CN107678068A - A kind of imaging method and device based on gravimetric data downward continuation - Google Patents
A kind of imaging method and device based on gravimetric data downward continuation Download PDFInfo
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- CN107678068A CN107678068A CN201610621086.9A CN201610621086A CN107678068A CN 107678068 A CN107678068 A CN 107678068A CN 201610621086 A CN201610621086 A CN 201610621086A CN 107678068 A CN107678068 A CN 107678068A
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Abstract
The application provides a kind of imaging method and device based on gravimetric data downward continuation, wherein, methods described includes：Obtain the discrete groups of data Jing Guo discrete Fourier transform；First object equation and the second target equation are established according to the discrete groups of data；Determine the downward parameter in the first object equation and determine the frequency parameter in the second target equation；Determine that the discrete groups of data passes through the continuation discrete groups of data of downward continuation, and discrete Fourier transform is carried out to the continuation discrete groups of data, obtain the gravimetric data group by downward continuation；Based on the gravimetric data group for passing through downward continuation corresponding to Different Strata depth, the downward continuation imaging results on stratum are obtained.A kind of imaging method and device based on gravimetric data downward continuation that the application embodiment provides, can be while the available information in retaining gravimetric data, weaken the higher-order of oscillation effect during downward continuation, so as to obtain accurate formation imaging result.
Description
Technical Field
The application relates to the technical field of geological imaging, in particular to an imaging method and device for downward continuation based on gravity data.
Background
In the technical field of geological imaging, downward continuation is continuation from an actually measured potential field to a field source. Since the nature and the depth of burial of the field source are unknown, the downward continuation has substantial difficulties, which in practical applications are reflected in two aspects: firstly, from the mathematical theory, if the boundary value has a slight change, the obtained solution is unstable; secondly, the field measured data always has certain errors, and meanwhile, certain errors are inevitably caused when the measured data are processed, and the errors are expressed into a large amount due to a high-frequency oscillation effect in downward continuation, so that the real solution is covered.
The downward continuation processing in the frequency domain has the characteristics of convenience in implementation, short calculation time, high speed and the like, and as for the research on the downward continuation method of the frequency domain, as early as 1958, W.C. dean provides a frequency response formula of the downward continuation of the bit field and indicates that the formula is the most difficult operation in approximate calculation. This is because the response is only suitable for the case where the observed value is an accurate value, and the observed error or high frequency interference is amplified significantly, which results in severe oscillation and even drowns out useful information. Later, researchers have proposed a series of methods for performing the down-delay by using an additional filter to suppress the high-frequency interference, and certain effects are achieved:
ku.c.c. proposes a series low pass filter; the Meyer.F.D. proposes the optimal filter response of series connection; the method is characterized in that a compensation ring sliding filter for suppressing the quotient frequency interference is proposed at the beginning of Hou's reputations, and the concept of compensation is combined with successive downward continuation to realize the down-extending of a frequency domain bit field; the maotai analyzes an oscillation mechanism of the frequency domain potential field descent and provides a descent method of an extension matching filter;
a ti-i \ 1093o proposes a frequency response of a regularization method for downward continuation; goldenrain, liangjinwen and the like are researched on the basis; wanyan, bear's light, proposes to solve the down-bound problem using a special combination filter, which contains both a spatial domain of a potential-varying filter and a frequency domain of a linear duplexer, which gives a new way to solve the down-bound problem.
However, these methods in the prior art have a unified drawback: when the bit field data extend to the area near the depth of the top surface of the field source, the problems that the strong oscillation effect of the bit field data cannot continue to extend downwards, the characteristics of the depth and the like of the field source are difficult to determine by using the spatial bit field characteristics, the observation abnormity is excessively suppressed, or the high-frequency suppression is insufficient are solved.
Disclosure of Invention
The embodiment of the application aims to provide an imaging method and device based on downward continuation of gravity data, which can weaken a high-frequency oscillation effect in a downward continuation process while keeping available information in the gravity data, so that an accurate formation imaging result can be obtained.
