CN110888162A - Method and system for enhancing continuity of same phase axis based on thermodynamic statistics - Google Patents
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Abstract
A method and a system for enhancing the continuity of a same phase axis based on thermodynamic statistics are disclosed. The method and system may include: arranging the data sampling points into a one-dimensional sequence, selecting the earthquake data sampling points, and setting an initial temperature; selecting seismic data sampling points to form a local correlation surface; selecting an alternative data set; selecting local correlation surface seismic data according to the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set; updating the temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface; carrying out weighted summation on the seismic data sample point values of the optimal local correlation surface and calculating an average value to replace central seismic data; and calculating the seismic data of all the data points of the one-dimensional sequence to obtain a final seismic data set. The method improves the signal-to-noise ratio of the seismic data and enhances the continuity of the seismic event by keeping the stratum structure form on the seismic image unchanged.
Description
Technical Field
The invention relates to the field of oil and gas geophysical exploration, in particular to a method and a system for enhancing the continuity of a same phase axis based on thermodynamic statistics.
Background
The underground geological structure can be found by explaining the propagation image of the seismic wave, the seismic wave meets the interface of the stratum (with wave impedance difference), the wave reflection occurs at the interface, the wave reflection on the ground is collected by the detector, the reflected wave is processed by a series of seismic data, the stacked seismic data is the basis for underground geological explanation, in the process, the reflected wave is often mixed with the unwanted interference such as the random interference generated by multiple waves, surface waves, wind blowing, grass movement and the like, and the interference is brought to the explanation of the seismic data, so the signal-to-noise ratio of the seismic data has great influence on the explanation precision.
The seismic data is a huge amount of manual interpretation which is a time-consuming process, and the automatic realization of some interpretation processes by computers enables interpreters to release energy to do more detailed interpretation, which is the trend of the development of seismic data interpretation technology. For example, earlier developed horizon automatic interpretation, global automatic interpretation of earthquake, automatic interpretation of fault and the like, the developed automatic interpretation technologies greatly relieve the labor intensity of the interpreter, and by taking sequence interpretation as an example, it is assumed that 600 lines of three-dimensional seismic data are provided, the seismic trace of each line is 400, the time sampling point number is 800, 2ms sampling is performed, more than 200 sequence of all large and small lines are provided, a skilled interpreter may need one month to interpret the horizons, psychological fatigue caused by long-time mechanical doing things can greatly affect the labor efficiency and interpretation precision of the interpreter, and the existing excellent layer automatic interpretation software can complete the work within tens of minutes. However, the promising efficiency is that the seismic event has higher continuity and signal-to-noise ratio, and similarly, most of the existing algorithms for seismic automation interpretation have higher requirements on signal-to-noise ratio, otherwise, the application effect of the automation algorithm is greatly discounted. The automatic interpretation algorithm of the seismic sequence usually requires that the event has good continuity, so that the continuity enhancement processing needs to be performed on the stacked seismic data, namely, the related data is enhanced to suppress random noise, the common method is to perform local five-point median filtering on the seismic image, and the five-point median filtering has the defects that: (1) the effect of suppressing random noise by means of local five seismic data sample values is sometimes not obvious, and the average value of the random noise is 0, so that a statistical result needs to be that as many sample points are related as possible. (2) The conventional five sample values are all located on the same horizontal line, which means that the local direction of the in-phase axis is horizontal but the actual direction on the in-phase axis is not, so that the result of the processing may cause the deformation of the in-phase axis to influence the interpretation result. In order to enhance the continuity of the in-phase axis, it is necessary to develop a method and a system for enhancing the continuity of the in-phase axis based on thermodynamic statistics.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention provides a method and a system for enhancing the continuity of a same phase axis based on thermodynamic statistics, which can improve the signal-to-noise ratio of seismic data and enhance the continuity of the seismic same phase axis under the condition of keeping the stratigraphic structure form on a seismic image unchanged.
According to an aspect of the present invention, a method for enhancing the continuity of the same phase axis based on thermodynamic statistics is presented. The method may include:
1) arranging data sampling points into a one-dimensional sequence according to line numbers, track numbers and time, taking the first data sampling point as a central seismic data sampling point, and setting an initial temperature;
2) selecting a group of n x n seismic data sampling points from the data sampling points along the direction of the track number and the line number by taking the central seismic data sampling points as the center to form a local correlation surface;
3) n based on local correlation surface2The seismic data sampling points are used for selecting N data sampling points upwards and downwards along the line number direction of the seismic data as an alternative data set;
4) selecting seismic data of the local correlation surface based on the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set;
5) updating the temperature, repeating the step 4) until the temperature is lower than the set threshold temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface;
6) carrying out weighted summation on the seismic data sample point values of the optimal local correlation surface and calculating an average value, wherein the obtained average value data replaces central seismic data;
7) selecting a next data sample point according to the sequence of the one-dimensional sequence in the step 1), and repeating the steps 2) to 6) to calculate the seismic data of all data points of the one-dimensional sequence to obtain a final seismic data set.
