CN110837120A - Method for calculating static correction value of floating reference surface of complex surface area - Google Patents
Method for calculating static correction value of floating reference surface of complex surface area Download PDFInfo
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Abstract
The invention relates to a method for calculating a static correction value of a floating reference surface of a complex surface area, wherein the static correction value of the floating reference surface is a static correction value of each CMP point in three-dimensional seismic data relative to a fixed reference surface, and the method comprises the following steps: calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method; and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
Description
Technical Field
The invention relates to the technical field of seismic signal processing, in particular to a method for calculating a static correction value of a floating reference surface of a complex surface area based on non-local mean filtering.
Background
In the seismic data processing of complex surface areas and high-precision three-dimensional seismic data, the static correction value is changed drastically due to the change of the near-surface, and the hyperbolic time-distance curve of the reflected wave is distorted. Floating datum correction is typically used to eliminate this effect. The currently common methods for calculating the static correction value of the floating reference surface comprise an average static correction value method and a smooth earth surface method, and the static correction values of the floating reference surface obtained by different calculation methods are different. For different regions, the adopted method for calculating the static correction value of the floating reference surface is different due to different near-surface undulations. At present, a common floating datum plane calculation method is an average static correction method. In southern, mid-western regions of our country, the calculated average static correction value may have a sudden change due to severe surface relief.
In a complex surface area, when the floating datum plane is calculated by adopting an average static correction method to carry out seismic data prestack time migration processing, a local sawtooth phenomenon exists on a section, which is caused by sudden change of the static correction value. Therefore, a smoother floating reference surface is needed for the calculation. That is, when the average static correction amount method is used for calculation, it is necessary to smooth the static correction amount at each CMP (Common Middle Point) Point in the spatial domain.
Disclosure of Invention
In order to solve the technical problem, the invention provides a method for calculating the static correction value of the floating reference surface based on non-local mean filtering, which can eliminate the abnormal mutation point of the static correction value, better protect the structural information of a signal, has better algorithm effect and does not influence the discrete point with larger change.
According to one aspect of the present invention, there is provided a method for calculating a floating reference plane statics correction amount for a complex surface area, the floating reference plane statics correction amount being a statics correction amount for each CMP point in three-dimensional seismic data with respect to a fixed reference plane, the method comprising:
calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method;
and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
In one embodiment, calculating the floating reference surface static correction amount for each CMP point by an average static correction amount method includes:
and summing and averaging the static correction values of the shot points and the demodulator probes of all the channels of each CMP gather relative to the fixed reference surface to obtain the static correction value of the floating reference surface of each CMP point.
In one embodiment, the static correction value T of the shot point and the demodulator probe relative to a fixed reference surfacemThe calculation formula of (2) is as follows:
wherein E isg(m) is the elevation of the mth shot or geophone point; h isnmThe thickness V of the nth layer low-speed zone corresponding to the mth shot point or demodulator probenIs the speed of each layer of the low speed belt; n is the number of layers of the low-speed belt; v. ofcIs the static correction replacement speed; edIs the elevation of the fixed reference plane.
In one embodiment, the weight value for each CMP point is added when calculating the floating reference surface static correction amount for each CMP point.
In one embodiment, smoothing the floating reference plane static correction amount at each CMP point in the spatial domain using a non-local mean filtering method comprises:
and selecting parameters for controlling the filtering strength, so that the smoothed static correction value of the floating reference surface of each CMP point is similar to the static correction value of the floating reference surface of each CMP point obtained by an average static correction method in shape.
In one embodiment, smoothing the floating reference plane static correction amount at each CMP point in the spatial domain using a non-local mean filtering method comprises:
assuming that a p point is a point to be processed by the filter, when the filter traverses to the p point, a pixel point in a p point neighborhood needs to be traversed, assuming that a q point is a pixel in the p point neighborhood, and when an algorithm traverses to the q point, a weight value between the p point and the q point needs to be calculated, which includes:
obtaining two rectangular similar windows B (p, f) and B (q, f) with the sizes of (2f +1) (2f +1) and taking p and q as centers respectively, wherein f is the radius of the similar windows; and
the gaussian-weighted euclidean distance between B (p, f) and B (q, f) is calculated.
