Free surface multiple wave mixed pressing method, device, equipment, medium and product

Abstract

The invention relates to the technical field of free surface multiple wave mixed suppression, in particular to a free surface multiple wave mixed suppression method, device, equipment, medium and product, and the method comprises the steps: carrying out multiple wave model prediction through preprocessing data based on a WEMA method, and obtaining a WEMA multiple wave model; on the basis of an SRME method, multiple wave model prediction is conducted through the preprocessed data, and an SRME multiple wave model is obtained; performing mixed subtraction on the WEMA multiple wave model and the SRME multiple wave model by using the preprocessed seismic data to obtain seismic data after mixed suppression of multiple waves; and the suppression effect of free surface multiples is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of free surface multiple wave mixing suppression, and in particular to a free surface multiple wave mixing suppression method, device, equipment, medium and product. Background Art

[0002] In offshore seismic exploration, the sea level is a natural good reflection interface, which means that almost all offshore seismic data imaging faces the challenge of multiple waves related to the sea level. The existence of multiple waves affects the primary wave imaging, reduces the signal-to-noise ratio of the data, and will form false reflection phase axes in the seismic profile, affecting the interpretation of seismic data. There is a technical problem in this field that the suppression effect of free surface multiple waves is poor. Summary of the invention

[0003] The present invention provides a free surface multiple wave mixed suppression method, device, equipment, medium and product, which solves the technical problem of poor suppression effect of free surface multiple waves.

[0004] In a first aspect, the present invention provides a free surface multiple wave mixed suppression method, the method comprising: based on the WEMA method, using preprocessed data to predict the multiple wave model to obtain the WEMA multiple wave model; based on the SRME method, using preprocessed data to predict the multiple wave model to obtain the SRME multiple wave model; mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed suppression of the multiple waves.

[0005] In some embodiments, before the step of using preprocessed data to perform multiple wave model prediction, the method also includes: preprocessing the original seismic data to obtain preprocessed seismic data; wherein the preprocessing includes: removing source characteristics, suppressing bubble noise, and suppressing ghost waves.

[0006] In some embodiments, based on the SRME method, the step of using preprocessed data to predict the multiple wave model includes: removing the first arrival wave of the preprocessed seismic data; based on the SRME method, processing the preprocessed seismic data with the first arrival wave removed to obtain the SRME multiple wave model.

[0007] In some embodiments, the step of mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed and suppressed multiple waves includes: subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data respectively, and mixing the minimum values ​​in the results to obtain the seismic data after mixed and suppressed multiple waves.

[0008] In some embodiments, the steps of subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data, respectively, and mixing the minimum values ​​in the results to obtain the seismic data after mixed suppression of multiple waves include: within a preset sliding time window, subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data, respectively, to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model; within the preset sliding time window, taking the minimum value of the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model as the seismic data after mixed suppression of multiple waves in the preset sliding time window.

[0009] In some embodiments, the steps of subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data, respectively, to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model include: subtracting the convolution of the WEMA multiple wave model and the non-stationary filter operator from the preprocessed seismic data; subtracting the convolution of the SRME multiple wave model and the non-stationary filter operator from the preprocessed seismic data.

[0010] In the second aspect, the present invention provides a free surface multiple wave mixed suppression device, the device comprising: a WEMA multiple wave prediction module, used to predict the multiple wave model based on the WEMA method using preprocessed data to obtain the WEMA multiple wave model; an SRME multiple wave prediction module, used to predict the multiple wave model based on the SRME method using preprocessed data to obtain the SRME multiple wave model; a parallel subtraction module, used to mix and subtract the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed suppression of the multiple waves.

[0011] In a third aspect, the present invention provides a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the free surface multiple wave mixing suppression methods described above.

[0012] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the free surface multiple wave mixing suppression methods described above.

[0013] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of any of the free surface multiple wave mixing suppression methods described above.

[0014] The present invention provides a free surface multiple wave mixed suppression method, device, equipment, medium and product, wherein the method comprises: based on the WEMA method, using preprocessed data to predict the multiple wave model to obtain the WEMA multiple wave model; based on the SRME method, using preprocessed data to predict the multiple wave model to obtain the SRME multiple wave model; mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain seismic data after mixed suppression of multiple waves; the suppression effect of free surface multiple waves can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0016] Figure 1 It is a flow chart of a free surface multiple wave mixing suppression method provided in an embodiment of the present application;

[0017] Figure 2 It is a structural schematic diagram of a free surface multiple wave mixing suppression device provided in an embodiment of the present application;

[0018] Figure 3 is a schematic diagram of an SRME method provided in an embodiment of the present application;

[0019] Figure 4 This is a schematic diagram of multiple wave prediction and subtraction of an SRME method provided in an embodiment of the present application;

[0020] Figure 5 is a schematic diagram of a WEMA method provided in an embodiment of the present application;

[0021] Figure 6 This is a schematic diagram of multiple wave prediction and subtraction of a WEMA method provided in an embodiment of the present application;

[0022] Figure 7 It is a schematic diagram of hybrid multiple wave prediction and subtraction provided by an embodiment of the present application;

[0023] Figure 8 This is a schematic diagram comparing the effects of suppressing multiple waves using different methods provided in the embodiments of the present application.

[0024] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, and to fully understand and implement how the present invention applies technical means to solve technical problems and achieve the corresponding technical effects, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only an embodiment of a part of the present invention, not all of the embodiments. The embodiments of the present invention and the various features in the embodiments can be combined with each other without conflict, and the technical schemes formed are all within the scope of protection of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] In offshore seismic exploration, the sea level is a natural good reflection interface, which means that almost all offshore seismic data imaging faces the challenge of multiple waves related to the sea level. The existence of multiple waves affects the primary wave imaging, reduces the signal-to-noise ratio of the data, and will form false reflection phase axes in the seismic profile, affecting the interpretation of seismic data. There is a technical problem in this field that the suppression effect of free surface multiple waves is poor.

[0029] Hereinafter, the technical solution of the present application will be described in conjunction with specific embodiments.

[0030] Embodiment 1

[0031] Figure 1 is a flow chart of a free surface multiple wave mixing suppression method provided in an embodiment of the present application, such as Figure 1As shown, in the technical solution of this embodiment, a free surface multiple wave mixed suppression method is provided, the method comprising: based on the WEMA method, using preprocessed data to predict the multiple wave model to obtain the WEMA multiple wave model; based on the SRME method, using preprocessed data to predict the multiple wave model to obtain the SRME multiple wave model; mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed suppression of the multiple waves.