Preferably, in step 4), the local correlation surface seismic data is selected by:
2-1) calculating the initial temperature T of the seismic data sampling point on the initial local correlation surface0Variance of time;
2-2) randomly selecting a seismic data sampling point on the initial local correlation surface and seismic data sampling points in the alternative data set for exchange, and calculating the variance increment delta V of the seismic data sampling points of the local correlation surface before and after exchange;
2-3) exchanging the seismic data according to the sampling point variance increment delta V;
2-4) at an initial temperature T0And randomly exchanging M times to obtain seismic data of the local correlation surface.
Preferably, in step 2-3), when Δ V<0, reserving the exchanged local correlation surface data; when Δ V>0、e-ΔV>0.3, reserving the exchanged local correlation surface data; other cases preserve the local correlation plane data before swapping.
Preferably, in step 2-1), the variance is expressed by the following formula:
wherein, BiRepresenting the seismic data sample point value, and E (B) is the seismic data sample point mean value.
Preferably, if the seismic data samples are contaminated by random noise, the mean value of the seismic data samples after noise interference is represented by the following formula:
wherein n isiRepresenting the ith random noise.
Preferably, the random noise mean value is summed to 0.
Preferably, in step 6), the weighted sum is performed by the following formula:
wherein A represents a central seismic data point, y is a line number of the central seismic data point, x is a track number of the central seismic data point, t is a time number of the central seismic data point,
preferably, in step 5), the temperature is updated by using T × α, where α is the temperature coefficient and T is the temperature before updating.
Preferably, in step 3), N/2 seismic data samples are taken up and down, respectively.
According to another aspect of the invention, a thermodynamic statistics based system for inphase axis continuity enhancement is presented, having stored thereon a computer program, wherein the program when executed by a processor implements the steps of:
step 1: arranging data sampling points into a one-dimensional sequence according to line numbers, track numbers and time, taking the first data sampling point as a central seismic data sampling point, and setting an initial temperature;
step 2: selecting a group of n x n seismic data sampling points from the data sampling points along the direction of the track number and the line number by taking the central seismic data sampling points as the center to form a local correlation surface;
and step 3: n based on local correlation surface2The seismic data sampling points are used for selecting N data sampling points upwards and downwards along the line number direction of the seismic data as an alternative data set;
and 4, step 4: selecting seismic data of the local correlation surface based on the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set;
and 5: updating the temperature, repeating the step 4 until the temperature is lower than the set threshold temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface;
step 6: carrying out weighted summation on the seismic data sample point values of the optimal local correlation surface and calculating an average value, wherein the obtained average value data replaces central seismic data;
and 7: and (3) selecting a next data sampling point according to the sequence of the one-dimensional sequence in the step (1), and repeating the step (2) to the step (6) to calculate the seismic data of all the data points of the one-dimensional sequence to obtain a final seismic data set.
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.
FIG. 1 is a flow chart illustrating the steps of a method for thermodynamic statistics based in-phase axis continuity enhancement in accordance with the present invention;
FIG. 2 shows a schematic of raw seismic data;
FIG. 3 is a schematic diagram of seismic data processed by the thermodynamic statistics-based method for enhancing continuity of the event axes of the invention.
Detailed Description
The invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 shows a flow chart of the steps of a method for the enhancement of the continuity of the in-phase axis based on thermodynamic statistics according to the invention.
In this embodiment, the method for enhancing the continuity of the same phase axis based on thermodynamic statistics according to the present invention may include:
step 101, arranging data sampling points into a one-dimensional sequence according to line numbers, track numbers and time, taking a first data sampling point as a central seismic data sampling point, and setting an initial temperature;
in one example, the initial temperature is set to be 5000 thermodynamic temperature T, and those skilled in the art can set other temperature values according to actual requirements.
Step 102, taking the central seismic data sampling points as centers, and selecting a group of n × n seismic data sampling points from the data sampling points along the direction of a track number and a line number to form a local correlation surface;
in one example, with the central data as the center of a square, a group of 7 × 7 seismic data, that is, 49 seismic data samples, are selected from the original seismic data samples along the track number and line number directions to obtain an initial local correlation plane, in this embodiment, n ═ 7 is used as a default selected value, and those skilled in the art may set other n values according to actual requirements. And 0 is used for the seismic data which cannot be obtained.
