CN113740908A - Two-dimensional variation analysis method for seismic slice, electronic device, and medium - Google Patents

Two-dimensional variation analysis method for seismic slice, electronic device, and medium Download PDF

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CN113740908A
CN113740908A CN202010475712.4A CN202010475712A CN113740908A CN 113740908 A CN113740908 A CN 113740908A CN 202010475712 A CN202010475712 A CN 202010475712A CN 113740908 A CN113740908 A CN 113740908A
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difference
data
seismic
line number
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CN113740908B (en
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张丰麒
盛秀杰
金之钧
彭成
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China Petroleum and Chemical Corp
Sinopec Exploration and Production Research Institute
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Sinopec Exploration and Production Research Institute
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
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Abstract

The invention discloses a two-dimensional variation analysis method of a seismic slice, electronic equipment and a medium, wherein the method comprises the following steps: respectively calculating the main survey line number difference and the tie line number difference between each point pair in the seismic section; using the point pairs with the same main measuring line number difference and the same tie line number difference as a group of data to obtain a plurality of groups of data; respectively calculating the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data, and respectively storing the square sum of the amplitude difference of each group of data and the number of the point pairs contained in each group of data in a first array and a second array; calculating a difference average value based on the first array and the second array; calculating a difference coefficient corresponding to each element of the first array; and obtaining a third array, and obtaining a variation analysis result based on the third array. The method takes the difference value of the sample point positions as a grouping standard, counts the change rules of the seismic data in different directions and scales, and has important significance for the parameter analysis of the crack development direction and scale in the geology statistics.

Description

Two-dimensional variation analysis method for seismic slice, electronic device, and medium
Technical Field
The invention belongs to the field of geostatistics, and particularly relates to a two-dimensional variation analysis method for seismic slices, electronic equipment and a medium.
Background
Geostatistical is a rapidly evolving branch of applied mathematics, which aims to describe the distribution of a certain property in space. It assumes the nature of spatial distribution, exhibiting some degree of continuity. Porosity and permeability are examples of spatially dependent properties that may be suitable for geostatistical description.
Geostatistical is a science that studies natural phenomena, both random and structural, or spatial correlation and dependence, with the help of variogram, based on regionalized variables. The spatial relationship of these variables is studied by assuming spatial correlation of neighboring data and assuming that the relationship expressing the degree of this correlation can be analyzed and counted using a function. The method is widely applied to quantitative description of natural variables in a space domain or a time domain, such as the fields of space variation and structural analysis, space prediction, space simulation and the like, can understand the attributes of non-systematic natural phenomena which change on a plurality of space scales, can estimate the probability that the predicted value of an unknown point exceeds a given threshold value, and combines expert knowledge to evaluate the uncertainty and risk of the predicted value so as to reduce the economic loss caused by estimation errors.
The geostatistics comprise phased geostatistics, geostatistics based on differential evolution and information entropy and the like, the influence of a variation function type on inversion result continuity is simulated and analyzed by phased geostatistics inversion method research and application thereof published in geophysical prospecting technology workshop of the Chinese Petroleum institute 2019, then the application conditions of different dimensionality phased conditions are contrastively analyzed, the corresponding relation between prior information and sand-to-ground ratio is established by a statistical analysis means, and a phased geostatistics inversion method for converting the prior information into sand-to-ground ratio constraint is provided. The geostatistical inversion technology is proposed to organically combine the horizontal continuous characteristics of seismic data and the longitudinal high resolution of logging data to obtain a high resolution well interpolation result under the constraint of the seismic data, and is one of the most important technical means for reservoir prediction at present, which is published in geostatistical random inversion method research based on differential evolution and information entropy in geophysical prospecting technical seminar of China Petroleum institute 2019. The formation parameter result is obtained through Markov Chain Monte Carlo (MCMC) random inversion of a Bayesian framework by using conventional geostatistical inversion, but the inversion result is easy to fall into a local optimal solution because the conventional MCMC method mostly uses a completely random sampling mode, or the difference of each inversion result is large, so that the inversion result is difficult to evaluate.
However, in describing the attributes of the spatial distribution of the seismic data, geostatistics usually only count the differences of the seismic data at different spatial positions, but in actual research and analysis, the change rules of the seismic data in two aspects, namely the direction and the scale, are sometimes more concerned, for example, the crack development direction, the crack scale, and the like are found. The existing geostatistical method does not pay attention to the two methods at the same time, namely the existing seismic statistics does not count the change rule of the seismic data in different directions and scales.
Therefore, a seismic statistical method is particularly needed to count the change rules of seismic data in different directions and scales.
Disclosure of Invention
The invention aims to provide a two-dimensional variation analysis method for seismic slices, which solves the problem that the change rule of seismic data in different directions and scales is not counted in the existing seismic statistics.
In view of this, the invention provides a two-dimensional variation analysis method for seismic slices, an electronic device and a medium, which at least solve the problem that the change rules of seismic data in different directions and scales are not counted in the existing seismic statistics.