[0032] The technical problem to be solved in this embodiment is how to improve the suppression effect of free surface multiple waves. In offshore seismic exploration, the sea level is a natural good reflection interface. The existence of free surface multiple waves seriously affects the primary wave imaging, reduces the data signal-to-noise ratio, and also forms false reflection phase axes in the seismic profile, interfering with the interpretation of seismic data. However, related technologies often have limitations in suppressing free surface multiple waves, and it is difficult to achieve an ideal suppression effect. There is a technical problem in this field that the suppression effect of free surface multiple waves needs to be improved.

[0033] In the technical solution of this embodiment, the concepts and functions of the WEMA model and the SRME model must be clarified first. WEMA, or the wave equation multiple wave attenuation technology, is the inverse process of the wave equation migration. It uses the velocity model and seismic migration modeling, and utilizes the physical process of wave field extrapolation to allow the recorded seismic wave field to propagate a round trip in the seawater layer, so that the original single reflection wave is transformed into a secondary reflection wave, and the multiple wave order is increased by one, thereby obtaining the WEMA multiple wave model. SRME is a data-driven multiple wave suppression technology, which is based on the concept of convolving two seismic traces with a common reflection point on the multiple wave reflection surface to generate multiple waves related to the reflection point, thereby obtaining the SRME multiple wave model. The technical solution of this embodiment first uses the pre-processed data based on the WEMA model to predict the multiple wave model, that is, the physical process and operation related to the WEMA are used to generate the corresponding multiple wave model; then, based on the SRME model, the pre-processed data is used to predict the multiple wave model, and the corresponding multiple wave model is obtained in accordance with the convolution method. After constructing multiple wave models based on preprocessed seismic data through these two different methods, they are mixed and subtracted, and the two models are associated with the preprocessed seismic data to improve the suppression effect of free surface multiple waves by combining their advantages.

[0034] The technical solution of this embodiment is to obtain respective multiple wave models by processing the pre-processed seismic data based on the WEMA model and the SRME model, and then perform a mixed subtraction operation. On the one hand, by utilizing the advantages of the wave field extrapolation combined with the velocity model and other information in the WEMA model, the propagation of seismic waves in the seawater layer can be better simulated, and some multiple wave characteristics related to the seawater layer can be accurately grasped; on the other hand, the data-driven characteristics of the SRME model can be used to mine relevant multiple wave information through convolution based on the existing seismic trace data. After the two are combined, they can make up for each other's shortcomings in the mixed subtraction process, so that the seismic data obtained after the mixed suppression of multiple waves has a significant improvement in the suppression of free surface multiple waves. Compared with the situation of using only one model to suppress free surface multiple waves, after adopting the solution of this embodiment, the residue of free surface multiple waves on the seismic profile is significantly reduced, the signal-to-noise ratio of the data is effectively improved, and the false reflection phase axis is greatly reduced, which is more conducive to the subsequent seismic data inversion and interpretation, so that the data quality related to free surface multiple waves in the entire offshore seismic exploration has been substantially improved, and a more reliable data basis is provided for subsequent geological analysis and other work.

[0035] Embodiment 2

[0036] On the basis of the above embodiment, before the step of using preprocessed data to perform multiple wave model prediction, the method also includes: preprocessing the original seismic data to obtain preprocessed seismic data; wherein the preprocessing includes: removing source characteristics, suppressing bubble noise, and suppressing ghost waves.

[0037] The technical problem solved by this embodiment is how to pre-process the original seismic data.

[0038] In the technical solution of this embodiment, removing the source characteristics refers to eliminating the special imprints caused by the source's own characteristics in the seismic data through preset algorithms and technical means, so that the seismic data can better reflect the wave propagation information corresponding to the real underground geological structure. Bubble noise suppression is to suppress the noise interference caused by bubbles generated by processes such as source excitation in seismic exploration. This noise will blur the real seismic signal and weaken it through corresponding filtering and other processing methods. Ghost wave suppression is to deal with ghost waves generated by interface reflections such as water surfaces during the propagation of seismic waves. Ghost waves will be superimposed on real effective waves, interfering with the identification and analysis of effective waves, and using special suppression methods to remove the influence of ghost waves. After the preprocessing operation of this embodiment, the interference factors in the original seismic data are largely removed, thereby converting them into higher quality preprocessed seismic data, laying a good data foundation for the subsequent construction of multiple wave models based on WEMA models and SRME models, and ensuring that subsequent operations can be carried out more accurately.

[0039] The technical solution of this embodiment is to perform preprocessing operations on the original seismic data, including removing source characteristics, suppressing bubble noise, suppressing ghost waves, etc. In actual offshore seismic exploration applications, when the original data is not preprocessed, due to the existence of source characteristics, some abnormal fluctuations that are irrelevant to the real geological reflection signal will appear on the seismic record. After removing the source characteristics, these abnormal fluctuations are significantly reduced, and the seismic record is smoother and can better reflect the real reflection situation. If the bubble noise is not suppressed, it will generate messy interference signals on the frequency band of the entire seismic data, causing the effective signal to be submerged. After corresponding suppression, the effective frequency band of the data is clearer and the signal recognizability is greatly improved. The existence of ghost waves will cause false phase axes to appear on the seismic profile, interfering with the judgment of the underground geological structure. After ghost wave suppression, the seismic profile becomes more regular and the real reflection phase axis is highlighted. When the seismic data obtained after preprocessing in this embodiment is used for subsequent operations such as building a multiple wave model based on different models and suppressing multiple waves, the accuracy of the operation and the final effect can be greatly improved, so that the multiple wave suppression can be carried out more accurately, and various errors caused by poor quality of original data can be reduced. This sets a good start for the data processing process of the entire offshore seismic exploration, allowing subsequent analysis and interpretation work to be carried out smoothly based on high-quality data.

[0040] Embodiment 3

[0041] On the basis of the above-mentioned embodiment, based on the SRME method, the step of using preprocessed data to predict the multiple wave model includes: removing the first arrival wave of the preprocessed seismic data; based on the SRME method, processing the preprocessed seismic data with the first arrival wave removed to obtain the SRME multiple wave model.