Step 103, based on n of local correlation surface2The seismic data sampling points are used for selecting N data sampling points upwards and downwards along the line number direction of the seismic data as an alternative data set;
in one example, N/2 seismic data samples are taken up and down, respectively.
Specifically, in addition to the central seismic data point, 20 data samples are selected from the data samples on the initial local correlation surface upward and downward, and 48 × 40 × 1920 data samples are used as the candidate data set, where the N value is 20, and those skilled in the art may set other N values according to actual requirements.
104, selecting local correlation surface seismic data based on the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set;
in one example, local correlation surface seismic data is selected by:
2-1) calculating the variance of the seismic data sampling points on the initial local correlation surface at the initial temperature T;
the seismic data samples related locally form a related surface, the surface is a square surface element of 7X7 with a total of 49 data samples, and the 49 samples related to the central sample data A are respectively set as B1,...B49The sampling points are regarded as the mean value of the digital characteristics of random variables, and E (B) is the mean value of the seismic data sampling points. Specifically, the variance is expressed by the following formula:
wherein, BiRepresenting the seismic data sample point value, and E (B) is the seismic data sample point mean value.
Local seismic data correlation points have small numerical difference, namely numerical fluctuation, and the most relevant points are found if the minimum variance is found from the optimization point of view.
In an exemplary embodiment, where the seismic data samples are contaminated with random noise, the mean of the noise-disturbed seismic data samples is represented by the following formula:
wherein n isiRepresenting the ith random noise.
Thus, it can be approximated that the picking of locally relevant points is not disturbed by random noise.
2-2) randomly selecting a seismic data sampling point on the initial local correlation surface and seismic data sampling points in the alternative data set for exchange, and calculating the variance increment delta V of the seismic data sampling points of the local correlation surface before and after exchange;
2-3) exchanging the seismic data according to the sampling point variance increment delta V;
in an exemplary embodiment, when Δ V<0, reserving the exchanged local correlation surface data; when Δ V>0、e-ΔV>0.3, reserving the exchanged local correlation surface data; other cases preserve the local correlation plane data before swapping.
2-4) randomly exchanging M times at the initial temperature T to obtain the seismic data of the local correlation surface.
In one example, the variance and local correlation surface seismic data are obtained by randomly swapping 50 times at T5000.
Step 105, updating the temperature, repeating step 104 until the temperature is lower than a set threshold temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface;
the local correlation points are optimized by using the thermodynamic statistical thought, namely, the simulated annealing. In thermodynamic statistical physics, it is believed that the macroscopic effect of a particle is the average statistical result of the microscopic thermodynamic effects. The thermal effect of the particles is not the same at each temperature and tends to stabilize as the temperature is gradually reduced. The temperature is required to be gradually reduced to obtain a stable state, the high temperature is required to be as high as possible, and the temperature difference is as small as possible during temperature reduction.
In one example, the temperature is updated with T × α, where α is the temperature coefficient and T is the temperature before update.
Specifically, the value of the temperature coefficient α is 0.9, and the minimum value of the temperature threshold is set to be 0.01, but those skilled in the art can set other coefficient values according to actual requirements.
Step 106, carrying out weighted summation on the seismic data sample values of the optimal local correlation surface and calculating an average value, wherein the obtained average value data replaces central seismic data;
in an exemplary embodiment, the weighted sum is performed by the following formula:
wherein A represents a central seismic data point, y is a line number of the central seismic data point, x is a track number of the central seismic data point, t is a time number of the central seismic data point,
and 107, selecting the next data sample point according to the sequence of the one-dimensional sequence in the step 101, and repeating the steps 102-106 to calculate the seismic data of all the data points of the one-dimensional sequence to obtain a final seismic data set.
The method improves the signal-to-noise ratio of the seismic data and enhances the continuity of the seismic event by keeping the stratum structure form on the seismic image unchanged.
Application example
To facilitate understanding of the solution of the embodiments of the present invention and the effects thereof, a specific application example is given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.
As shown in fig. 2, the initial local correlation plane diagram selected in the embodiment of the present invention includes 49 seismic data samples, and the seismic data diagram shown in fig. 3 is obtained after the processing of the present invention, and it can be seen from the diagram that the processed data maintains the stratigraphic structure morphology, but increases the continuity of the seismic event and improves the signal-to-noise ratio of the seismic data.
In conclusion, the method improves the signal-to-noise ratio of the seismic data and enhances the continuity of the seismic event by keeping the stratum structure form on the seismic image unchanged. Compared with the conventional five-point mean method, the method has the advantage that the filtering of the invention hardly transforms the morphology of the seismic event.
It will be appreciated by persons skilled in the art that the above description of embodiments of the invention is intended only to illustrate the benefits of embodiments of the invention and is not intended to limit embodiments of the invention to any examples given.
