CN109614590B - Data mining method for researching influence of deposition environment on form of deepwater channel - Google Patents
Data mining method for researching influence of deposition environment on form of deepwater channel Download PDFInfo
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Abstract
The invention discloses a data mining method for researching influence of a deposition environment on the form of a deepwater water channel, which comprises the following steps of: A. characterizing the deposition environments of different water channel cases by using a characteristic matrix; B. calculating the influence of a single control factor on the water channel characterization parameters according to the statistical data; C. calculating the influence of the integral deposition environment on the water channel characterization parameters according to a cosine distance formula; D. calculating the form similarity of different water channels by using a lattice closeness formula; according to the method, different deposition environments are analyzed through mathematical methods such as data mining and the like, and the influence degrees of the different deposition environments on different characterization parameters are analyzed, so that the relationship between the deposition environments and the water channel forms is obtained. In the engineering field, the sedimentary environment is linked with the deep-sea oil reservoir distribution through the relationship between the reservoir and the water channel form and the relationship between the form obtained by the method and the environment, so that the reservoir property of the deep-water channel in an unexplored area can be evaluated and predicted through the information of the sedimentary environment.
Description
Technical Field
The invention relates to geological resources and geological engineering, in particular to a data mining method for researching the influence of a deposition environment on the form of a deep water channel.
Background
The deep water channel is an important channel for conveying sediments to a basin by a land frame, and is also an important place for storing oil and gas. The deposition environment in deep sea often determines the nature of the sediment in the waterway, thereby affecting the nature of the reservoirs in waterway systems in different regions. In addition to the effects on the reservoir, the sediment environment can have a tremendous effect on the channel morphology. Exploration means such as earthquakes and submarine cables provide researchers with a large amount of quantitative data about the form of deep water channels.
In recent years, a great deal of case study has utilized characterization parameters (such as width and depth) to characterize the geometry of a water course and control factors (such as land type and basin type) to describe different deepwater deposition environments. In addition, the traditional method for characterizing the influence of different control factors on the characterization parameters through a statistical chart and linear regression cannot clearly explain the quantitative relationship between the two. In the fields of geological resources and geological engineering, researchers often analyze the influence of a single control factor on the water channel characterization parameters by using the traditional method, but the method cannot reflect the influence of the overall deposition environment on the characterization parameters and cannot express the influence of the control factor on the overall shape of the water channel.
At present, no method for directly representing different control factors for different water channel characterization parameters exists, and no method for analyzing the integral form of the water channel by the integral deposition environment exists. The fuzzy quantitative relation between the control factors and the water channel characterization parameters hinders the research on the correlation between the deposition environment and the water channel form.
Disclosure of Invention
Aiming at the problems, the invention provides a data mining algorithm for researching the influence of the sedimentation environment on the form of the deep water channel, and aims to establish the quantitative relation between the characteristic parameters and the control factors by using the algorithm in the data mining and calibrate the quantitative relation between the integral sedimentation environment and the integral form characteristics of the water channel.
The invention adopts the following technical scheme:
a data mining method for researching influence of a deposition environment on a deepwater water channel form comprises the following steps:
A. and (3) characterizing the deposition environment of different water channel cases by using a characteristic matrix: according to the control factors of the deposition environment recorded by the water channel case, 0 is used for representing the control factor which does not appear in the case, and 1 is used for representing the control factor which appears, so that different water channel cases can be represented by a characteristic matrix consisting of 0 and 1;
B. and calculating the influence of a single control factor on the water channel characterization parameters according to the statistical data: calculating the average value of the characterization parameters of all the water channel cases, screening out cases of specific control factors from all the water channel cases, calculating the average value of the characterization parameters of the cases of the specific control factors, and then characterizing the influence of a single control factor on the characterization parameters through the difference of the two average values;
C. and calculating the influence of the integral deposition environment on the water channel characterization parameters according to a cosine distance formula: b, according to the influence values of all the control factors obtained in the step B on the characterization parameters, calculating the influence values of the integral deposition environment on the characterization parameters by using cosine distances;
D. and calculating the form similarity of different water channels by using a lattice closeness formula: calculating morphological similarity among different water channel cases according to descriptive statistical parameters corresponding to the characterization parameters in the water channel cases and by using the lattice similarity in fuzzy mathematics;
E. and (3) calculating the environmental similarity of different water channels by using a minimum hash algorithm: and B, calculating the similarity of the overall deposition environments of the different water channel cases by using the minimum hash according to the characteristic matrix for recording the control factors of the different cases in the step A.
Preferably, the sediment environment is used to predict the channel morphology in the unexplored area: and C, deducing the channel morphological characteristics of the unexplored area by using the combination of the control factors according to the numerical result obtained by calculation in the steps C-E.
The invention has the beneficial effects that:
the invention discloses a data mining method for researching the influence of deposition environment on the form of a water channel. In the engineering field, the sedimentary environment is linked with the deep-sea oil reservoir distribution through the relationship between the reservoir and the water channel form and the relationship between the form obtained by the method and the environment, so that the reservoir property of the deep-water channel in an unexplored area can be evaluated and predicted through the information of the sedimentary environment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly described below, and it is apparent that the drawings in the following description only relate to some embodiments of the present invention and are not limiting on the present invention.