[0042] The technical problem solved by this embodiment is how to obtain the SRME multiple wave model based on the SRME model and pre-processed seismic data.

[0043] In the technical solution of this embodiment, the SRME model is a data-driven multiple wave suppression technology, the core of which is to generate a multiple wave model by convolution of two seismic traces with a common reflection point on the multiple wave reflection surface. In this process, cutting out the first arrival wave of the pre-processed seismic data is a key pre-operation. The first arrival wave is the first part of the seismic wave to reach the detector. It contains some special propagation paths and characteristic information, but for the construction of the SRME multiple wave model by convolution, it is easy to bring additional interference factors and affect the accuracy of the convolution result. Therefore, it should be cut off first, and then the pre-processed seismic data after cutting out the first arrival wave is processed based on the SRME model, that is, according to the principle of its convolution, the corresponding two seismic traces are found for convolution operation, so as to generate multiple waves related to the reflection point and obtain an accurate SRME multiple wave model. The SRME multiple wave model processed in this way can better reflect the real multiple wave situation, and provide a reliable model basis for the subsequent combination with the WEMA multiple wave model to mix and subtract the suppression of multiple waves.

[0044] The technical solution of this embodiment is to obtain the SRME multiple wave model by first cutting off the first arrival wave of the pre-processed seismic data and then processing it based on the SRME model. In the actual offshore seismic exploration data analysis, if the SRME model is used directly to construct the multiple wave model without cutting off the first arrival wave, it will be found that the multiple wave model finally obtained has a large deviation from the actual multiple wave situation, which affects the multiple wave suppression effect. After cutting off the first arrival wave and then constructing the model, the SRME multiple wave model obtained is more in line with the real multiple wave characteristics. When this accurate SRME multiple wave model is mixed and subtracted with the multiple wave model obtained by the subsequent WEMA model, the accuracy of the SRME multiple wave model is improved, and the synergy of the two is also stronger, so that the effect of mixed suppression of multiple waves is significantly improved. For example, in suppressing free surface multiple waves, it is possible to more accurately remove multiple wave interference, make the imaging of a wave clearer, and further improve the signal-to-noise ratio of the data, which is more conducive to the subsequent accurate judgment and analysis of the submarine geological structure and other conditions, and provide more valuable data support for the entire offshore seismic exploration work.

[0045] Embodiment 4

[0046] On the basis of the above embodiment, the steps of mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed suppression of multiple waves include: subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data respectively, and mixing the minimum values ​​in the results to obtain the seismic data after mixed suppression of multiple waves.

[0047] The technical problem solved by this embodiment is how to mix and subtract the WEMA multiple wave model and the SRME multiple wave model from the pre-processed seismic data. When using the WEMA multiple wave model and the SRME multiple wave model to suppress multiple waves in the pre-processed seismic data, simply subtracting the two from the pre-processed seismic data cannot give full play to their advantages, and it is difficult to accurately find the optimal suppression result. A reasonable mixed subtraction strategy is needed to ensure that the final seismic data can minimize the impact of multiple waves.

[0048] In the technical solution of this embodiment, the WEMA multiple wave model and the SRME multiple wave model are subtracted from the preprocessed seismic data respectively, and the minimum value in the result is mixed. The WEMA multiple wave model is constructed by the inverse process of wave equation migration, combined with the velocity model and other physical processes such as wave field extrapolation, which reflects the multiple wave situation based on the wave equation; the SRME multiple wave model is obtained by data-driven convolution, which reflects the multiple wave characteristics mined from the existing seismic trace data. Subtracting these two models from the preprocessed seismic data respectively will obtain two sets of different difference results, and the preset sliding time window is selected to mix the minimum value therein because this minimum value means that in the current operation process, the corresponding model has a better suppression effect on the multiple waves, which is closer to the real, ideal state where the multiple waves are removed. Through such a mixed subtraction operation, the two models can be comprehensively utilized, combining the advantages of the two multiple wave suppression technologies, so that the final seismic data after the mixed suppression of multiple waves is closer to the real ideal state of only containing effective waves, thereby improving the overall effect of multiple wave suppression.

[0049] The technical solution of this embodiment is to subtract the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data respectively, and select the minimum value in the result for mixing. In the actual offshore seismic exploration scenario, if a single model is simply used to perform the multiple wave subtraction operation, it is often the case that either the free surface multiple waves are not completely suppressed, or there are still many residual multiple waves between layers near the seabed. After adopting the mixed subtraction strategy of this embodiment, it is possible to adaptively select a better model suppression result for mixing according to the multiple wave conditions of different locations and different characteristics. For example, in the seabed area, at certain moments, the result after subtracting the WEMA multiple wave model is better, and this result will be selected for the final mixing; and for the interlayer multiple waves near the seabed, the result after subtracting the SRME multiple wave model may be better, and it will also be selected for mixing. In this way, the final seismic data after mixed suppression of multiple waves can improve the multiple wave suppression effect in the entire area, the seismic profile is clearer and more accurate, the signal-to-noise ratio of the data is significantly improved, and the false reflection phase axis is greatly reduced, providing higher quality data for subsequent seismic interpretation, geological structure analysis and other work, allowing offshore seismic exploration to have a deeper and more accurate understanding of the underground situation.

[0050] Embodiment 5

[0051] On the basis of the above embodiments, the WEMA multiple wave model and the SRME multiple wave model are respectively subtracted from the preprocessed seismic data, and the minimum values ​​in the results are mixed to obtain the seismic data after mixed suppression of multiple waves, including: within a preset sliding time window, the WEMA multiple wave model and the SRME multiple wave model are respectively subtracted from the preprocessed seismic data to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model; within the preset sliding time window, the minimum value of the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model is used as the seismic data after mixed suppression of multiple waves in the preset sliding time window.

[0052] The technical problem solved by this embodiment is how to perform mixed subtraction of the WEMA multiple wave model and the SRME multiple wave model on the pre-processed seismic data to obtain seismic data after mixed suppression of multiple waves.

