CN111582114A - Seismic fault identification method, device, equipment and storage medium - Google Patents
Seismic fault identification method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a seismic fault identification method, a seismic fault identification device, seismic fault identification equipment and a storage medium. The method comprises the following steps: determining an inclination angle body according to an original seismic data body of the seismic fault to be identified; under the constraint of the dip angle body, performing guided filtering on the seismic fault to be identified, and determining an optimized seismic data body; performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume; and carrying out fault identification processing on the enhanced seismic data body to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified. The embodiment of the invention performs guiding filtering on the seismic data volume of the seismic fault to be identified under the constraint of the inclination angle body so as to realize smooth processing on the same-phase axis parallel to the seismic fault and improve the sharpness of the fault so as to improve the identification accuracy of the fault; and the seismic data volume is enhanced, so that the fault identification accuracy is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of geophysical exploration, in particular to a seismic fault identification method, a seismic fault identification device, seismic fault identification equipment and a storage medium.
Background
In the development process of the extended fault trap, due to the fact that differential motion exists between the blocks, the fault is extended differentially, and a transformation structural zone (the distortion and the fracture of the stratum) is generated at the intersection of the head and the tail of two fractures, so that a transformation fault is formed. At present, the increasing degree of petroleum development is important for accurately identifying micro faults in the conversion fault, and the micro faults affect the identification of oil reservoir boundaries, the reserve calculation and the like.
The current common fracture identification method mainly utilizes seismic geometric attributes such as coherent bodies, curvature bodies, ant bodies and inclination bodies to assist in finishing dominant transformation fault identification and interpretation work. The common methods have ideal fracture identification effect on obvious fault distance (earthquake homophase axis dislocation).
However, the existing micro-fault imaging of seismic data is not very good, and fine depiction is not performed, and interpretation or prediction result errors are often caused by unclear sections, crisp breakpoints and heavy noise of the seismic data, so that the fine interpretation requirements are difficult to meet, and therefore, a processing technology for improving fault identification degree needs to be researched to enhance the identification capability of the micro-fault.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for identifying a seismic fault, which are used for improving the accuracy of identifying a micro fault in a conversion fault.
In a first aspect, an embodiment of the present invention provides a seismic fault identification method, including:
determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
under the constraint of the inclination angle body, performing guiding filtering on the seismic fault to be identified, and determining an optimized seismic data body;
performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume;
and carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
In a second aspect, an embodiment of the present invention further provides a seismic fault identification apparatus, including:
the inclination angle body determining module is used for determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
the guiding filtering module is used for guiding filtering of the seismic fault to be identified under the constraint of the inclination angle body and determining an optimized seismic data body;
the seismic data volume enhancement module is used for enhancing the optimized seismic data volume to obtain an enhanced seismic data volume;
and the fault identification module is used for carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
In a third aspect, an embodiment of the present invention further provides an apparatus, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method of seismic fault identification as described in any embodiment of the invention.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the seismic fault identification method according to any one of the embodiments of the present invention.
The embodiment of the invention performs guiding filtering on the seismic data volume of the seismic fault to be identified under the constraint of the inclination angle body so as to realize smooth processing on the same-phase axis parallel to the seismic fault and improve the sharpness of the fault so as to improve the identification accuracy of the fault; and the seismic data volume is enhanced, so that the fault identification accuracy is improved.
