CN111751871B

CN111751871B - Three-dimensional seismic edge layer coherent slice processing method and device and electronic equipment

Info

Publication number: CN111751871B
Application number: CN201910251412.5A
Authority: CN
Inventors: 刘万辉
Original assignee: China National Petroleum Corp; BGP Inc
Current assignee: China National Petroleum Corp; BGP Inc
Priority date: 2019-03-29
Filing date: 2019-03-29
Publication date: 2023-02-07
Anticipated expiration: 2039-03-29
Also published as: CN111751871A

Abstract

The application provides a three-dimensional seismic bedding coherent slice processing method, a device and electronic equipment, wherein the method comprises the following steps: filtering abnormal signal-to-noise ratio bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice with the band abnormal type only being fault abnormal; sharpening fault abnormal strips in the coherent slice to obtain a fault trajectory of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault trajectory; and automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval, and generating a corresponding azimuth angle distribution histogram. The method and the device can effectively improve the resolution ratio of the three-dimensional seismic bedding coherent slice, can effectively and quantitatively improve the reliability and the processing efficiency of the processing process, can automatically and accurately acquire the distribution condition of the azimuth angle, and can effectively improve the accuracy of fault identification.

Description

Three-dimensional seismic edge layer coherent slice processing method and device and electronic equipment

Technical Field

The application relates to the technical field of geophysical exploration, in particular to a three-dimensional seismic bedding coherent slice processing method and device and electronic equipment.

Background

The coherent data volume technique is to calculate the similarity between adjacent seismic traces, and then extract the along-layer similarity value along a specific stratum, thus obtaining the along-layer coherent slice. Coherent slicing has become one of the important technical means for identifying and analyzing faults using three-dimensional seismic data. Spatial discontinuities in the formation may result due to the presence of faults. The reflection on the seismic data is that the similarity between seismic channels in a certain range at two sides of the fault is reduced, and the figure 1b is shown. Each seismic trace is a curve corresponding to a specific point in space (for a three-dimensional seismic survey area, a CDP on a Line), the numerical value of each point on the curve represents the reflection amplitude of seismic waves, and the vertical position of each point on the curve corresponds to the two-way travel time (t 0) of the seismic waves in milliseconds (ms), which is shown in fig. 1a.

Near the fault, due to the poor similarity between adjacent seismic traces, a "discontinuity" anomalous band appears on the coherent slice, see FIG. 2a. Due to the lateral resolution limitations of the seismic survey itself, such "discontinuity" anomaly bands can have a certain "width" and fail to accurately locate the fault trajectory at a specific Line/CDP point. Although the impact on aided manual fault interpretation is low, if fault parameters (such as fault azimuth) are to be extracted along the fault trajectory, multiple parameter values may be calculated at one fault point. The wider the anomaly band (lower resolution), the more values are calculated, which makes subsequent quantitative analysis silent, and further affects the accuracy of fault identification and analysis using three-dimensional seismic data.

Therefore, a method for processing a three-dimensional seismic bedding coherent slice for a complex fracture system is needed to solve the problem of poor fault identification accuracy caused by improper processing of the coherent slice.

Disclosure of Invention

Aiming at the problems in the prior art, the application provides a three-dimensional seismic bedding coherent slice processing method, a three-dimensional seismic bedding coherent slice processing device and electronic equipment, which can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and the processing efficiency of the processing process, automatically and accurately acquire the distribution condition of an azimuth angle, and further effectively improve the accuracy of fault identification.

In order to solve the technical problem, the application provides the following technical scheme:

in a first aspect, the present application provides a three-dimensional seismic interval coherent slice processing method, including:

filtering abnormal signal-to-noise ratio bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice with the band abnormal type only being fault abnormal;

sharpening the fault abnormal strip in the coherent slice to obtain a fault trajectory of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault trajectory;

and automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval, and generating a corresponding azimuth angle distribution histogram.

Further, before the filtering the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic along-layer coherent slice of the target layer, the method further includes:

acquiring a three-dimensional seismic zonal coherence slice of a target zone;

gaussian filtering the coherent slice;

determining a change gradient value and a change gradient azimuth angle of the coherent slice after Gaussian filtering;

and respectively carrying out position matching on the change gradient value and the change gradient azimuth angle with the coherent slice.

Further, the determining a change gradient value and a change gradient azimuth angle of the gaussian filtered coherent slice includes:

and a first-order finite difference algorithm is applied to obtain a change gradient value and a change gradient azimuth angle of the coherent slice after Gaussian filtering.

Further, the filtering out the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice with the band abnormal type only being fault abnormal, includes:

filtering the abnormal signal-to-noise ratio bands in the coherent slice by applying a comparison result between a preset threshold range and the gradient value of each sampling point in the coherent slice to obtain the coherent slice with the abnormal band type only being fault abnormity;

correspondingly, if the gradient value of the sampling point is greater than the first threshold value, the sampling point is determined to be a fault abnormal point; if the gradient value of the sampling point is smaller than the second threshold value, setting the coherence value of the sampling point to be 0; if the gradient value of the sampling point is in the threshold range, further judging whether adjacent sampling points larger than the first threshold exist in each neighborhood of the sampling point, and if not, setting the coherence value of the sampling point to be 0.

Further, the sharpening the fault abnormal band in the coherent slice to obtain the fault trajectory of the coherent slice includes:

and sharpening fault abnormal strips in the coherent slices by applying a non-maximum suppression mode, so that each breakpoint in the coherent slices corresponds to an intersection point of a horizontal line and a vertical track in one coherent slice, and a fault track line of the coherent slice is obtained.

Further, the determining the fault strike azimuth at the corresponding fault point according to the fault trajectory line includes:

determining a corresponding gradient azimuth angle according to the fault trajectory;

and converting the gradient azimuth angle into a fault trend azimuth angle at the corresponding breakpoint.

In a second aspect, the present application provides a three-dimensional seismic interval coherent slice processing apparatus, comprising:

the filtering module is used for filtering the signal-to-noise ratio abnormal bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice with the band abnormal type only being fault abnormal;

the sharpening module is used for sharpening the fault abnormal strip in the coherent slice to obtain a fault track line of the coherent slice, and determining a fault trend azimuth angle at a corresponding breakpoint according to the fault track line;

and the histogram generation module is used for automatically counting azimuth angles in all directions of the coherent slice based on the fault azimuth angle and a preset azimuth angle interval and generating a corresponding azimuth angle distribution histogram.

