Time-lapse seismic data processing method and device and computing equipment

Abstract

The invention discloses a time-lapse seismic data processing method, a time-lapse seismic data processing device and computing equipment. The time-lapse seismic data processing method comprises the steps of inputting basic seismic data, basic difference data, monitoring seismic data and monitoring difference data into a preset attenuation algorithm; the basic difference data is the difference data between the basic seismic data and the data after 3D adaptive multiple attenuation, and the monitoring difference data is the difference data between the monitoring seismic data and the data after 3D adaptive multiple attenuation; controlling an optimization process of a target matching operator by using a target function of a preset attenuation algorithm; the target function is constructed according to the basic seismic data, the basic difference data, the monitoring seismic data, the monitoring difference data and a target matching operator; obtaining basic seismic data and monitoring seismic data which are processed by a preset attenuation algorithm and subjected to 4D consistency multiple matching attenuation; by means of the mode, the effect that only oil reservoir difference information is reserved in attenuated data, and multiple waves and noise differences influencing fidelity are suppressed can be achieved.

Description

Technical Field

[0001] The present application relates to the technical field of seismic exploration and oil and gas field development, and in particular to a time-lapse seismic data processing method, apparatus, computing equipment, computer storage medium, and computer program product. Background Art

[0002] Time-lapse seismic is a method of quantitatively evaluating reservoir fluid dynamics during residual oil development by collaboratively processing seismic data from two different periods. It is one of the key technologies for improving oil and gas recovery by quantitatively evaluating reservoir fluid dynamics during residual oil development in the target area by using the amplitude difference between seismic data before and after oil reservoir production.

[0003] The interpretation accuracy of time-lapse seismic data mainly depends on two aspects: consistent collaborative processing and differential noise suppression. Consistent processing depends on whether the basic data have the same acquisition parameters, while differential noise suppression comes from multiple factors, including initial differences and processing errors. In marine seismic data processing, multiple suppression has the greatest impact on amplitude and frequency changes. For time-lapse seismic, the requirements for multiple suppression are much higher than those for traditional 3D seismic data processing. The specific reasons are: First, the sensitivity of time-lapse data. The core of time-lapse seismic is to extract weak differential signals between two explorations (such as fluid migration and pressure changes). Residual or erroneous suppression of multiples may cause the differential signals to be submerged in noise, or even produce false time-lapse responses. Second, the challenge of non-repetitive acquisition. In actual time-lapse exploration, due to environmental, equipment, or cost constraints, the source locations, receiver layouts, or background noise of the two seismic acquisitions may not be completely consistent, resulting in a decrease in the applicability of traditional multiple subtraction between the two data sets. Third, the high-fidelity requirement of time-lapse data. Conventional multiple suppression algorithms may over-rely on stratigraphic assumptions (such as horizontally layered media) or sacrifice primary wave energy. Time-lapse processing must suppress multiples while retaining the amplitude and phase information of the primary wave to the greatest extent possible to ensure the reliability of the quantitative interpretation of time-lapse differences.

[0004] Based on this, there is an urgent need for a time-lapse seismic data processing method that only retains reservoir difference information while suppressing multiple waves and noise differences that affect fidelity. Summary of the Invention

[0005] In view of the above problems, the present application is proposed to provide a time-lapse seismic data processing method, apparatus, computing device, computer storage medium and computer program product that overcome the above problems or at least partially solve the above problems.

[0006] According to one aspect of the present application, a time-lapse seismic data processing method is provided, comprising:

[0007] Inputting basic seismic data and basic difference data thereof and monitoring seismic data and monitoring difference data thereof into a preset attenuation algorithm; wherein the basic difference data is the difference data between the basic seismic data and the data after 3D adaptive multiple wave attenuation, and the monitoring difference data is the difference data between the monitoring seismic data and the data after 3D adaptive multiple wave attenuation;

[0008] Using the objective function corresponding to the preset attenuation algorithm to control the optimization process of the target matching operator to obtain an optimized target matching operator;

[0009] wherein the objective function is constructed based on the basic seismic data, the basic difference data, the monitored seismic data, the monitored difference data, and the target matching operator;

[0010] The basic seismic data and monitoring seismic data after 4D consistent multiple wave matching attenuation obtained by the preset attenuation algorithm are obtained. The preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing.

[0011] Optionally, the objective function is specifically a weighted sum function based on a first function term and a second function term; the first function term is determined based on monitored seismic data, a target matching operator, and monitored difference data; the second function term is determined based on basic seismic data, monitored seismic data, basic difference data, a target matching operator, and monitored difference data.

[0012] Optionally, the objective function formula is specifically:

[0013]

[0014] Where Π represents the objective function, E′ Base represents the basic seismic data after 4D consistent multiple wave matching attenuation, E′ Monitor represents the monitored seismic data after 4D consistent multiple wave matching attenuation, represents the least squares subtraction operation, d Monitor represents the monitored earthquake data, f match represents the target matching operator, M monitor represents the monitoring difference data, * represents the convolution operation, λ represents the weight coefficient, d Base represents basic seismic data, M Base Indicates basic difference data.

[0015] Optionally, the method further comprises:

[0016] performing 3D adaptive multiple wave attenuation processing on the basic seismic data and the monitoring seismic data respectively to obtain basic attenuated data and monitoring attenuated data;

[0017] determine the base difference data according to the base seismic data and the base deconvolved data;

[0018] determine the monitoring difference data according to the monitoring seismic data and the monitoring deconvolved data.