Drawings
FIG. 1A is a flow chart of a seismic fault identification method in accordance with a first embodiment of the invention;
FIG. 1B is a diagram illustrating the results of guided filtering under the constraint of a pitch volume;
FIG. 1C is a schematic diagram of a single tone after wavelet frequency division processing;
FIG. 1D is a schematic diagram of the results of coherent object extraction processing on a monosome;
FIG. 2A is a flow chart of a seismic fault identification method according to a second embodiment of the present invention;
FIG. 2B is a schematic illustration of seismic fault identification using a quingram method;
FIG. 3 is a schematic structural diagram of a seismic fault identification device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus in the fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1A is a flowchart of a seismic fault identification method according to a first embodiment of the present invention, which is applicable to identifying a fault in a transition fault and guiding exploration of a high-quality reservoir development area. The method may be performed by a seismic fault recognition apparatus, which may be implemented in software and/or hardware and may be configured in a device, for example, a device having communication and computing capabilities such as a background server. As shown in fig. 1A, the method specifically includes:
The seismic fault to be identified is a conversion fault needing fault fracture identification, the geometric morphology of the current conversion fracture can be identified through identification and analysis of the seismic fault to be identified, the kinematics process of recessive conversion fracture development in a certain historical period can be restored, identification of fracture properties of a control reservoir development period and a key accumulation period is improved, and oil and gas exploration efficiency is improved. The original seismic data volume is data for representing the section form of the seismic fault, contains rich stratum and lithology information and can provide basis for seismic fault analysis. The dip angle body is one of seismic geometrical attributes of the seismic data body and can assist in completing identification and interpretation work of the dominant conversion fault. Common seismic geometric attributes also include coherence, curvature, and ant.
There are many methods for calculating the tilt angle body, such as tilt angle scanning, complex analysis, local radon transform, local gradient method, cross-correlation operation, structure tensor method, and instantaneous phase gradient method.
Optionally, determining an inclination angle body according to an original seismic data body of the seismic fault to be identified includes:
and determining an inclination angle body by adopting a Fourier transform maximum amplitude method for an original seismic data body of the seismic fault to be identified.
The Fourier transform maximum amplitude method is suitable for reflection disordered seismic data with low signal-to-noise ratio, firstly, Fourier transform is applied to transform a seismic data volume from a time domain to a frequency domain, then, the frequency maximum value of a sampling point is detected and is used as the dip angle of a main measuring line and an interconnection measuring line, and therefore, the attribute of the dip angle volume is determined. Illustratively, to improve the efficiency of the determination of the inclinometer, a fast fourier transform maximum amplitude method may be employed.
Through the determination of the original seismic data volume with the fused dip angle volume attributes, a dip angle abnormal high value area can be obtained from the seismic data volume, wherein the area is a dip angle steepening place, a stratum deflection place or a micro fracture development place. Because a large amount of noise exists in the original seismic data volume, certain interference can be caused to the micro fracture identification, and the accuracy of the micro fracture identification is improved through the determination of the attributes of the dip angle body.
And 102, performing guided filtering on the seismic fault to be identified under the constraint of the dip angle body, and determining an optimized seismic data body.
And (3) guiding filtering, namely, aiming at a smoothing operation parallel to the seismic event information, finishing filtering by utilizing the inclination and trend of an edge-keeping dip angle guiding filter along a seismic reflection interface so as to eliminate random noise, improve the transverse continuity of the event, enhance the lateral resolution at the fault termination part of the event and improve the sharpness of the fault. For example, the guided filtering may be an anisotropic diffusion filtering method, in which the image is convolved with gaussian kernel functions of different noise scales by using a nonlinear operator set by a nonlinear partial differential equation, so as to obtain smooth images of different scales. The method has the advantages of having the optimal smooth characteristic and edge retention characteristic when being applied to seismic data processing, effectively suppressing noise, improving transverse continuity and enhancing the imaging capability of the internal structure of the seismic sequence.
Specifically, the original seismic data volume with the dip angle volume attribute fused is subjected to guiding filtering operation, and the seismic data volume is subjected to smoothing operation to obtain an optimized seismic data volume. By guiding the seismic data body after filtering, namely analyzing the seismic profile, the signal-to-noise ratio of seismic data can be improved, the continuity of seismic in-phase axes is improved, the micro-fracture imaging precision is enhanced, the accuracy of identifying the section of the micro-fault is improved, and the subsequent construction and interpretation work on the seismic data body is facilitated. FIG. 1B is a diagram illustrating the results of guided filtering of seismic faults to be identified under the constraint of a dip cube.
Optionally, the guided filtering of the seismic fault to be identified includes dip-guided median filtering, dip-guided diffusion filtering, or fault edge preservation filtering.
Different guiding filtering is adopted according to the concrete expression of the earthquake fault, such as dip guiding median filtering, dip guiding diffusion filtering or fault edge holding filtering.
And 103, performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume.