In a first aspect, the present invention provides a method for analyzing two-dimensional variations of seismic slices, comprising: respectively calculating the main survey line number difference and the tie line number difference between each point pair in the seismic section; establishing a first array and a second array based on the seismic slice; taking the point pairs with the same main measuring line number difference and the same contact line number difference as a group of data to obtain a plurality of groups of data; respectively calculating the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data, and respectively storing the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data in the first array and the second array; calculating a difference average based on the first array and the second array; calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value and a preset threshold value; and obtaining a third array according to the difference coefficient corresponding to each element of the first array, and obtaining a variation analysis result based on the third array.
Optionally, the establishing a first array and a second array based on the seismic slices includes: determining a row dimension and a column dimension of a two-dimensional array corresponding to the seismic slice, recording the row dimension as m, and recording the column dimension as n; respectively establishing a first array and a second array, so that the row dimension of the first array and the row dimension of the second array are both 2m-1, the column dimension of the first array and the second array is n, the row dimension of the first array and the second array represents a main measuring line number difference value, and the column dimension represents a connecting line number difference value.
Optionally, the sum of squares of the amplitude differences for each set of data is calculated according to the following steps: calculating a square of the difference in amplitude for each point pair in the data; summing the squares of the differences in amplitude for each point pair as the sum of the squares of the differences in amplitude for the data.
Optionally, storing the sum of squares of the amplitude differences of each group of data and the number of point pairs included in each group of data in the first array and the second array respectively includes: determining a main measuring line number difference value and a connecting line number difference value corresponding to the data; storing the square sum of the amplitude differences of the data in the first array, and enabling the position of the square sum of the amplitude differences of the data in the first array to correspond to the main line number difference and the tie line number difference corresponding to the data; and storing the number of the point pairs contained in the data in the second array, so that the positions of the number of the point pairs contained in the data in the second array correspond to the main test line number difference and the contact line number difference corresponding to the data.
Optionally, the calculating the difference average value based on the first array and the second array includes: calculating the sum of all elements of the first array to obtain a difference sum; calculating the sum of all elements of the second array to obtain the sum of the number; dividing the sum of differences by the sum of numbers to obtain the average of differences.
Optionally, the calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value, and a preset threshold includes: for each element in the first array, acquiring a corresponding element with the same row number and column number as the element in the second array; comparing corresponding elements in the second array with a preset threshold, and when the corresponding elements in the second array are larger than the preset threshold, calculating the quotient of the elements in the first array and the corresponding elements in the second array; dividing the quotient by the difference average as a difference coefficient corresponding to the element in the first array.
Optionally, the row dimension of the third array is 2m-1, the column dimension is 2n-1, and obtaining the third array according to the difference coefficient corresponding to each element of the first array includes: for each element of the first array, storing a difference coefficient corresponding to the element in a position corresponding to the row number and the column number of the element in the third array; and completing the elements in the third array in a central symmetry mode.
Optionally, the obtaining a variation analysis result based on the third array includes: drawing an image based on the third array, wherein the abscissa of the image represents a row dimension, the ordinate represents a column dimension, and data are elements stored in the third array.
In a second aspect, the present invention also provides an electronic device, including: a memory storing executable instructions; a processor executing the executable instructions in the memory to implement the above-described method of two-dimensional variation analysis of seismic slices.
In a third aspect, the present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described method for two-dimensional variation analysis of seismic slices.
The invention has the beneficial effects that: the two-dimensional variation analysis method of the seismic section of the invention takes the point pairs with the same main survey line number difference and the same tie line number difference in the seismic section as the same group of data, calculates the square sum of the amplitude difference of the point pairs in each group of data, and the number of pairs of points included in each set of data, storing the sum of squares of the amplitude differences in the corresponding positions of the first data, respectively, storing the number of pairs of points included in the corresponding positions of the second data, calculating a difference coefficient corresponding to each element of the first array, respectively, based on the elements of the first array and the elements of the second array, storing the difference coefficient in the corresponding position of the third array, plotting a variation analysis result based on the third array, the difference value of the sample point positions is used as a grouping standard, the change rules of the seismic data in different directions and scales are counted, and the method has important significance for analyzing the parameters of the crack development direction and scale in the geostatistics.
The present invention has other features and advantages which will be apparent from or are set forth in detail in the accompanying drawings and the following detailed description, which are incorporated herein, and which together serve to explain certain principles of the invention.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
FIG. 1 shows a flow diagram of a method of two-dimensional variation analysis of seismic slices, according to one embodiment of the invention.
FIG. 2 illustrates a two-dimensional variation analysis method of seismic slices grouped by grid position difference values according to an embodiment of the invention.
FIG. 3 illustrates a schematic diagram of a centrosymmetric approach to a two-dimensional variation analysis method of seismic slices, according to one embodiment of the present invention.
FIG. 4 illustrates the variation analysis results of a two-dimensional variation analysis method of seismic slices according to one embodiment of the invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein.