In an embodiment, smoothing the floating reference plane static correction amount at each CMP point in the spatial domain by using a non-local mean filtering method further includes:
and adding Gaussian kernel calculation to obtain a weight value between the point p and the point q.
In an embodiment, smoothing the floating reference plane static correction amount at each CMP point in the spatial domain by using a non-local mean filtering method further includes:
and calculating a smoothing result of the point p according to the obtained weight value and the value at the point q.
In one embodiment, smoothing the floating reference plane static correction amount at each CMP point in the spatial domain using a non-local mean filtering method comprises:
the selected search radius is 9, the similar radius is 5, and the parameter controlling the filtering strength is 80.
According to another aspect of the present invention, there is provided a storage medium having stored therein a computer-executable program adapted to, when executed, perform a method for calculating a floating reference plane static correction amount for a complex surface area, the floating reference plane static correction amount being a static correction amount for each CMP point in three-dimensional seismic data with respect to a fixed reference plane, the method comprising:
calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method;
and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
by applying the method for calculating the static correction value of the floating datum plane of the complex surface area based on the non-local mean filtering, provided by the embodiment of the invention, the problem of calculating the static correction value of the floating datum plane in the complex surface area and the high-precision three-dimensional seismic data during seismic data processing is solved, and the sawtooth phenomenon in a seismic section is eliminated. The non-local mean filtering algorithm is applied to smooth the static correction value of the floating reference surface, so that abnormal catastrophe points of the static correction value can be eliminated, the structural information of the signal can be better protected, the algorithm effect is good, and the influence on discrete points with large changes is avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 schematically illustrates a floating reference plane static correction amount calculated using the average static correction method;
FIG. 2 is a flow chart of a method for calculating a floating reference plane static correction for a complex surface region according to an embodiment of the present invention;
FIG. 3 illustrates smoothed floating reference plane static corrections according to an embodiment of the present invention;
FIGS. 4a and 4b are diagrams illustrating the average static correction of a selected measurement line respectively showing the static correction of the floating reference plane calculated by the average static correction method and the static correction of the floating reference plane calculated according to the embodiment of the present invention;
fig. 5a and 5b show a superposition profile obtained by the average static correction method and a superposition profile obtained according to an embodiment of the invention, respectively.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without these specific details or with a specific implementation described herein.
As described above, in order to solve the problem of calculating the static correction value of the floating reference plane during the seismic data processing of the complex surface area and the high-precision three-dimensional seismic data in the prior art and eliminate the sawtooth phenomenon occurring in the seismic section, the embodiment of the invention provides a method for calculating the static correction value of the floating reference plane based on the non-local mean filtering.
In this embodiment, three-dimensional seismic data of a complex mountain land in a certain place in south of China is taken as an example for explanation. The mountain land has severe surface fluctuation and large elevation difference.
Fig. 1 schematically shows a floating reference surface static correction amount calculated by the average static correction amount method. As shown in fig. 1, the abscissa represents the abscissa of the floating reference plane static correction amount for each CMP point, i.e., the point number; the vertical axis represents the vertical coordinate, i.e., the line number, of the floating reference plane static correction amount for each CMP point. Each CMP point has a floating reference surface static correction amount corresponding thereto, i.e., a static correction amount of each CMP point with respect to a fixed reference surface. The abscissa of each CMP point is the same as the abscissa of the static correction amount of each CMP point with respect to the fixed reference surface, and the ordinate of each CMP point is the same as the ordinate of the static correction amount of each CMP point with respect to the fixed reference surface. Therefore, the abscissa in fig. 1 can also be regarded as the abscissa of each CMP point, and the ordinate in fig. 1 can also be regarded as the ordinate of each CMP point. The static correction amount of each CMP point with respect to the fixed reference plane constitutes a diagram of the static correction amount of the floating reference plane as shown in fig. 1.