Enhancement processing refers to further processing of fractures in the seismic data volume to improve recognition resolution. By performing enhancement processing on the seismic data body, the conversion fracture in the enhanced seismic data body can be more finely explained. On the processed data body, the recognition and interpretation work of the current form of the conversion fault can be better completed.
Optionally, the enhanced processing is performed on the optimized seismic data volume to obtain an enhanced seismic data volume, including:
performing wavelet frequency division processing on the optimized seismic data body to obtain a single frequency body data body with at least two frequency bands;
performing coherent body extraction processing on the single-frequency body data body to obtain a seismic attribute body;
and fusing the seismic attribute bodies of at least two frequency bands to obtain an enhanced seismic data body.
Specifically, wavelet frequency division processing is further carried out on the basis of finishing the guided filtering, and the micro fracture sharp effect is further optimized. The wavelet transform is a time-frequency analysis method of signals, can represent local characteristics of the signals in both a time domain and a frequency domain, and is a time-frequency localization analysis method with the size of a time-frequency window unchanged and the shape, the time window and the frequency window changed. Among them, the continuous wavelet transform is commonly used for seismic data processing, and is defined as follows.
In the formula: f (t) is the original signal;
is a wavelet basis function; a is a scale factor; b is a time shift factor; t is a time parameter.
Illustratively, the Marr wavelet is used for frequency division processing. The Marr wavelet is a second derivative of a Gaussian function, and the mother function formula of the Marr wavelet is as follows: in the time domain:
in the frequency domain are
Where Ψ (ω ═ 0) ═ 0. Using t in the expression of the time domain in the Marr wavelet
Alternatively, it is an expression of the Ricker wavelet. Therefore, the Marr wavelet can be used for simulating Ricker wavelets with different frequencies to perform frequency division processing on seismic signals, and the processed result signals have clear physical significance which is not possessed by other wavelet frequency division.
Through wavelet frequency division processing, a single frequency body of at least two frequency bands is obtained, such as a low frequency body and a high frequency body, or a wavelet frequency division body of 20 Hz, a wavelet frequency division body of 30 Hz and a wavelet frequency division body of 50 Hz are obtained respectively. Fig. 1C is a schematic diagram of a single frequency after wavelet frequency division processing.
On the basis of wavelet frequency division, coherent body extraction processing is carried out on a single frequency body, and interpretation work of micro-faults is completed. Coherence represented by coherent bodies is a direct measure of waveform similarity, and coherent body technology uses the similarity of adjacent seismic signals to describe the lateral heterogeneity of stratigraphy and lithology, and mainly comprises coherence technology based on cross correlation, similarity, variance, feature construction, gradient construction tensor and least square method. Changes in travel time, amplitude, frequency and phase between adjacent reflections at the micro-fractures can be identified by coherence.
Along with the frequency increase of the single frequency body, the earthquake in-phase axis is gradually thinned, the resolution ratio is improved, and the micro-fracture identification capability is stronger and stronger. The low-frequency coherent body has good identification effect on large fractures and poor identification effect on small faults; the high-frequency coherent body can improve the identification effect of micro fracture and deflection micro fault, and the low-frequency coherent body and the high-frequency coherent body are comprehensively applied to finish the fine carving of the converted fracture. Therefore, all seismic attribute bodies obtained by frequency-division coherent body extraction are fused to obtain an enhanced seismic data body, various faults can be better identified through the enhanced seismic data body, and a basis is provided for completing the identification and interpretation work of the current forms of the converted faults. FIG. 1D is a schematic diagram showing the result of coherent body extraction processing on a monosome.
And 104, carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
As the enhanced seismic data body strengthens the fine description of the seismic fault, the segmentation point information of the seismic fault to be identified can be obtained from the enhanced seismic data body, the identification interpretation work of the cash form of the conversion fault is completed based on the segmentation point information, namely, the dominant conversion fault is identified, and the conversion point information of the fault to be identified is obtained through analysis, so that the recovery of the form in the historical evolution period is completed, namely, the recessive conversion fault is identified.
