CN106199714B - The method and apparatus that the equivalent dominant frequency of geological data calculates - Google Patents
The method and apparatus that the equivalent dominant frequency of geological data calculates Download PDFInfo
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Abstract
The present invention relates to seismic data analysis field, and in particular to the method and apparatus that the equivalent dominant frequency of geological data calculates.The present invention assesses the quality of geological data by the acquisition equivalent dominant frequency directly related with seismic wavelet time span and based on the equivalent dominant frequency, can obtain reliable, deterministic assessment result.The advantageous effects of the present invention are fully proved by theoretical model and actual seismic data.
Description
Technical Field
The invention relates to the field of seismic data analysis, in particular to a method and a device for calculating equivalent dominant frequency of seismic data.
Background
Artificial seismic methods are one of the major techniques for oil and gas exploration. The artificial seismic method petroleum and natural gas exploration data (hereinafter referred to as seismic data) contain a large amount of geological information of underground petroleum and natural gas reservoirs, and the quality of the geological information directly influences the success rate of oil-gas exploration. The amount of information contained in the seismic data and the authenticity of the seismic data are objective standards for measuring the quality of the seismic data. The signal-to-noise ratio of the seismic data, the accuracy degree of the stratigraphic structure form and the longitudinal thickness resolution capability are three main standards for measuring the quality of the seismic data.
The longitudinal thickness resolution is generally referred to as the resolution tr (resolution), and the reciprocal is referred to as the resolution pa (resolving power), and the two definitions are essentially identical.
As the development of oil and gas fields enters the middle and later stages, the scale of oil and gas reservoirs to be searched is smaller and more concealed, and the requirement on the resolution ratio of seismic data is higher and higher. Resolution is becoming an increasingly important criterion for seismic data quality. How to calculate the resolution of the seismic data, whether the result is true, will directly affect the judgment of the seismic data quality.
Seismic wavelets are the fundamental signals that make up the seismic data, and the resolution of the seismic wavelets represents the resolution of the seismic data.
A seismic wavelet is a signal that is stable and has a certain time delay (i.e., a certain length of time). The larger the seismic wavelet length is, the more serious the mutual interference of the adjacent stratum reflections is, and the greater the difficulty in obtaining stratum interface reflection coefficients and stratum thickness information from seismic data is. Only if adjacent reflection wavelets are completely separated, mutual interference cannot be caused, and the formation interface reflection coefficient and formation thickness information can be obtained completely and accurately. Therefore, a strict resolution must be defined in terms of the time duration of the seismic wavelet.
FIG. 1(a) is a reflection coefficient and corresponding amplitude spectrum of a thin sand reservoir geological model; FIG. 1(b) is an artificially synthesized seismic record and corresponding amplitude spectra obtained using short wavelets (dominant frequency 35 Hz); FIG. 1(c) shows an artificially synthesized seismic record and corresponding amplitude spectra obtained using a long wavelet (dominant frequency 35Hz), i.e., FIG. 1(b) and FIG. 1(c) have the same dominant frequency but different wavelet wavelengths. As shown in FIG. 1(b), in the short wavelet synthesis record, because the wavelet length is short enough, all the reflected wavelets at the sand body interface do not interfere with each other, the top and bottom reflection of the sand body can be clearly defined, and even the reflection of the top interface of the sand body 3 with very weak reflection can be clearly seen. In the long wavelet synthesis record, as shown in fig. 1(c), since the wavelet length is too long, the reflected wavelets at the interface of "sand 2" and "sand 3" interfere with each other, and the positions and polarities of the top and bottom reflections of the sand cannot be defined.
FIG. 2(a) is a reflection coefficient and corresponding amplitude spectrum of a thin sand reservoir geological model; FIG. 2(b) is an artificially synthesized seismic record and corresponding amplitude spectrum obtained using short wavelets (dominant frequency 30 Hz); fig. 2(c) shows an artificially synthesized seismic record and a corresponding amplitude spectrum obtained by using a long wavelet (dominant frequency of 15Hz), that is, the wavelets in fig. 2(a) and fig. 2(b) have different wavelengths and dominant frequencies, fig. 2(b) shows a high dominant frequency of a short wavelet, and fig. 2(c) shows a low dominant frequency of a long wavelet. In the wavelet synthesis record with high dominant frequency and short length, all sand interface reflections can be clearly defined because the wavelet length is short enough, as shown in fig. 2 (b). As shown in fig. 2(c), in the wavelet synthesis record with low dominant frequency and long length, because the wavelet length is too long, it cannot be determined whether the reflection characteristic at the "sand 2" is a reaction of wavelet phase change or a reaction of superposition of more than one interface reflection; it is not possible to determine whether one or two reflecting interfaces are present at the "sand body 3".