Further, still include:

the slice acquisition module is used for acquiring a three-dimensional seismic bedding coherent slice of a target layer;

a filtering module for performing Gaussian filtering on the coherent slice;

the calculation module is used for determining a change gradient value and a change gradient azimuth angle of the coherent slice after Gaussian filtering;

and the position matching module is used for respectively carrying out position matching on the change gradient value and the change gradient azimuth angle with the coherent slice.

Further, the calculation module includes:

and the calculation unit is used for acquiring the change gradient value and the change gradient azimuth angle of the coherent slice after Gaussian filtering by applying a first-order finite difference algorithm.

Further, the filtering module includes:

the filtering unit is used for filtering an abnormal signal-to-noise ratio band in the coherent slice by applying a comparison result between a preset threshold range and gradient values of all sampling points in the coherent slice to obtain the coherent slice of which the band abnormal type is only fault abnormality;

Further, the sharpening module includes:

and the sharpening unit is used for sharpening fault abnormal strips in the coherent slices by applying a non-maximum suppression mode, so that each breakpoint in the coherent slices corresponds to an intersection point of a horizontal line and a vertical line in one coherent slice, and a fault track line of the coherent slice is obtained.

Further, the sharpening module includes:

the gradient azimuth angle acquisition unit is used for determining a corresponding gradient azimuth angle according to the fault trajectory line;

and the fault strike azimuth angle acquisition unit is used for converting the gradient azimuth angle into a fault strike azimuth angle at a corresponding breakpoint.

In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the three-dimensional seismic along-the-horizon coherent slice processing method when executing the program.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the three-dimensional seismic along-layer coherent slice processing method.

According to the technical scheme, the application provides a three-dimensional seismic along-layer coherent slice processing method, a device and electronic equipment, and the method comprises the following steps: filtering the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice of which the band abnormal type is only fault abnormality; sharpening fault abnormal strips in the coherent slice to obtain a fault trajectory of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault trajectory; the method comprises the steps of automatically counting azimuth angles in all directions of coherent slices based on fault orientation angles and preset orientation angle intervals, generating corresponding azimuth angle distribution histograms, effectively improving the resolution ratio of the three-dimensional seismic bedding coherent slices, effectively and quantitatively improving the reliability and the processing efficiency of the processing process, automatically and accurately acquiring the distribution conditions of the azimuth angles, further effectively improving the fault identification accuracy according to the coherent slices and the azimuth angle distribution histograms after the resolution ratio is improved, and providing an accurate data basis for petroleum exploration according to the fault identification result so as to improve the accuracy of the petroleum exploration process.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1a is a schematic seismic section of a typical developing multiple faults.

FIG. 1b is a partial enlarged view of three seismic "trace" waveforms on both sides of a fault and at a breakpoint, and the waveforms of the seismic traces (trace A and trace C) on both sides of the fault are different but usually not much different; the waveform of the seismic trace at the break point (trace B) is greatly different from that of the seismic trace at two sides (trace A and trace C) due to stratum fracture. Due to the fact that faults have certain dip angles, a 'fracture zone' spans a plurality of seismic traces in a certain time window (selected vertical intervals in the process of calculating coherence), and due to the fact that the transverse resolution factor of seismic exploration is added, each trace is affected by a certain adjacent range, and therefore 'discontinuity' abnormal strips related to the faults on coherent slices have certain widths.

FIG. 2a is a typical three-dimensional seismic interval coherence slice.

FIG. 2b is a diagram of the effect of a three-dimensional seismic interval coherent slice after Gaussian filtering.

Fig. 3 is a schematic flow chart of a three-dimensional seismic along-layer coherent slice processing method in an embodiment of the present application.

Fig. 4 is a schematic flow chart of steps 001 to 004 in the three-dimensional seismic along-the-horizon coherent slice processing method in the embodiment of the present application.

FIG. 5 is a flow chart illustrating step 200 of a three-dimensional seismic interval coherent slicing method in an embodiment of the present application.

FIG. 6a is a logic diagram of the horizontal-vertical operator for calculating the gradient value and the azimuth angle of the coherent slice in the application example of the present application.

FIG. 6b is a logic diagram of the diagonal operators for calculating gradient values and azimuth angles of coherent slice in the application example of the present application.

FIG. 7a is a diagram illustrating coherence gradient values calculated by Sobel "horizontal-vertical operator" in an example of application of the present application.

FIG. 7b is a schematic diagram of the coherence gradient value calculated by the "diagonal operator" in the application example of the present application.

FIG. 7c is a diagram showing the result of fusion of the coherence gradient value calculated by the "horizontal-vertical operator" and the "diagonal operator" in the application example of the present application.

Fig. 8a is a schematic diagram of a locally enlarged coherent slice in an application example of the present application.

Fig. 8b is a schematic diagram of a partially enlarged gradient value in an application example of the present application.

Fig. 9a is a schematic diagram of the intersection of a coherent slice and a gradient in an application example of the present application.

Fig. 9b is a schematic diagram of the intersection of coherent slice and gradient value after position matching in the application example of the present application.

Fig. 10a is a schematic diagram of gaussian filtered coherent slicing in an embodiment of the present application.

FIG. 10b is a schematic diagram of coherent slicing after Gaussian filtering and after "low gradient value occlusion" in the embodiment of the present application.

FIG. 10c is a schematic diagram of a coherent slice after "sharpening" based on "low gradient value occlusion" in the embodiment of the present application.

Fig. 11 is a schematic structural diagram of a three-dimensional seismic along-layer coherent slice processing apparatus in an embodiment of the present application.