The invention provides a two-dimensional variation analysis method of an earthquake slice, which comprises the following steps: respectively calculating the main survey line number difference and the tie line number difference between each point pair in the seismic section; establishing a first array and a second array based on the seismic slices; using the point pairs with the same main measuring line number difference and the same tie line number difference as a group of data to obtain a plurality of groups of data; respectively calculating the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data, and respectively storing the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data in a first array and a second array; calculating a difference average value based on the first array and the second array; calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value and a preset threshold value; and obtaining a third array according to the difference coefficient corresponding to each element of the first array, and obtaining a variation analysis result based on the third array.
When describing the attributes of the seismic data spatial distribution, it is common to only count the differences of the seismic data at different spatial positions, but sometimes more attention is paid to the change rules of the seismic data in both directions and dimensions, such as finding crack development directions, crack dimensions, and the like. Existing geostatistical methods do not focus on both. In some scenes, the spatial position difference rather than the spatial position is used as a grouping standard, and the seismic data with the same spatial difference are divided into the same group, so that the change rule of the required information can be counted.
Specifically, the amplitude difference between each point pair in the seismic slice is obtained, and then grouping is performed according to the phase difference of the grid positions between the two points, wherein the grouping according to the phase difference of the grid positions is as follows: if the inline number difference between two points is a and the crossline number difference is b, then all pairs with inline number difference a and crossline number difference b are counted as the same group. Then, the differences in the same group are accumulated and averaged, two-dimensional arrays, a first array Var _2D and a second array fold _2D are defined, the first array Var _2D is used for storing amplitude difference values (the square sum of the amplitude differences), the second array fold _2D is used for storing and counting the number of point pairs falling in the same group, and finally, the amplitude value difference statistical result grouped according to the grid position difference value is obtained according to the elements of the first array and the elements of the second array.
According to an exemplary embodiment, the two-dimensional variation analysis method for seismic slices takes pairs of points in the seismic slice having the same inline number difference and the same crossline number difference as the same group of data, calculates the sum of squares of amplitude differences for all the pairs of points in each group of data, and the number of pairs of points included in each set of data, storing the sum of squares of the amplitude differences in the corresponding positions of the first data, respectively, storing the number of pairs of points included in the corresponding positions of the second data, calculating a difference coefficient corresponding to each element of the first array, respectively, based on the elements of the first array and the elements of the second array, storing the difference coefficient in the corresponding position of the third array, plotting a variation analysis result based on the third array, the difference value of the sample point positions is used as a grouping standard, the change rules of the seismic data in different directions and scales are counted, and the method has important significance for analyzing the parameters of the crack development direction and scale in the geostatistics.
Alternatively, building the first array and the second array based on the seismic slices comprises: determining a row dimension and a column dimension of a two-dimensional array corresponding to the seismic slice, recording the row dimension as m, and recording the column dimension as n; respectively establishing a first array and a second array, so that the row dimension of the first array and the row dimension of the second array are both 2m-1, the column dimension of the first array and the second array is n, the row dimension of the first array and the second array represents a main measuring line number difference value, and the column dimension represents a connecting line number difference value.
Specifically, the input data of the two-dimensional variation analysis is a seismic slice, the data organization mode of the two-dimensional variation analysis is a two-dimensional array, two dimensions respectively correspond to the directions of a main measuring line and a connecting line of a seismic measuring network plane, and the values of elements in the array are seismic amplitude values, namely seismic response values of each grid point of the seismic measuring network at a certain depth. The seismic slice can be divided into an isochronous slice and a slab-along slice, wherein the isochronous slice represents that each element is a seismic amplitude value acquired from the same depth, and the slab-along slice represents that the depth of data acquired at each grid point is the depth corresponding to the position of the specified stratum at the grid point according to the trend of the specified stratum.
Determining a row dimension m and a column dimension n of a two-dimensional array corresponding to the seismic slice, wherein the range of the main measurement line number difference of the point pair is from- (m-1) to m-1, and the range of the tie line number difference is from 0 to n-1, so that a first array Var _2D and a second array fold _2D are established, the row dimension is 2m-1, the column dimension is n, the initial values of elements of the first array Var _2D and the second array fold _2D are 0, the first array Var _2D is used for storing amplitude difference values, and the second array fold _2D counts the number of the point pair falling in the same group.
Alternatively, the sum of the squares of the amplitude differences for each set of data is calculated according to the following steps: calculating the square of the difference in amplitude for each point pair in the data; the squares of the differences in amplitude for each point pair are summed as the sum of the squares of the differences in amplitude for the data.
Alternatively, storing the sum of squares of the amplitude differences of each set of data and the number of pairs of points included in each set of data in the first array and the second array, respectively, comprises: determining a main measuring line number difference value and a connecting line number difference value corresponding to the data; storing the square sum of the amplitude difference of the data in a first array, and enabling the position of the square sum of the amplitude difference of the data in the first array to correspond to the main measuring line number difference and the connecting line number difference corresponding to the data; and storing the number of the point pairs contained in the data in a second array, and enabling the positions of the number of the point pairs contained in the data in the second array to correspond to the main test line number difference and the contact line number difference corresponding to the data.