Defining the seismic data resolution strictly by seismic wavelet length is the most accurate definition method, but is difficult to be effectively applied in actual oil and gas exploration. Due to the complexity of the underground reflection interface and the interference of various noises, the length of the wavelet in the seismic data can not be obtained accurately no matter in a time domain or a frequency domain, and the resolution of the seismic data can not be accurately estimated by using the length of the wavelet. Therefore, strict seismic wavelet lengths are often rarely used to define seismic data resolution.
In the prior art, a plurality of common seismic data resolution definition methods are used. The results of these methods are not completely consistent, but the differences are not large. In actual production, the most intuitive and most convenient resolution definition method should have the following two methods, both of which have the characteristics of intuition and convenience in use, and become the most used and frequently used method for people.
Dominant frequency definition method based on time domain waveform characteristics
Sine waves are generally characterized by wavelength, period, and frequency, but seismic wavelets differ from sine waves by not having a single constant wavelength, period, and frequency. In oil and gas seismic exploration, the characteristics of seismic wavelets are described by adopting a dominant wavelength (also called apparent wavelength), a dominant period (also called apparent period) and a dominant frequency (also called apparent frequency) according to a sine wave definition mode. Generally defining the time interval of adjacent peaks (or valleys) in a wavelet waveform as a dominant period TbThe reciprocal of which is called the main frequency fb＝1/Tb. If the velocity v of the seismic wave is known, the dominant wavelength is obtained
λb＝vTb＝v/fb， (1)
The dominant wavelength, dominant period, and dominant frequency are actually reflections of the frequency components that play a major role in seismic wavelets.
In actual production, people are used to firstly obtain the main frequency of seismic wavelets (namely seismic data), then calculate the main period or main wavelength of the seismic wavelets, and estimate the resolution of the seismic data. The resolution can be expressed as thickness or length of time. It is believed that adjacent reflected wavelets are separated by a time greater than or equal to one-half of the dominant period and are considered resolvable. Since the seismic data records the two-way travel time of the reflection wavelet, the time resolution is Tr：
Tr＝(Tb/2)/2＝Tb/4＝1/(4fb)。 (2)
Second, mean center frequency definition method based on frequency domain spectrum characteristics
First, an average center frequency f is definedmThe frequency at the boundary 1/2 of the area encompassed by the amplitude spectrum curve. Namely, the amplitude spectrum of the amplitude spectrum curve is set as a (f), and the area included in the curve is A:
wherein f isl、fhRespectively the low and high cut-off frequencies of the amplitude spectrum.
Average center frequency fmTo satisfy the frequency of the following equation:
as known to those skilled in the art, the upper and lower integral limits in equations (3) and (4) may be adjusted according to the actual conditions of the seismic data (such as signal-to-noise ratio) to reduce interference from other factors and improve estimation accuracy.
F can be obtained in the same way as the main frequency definition method for calculating the resolutionmCorresponding main period TbAnd temporal resolution Tr。
Tb＝1/fm，Tr＝1/(4fm)。 (5)
The mean center frequency definition method is based on the amplitude values of all frequency components, is slightly influenced by the amplitude value of a single frequency, and is a relatively robust calculation method. The method has the advantages of easy calculation, very close calculation result to the main frequency definition method, and convenient use.
FIG. 3(a) is a schematic diagram of a dominant frequency method for estimating the dominant period Tb20ms, main frequency fb50Hz, time resolution Tr10 ms; FIG. 3(b) is a schematic diagram of an estimation method by the mean center frequency method, wherein the mean center frequency fm50Hz, main period Tb20ms, time resolution Tr10 ms. As shown, the results of both methods are completely consistent when the amplitude spectrum curves of the sub-waves are completely symmetric about the average center frequency.