[0053] In the technical solution of this embodiment, it is key to carry out the operation within the preset sliding time window. First, within the preset sliding time window, the WEMA multiple wave model and the SRME multiple wave model are subtracted from the pre-processed seismic data, so that the corresponding difference can be obtained in different time intervals and local spatial ranges. Because in offshore seismic exploration, the multiple wave characteristics at different times and positions are dynamically changing, and this change can be captured more carefully through the sliding time window. Then, within the preset sliding time window, the minimum value of the difference between the pre-processed seismic data and the WEMA multiple wave model and the difference between the pre-processed seismic data and the SRME multiple wave model is used as the seismic data after the mixed suppression of multiple waves of the preset sliding time window. In other words, within each small sliding time window range, the result that best reflects the effective suppression of multiple waves can be selected as the final output according to the actual multiple wave situation at that time and place. This method is more accurate than the overall unified operation, and can fully take into account the complexity and variability of seismic data in time and space, so that the seismic data after the mixed suppression of multiple waves obtained by mixed subtraction is more in line with the ideal data state corresponding to the actual geological conditions.

[0054] The technical solution of this embodiment is to perform a subtraction operation of the WEMA multiple wave model and the SRME multiple wave model with the pre-processed seismic data within a preset sliding time window, and select the minimum value as the seismic data after the mixed suppression of the multiple waves of the corresponding time window. In the actual practice of offshore seismic exploration, if the sliding time window method is not adopted, and only the overall mixing is subtracted to select the minimum value, there will be a situation where the multiple waves in some local areas are over-suppressed or under-suppressed. For example, in areas with complex seabed terrain, the reflection characteristics of multiple waves at different locations are quite different. After using the sliding time window, the appropriate model suppression result can be accurately selected according to the specific situation in each small window, so that in the entire complex area, the free surface multiple waves can be suppressed more evenly and thoroughly. The same is true for the interlayer multiple waves near the seabed. The interlayer multiple waves at different depths and different locations can obtain better suppression effects through precise operations within the sliding time window. The final seismic data obtained after mixed suppression of multiple waves is of higher quality overall, and the seismic profile is clearer. It is more accurate in displaying the seabed geological structure and reflecting the interlayer structure, providing a reliable data basis for subsequent geological analysis, oil reservoir exploration and other related work, and improving the accuracy and value of the entire offshore seismic exploration work.

[0055] Embodiment 6

[0056] On the basis of the above embodiment, the WEMA multiple wave model and the SRME multiple wave model are respectively subtracted from the preprocessed seismic data to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model, including: subtracting the convolution of the WEMA multiple wave model and the non-stationary filter operator from the preprocessed seismic data; subtracting the convolution of the SRME multiple wave model and the non-stationary filter operator from the preprocessed seismic data.

[0057] The technical problem solved by this embodiment is how to combine the non-stationary filtering operator to subtract the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data respectively, to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model.

[0058] In the technical solution of this embodiment, the convolution of the WEMA multiple wave model and the non-stationary filter operator is subtracted from the pre-processed seismic data, and the convolution of the SRME multiple wave model and the non-stationary filter operator is subtracted from the pre-processed seismic data. The non-stationary filter operator can adaptively adjust the filtering effect of the multiple wave model according to the non-stationary characteristics of the seismic data, that is, the changes in the propagation characteristics of seismic waves at different times and different positions. For the WEMA multiple wave model, it is itself constructed based on wave equations, etc., and after combining with the non-stationary filter operator, it can better adapt to the complex changes of seismic waves propagating in different areas such as seawater layers and seabeds, so that the subtraction operation can more accurately remove the corresponding multiple wave components. Similarly, for the SRME multiple wave model, it is obtained by convolution. In different characteristic areas of seismic trace data, the degree of suppression of multiple waves can be adjusted according to actual conditions with the help of non-stationary filter operators, so as to accurately obtain the difference between the pre-processed seismic data and the WEMA multiple wave model and the difference between the pre-processed seismic data and the SRME multiple wave model, and provide reliable basic data for further accurate mixed subtraction and other operations.

[0059] The technical solution of this embodiment is to perform the subtraction operation of the WEMA multiple wave model and the SRME multiple wave model from the pre-processed seismic data by combining the non-stationary filter operator. In the actual multiple wave processing of offshore seismic data, the prediction of the multiple wave model is affected by various factors, resulting in the frequency, amplitude and phase differences between the predicted multiple wave model and the actual data in time and space, showing non-stationary characteristics. If the non-stationary filter operator is not used, and the multiple wave model is simply subtracted, the multiple wave suppression effect will be greatly reduced in some complex areas, such as the sudden change of the submarine topography, and there will be too many multiple waves remaining or the effective waves will be mistakenly removed as multiple waves. After adopting the scheme of this embodiment, the non-stationary filter operator can be dynamically adjusted according to these complex geological and environmental factors, and the suppression of multiple waves can be accurately controlled in different areas. For example, near the submarine mountain range, the non-stationary filter operator can reasonably adjust the filter weights of the WEMA and SRME multiple wave models according to the special situation of the seismic wave propagation here, so that the multiple waves are effectively suppressed, while protecting the effective wave components. Ultimately, the difference data obtained after such an operation is more accurate, and the overall effect of multiple wave suppression can be further improved in subsequent processes such as mixed subtraction, making the seismic profile clearer and more accurate, and providing more reliable data support for the judgment of seabed geological structure, resource distribution and other conditions in offshore seismic exploration.

[0060] Embodiment 7

[0061] Figure 2 is a schematic diagram of the structure of a free surface multiple wave mixing suppression device provided in an embodiment of the present application, such as Figure 2 As shown, in the technical solution of this embodiment, a free surface multiple wave mixed suppression device is provided, and the device includes: a WEMA multiple wave prediction module, which is used to predict the multiple wave model based on the WEMA method using preprocessed data to obtain the WEMA multiple wave model; an SRME multiple wave prediction module, which is used to predict the multiple wave model based on the SRME method using preprocessed data to obtain the SRME multiple wave model; a parallel subtraction module, which is used to mix and subtract the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the seismic data after mixed suppression of the multiple waves.

[0062] The technical problem to be solved in this embodiment is how to improve the suppression effect of free surface multiple waves. In offshore seismic exploration, the sea level is a natural good reflection interface. The existence of free surface multiple waves seriously affects the primary wave imaging, reduces the data signal-to-noise ratio, and also forms false reflection phase axes in the seismic profile, interfering with the interpretation of seismic data. However, related technologies often have limitations in suppressing free surface multiple waves, and it is difficult to achieve an ideal suppression effect. There is a technical problem in this field that the suppression effect of free surface multiple waves needs to be improved.