[0019] Optionally, the 3D adaptive multiple deconvolution processing of the base seismic data and the monitoring seismic data respectively to obtain the base deconvolved data and the monitoring deconvolved data further comprises:

[0020] determine a base predicted multiple model according to the base seismic data and a corresponding information propagation operator; and calculate the base deconvolved data according to the base seismic data, the base predicted multiple model and a corresponding matching operator;

[0021] determine a monitoring predicted multiple model according to the monitoring seismic data and a corresponding information propagation operator; and calculate the monitoring deconvolved data according to the monitoring seismic data, the monitoring predicted multiple model and a corresponding matching operator.

[0022] Optionally, the base deconvolved data is calculated in the following manner:

[0023]

[0024] wherein, E Base represents the base deconvolved data, d Base represents the base seismic data, f Base represents a matching operator corresponding to the base seismic data, m Base represents the base predicted multiple model.

[0025] The monitoring deconvolved data is calculated in the following manner:

[0026]

[0027] wherein, E Monitor represents the monitoring deconvolved data, d Monitor represents the monitoring seismic data, f Monitor represents a matching operator corresponding to the monitoring seismic data, m Monitor represents the monitoring predicted multiple model.

[0028] According to another aspect of the present application, a time-lapse seismic data processing device is provided, comprising:

[0029] a processing module adapted to input basic seismic data and basic difference data thereof and monitoring seismic data and monitoring difference data thereof into a preset attenuation algorithm; wherein the basic difference data is difference data between the basic seismic data and data after 3D adaptive multiple wave attenuation, and the monitoring difference data is difference data between the monitoring seismic data and data after 3D adaptive multiple wave attenuation;

[0030] an optimization module adapted to control the optimization process of the target matching operator using the objective function corresponding to the preset attenuation algorithm to obtain an optimized target matching operator;

[0031] wherein the objective function is constructed based on the basic seismic data, the basic difference data, the monitored seismic data, the monitored difference data, and the target matching operator;

[0032] The processing module is further adapted to obtain basic seismic data and monitoring seismic data obtained by the preset attenuation algorithm after 4D consistent multiple wave matching attenuation, wherein the preset attenuation algorithm performs 4D consistent multiple wave matching attenuation processing using the optimized target matching operator.

[0033] Optionally, the objective function is specifically a weighted sum function based on a first function term and a second function term; the first function term is determined based on monitored seismic data, a target matching operator, and monitored difference data; the second function term is determined based on basic seismic data, monitored seismic data, basic difference data, a target matching operator, and monitored difference data.

[0034] Optionally, the objective function formula is specifically:

[0035]

[0036] Where Π represents the objective function, E′ Base represents the basic seismic data after 4D consistent multiple wave matching attenuation, E′ Monitor represents the monitored seismic data after 4D consistent multiple wave matching attenuation, represents the least squares subtraction operation, d Monitor represents the monitored earthquake data, f match represents the target matching operator, M Monitor represents the monitoring difference data, * represents the convolution operation, λ represents the weight coefficient, d Base represents basic seismic data, M Base Indicates basic difference data.

[0037] Optionally, the processing module is further adapted to:

[0038] performing 3D adaptive multiple attenuation on the base seismic data and the monitoring seismic data respectively to obtain base attenuated data and monitoring attenuated data;

[0039] determining the base difference data according to the base seismic data and the base attenuated data;

[0040] determining the monitoring difference data according to the monitoring seismic data and the monitoring attenuated data.

[0041] Optionally, the processing module is further adapted to:

[0042] determining a base predicted multiple model according to the base seismic data and a corresponding information propagation operator; and calculating the base attenuated data according to the base seismic data, the base predicted multiple model and a corresponding matching operator;

[0043] determining a monitoring predicted multiple model according to the monitoring seismic data and a corresponding information propagation operator; and calculating the monitoring attenuated data according to the monitoring seismic data, the monitoring predicted multiple model and a corresponding matching operator.

[0044] Optionally, the base attenuated data is calculated in the following manner:

[0045]

[0046] wherein E Base represents the base attenuated data, d Base represents the base seismic data, f Base represents a matching operator corresponding to the base seismic data, m Base represents the base predicted multiple model.

[0047] the monitoring attenuated data is calculated in the following manner:

[0048]

[0049] wherein E Monitor represents the monitoring attenuated data, d Monitor represents the monitoring seismic data, f Monitor represents a matching operator corresponding to the monitoring seismic data, m Monitor represents the monitoring predicted multiple model.

[0050] According to yet another aspect of the present application, there is provided a computing device comprising a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface being in communication with each other via the communication bus;

[0051] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned time-lapse seismic data processing method.

[0052] According to another aspect of the present application, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to perform operations corresponding to the above-mentioned time-lapse seismic data processing method.

[0053] According to another aspect of the present application, a computer program product is provided, comprising at least one executable instruction, wherein the executable instruction enables a processor to perform operations corresponding to the above-mentioned time-lapse seismic data processing method.

[0054] According to the time-lapse seismic data processing method, apparatus, computing device, computer storage medium and computer program product provided in the embodiments of the present application, first, the basic seismic data and its corresponding basic difference data and the monitoring seismic data and its corresponding monitoring difference data are input into a preset attenuation algorithm; secondly, the objective function corresponding to the preset attenuation algorithm is used to control the optimization process of the target matching operator to obtain the optimized target matching operator; wherein, the objective function is constructed based on the basic seismic data, the basic difference data, the monitoring seismic data, the monitoring difference data and the target matching operator; finally, the basic seismic data and the monitoring seismic data after 4D consistent multiple wave matching attenuation obtained by the preset attenuation algorithm are obtained, and the preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing. Through the above method, in addition to considering the differences between the basic seismic data and the monitoring seismic data, the differences between the data attenuated after 3D adaptive attenuation are also considered, so that the basic seismic data and the monitoring seismic data are subjected to 4D consistent multiple wave matching attenuation processing, abandoning the traditional independent processing scheme of time-lapse seismic data, and performing consistent matching between the original data without multiple wavefronts and the corresponding 3D adaptively attenuated data, so as to achieve the true consistent collaborative processing requirements of time-lapse seismic, effectively enhance the 4D effective signal strength in the difference between the two sets of seismic data, suppress the surrounding 4D noise, and achieve the effect of retaining only reservoir difference information in the attenuated data while suppressing the multiple waves and noise differences that affect the fidelity.