However, further analysis can find that the shape of the wavelet amplitude spectrum curve (such as effective frequency bandwidth of the wavelet) is directly related to the time length of the wavelet, and the resolution of the wavelet can be accurately reflected; the dominant frequency and the average center frequency mainly reflect the width degree of the wave crest or the wave trough of the wavelet, have no direct relation with the length of the wavelet, and cannot really reflect the resolution of the wavelet. Thus, in some cases, it is not reliable to evaluate the resolution of seismic data using existing techniques such as dominant frequency definition and mean center frequency definition.
FIG. 4(a) is a waveform of a wavelet with a dominant frequency of 50Hz and its amplitude spectrum; FIG. 4(b) shows the waveform and amplitude spectrum of the wavelet with the same time length as FIG. 4(a) but with the main frequency of 100Hz, and the amplitude spectrum of the wavelet with the main frequency of 100Hz is equivalent to shifting the amplitude spectrum of the wavelet with the main frequency of 50Hz by 50Hz, so that the two wavelets have the same shape of the amplitude spectrum curve and the same effective frequency bandwidth, i.e. the same time length. As is well known to those skilled in the art, the same length of time, the exact resolution of the two wavelets should be the same. No matter a dominant frequency definition method or an average center frequency definition method is adopted, the resolution of two wavelets obtained by calculation is doubled, a large error exists, the real situation of seismic data cannot be reflected, and great uncertainty is brought to the evaluation of the quality of the seismic data.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a method capable of reliably evaluating seismic data and a corresponding device.
According to an aspect of the present invention, a method for calculating equivalent dominant frequency of seismic data is provided, the method comprising: obtaining an amplitude spectrum a (f) of the seismic wavelet; determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fppeak frequency, f, corresponding to the maximum of the amplitude spectrum a (f)esIs based onDetermining an equivalent starting frequency; based on equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
According to another aspect of the invention, in case the amplitude spectrum a (f) is completely or substantially symmetric with respect to the mean center frequency, the equivalent dominant frequency f may be determined byeb：Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f).
According to another aspect of the invention, the equivalent dominant frequency f may be determined byeb：feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onThe determined equivalent starting frequency.
According to another aspect of the invention, the equivalent dominant frequency f may be determined byeb：feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f).
According to one aspect of the invention, seismic data equivalent dominant frequency calculation is providedAn apparatus, the apparatus comprising: an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet; an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fppeak frequency, f, corresponding to the maximum of the amplitude spectrum a (f)esIs based onDetermining an equivalent starting frequency; a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
According to another aspect of the invention, in case the amplitude spectrum a (f) is completely or substantially symmetric with respect to the average center frequency, the equivalent dominant frequency obtaining unit may determine the equivalent dominant frequency f byeb：Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f).
According to an aspect of the invention, the equivalent dominant frequency obtaining unit may determine the equivalent dominant frequency f by the following formulaeb：feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onThe determined equivalent starting frequency.
According to another aspect of the present invention, the equivalent dominant frequency obtaining unit may determine the equivalent dominant frequency f by the following equationeb：feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f).
Aspects of the invention can obtain a reliable and deterministic evaluation result by obtaining an equivalent dominant frequency directly related to the time length of the seismic wavelet and evaluating the quality of the seismic data based on the equivalent dominant frequency. The calculation analysis results of the theoretical model and the actual seismic data also show that the equivalent main frequency is a parameter capable of accurately reflecting the real resolution of the seismic data, and the resolution capability of the seismic data on the underground geologic body can be completely represented. Furthermore, the calculation and the use of the equivalent dominant frequency are concise and intuitive, and the equivalent dominant frequency is a convenient and practical quality measurement parameter.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
FIG. 1(a) shows the reflection coefficient and corresponding amplitude spectra of a thin sand reservoir geological model; FIG. 1(b) shows an artificially synthesized seismic record and corresponding amplitude spectra obtained using short wavelets (dominant frequency 35 Hz); FIG. 1(c) shows an artificially synthesized seismic record and the corresponding amplitude spectrum obtained using a long wavelet (dominant frequency 35 Hz).