Fig. 12 is a schematic structural diagram of an electronic device in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The coherent data volume technology is to calculate the similarity between adjacent seismic traces, and then extract the similarity value of the boundary along a specific stratum, so as to obtain the boundary coherent slice. In places without faults, the adjacent seismic channels have good similarity and show a continuous background on a coherent slice; near the fault, due to the poor similarity between adjacent seismic traces, see 1b, an anomalous band of "discontinuities" appears on the coherent slice, see FIG. 2a. Due to the lateral resolution limitations of seismic surveys themselves, such "discontinuity" anomaly bands can have a certain "width" and fail to accurately locate the fault trajectory at the intersection of a specific horizontal and vertical trace (Line/CDP point). Although the effect is not great in assisting manual fault interpretation, if fault parameters (such as fault azimuth) are to be extracted along fault trajectory lines, multiple parameter values may be calculated at one fault point. The wider the anomaly band (lower resolution), the more values are calculated, which makes subsequent quantitative analysis silent.

Faults and folds are combined to refer to the two most prominent deformation phenomena of geological structures, and are closely related. Modern constructivity holds that the form and scale of a wrinkle depend on the occurrence of faults, disconnected horizons, section forms, spatial variations thereof and the like adjacent to the wrinkle in the same stress field, and the wrinkle is called Fault-related wrinkles (Fault-related Folds). Depending on the relationship between Folds and faults, they are classified into Fault-bending Folds (Fault-bending Folds), fault-sliding Folds (Fault-sliding Folds), and Fault-propagation Folds (Fault-propagation Folds). Therefore, fault research is the most important research content in tectogeology.

For the description of faults, three elements are included: fault properties, fault occurrence, fault distance, and disconnected horizon, etc. Wherein fault occurrence (including dip and strike) is an important parameter that characterizes the formation stress field of a zone. In particular, the fault strike, i.e. the extension direction of the plane trajectory of the fault (which can be described by the azimuth angle), is an important index for reflecting the structural stress direction.

In the case of relatively complex fracture systems, a fracture system that may be of non-structural origin (or not formed mainly by structural motion) has been newly discovered in many areas in the past, especially in recent years, and is characterized by a large number of faults, a short extension of a single fault plane and a uniform length, and most importantly, by no apparent directionality, see fig. 2a. And many faults are connected end to end, and the trend of a single fault is difficult to determine. This fault is currently known by the academia as multilateral Faults (polygon Faults) and there is a close link between their formation, development and the formation of the oil and gas system. The analytical research on the fault is of great significance in oil and gas exploration.

For the fault, the geological significance contained in fault azimuth angle information cannot be effectively expressed by conventional means such as a tectonic graph and a seismic coherent data volume slice along the layer. Therefore, considering the fact that there are a great number of faults with complex orientation (azimuth) and whether their azimuths have dominant directions, if any, and how to do scientific and quantitative analysis, etc., based on the above considerations, the present application provides a three-dimensional seismic horizon coherent slice processing method, a three-dimensional seismic horizon coherent slice processing apparatus, an electronic device and a computer readable storage medium, which can locate each fault trace to a specific single Line/CDP point by performing a series of processing on coherent slices to "sharpen" abnormal bands on the coherent slices. Then extracting corresponding fault strike (extending direction) values (quantitative azimuth data) according to the positions of the fault track lines, and automatically counting histogram distribution data according to given azimuth intervals to realize the quantification of fault strike analysis. That is to say, the three-dimensional seismic bedding coherent slice processing method provided by the application is a method for improving resolution processing, automatically calculating an azimuth angle and counting an azimuth angle distribution histogram for a three-dimensional seismic coherent slice of a complex fracture system, can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of a processing process, and automatically and accurately acquire the distribution condition of the azimuth angle, so that the accuracy of fault identification can be effectively improved according to the coherent slice and the azimuth angle distribution histogram after the resolution is improved, and an accurate data base is provided for oil exploration according to the result of the fault identification, so that the accuracy of the oil exploration process is improved.

Based on the above, the present application further provides a three-dimensional seismic along-horizon coherent slice processing apparatus, which may be a processor, where the processor may be communicatively connected to at least one client device, or may be communicatively connected to at least one server, and the processor may receive, through the client device, three-dimensional seismic data input by a user, and run generation software of the along-horizon coherent slice according to an instruction to obtain a corresponding coherent slice according to the three-dimensional seismic data, or the processor may directly receive a three-dimensional seismic along-horizon coherent slice sent by the client device or the server. Then, the processor filters the signal-to-noise ratio abnormal bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice of which the band abnormal type is only fault abnormal; sharpening the fault abnormal strip in the coherent slice to obtain a fault trajectory of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault trajectory; and automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval, generating a corresponding azimuth angle distribution histogram, and sending the sharpened three-dimensional earthquake bedding coherent slice and the azimuth angle distribution histogram to client equipment with a display screen for displaying.

In addition, the processor may be provided in the client device, or the processor may be replaced with a software program installed in the client device. For example, the client device may specifically include a smart phone, a tablet electronic device, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, and a smart wearable device with a display function. Wherein, intelligence wearing equipment can specifically contain intelligent glasses, intelligent wrist-watch and intelligent bracelet etc. that have the display function.

The client device may have a communication module (i.e., a communication unit), and may be communicatively connected to a remote server to implement data transmission with the server. The communication unit can also receive a data processing result returned by the server. The server may specifically include a server on the task scheduling center side, and in other implementation scenarios, the server may also specifically include a server of an intermediate platform, for example, a server of a third-party server platform having a communication link with the task scheduling center server. The server may specifically include a single computer device, or may specifically include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.

The server and the client device may communicate using any suitable network protocol, including network protocols not yet developed at the filing date of this application. The network protocol may specifically include, for example, a TCP/IP protocol, a UDP/IP protocol, an HTTP protocol, an HTTPs protocol, and the like. Of course, the network Protocol may also specifically include, for example, an RPC Protocol (Remote Procedure Call Protocol), a REST Protocol (Representational State Transfer Protocol), and the like used above the above Protocol.

In order to effectively improve the resolution of a three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and the processing efficiency of a processing process, automatically and accurately acquire the distribution condition of an azimuth angle, and further effectively improve the accuracy of fault identification, the application provides an embodiment of a three-dimensional seismic bedding coherent slice processing method, which specifically includes the following contents, referring to fig. 3:

step 100: and filtering the abnormal signal-to-noise ratio bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain the coherent slice with the band abnormal type only being fault abnormal.