The method includes the steps of regarding the point pairs with the same inline number difference and the same tie line number difference as a set of data, calculating the square of the difference of the amplitude of each point pair included in the set of data, summing the squares of the differences of the amplitudes of each point pair as the sum of the squares of the differences of the amplitudes of the set of data, and storing the sum as the sum of the squares of the differences of the amplitudes of the set of data at the corresponding position of the first data.
When the data is stored in the corresponding position of the first data, two calculation and storage modes are provided, the first mode is to fill the calculated data in the corresponding position of the first array, specifically, all the point pairs with equal main survey line number difference and equal tie line number difference are extracted from the two arrays of the seismic slice to be used as a group of data, the accumulated sum of the squares of the differences of the amplitudes of the point pairs in the same group of data is calculated, the accumulated sum is used as the sum of the squares of the amplitude differences, the finally calculated sum of the squares of the amplitude differences is stored in the corresponding position of the first data, if the main survey line number difference of the point pairs is i, and the tie line number difference is j, the sum of the squares of the differences of the amplitudes of the group of data is filled in the corresponding position of the first array with the number of lines being i + m-1 and the number of columns being j.
And taking the point pairs with the same main measuring line number difference and the same connecting line number difference as a group of data, calculating the number of the point pairs contained in the group of data, and storing the number of the contained point pairs in the corresponding position of the second data.
When the data is stored in the corresponding position of the second data, two calculation and storage modes are available, the first mode is to fill the calculated data in the corresponding position of the second array, specifically, all the point pairs with equal main measurement line number difference and equal tie line number difference are extracted from the two arrays of the seismic slice to be used as a group of data, the number of the point pairs contained in the same group of data is calculated, finally, the number of all the calculated point pairs contained in the group is stored in the corresponding position of the second data, if the main measurement line number difference of the point pairs is i and the tie line number difference is j, the number of the point pairs contained in the group is filled in the corresponding position of the second array with the line number of i + m-1 and the column number of j.
A second method of storing the corresponding locations of the first data is to, for a point pair of the two-dimensional array slice corresponding to the seismic slice, add the element of the first array corresponding to the point pair to the square of the difference in amplitude of the point pair, traverse all the point pairs, and accumulate the square of the difference in amplitude of each point pair over the corresponding element of the first array. For example, for a point pair ij, the row number of the point i in the two-dimensional array corresponding to the seismic slice is i1, the column number is j1, the row number of the point j in the two-dimensional array corresponding to the seismic slice is i2, the column number is j2, the square of the difference of the amplitudes of the point pair is calculated first and is recorded as temp, then the difference of the main survey line numbers of the point pair ij is obtained as i2-i1, and the difference of the tie line numbers is j2-j1, and then the position of the point pair ij in the first array Var _2D is calculated. The first dimension of the first array Var _2D represents inline number differences ranging from- (m-1) to m-1, and the second dimension represents tie-line number differences ranging from 0 to n-1. And recording the corresponding elements of the ith point and the jth point in the two-dimensional array slice corresponding to the seismic slice as slice [ i1] [ j1], slice [ i2] [ j2], wherein the element of the point pair ij corresponding to the first array Var _2D [ i2-i1+ m-1] [ j2- _ j1], adding the square temp of the difference value of the amplitude of the point pair ij to the element of the first array Var _2D [ i2-i1+ m-1] [ j2- _ j1], traversing the next point pair by the same method, traversing all the point pairs of the seismic slice corresponding to the two-dimensional array slice, accumulating the square of the difference value of the amplitude corresponding to each point pair on the corresponding element of the first array, and traversing all the point pairs by the element of the square sum of the amplitude difference.
The traversal method of the point pair adopts double-layer circulation, the first layer circulation is to traverse all points in the two-dimensional array slice of the seismic slice, the current traversed point is recorded as the ith point, the second layer circulation is to traverse the points in the two-dimensional array slice of the seismic slice, i and the points behind i, the current traversed point is recorded as the jth point, and the current point pair ij is obtained. Since the results obtained when calculating the square of the amplitude difference are the same for point pair ij and point pair ji, the value of j in the second layer loop starts from i instead of 0, and only half of the point pairs need to be calculated, and the results of the other half of the point pairs are filled in the later step.
For all the points in the two-dimensional array slice of the traversal seismic slice, the sequence is carried out according to the rule of firstly traversing the main measuring line and then traversing the connecting line, and according to the traversal method, the difference value range of the main measuring line between the points ij is 2m-1 from- (m-1) to m-1; since the point pair traverses the point j all the time after the point i, the values of the tie line difference between the point pairs ij range from 0 to n-1. The first array Var _2D and the second array fold _2D above have a first dimension of 2m-1 and a second dimension of n.