FIG. 2(a) shows the reflection coefficient and corresponding amplitude spectra for a thin sand reservoir geological model; FIG. 2(b) shows an artificially synthesized seismic record and corresponding amplitude spectra obtained using short wavelets (dominant frequency 30 Hz); figure 2(c) shows an artificially synthesized seismic record and the corresponding amplitude spectrum obtained using a long wavelet (dominant frequency 15 Hz).
FIG. 3(a) is a schematic diagram of a dominant frequency method estimation method; fig. 3(b) is a schematic diagram of an estimation method by the mean center frequency method.
FIG. 4(a) is a waveform of a wavelet with a dominant frequency of 50Hz and its amplitude spectrum; FIG. 4(b) shows the waveform and amplitude spectrum of a wavelet with the same time length as FIG. 4(a) but with a dominant frequency of 100 Hz.
FIG. 5(a) shows wavelet shapes with side lobes and amplitude spectra; fig. 5(b) is a waveform and amplitude spectrum curve of wavelets without side lobes having the same time length.
Fig. 6(a) to (c) show schematic diagrams of obtaining the adjusted amplitude spectrum curve a' (f).
FIG. 7(a) is a time domain waveform diagram of a bandpass theoretical wavelet with a dominant frequency of 25 Hz; FIG. 7(b) is an amplitude spectrum curve a (f) of the sub-wave shown in FIG. 7 (a); FIG. 7(c) shows an amplitude spectrum curve a' (f); FIG. 7(d) is a time domain wavelet corresponding to the amplitude spectrum curve a' (f), with an equivalent dominant frequency of 13 Hz; FIG. 7(e) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 7 (a); FIG. 7(f) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 7 (d).
FIG. 8(a) is a time domain waveform diagram of a bandpass theoretical wavelet with a dominant frequency of 25 Hz; FIG. 8(b) is an amplitude spectrum curve a (f) of the wavelet shown in FIG. 8 (a); FIG. 8(c) shows an amplitude spectrum curve a' (f); FIG. 8(d) is a time domain wavelet corresponding to the amplitude spectrum curve a' (f), with an equivalent dominant frequency of 13 Hz; FIG. 8(e) is a synthetic seismic record of the wavelet-generated wedge geologic model shown in FIG. 8 (a); FIG. 8(f) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 8 (d).
FIGS. 9(a), (b) and (c) show seismic data for a channel sand hydrocarbon reservoir at different seismic wavelets, respectively.
FIGS. 10(a), (b) and (c) show seismic data for an address anomaly formation under different seismic wavelets, respectively.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Here, the basic principle related to the present invention will be described.
The inventor researches and discovers that two factors influence the wavelet length: the width of the wave crest and the wave trough is first; second, the number of wave crests and wave troughs. It is common practice to refer to peaks and troughs other than the main peak and the main trough as side lobes, and the absence of low frequency components is the cause of the side lobes generated by the wavelets. In the prior art, the main frequency or average central frequency for evaluating the seismic data quality mainly reflects the widths of wave crests and wave troughs of wavelets, but cannot reflect the numbers of the wave crests and the wave troughs. This is the root cause of large error in the calculation result.
If the wavelet waveform only has one peak, the influence factor of the number of the peaks and the troughs can be eliminated, and a direct relation can be established between the wavelet time length and the dominant frequency (or average central frequency). Such a dominant frequency (or average center frequency) may accurately describe the resolution of the seismic data.
FIG. 5(a) shows wavelet shapes with side lobes and amplitude spectra; fig. 5(b) is a waveform and amplitude spectrum curve of wavelets without side lobes having the same time length. One characteristic of wavelets with side lobes is that their low-frequency components are missing, the wavelet dominant frequency (or average center frequency) has no direct relation with the wavelet time length, and cannot reflect a strict resolution. The wavelet without side lobes is characterized in that low-frequency components are not lost, only a single main lobe is provided, the width of a wave peak is the length of the wavelet, and the main frequency (or average central frequency) directly determines the width of the wave peak and also determines the length of the wavelet. Therefore, the dominant frequency (or average center frequency) of the sidelobe-free wavelet is directly related to the wavelet length, and the strict resolution of the wavelet can be completely reflected.