To achieve the above object, an embodiment of the present application provides an imaging method for downward continuation based on gravity data, the method including: extracting a first discrete data set of a preset measuring line position from the gravity data, wherein the first discrete data set comprises a preset number of gravity abnormal values; performing discrete Fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, wherein the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one by one; establishing a first target equation based on the second discrete data set, wherein the first target equation further comprises a first downward extension parameter and a second downward extension parameter to be determined; determining a parameter value of the first downward extending parameter and a parameter value of the second downward extending parameter based on a golden section algorithm; establishing a second target equation according to the second discrete data set and the first downward extension parameter and the second downward extension parameter of which the parameter values are determined, wherein the second target equation also comprises a first frequency parameter and a second frequency parameter to be determined; determining a parameter value of a first frequency parameter and a parameter value of a second frequency parameter corresponding to the minimum value obtained by the second target equation; determining a continuation discrete data set subjected to downward continuation by the second discrete data set according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter with the determined parameter values, and the first frequency parameter and the second frequency parameter with the determined parameter values, and performing discrete Fourier transform on the continuation discrete data set to obtain a gravity data set subjected to downward continuation; and acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
To achieve the above object, an embodiment of the present application further provides an imaging apparatus extending downward based on gravity data, the apparatus including: the first discrete data set acquisition unit is used for extracting a first discrete data set of a preset measuring line position from the gravity data, and the first discrete data set comprises a preset number of gravity abnormal values; a second discrete data set acquisition unit, configured to perform discrete fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, where the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one to one; the first target equation establishing unit is used for establishing a first target equation based on the second discrete data set, and the first target equation further comprises a first downward extension parameter and a second downward extension parameter to be determined; a downward extension parameter determining unit, configured to determine a parameter value of the first downward extension parameter and a parameter value of the second downward extension parameter based on a golden section algorithm; a second target equation establishing unit, configured to establish a second target equation according to the second discrete data set and the first downward-extending parameter and the second downward-extending parameter for which the parameter value is determined, where the second target equation further includes a first frequency parameter and a second frequency parameter to be determined; the frequency parameter determining unit is used for determining a parameter value of the first frequency parameter and a parameter value of the second frequency parameter corresponding to the minimum value obtained by the second objective equation; a continuation discrete data set determining unit, configured to determine, according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter for which the parameter value is determined, and the first frequency parameter and the second frequency parameter for which the parameter value is determined, a continuation discrete data set in which the second discrete data set is subjected to downward continuation, and perform discrete fourier transform on the continuation discrete data set to obtain a downward continuation gravity data set; and the imaging unit is used for acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
According to the embodiment of the application, the parameter values of the first downward extension parameter, the second downward extension parameter, the first frequency parameter and the second frequency parameter are determined through the first target equation and the second target equation respectively. When the first downward extending parameter and the second downward extending parameter are determined, the golden section algorithm is adopted, and therefore the efficiency of parameter value determination is improved. After the parameter values of the first downward-extending parameter, the second downward-extending parameter, the first frequency parameter and the second frequency parameter are determined, a continuation discrete data set of the second discrete data set subjected to downward continuation can be determined. Therefore, according to the downwardly extended gravity data set corresponding to different stratum depths, a downwardly extended imaging result of the stratum can be obtained. According to the imaging method and device for downward continuation based on the gravity data, the available information in the gravity data can be kept, and meanwhile the high-frequency oscillation effect in the downward continuation process can be weakened, so that an accurate stratum imaging result can be obtained.
Specific embodiments of the present application are disclosed in detail with reference to the following description and drawings, indicating the manner in which the principles of the application may be employed. It should be understood that the embodiments of the present application are not so limited in scope. The embodiments of the application include many variations, modifications and equivalents within the spirit and scope of the appended claims.
Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments, in combination with or instead of the features of the other embodiments.