When the dot pairs are traversed, the corresponding elements of the ith dot and the jth dot in the slice are respectively slice [ d _ inline1] [ d _ xline1], slice [ d _ inline2] [ d _ xline2], according to the rule of traversing all the dots in the slice, d _ inline1 ═ i% m, d _ xline1 ═ i/m, d _ inline2 ═ j% m, and d _ xline2 ═ j/m, wherein the percentage represents the remainder, and the slash represents the division and then the integer result is obtained. Note that slice [ d _ inline1] [ d _ xline1], slice [ d _ inline2] [ d _ xline2] are data1 and data2, respectively. The square of the difference between data1 and data2 is calculated and is denoted as temp.
The second method for storing the corresponding position of the second data is to add 1 to the element of the second array corresponding to a point pair of the two-dimensional array slice corresponding to the seismic slice, traverse all the point pairs, and accumulate the number of the point pairs on the element of the corresponding first array. For example, for a point ij, the row number of the point i in the two-dimensional array corresponding to the seismic slice is i1, the column number is j1, the row number of the point j in the two-dimensional array corresponding to the seismic slice is i2, the column number is j2, the difference of the inline numbers of the ij points is i2-i1, the difference of the inline numbers is j2-j1, and then the corresponding position of the point ij in the second array fold _2D is calculated. The first dimension of the second set of fold _2D represents inline number differences ranging from- (m-1) to m-1, and the second dimension represents tie line number differences ranging from 0 to n-1. And recording that the corresponding elements of the ith point and the jth point in the two-dimensional array slice corresponding to the seismic slice are respectively slice [ i1] [ j1], slice [ i2] [ j2], adding 1 to the element of the second group of fold _2D [ i2-i1+ m-1] [ j2- _ j1] corresponding to the ij, traversing the next point pair in the same way, traversing all the point pairs of the two-dimensional array slice corresponding to the seismic slice, and accumulating the number of the point pairs on the corresponding element of the second array.
The traversal method of the point pair adopts double-layer circulation, the first layer circulation is to traverse all points in the two-dimensional array slice of the seismic slice, the current traversed point is recorded as the ith point, the second layer circulation is to traverse the points in the two-dimensional array slice of the seismic slice, i and the points behind i, the current traversed point is recorded as the jth point, and the current point pair ij is obtained. Since the results obtained when calculating the square of the amplitude difference are the same for point pair ij and point pair ji, the value of j in the second layer loop starts from i instead of 0, and only half of the point pairs need to be calculated, and the results of the other half of the point pairs are filled in the later step.
For all the points in the two-dimensional array slice of the traversal seismic slice, the sequence is carried out according to the rule of firstly traversing the main measuring line and then traversing the connecting line, and according to the traversal method, the difference value range of the main measuring line between the points ij is 2m-1 from- (m-1) to m-1; since the point pair traverses the point j all the time after the point i, the values of the tie line difference between the point pairs ij range from 0 to n-1.
Alternatively, calculating the difference average based on the first array and the second array comprises: calculating the sum of all elements of the first array to obtain the difference sum; calculating the sum of all elements of the second array to obtain the sum of the number; the difference sum is divided by the number sum to obtain a difference average.
Specifically, after obtaining all elements of the first array Var _2D and all elements of the second array fold _2D, the sum of all elements of the first array Var _2D and the sum of all elements of the second array fold _2D are counted, and the sum of all elements of the first array Var _2D is divided by the sum of all elements of the second array fold _2D to obtain an average value of squares of all amplitude differences, i.e., an average value of differences, which is denoted as c0_ hor.
As an alternative, calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value and the preset threshold includes: for each element in the first array, acquiring a corresponding element with the same row number and the same column number as the element in the second array; comparing the corresponding elements in the second array with a preset threshold, and calculating the quotient of the elements in the first array and the corresponding elements in the second array when the corresponding elements in the second array are larger than the preset threshold; and dividing the quotient by the difference average value to be used as a difference coefficient corresponding to the element in the first array.
Specifically, the average value of the sum of squares of all amplitude differences is counted, a preset threshold is calculated according to a threshold proportion Ratio _ Crit input by a user, the preset threshold is (1-Ratio _ Crit) × m × n, and the water meter determines which part of data is displayed finally. Aiming at one element in the first array, acquiring a corresponding element with the same row number and the same column number as the elements in the first array from the second array, comparing the corresponding element in the second array with a preset threshold, displaying when the corresponding element in the second array is larger than the preset threshold, and calculating the quotient of the element in the first array and the corresponding element in the second array; and dividing the obtained quotient by the difference average value to be used as a difference coefficient corresponding to the element in the first array. And traversing all the points in the first array to obtain the difference coefficient corresponding to each element.
Alternatively, the third array has a row dimension of 2m-1 and a column dimension of 2n-1, and obtaining the third array from the difference coefficient corresponding to each element of the first array comprises: for each element of the first array, storing a difference coefficient corresponding to the element in a position corresponding to the row number and the column number of the element in the third array; and completing the elements in the third array in a central symmetry mode.