[0063] In the technical solution of this embodiment, the concepts and functions of the WEMA model and the SRME model must be clarified first. WEMA, or the wave equation multiple wave attenuation technology, is the inverse process of the wave equation migration. It uses the velocity model and seismic migration modeling, and utilizes the physical process of wave field extrapolation to allow the recorded seismic wave field to propagate a round trip in the seawater layer, so that the original single reflection wave is transformed into a secondary reflection wave, and the multiple wave order is increased by one, thereby obtaining the WEMA multiple wave model. SRME is a data-driven multiple wave suppression technology, which is based on the concept of convolving two seismic traces with a common reflection point on the multiple wave reflection surface to generate multiple waves related to the reflection point, thereby obtaining the SRME multiple wave model. The technical solution of this embodiment first uses the pre-processed data based on the WEMA model to predict the multiple wave model, that is, the physical process and operation related to the WEMA are used to generate the corresponding multiple wave model; then, based on the SRME model, the pre-processed data is used to predict the multiple wave model, and the corresponding multiple wave model is obtained in accordance with the convolution method. After constructing multiple wave models based on preprocessed seismic data through these two different methods, they are mixed and subtracted, and the two models are associated with the preprocessed seismic data to improve the suppression effect of free surface multiple waves by combining their advantages.

[0064] The technical solution of this embodiment is to obtain respective multiple wave models by processing the pre-processed seismic data based on the WEMA model and the SRME model, and then perform a mixed subtraction operation. On the one hand, by utilizing the advantages of the wave field extrapolation combined with the velocity model and other information in the WEMA model, the propagation of seismic waves in the seawater layer can be better simulated, and some multiple wave characteristics related to the seawater layer can be accurately grasped; on the other hand, the data-driven characteristics of the SRME model can be used to mine relevant multiple wave information through convolution based on the existing seismic trace data. After the two are combined, they can make up for each other's shortcomings in the mixed subtraction process, so that the seismic data obtained after the mixed suppression of multiple waves has a significant improvement in the suppression of free surface multiple waves. Compared with the situation of using only one model to suppress free surface multiple waves, after adopting the solution of this embodiment, the residue of free surface multiple waves on the seismic profile is significantly reduced, the signal-to-noise ratio of the data is effectively improved, and the false reflection phase axis is greatly reduced, which is more conducive to the subsequent seismic data inversion and interpretation, so that the data quality related to free surface multiple waves in the entire offshore seismic exploration has been substantially improved, and a more reliable data basis is provided for subsequent geological analysis and other work.

[0065] Other technical features of this embodiment correspond to those of the above embodiment and will not be repeated here.

[0066] Embodiment 8

[0067] In the technical solution of this embodiment, a computer device is provided, including a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to implement the steps of any free surface multiple wave mixing suppression method of the above embodiments.

[0068] In the technical solution of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any free surface multiple wave mixing suppression method of the above embodiments are implemented.

[0069] In the technical solution of this embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of any free surface multiple wave mixing suppression method of the above embodiments.

[0070] The processor may include, but is not limited to, for example, one or more processors or microprocessors. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to implement the method in the above embodiment. The computer readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and the computer readable storage medium may include, but is not limited to, for example, a random access memory (RAM), a read-only memory (ROM), a flash memory, an EPROM memory, an EEPROM memory, a register, a computer storage medium (such as a hard disk, a floppy disk, a solid state drive, a removable disk, a CDROM, a DVDROM, a Blu-ray disc, etc.).

[0071] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0072] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and an input / output device (e.g., a keyboard, a mouse, a speaker, etc.). The processor may communicate with external devices via the I / O bus via a wired or wireless network. In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by the processor to perform the various functions and / or steps of the method in the embodiments described in the present technology.

[0073] Embodiment 9

[0074] Based on the above embodiments, this embodiment provides an application example.

[0075] In offshore seismic exploration, the sea level is a natural good reflection interface, which means that almost all offshore seismic data imaging faces the challenge of multiple waves related to the sea level. The existence of multiple waves affects the imaging of the primary wave, reduces the signal-to-noise ratio of the data, and forms false reflection phase axes in the seismic profile, affecting the interpretation of seismic data. At present, there are many methods to suppress multiple waves, which can be roughly divided into two categories. The first category is to attenuate multiple waves based on the velocity difference between multiple waves and effective waves or the periodicity of multiple waves. Typical methods include Radon filtering, fK filtering, τ-p transformation, beam filtering and predictive deconvolution. In the near-offset part of seismic data and shallow water seismic data, the velocity difference between the primary wave and the free surface multiple waves is very small, and the filtering method based on the velocity difference between the primary wave and the multiple waves is often not ideal. Predictive deconvolution is widely used in suppressing short-period ringing earthquakes, but it is powerless when dealing with long-period multiple waves. Therefore, in current seismic data processing, the second method of predicting the multiple wave model and subtracting the multiple waves from the original data, or the processing flow combining prediction subtraction and filtering is often used to suppress the seabed and near-seabed reflection multiple waves related to the free surface.

[0076] In practice, the multiple wave prediction and subtraction of surface-related multiple wave suppression technology based on seismic wave propagation theory includes two main steps. First, predict surface-related multiple waves; second, adaptively subtract the predicted multiple waves from the original data to achieve the purpose of suppressing multiple waves. According to the different multiple wave prediction methods, this type of multiple wave suppression method is mainly divided into two types. One is to establish a multiple wave model through wave field extrapolation, and then subtract multiple waves from the original data. We can call it WEMA (wave equation multiple attenuation); the other is to predict multiple waves by finding the target seismic trace, using the convolution method, and subtracting multiple waves from the original seismic record. The industry calls this data-driven multiple wave suppression technology SRME (surface related multiple elimination).

[0077] When suppressing multiple waves, WEMA and SRME have different theoretical foundations, and the effects of suppressing multiple waves are also different. When dealing with free surface multiple wave attenuation, each has its own unique advantages and limitations. In this paper, we propose a method of using SRME and WEMA to jointly predict multiple waves and hybridly use adaptive subtraction of multiple wave models to combine the advantages of SRME and WEMA techniques to achieve better multiple wave suppression effects.