According to the respective amplitude spectrum curve characteristics of wavelets with side lobes and wavelets without side lobes, the equivalent main frequency f of the seismic wavelets can be obtained through the following thoughteb。
First, an equivalent start frequency f can be definedes. The wavelet amplitude spectrum curve is relatively smooth after being subjected to proper smoothing treatment, and the peak frequency corresponding to the maximum value (usually 1) is fp. A frequency f satisfying the following condition can be definedesEquivalent start frequency: as shown in FIG. 6(a), if the frequency fesF is equal in area between the region (1) and the region (2) divided by the vertical lineesMay be referred to as the effective start frequency, i.e.:
to obtain fesThereafter, the amplitude spectrum curve a (f) may be shifted to the left by fesThe new amplitude spectrum curve shown in fig. 6(b) is obtained. In the graph shown in FIG. 6(b), from-fesThe frequency component to 0Hz is physically unachievable and has no physical significance. From fesAs can be seen from the definition of (1), the areas of the regions (1) and (2) are equal. Therefore, it is considered that the area of the region (2) is moved and filled into the area of the region (1), and the adjusted amplitude spectrum curve a' (f) shown in fig. 6(c) can be obtained, and the above-mentioned process can be used to find that
Similar to equation (4), the equivalent average center dominant frequency f can be obtained byem：
Considering that it is difficult to obtain the main frequency of a' (f) in the time domain and considering the use habit of people in actual production, the frequency f can be directly usedemAs equivalent dominant frequency febThe equivalent dominant frequency f can be obtained by the following formulaeb：
From equivalent dominant frequency febThe equivalent dominant frequency f can be known by the calculation methodebDirectly related to the wavelet time length. Theoretically, equivalent dominant frequency febThe same wavelet has the same wavelet length and the same time resolution. Equivalent dominant frequency febThe method meets the strict definition requirement of resolution and can truly reflect the resolution of the seismic data.
The strict equivalent dominant frequency f is defined aboveeb. In actual production, the calculation method thereof can be appropriately adjusted, and a significant reduction in the calculation amount is obtained at the expense of a small calculation accuracy.
On the basis of the inventive concept described above, it can be found that when the amplitude spectrum curve is completely or substantially symmetrical with respect to the mean center frequency (see definition of equation (4)), a very compact equivalent main frequency f can be obtained as followsebThe approximate calculation formula of (c):
wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f). The effective bandwidth is a commonly used concept in practical applications, and as known to those skilled in the art, the frequencies of the half-width points at the low and high frequency ends are respectively defined as the initial effective frequency fvlAnd terminating the effective frequency fvh。
The inventor has proved thatIn general, the equivalent dominant frequency febCan be approximately expressed as a main frequency fb(see dominant frequency f defined in dominant frequency definition methodb) With an equivalent starting frequency fesThe difference of (a) to (b), namely:
feb＝fb-fes。 (10)
in practice, moreover, the starting effective frequency fvlAnd the equivalent starting frequency f defined hereinbeforeesUsually very closely, by fvlIn place of fesThe introduced error is very small, and the precision requirement of most practical data can be met, so that the equivalent main frequency f can be obtained by the following formulaeb：
feb＝fb-fvl。 (11)
Example 1
According to one embodiment of the invention, a method for calculating equivalent dominant frequency of seismic data is disclosed, which comprises the following steps:
step 101, obtaining an amplitude spectrum a (f) of the seismic wavelet;
step 102, determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fppeak frequency, f, corresponding to the maximum of the amplitude spectrum a (f)esIs based onDetermining an equivalent starting frequency;
103, based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
In the above embodiment, a reliable and deterministic evaluation result can be obtained by obtaining an equivalent dominant frequency directly related to the time length of the seismic wavelet and evaluating the quality of the seismic data based on the equivalent dominant frequency. The beneficial technical effects of the present invention have been explained in detail above from the theoretical point of view, and the following two examples will further demonstrate the beneficial technical effects of the present invention from the point of view of practical data experiments.
FIG. 7(a) is a time domain waveform diagram of a bandpass theoretical wavelet with a dominant frequency of 25 Hz; FIG. 7(b) is an amplitude spectrum curve a (f) of the sub-wave shown in FIG. 7 (a); FIG. 7(c) shows an amplitude spectrum curve a' (f); FIG. 7(d) is a time domain wavelet corresponding to the amplitude spectrum curve a' (f), with an equivalent dominant frequency of 13 Hz; FIG. 7(e) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 7 (a); FIG. 7(f) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 7 (d). Comparing fig. 7(e) and (f), it can be seen that the synthetic recordings of the two wavelets are very close to the resolution of the wedge geologic volume, with the different wavelets of the same equivalent dominant frequency having very close resolutions.