In fig. 1, darker areas indicate that the absolute value of the floating reference plane static correction amount for the areas is larger, and lighter areas indicate that the absolute value of the floating reference plane static correction amount for the areas is smaller. The floating reference surface static correction amount indicated by, for example, a dot number 100, a line number 40 is-30; the floating reference surface static correction amount indicated by the dot number 200 and the line number 40 is 0. As shown in fig. 1, the floating reference surface static correction amount calculated by the average static correction amount method varies drastically and does not conform to the essence of the floating reference surface. When the static correction value is applied to seismic processing, a sawtooth phenomenon occurs on a seismic section, the same-phase axis on the section shakes, the wave group characteristics are discontinuous, and the subsequent seismic data interpretation is influenced because the same-phase axis cannot be corrected into the continuous same-phase axis by applying the subsequent static correction method.
It is to be noted that fig. 1 is a schematic view showing only the rough case of the floating reference surface static correction amount, and does not accurately reflect the floating reference surface static correction amount for each CMP point. The actual situation is more complicated than the situation shown in fig. 1, so that the static correction value of the floating reference surface calculated by the average static correction value method is far less than the data requirement of subsequent seismic data interpretation.
In view of this, the embodiment of the present invention provides a method for calculating a floating reference plane static correction value based on non-local mean filtering. FIG. 2 is a flow chart of a method for calculating a floating reference plane static correction for a complex surface region according to an embodiment of the present invention. As shown in fig. 2, the method includes:
step S201: calculating the static correction value of the floating datum plane of each CMP point in the three-dimensional seismic data by an average static correction value method; and
step S202: and smoothing the static correction value of the floating reference surface of each CMP point one by one in a space domain by using a non-local mean filtering method.
The conventional static correction value calculation is to calculate the static correction value T of the shot point and the demodulator probe relative to a fixed reference surfacemThe calculation formula is as follows:
in the formula: eg(m) is the elevation of the mth shot or geophone point; h isnmThe thickness of the nth layer of low-speed zone corresponding to the mth shot point or the demodulator probe; vnIs the speed of each layer of the low speed belt; n is the number of layers of the low-speed belt; v. ofcIs the static correction replacement speed; edIs the elevation of the fixed reference plane.
The static correction values of the shot point and the demodulator probe with respect to the fixed reference plane are calculated by the formula (1), and then these static correction values are assigned to each track.
This is basically possible in situations where the surface relief is not very large and the accuracy requirements of the survey are not too high. However, at present, as the ground surface condition of a exploration area is more and more complex, the exploration precision requirement is higher and higher, and the fixed datum plane cannot meet the precision requirement, so that the fixed datum plane is replaced by the floating datum plane.