In step 100, the three-dimensional seismic horizon coherent slice processing device first obtains a preprocessed three-dimensional seismic horizon coherent slice of a target horizon, and then performs "dual threshold" and "low gradient value" blocking on the coherent slice to filter "discontinuity" abnormality caused by low signal-to-noise ratio of seismic data, so as to ensure that the remaining abnormal zones are all generated due to faults.

Step 200: and sharpening the fault abnormal strip in the coherent slice to obtain a fault trajectory line of the coherent slice, and determining a fault trend azimuth angle at a corresponding breakpoint according to the fault trajectory line.

In step 200, the three-dimensional seismic horizon coherent slice processing apparatus performs "sharpening" processing on "discontinuity" abnormal bands on the "low gradient value" shielded coherent slice, so as to ensure that each breakpoint corresponds to a single intersection point ("Line/Trace" point) of a horizontal Line and a vertical Line.

Step 300: and automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval, and generating a corresponding azimuth angle distribution histogram.

In step 300, the three-dimensional seismic bedding coherent slice processing device extracts a gradient azimuth from the "sharpened" fault trajectory line position, converts the gradient azimuth into a fault strike azimuth (which is perpendicular to each other) at the fault point, and automatically distributes histograms of azimuths in various directions according to a given strike azimuth interval.

From the above description, the three-dimensional seismic bedding coherent slice processing method provided in the embodiment of the present application can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately obtain the distribution of the azimuth angle, so that the accuracy of fault identification can be effectively improved according to the coherent slice and the distribution histogram of the azimuth angle after the resolution is improved, and an accurate data basis is provided for oil exploration according to the result of the fault identification, so as to improve the accuracy of the oil exploration process.

In order to provide a more accurate and reliable data base for the subsequent processing process of the coherent slice, so as to further improve the resolution of the three-dimensional seismic interval coherent slice, in an embodiment of the three-dimensional seismic interval coherent slice processing method of the present application, referring to fig. 4, step 100 of the three-dimensional seismic interval coherent slice processing method further includes steps 001 to step 004, which include the following specifically:

step 001: and acquiring a three-dimensional seismic bedding coherent slice of the target layer.

Step 002: gaussian filtering is performed on the coherent slice.

Step 003: and determining a change gradient value and a change gradient azimuth angle of the Gaussian filtered coherent slice.

In step 003, the three-dimensional seismic interval coherent slice processing apparatus applies a first-order finite difference algorithm to obtain a variation gradient value and a variation gradient azimuth of the gaussian-filtered coherent slice.

Step 004: and respectively carrying out position matching on the change gradient value and the change gradient azimuth angle with the coherent slice.

In order to improve the reliability and accuracy of filtering the abnormal signal-to-noise ratio bands in the coherent slice, further improve the resolution of the three-dimensional seismic interval coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately acquire the distribution condition of the azimuth angle, thereby effectively improving the accuracy of fault identification, in the embodiment of the three-dimensional seismic interval coherent slice processing method, step 100 of the three-dimensional seismic interval coherent slice processing method specifically comprises the following contents:

and filtering the abnormal signal-to-noise ratio bands in the coherent slice by applying a comparison result between a preset threshold range and the gradient value of each sampling point in the coherent slice to obtain the coherent slice with the abnormal band type only being fault abnormity.

In order to improve the reliability and accuracy of sharpening the fault abnormal band, so as to further improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately acquire the distribution condition of the azimuth angle, thereby effectively improving the accuracy of fault identification, in an embodiment of the three-dimensional seismic bedding coherent slice processing method of the present application, referring to fig. 5, a step 200 of the three-dimensional seismic bedding coherent slice processing method specifically includes the following contents:

step 201: and sharpening fault abnormal strips in the coherent slices by applying a non-maximum suppression mode, so that each breakpoint in the coherent slices corresponds to an intersection point of a horizontal line and a vertical track in one coherent slice, and a fault track line of the coherent slice is obtained.

In order to improve the reliability and accuracy of obtaining a fault strike azimuth at a breakpoint, so as to further improve the resolution of a three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of a processing process, and automatically and accurately obtain the distribution condition of an azimuth, thereby effectively improving the accuracy of fault identification, in an embodiment of a three-dimensional seismic bedding coherent slice processing method of the present application, referring to fig. 5, a step 200 of the three-dimensional seismic bedding coherent slice processing method specifically includes the following contents:

step 202: and determining a corresponding gradient azimuth angle according to the fault trajectory.

Step 203: and converting the gradient azimuth angle into a fault strike azimuth angle at the corresponding breakpoint.

To further explain the scheme, the application also provides a specific application example of the three-dimensional seismic interval coherent slice processing method, which specifically comprises the following contents:

s1: basic data acquisition

On professional software, a coherent data volume is calculated and an along-layer coherent slice is extracted, and then a coherent slice file is output, which should include three columns: line number (Line No.), track number (Trace No.), and coherence value of the corresponding point.

S2: gaussian filtering of coherent slices

The directly output coherent slice has a low signal-to-noise ratio, and has some high-frequency anomalies locally, which is shown in fig. 2a, and can adversely affect the stability of subsequent calculations. After gaussian filtering, local high frequency anomalies are effectively suppressed, and the planar change of the graph is smoother, as shown in fig. 2b.

The C language code implementation of the graphics processing in S2 is shown in table 1.

TABLE 1

The Gaussian filtering is two-dimensional (in the longitudinal direction and the transverse direction), a two-dimensional Gaussian filter can be designed to carry out primary filtering treatment, a one-dimensional Gaussian filter can also be designed to carry out primary filtering treatment in two directions in sequence, and the two are completely equivalent. However, the code implementation of performing the filtering processing twice by using the one-dimensional filter is simpler, easier to read and easier to understand, so that the one-dimensional gaussian filter adopted by the code performs the filtering processing twice in sequence along the directions of a Line (Line) and a Trace (Trace).

The smoothing effect of gaussian filtering is ideal, and subsequent calculations, if involving coherent data, are performed on the gaussian filtered data without using the original coherent slice data.