FIG. 8(a) is a time domain waveform diagram of a bandpass theoretical wavelet with a dominant frequency of 25 Hz; FIG. 8(b) is an amplitude spectrum curve a (f) of the wavelet shown in FIG. 8 (a); FIG. 8(c) shows an amplitude spectrum curve a' (f); FIG. 8(d) is a time domain wavelet corresponding to the amplitude spectrum curve a' (f), with an equivalent dominant frequency of 13 Hz; FIG. 8(e) is a synthetic seismic record of the wavelet-generated wedge geologic model shown in FIG. 8 (a); FIG. 8(f) is a synthetic seismic record of the wedge geologic model generated by the wavelets shown in FIG. 8 (d). Comparing fig. 8(e) and (f), it can be seen that the synthetic recordings of the two wavelets are very close to the resolution of the wedge geologic volume, with the different wavelets of the same equivalent dominant frequency having very close resolutions.
Example 2
According to one embodiment of the invention, a method for calculating equivalent dominant frequency of seismic data is disclosed, which comprises the following steps:
step 201, obtaining an amplitude spectrum a (f) of the seismic wavelet, wherein the amplitude spectrum a (f) is completely symmetrical or substantially symmetrical about an average center frequency;
step 202, determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：
Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f);
step 203, based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 3
According to one embodiment of the invention, a method for calculating equivalent dominant frequency of seismic data is disclosed, which comprises the following steps:
step 301, obtaining an amplitude spectrum a (f) of the seismic wavelet;
step 302, determining an equivalent dominant frequency f of said seismic wavelets based on said amplitude spectra a (f)eb：
feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onDetermining an equivalent starting frequency;
step 303, based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 4
According to one embodiment of the invention, a method for calculating equivalent dominant frequency of seismic data is disclosed, which comprises the following steps:
step 401, obtaining an amplitude spectrum a (f) of the seismic wavelet;
step 402, determining an equivalent dominant frequency f of said seismic wavelets based on said amplitude spectra a (f)eb：
feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f);
step 403, based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 5
According to an embodiment of the invention, an apparatus for seismic data equivalent dominant frequency calculation is disclosed, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fppeak frequency, f, corresponding to the maximum of the amplitude spectrum a (f)esIs based onDetermining an equivalent starting frequency;
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 6
According to an embodiment of the invention, an apparatus for seismic data equivalent dominant frequency calculation is disclosed, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet, wherein the amplitude spectrum a (f) is completely or substantially symmetric with respect to an average center frequency;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f);
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 7
According to an embodiment of the invention, an apparatus for seismic data equivalent dominant frequency calculation is disclosed, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onDetermining an equivalent starting frequency;
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Example 8
According to an embodiment of the invention, an apparatus for seismic data equivalent dominant frequency calculation is disclosed, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f);
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
Application example
To facilitate understanding of the solution of the embodiments of the present invention and the effects thereof, a specific application example is given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.
FIGS. 9(a), (b) and (c) show seismic data for a channel sand hydrocarbon reservoir at different seismic wavelets, respectively. Table 1 is a comparative listing of seismic data dominant frequencies and equivalent dominant frequencies for each of fig. 9(a), (b), and (c).
TABLE 1 earthquake data dominant frequency and equivalent dominant frequency comparison table
The dominant frequency of the data of fig. 9(a) is not the highest, but the equivalent dominant frequency is the highest, and the resolution is the highest. In the data, the shape and the boundary of the river sand body are the clearest (indicated by an ellipse), and the geological interface reflection indicated by an arrow is also clear and easy to track.
The dominant frequency and equivalent dominant frequency of the data in FIG. 9(b) are both low, and the resolution is relatively low. In the data, the shape and boundary of the river sand body cannot be identified (indicated by an ellipse), but the geological interface reflection indicated by a red arrow is clear and easy to track.
FIG. 9(c) shows the highest dominant frequency, the lowest equivalent dominant frequency and the lowest resolution. In the data, the shape and the boundary of the river sand body are difficult to identify (marked by an ellipse), and the geological interface reflection indicated by an arrow is not clear and is difficult to track.