The floating reference plane is a smooth curve formed by the elevations of the various CMP points. Therefore, determining the floating datum requires determining the horizontal datum level for each CMP point. The floating datum planes determined by different methods are different, and the common methods include a smooth earth surface elevation method, an average static correction method and the like. The average static correction method is more commonly used at present. The average static correction method comprises the following steps: firstly, obtaining the static correction value of each shot point and each demodulator probe through the formula (1); then summing and averaging the static correction values of all tracks in each CMP point to serve as the correction value of the CMP point, wherein the correction value refers to the correction value from the floating reference surface to the fixed reference surface; then, the elevation N of the floating datum plane at each CMP point is obtained by reverse-deducing the equation (2) belowd(j)：
Tc(j)＝2(Nd(j)-Ed)/vc(2)
In the formula: edFor fixing the elevation of the reference plane vcFor static correction of the replacement speed, Tc(j) Is a static correction amount from the fixed reference surface to the floating reference surface. Note here that the average value of the CMP gather trace static correction values with respect to the fixed reference plane is negative Tc(j) In that respect In this document, the floating reference plane static correction amount refers to a floating reference plane to fixed reference plane static correction amount (the floating reference plane to fixed reference plane static correction amount differs from the fixed reference plane to floating reference plane static correction amount by a minus sign). One correction for a CMP is for a two-way trip. Therefore, when the near-surface condition is complex and the elevation changes drastically, the static correction value at each CMP point obtained by summing and averaging also varies drastically, and the calculated static correction value of the floating reference surface is not smooth. Therefore, the non-local mean filtering algorithm is introduced to calculate the static correction value T of the smooth floating reference surfacec(j)。
The basic principle of the non-local mean filtering algorithm is similar to that of mean filtering, and averaging is required, but the non-local mean filtering adds a weight value of each point in calculation, so that the influence of adjacent and widely different points on averaging in a block can be reduced.
Assuming a two-dimensional matrix u, NL [ u ] is used to represent the result after smoothing by the non-local mean filtering algorithm, which is expressed by the following equation (3):
NL[u](i)＝∑i,j∈uw(i,j)u(j) (3)
in the formula: i. j are all elements of matrix u. The left side of the formula (3) represents the value after the non-local mean filtering algorithm; the right side w (i, j) represents the influence of element j on element i, i.e. the weight of element j relative to element i; u (j) are elements in the neighborhood of the similarity point i; wherein w (i, j) is more than or equal to 0 and less than or equal to 1, and the sum of the weights of all the elements is 1. The weight w (i, j) of the non-local mean filtering algorithm reflects the similarity degree of two similar windows of the element i and the element j. Similar window is denoted as u (N)k) It represents a rectangular area centered on the element k, in a non-local meanThis is called the neighborhood window in the filtering algorithm.
The specific calculation process of the algorithm is as follows:
assuming that a p point is a point to be processed by the filter, when the filter traverses to the p point, a pixel point in a p point neighborhood needs to be traversed, assuming that a q point is a pixel in the p point neighborhood, and when an algorithm traverses to the q point, a weight value between the p point and the q point needs to be calculated, which includes: obtaining two rectangular neighborhoods B (p, f) and B (q, f) of size (2f +1) (2f +1) centered on p and q, respectively, called similarity windows, where f is the radius of the similarity windows, and then calculating the gaussian weighted euclidean distance between B (p, f) and B (q, f) by the following equation (4):
in the formula: j means that there are several elements in the similarity window, the size is determined by f; sigmaj∈B(0,f)(ui(p+j)-ui(q+j))2Means summing after square of corresponding subtraction for each element in a similar window with p and q as the center respectively; i refers to the number of search windows, which are not involved in the calculation. The sum is calculated according to equation (4). Adding a Gaussian kernel to calculate to obtain a weight value between the point p and the point q:
the normalized coefficients are:
C(p)＝∑q∈B(p,q)w(p,q) (6)
where c (p) refers to the sum of the weights of each q point and p point relative to p point, σ is the standard deviation of a gaussian kernel greater than zero, the gaussian-weighted euclidean distance is to calculate the similarity of two similarity windows of element i and element j, and h is a parameter to control the filter strength, which controls the decay rate of the exponential function to control the weight magnitude of the euclidean distance and thus the degree of smoothing of the elements.
Then, the value at the q point (i.e., the weighted value) is calculated according to the obtained weighted valueui(q)) the smoothing result for p points is calculated as:
where q ∈ B (p, r) means that q is an element located within the search window B, Σq∈B(p,r)ui(q) w (p, q) refers to weighting of a similar window centered around p and q, for each pixel q within the window a weighted sum of p and the resulting similar window, ui(q) is the value at the element q point.