[0055] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0057] Figure 1 A flow chart of a time-lapse seismic data processing method provided by an embodiment of the present application is shown;

[0058] Figure 2 A flow chart of a time-lapse seismic data processing method provided by another embodiment of the present application is shown;

[0059] Figure 3 This is the cross-section of the Base data before the multiple waves decay;

[0060] Figure 4 This is the profile of Monitor data before multiple waves attenuate;

[0061] Figure 5 This is the cross-section of the Base data after 3D adaptive multiple wave attenuation;

[0062] Figure 6 This is the Monitor data profile after 3D adaptive multiple wave attenuation;

[0063] Figure 7 This is the profile of the multiple wave noise attenuated by the Base data;

[0064] Figure 8 This is the multiple noise profile of the attenuated Monitor data;

[0065] Figure 9 This is a cross-section of the Base data after 4D consistency multiple wave matching attenuation;

[0066] Figure 10 Monitor data profile after attenuation for 4D consistency multiple matching;

[0067] Figure 11 This is the difference profile of the Base data and Monitor data after 3D adaptive multiple wave attenuation;

[0068] Figure 12 This is the difference profile of the Base data and Monitor data after 4D consistent multiple wave matching and attenuation;

[0069] Figure 13 Schematic diagram of the global NRMS of the Base data and Monitor data after 3D adaptive multiple wave subtraction attenuation;

[0070] Figure 14 a global NRMS diagram for 4D consistent multiple matching and attenuation of the base data and the monitor data;

[0071] Figure 15 A functional structure schematic diagram of a time-lapse seismic data processing device provided by an embodiment of the present application is shown.

[0072] Figure 16 A structure schematic diagram of a computing device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0073] Exemplary embodiments of the present application will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the drawings, it is understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present application can be more thoroughly understood and so that the scope of the present application can be completely conveyed to those skilled in the art.

[0074] Figure 1 A flowchart of a time-lapse seismic data processing method provided by an embodiment of the present application is shown. As shown in the flowchart, the method comprises the following steps: Figure 1

[0075] In step S110, the base seismic data and its base difference data and the monitor seismic data and its monitor difference data are input to a preset attenuation algorithm.

[0076] The base difference data is the difference data between the base seismic data and the data obtained by performing 3D adaptive multiple attenuation on the base seismic data, and the monitor difference data is the difference data between the monitor seismic data and the data obtained by performing 3D adaptive multiple attenuation on the monitor seismic data.

[0077] The base difference data corresponding to the base seismic data and the monitor difference data corresponding to the monitor seismic data are obtained. For the same target area, 4D seismic data of different periods are collected to obtain the base seismic data and the monitor seismic data. The base seismic data is specifically seismic data collected before reservoir exploitation, and the monitor seismic data is specifically seismic data collected after reservoir exploitation. At the same time, the base difference data corresponding to the base seismic data is obtained. The base difference data is specifically the difference data between the base seismic data and the data obtained by performing 3D adaptive multiple attenuation on the base seismic data. The monitor difference data corresponding to the monitor seismic data is obtained. The monitor difference data is specifically the difference data between the monitor seismic data and the data obtained by performing 3D adaptive multiple attenuation on the monitor seismic data.

[0078] ​The preset attenuation algorithm is used to perform 4D consistent multiple wave matching attenuation processing on seismic data. Its input includes: basic seismic data, basic difference data, monitoring seismic data and monitoring difference data. Its output includes: basic seismic data after 4D consistent multiple wave matching attenuation and monitoring seismic data after 4D consistent multiple wave matching attenuation.

[0079] Step S120 , using the objective function corresponding to the preset attenuation algorithm to control the optimization process of the target matching operator, to obtain an optimized target matching operator.

[0080] The preset attenuation algorithm has a corresponding objective function. The objective function is constructed based on the basic seismic data, basic difference data, monitoring seismic data, monitoring difference data, and a target matching operator. The objective function controls the optimization process of the target matching operator. The optimization goal of the target matching operator is to make the objective function meet a specified condition, such as minimizing the objective function. When the objective function meets the specified condition, the optimization process of the target matching operator is terminated.

[0081] Step S130 , obtaining basic seismic data and monitoring seismic data after 4D consistent multiple wave matching and attenuation obtained by a preset attenuation algorithm.

[0082] Among them, the preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing. The preset attenuation algorithm realizes 4D consistent multiple wave matching attenuation processing on the basic seismic data and the monitoring seismic data according to the optimized target matching operator when the objective function reaches the specified conditions, and outputs the basic seismic data after 4D consistent multiple wave matching attenuation and the monitoring seismic data after 4D consistent multiple wave matching attenuation.