It should be emphasized that the term "comprises/comprising" when used herein, is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps or components.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the application, are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. It should be apparent that the drawings in the following description are merely some embodiments of the present application and that other drawings may be derived by those skilled in the art without inventive faculty. In the drawings:
fig. 1 is a flowchart of an imaging method for downward continuation based on gravity data according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a golden segmentation algorithm in an embodiment of the present application;
fig. 3 is a functional block diagram of an image forming apparatus extending downward based on gravity data according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making creative efforts shall fall within the protection scope of the present application.
Fig. 1 is a flowchart of an imaging method for downward continuation based on gravity data according to an embodiment of the present disclosure. Although the flow described below includes operations that occur in a particular order, it should be appreciated that the processes may include more or less operations that are performed sequentially or in parallel (e.g., using parallel processors or a multi-threaded environment). As shown in fig. 1, the method includes:
step S1: and extracting a first discrete data set of preset measuring line positions from the gravity data, wherein the first discrete data set comprises a preset number of gravity abnormal values.
In this embodiment, the gravity data may be presented in the form of a gravity data plan. Several gravity outliers may be distributed on the gravity data plane. In this embodiment, data of a preset line position may be extracted from the gravity data plane. The extracted data may be provided as an original discrete data set. A plurality of raw gravity outliers may be included in the raw discrete data set. The original gravity outliers can be the annotated gravity outliers on the gravity data plane graph.
In this embodiment, after the original discrete data set is extracted, interpolation calculation may be performed on the original gravity abnormal values in the original discrete data set, so that a series of gravity abnormal values of the equal stride distribution may be generated. The series of gravity outliers of the equal-step distribution can be the first discrete data set, and the step size between any two adjacent gravity outliers in the first discrete data set is the same. After the interpolation calculation, the first discrete data set may include a preset number of gravity outliers, and then the gravity outliers in the first discrete data set may be processed.
In this embodiment, each gravity anomaly value in the first discrete data set may be represented by the following formula:
wherein the content of the first and second substances,representing the ith gravity anomaly value, S, in the first discrete data set i Represents a given point low frequency signal, N, contained in the ith gravity anomaly value i Indicates a high value included in the ith gravity abnormal valueA frequency interference signal.
Step S2: and performing discrete Fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, wherein the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one by one.
In this embodiment, since it is convenient to process the gravity data in the frequency domain, the discrete data values in the first discrete data set may be subjected to discrete fourier transform to obtain the second discrete data set in the frequency domain, where the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values in a one-to-one manner. In this embodiment, each discrete data value in the second discrete data set may be represented by:
wherein the content of the first and second substances,representing the ith discrete data value, S, in said second discrete data set mi Representing the low frequency signal value, N, corresponding to the ith discrete data value in said second discrete data set mi And representing the high-frequency interference value corresponding to the ith discrete data value in the second discrete data group. Wherein, the first and the second end of the pipe are connected with each other,S mi and N mi Are respectively connected withS i And N i And correspondingly.
And step S3: establishing a first target equation based on the second discrete data set, wherein the first target equation further comprises a first downward extension parameter and a second downward extension parameter to be determined;
and step S4: and determining the parameter value of the first downward extending parameter and the parameter value of the second downward extending parameter based on a golden section algorithm.
In this embodiment, the first target equation may be established according to the following formula:
wherein φ (β) represents the first objective equation, S mi 0 Represents a stable approximation, S, corresponding to the ith discrete data value in the second discrete data set mi * Represents the ith discrete data value in the second discrete data set, a represents the first down-scaling parameter, β represents the second down-scaling parameter, u represents the first down-scaling parameter, u represents the second down-scaling parameter, and 0 representing the minimum wave number, lambda, of the high-frequency signal to be cancelled x Representing the fundamental wavelength, M being the total number of discrete data values in said second discrete data set, u = i/λ x 。
In the first objective equation, the unknowns are α and β, in order to determine specific values for α and β. In the present embodiment, β can be set in a range of 0.5 to 2.5 in steps of 0.1. For example, β may take on a value of 0.5 for the first time, 0.6 for the second time, and so on. In this embodiment, the value of β can be taken as the test parameter value of the second downward parameter each time. After each determination of the test parameter value of the second down-extending parameter, the test parameter value of the first down-extending parameter α can be further determined.
