AVO feature preserving denoising method and system based on compressed sensing

Abstract

The present invention discloses a denoising method and system for protecting the AVO characteristics of pre-stack seismic data. The specific technology is an AVO characteristic transformation method on pre-stack angle gathers based on extended Radon transform. The method can remove noise while effectively protecting the AVO characteristics of seismic data, and provide high signal-to-noise ratio, true and reliable input data for AVO or pre-stack inversion, which plays a vital role in obtaining high-resolution and reliable pre-stack inversion results.

Description

Technical Field

[0001] The present invention relates to a noise removal method in the field of seismic gather optimization, and in particular to an AVO feature preserving noise removal method and system based on compressed sensing. Background Art

[0002] The denoising of seismic data is a very important problem that has not been completely solved. A lot of work has been done by predecessors, and many mature methods have been obtained. With the continuous development of oil exploration, the focus of seismic data processing has shifted from post-stack to pre-stack. Since the 1980s, the use of AVO technology to directly search for oil and gas has become a popular technology. After decades of development, AVO technology has made progress to varying degrees. Among them, the AVO inversion method is an important means to extract lithological parameters and establish AVO markers for oil and gas detection. However, since the pre-stack data is a single-shot record, it is severely affected by interference. If you want to do various processing in the pre-stack data, you should first improve the recording quality of the pre-stack data. In some areas, the pre-stack records are seriously covered with various interferences, and the phase axis of the effective signal is almost unrecognizable, which brings great difficulties to the AVO analysis and inversion based on the pre-stack gathers. Therefore, it is very necessary to study and apply new seismic data denoising methods to ensure the quality of pre-stack AVO inversion input data.

[0003] At present, some denoising methods commonly used in the actual production of seismic exploration in my country, such as conventional pre-stack gather denoising methods such as FX prediction filtering (Hornbostel, 1991), linear and hyperbolic Radon (Trad et al., 2003) transform methods, do not consider the important AVO feature of seismic reflection amplitude changing with reflection angle, so there are obvious deficiencies in denoising and signal AVO feature protection. In recent years, researchers have begun to consider the AVO effect in the process of seismic data denoising, and proposed the AVO amplitude-preserving Radon transform (Wang et al., 2011), high-order Radon transform (Xue et al., 2014) and extended domain Radon transform method (Vyas et al., 2016). However, the expression of the reflection signal amplitude in the above methods is still quite different from the expression of the AVO effect in seismic data, so there is a lot of room for improvement in their denoising and amplitude preservation effects. Summary of the invention

[0004] The purpose of the present invention is to provide an AVO feature preserving denoising method and system based on compressed sensing.

[0005] In order to solve the technical problem, the technical solution of the present invention is:

[0006] A method for denoising pre-stack seismic data by preserving the AVO characteristics is based on extended Radon transform; the method comprises:

[0007] Divide the input angle gathers into overlapping time windows to determine the range of t in the angle gathers;

[0008] Based on the range of t in the angle gather, the input angle gather is converted from the angle domain to the feature domain through the compressed sensing algorithm;

[0009] Filter the angle gathers in the feature domain to obtain effective signals that fully retain the AVO characteristics of the original data;

[0010] Perform inverse transformation on the effective signal to obtain the optimized angle gather data in the corresponding time window;

[0011] The optimized angle gather data in multiple time windows are overlapped and spliced ​​to obtain complete angle gather signals, thus achieving denoising of pre-stack seismic data with guaranteed AVO characteristics.

[0012] Furthermore, based on the range of t in the angle gathers, the model parameters m(t, R0, b) are obtained by inverting the formula (1) through the formula (2). The model parameters m(t, R0, b) are used to transform the angle gathers in the prestack seismic data from the angle domain to the feature domain.

[0013]

[0014]

[0015] Where D(t,θ) is the angle gather data, R0+bsin 2 θ represents the AVO effect template of the seismic reflection amplitude changing with angle. The model parameter m(t, R0, b) in the transformation space contains the AVO characteristics of the data; t is time, θ is the angle; d is the data; R0, b is used to characterize the AVO characteristics.

[0016] Furthermore, the inversion algorithm based on the compressed sensing theory is used to invert formula (1) to obtain the model parameters m(t, R0, b).

[0017] Furthermore, two-dimensional filtering is performed on the angle gathers in the feature domain to obtain effective signals that fully retain the AVO characteristics of the original data.

[0018] Furthermore, the effective signal is inversely transformed using formula (1) to obtain the optimized angle gather data in the corresponding time window.