[0083] To sum up, according to the time-lapse seismic data processing method of the embodiment of the present application, in addition to considering the difference between the basic seismic data and the monitoring seismic data, the difference between the data attenuated after 3D adaptive attenuation is also considered, thereby performing 4D consistent multiple wave matching attenuation processing on the basic seismic data and the monitoring seismic data, abandoning the traditional independent processing scheme of time-lapse seismic data, and performing consistency matching on the original data without multiple wavefronts and the corresponding 3D adaptively attenuated data, so as to achieve the true consistency collaborative processing requirements of time-lapse seismic, effectively improve the 4D effective signal strength in the difference between the two sets of seismic data, suppress the surrounding 4D noise, and achieve the effect of retaining only the reservoir difference information in the attenuated data and suppressing the multiple waves and noise differences that affect the fidelity.

[0084] Figure 2 FIG. 1 is a flow chart showing a time-lapse seismic data processing method according to another embodiment of the present invention. Figure 2 As shown, the method includes the following steps:

[0085] Step S210, perform 3D adaptive multiple wave attenuation processing on the basic seismic data and the monitoring seismic data respectively to obtain basic attenuated data and monitoring attenuated data; determine basic difference data based on the basic seismic data and the basic attenuated data; determine monitoring difference data based on the monitoring seismic data and the monitoring attenuated data.

[0086] 3D adaptive multiple wave attenuation processing refers to the use of information in the data itself to perform multiple wave attenuation processing. A data-driven method is used to calculate the predicted multiple wave models corresponding to the basic seismic data and the predicted multiple wave models corresponding to the monitored seismic data. The respective predicted multiple wave models are then attenuated through 3D adaptive matching subtraction, completing the 3D adaptive multiple wave attenuation processing. Afterwards, the data before and after 3D adaptive attenuation are subtracted to obtain the actual attenuated data, thereby obtaining the basic difference data and monitoring difference data.

[0087] Among them, 3D adaptive multiple wave attenuation processing is performed on the basic seismic data to obtain basic attenuated data. This step specifically includes: determining the basic predicted multiple wave model based on the basic seismic data and the corresponding information propagation operator; and calculating the basic attenuated data based on the basic seismic data, the basic predicted multiple wave model and the corresponding matching operator.

[0088] Specifically, the SRME (Surface-Related Multiple Elimination) method is used to predict the multiple wave model using the information of the seismic data itself. The calculation method of the basic prediction multiple wave model is as follows:

[0089] m Base =d BaSe *γ d_Base

[0090] Among them, m Base represents the basic prediction multiple wave model, d Base represents the basic seismic data, γ d_Base It represents the information propagation operator corresponding to the basic seismic data, that is, the operator containing the wavefield propagation information of the seismic data between the shot point and the receiver point. * is the convolution operator symbol.

[0091] Afterwards, the basic attenuated data is calculated using the basic seismic data, the basic predicted multiple wave model, and the matching operator corresponding to the basic seismic data. The calculation method is as follows:

[0092]

[0093] Among them, E Base represents the data after basic attenuation, d Base represents the basic seismic data, fBase represents the matching operator corresponding to the basic seismic data, m Base Represents the basic prediction multiple wave model, * is the convolution operator symbol, Represents the least squares subtraction operation.

[0094] Accordingly, 3D adaptive multiple wave attenuation processing is performed on the monitoring seismic data to obtain the monitoring attenuated data. This step specifically includes: determining the monitoring prediction multiple wave model based on the monitoring seismic data and the corresponding information propagation operator; and calculating the monitoring attenuated data based on the monitoring seismic data, the monitoring prediction multiple wave model and the corresponding matching operator.

[0095] Specifically, the SRME (Surface-Related Multiple Elimination) method is used to predict the multiple wave model using the information of the seismic data itself. The calculation method of the monitoring and prediction multiple wave model is as follows:

[0096] m Monitor =d Monitor *γ d_Monitor

[0097] Among them, m Monitor represents the monitoring and prediction multiple wave model, d Monitor represents the monitored earthquake data, γ d_Monitor It represents the information propagation operator corresponding to the monitored seismic data, that is, the operator containing the wavefield propagation information of the seismic data between the shot point and the receiver point. * is the convolution operator symbol.

[0098] Afterwards, the monitoring attenuation data is calculated using the monitoring seismic data, the monitoring prediction multiple wave model, and the matching operator corresponding to the monitoring seismic data. The calculation method is as follows:

[0099]

[0100] Among them, E Monitor Indicates the data after monitoring attenuation, d Monitor represents the monitored earthquake data, f Monitor represents the matching operator corresponding to the monitored earthquake data, m Monitor Indicates the monitoring and prediction multiple wave model, * is the convolution operator symbol, It can be seen that the embodiment of the present application is to perform energy and frequency correction based on the matching operator on the predicted multiple wave models of the basic seismic data and the monitored seismic data.

[0101] Subtract the basic seismic data from the basic attenuated data to obtain the basic difference data. The calculation method is as follows:

[0102] M Base=d Base -E Base

[0103] Among them, M Base Indicates basic difference data, d Base represents basic seismic data, E Base Represents the basic attenuated data.

[0104] Subtract the monitored earthquake data from the monitored attenuation data to obtain the monitored difference data. The calculation method is as follows:

[0105]

[0106] Among them, M Monitor Indicates monitoring difference data, d Monitor Indicates monitoring earthquake data, E Monitor Indicates the data after monitoring attenuation.

[0107] Step S220 , inputting the basic seismic data, basic difference data, monitoring seismic data and monitoring difference data into a preset attenuation algorithm.

[0108] The preset attenuation algorithm is used to perform 4D consistent multiple wave matching attenuation processing on basic seismic data and monitoring seismic data. Its input includes: basic seismic data, basic difference data, monitoring seismic data and monitoring difference data, and its output includes: basic seismic data after 4D consistent multiple wave matching attenuation and monitoring seismic data after 4D consistent multiple wave matching attenuation.