In this embodiment, the trial parameter value of the first lag parameter may be determined according to the following equation:
wherein, delta 0 Representing a preset constant, the left side of the above equation can be represented by phi (alpha).
In the present embodiment, it is relatively troublesome to directly solve the above equation, and the calculation efficiency is also relatively low. Thus, the deviceThe golden section algorithm may be used to find the trial parameter values for the first lag parameter that enables the above equation to hold. Specifically, in this embodiment, the value range of the first downward delay parameter may be between 0.5 and 5. Referring to fig. 2, two boundary points may be selected first, and the two boundary points selected for the first time may be two critical points of the value range, where the boundary point a may be 5 and the boundary point B may be 0.5. At this time, α can be determined within the two boundary points 1 And alpha 2 Wherein α is 1 The distance from the boundary point B was (0.618 × (A-B)), and α 2 The distance from the boundary point A was also (0.618 × (A-B)).
At the determination of alpha 1 And alpha 2 Then, phi (alpha) can be calculated 1 ) And phi (alpha) 2 ) The value of (c). After calculating the corresponding values of the two points, if phi (alpha) 1 )>φ(α 2 ) Then, it is found that the interval (B, α) of α is such that φ (α) has a minimum value 1 ) And (4) inside. Thus, can discard (alpha) 1 A) interval of 1 The same process continues as the new a value until the final a value is determined.
Thus, the value α calculated by the golden section algorithm can be the value of the trial parameter of the first lag parameter α. In this way, the test parameter value of the first downward extending parameter and the test parameter value of the second downward extending parameter can form a test data set.
In this embodiment, each time β changes, its corresponding α will also change, so that a different set of test data can be obtained. In this way, different sets of test data can be substituted into the first objective equation, thereby obtaining a plurality of values corresponding to the first objective equation.
In this embodiment, a target test data set corresponding to the first target equation when the first target equation obtains the minimum value may be determined, and target test parameter values corresponding to a first downward-extending parameter and a second downward-extending parameter in the target test data set may be determined as parameter values of the first downward-extending parameter and the second downward-extending parameter, respectively.
Thus, the final values of α and β can be determined by steps S3 and S4.
Step S5: and establishing a second target equation according to the second discrete data set and the first downward extension parameter and the second downward extension parameter of which the parameter values are determined, wherein the second target equation comprises a first frequency parameter and a second frequency parameter to be determined.
In the present embodiment, after determining the parameter values of the first downward-extending parameter and the second downward-extending parameter, a second objective equation may be further established. The second objective equation may calculate a downward continuation of the passband range. In this embodiment, the second target equation may be established according to the following formula:
wherein, f α ＝1/{(1+αξ m1 )·(1+αξ m2 )}，φ(u 1 ,u 2 ) Representing said second target equation, u 1 Represents said first frequency parameter, u 2 Represents the second frequency parameter, S mi And the low-frequency signal value corresponding to the ith discrete data value in the second discrete data group is represented, and z is the depth corresponding to the second discrete data group.
Step S6: and determining the parameter value of the first frequency parameter and the parameter value of the second frequency parameter corresponding to the minimum value obtained by the second target equation.
In this embodiment, the second target equation includes two unknowns: a first frequency parameter and a second frequency parameter. In order to determine values of the first frequency parameter and the second frequency parameter, the first frequency parameter and the second frequency parameter may be sequentially assigned, and the first frequency parameter and the second frequency parameter after assignment are substituted into the second objective equation. Therefore, different values of the second target equation can be obtained after the assignment is substituted into the second target equation because the assignments in each time are different. In this embodiment, the assignment values of the first frequency parameter and the second frequency parameter corresponding to the minimum value of the second objective equation may be determined as the parameter values of the first frequency parameter and the second frequency parameter.