The embodiment of the invention performs guiding filtering on the seismic data volume of the seismic fault to be identified under the constraint of the inclination angle body so as to realize smooth processing on the same-phase axis parallel to the seismic fault and improve the sharpness of the fault so as to improve the identification accuracy of the fault; and the seismic data volume is enhanced, so that the fault identification accuracy is improved.
Example two
Fig. 2A is a flowchart of a seismic fault identification method in the second embodiment of the present invention, and the second embodiment is further optimized based on the first embodiment. As shown in fig. 2A, the method includes:
And 203, performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume.
And 204, performing section interpolation on the fault data in the enhanced seismic data volume to obtain a fault model.
On the basis of performing optimization and enhancement processing on the seismic data volume, carrying out construction interpretation work on the seismic fault, completing construction model establishment according to the construction interpretation, and completing fault attribute analysis by utilizing the established construction model. The construction model comprises a fault model and an aspect model. The model construction can be performed through modeling based on a construction framework or modeling based on a corner grid, and the construction method is exemplified in the embodiment of the present invention.
The fault data in the enhanced seismic data volume is used for completing the work of section interpolation and model editing, the section form is adjusted, the intersection relation between the faults is processed, and a foundation is laid for the subsequent layer modeling.
And step 205, refining the bedding surface data in the enhanced seismic data body based on the fault model to obtain a stratum model so as to construct and explain the enhanced seismic data body.
And refining and creating an bedding surface model by using bedding surface data in the enhanced seismic data body, creating the bedding surface model based on the fault model, and forming a complete construction model, namely a stratum model, by using the two models. The attribute information of the seismic fault to be identified can be determined more intuitively and clearly based on the stratum model.
Illustratively, the constructed stratum model is subjected to gridding processing, a stepped grid is established, and the quickly generated stepped fault can be used for subsequent geological modeling and digital-analog research, fault plugging performance, lithology, physical analysis and other researches so as to improve the research efficiency and accuracy.
Optionally, the refining process includes processing a cross-connection relationship between a fault layer and a fault plane in the fault model.
And step 206, determining a fault identification result of the seismic fault to be identified according to the stratum model.
And according to the determined stratum model, realizing the identification of fault points and conversion points in the seismic fault to be identified from the model.
Optionally, step 206 includes: determining at least one attribute map of the seismic fault to be identified according to the stratum model, wherein the attribute map comprises the following attributes: a fault-break distance curve graph, a fault growth index curve graph, an ancient fault-break distance curve graph, a fault-break contour map and a fault-break buried depth contour map; and determining a fault identification result of the seismic fault to be identified according to the at least one attribute map.
After the stratum model is established, adding each fault distance value and buried depth value of a target layer into a fault attribute column, and extracting a fault distance contour map and a fault distance buried depth contour map; meanwhile, the formed structural diagram of each target layer is explained by using earthquake, and a fault-distance curve graph, a fault growth index curve graph and a paleofault-distance curve graph are counted. And (3) integrating the fault-break distance curve graph, the fault growth index curve graph, the paleofault-break distance curve graph, the fault-break contour map and the fault-break buried depth contour map, carrying out five-map fault attribute analysis, identifying paleofault segmentation points and conversion points, and dividing an evolution period conversion fault development part.
The five-graph method identifies fault segmentation points and conversion points by the following marks: on the pitch distance curve graph, the fault growth index curve graph and the ancient pitch distance curve graph, the segmentation points and the conversion points are represented as points with suddenly reduced pitch distance or points with suddenly zero pitch distance, and characteristics of early segmentation growth and later superposition of the connecting piece of the fault layer are indicated. In the fault-line contour diagram, the segmentation points and the conversion points are represented as zones of ellipse-to-strip transition, representing sudden reduction of the fault line; in the fault-throw-buried-depth contour plot, the segmentation points and the transition points appear as sudden deflections of the section contour, abrupt changes in morphology, indicating the presence of the transition points. For example, segmentation point and transition point identification results in a fault are shown in fig. 2B at labels 1, 2, and 3.