[0019] A system for denoising pre-stack seismic data AVO features is based on extended Radon transform; the system comprises:

[0020] The first processing module is used to divide the input angle gathers into overlapping time windows for processing and determine the range of t in the angle gathers;

[0021] A conversion module, used for converting the input angle gather from the angle domain to the feature domain through a compressed sensing algorithm based on the range of t in the angle gather;

[0022] The filtering module is used to filter the angle gathers in the feature domain to obtain effective signals that fully maintain the AVO characteristics of the original data;

[0023] The inverse transformation module is used to perform inverse transformation processing on the effective signal to obtain the optimized angle gather data in the corresponding time window;

[0024] The second processing module is used to perform overlapping time window splicing processing on the optimized angle gather data in multiple time windows to obtain a complete angle gather signal, that is, to achieve denoising processing to ensure AVO characteristics of pre-stack seismic data.

[0025] A computer-readable storage medium stores computer-executable instructions, which are used to implement any of the above methods when executed by a processor.

[0026] Compared with the prior art, the advantages of the present invention are:

[0027] The AVO feature preserving denoising method and system based on compressed sensing, the specific technology is the AVO feature transformation method on the prestack angle gather based on the extended Radon transform, which can remove noise under the premise of effectively protecting the AVO characteristics of seismic data, and provide high signal-to-noise ratio, real and reliable input data for AVO or prestack inversion, which plays a vital role in obtaining high-resolution and reliable prestack inversion results. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 , main flow chart. DETAILED DESCRIPTION

[0029] The specific implementation mode of the present invention is described below in conjunction with embodiments:

[0030] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to match the contents disclosed in the specification so that people familiar with this technology can understand and read them, and are not used to limit the conditions under which the present invention can be implemented. Any structural modification, change in proportional relationship or adjustment of size should still fall within the scope of the technical content disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0031] At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" cited in this specification are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments to their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.

[0032] Embodiment 1:

[0033] The purpose of the present invention is to provide a denoising method for pre-stack seismic data AVO characteristics. The method is an AVO characteristic transformation method on pre-stack angle gathers based on extended Radon transform, which can remove noise in the angle gathers while maintaining the AVO characteristics of the signal.

[0034] The specific transformation is expressed as:

[0035]

[0036] Where D(t,θ) is the angle gather data, R0+bsin 2 θ characterizes the AVO effect template of the seismic reflection amplitude varying with angle, so the model parameters m(t, R0, b) in the transformation space contain the AVO characteristics of the data.

[0037] By inverting the above formula to solve m(t, R0, b), the signal and noise can be separated in the transform domain. The key to accurate separation of signal and noise lies in accurate characterization of the signal and high-resolution transformation results. The present invention proposes a method based on compressed sensing, that is, to study the inversion method of 1-norm constraint to invert formula (1) to solve the transformed model parameter m and obtain high-resolution results to achieve accurate separation of signal and noise. The objective function is:

[0038]

[0039] After minimizing formula (2) to solve the model parameter m, the noise is removed, and then the forward transformation is performed using formula (1) to obtain the denoised angle gather. Since the obtained model parameter m can accurately characterize the AVO characteristics of the data, and the high-resolution inversion result constrained by the 1-norm can achieve more reliable signal-noise separation, the above transformation processing can fully protect the AVO characteristics of the data and remove the noise in the data.

[0040] Embodiment 2:

[0041] like Figure 1 As shown, the purpose of the present invention is to provide a denoising method for preserving the AVO characteristics of prestack seismic data. The method is an AVO characteristic transformation method on prestack angle gathers based on extended Radon transform, which can remove noise in the angle gathers while maintaining the AVO characteristics of the signal.

[0042] The specific transformation is expressed as:

[0043]

[0044] Where D(t,θ) is the angle gather data, R0+bsin 2 θ characterizes the AVO effect template of the seismic reflection amplitude varying with angle, so the model parameters m(t, R0, b) in the transformation space contain the AVO characteristics of the data.

[0045] By inverting the above formula to solve m(t, R0, b), the signal and noise can be separated in the transform domain. The key to accurate separation of signal and noise lies in accurate characterization of the signal and high-resolution transformation results. The present invention proposes a method based on compressed sensing, that is, to study the inversion method of 1-norm constraint to invert formula (1) to solve the transformed model parameter m and obtain high-resolution results to achieve accurate separation of signal and noise. The objective function is:

[0046]

[0047] After minimizing formula (2) to solve the model parameter m, the noise is removed, and then the forward transformation is performed using formula (1) to obtain the denoised angle gather. Since the obtained model parameter m can accurately characterize the AVO characteristics of the data, and the high-resolution inversion result constrained by the 1-norm can achieve more reliable signal-noise separation, the above transformation processing can fully protect the AVO characteristics of the data and remove the noise in the data.