[0109] Step S230 , using the objective function corresponding to the preset attenuation algorithm to control the optimization process of the target matching operator, to obtain an optimized target matching operator.

[0110] The objective function is specifically a weighted sum function based on a first function term and a second function term; the first function term is determined based on the monitored seismic data, the target matching operator, and the monitored difference data; the second function term is determined based on the basic seismic data, the monitored seismic data, the basic difference data, the target matching operator, and the monitored difference data. Specifically, the first function term is used to measure the difference between the monitored seismic data and the monitored difference data processed by the target matching operator, and the second function term is used to measure the difference between the first difference and the second difference, wherein the first difference is the difference between the basic seismic data and the monitored seismic data, and the second difference is the difference between the basic difference data and the monitored difference data processed by the target matching operator.

[0111] Specifically, the formula of the objective function is:

[0112]

[0113]

[0114] Basic seismic data, E′ Monitor represents the monitored seismic data after 4D consistent multiple wave matching attenuation, represents the least squares subtraction operation, d Monitor represents the monitored earthquake data, f match represents the target matching operator, M Monitor represents the monitoring difference data, * represents the convolution operation, λ represents the weight coefficient, d Base represents basic seismic data, M Base Represents the basic difference data. This objective function compares the basic seismic data with the monitored seismic data, and also compares the difference between the data after 3D adaptive attenuation. This subtracts the consistent parts of the multiple wave model from the seismic data, while retaining the differential parts. Furthermore, due to the presence of the target matching operator, the energy and frequency differences of the multiple wave model are reduced, further suppressing the noise in the differential part, which becomes the 4D signal.

[0115] in, This is the first function term in the objective function. is the second function term in the objective function, and λ is the weight parameter that controls the 4D consistent multiple wave subtraction method. Its value is between 0 and 1, which is selected according to the difference between the basic seismic data and the monitoring seismic data.

[0116] The core idea of ​​the objective function is to use the basic seismic data as a benchmark to make the monitoring seismic data closer to it; the least squares subtraction operation is performed on the monitoring seismic data and the monitoring difference data processed by the target matching operator, and the matching change of the target matching operator can make the monitoring seismic data after the 4D consistency multiple wave matching attenuation (i.e., E') Monitor ) is more reasonable; the least squares subtraction operation is performed on the first difference and the second difference, and the matching change of the target matching operator can make the basic seismic data (ie E') after the 4D consistent multiple wave matching attenuation Base ) is more reasonable. Using this objective function, we can obtain consistent results, eliminate discrepant signals and multiple waves, and retain consistent signals and multiple waves.

[0117] The multiple waves of basic seismic data and monitoring seismic data are predicted and adaptively subtracted separately. For 3D seismic data, the optimal effect after attenuating the multiple waves can be obtained. However, for 4D seismic data, due to the matching operator f Base and f Monitor There are differences between the basic prediction multiple wave model m Base and monitoring and prediction multiple wave model m Monitor There are differences between the basic seismic data dBase and monitoring earthquake data Monitor The difference between them is less than the basic attenuated data E Base And monitor the decay data E Monitor In the method of the embodiment of the present application, the above objective function is used to implement a 4D consistent multiple wave matching attenuation method, so as to ensure that the difference between the attenuated data is reduced while attenuating the multiple waves.

[0118] Step S240 , obtaining basic seismic data and monitoring seismic data after 4D consistent multiple wave matching and attenuation obtained by a preset attenuation algorithm.

[0119] The preset attenuation algorithm implements 4D consistent multiple wave matching attenuation processing on the basic seismic data and the monitoring seismic data according to the optimized target matching operator when the objective function meets the specified conditions, and outputs the basic seismic data after 4D consistent multiple wave matching attenuation and the monitoring seismic data after 4D consistent multiple wave matching attenuation.

[0120] Step S250 , calculating a multiple wave attenuation quality control index based on the basic seismic data and the monitoring seismic data after 4D consistent multiple wave matching and attenuation.

[0121] The multiple wave attenuation quality control index is used to measure the differences between data volumes after multiple wave attenuation, indicating the quality of 4D seismic data processing. Specifically, NRMS can be used as a multiple wave attenuation quality control index. It is a root mean square amplitude difference parameter calculated based on two data volumes. It is a standard for measuring the effectiveness of time-lapse seismic processing. The smaller the NRMS value, the better the processing effect. Under normal circumstances, the NRMS will become smaller as the processing steps are optimized.

[0122] In specific implementation, the NRMS between the basic seismic data and the monitoring seismic data is calculated, and the NRMS between the basic seismic data and the monitoring seismic data after 4D consistent multiple wave matching attenuation is calculated. By comparing the two calculated NRMS, the effectiveness of the 4D consistent multiple wave matching attenuation processing can be determined.

[0123] In the method of the embodiment of the present application, first, based on the seismic data, a data-driven method is used to calculate the predicted multiple wave models corresponding to the two sets of time-lapse seismic data, and then the respective multiple waves are attenuated respectively through 3D adaptive matching subtraction. The data before and after attenuation are subtracted to obtain the real attenuated noise models. Finally, the Base data, Monitor data and the attenuated noise model are used as input, and weight coefficients are added to perform consistency matching of multiple wave attenuation. The Base data and Monitor data are used to perform coordinated consistency multiple wave subtraction. Compared with the traditional method of subtracting them separately and then matching, the 4D error can be greatly reduced, the accuracy of the 4D signal is guaranteed, and the reduction of NRMS is used as a quality control method for 4D consistency matching attenuation.