In the three-dimensional seismic data, the static correction value of any point p is expressed as s (p), and then according to the above formulas (6) and (7), the non-local mean filtering algorithm is used to obtain the static correction value of the smoothed floating reference surface, which is:
here, the
The smoothed result at element point p. Wherein, I (p) represents the weighted sum of all similar windows with the element p as the center, and W (p) represents the weighted sum of all similar windows with the element p as the center. The specific algorithm is to traverse all elements from top to bottom and from left to right.
And selecting proper parameters for controlling the filtering strength, and smoothing the CMP static correction values in a spatial domain to obtain smoothed static correction values of the floating reference surface.
When applying non-local mean filtering for smoothing, a suitable parameter h for controlling the filtering strength must be selected. If the h value is too small, the smoothing effect is not obvious, and the catastrophe point cannot be removed; if the value of h is too large, the smoothing effect is too pronounced, resulting in much detail disappearing. When the method is applied to carry out the floating reference surface static correction amount smoothing, if h is 0, the smoothing is basically not carried out, and a value with h larger than 0 needs to be selected for smoothing. During actual data processing, the floating reference surface static correction value obtained by smoothing is compared with the floating reference surface static correction value generated by the average static correction value method, and the forms of the floating reference surface static correction value and the floating reference surface static correction value are similar as much as possible.
FIG. 3 illustrates smoothed floating reference plane static corrections according to an embodiment of the present invention. As shown in fig. 3, the static correction amount of the floating reference surface is smooth, and there is no abrupt point of the static correction amount, which conforms to the essence of the floating reference surface. In this embodiment, the search radius is selected to be 9, the similarity radius is selected to be 5, and the parameter h for controlling the filtering strength is selected to be 80.
Fig. 4a and 4b show the floating reference plane static correction amount calculated by the average static correction amount method of a selected measuring line and the floating reference plane static correction amount calculated according to the embodiment of the present invention, respectively. Specifically, fig. 4a and 4b show the floating reference plane static correction amount calculated by the average static correction amount method at the line 80 from the vertical axis selected in fig. 1 and the floating reference plane static correction amount calculated according to the embodiment of the present invention, respectively. As can be seen from fig. 4a and 4b, the floating reference surface static correction value calculated according to the embodiment of the present invention is relatively smooth, and the shape is very close to the floating reference surface static correction value calculated by the average static correction value method.
Fig. 5a and 5b show a superposition profile obtained by the average static correction method and a superposition profile obtained according to an embodiment of the invention, respectively. As shown in fig. 5a, the seismic stack section obtained by the average statics correction method has a jagging phenomenon, for example, a severe jagging phenomenon exists at the point number 150 section. As can be seen from FIG. 5b, the floating reference plane obtained according to the embodiment of the invention well solves the sawtooth phenomenon of the superposed section, the in-phase axis is continuous and smooth, and the quality of the section is obviously improved. Therefore, the method according to the embodiment of the invention can well smooth the floating reference surface, and the application of practical data proves the feasibility and effectiveness of the method.
In summary, the invention provides a method for calculating a static correction value of a floating reference plane in a complex surface area based on non-local mean filtering, which solves the problem of calculating the static correction value of the floating reference plane in the complex surface area and in the seismic data processing of high-precision three-dimensional seismic data, and eliminates the sawtooth phenomenon in a seismic section. The non-local mean filtering algorithm is applied to smooth the static correction value of the floating reference surface, so that abnormal catastrophe points of the static correction value can be eliminated, the structural information of the signal can be better protected, the algorithm effect is good, and the influence on discrete points with large changes is avoided.
In another aspect, the present invention also provides a storage medium having stored therein a computer-executable program adapted to, when executed, perform a method for calculating a floating reference plane static correction amount for a complex surface area, the floating reference plane static correction amount being a static correction amount for each CMP point in three-dimensional seismic data relative to a fixed reference plane, the method comprising: calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method; and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
It is to be understood that the disclosed embodiments of the invention are not limited to the particular process steps or materials disclosed herein, but rather, are extended to equivalents thereof as would be understood by those of ordinary skill in the relevant art. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
Reference in the specification to "an embodiment" means that a particular feature, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "an embodiment" appearing in various places throughout the specification are not necessarily all referring to the same embodiment.