[0048] Embodiment three:

[0049] In order to better implement the above-mentioned AVO feature preserving denoising method based on compressed sensing, this embodiment also proposes an AVO feature preserving denoising system based on compressed sensing;

[0050] The system comprises:

[0051] The first processing module is used to divide the input angle gathers into overlapping time windows for processing and determine the range of t in the angle gathers;

[0052] A conversion module, used for converting the input angle gather from the angle domain to the feature domain through a compressed sensing algorithm based on the range of t in the angle gather;

[0053] The filtering module is used to filter the angle gathers in the feature domain to obtain effective signals that fully maintain the AVO characteristics of the original data;

[0054] The inverse transformation module is used to perform inverse transformation processing on the effective signal to obtain the optimized angle gather data in the corresponding time window;

[0055] The second processing module is used to perform overlapping time window splicing processing on the optimized angle gather data in multiple time windows to obtain a complete angle gather signal, that is, to achieve denoising processing to ensure AVO characteristics of pre-stack seismic data.

[0056] Embodiment 4:

[0057] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0058] To this end, an embodiment of the present invention provides a storage medium storing a plurality of instructions, which can be loaded by a processor to execute the steps of any compressed sensing-based AVO feature preserving denoising method provided by the embodiment of the present invention.

[0059] For example, the instruction can execute the following steps:

[0060] Divide the input angle gathers into overlapping time windows to determine the range of t in the angle gathers;

[0061] Based on the range of t in the angle gather, the input angle gather is converted from the angle domain to the feature domain through the compressed sensing algorithm;

[0062] Filter the angle gathers in the feature domain to obtain effective signals that fully retain the AVO characteristics of the original data;

[0063] Perform inverse transformation on the effective signal to obtain the optimized angle gather data in the corresponding time window;

[0064] The optimized angle gather data in multiple time windows are overlapped and spliced ​​to obtain complete angle gather signals, thus achieving denoising of pre-stack seismic data with guaranteed AVO characteristics.

[0065] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the technical principles of the present invention, and these improvements and modifications should also be regarded as within the scope of protection of the present invention.

[0066] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0067] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0070] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0071] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for denoising pre-stack seismic data by preserving the AVO characteristics, based on extended Radon transform; characterized in that: The method comprises: Divide the input angle gathers into overlapping time windows to determine the range of t in the angle gathers; Based on the range of t in the angle gather, the input angle gather is converted from the angle domain to the feature domain through the compressed sensing algorithm; Based on the range of t in the angle gather, the model parameter m(t, R0, b) is obtained by inverting the formula (1) through the formula (2). The angle gather in the prestack seismic data is converted from the angle domain to the feature domain using the model parameter m(t, R0, b); Where D(t,θ) is the angle gather data, R0+bsin 2 θ represents the AVO effect template of the seismic reflection amplitude changing with angle. The model parameter m(t, R0, b) in the transformation space contains the AVO characteristics of the data; t is time, θ is the angle; d is the data; R0, b is used to characterize the AVO characteristics; Filter the angle gathers in the feature domain to obtain effective signals that fully retain the AVO characteristics of the original data; Perform inverse transformation on the effective signal to obtain the optimized angle gather data in the corresponding time window; The optimized angle gather data in multiple time windows are overlapped and spliced ​​to obtain complete angle gather signals, thus achieving denoising of pre-stack seismic data with guaranteed AVO characteristics.

2. A method for denoising pre-stack seismic data by preserving AVO characteristics according to claim 1, characterized in that: The inversion algorithm based on compressed sensing theory inverts formula (1) and obtains the model parameters m(t, R0, b).

3. A method for denoising pre-stack seismic data by preserving AVO characteristics according to claim 1, characterized in that: The angle gathers in the feature domain are processed by two-dimensional filtering to obtain effective signals that fully retain the AVO characteristics of the original data.

4. A method for denoising pre-stack seismic data by preserving AVO characteristics according to claim 1, characterized in that: The effective signal is inversely transformed using formula (1) to obtain the optimized angle gather data within the corresponding time window.

5. A system for denoising pre-stack seismic data AVO features, based on extended Radon transform; characterized in that: The method according to any one of claims 1 to 4, wherein the system comprises: The first processing module is used to divide the input angle gathers into overlapping time windows for processing and determine the range of t in the angle gathers; A conversion module, used for converting the input angle gather from the angle domain to the feature domain through a compressed sensing algorithm based on the range of t in the angle gather; The filtering module is used to filter the angle gathers in the feature domain to obtain effective signals that fully maintain the AVO characteristics of the original data; The inverse transformation module is used to perform inverse transformation processing on the effective signal to obtain the optimized angle gather data in the corresponding time window; The second processing module is used to perform overlapping time window splicing processing on the optimized angle gather data in multiple time windows to obtain a complete angle gather signal, that is, to achieve denoising processing to ensure AVO characteristics of pre-stack seismic data.

6. A computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 4.

Images