FIG. 1 is a data plot of all maximum measured widths for a channel case of the present invention;
FIG. 2 is a schematic diagram of the descriptive statistics of the characterization parameters of a water channel case of the present invention;
FIG. 3 is a diagram illustrating the names and morphological definitions of channel profile characterization parameters according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
Unless otherwise defined, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this disclosure belongs. The use of the word "comprising" or "comprises", and the like, in this disclosure is intended to mean that the elements or items listed before that word, include the elements or items listed after that word, and their equivalents, without excluding other elements or items. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
The present invention will be further described with reference to the following examples.
The types of control factors used by the method to represent the overall deposition environment are shown in table 1, and the classification follows the classification proposed by Stow et al in 1996, and completely describes the concept of the deep water deposition environment in terms of sources, land frames, construction of sea basins, global sea level elevation and the like. The control factor information can be obtained from the work area background of different channel cases.
Table 1 list of control parameter information
A data mining method for researching influence of deposition environment on water channel form comprises the following steps:
A. and (3) characterizing the deposition environment of different water channel cases by using a characteristic matrix: as shown in table 2, the data table records control factors corresponding to a plurality of water channel case deposition environments, and the entries in the table correspond to case information. The control factor present in the case is represented as 1, and the absence represents 0, so that a feature vector consisting of 1 and 0 can be obtained. The feature vector represents the combination of control factors of different cases, and the feature matrix corresponding to table 2 is expressed as follows:
the data for each row in the matrix corresponds to a combination of different control factors in the case.
TABLE 2 statistical table of control factors of different cases
B. And obtaining the influence of a single control factor on the water channel characterization parameters according to the statistical data: as shown in FIG. 1, values for all maximum survey widths (273 data in the figure) for a channel case are shown, measured from seismic sections along the channel flow in a seismic region; the maximum measured width for the water channel case in fig. 1 is represented by the average W of the 273 profile parameters, which is expressed as follows:
as shown in Table 3, the width value of case one is 224, which is the average of the 273 width data in FIG. 1, and the average width values of a plurality of channels are included in Table 3.
TABLE 3 statistical table of water channel widths for different cases
| Case 1 | Case 2 | Case 3 | Case 4 | Case 5 | |
Case 7 | Case 8 | … | |
| Width W | 224 | 235 | 321 | 567 | 489 | 190 | 241 | 389 | … |
As shown in Table 3, a certain characterization parameter of each case is counted, and the width W is taken as an example, and the total number of the cases is m, so that the average value W of the widths of all cases is calculatedmeanIs represented as follows:
mean width W of all cases in Table 3meanIs 324 (part data not shown in the table, which lists the case width mean W of the partmean352.25).
Cases with a specific control factor (a control factor commonly owned in some cases) were selected, as shown in table 4.1: the width of all passive continent edge cases is 4 (n is 4 in formula 2), and the width F of each passive continent edge is calculatedn(i.e., each data in Table 4.1) with the width average Wmean(here 324)), the passive continental edge influence on channel width is expressed as RmThe following were used:
r calculated from the data in Table 4.1mIs 15. The width impact value corresponding to the passive continent edge in table 4.2 is calculated as 15. According to the formulas (1) and (2), the influence of other control factors on the width of the water channel can be calculated, and finally, the influence values of all the control factors on the width of the water channel shown in the table 4.2 can be obtained. In addition to the width, the calculations involved in this step also include the effect of control factors on other characterizing parameters, such as slope, depth, etc., and the width is used in this specification for illustration only.
TABLE 4.1 statistical Table of Width values for Passive continental edge cases
| Case code with passive continent edge | Case 3 | |
Case 9 | Case 10 |
| Width of | 334 | 339 | 340.1 | 342.1 |
TABLE 4.2 statistical table of influence of control factors on channel width
C. And calculating the influence of the integral deposition environment on the water channel characterization parameters according to a cosine distance formula: according to the characteristic matrix in the step A, all control factors in a certain case can be obtained, and the characteristic matrix value corresponding to the control factors is set as P; and then, according to the influence values of different control factors on the characterization parameters in the step B, setting the influence values as R, wherein the influence values are n control factors, and the influence value X of the integral deposition environment on the characterization parameters in a certain case can be obtained through cosine distance, and is expressed as follows:
by selecting different water channel cases, the influence of the deposition environment in each case on the water channel characterization parameters can be obtained.