[0124] The method of the present application embodiment can be applied to reservoir fluid dynamic monitoring in offshore oil and gas field development, particularly for the collaborative processing of time-lapse seismic data under non-repetitive acquisition conditions. By using a 4D consistent multiple wave attenuation algorithm, the method addresses technical challenges faced by traditional multiple wave suppression methods in time-lapse seismic processing, such as insufficient signal fidelity and residual multiple waves interfering with 4D difference signals. The core of the method lies in achieving collaborative optimization of multiple wave attenuation between two sets of seismic data volumes, effectively suppressing differential noise while maximally retaining information on reservoir dynamic changes. This method can provide a high-precision seismic data foundation for quantitative evaluation of remaining oil distribution and improving oil and gas recovery rates.

[0125] The embodiment method of the present application decomposes the signal and noise of the data before and after the multiple waves of the two time-lapse seismic acquisition data, and then performs primary wave energy compensation on the data after the two suppression of multiple waves, so as to ensure the authenticity of the reservoir signal in the target area, and at the same time, the residual multiple waves of the two data are subjected to target consistency attenuation, so as to ultimately retain only the reservoir difference information in the signals of the two data while suppressing the multiple waves and noise differences that affect the fidelity. Compared with the 3D adaptive multiple wave attenuation method, the embodiment method of the present application compares the attenuated noise data in the two sets of seismic data, and then sets a joint consistency multiple wave attenuation algorithm. The algorithm further distinguishes between the effective reservoir signal with higher consistency and the multiple wave noise signal with lower consistency by adding target matching operators and weight parameters, and ultimately makes the difference in reservoir position in the seismic data after 4D consistency multiple wave attenuation more obvious, and NRMS is effectively reduced.

[0126] The following diagrams illustrate the effect of the method of the embodiment of the present application. By collecting and processing seismic data in the target area, the following diagrams are drawn: Figures 3 to 13 ; Figure 3 This is the cross-section of the base data before the multiple waves attenuate, that is, the cross-section of the basic seismic data; Figure 4 This is the profile of Monitor data before multiple waves attenuate, that is, the profile of monitored seismic data; Figure 5It is the cross-section of the base data after 3D adaptive multiple wave attenuation, that is, the cross-section of the basic seismic data after 3D adaptive multiple wave attenuation; Figure 6 It is the profile of Monitor data after 3D adaptive multiple wave attenuation, that is, the profile of monitoring seismic data after 3D adaptive multiple wave attenuation; Figure 7 This is the multiple noise profile of the attenuated Base data, that is, the multiple noise profile of the attenuated basic seismic data after 3D adaptive multiple attenuation processing; Figure 8 This is the multiple noise profile of the attenuated Monitor data, that is, the multiple noise profile of the attenuated monitoring seismic data after 3D adaptive multiple attenuation processing; Figure 9 This is the cross-section of the base data after 4D consistent multiple wave matching and attenuation, that is, the cross-section of the basic seismic data after 4D consistent multiple wave matching and attenuation; Figure 10 This is the profile of the Monitor data after 4D consistent multiple wave matching and attenuation, that is, the profile of the monitoring seismic data after 4D consistent multiple wave matching and attenuation.

[0127] Figure 11 This is the difference profile of the Base data and Monitor data after 3D adaptive multiple wave attenuation, that is, the difference profile of the two sets of seismic data after 3D adaptive multiple wave attenuation; Figure 12 This is the difference profile of the Base data and Monitor data after 4D consistent multiple wave matching and attenuation, that is, the difference profile of the two sets of seismic data after 4D consistent multiple wave matching and attenuation.

[0128] It should be noted that Figures 3 to 12 In each schematic diagram, the horizontal axis represents the point number of the seismic profile, the vertical axis is the time scale of the seismic profile, and different colors represent different amplitude values. Figure 11 The position pointed by the black arrow is the position where the reservoir changes, that is, there should be a difference in theory at this position, which is reflected in the figure that there should be an amplitude response. The position pointed by the blue arrow is the position where there is no reservoir change, that is, there should be no amplitude response in theory. By comparison Figure 11 and Figure 12 , Figure 11 This indicates that the 3D adaptive multiple wave attenuation method cannot completely attenuate the 4D noise, resulting in differences in the results where there should not be differences (blue arrows). Figure 12 This shows that 4D noise can be effectively suppressed by 4D consistent multiple wave matching attenuation, weakening the places where there should be no differences. Correspondingly, the places where there should be differences are well reflected.

[0129] Figure 13Schematic diagram of the global NRMS of the base data and monitor data after 3D adaptive multiple wave subtraction attenuation, that is, the global NRMS diagram of the base seismic data and monitor seismic data after 3D adaptive multiple wave attenuation; Figure 14 This is a global NRMS diagram of the Base data and Monitor data after 4D consistent multiple wave matching and attenuation, that is, a global NRMS diagram of the basic seismic data and the monitoring seismic data after 4D consistent multiple wave matching and attenuation; the NRMS diagram is the attribute diagram obtained by the seismic data volume through the space-time window, the horizontal axis is the xline, that is, the point number, the vertical axis is the inline, that is, the line number, and the color scale on the right is the color bar corresponding to the color of the diagram, and different colors represent different NRMS values.