Specifically, the first array Var _2D represents the sum of squares of differences in amplitude values of half of the point pairs, and in order to display the final result, it is necessary to form the variation analysis results of all the point pairs, and a third array Var _2D _ show is defined for storing the final variation analysis results, where the row dimension is 2 × m-1 and the column dimension is 2 × n-1. For a point in the first array Var _2D, the current element is noted as Var _2D [ i ] [ j ], if the second array element fold _2D [ i ] [ j ] corresponding to the element of the first array is greater than a preset threshold, the third array Var _2D _ show [ i ] [ j + n-1] is assigned as Var _2D [ i ] [ j ]/fold _2D [ i ] [ j ]/c0_ hor, c0_ hor is the difference average, the preset threshold is (1-Ratio _ Crit) m × n, Ratio _ Crit is the display threshold proportion input by the user, and the element value of the third array Var _2D _ show [ i ] [ j ] + n-1] represents the average of the squares of the differences of the amplitudes within one packet divided by the average of the squares of all differences.
Traversing all the points in the first array Var _2D, filling the difference coefficient corresponding to each element in the position corresponding to the third array Var _2D _ show, because only half of the point pairs are calculated before, only half of the data in the third array Var _2D _ show is calculated, and the other half of the data in the third array is filled in a central symmetry manner.
Alternatively, obtaining the variation analysis result based on the third array comprises: and drawing the image based on the third array, wherein the abscissa of the image represents a row dimension, the ordinate represents a column dimension, and the data are elements stored in the third array.
Specifically, the third array is drawn into an image, the value ranges of the x coordinate axis and the y coordinate axis of the two-dimensional array are respectively- (m-1) to m-1 and- (n-1) to n-1 when the two-dimensional array is finally displayed, the two dimensions of the third array are respectively corresponded, and the data is elements stored in the third array.
The present invention also provides an electronic device, comprising: a memory storing executable instructions; and the processor runs the executable instructions in the memory to realize the two-dimensional variation analysis method of the seismic slice.
The present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described method of two-dimensional variation analysis of seismic slices.
Example one
FIG. 1 shows a flow diagram of a method of two-dimensional variation analysis of seismic slices, according to one embodiment of the invention. FIG. 2 illustrates a two-dimensional variation analysis method of seismic slices grouped by grid position difference values according to an embodiment of the invention. FIG. 3 illustrates a schematic diagram of a centrosymmetric approach to a two-dimensional variation analysis method of seismic slices, according to one embodiment of the present invention. FIG. 4 illustrates the variation analysis results of a two-dimensional variation analysis method of seismic slices according to one embodiment of the invention.
Referring to fig. 1, 2, 3 and 4, the method for analyzing two-dimensional variation of a seismic slice includes:
step 1: respectively calculating the main survey line number difference and the tie line number difference between each point pair in the seismic section;
step 2: establishing a first array and a second array based on the seismic slices;
wherein, based on the seismic slice, establishing the first array and the second array comprises: determining a row dimension and a column dimension of a two-dimensional array corresponding to the seismic slice, recording the row dimension as m, and recording the column dimension as n; respectively establishing a first array and a second array, so that the row dimension of the first array and the row dimension of the second array are both 2m-1, the column dimension of the first array and the second array is n, the row dimension of the first array and the second array represents a main measuring line number difference value, and the column dimension represents a connecting line number difference value.
Specifically, a row dimension m and a column dimension n of a two-dimensional array corresponding to the seismic slice are determined, a main measurement line number difference value of a point pair ranges from- (m-1) to m-1, a tie line number difference value ranges from 0 to n-1, therefore, a first array Var _2D and a second array fold _2D are established, the row dimension is 2m-1, the column dimension is n, initial values of elements of the first array Var _2D and the second array fold _2D are 0, the first array Var _2D is used for storing amplitude difference values, and the second array fold _2D counts the number of the point pairs falling in the same group.
And step 3: using the point pairs with the same main measuring line number difference and the same tie line number difference as a group of data to obtain a plurality of groups of data;
as shown in fig. 2, the difference between the geodesic line numbers of the point pairs consisting of the point (m, n) and the point (m + a, n + b) in the seismic slice is a, the difference between the crossline numbers is b, the difference between the geodesic line numbers of the point pairs consisting of the point (p, q) and the point (p + a, q + b) is a, and the difference between the crossline numbers is b, and the calculation results of the two point pairs are grouped into the same group. The difference value of the grid positions of two points in each point pair can be regarded as a vector, under the grouping rule, all the point pairs contained in each group have the same vector, namely the length and the direction are the same, and the result counted according to the grouping can reflect the nature of the seismic slice in the aspect of anisotropy.
And 4, step 4: respectively calculating the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data, and respectively storing the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data in a first array and a second array;
wherein the sum of the squares of the amplitude differences for each set of data is calculated according to the following steps: calculating the square of the difference in amplitude for each point pair in the data; the squares of the differences in amplitude for each point pair are summed as the sum of the squares of the differences in amplitude for the data.
