 602 is configured to obtain a pre-stack depth migration velocity model; input the first seismic data into the pre-stack depth migration velocity model to obtain depth migration velocity; and perform pre-stack depth migration processing on the first seismic data based on the depth migration velocity to obtain a first pre-stack depth migration image.

[0132] In another possible implementation, the first pre-stack depth migration image includes a plurality of second pre-stack depth migration images;

[0133] The determination module 603 is configured to determine a frequency range in which each second pre-stack depth migration image is imaged at different depths; and to combine the frequency range corresponding to each second pre-stack depth migration image into an effective frequency range.

[0134] In another possible implementation, the acquisition module 601 is configured to determine a seismic wave field corresponding to a seismic wave; acquire third seismic data acquired based on the seismic wave field; and preprocess the third seismic data to obtain first seismic data.

[0135] In another possible implementation, the fusion module 606 is configured to stitch the first number of reverse time migrated sub-images based on the depth range corresponding to each sub-frequency range to obtain a reverse time migrated image.

[0136] The reverse time migration imaging device provided in an embodiment of the present application generates seismic waves based on excitation of a source signal within a preset frequency range, collects seismic data corresponding to the seismic waves, and determines an effective frequency range for imaging the seismic data at different depths based on a first pre-stack depth migration image of the seismic data. Since an invalid frequency range is removed from the preset frequency range, reverse time migration processing is performed on the seismic data based on the effective frequency range, saving time for reverse time migration processing of the seismic data through the invalid frequency range, thereby improving the processing efficiency of the seismic data.

[0137] Figure 7 The following is a block diagram of a computer device 700 according to an exemplary embodiment of the present application. The computer device 700 may be a portable mobile computer device, such as a smartphone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer, or a desktop computer. The computer device 700 may also be referred to as a user device, a portable computer device, a laptop computer device, a desktop computer device, or other similar names.

[0138] Typically, the computer device 700 includes a processor 701 and a memory 702 .

[0139] The processor 701 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 701 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 701 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 701 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 701 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0140] Memory 702 may include one or more computer-readable storage media, which may be non-transitory. Memory 702 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in memory 702 is used to store at least one instruction, which is executed by processor 701 to implement the reverse time migration imaging method provided in the method embodiments of the present application.

[0141] In some embodiments, computer device 700 may optionally include a peripheral device interface 703 and at least one peripheral device. Processor 701, memory 702, and peripheral device interface 703 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 703 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 704, a display screen 705, a camera assembly 706, an audio circuit 707, a positioning assembly 708, and a power supply 709.

[0142] The peripheral device interface 703 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 701 and the memory 702. In some embodiments, the processor 701, the memory 702, and the peripheral device interface 703 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 701, the memory 702, and the peripheral device interface 703 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0143] The RF circuit 704 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 704 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 704 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the RF circuit 704 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. The RF circuit 704 can communicate with other computer devices via at least one wireless communication protocol. Such wireless communication protocols include, but are not limited to, the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 704 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0144] Display screen 705 is used to display a user interface (UI). This UI may include graphics, text, icons, videos, or any combination thereof. When display screen 705 is a touchscreen display, it is also capable of collecting touch signals on or above the surface of display screen 705. These touch signals can be input as control signals to processor 701 for processing. Display screen 705 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there can be one display screen 705, located on the front panel of computer device 700. In other embodiments, there can be at least two display screens 705, located on different surfaces of computer device 700 or in a foldable design. In other embodiments, display screen 705 can be a flexible display, located on a curved or foldable surface of computer device 700. Display screen 705 can also be configured as a non-rectangular, irregular shape, also known as a special-shaped screen. Display screen 705 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0145] The camera assembly 706 is used to capture images or videos. Optionally, the camera assembly 706 includes a front camera and a rear camera. Typically, the front camera is set on the front panel of the computer device, and the rear camera is set on the back of the computer device. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 706 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0146] The audio circuit 707 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals to be input into the processor 701 for processing, or input into the radio frequency circuit 704 to achieve voice communication. For the purpose of stereo sound collection or noise reduction, there can be multiple microphones, which are respectively arranged in different parts of the computer device 700. The microphone can also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert the electrical signals from the processor 701 or the radio frequency circuit 704 into sound waves. The speaker can be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signals into sound waves audible to humans, but also convert the electrical signals into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 707 may also include a headphone jack.