[0130] Figure 15 FIG. 1 shows a functional structure diagram of a time-lapse seismic data processing device provided in an embodiment of the present application. Figure 15 As shown, the device includes:

[0131] The processing module 1501 is adapted to input the basic seismic data and basic difference data thereof and the monitoring seismic data and monitoring difference data thereof into a preset attenuation algorithm; wherein the basic difference data is the difference data between the basic seismic data and the data after 3D adaptive multiple wave attenuation, and the monitoring difference data is the difference data between the monitoring seismic data and the data after 3D adaptive multiple wave attenuation;

[0132] An optimization module 1502 is adapted to control the optimization process of the target matching operator using the objective function corresponding to the preset attenuation algorithm to obtain an optimized target matching operator;

[0133] wherein the objective function is constructed based on the basic seismic data, the basic difference data, the monitored seismic data, the monitored difference data, and the target matching operator;

[0134] The processing module 1501 is further adapted to: obtain basic seismic data and monitoring seismic data after 4D consistent multiple wave matching attenuation obtained by the preset attenuation algorithm, and the preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing.

[0135] In an optional manner, the objective function is specifically a weighted sum function based on a first function term and a second function term; the first function term is determined based on monitored seismic data, a target matching operator, and monitored difference data; the second function term is determined based on basic seismic data, monitored seismic data, basic difference data, a target matching operator, and monitored difference data.

[0136] In an optional manner, the formula of the objective function is specifically:

[0137]

[0138] Where Π represents the objective function, E′ Base represents the basic seismic data after 4D consistent multiple wave matching attenuation, E′ Monitor represents the monitored seismic data after 4D consistent multiple wave matching attenuation, represents the least squares subtraction operation, d Monitor represents the monitored earthquake data, f match represents the target matching operator, M Monitor represents the monitoring difference data, * represents the convolution operation, λ represents the weight coefficient, d Base represents basic seismic data, M Base Indicates basic difference data.

[0139] In an optional manner, the processing module 1501 is further adapted to:

[0140] performing 3D adaptive multiple wave attenuation processing on the basic seismic data and the monitoring seismic data respectively to obtain basic attenuated data and monitoring attenuated data;

[0141] Determining the basic difference data according to the basic seismic data and the basic attenuated data;

[0142] The monitoring difference data is determined according to the monitoring seismic data and the monitoring attenuated data.

[0143] In an optional manner, the processing module 1501 is further adapted to:

[0144] Determining a basic predicted multiple wave model based on the basic seismic data and a corresponding information propagation operator; calculating and obtaining basic attenuated data based on the basic seismic data, the basic predicted multiple wave model and a corresponding matching operator;

[0145] According to the monitoring seismic data and the corresponding information propagation operator, a monitoring prediction multiple wave model is determined; according to the monitoring seismic data, the monitoring prediction multiple wave model and the corresponding matching operator, the monitoring attenuated data is calculated.

[0146] In an optional manner, the basic attenuated data is calculated as follows:

[0147]

[0148] Among them, E Base represents the data after basic attenuation, d Base represents the basic seismic data, f Base represents the matching operator corresponding to the basic seismic data, mBase represents the basic forecast multiple wave model;

[0149] The calculation method of the monitoring attenuation data is as follows:

[0150]

[0151] Among them, E Monitor Indicates the data after monitoring attenuation, d Monitor represents the monitored earthquake data, f Monitor represents the matching operator corresponding to the monitored earthquake data, m Monitor Represents the monitoring and prediction multiple wave model.

[0152] To sum up, according to the time-lapse seismic data processing device provided in this embodiment, in addition to considering the difference between the basic seismic data and the monitoring seismic data, the difference between the data attenuated after 3D adaptive attenuation is also considered, thereby performing 4D consistent multiple wave matching attenuation processing on the basic seismic data and the monitoring seismic data, abandoning the traditional independent processing scheme of time-lapse seismic data, and performing consistency matching on the original data without multiple wavefronts and the corresponding 3D adaptively attenuated data, so as to achieve the true consistency collaborative processing requirements of time-lapse seismic, effectively improve the 4D effective signal strength in the difference between the two sets of seismic data, suppress the surrounding 4D noise, and achieve the effect of retaining only the reservoir difference information in the attenuated data and suppressing the multiple waves and noise differences that affect the fidelity.

[0153] An embodiment of the present application provides a non-volatile computer storage medium, which stores at least one executable instruction or computer program, which can enable a processor to perform operations corresponding to the time-lapse seismic data processing method in any of the above method embodiments.

[0154] An embodiment of the present application provides a computer program product, which includes at least one executable instruction or computer program, and the executable instruction or computer program can enable a processor to perform operations corresponding to the time-lapse seismic data processing method in any of the above method embodiments.

[0155] Figure 16 A schematic diagram of the structure of an embodiment of a computing device of the present application is shown. The specific embodiment of the present application does not limit the specific implementation of the computing device.

[0156] like Figure 16 As shown, the computing device may include: a processor 1602 , a communications interface 1604 , a memory 1606 , and a communication bus 1608 .

[0157] Processor 1602, communication interface 1604, and memory 1606 communicate with each other via communication bus 1608. Communication interface 1604 is used to communicate with other devices, such as client devices or other server network elements. Processor 1602 is used to execute program 1610, which may specifically perform the steps described in the embodiment of the time-lapse seismic data processing method for a computing device.

[0158] Specifically, the program 1610 may include program codes, which include computer operation instructions.

[0159] Processor 1602 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0160] The memory 1606 is used to store the program 1610. The memory 1606 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0161] Program 1610 can be specifically configured to cause processor 1602 to execute the time-lapse seismic data processing method in any of the aforementioned method embodiments. The specific implementation of each step in program 1610 can be found in the corresponding descriptions of the corresponding steps and units in the time-lapse seismic data processing embodiments and will not be repeated here. Those skilled in the art will clearly understand that, for ease and brevity of description, the specific operating processes of the devices and modules described above can refer to the corresponding process descriptions in the aforementioned method embodiments and will not be repeated here.