[0078] SRME, or free surface related multiples attenuation technique. SRME, proposed by Vercschuur et al. in 1992, is a data-driven multiples suppression technique. Currently, SRME and extended SRME techniques are widely used in seismic data processing to suppress free surface multiples and interlayer multiples. It is based on a simple and powerful concept of convolving two seismic traces with a common reflection point on the multiple reflection surface to generate multiples associated with the reflection point. It can predict all free surface related multiples.

[0079] Figure 3 The basic principle of the SRME method is shown. s A seismic wave was excited at X r A surface-related multiple wave is recorded at X. It has experienced at least one downward reflection at the surface (in this case A) during its propagation. This surface-related multiple wave event can be regarded as a combination of two events: one is at X s The other event is excited at A and recorded at X1(t). rThe two events x1(t) and x2(t) are recorded independently during the seismic acquisition. Then, the multiple waves can be predicted by convolving the two recorded events.

[0080] m SRME (t) = x1(t)*x2(t)

[0081] Next, the predicted multiple wave model is adaptively subtracted from the input data to achieve the purpose of suppressing multiple waves.

[0082] x o (t) = x i (t)-f(t)*m SRME (t)

[0083] Where: x o (t) is the seismic data after multiple wave attenuation, x i (t) is the input seismic data containing multiple waves, f(t) is the adaptive filter operator, which is obtained by the following formula:

[0084] argmin‖x i (t)-f(t)*m SRME (t) ‖2

[0085] Figure 3 is a schematic diagram of the SRME method. Figure 4 It is a schematic diagram of multiple wave prediction and subtraction using the SRME method, including input records, multiple waves predicted by SRME, records after subtracting multiple waves, and subtracted multiple waves.

[0086] The method is completely data-driven, meaning that no auxiliary prior information is required and all multiples associated with the water surface can be predicted. However, like any other multiple suppression technique, SRME has its own limitations:

[0087] (1) Limited aperture: Modeling the most distant multiples may require unrecorded data beyond the receiver range, especially when the data structure is complex;

[0088] (2) Directivity effect: Both the source and the receiver (even if the ghost waves are eliminated) are anisotropic. This leads to incident angle-dependent sub-wave characteristics, which greatly reduces the effectiveness of the adaptive subtraction process in the long offset range (stack of events with different incident angles);

[0089] (3) Strict spatial sampling requirements: In order to find matching convolution traces, regular spatial sampling and sufficient sampling density are required. Irregular sampling or undersampling of seismic data will cause multiple wave prediction errors.

[0090] (4) Slightly poor prediction of seafloor reflection multiple waves: Compared with the wave field extrapolation (WEMA) method, the free surface multiple wave suppression effect is slightly worse.

[0091] WEMA, or wave equation multiple attenuation technology. WEMA is essentially the inverse process of wave equation migration. It uses velocity models and seismic migration modeling to predict multiple wave models. The physical process is to use wave field extrapolation to allow the recorded seismic wave field to propagate a round trip in the seawater layer, so that the original primary reflection wave becomes a secondary reflection wave, and the order of each specific order of multiple waves is increased by one. Then, the multiple waves obtained by the above process are subtracted from the original wave field to achieve the purpose of attenuating the multiple waves. According to Morley's statement, for the realization of multiple wave model prediction, if expressed in a simplified form, including wave field extrapolation of both uplink and downlink processes,

[0092] m WEMA (t) = x(t)*g d (X r ,X′)*R s (x)*g u (X′,X″)*R b (x)

[0093] Where: x(t) is the recorded earthquake data, g d (X r ,X′) is the r The wave field extrapolator from the position to the seafloor (X′, z) downward, R s (x) is the position (X r ,0) of the water surface, g u (X′,X″) is the wave field extrapolator from the seabed position (X′,z) to the water surface position (X″,0), R b (x) is the reflection coefficient of the sea floor at position (X′,z).

[0094] Similar to the SRME method, the predicted multiple wave model is then adaptively subtracted from the input data to achieve the purpose of suppressing multiple waves.

[0095] x o (t) = x i (t)-f(t)*m WEMA (t)

[0096] Where: x o (t) is the seismic data after multiple wave attenuation, x i (t) is the input seismic data containing multiple waves, f(t) is the adaptive filter operator, which is obtained by the following formula:

[0097] argmin‖x i (t)-f(t)*mWEMA (t) ‖2

[0098] Figure 5 This is a schematic diagram of the WEMA method. Figure 6 It is a schematic diagram of multiple wave prediction and subtraction using the WEMA method, including input records, multiple waves predicted by WEMA, records after subtracting multiple waves, and subtracted multiple waves.

[0099] With the additional information of the water layer model, WEMA has more relaxed restrictions on surface spatial sampling than SRME. However, the traditional implementation of wave equation extrapolation and adaptive subtraction suffers from several disadvantages:

[0100] (1) Sampling requirements still exist: Due to insufficient sampling in the offset dimension, the prediction effect is poor when there is spatial aliasing;

[0101] (2) The influence of bottom complexity on multiple wave prediction: Since the multiple wave simulation does not fully conform to the real bottom geometry, the prediction performs poorly in the presence of short-period multiple waves from the inclined bottom;

[0102] (3) Incapable of dealing with multiple waves between layers below the seabed: When dealing with multiple waves, the wave field extrapolation method only considers the multiple propagation of seismic waves in the water layer. Therefore, this method cannot simulate the multiple waves between layers of reflection surfaces below the seabed that are related to the water surface.

[0103] Since SRME and WEMA each have their own advantages and limitations in processing water surface related multiple waves, the present invention proposes a method of using SRME and WEMA to jointly predict multiple waves, and hybridly use adaptive subtraction of multiple wave models to combine the advantages of SRME and WEMA technology to achieve better multiple wave suppression effect.