[0147] Positioning component 708 is used to locate the current geographic location of computer device 700 to implement navigation or LBS (Location Based Service). Positioning component 708 can be a positioning component based on the US GPS (Global Positioning System), China's Beidou system, or Russia's Galileo system.

[0148] Power supply 709 is used to power the various components of computer device 700. Power supply 709 can be AC power, DC power, a disposable battery, or a rechargeable battery. When power supply 709 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0149] In some embodiments, the computer device 700 further includes one or more sensors 710 , including but not limited to: an acceleration sensor 711 , a gyroscope sensor 712 , a pressure sensor 713 , a fingerprint sensor 714 , an optical sensor 715 , and a proximity sensor 716 .

[0150] The accelerometer 711 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the computer device 700. For example, the accelerometer 711 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 701 can control the display screen 705 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 711. The accelerometer 711 can also be used to collect game or user motion data.

[0151] The gyroscope sensor 712 can detect the orientation and rotation angle of the computer device 700. It can also work with the accelerometer 711 to collect 3D motions of the user on the computer device 700. Based on the data collected by the gyroscope sensor 712, the processor 701 can implement the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0152] The pressure sensor 713 can be installed on the side frame of the computer device 700 and / or below the display screen 705. When the pressure sensor 713 is installed on the side frame of the computer device 700, it can detect the user's grip signal of the computer device 700. The processor 701 can perform left and right hand recognition or shortcut operations based on the grip signal collected by the pressure sensor 713. When the pressure sensor 713 is installed below the display screen 705, the processor 701 controls the operational controls on the UI interface based on the user's pressure operation on the display screen 705. The operational controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0153] The fingerprint sensor 714 is used to collect the user's fingerprint. The processor 701 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 714, or the fingerprint sensor 714 identifies the user's identity based on the collected fingerprint. When the user's identity is recognized as a trusted identity, the processor 701 authorizes the user to perform relevant sensitive operations, such as unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings. The fingerprint sensor 714 can be set on the front, back, or side of the computer device 700. When a physical button or manufacturer logo is set on the computer device 700, the fingerprint sensor 714 can be integrated with the physical button or manufacturer logo.

[0154] The optical sensor 715 is used to detect ambient light intensity. In one embodiment, the processor 701 can control the display brightness of the display screen 705 based on the ambient light intensity detected by the optical sensor 715. Specifically, when the ambient light intensity is high, the display brightness of the display screen 705 is increased; when the ambient light intensity is low, the display brightness of the display screen 705 is decreased. In another embodiment, the processor 701 can also dynamically adjust the shooting parameters of the camera assembly 706 based on the ambient light intensity detected by the optical sensor 715.

[0155] Proximity sensor 716, also known as a distance sensor, is typically located on the front panel of computer device 700. Proximity sensor 716 is used to detect the distance between the user and the front of computer device 700. In one embodiment, when proximity sensor 716 detects that the distance between the user and the front of computer device 700 is gradually decreasing, processor 701 controls display screen 705 to switch from the screen-on state to the screen-off state. When proximity sensor 716 detects that the distance between the user and the front of computer device 700 is gradually increasing, processor 701 controls display screen 705 to switch from the screen-off state to the screen-on state.

[0156] Those skilled in the art will understand that Figure 7 The structure shown in the figure does not constitute a limitation on the computer device 700, and the computer device 700 may include more or fewer components than shown in the figure, or combine some components, or adopt a different component arrangement.

[0157] The embodiment of the present application further provides a computer-readable storage medium, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement the operations performed in the reverse time migration imaging method in the embodiment of the present application.

[0158] Embodiments of the present application also provide a computer program product or computer program, which includes computer program code stored in a computer-readable storage medium. A processor of a computer device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the computer device to perform the operations performed by the reverse time migration imaging method described above.

[0159] In some embodiments, the computer program involved in the embodiments of the present application may be deployed and executed on a computer device, or on multiple computer devices located at one location, or on multiple computer devices distributed at multiple locations and interconnected through a communication network. Multiple computer devices distributed at multiple locations and interconnected through a communication network may constitute a blockchain system.

[0160] The above description is only for the purpose of facilitating those skilled in the art to understand the technical solution of this application and is not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included in the scope of protection of this application.