S3: calculating the plane-varying gradient value of the coherence value and the azimuth angle of the varying gradient

The Gaussian filtering is two-dimensional (in the longitudinal direction and the transverse direction), a two-dimensional Gaussian filter can be designed to carry out filtering processing once, and a one-dimensional Gaussian filter can be designed to carry out filtering processing once along the two directions in sequence, and the two filtering processes are completely equivalent. However, the code implementation of performing the filtering processing twice by using the one-dimensional filter is simpler, easier to read and easier to understand, so that the one-dimensional gaussian filter adopted by the code performs the filtering processing twice in sequence along the directions of a Line (Line) and a Trace (Trace).

(3) The plane-varying gradient value of the coherence value and the azimuth angle of the varying gradient are calculated.

If the coherent slice is regarded as a black and white gray scale image, the abnormal strip representing strong discontinuity of the fault is a high gray scale region, and the weak discontinuity region without the fault is a relatively low gray scale region, the gradient (change rate) of the gray scale change between each point (representing the strength of the discontinuity) and the adjacent sample point on the coherent slice and the azimuth angle of the change gradient can be calculated by using a first-order finite difference algorithm for a long time.

Because the fault track is distributed in a line shape on a plane, the azimuth angle with the maximum gradient change between the fault and the adjacent fault-free zone is perpendicular to the 'trend' (the extending direction of the fault track line) of the fault track at the point, and the gradient azimuth angle corresponding to each point on the fault track line can be easily converted into the fault 'trend' azimuth angle at the point.

The first order finite difference for discrete points (one point for each Line/Trace pair on the coherent slice) can be achieved by a Sobel operator, which has two forms, a "horizontal-vertical operator" as shown in FIG. 6a and a "diagonal operator" as shown in FIG. 6 b. Actual calculation tests show that the two methods have good detection sensitivity to near horizontal (namely, east-west direction in geographic sense) and near vertical (namely, north-south direction in geographic sense), but the horizontal-vertical operator reacts more sensitively to upper-left-lower-right (namely, north-south-east direction in geographic sense) coherent anomalies, as shown in the arrow of fig. 7a, and the diagonal operator has better continuity of calculation effect to upper-right-lower-left (namely, north-south-east direction in geographic sense) coherent anomalies, as shown in the arrow of fig. 7 b. Then, the gradient values calculated by the two operators can be fused according to the gradient azimuth angle of each sampling point, and the fusion principle is that the calculation result of the diagonal operator is taken as the fused value in the direction from upper right to lower left of the gradient direction (the azimuth angle is between-22.5 degrees and-67.5 degrees); and for sampling points with other gradient directions in the horizontal direction, the vertical direction and the upper-left-lower-right direction, taking the result calculated by the 'horizontal-vertical operator' operator as a fused value. Thus, the fused gradient values have better response to the gradient change abnormality in each direction, as shown by the arrows in FIG. 7 c.

The specific operation steps are as follows:

(1) and (3) calculating gradient values and gradient azimuth angles of the coherent slice by using a Sobel 'horizontal-vertical operator', wherein the calculation formula is as follows:

Gx＝(Gauss2[i+1][j]+2*Gauss2[i+1][j+1])+(Gauss2[i][j+1])-(2*Gauss2[i-1][j-1]+Gauss2[i-1][j])+(Gauss2[i][j-1]) (1)

Gy＝(Gauss2[i-1][j]+2*Gauss2[i-1][j+1])+(Gauss2[i][j+1])-(2*Gauss2[i+1][j-1]+Gauss2[i+1][j])+(Gauss2[i][j-1]) (2)

G＝sqrt(Gx2+Gy2)) (3)

θ＝arctan(Gy/Gx)) (4)

wherein:

gauss [ i ] [ j ] -, the coherent value after Gaussian filtering at the ith row and the jth column;

g-gradient value;

sqrt () -square-on operation;

theta-gradient azimuth (in radians);

arctan () -arctangent calculation.

The C language code implementation of S3 is shown in table 2.

TABLE 2

Note that the last part of the code converts "gradient azimuth" to "gradient direction". Since the distribution of the calculated gradient azimuth angles is between-180 degrees and +180 degrees (the calculation result is in radians, for more intuition, "radians" has been converted to "angles" by the formula "gradthta [ i ] [ j ]. Times.180/3.1415926" in the code), in practice, the gradient azimuth angle data is not directly used in the subsequent processing calculation. But determines a certain appointed sampling point to compare with 4 directions (up and down, left and right, upper left, lower left and lower right) composed of 8 neighborhoods (up and down, left and right, upper right-lower left and upper left-lower right) according to the gradient azimuth angle and calculates, and lays a foundation for subsequent calculation through conversion at the position.

(2) The gradient values of the coherent slice are calculated using Sobel "diagonal operators".

It is not meaningful for the "diagonal operator" to calculate the gradient azimuth, only the gradient value. The calculation formula is the same as a horizontal-vertical operator; the code implementation is also similar, and no code is attached here.

(3) Fusing results calculated using two different operators

As mentioned above, for the point with gradient azimuth angle between-22.5 degrees and-67.5 degrees, the calculation result of the diagonal operator is taken as the fusion value; and taking the extreme result of the horizontal-vertical operator as a fusion value.

S4: position matching of gradient value and gradient azimuth calculation result with coherent slice

The Sobel algorithm is an edge detection method, and the maximum value of the calculated variation gradient will appear at the boundary between the "discontinuous" abnormal zone representing the fault and the background zone without the fault, so the strong gradient abnormality and the strong "discontinuous" abnormality are not matched in position, see fig. 8a and 8b, wherein the position of the cross line is the same, but it can be seen that the strong abnormal strip of the two is not matched in position, the gradient value is deviated to the lower left, that is, the position where the variation gradient appears lags behind the coherent slice by one unit in both directions of the "line/track", which will cause adverse effect on the next step of "low gradient value shielding". Through comparison of actual data calculation results, the gradient value abnormity is found to lag behind the coherent abnormity by one sampling point in the longitudinal direction and the transverse direction, and the position of one sampling point is translated in two directions. While the gradient azimuth contrast coherent slice lags behind one sample point in the Trace (CDP) direction and leads three sample points in the Line direction, and position matching can also be realized through proper translation. The C language code implementation is shown in table 3:

TABLE 3

After the position translation, the strong gradient value and the strong discontinuity are abnormally matched, as shown in an intersection graph of the coherent slice and the gradient shown in fig. 9a and an intersection graph of the coherent slice and the gradient value after the position matching shown in fig. 9b, it can be seen that after the position matching, the linear correlation relationship between the coherent slice and the gradient value is more obvious, and thus, a strong discontinuity coherent slice abnormal band corresponding to a relatively high gradient value can be well kept when the subsequent shielding of a low gradient value is performed.