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 method for enhancing the continuity of a same phase axis based on thermodynamic statistics is characterized by comprising the following steps:
1) arranging data sampling points into a one-dimensional sequence according to line numbers, track numbers and time, taking the first data sampling point as a central seismic data sampling point, and setting an initial temperature;
2) selecting a group of n x n seismic data sampling points from the data sampling points along the direction of the track number and the line number by taking the central seismic data sampling points as the center to form a local correlation surface;
3) n based on local correlation surface2The seismic data sampling points are used for selecting N data sampling points upwards and downwards along the line number direction of the seismic data as an alternative data set;
4) selecting seismic data of the local correlation surface based on the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set;
5) updating the temperature, repeating the step 4) until the temperature is lower than the set threshold temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface;
6) carrying out weighted summation on the seismic data sample point values of the optimal local correlation surface and calculating an average value, wherein the obtained average value data replaces central seismic data;
7) selecting a next data sample point according to the sequence of the one-dimensional sequence in the step 1), and repeating the steps 2) to 6) to calculate the seismic data of all data points of the one-dimensional sequence to obtain a final seismic data set.
2. The method for enhancing continuity of the same phase axis based on thermodynamic statistics as claimed in claim 1, wherein in step 4), the local correlation surface seismic data is selected by the following steps:
2-1) calculating the initial temperature T of the seismic data sampling point on the initial local correlation surface0Variance of time;
2-2) randomly selecting a seismic data sampling point on the initial local correlation surface and seismic data sampling points in the alternative data set for exchange, and calculating the variance increment delta V of the seismic data sampling points of the local correlation surface before and after exchange;
2-3) exchanging the seismic data according to the sampling point variance increment delta V;
2-4) at an initial temperature T0And randomly exchanging M times to obtain seismic data of the local correlation surface.
3. The method for enhancing the continuity of the same phase axis based on the thermodynamic statistics as claimed in claim 2, wherein in the step 2-3), when Δ V is applied<0, reserving the exchanged local correlation surface data; when Δ V>0、e-ΔV>0.3, reserving the exchanged local correlation surface data; other cases preserve the local correlation plane data before swapping.
4. The thermodynamic statistics-based method for enhancing continuity of the in-phase axis as claimed in claim 2, wherein in step 2-1), the variance is expressed by the following formula:
wherein, BiRepresenting the seismic data sample point value, and E (B) is the seismic data sample point mean value.
5. The method for enhancing continuity of the same phase axis based on thermodynamic statistics as claimed in claim 4, wherein if the seismic data samples are contaminated by random noise, the mean value of the seismic data samples after noise disturbance is represented by the following formula:
wherein n isiRepresenting the ith random noise.
6. The thermodynamic statistics based method for inphase axis continuity enhancement according to claim 5, wherein the random noise mean value is summed to 0.
7. The thermodynamic statistics based method for inphase axis continuity enhancement according to claim 1, wherein in step 6) the weighted summation is performed by the following formula:
8. the method for enhancing the continuity of the same phase axis based on the thermodynamic statistics as claimed in claim 1, wherein in step 5), the temperature is updated by T α, wherein α is the temperature coefficient and T is the temperature before updating.
9. The method for enhancing continuity of the same phase axis based on thermodynamic statistics as claimed in claim 1, wherein in step 3), N/2 seismic data samples are taken up and down, respectively.
10. A thermodynamic statistics based in-phase axis continuity enhancement system having a computer program stored thereon, wherein the program when executed by a processor implements the steps of:
step 1: arranging data sampling points into a one-dimensional sequence according to line numbers, track numbers and time, taking the first data sampling point as a central seismic data sampling point, and setting an initial temperature;
step 2: selecting a group of n x n seismic data sampling points from the data sampling points along the direction of the track number and the line number by taking the central seismic data sampling points as the center to form a local correlation surface;
and step 3: n based on local correlation surface2The seismic data sampling points are used for selecting N data sampling points upwards and downwards along the line number direction of the seismic data as an alternative data set;
and 4, step 4: selecting seismic data of the local correlation surface based on the variance value of the seismic data sample points on the local correlation surface and the data sample points in the alternative data set;
and 5: updating the temperature, repeating the step 4 until the temperature is lower than the set threshold temperature, and obtaining a final local correlation surface formed by the seismic data of the local correlation surface as an optimal local correlation surface;
step 6: carrying out weighted summation on the seismic data sample point values of the optimal local correlation surface and calculating an average value, wherein the obtained average value data replaces central seismic data;
and 7: and (3) selecting a next data sampling point according to the sequence of the one-dimensional sequence in the step (1), and repeating the step (2) to the step (6) to calculate the seismic data of all the data points of the one-dimensional sequence to obtain a final seismic data set.
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