Claims

1. A reverse time migration imaging method, characterized in that: The method comprises: Acquire first seismic data, where the first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range; performing prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image; determining, based on the first pre-stack depth migration image, an effective frequency range for imaging the first seismic data at different depths; Dividing the effective frequency range into a first number of sub-frequency ranges along the depth direction, where the first number is greater than 1 and does not exceed a preset number threshold; Based on the preset frequency range and each sub-frequency range, performing reverse time migration processing on the first seismic data respectively to obtain a first number of reverse time migration sub-images; The first number of reverse time migrated sub-images are fused to obtain a reverse time migrated image.

2. The method according to claim 1, characterized in that The step of performing reverse time migration processing on the first seismic data based on the preset frequency range and each sub-frequency range to obtain a first number of reverse time migration sub-images includes: For each sub-frequency range, filtering the first seismic data based on the preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range; determining an imaging frequency corresponding to the sub-frequency range, and determining an imaging depth of a depth range corresponding to the sub-frequency range; Based on the imaging frequency and imaging depth corresponding to each sub-frequency range, reverse time migration processing is performed on the second seismic data corresponding to each sub-frequency range to obtain a first number of reverse time migration sub-images.

3. The method according to claim 2, characterized in that The filtering process is performed on the first seismic data based on the preset frequency range and the sub-frequency range to obtain second seismic data corresponding to the sub-frequency range, including: Based on the preset frequency range and the sub-frequency range, determining an invalid frequency range corresponding to the sub-frequency range; Seismic data corresponding to the invalid frequency range is filtered out from the first seismic data to obtain second seismic data.

4. The method according to claim 1, wherein If the first number is 2, dividing the effective frequency range into a first number of sub-frequency ranges along the depth direction includes: The effective frequency range is divided into a first sub-frequency range and a second sub-frequency range along the depth direction, and if the maximum depth of the depth range corresponding to the first sub-frequency range is less than the maximum depth of the depth range corresponding to the second sub-frequency range, then the frequency range of the first sub-frequency range is wider than the frequency range of the second sub-frequency range.

5. The method according to claim 1, wherein The performing prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image includes: Obtain prestack depth migration velocity model; inputting the first seismic data into the prestack depth migration velocity model to obtain depth migration velocity; Based on the depth migration velocity, prestack depth migration processing is performed on the first seismic data to obtain a first prestack depth migration image.

6. The method according to claim 1, wherein The first pre-stack depth migration image includes a plurality of second pre-stack depth migration images; The determining, based on the first pre-stack depth migration image, an effective frequency range of imaging of the first seismic data at different depths includes: determining a frequency range in which each second prestack depth migration image is imaged at different depths; The frequency range corresponding to each second pre-stack depth migration image is combined into the effective frequency range.

7. The method according to claim 1, characterized in that The acquiring of the first seismic data comprises: Determine the seismic wave field corresponding to the seismic wave; Acquiring third seismic data acquired based on the seismic wavefield; The third seismic data is preprocessed to obtain the first seismic data.

8. The method according to claim 1, characterized in that The fusing the first number of reverse time migrated sub-images to obtain a reverse time migrated image includes: Based on the depth range corresponding to each sub-frequency range, the first number of reverse time migrated sub-images are spliced to obtain the reverse time migrated image.

9. A reverse time migration imaging device, characterized in that: The device comprises: An acquisition module, configured to acquire first seismic data, wherein the first seismic data is acquired based on seismic waves excited by a source signal within a preset frequency range; a first processing module, configured to perform prestack depth migration processing on the first seismic data to obtain a first prestack depth migration image; a determination module, configured to determine, based on the first pre-stack depth migration image, an effective frequency range of imaging of the first seismic data at different depths; a division module, configured to divide the effective frequency range into a first number of sub-frequency ranges along a depth direction, where the first number is greater than 1 and does not exceed a preset number threshold; a second processing module, configured to perform reverse time migration processing on the first seismic data based on the preset frequency range and each sub-frequency range, to obtain a first number of reverse time migration sub-images; A fusion module is used to fuse the first number of reverse time migrated sub-images to obtain a reverse time migrated image.

10. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor to implement the reverse time migration imaging method according to any one of claims 1 to 8.

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