Thus, through the steps S3 to S6, specific values of the first downward extension parameter, the second downward extension parameter, the first frequency parameter, and the second frequency parameter can be determined.
Step S7: and determining a continuation discrete data set subjected to downward continuation by the second discrete data set according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter with the determined parameter values, and the first frequency parameter and the second frequency parameter with the determined parameter values, and performing discrete Fourier transform on the continuation discrete data set to obtain a gravity data set subjected to downward continuation.
In this embodiment, the second discrete data set may be downwardly extended by a downwardly extending filter operator. The downward continuation filter operator may be established by the second discrete data set, the first and second downward continuation parameters determining parameter values, and the first and second frequency parameters determining parameter values. Specifically, the downward continuation filter operator may be expressed as:
S um ＝S m * ·f α ·e -2πuz
wherein S is um Continuation discrete data set representing downward continuation of said second discrete data set, S m * Representing the second discrete data set.
In this way, the extended discrete data set, which is extended downwards by the second discrete data set, can be determined by the downward extension filter operator.
In the downward continuation filter operator, f α ＝1/{(1+αξ m1 )·(1+αξ m2 )}， Since the specific values of the first downward extension parameter, the second downward extension parameter, the first frequency parameter and the second frequency parameter are determined, and other parameters are constants, the second discrete data set can be substituted into the downward continuation filter operator, so that the continuation discrete data set S of the second discrete data set subjected to downward continuation can be obtained um 。
Step S8: and acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
In this embodiment, for the discrete data sets corresponding to different depths of the stratum, the corresponding downward continuation gravity data set can be finally obtained through the schemes described in steps S1 to S7. In this way, downwardly extended gravity data sets corresponding to different depths of the horizon can be generated. In the embodiment, the gravity data set subjected to downward continuation can be subjected to interpolation and then imaged by utilizing mature double fox software in the field, so that the downward continuation imaging result of the stratum can be obtained.
Referring to fig. 3, the present application further provides an image forming apparatus for downward continuation based on gravity data, the apparatus comprising:
a first discrete data set acquisition unit 100, configured to extract a first discrete data set of preset line positions from the gravity data, where the first discrete data set includes a preset number of gravity abnormal values;
a second discrete data set obtaining unit 200, configured to perform discrete fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, where the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one to one;
a first target equation establishing unit 300, configured to establish a first target equation based on the second discrete data set, where the first target equation includes a first downward delay parameter to be determined and a second downward delay parameter;
a downward extension parameter determining unit 400, configured to determine a parameter value of the first downward extension parameter and a parameter value of the second downward extension parameter based on a golden section algorithm;
a second target equation establishing unit 500, configured to establish a second target equation according to the second discrete data set and the first downward-extending parameter and the second downward-extending parameter for which the parameter value is determined, where the second target equation further includes a first frequency parameter and a second frequency parameter to be determined;
a frequency parameter determining unit 600, configured to determine a parameter value of the first frequency parameter and a parameter value of the second frequency parameter corresponding to the minimum value obtained by the second objective equation;
a continuation discrete data set determining unit 700, configured to determine, according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter for which the parameter value is determined, and the first frequency parameter and the second frequency parameter for which the parameter value is determined, a continuation discrete data set in which the second discrete data set is extended downward, and perform discrete fourier transform on the continuation discrete data set to obtain a gravity data set in which the second discrete data set is extended downward;
and the imaging unit 800 is used for acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
In a preferred embodiment of the present application, the first discrete data set obtaining unit 100 specifically includes:
an original discrete data set acquisition module, configured to extract an original discrete data set at a preset line measurement position from the gravity data, where the original discrete data set includes multiple original gravity outliers;
and the interpolation calculation module is used for performing interpolation calculation on the plurality of original gravity abnormal values to generate the first discrete data group, and the step length between any two adjacent gravity abnormal values in the first discrete data group is the same.