FIGS. 10(a), (b) and (c) show seismic data for an address anomaly formation under different seismic wavelets, respectively. Table 2 is a comparative listing of seismic data dominant frequencies and equivalent dominant frequencies for each of fig. 10(a), (b), and (c).
TABLE 2 earthquake data dominant frequency and equivalent dominant frequency comparison table
The dominant frequency of the data of fig. 10(a) is not the highest, but the equivalent dominant frequency is the highest, and the resolution is the highest. In the data, the morphology of the geological anomaly is the clearest (indicated by the ellipse), and the geological interface reflections indicated by the arrows are also clear and easy to track.
The dominant frequency, equivalent dominant frequency of the data of fig. 10(b) are both low, and the resolution is relatively low. In this data, geological anomalies cannot be identified (indicated by the ellipse), geological interface reflections indicated by the arrows can be tracked, but the interface locations cannot be realized.
FIG. 10(c) shows the highest dominant frequency, the lowest equivalent dominant frequency and the lowest resolution. In this data, geological anomalies are not identifiable (at the oval markers) and geological interface reflections indicated by the arrows are difficult to track.
The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present invention may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. A method of seismic data equivalent dominant frequency calculation, the method comprising:
obtaining an amplitude spectrum a (f) of the seismic wavelet;
determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：
Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fppeak frequency, f, corresponding to the maximum of the amplitude spectrum a (f)esIs based onDetermining an equivalent starting frequency;
based on equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
2. A method of seismic data equivalent dominant frequency calculation, the method comprising:
obtaining an amplitude spectrum a (f) of the seismic wavelet, wherein the amplitude spectrum a (f) is completely or substantially symmetric about an average center frequency;
determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：
Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f);
based on equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
3. A method of seismic data equivalent dominant frequency calculation, the method comprising:
obtaining an amplitude spectrum a (f) of the seismic wavelet;
determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：
feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onDetermined equivalent starting frequency, flIs the low cut-off frequency, f, of the amplitude spectrum a (f)pPeak frequencies corresponding to maxima of the amplitude spectrum a (f);
based on equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
4. A method of seismic data equivalent dominant frequency calculation, the method comprising:
obtaining an amplitude spectrum a (f) of the seismic wavelet;
determining an equivalent dominant frequency f of the seismic wavelets based on the amplitude spectrum a (f)eb：
feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f);
based on equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
5. An apparatus for seismic data equivalent dominant frequency calculation, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
Wherein,flis the low cut-off frequency, f, of the amplitude spectrum a (f)hThe high cut-off frequency of the amplitude spectrum a (f),fpcorresponding to the maximum value of the amplitude spectrum a (f)Peak frequency of fesIs based onDetermining an equivalent starting frequency;
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
6. An apparatus for seismic data equivalent dominant frequency calculation, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet, wherein the amplitude spectrum a (f) is completely or substantially symmetric with respect to an average center frequency;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
Wherein f isvhIs the effective frequency of termination, f, of the amplitude spectrum a (f)vlIs the starting effective frequency of the amplitude spectrum a (f);
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
7. An apparatus for seismic data equivalent dominant frequency calculation, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
feb＝fb-fesWherein f isbIs the main frequency of the amplitude spectrum a (f), fesIs based onDetermined equivalent starting frequency, flIs the low cut-off frequency, f, of the amplitude spectrum a (f)pPeak frequencies corresponding to maxima of the amplitude spectrum a (f);
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
8. An apparatus for seismic data equivalent dominant frequency calculation, the apparatus comprising:
an amplitude spectrum acquisition unit for obtaining an amplitude spectrum a (f) of the seismic wavelet;
an equivalent dominant frequency obtaining unit for determining an equivalent dominant frequency f of the seismic wavelet based on the amplitude spectrum a (f)eb：
feb＝fb-fvlWherein f isbIs the main frequency of the amplitude spectrum a (f), fvlIs the starting effective frequency of the amplitude spectrum a (f);
a seismic data quality evaluation unit for evaluating the quality of seismic data based on the equivalent dominant frequency febThe higher the quality, the higher the quality of the seismic data.
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