[0162] The algorithm or demonstration provided here are not inherently relevant to any particular computer, virtual system or other equipment. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the present application.

[0163] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0164] Similarly, it should be understood that in order to streamline the present application and aid in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the present application.

[0165] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0166] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of this application and to form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

[0167] Various component embodiments of the present application can be implemented in hardware, or as software modules running in one or more processors, or in combinations thereof. As will be appreciated by persons skilled in the art, a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all of the functionality of some or all of the components according to the embodiments of the present application. The present application can also be implemented as a program of apparatus or device (e.g., a computer program and a computer program product) for performing part or all of the methods described herein. Such a program implementing the present application can be stored on a computer readable medium, or can be in the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0168] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a unit claim, several devices can be listed with a conjunction like 'or', but it is to be understood that each of these devices can be implemented by its own hardware item. The use of the words 'first','second' and 'third', etc. do not imply any ordering but rather are used as names for different elements. The steps of any of the methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that expressed integers are to be executed in a specific order.

Claims

1. A time-lapse seismic data processing method, characterized in that: include: Inputting basic seismic data and basic difference data thereof and monitoring seismic data and monitoring difference data thereof into a preset attenuation algorithm; wherein the basic difference data is the difference data between the basic seismic data and the data after 3D adaptive multiple wave attenuation, and the monitoring difference data is the difference data between the monitoring seismic data and the data after 3D adaptive multiple wave attenuation; Using the objective function corresponding to the preset attenuation algorithm to control the optimization process of the target matching operator to obtain an optimized target matching operator; wherein the objective function is constructed based on the basic seismic data, the basic difference data, the monitored seismic data, the monitored difference data, and the target matching operator; The basic seismic data and monitoring seismic data after 4D consistent multiple wave matching attenuation obtained by the preset attenuation algorithm are obtained. The preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing.

2. The time-lapse seismic data processing method according to claim 1, characterized in that: The objective function is specifically a weighted sum function based on the first function term and the second function term; the first function term is determined based on the monitored seismic data, the target matching operator and the monitored difference data; the second function term is determined based on the basic seismic data, the monitored seismic data, the basic difference data, the target matching operator and the monitored difference data.

3. The time-lapse seismic data processing method according to claim 2, characterized in that: The formula of the objective function is specifically: Where Π represents the objective function, E′ Base represents the basic seismic data after 4D consistent multiple wave matching attenuation, E′ Monitor represents the monitored seismic data after 4D consistent multiple wave matching attenuation, represents the least squares subtraction operation, d Monitor represents the monitored earthquake data, f match represents the target matching operator, M Monitor represents the monitoring difference data, * represents the convolution operation, λ represents the weight coefficient, d Base represents basic seismic data, M Base Indicates basic difference data.

4. The time-lapse seismic data processing method according to any one of claims 1 to 3, characterized in that: The method further comprises: performing 3D adaptive multiple wave attenuation processing on the basic seismic data and the monitoring seismic data respectively to obtain basic attenuated data and monitoring attenuated data; Determining the basic difference data according to the basic seismic data and the basic attenuated data; The monitoring difference data is determined according to the monitoring seismic data and the monitoring attenuated data.

5. The time-lapse seismic data processing method according to claim 4, characterized in that: The performing 3D adaptive multiple wave attenuation processing on the basic seismic data and the monitoring seismic data to obtain basic attenuated data and monitoring attenuated data further includes: Determining a basic predicted multiple wave model based on the basic seismic data and a corresponding information propagation operator; calculating and obtaining basic attenuated data based on the basic seismic data, the basic predicted multiple wave model and a corresponding matching operator; According to the monitoring seismic data and the corresponding information propagation operator, a monitoring prediction multiple wave model is determined; according to the monitoring seismic data, the monitoring prediction multiple wave model and the corresponding matching operator, the monitoring attenuated data is calculated.

6. The time-lapse seismic data processing method according to claim 5, characterized in that: The calculation method of the basic attenuated data is as follows: Among them, E Base Represents the data after basic attenuation, d Base represents the basic seismic data, f Base represents the matching operator corresponding to the basic seismic data, m Base represents the basic forecast multiple wave model; The calculation method of the monitoring attenuation data is as follows: Among them, E Monitor Indicates the data after monitoring attenuation, d Monitor represents the monitored earthquake data, f Monitor represents the matching operator corresponding to the monitored earthquake data, m Monitor Represents the monitoring and prediction multiple wave model.

7. A time-lapse seismic data processing device, characterized in that: include: a processing module adapted to input basic seismic data and basic difference data thereof and monitoring seismic data and monitoring difference data thereof into a preset attenuation algorithm; wherein the basic difference data is difference data between the basic seismic data and data after 3D adaptive multiple wave attenuation, and the monitoring difference data is difference data between the monitoring seismic data and data after 3D adaptive multiple wave attenuation; an optimization module adapted to control the optimization process of the target matching operator using the objective function corresponding to the preset attenuation algorithm to obtain an optimized target matching operator; wherein the objective function is constructed based on the basic seismic data, the basic difference data, the monitored seismic data, the monitored difference data, and the target matching operator; The processing module is further adapted to obtain basic seismic data and monitoring seismic data obtained by processing the preset attenuation algorithm after 4D consistent multiple wave matching attenuation, and the preset attenuation algorithm uses the optimized target matching operator to perform 4D consistent multiple wave matching attenuation processing.

8. A computing device, characterized in that include: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the time-lapse seismic data processing method according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that The storage medium stores at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the time-lapse seismic data processing method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the time-lapse seismic data processing method according to any one of claims 1 to 6.

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