Wherein storing the sum of squares of the amplitude differences of each set of data and the number of point pairs included in each set of data in the first array and the second array, respectively, comprises: determining a main measuring line number difference value and a connecting line number difference value corresponding to the data; storing the square sum of the amplitude difference of the data in a first array, and enabling the position of the square sum of the amplitude difference of the data in the first array to correspond to the main measuring line number difference and the connecting line number difference corresponding to the data; and storing the number of the point pairs contained in the data in a second array, and enabling the positions of the number of the point pairs contained in the data in the second array to correspond to the main test line number difference and the contact line number difference corresponding to the data.
And 5: calculating a difference average value based on the first array and the second array;
wherein calculating the difference average based on the first array and the second array comprises: calculating the sum of all elements of the first array to obtain the difference sum; calculating the sum of all elements of the second array to obtain the sum of the number; the difference sum is divided by the number sum to obtain a difference average.
Step 6: calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value and a preset threshold value;
wherein, based on the first array, the second array, the difference average value and the preset threshold, calculating a difference coefficient corresponding to each element of the first array comprises: for each element in the first array, acquiring a corresponding element with the same row number and the same column number as the element in the second array; comparing the corresponding elements in the second array with a preset threshold, and calculating the quotient of the elements in the first array and the corresponding elements in the second array when the corresponding elements in the second array are larger than the preset threshold; and dividing the quotient by the difference average value to be used as a difference coefficient corresponding to the element in the first array.
And 7: and obtaining a third array according to the difference coefficient corresponding to each element of the first array, and obtaining a variation analysis result based on the third array.
Wherein the row dimension of the third array is 2m-1, the column dimension is 2n-1, and obtaining the third array according to the difference coefficient corresponding to each element of the first array comprises: for each element of the first array, storing a difference coefficient corresponding to the element in a position corresponding to the row number and the column number of the element in the third array; and completing the elements in the third array in a central symmetry mode.
Specifically, the first array Var _2D represents the sum of squares of differences in amplitude values of half of the point pairs, and in order to display the final result, it is necessary to form the variation analysis results of all the point pairs, and a third array Var _2D _ show is defined for storing the final variation analysis results, where the row dimension is 2 × m-1 and the column dimension is 2 × n-1. For a point in the first array Var _2D, the current element is noted as Var _2D [ i ] [ j ], if the second array element fold _2D [ i ] [ j ] corresponding to the element of the first array is greater than a preset threshold, the third array Var _2D _ show [ i ] [ j + n-1] is assigned as Var _2D [ i ] [ j ]/fold _2D [ i ] [ j ]/c0_ hor, c0_ hor is the difference average, the preset threshold is (1-Ratio _ Crit) m × n, Ratio _ Crit is the display threshold proportion input by the user, and the element value of the third array Var _2D _ show [ i ] [ j ] + n-1] represents the average of the squares of the differences of the amplitudes within one packet divided by the average of the squares of all differences.
Traversing all the points in the first array Var _2D, filling the difference coefficient corresponding to each element in the position corresponding to the third array Var _2D _ show, because only half of the point pairs are calculated before, only half of the data in the third array Var _2D _ show is calculated, and the other half of the data in the third array is filled in a central symmetry manner. As shown in fig. 3, the gray portion is the corresponding position of the already traversed point pair in Var _2D _ show, i.e. all point pairs that satisfy the second point order after the first point, as shown in fig. 3. For a point pair, assuming that the group in which the point pair is located is Var _2D _ show [ i ] [ j ], the row dimension of the two-dimensional array corresponding to the seismic slice is N _ inline, and the column dimension is N _ xline, the group in which the point pair after the point pair is sequentially exchanged for two points is Var _2D _ show [ 2N _ inline-i-2] [ 2N _ xline-j-2], the symmetrical value of all the point pairs is complemented, i.e. i is from 0 to N _ line-1, and the order is that
Var_2D_show[i][N_xline-1]＝Var_2D_show[2*N_inline-i-2][N_xline-1]；
Let i go from 0 to 2 x N _ inline-1, j go from 0 to N _ xline-1,
the third array Var _2D _ show can be obtained by Var _2D _ show [ i ] [ j ] ═ Var _2D _ show [2 × N _ inline-i-2] [2 × N _ xline-j-2 ].
Wherein, based on the third array, obtaining a variation analysis result comprises: and drawing the image based on the third array, wherein the abscissa of the image represents a row dimension, the ordinate represents a column dimension, and the data are elements stored in the third array.
Specifically, the third array is drawn into an image, the value ranges of the x and y coordinate axes of the two-dimensional array are respectively- (m-1) to m-1 and- (n-1) to n-1 when the two-dimensional array is finally displayed, the two dimensions of the third array are respectively corresponded, the data is the elements stored in the third array, and the drawing result is shown in fig. 4. The image shows that the main line number difference is 70, and the value of the position with the tie line number difference of 100 is larger, which indicates that the amplitude of the seismic slice in the direction and the scale is larger, and cracks are possible. This image is a centrosymmetric image because the point pair ij and the point pair ji have the same calculation result and are written into the centrosymmetric two element positions in the third array, respectively.
Example two
The present disclosure provides an electronic device including: a memory storing executable instructions; and the processor runs the executable instructions in the memory to realize the two-dimensional variation analysis method of the seismic slice.