S5: masking the coherent slice after Gaussian filtering with low gradient value "

On the relevant slice, there are two factors that cause the "discontinuity" anomaly: one is the presence of faults and the other is due to the low signal-to-noise ratio of the geological data. Due to the factors such as the difference of the ground topography or the complex structural form of the underground, in a three-dimensional survey area, some local low signal-to-noise ratios always appear as irregular 'discontinuity' anomalies on seismic coherent slices. However, the "discontinuity" anomaly bands due to the low signal-to-noise ratio of seismic data are different from faults, and are relatively uniform and have no obvious boundaries inside. Therefore, their corresponding gradient of variation appears to be relatively low. Correspondingly, the fault and the neighborhood show high gradient value abnormity because the coherence value difference is obvious.

According to the phenomenon, the coherent slice after Gaussian filtering can be shielded by a low gradient value, and mathematically, the coherent value of which the gradient value is lower than a certain threshold value is set to be 0. The selection of the threshold value is very important, and if the selection is too low, discontinuity abnormity caused by all non-fault layers cannot be effectively filtered; if the selection is too high, some fault-type 'discontinuity' abnormal belts with lower variation gradient due to smaller fault distance can be 'mistakenly killed'. Both of these cases can cause distortion in the final calculation.

In order to achieve effective "low gradient value occlusion" of the gaussian filtered coherent slice, it needs to be done in two steps.

(1) A gradient "threshold" is determined.

According to the method, the shielding calculation is carried out by adopting a method of 'double threshold values' or 'double threshold values', and a better effect is obtained. If the gradient value at a certain point is greater than a high threshold value, the corresponding coherence value is considered to be caused by faults, and the coherence value (after Gaussian filtering) is kept unchanged; if the gradient value at a certain point is smaller than a low threshold value, the point can be a background area without fault, and the corresponding coherence value is set to be 0; if the gradient value at a certain point is between the high threshold value and the low threshold value, whether 8 neighborhoods (upper, lower, left, right, upper left, lower left and lower right) of the certain point have points larger than the high threshold value or not is judged, if yes, the fault is regarded as a fault, the original value is reserved, and if not, the fault is set as '0'.

The "high threshold" is determined by accumulating histograms, i.e.: and selecting the gradient value corresponding to the gradient value reaching 85% of the gradient cumulative histogram as a high threshold value. The theoretical basis is that although the fracture system is relatively complex and the fracture number is relatively large, the fracture-free region (with relatively low gradient value) serving as the background is still significantly larger in area than the region with fracture development (with relatively high gradient value), and then the histogram statistics is performed according to the gradient values from small to large, and the "high threshold" should occur at least when the cumulative histogram reaches more than 60%. In actual calculation, the test is started when the cumulative histogram reaches 60%, and each time a percentile is added, and the final test result is that the "high threshold" has the best effect of taking the gradient value corresponding to the cumulative histogram when the gradient reaches 85%, see the coherent slice after gaussian filtering shown in fig. 10a and the coherent slice after gaussian filtering and after shielding by the "low gradient value" shown in fig. 10b. Taking half of the "high threshold" as the "low threshold" is a proven effective "low threshold" determination method in the graphics processing field. The C language code implementation is shown in table 4:

TABLE 4

(2) And carrying out low gradient value occlusion processing according to the determined double thresholds. The C language code implementation is shown in table 5:

TABLE 5

S6: carrying out sharpening on the Gaussian filtered coherent slice shielded by low gradient value

On the coherent slice after the "low gradient value occlusion", only the strong "discontinuity" anomalies due to faults are retained, see fig. 10b. These strong "discontinuity" anomalies indicate the presence of a fault, but do not determine the precise location of the breakpoint. Because the strip-shaped anomalies are all of a certain width, in order to determine the precise position of the fault trajectory Line for the next step of automatically counting the fault trend histogram, the strip-shaped anomalies need to be sharpened, and each breakpoint corresponds to a unique Line/track (Line/Trace).

The "sharpening" is realized by the "Non-Maximum Suppression (Non-Maximum Suppression)", and the specific method is to compare the magnitude of the coherence value after the "low gradient value occlusion" according to the gradient direction (converted from the gradient azimuth angle and divided into 4 directions of horizontal, vertical, upper-left-lower-right, and lower-left-upper-right) calculated in step S3, and only the Maximum value is retained, and the rest is "0". The visual effect is that the strong discontinuity and abnormal band with certain width are compressed into the strong discontinuity and abnormal line with the width value of 1. This "anomaly line" is the fault trajectory line, whose position is taken perpendicular to the center point of the strong "discontinuity" or "anomaly zone" (the point where the gradient value is greatest), see FIG. 10c. The C language code implementation is shown in table 6:

TABLE 6

S7: automatic statistics fault azimuth histogram

The precise location of the fault trajectory on the coherent slice is determined by the "sharpening" process of the previous step. Then, gradient azimuth information of corresponding points can be extracted according to the positions of the fault trajectory lines. According to the rule that the gradient azimuth is perpendicular to the fault orientation azimuth of the corresponding point, the gradient azimuth can be conveniently converted into the fault orientation azimuth. A fault strike azimuth histogram may then be automatically computed based on the given walk azimuth interval.

Geologically, the fault strike azimuth distribution is [0 °,180 °), i.e.: the north is 0 degrees, the counterclockwise is increased, the north is 90 degrees, and the west is 180 degrees. The gradient azimuth angle (unit is radian, for the sake of intuition, the code has been converted into an angle) calculated in the step S3 is 0 ° due to north, is increased counterclockwise to west by +90 °, and is decreased clockwise to east by-90 °. According to the corresponding relation, the gradient azimuth angle can be converted into the fault strike azimuth angle, and the C language code is realized as shown in the table 7:

TABLE 7

In the above example, the statistics are performed every 15 azimuth intervals. The calculation can be done at virtually any azimuth interval (as long as it is evenly divisible by 180 to ensure that each azimuth interval is equal), simply by modifying the code. The results of the outputs of the actual data are shown in Table 8:

TABLE 8

Where "AzimuthHisto [ k ]" represents the number of fault-like points in the "k" th histogram bin. Incrementing the "k" value from "1" to "12" represents each partition from the right east counterclockwise to the right west. Based on this output, the histogram can be easily created in other software.