It will be appreciated by those of skill in the art that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for calculating a floating reference surface statics correction for a complex surface area, the floating reference surface statics correction being a statics correction for each CMP point in three-dimensional seismic data relative to a fixed reference surface, the method comprising:
calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method;
and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
2. The method of claim 1, wherein calculating the floating reference plane static correction amount for each CMP point by an average static correction amount method comprises:
and summing and averaging the static correction values of the shot points and the demodulator probes of all the channels of each CMP gather relative to the fixed reference surface to obtain the static correction value of the floating reference surface of each CMP point.
3. The method of claim 2, wherein the shot and geophone points are relatively solidStatic correction value T of fixed reference surfacemThe calculation formula of (2) is as follows:
wherein E isg(m) is the elevation of the mth shot or geophone point; h isnmThe thickness V of the nth layer low-speed zone corresponding to the mth shot point or demodulator probenIs the speed of each layer of the low speed belt; n is the number of layers of the low-speed belt; v. ofcIs the static correction replacement speed; edIs the elevation of the fixed reference plane.
4. The method according to claim 1, wherein the weight value for each CMP point is added in calculating the floating reference surface static correction amount for each CMP point.
5. The method of claim 1, wherein smoothing the floating reference plane static correction amount for each CMP point in the spatial domain using a non-local mean filtering method comprises:
and selecting parameters for controlling the filtering strength, so that the smoothed static correction value of the floating reference surface of each CMP point is similar to the static correction value of the floating reference surface of each CMP point obtained by an average static correction method in shape.
6. The method of claim 1, wherein smoothing the floating reference plane static correction amount for each CMP point in the spatial domain using a non-local mean filtering method comprises:
assuming that a p point is a point to be processed by the filter, when the filter traverses to the p point, a pixel point in a p point neighborhood needs to be traversed, assuming that a q point is a pixel in the p point neighborhood, and when an algorithm traverses to the q point, a weight value between the p point and the q point needs to be calculated, which includes:
obtaining two rectangular similar windows B (p, f) and B (q, f) with the sizes of (2f +1) (2f +1) and taking p and q as centers respectively, wherein f is the radius of the similar windows; and
the gaussian-weighted euclidean distance between B (p, f) and B (q, f) is calculated.
7. The method of claim 6, wherein smoothing the floating reference plane static correction amount for each CMP point in the spatial domain using a non-local mean filtering method further comprises:
and adding Gaussian kernel calculation to obtain a weight value between the point p and the point q.
8. The method of claim 7, wherein smoothing the floating reference plane static correction amount for each CMP point in the spatial domain using a non-local mean filtering method further comprises:
and calculating a smoothing result of the point p according to the obtained weight value and the value at the point q.
9. The method of claim 8, wherein smoothing the floating reference plane static correction amount for each CMP point in the spatial domain using a non-local mean filtering method comprises:
the selected search radius is 9, the similar radius is 5, and the parameter controlling the filtering strength is 80.
10. A storage medium having stored thereon a computer-executable program adapted to, when executed, perform a method for calculating a floating datum static correction for a complex surface area, the floating datum static correction being a static correction for each CMP point in three-dimensional seismic data relative to a fixed datum, the method comprising:
calculating the static correction value of the floating reference surface of each CMP point by an average static correction value method;
and smoothing the static correction value of the floating reference surface of each CMP point in a spatial domain by using a non-local mean value filtering method.
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| 余青露 等: "基于中值滤波的复杂地表区浮动基准面计算方法", 《2014年中国地球科学联合学术年会——专题19：地震波传播与成像论文集》 * |
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