D. And calculating the form similarity of different water channels by using a lattice closeness formula: calculating descriptive statistics of the characterizing parameters of different cases, as shown in fig. 2, which represents the frequency of occurrence of a certain characterizing parameter in a certain water channel case within different value ranges; as in the first pie chart of FIG. 2, the case has 273 values of the maximum measured width, the percentage of the values between 100 and 250m being about 96%. The types of characterizing parameters and the forms referred to in fig. 2 are defined as the parameters numbered (r) - (r) shown in fig. 3, and the cross-sectional area not shown in fig. 3 refers to the area of the U or V-shaped cross-section of the water course. As shown in table 5 (statistical table of water channel characterization parameters for different cases), statistics are statistically described for each water channel case, and the values of case 1 in the table correspond to the statistical data in the pie chart in fig. 2 (maximum measured width w1, maximum measured width w2, maximum measured width w3, minimum measured width w1, minimum measured width w2, minimum measured width w3, maximum measured depth D1, maximum measured depth D2, and maximum measured depth D3). Also included in table 5 are minimum depth of measurement D1, minimum depth of measurement D2, minimum depth of measurement D3, cross-sectional area a0, cross-sectional area a1, and the like.
TABLE 5 statistical table of water course characterization parameters for different cases
Let the characterizing parameter item of case 1 be A (x)o) The characterizing parameter term of case 2 is B (x)o) And o ranges from 1 to 9, the order of the characterization parameters in table 5. The outer product x in fuzzy mathematics is calculated, expressed as follows:
X＝max{min[A(x1),B(x1)],min[A(x2),B(x2)],min[A(x3),B(x3)],...,min[A(xn),B(xn)]} (4)
then, the inner product y is calculated, expressed as follows:
Y＝min{max[A(x1),B(x1)],max[A(x2),B(x2)],max[A(x3),B(x3)],...,max[A(xn),B(xn)]} (5)
and finally, calculating the lattice closeness L through the inner product x and the outer product y, wherein the expression is as follows:
the lattice similarity expresses the overall shape similarity of the two water channels, and the shape similarity of all the water channel cases can be obtained by the method.
E. And (3) calculating the environmental similarity of different water channels by using a minimum hash algorithm: and B, obtaining the combination of the control factors of the two cases according to the characteristic matrix obtained in the step A. Through a minimum hash algorithm, the number of control factors of the two cases is assumed to be J, namely, the matrix values in the two cases are both 1; if only one case has the control factor K, that is, one case has a matrix value of 1 and the other case has a matrix value of 0, the calculated deposition environment similarity E has the expression:
and (3) obtaining the deposition environment similarity among all the channel cases through a minimum hash algorithm.
Predicting the channel morphology of an unexplored area by using a deposition environment: and D, according to the overall shape similarity obtained in the step D and the sedimentation environment similarity obtained in the step E, whether similar sedimentation environment develops into a deep water channel with similar shape or not can be known. Through comparison of a plurality of cases, if a certain deposition environment (namely, a combination of similar control factors) is found to generate a similar water channel form, namely, the similarity of the overall form L and the similarity of the deposition environment E are both greater than 0.8 (the similarity is 80%, and the value is determined according to the accuracy required by specific engineering and can be 85%, 90% and the like), the deposition environment is judged to generate a specific water channel form; then, the influence degree X of the obtained deposition environment on the characterization parameters is calculated through the step C, and the deposition environment is specifically analyzed to generate similar morphological characteristics. If the deposition environment of the unknown area is similar to an environment that can generate a specific channel form, the form characteristics of the channel in the unknown area can be estimated according to the form of the known channel in the deposition environment, namely, the potential form characteristics of the channel in the unknown area are recommended to researchers through the similar deposition environment.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (2)
1. A data mining method for researching influence of a deposition environment on a deepwater water channel form is characterized by comprising the following steps:
A. and (3) characterizing the deposition environment of different water channel cases by using a characteristic matrix: according to the control factors of the deposition environment recorded by the water channel case, 0 is used for representing the control factor which does not appear in the case, and 1 is used for representing the control factor which appears, so that different water channel cases can be represented by a characteristic matrix consisting of 0 and 1;
B. and calculating the influence of a single control factor on the water channel characterization parameters according to the statistical data: calculating the average value of the characterization parameters of all the water channel cases, screening out cases of specific control factors from all the water channel cases, calculating the average value of the characterization parameters of the cases of the specific control factors, and then characterizing the influence of a single control factor on the characterization parameters through the difference of the two average values;
C. and calculating the influence of the integral deposition environment on the water channel characterization parameters according to a cosine distance formula: b, according to the influence values of all the control factors obtained in the step B on the characterization parameters, calculating the influence values of the integral deposition environment on the characterization parameters by using cosine distances;
D. and calculating the form similarity of different water channels by using a lattice closeness formula: calculating morphological similarity among different water channel cases according to descriptive statistical parameters corresponding to the characterization parameters in the water channel cases and by using the lattice similarity in fuzzy mathematics;
E. and (3) calculating the environmental similarity of different water channels by using a minimum hash algorithm: and B, calculating the similarity of the overall deposition environments of the different water channel cases by using the minimum hash according to the characteristic matrix for recording the control factors of the different cases in the step A.
2. The data mining method for researching the influence of the sedimentary environment on the deepwater channel morphology as claimed in claim 1, wherein the sedimentary environment is used for predicting the channel morphology of an unexplored area: and C, deducing the channel morphological characteristics of the unexplored area by using the combination of the control factors according to the numerical result obtained by calculation in the steps C-E.
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