In a preferred embodiment of the present application, the first target equation establishing unit 300 establishes the first target equation according to the following formula:
wherein φ (β) represents the first objective equation, S mi 0 Represents a stable approximation, S, corresponding to the ith discrete data value in the second discrete data set mi * Represents the ith discrete data value in the second discrete data set, a represents the first down-scaling parameter, β represents the second down-scaling parameter, u represents the first down-scaling parameter, u represents the second down-scaling parameter, and 0 representing the minimum wave number, lambda, of the high-frequency signal to be cancelled x Representing the fundamental wavelength, M being the total number of discrete data values in said second discrete data set, u = i/λ x 。
In a preferred embodiment of the present application, the downward parameter determining unit 400 specifically includes:
a test data set obtaining module, configured to determine a test parameter value of the second downward extending parameter, and determine, based on the test parameter value of the second downward extending parameter and the golden section algorithm, a test parameter value of the first downward extending parameter that makes the following equation hold:
wherein, delta 0 Representing a preset constant, wherein the test parameter value of the first downward delay parameter and the test parameter value of the second downward delay parameter form a test data group;
a substitution module for substituting different test data sets into the first target equation;
and the parameter value determining module is used for determining a target test data group corresponding to the minimum value obtained by the first target equation, and determining target test parameter values corresponding to a first downward delay parameter and a second downward delay parameter in the target test data group as parameter values of the first downward delay parameter and the second downward delay parameter.
It should be noted that the specific implementation manner and the calculation formula of each functional module are consistent with those described in steps S1 to S8, and are not described herein again.
As can be seen from the above, in the embodiments of the present application, the first target equation and the second target equation are respectively used, so that the parameter values of the first downward-extending parameter, the second downward-extending parameter, the first frequency parameter, and the second frequency parameter can be determined. When the first downward extending parameter and the second downward extending parameter are determined, the golden section algorithm is adopted, and therefore the efficiency of parameter value determination is improved. After the parameter values of the first downward-extending parameter, the second downward-extending parameter, the first frequency parameter and the second frequency parameter are determined, a continuation discrete data set of the second discrete data set subjected to downward continuation can be determined. Therefore, according to the downwardly extended gravity data set corresponding to different stratum depths, a downwardly extended imaging result of the stratum can be obtained. According to the imaging method and device for downward continuation based on the gravity data, the available information in the gravity data can be kept, and meanwhile the high-frequency oscillation effect in the downward continuation process can be weakened, so that an accurate stratum imaging result can be obtained.
In this specification, adjectives such as first and second may be used solely to distinguish one element or action from another element or action without necessarily requiring or implying any actual such relationship or order. References to an element or component or step (etc.) should not be construed as limited to only one of the element, component, or step but rather to one or more of the element, component, or step, etc., where the context permits.
The foregoing description of various embodiments of the present application is provided for the purpose of illustration to those skilled in the art. It is not intended to be exhaustive or to limit the invention to a single disclosed embodiment. As described above, various alternatives and modifications of the present application will be apparent to those skilled in the art to which the above-described technology pertains. Thus, while some alternative embodiments have been discussed in detail, other embodiments will be apparent or relatively easy to derive by those of ordinary skill in the art. This application is intended to cover all alternatives, modifications, and variations of the invention discussed herein, as well as other embodiments, which fall within the spirit and scope of the above-mentioned application.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Although the present application has been described in terms of embodiments, those of ordinary skill in the art will recognize that there are numerous variations and modifications of the present application without departing from the spirit of the application, and it is intended that the appended claims encompass such variations and modifications without departing from the spirit of the application.