[0104] For seismic waves, the sea level is a natural good reflection interface, which leads to the challenge of multiple waves related to the sea level in almost all offshore seismic exploration. The existence of multiple waves affects the imaging of the primary wave, reduces the signal-to-noise ratio of the data, and forms false reflection phase axes in the seismic profile, affecting the interpretation of seismic data. At present, there are many methods to suppress multiple waves, which can be roughly divided into two categories. The first category is to attenuate multiple waves based on the velocity difference between multiple waves and effective waves or the periodicity of multiple waves. Typical methods include Radon filtering, fK filtering, τ-p transformation, beam filtering and predictive deconvolution. In shallow water seismic data, the velocity difference between the primary wave and the free surface multiple waves is very small. The filtering method based on the velocity difference between the primary wave and the multiple waves is often not ideal; moreover, this type of filtering method basically has no good multiple wave suppression effect on close offset data. Predictive deconvolution is widely used in suppressing short-period ringing earthquakes, but it is powerless when dealing with long-period multiple waves. Therefore, in current seismic data processing, the second method of predicting the multiple wave model and subtracting the multiple waves from the original data, or a processing flow combining prediction subtraction and filtering is often used to suppress free surface multiple waves.

[0105] In practice, the surface-related multiple wave suppression technology based on multiple wave prediction and subtraction based on seismic wave propagation theory includes two main steps. First, predict surface-related multiple waves; second, adaptively subtract the predicted multiple waves from the original data to achieve the purpose of suppressing multiple waves. According to the different multiple wave prediction methods, this type of multiple wave suppression method is mainly divided into two types. One is to establish a multiple wave model through wave field extrapolation, and then subtract multiple waves from the original data, which we can call WEMA; the other is to predict multiple waves by finding the target seismic trace, using the convolution method, and subtracting multiple waves from the original seismic record. The industry calls this data-driven multiple wave suppression technology SRME.

[0106] When suppressing multiple waves, WEMA and SRME have different theoretical foundations, and the effects of suppressing multiple waves are also different. When dealing with free surface multiple wave attenuation, each has its own unique advantages and limitations. In this invention, we propose a method of using SRME and WEMA to jointly predict multiple waves, and hybrid use of adaptive subtraction of multiple wave models to combine the advantages of SRME and WEMA techniques to achieve better multiple wave suppression effect.

[0107] Preprocess the seismic data. Whether it is SRME or WEMA method to predict multiple wave models, data preprocessing is required. The preprocessing includes removing source characteristics from seismic data, suppressing bubble noise, ghost waves, and suppressing seismic noise such as Schulte waves and guided waves, etc., in order to improve the quality of seismic data and provide high-quality input data for multiple wave prediction.

[0108] Use the WEMA method to predict the multiple wave model. WEMA is essentially the inverse process of wave equation migration. It uses velocity models and seismic migration modeling to predict the multiple wave model. The physical process is to use wave field extrapolation to allow the recorded seismic wave field to propagate a round trip in the seawater layer. In this way, the original primary reflection wave becomes a secondary reflection wave, and the order of each specific order of multiple waves is increased by one. Then, the multiple waves obtained by the above process are subtracted from the original wave field to achieve the purpose of attenuating the multiple waves. According to Morley's statement, the realization of the prediction of the multiple wave model, if expressed in a simplified form, includes the wave field extrapolation of the uplink and downlink processes,

[0109] m WEMA (t) = x(t)*g d (X r ,X′)*R s (x)*g u (X′,X″)*R b (x)

[0110] Where: x(t) is the recorded earthquake data, g d (X r ,X′) is the r The wave field extrapolator from the position to the seafloor (X′, z) downward, R s (x) is the position (X r ,0) of the water surface, g u (X′,X″) is the wave field extrapolator from the seabed position (X′,z) to the water surface position (X″,0), R b (x) is the reflection coefficient of the sea floor at position (X′,z).

[0111] Predict multiple wave models using SRME method. SRME is a data-driven multiple wave suppression technique. Currently, SRME and extended SRME techniques are widely used in seismic data processing to suppress free surface multiple waves and interlayer multiple waves. It is based on a simple but powerful concept of convolving two seismic traces with a common reflection point on the multiple wave reflection surface to generate multiple waves associated with the reflection point. It can predict all multiple waves associated with the free surface.

[0112] To predict the multiple wave model using SRME, first remove the first arrival of the seismic data on the preprocessed gathers. Then use the two seismic traces x1(t) and x2(t) involved in the convolution to predict the multiple waves.

[0113] m SRME (t) = x1(t)*x2(t)

[0114] The multiple wave models predicted by WEMA and SRME are used to suppress the multiple waves.

[0115] The multiple wave model m was predicted by WEMA and SRME respectively. WEMA (t) and m SRME (t). Next, the task of hybrid adaptive subtraction is to find a non-stationary filter f(t) to minimize the objective function.

[0116] ‖x i (t)-f(t)*m(t)‖2

[0117] Where: x i (t) is the input record, and m(t) is the multiple wave model predicted by WEMA or SRME. Therefore, the non-stationary filter f(t) can be obtained by the following formula:

[0118] argmin[‖x i (t)-f(t)*m WEMA (t)‖2||‖x i (t)-f(t)*m WEMA (t)‖2]

[0119] In fact, for each sliding time window, the present invention will subtract the WEMA predicted multiple wave model and the SRME predicted multiple wave model from the input data respectively, and then select the one with smaller energy as the final output record, that is, hybrid adaptive suppression of multiple waves,

[0120] x o (t) = argmin{[x i (t)-f(t)*m WEMA (t)]||[x i (t)-t(t)*m SRME (t)]}

[0121] Figure 7 The hybrid subtraction result is shown, which combines the advantages of SRME and WEMA and provides better multiple suppression results. The attenuation effect of the seabed reflection multiples is better than the SRME result, while the attenuation effect of the near-seabed inter-reflector multiples is better than the WEMA result. Figure 7 Includes: input records, SRME predicted multiples, WEMA predicted multiples, output records, subtracted multiples.

[0122] The present invention provides a hybrid prediction and suppression technology for water surface related multiple waves in offshore seismic exploration, which predicts multiple waves respectively using WEMA and SRME methods, and mixes and subtracts these two multiple wave models from the input data, thereby achieving a better multiple wave suppression effect than using only WEMA or SRME. The specific implementation process is as follows:

[0123] 1. Preprocess the original seismic data to prepare data for multiple wave prediction.

[0124] 2. Input the earthquake data obtained in step 1 and use the WEMA method to predict the multiple wave model.

[0125] 3. Input the seismic data obtained in step 1, define the excision parameters, and excise the first arrival wave of the seismic data.

[0126] 4. The seismic data obtained in step 3 is used to predict the multiple wave model using the SRME method.

[0127] 5. The seismic data obtained in step 1 and the multiple wave models obtained in steps 2 and 4 are used to obtain the filtering operator under the least squares constraint.