From the above, the core of the three-dimensional seismic along-layer coherent slice processing method provided by the application example of the present application lies in that the coherent slice is taken as a gray image, and by means of the gradient value and gradient azimuth calculation technique in the graphic processing technique, the gaussian filtering processing is performed on the coherent slice, and then the plane change characteristic of the coherence value (representing the strength of "discontinuity" between the point and the adjacent point) of each sample point on the coherent slice is obtained. And then, the position matching of the strong gradient anomaly and the strong coherent anomaly is ensured by carrying out translation processing on the gradient value and the gradient azimuth angle. On the basis, the 'earth gradient value shielding' processing is carried out on the coherent slice after Gaussian filtering so as to filter out strong 'discontinuity' abnormity caused by earthquake low signal-to-noise ratio and only keep an abnormal zone generated by a fault. Then, the reserved fault type strong discontinuity abnormal band is subjected to sharpening processing (mathematically called Non-maximum Suppression) to obtain an accurate fault track line, so that the plane resolution of the coherent slice is greatly improved. Then, gradient azimuth information is extracted according to the obtained fault trajectory, and the gradient azimuth is converted into a fault heading azimuth according to the relation that the gradient azimuth is perpendicular to the fault heading azimuth. On the basis, the fault strike azimuth partition number can be determined according to the given fault strike azimuth interval, and a fault strike azimuth histogram is automatically calculated. The thinking, the method and the implementation process of coherent abnormity caused by faults in all directions are accommodated by comparing gradient values calculated by two Sobel operators and fusing according to gradient azimuth angles; matching the gradient value and gradient azimuth data obtained by calculation with the coherent slice obtained by calculation, and checking through a cross plot; the thinking, the method and the implementation process of carrying out double threshold value and low gradient value shielding on the coherent slice so as to filter out strong discontinuity abnormity caused by non-fault factors (low signal to noise ratio of seismic data); the thinking and the method convert the gradient azimuth angle distributed in the intervals of [0 degrees and +/-90 degrees into the fault strike azimuth angle distributed in the intervals of [0 degrees and +/-180 degrees according to the relationship that the gradient azimuth angle and the fault strike azimuth angle are mutually perpendicular; the thinking, the method and the implementation process of extracting the gradient azimuth angle and converting the gradient azimuth angle into the fault trend azimuth angle according to the sharpened fault trajectory line position (the sharpened fault trajectory line belongs to non-maximum suppression in the graphic processing technology and is a mature technical means).

(1) The circuit is clear, and the steps are clear.

(2) Accurate, reliable and quantitative.

(3) High efficiency, and all the work is completed by a computer through programming.

(4) For a particularly complex fracture system, manual statistics of the fault trend distribution histogram is almost impossible, and the invention is not limited by the fracture complexity.

(5) And C language codes of all processes are debugged, so that the industrial production can be quickly realized.

In order to effectively improve the resolution of a three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of a processing process, automatically and accurately acquire the distribution condition of an azimuth angle, and further effectively improve the accuracy of fault identification, the application provides an embodiment of a three-dimensional seismic bedding coherent slice processing apparatus for implementing all or part of the contents in the three-dimensional seismic bedding coherent slice processing method, and referring to fig. 11, the three-dimensional seismic bedding coherent slice processing apparatus specifically includes the following contents:

and the filtering module 10 is configured to filter the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer, so as to obtain a coherent slice with a band abnormal type only being fault abnormal.

And the sharpening module 20 is configured to sharpen the abnormal fault band in the coherent slice to obtain a fault trajectory of the coherent slice, and determine a fault heading azimuth at a corresponding breakpoint according to the fault trajectory.

A histogram generating module 30, configured to automatically count azimuth angles in each direction of the coherent slice based on the fault heading azimuth angle and a preset heading azimuth angle interval, and generate a corresponding azimuth angle distribution histogram.

From the above description, the three-dimensional seismic bedding coherent slice processing device provided in the embodiment of the present application can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately obtain the distribution of the azimuth angle, so that the accuracy of fault identification can be effectively improved according to the coherent slice and the distribution histogram of the azimuth angle after the resolution is improved, and an accurate data basis is provided for oil exploration according to the result of the fault identification, so as to improve the accuracy of the oil exploration process.

In order to provide a more accurate and reliable data base for the subsequent coherent slice processing process, so as to further improve the resolution of the three-dimensional seismic interval coherent slice, in an embodiment of the three-dimensional seismic interval coherent slice processing apparatus of the present application, the following contents are further specifically included:

a filtering module for performing Gaussian filtering on the coherent slice;

the position matching module specifically comprises the following contents:

and the position matching unit is used for acquiring the change gradient value and the change gradient azimuth angle of the coherent slice after Gaussian filtering by applying a first-order finite difference algorithm.

In order to improve the reliability and accuracy of filtering the abnormal signal-to-noise ratio bands in the coherent slice, further improve the resolution of the three-dimensional seismic edge coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately obtain the distribution of azimuth angles, thereby effectively improving the accuracy of fault identification, in an embodiment of the three-dimensional seismic edge coherent slice processing apparatus of the present application, the filtering module 10 of the three-dimensional seismic edge coherent slice processing apparatus specifically includes the following contents:

and the filtering unit is used for filtering the abnormal signal-to-noise ratio band in the coherent slice by applying a comparison result between a preset threshold range and the gradient value of each sampling point in the coherent slice to obtain the coherent slice with the abnormal band type only being fault abnormity.