Claims (10)
1. An imaging method for downward continuation based on gravity data, the method comprising:
extracting a first discrete data set of a preset measuring line position from the gravity data, wherein the first discrete data set comprises a preset number of gravity abnormal values;
performing discrete Fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, wherein the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one by one;
establishing a first target equation based on the second discrete data set, wherein the first target equation comprises a first downward extension parameter and a second downward extension parameter to be determined;
determining a parameter value of the first downward extending parameter and a parameter value of the second downward extending parameter based on a golden section algorithm;
establishing a second target equation according to the second discrete data set and the first downward extending parameter and the second downward extending parameter of which the parameter values are determined, wherein the second target equation comprises a first frequency parameter and a second frequency parameter to be determined;
determining a parameter value of a first frequency parameter and a parameter value of a second frequency parameter corresponding to the minimum value obtained by the second target equation;
determining a continuation discrete data set subjected to downward continuation by the second discrete data set according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter which are determined as parameter values, and the first frequency parameter and the second frequency parameter which are determined as parameter values, and performing discrete Fourier transform on the continuation discrete data set to obtain a gravity data set subjected to downward continuation;
and acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
2. The method of claim 1, wherein extracting a first discrete data set of preset line positions from the gravity data specifically comprises:
extracting an original discrete data set of a preset measuring line position from the gravity data, wherein the original discrete data set comprises a plurality of original gravity abnormal values;
and performing interpolation calculation on the plurality of original gravity abnormal values to generate the first discrete data set, wherein the step length between any two adjacent gravity abnormal values in the first discrete data set is the same.
3. The method of claim 1, wherein the first target equation is established according to the following equation:
wherein φ (β) represents the first objective equation, S mi 0 Represents a stable approximation corresponding to the ith discrete data value in the second discrete data set, S mi * Represents the ith discrete data value in the second discrete data set, a represents the first down-extending parameter, β represents the second down-extending parameter, u 0 Representing the minimum wave number, lambda, of the high-frequency signal to be cancelled x Represents the fundamental wavelength, M isThe total number of discrete data values in the second discrete data set, u = i/λ x 。
4. The method of claim 3, wherein determining the parameter values of the first and second downward-extending parameters based on a golden section algorithm specifically comprises:
determining a test parameter value of the second downward extending parameter, and determining a test parameter value of the first downward extending parameter which makes the following equation satisfied based on the test parameter value of the second downward extending parameter and the golden section algorithm:
wherein, delta 0 Representing a preset constant, wherein the test parameter value of the first downward delay parameter and the test parameter value of the second downward delay parameter form a test data group;
substituting different test data sets into the first target equation;
and determining a target test data group corresponding to the first target equation when the first target equation obtains the minimum value, and determining target test parameter values corresponding to a first downward extension parameter and a second downward extension parameter in the target test data group as parameter values of the first downward extension parameter and the second downward extension parameter.
5. The method of claim 4, wherein the second target equation is:
wherein f is α ＝1/{(1+αξ m1 )·(1+αξ m2 )}，φ(u 1 ,u 2 ) Representing said second target equation, u 1 To representThe first frequency parameter u 2 Representing said second frequency parameter, S mi And z is the depth corresponding to the second discrete data set.
6. The method of claim 5, wherein the downwardly extended discrete data set of the second discrete data set is determined according to the following equation:
S um ＝S m * ·f α ·e -2πuz
wherein S is um Extended discrete data set, S, representing downward extension of said second discrete data set m * Representing the second discrete data set.