[0128] 6. A sliding time window for adaptive subtraction is used to input the seismic data obtained in step 1, the multiple wave models obtained in step 2 and step 4, and the filter operator obtained in step 5, and the WEMA predicted multiple wave model and the SRME predicted multiple wave model are subtracted from the input data.

[0129] 7. Subtract the multiple wave data in step 6 to obtain the seismic data after mixed suppression of multiple waves.

[0130] In offshore seismic exploration, since the sea level is a natural good reflection interface, almost all offshore seismic explorations face the challenge of multiple waves related to the sea level. The existence of multiple waves affects the imaging of the primary wave, reduces the signal-to-noise ratio of the data, and will form false reflection phase axes in the seismic profile, affecting the inversion and interpretation of seismic data. Therefore, suppressing multiple waves has always been one of the main challenges of seismic data imaging. At present, when suppressing multiple waves related to the water surface, the main methods used are multiple wave prediction and adaptive subtraction such as SRME and WEMA. However, SRME and WEMA have their own limitations. The present invention proposes to comprehensively utilize SRME and WEMA to predict the multiple wave model related to the water surface, and mix and adaptively subtract the multiple waves from the original data to achieve the purpose of suppressing multiple waves related to the water surface. The present invention overcomes the limitations of the single prediction and subtraction method of SRME or WEMA, combines the advantages of both, and has a better effect of suppressing multiple waves.

[0131] Compared with the SRME method, a technical solution related to the present invention, the present invention is more thorough in suppressing the seabed-water surface multiple waves. Figure 8 The remnants of free surface multiple waves can be clearly seen on the superimposed section of the data after the multiple waves are suppressed by the medium SRME, as indicated by the arrow. After suppressing the multiple waves by the hybrid prediction and subtraction method of the present invention, the free surface multiple waves are suppressed more thoroughly on the superimposed section.

[0132] Compared with the WEMA method of the second technical solution related to the present invention, the present invention has a better effect in suppressing the layers near the seabed. Figure 8 The remnants of the multiple waves between the near-sea bottom layers at the position circled by the ellipse can be clearly seen on the superimposed section of the data after the multiple waves are suppressed by the WEMA method. After suppressing the multiple waves by the hybrid prediction and subtraction method of the present invention, these inter-layer multiple waves on the superimposed section are better suppressed.

[0133] Figure 8 Schematic diagram for comparing the effects of suppressing multiple waves using different methods, including: input data stacking profile, SRME suppressing multiple waves and then stacking, WEMA suppressing multiple waves and then stacking, and hybrid prediction and subtracting multiple waves and stacking.

[0134] This application example uses WEMA and SRME to jointly predict multiple waves; obtains a non-stationary filter operator for adaptive subtraction under the least squares constraint; and adaptively subtracts the multiple waves predicted by WEMA and SRME from the seismic data to suppress the multiple waves related to the water surface.

[0135] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0136] It should be noted that, in the present invention, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0137] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A free surface multiple wave mixing suppression method, characterized in that: The method comprises: Based on the WEMA method, the preprocessed data is used to predict the multiple wave model and the WEMA multiple wave model is obtained; Based on the SRME method, the preprocessed data is used to predict the multiple wave model and the SRME multiple wave model is obtained; The pre-processed seismic data is mixed and subtracted from the WEMA multiple wave model and the SRME multiple wave model to obtain seismic data after mixed suppression of multiple waves.

2. The free surface multiple wave mixing suppression method according to claim 1, characterized in that: Before the step of using the pre-processed data to perform multiple wave model prediction, the method further comprises: Preprocessing the original seismic data to obtain preprocessed seismic data; Wherein, the preprocessing includes: removing source characteristics, suppressing bubble noise, and suppressing ghost waves.

3. The free surface multiple wave mixing suppression method according to claim 1, characterized in that: The step of using the pre-processed data to perform multiple wave model prediction based on the SRME method includes: removing the first arrival wave of the preprocessed seismic data; Based on the SRME method, the preprocessed seismic data with the first arrival wave removed are processed to obtain the SRME multiple wave model.

4. The free surface multiple wave mixing suppression method according to claim 1, characterized in that: The step of mixing and subtracting the WEMA multiple wave model and the SRME multiple wave model from the pre-processed seismic data to obtain seismic data after mixed suppression of multiple waves comprises: The WEMA multiple wave model and the SRME multiple wave model are respectively subtracted from the preprocessed seismic data, and the minimum values ​​in the results are mixed to obtain seismic data after mixed suppression of multiple waves.

5. The free surface multiple wave mixing suppression method according to claim 4, characterized in that: The step of subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data respectively and mixing the minimum values ​​in the results to obtain seismic data after mixed suppression of multiple waves comprises: In a preset sliding time window, the WEMA multiple wave model and the SRME multiple wave model are respectively subtracted from the preprocessed seismic data to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model; Within the preset sliding time window, the minimum value of the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model is used as the seismic data after mixed suppression of multiple waves in the preset sliding time window.

6. The free surface multiple wave mixing suppression method according to claim 5, characterized in that: The step of subtracting the WEMA multiple wave model and the SRME multiple wave model from the preprocessed seismic data to obtain the difference between the preprocessed seismic data and the WEMA multiple wave model and the difference between the preprocessed seismic data and the SRME multiple wave model comprises: subtracting the convolution of the WEMA multiple wave model with a non-stationary filter operator from the preprocessed seismic data; The convolution of the SRME multiple model with a non-stationary filter operator is subtracted from the pre-processed seismic data.

7. A free surface multiple wave mixing suppression device, characterized in that: The device comprises: WEMA multiple wave prediction module, used to predict multiple wave models based on the WEMA method using preprocessed data to obtain the WEMA multiple wave model; SRME multiple wave prediction module, used to predict multiple wave models using preprocessed data based on the SRME method to obtain SRME multiple wave models; The parallel subtraction module is used to perform mixed subtraction of the WEMA multiple wave model and the SRME multiple wave model on the pre-processed seismic data to obtain seismic data after mixed suppression of multiple waves.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the free-surface multiple wave mixing suppression method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the free surface multiple wave mixing suppression method as claimed in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the free surface multiple wave mixing suppression method as claimed in any one of claims 1 to 6 are implemented.

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