For example, fig. 2B shows a schematic diagram of determining a seismic fault recognition result by a quingram method, and shows an example of a technology for performing implicit conversion fault recognition and zone of old conversion reduction by a certain concave quingram method. FIG. 2B is a five-attribute diagram of F2 fault in the study area, wherein the F2 fault is a three-level control zone fracture with large development scale, the maximum fault distance locally reaches 600m, and the fault trap period continuously moves for a long time. From the statistical F2 fault distance graph, 3 points with suddenly reduced fault distance obviously exist in the fault, which shows that the activity intensity of different parts in the fault development process is different, and the 3 points with small fault distance correspond to the fault transition zone development position; the fault-line contour plot of the F2 fault also demonstrates the existence of 3 transition points; from the contour map of the buried depth of the section, 3 conversion points correspond to the parts of the section which are bent; the fault distance back stripping technology is used for recovering the paleofault distance of the F2 fault, and as can be seen from a paleofault distance curve graph, the fault obviously develops in a 3-section mode in the early stage, the fault is gradually connected into a single line in the later stage, and the 3-position section point corresponds to the position of the fault development converted in the early stage. The paleoconversion zone in the F2 fault development period can be recovered through a quingram method, the position of the fault for controlling the development of the sedimentary reservoir at the early stage is determined, and the exploration of a high-quality reservoir development area is guided.
According to the method, the stratum model is obtained by enhancing fault data and bedding surface data construction models in the seismic data body, the five graphs are determined based on the stratum model, the geometric morphology recognition of the current dominant conversion fracture of the seismic fault to be recognized is realized through the five-graph method, the kinematic process of recessive conversion fracture development in a certain historical period can be restored, and the accuracy and efficiency of fracture property recognition for controlling the reservoir development period and the key accumulation period are improved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a seismic fault identification device in a third embodiment of the present invention, which is applicable to identifying faults in a transition fault and guiding exploration of a high-quality reservoir development area. As shown in fig. 3, the apparatus includes:
and the inclination angle body determining module 310 is used for determining an inclination angle body according to the original seismic data body of the seismic fault to be identified.
And the guiding filtering module 320 is configured to perform guiding filtering on the seismic fault to be identified under the constraint of the dip angle body, and determine an optimized seismic data body.
And the seismic data volume enhancement module 330 is configured to perform enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume.
And the fault identification module 340 is configured to perform fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, where the fault identification result at least includes a segmentation point and/or a conversion point of the seismic fault to be identified.
The embodiment of the invention performs guiding filtering on the seismic data volume of the seismic fault to be identified under the constraint of the inclination angle body so as to realize smooth processing on the same-phase axis parallel to the seismic fault and improve the sharpness of the fault so as to improve the identification accuracy of the fault; and the seismic data volume is enhanced, so that the fault identification accuracy is improved.
Optionally, the fault identification module 340 includes:
the fault model determining unit is used for carrying out section interpolation on fault data in the enhanced seismic data volume to obtain a fault model;
the bottom layer model determining unit is used for carrying out thinning processing on the bedding surface data in the enhanced seismic data body based on the fault model to obtain a stratum model so as to construct and explain the enhanced seismic data body;
and the fault identification result determining unit is used for determining the fault identification result of the seismic fault to be identified according to the stratum model.
Optionally, the refining process includes processing a cross-connection relationship between a fault layer and a fault plane in the fault model.
Optionally, the fault identification result determining unit is specifically configured to:
determining at least one attribute map of the seismic fault to be identified according to the stratum model, wherein the attribute map comprises the following attributes: a fault-break distance curve graph, a fault growth index curve graph, an ancient fault-break distance curve graph, a fault-break contour map and a fault-break buried depth contour map;
and determining the fault identification result of the seismic fault to be identified according to the at least one attribute map.
Optionally, the inclinometer determination module 310 is specifically configured to:
and determining an inclination angle body by adopting a Fourier transform maximum amplitude method for an original seismic data body of the seismic fault to be identified.
Optionally, the guided filtering of the seismic fault to be identified includes dip-guided median filtering, dip-guided diffusion filtering, or fault edge preservation filtering.
Optionally, the seismic data volume enhancement module 330 is specifically configured to:
performing wavelet frequency division processing on the optimized seismic data volume to obtain a single frequency volume data volume of at least two frequency bands;
performing coherent body extraction processing on the single frequency body data body to obtain a seismic attribute body;
and fusing the seismic attribute bodies of at least two frequency bands to obtain an enhanced seismic data body.