7. An imaging device for downward continuation based on gravity data, the device comprising:
the first discrete data set acquisition unit is used for extracting a first discrete data set of a preset measuring line position from the gravity data, and the first discrete data set comprises a preset number of gravity abnormal values;
a second discrete data set acquisition unit, configured to perform discrete fourier transform on the gravity abnormal values in the first discrete data set to obtain a second discrete data set, where the discrete data values in the second discrete data set correspond to the preset number of gravity abnormal values one to one;
the first target equation establishing unit is used for establishing a first target equation based on the second discrete data set, wherein the first target equation comprises a first downward extension parameter and a second downward extension parameter to be determined;
a downward extension parameter determining unit, configured to determine a parameter value of the first downward extension parameter and a parameter value of the second downward extension parameter based on a golden section algorithm;
a second target equation establishing unit, configured to establish a second target equation according to the second discrete data set and the first downward-extending parameter and the second downward-extending parameter for which the parameter value is determined, where the second target equation further includes a first frequency parameter and a second frequency parameter to be determined;
the frequency parameter determining unit is used for determining a parameter value of the first frequency parameter and a parameter value of the second frequency parameter corresponding to the minimum value obtained by the second objective equation;
a continuation discrete data set determining unit, configured to determine, according to the second discrete data set, the first downward continuation parameter and the second downward continuation parameter for which the parameter value is determined, and the first frequency parameter and the second frequency parameter for which the parameter value is determined, a continuation discrete data set in which the second discrete data set is subjected to downward continuation, and perform discrete fourier transform on the continuation discrete data set to obtain a downward continuation gravity data set;
and the imaging unit is used for acquiring a downward continuation imaging result of the stratum based on the downward continuation gravity data group.
8. The apparatus according to claim 7, wherein the first discrete data set obtaining unit specifically includes:
the original discrete data set acquisition module is used for extracting an original discrete data set of a preset line measurement position from the gravity data, and the original discrete data set comprises a plurality of original gravity abnormal values;
and the interpolation calculation module is used for performing interpolation calculation on the plurality of original gravity abnormal values to generate the first discrete data group, and the step length between any two adjacent gravity abnormal values in the first discrete data group is the same.
9. The apparatus according to claim 7, wherein the first target equation establishment unit establishes the first target equation in accordance with the following formula:
wherein φ (β) represents the first objective equation, S mi 0 Represents a stable approximation corresponding to the ith discrete data value in the second discrete data set, S mi * Represents the ith discrete data value in the second discrete data set, a represents the first down-scaling parameter, β represents the second down-scaling parameter, u represents the first down-scaling parameter, u represents the second down-scaling parameter, and 0 representing the minimum wave number, lambda, of the high-frequency signal to be cancelled x Representing the fundamental wavelength, M being the total number of discrete data values in said second discrete data set, u = i/λ x 。
10. The apparatus of claim 9, wherein the downward parameter determining unit specifically comprises:
a test data set obtaining module, configured to determine a test parameter value of the second downward parameter, and determine, based on the test parameter value of the second downward parameter and a golden section algorithm, a test parameter value of the first downward parameter that enables the following equation to be satisfied:
wherein, delta 0 Representing a preset constant, wherein the test parameter value of the first downward-extending parameter and the test parameter value of the second downward-extending parameter form a test data group;
a substitution module for substituting different test data sets into the first target equation;
and the parameter value determining module is used for determining a target test data group corresponding to the first target equation when the first target equation obtains the minimum value, and determining target test parameter values corresponding to a first downward-extending parameter and a second downward-extending parameter in the target test data group as parameter values of the first downward-extending parameter and the second downward-extending parameter respectively.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1230260A (en) * | 1996-09-13 | 1999-09-29 | Pgs张量公司 | Method for time lapse reservoir monitoring |
| CN103399350A (en) * | 2013-07-29 | 2013-11-20 | 中国人民解放军国防科学技术大学 | Airborne gravity downward continuation method based on integral iteration algorithm |
-
2016
- 2016-08-01 CN CN201610621086.9A patent/CN107678068A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1230260A (en) * | 1996-09-13 | 1999-09-29 | Pgs张量公司 | Method for time lapse reservoir monitoring |
| CN103399350A (en) * | 2013-07-29 | 2013-11-20 | 中国人民解放军国防科学技术大学 | Airborne gravity downward continuation method based on integral iteration algorithm |
Non-Patent Citations (2)
| Title |
|---|
| 张志厚 等: "位场向下延拓的相关系数法", 《吉林大学学报（地球科学版）》 * |
| 王纯: "基于深度变化的重力位场正则化下延方法研究", 《中国优秀硕士学位论文全文数据库》 * |
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