In order to improve the reliability and accuracy of sharpening the abnormal fault band, so as to further improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately obtain the distribution of azimuth angles, thereby effectively improving the accuracy of fault identification, in an embodiment of the three-dimensional seismic bedding coherent slice processing apparatus of the present application, the sharpening module 20 of the three-dimensional seismic bedding coherent slice processing apparatus specifically includes the following contents:

In order to improve the reliability and accuracy of obtaining a fault strike azimuth at a breakpoint, so as to further improve the resolution of a three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of a processing process, and automatically and accurately obtain the distribution of the azimuth, and further effectively improve the accuracy of fault identification, in an embodiment of a three-dimensional seismic bedding coherent slice processing apparatus according to the present application, the sharpening module 20 of the three-dimensional seismic bedding coherent slice processing apparatus specifically includes the following contents:

From a hardware level, an embodiment of the present application further provides a specific implementation manner of an electronic device capable of implementing all steps in the three-dimensional seismic along-layer coherent slice processing method in the foregoing embodiment, and referring to fig. 12, the electronic device specifically includes the following contents:

a processor (processor) 601, a memory (memory) 602, a communication Interface (Communications Interface) 603, and a bus 604;

the processor 601, the memory 602 and the communication interface 603 complete mutual communication through the bus 604; the communication interface 603 is used for realizing information transmission among the three-dimensional seismic bedding coherent slice processing device, the front-end display, the client terminal and other participating mechanisms;

the processor 601 is configured to invoke a computer program in the memory 602, and the processor implements all the steps of the three-dimensional seismic layer coherent slicing processing method in the above embodiment when executing the computer program, for example, the processor implements the following steps when executing the computer program:

From the above description, the electronic device provided in the embodiment of the present application can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately acquire the distribution of the azimuth angle, so that the accuracy of fault identification can be effectively improved according to the coherent slice after the resolution is improved and the distribution histogram of the azimuth angle, and an accurate data basis is provided for oil exploration according to the result of the fault identification, so as to improve the accuracy of the oil exploration process.

Embodiments of the present application further provide a computer-readable storage medium capable of implementing all steps in the three-dimensional seismic interval coherent slice processing method in the above embodiments, where the computer-readable storage medium stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements all steps of the three-dimensional seismic interval coherent slice processing method in the above embodiments, for example, the processor implements the following steps when executing the computer program:

step 100: and filtering the signal-to-noise ratio abnormal bands in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain the coherent slice with the band abnormal type only being fault abnormality.

Step 200: and sharpening the fault abnormal strip in the coherent slice to obtain a fault track line of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault track line.

As can be seen from the above description, the computer-readable storage medium provided in the embodiment of the present application can effectively improve the resolution of the three-dimensional seismic bedding coherent slice, effectively and quantitatively improve the reliability and processing efficiency of the processing process, and automatically and accurately obtain the distribution of the azimuth angles, so that the accuracy of fault identification can be effectively improved according to the coherent slice after the resolution is improved and the distribution histogram of the azimuth angles, and an accurate data basis can be provided for oil exploration according to the result of fault identification, so as to improve the accuracy of the oil exploration process.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

Although the present application provides method steps as described in an embodiment or flowchart, additional or fewer steps may be included based on routine or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.

The systems, apparatuses, modules or units described in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle human interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the embodiments described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.

The embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The described embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.

Claims

1. A three-dimensional seismic interval coherent slice processing method is characterized by comprising the following steps:

sharpening fault abnormal strips in the coherent slice to obtain a fault trajectory of the coherent slice, and determining a fault trend azimuth at a corresponding breakpoint according to the fault trajectory;

automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval, and generating a corresponding azimuth angle distribution histogram; wherein,

the method for filtering the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain the coherent slice with the abnormal band type only being fault abnormality comprises the following steps:

applying a comparison result between a preset threshold range and gradient values of all sampling points in the coherent slice, filtering an abnormal signal-to-noise ratio band in the coherent slice, and obtaining the coherent slice of which the abnormal type of the band is only fault abnormality;

2. The method as claimed in claim 1, further comprising, before the filtering the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic interval coherent slice of the target interval:

acquiring a three-dimensional seismic bedding coherent slice of a target layer;

gaussian filtering the coherent slice;

3. The method of claim 2, wherein the determining of the varying gradient value and the varying gradient azimuth of the gaussian filtered coherent slice comprises:

and (3) applying a first-order finite difference algorithm to obtain a change gradient value and a change gradient azimuth angle of the coherent slice after Gaussian filtering.

4. The three-dimensional seismic tomography slice processing method of claim 1, wherein the sharpening of fault anomaly bands in the coherent slice to obtain a fault trajectory of the coherent slice comprises:

5. The three-dimensional seismic slice processing method according to claim 1, wherein determining the fault strike azimuth at the corresponding fault point from the fault trajectory line comprises:

6. A three-dimensional seismic bedding coherent slice processing apparatus comprising:

the filtering module is used for filtering the signal-to-noise ratio abnormal band in the preprocessed three-dimensional seismic edge layer coherent slice of the target layer to obtain a coherent slice of which the band abnormal type is only fault abnormality;

the histogram generation module is used for automatically counting azimuth angles in all directions of the coherent slice based on the fault orientation angle and a preset orientation angle interval and generating a corresponding azimuth angle distribution histogram; wherein,

the filtering module includes:

the filtering unit is used for filtering the abnormal signal-to-noise ratio band in the coherent slice by applying a comparison result between a preset threshold range and the gradient value of each sampling point in the coherent slice to obtain the coherent slice of which the band abnormal type is only fault abnormal;

7. The three-dimensional seismic bedding coherent slice processing apparatus of claim 6, further comprising:

a filtering module for performing Gaussian filtering on the coherent slice;

8. The three-dimensional seismic interval coherent slice processing apparatus of claim 7, wherein the computation module comprises:

9. The three-dimensional seismic interval coherent slice processing device of claim 6, wherein the sharpening module comprises:

10. The three-dimensional seismic interval coherent slice processing apparatus of claim 6, wherein the sharpening module comprises:

and the fault strike azimuth acquisition unit is used for converting the gradient azimuth into a fault strike azimuth at the corresponding breakpoint.

11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the three-dimensional seismic in-horizon coherent slicing method of any of claims 1 to 5.

12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the three-dimensional seismic along-layer coherent slice processing method of any one of claims 1 to 5.