The seismic fault recognition device provided by the embodiment of the invention can execute the seismic fault recognition method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the seismic fault recognition method.
Example four
Fig. 4 is a schematic structural diagram of an apparatus according to a fourth embodiment of the present invention. Fig. 4 illustrates a block diagram of an exemplary device 12 suitable for use in implementing embodiments of the present invention. The device 12 shown in fig. 4 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present invention.
As shown in FIG. 4, device 12 is in the form of a general purpose computing device. The components of device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory device 28, and a bus 18 that couples various system components including the system memory device 28 and the processing unit 16.
The system storage 28 may include computer system readable media in the form of volatile storage, such as Random Access Memory (RAM)30 and/or cache storage 32. Device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Storage 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in storage 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system storage device 28, for example, to implement the seismic fault identification method provided by the embodiment of the present invention, including:
determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
under the constraint of the inclination angle body, performing guiding filtering on the seismic fault to be identified, and determining an optimized seismic data body;
performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume;
and carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
EXAMPLE five
The fifth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the seismic fault identification method provided by the fifth embodiment of the present invention, and the method includes:
determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
under the constraint of the inclination angle body, performing guiding filtering on the seismic fault to be identified, and determining an optimized seismic data body;
performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume;
and carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A seismic fault identification method, comprising:
determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
under the constraint of the inclination angle body, performing guiding filtering on the seismic fault to be identified, and determining an optimized seismic data body;
performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume;
and carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
2. The method of claim 1, wherein performing fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified comprises:
performing section interpolation on the fault data in the enhanced seismic data volume to obtain a fault model;
refining the bedding surface data in the enhanced seismic data body based on the fault model to obtain a stratum model so as to construct and explain the enhanced seismic data body;
and determining the fault identification result of the seismic fault to be identified according to the stratum model.
3. The method of claim 2, wherein the refining process comprises processing a cross-over relationship between fault model fault layers and levels.
4. The method of claim 2, wherein determining the fault identification result for the seismic fault to be identified from the stratigraphic model comprises:
determining at least one attribute map of the seismic fault to be identified according to the stratum model, wherein the attribute map comprises the following attributes: a fault-break distance curve graph, a fault growth index curve graph, an ancient fault-break distance curve graph, a fault-break contour map and a fault-break buried depth contour map;
and determining the fault identification result of the seismic fault to be identified according to the at least one attribute map.
5. The method of claim 1, wherein determining the dip angle volume from the original seismic data volume of the seismic fault to be identified comprises:
and determining an inclination angle body by adopting a Fourier transform maximum amplitude method for an original seismic data body of the seismic fault to be identified.
6. The method of claim 1, wherein the guided filtering of the seismic fault to be identified comprises dip-guided median filtering, dip-guided diffusion filtering, or fault edge-preserving filtering.
7. The method of claim 1, wherein performing enhancement processing on the optimized seismic data volume to obtain an enhanced seismic data volume comprises:
performing wavelet frequency division processing on the optimized seismic data volume to obtain a single frequency volume data volume of at least two frequency bands;
performing coherent body extraction processing on the single frequency body data body to obtain a seismic attribute body;
and fusing the seismic attribute bodies of at least two frequency bands to obtain an enhanced seismic data body.
8. A seismic fault recognition device, comprising:
the inclination angle body determining module is used for determining an inclination angle body according to an original seismic data body of the seismic fault to be identified;
the guiding filtering module is used for guiding filtering of the seismic fault to be identified under the constraint of the inclination angle body and determining an optimized seismic data body;
the seismic data volume enhancement module is used for enhancing the optimized seismic data volume to obtain an enhanced seismic data volume;
and the fault identification module is used for carrying out fault identification processing on the enhanced seismic data volume to obtain a fault identification result of the seismic fault to be identified, wherein the fault identification result at least comprises a segmentation point and/or a conversion point of the seismic fault to be identified.
9. An apparatus, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the seismic fault identification method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the seismic fault identification method according to any one of claims 1 to 7.
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