An electronic device according to an embodiment of the present disclosure includes a memory and a processor.
The memory is to store non-transitory computer readable instructions. In particular, the memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the disclosure, the processor is configured to execute the computer readable instructions stored in the memory.
Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus, an interface, and the like, and these well-known structures should also be included in the protection scope of the present disclosure.
For the detailed description of the present embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, which are not repeated herein.
EXAMPLE III
The present disclosure provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described two-dimensional variation analysis method of a seismic slice.
A computer-readable storage medium according to an embodiment of the present disclosure has non-transitory computer-readable instructions stored thereon. The non-transitory computer readable instructions, when executed by a processor, perform all or a portion of the steps of the methods of the embodiments of the disclosure previously described.
The computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or removable disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROMs (e.g., ROM cartridges).
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims (10)

1. A two-dimensional variation analysis method of seismic slices is characterized by comprising the following steps:
respectively calculating the main survey line number difference and the tie line number difference between each point pair in the seismic section;
establishing a first array and a second array based on the seismic slice;
taking the point pairs with the same main measuring line number difference and the same contact line number difference as a group of data to obtain a plurality of groups of data;
respectively calculating the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data, and respectively storing the square sum of the amplitude difference of each group of data and the number of point pairs contained in each group of data in the first array and the second array;
calculating a difference average based on the first array and the second array;
calculating a difference coefficient corresponding to each element of the first array based on the first array, the second array, the difference average value and a preset threshold value;
and obtaining a third array according to the difference coefficient corresponding to each element of the first array, and obtaining a variation analysis result based on the third array.
2. The method of two-dimensional variation analysis of a seismic slice of claim 1, wherein the establishing a first array and a second array based on the seismic slice comprises:
determining a row dimension and a column dimension of a two-dimensional array corresponding to the seismic slice, recording the row dimension as m, and recording the column dimension as n;
respectively establishing a first array and a second array, so that the row dimension of the first array and the row dimension of the second array are both 2m-1, the column dimension of the first array and the second array is n, the row dimension of the first array and the second array represents a main measuring line number difference value, and the column dimension represents a connecting line number difference value.
3. A method for two-dimensional variation analysis of seismic slices as claimed in claim 2, wherein the sum of the squares of the amplitude differences for each set of data is calculated according to the following steps:
calculating a square of the difference in amplitude for each point pair in the data;
summing the squares of the differences in amplitude for each point pair as the sum of the squares of the differences in amplitude for the data.
4. A method for two-dimensional variation analysis of a seismic slice according to claim 3, wherein storing the sum of squares of the amplitude differences of each set of data and the number of point pairs included in each set of data in the first array and the second array, respectively, comprises:
determining a main measuring line number difference value and a connecting line number difference value corresponding to the data;
storing the square sum of the amplitude differences of the data in the first array, and enabling the position of the square sum of the amplitude differences of the data in the first array to correspond to the main line number difference and the tie line number difference corresponding to the data;
and storing the number of the point pairs contained in the data in the second array, so that the positions of the number of the point pairs contained in the data in the second array correspond to the main test line number difference and the contact line number difference corresponding to the data.
5. The method of two-dimensional variation analysis of a seismic slice of claim 4, wherein calculating a difference average based on the first array and the second array comprises:
calculating the sum of all elements of the first array to obtain a difference sum;
calculating the sum of all elements of the second array to obtain the sum of the number;
dividing the sum of differences by the sum of numbers to obtain the average of differences.
6. The method of two-dimensional variation analysis of a seismic slice of claim 5, wherein the calculating a difference coefficient for each element of the first array based on the first array, the second array, the difference average, and a preset threshold comprises:
for each element in the first array, acquiring a corresponding element with the same row number and column number as the element in the second array;
comparing corresponding elements in the second array with a preset threshold, and when the corresponding elements in the second array are larger than the preset threshold, calculating the quotient of the elements in the first array and the corresponding elements in the second array;
dividing the quotient by the difference average as a difference coefficient corresponding to the element in the first array.
7. A method for two-dimensional variation analysis of a seismic slice according to claim 6, wherein the third array has a row dimension of 2m-1 and a column dimension of 2n-1, and wherein the obtaining of the third array from the difference coefficients corresponding to each element of the first array comprises:
for each element of the first array, storing a difference coefficient corresponding to the element in a position corresponding to the row number and the column number of the element in the third array;
and completing the elements in the third array in a central symmetry mode.
8. The method of two-dimensional variation analysis of a seismic slice of claim 7, wherein obtaining variation analysis results based on the third array comprises:
drawing an image based on the third array, wherein the abscissa of the image represents a row dimension, the ordinate represents a column dimension, and data are elements stored in the third array.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing executable instructions;
a processor executing the executable instructions in the memory to implement a method of two-dimensional variation analysis of a seismic slice according to any of claims 1-8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements a method of two-dimensional variation analysis of a seismic slice according to any of claims 1-8.
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