CN109991661B - Oil gas detection method and device - Google Patents
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Abstract
The embodiment of the application provides an oil-gas detection method and device, by calculating the time-frequency energy difference of a near offset signal and a far offset signal in each seismic channel signal of pre-stack seismic data and detecting the oil-gas content of a target geological formation of a corresponding detection work area based on the time-frequency energy difference, the weak change of seismic signals caused by an oil-gas reservoir is highlighted, and the oil-gas content of the reservoir can be identified more accurately.
Description
Technical Field
The application relates to the field of geophysical reservoir oil and gas detection, in particular to an oil and gas detection method and device.
Background
In the field of geophysical data-based hydrocarbon testing, pre-stack seismic data are increasingly used, but the information obtained and used from the pre-stack seismic data is currently very limited.
For example, at present, prestack AVO (amplitude variation with offset) inversion is usually adopted to obtain various prestack information such as elastic parameters, poisson ratio, intercept and the like, and this way, the difference of seismic signals in different offset gathers (or angle gathers) is utilized, and more reflects the difference of the amplitudes of the seismic signals. However, the difference in amplitude of the transmitted seismic signals caused by both the hydrocarbon-bearing and hydrocarbon-free reservoirs is very weak, and therefore, it is difficult to accurately detect whether the reservoirs are hydrocarbon-bearing by the difference in amplitude alone.
Disclosure of Invention
In order to overcome at least the above-mentioned shortcomings in the prior art, an object of the present application is to provide a method and an apparatus for hydrocarbon detection, so as to detect the hydrocarbon content of a reservoir more accurately.
In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:
in a first aspect, an embodiment of the present application provides a method for hydrocarbon detection, the method including:
acquiring pre-stack seismic data of a detection work area;
respectively acquiring seismic wave signals with the offset distance in a first specified range and seismic wave signals with the offset distance in a second specified range from a common depth point CDP gather corresponding to the seismic channel signals aiming at each seismic channel signal in the pre-stack seismic data;
superposing the seismic wave signals with the offset distance in a first specified range to obtain near offset distance signals, and superposing the seismic wave signals with the offset distance in a second specified range to obtain far offset distance signals;
calculating a time-frequency energy difference according to the near offset signal and the far offset signal;
and detecting whether the target geological formation of the detection work area contains oil gas or not according to the time-frequency energy difference.
In a second aspect, an embodiment of the present application further provides an oil and gas detection device, the device includes:
the data acquisition module is used for acquiring pre-stack seismic data of the detection work area;
a signal acquisition module, configured to acquire, for each seismic trace signal in the pre-stack seismic data, a seismic wave signal with an offset distance in a first specified range and a seismic wave signal with an offset distance in a second specified range from a common depth point CDP gather corresponding to the seismic trace signal;
the signal superposition module is used for superposing the seismic wave signals with the offset distance in a first specified range to obtain near offset distance signals and superposing the seismic wave signals with the offset distance in a second specified range to obtain far offset distance signals;
the calculation module is used for calculating a time-frequency energy difference according to the near offset signal and the far offset signal;
and the detection module is used for detecting whether the target geological formation of the detection work area contains oil gas or not according to the time-frequency energy difference.
Compared with the prior art, the method has the following beneficial effects:
according to the oil-gas detection method and device provided by the embodiment of the application, the time-frequency energy difference of the near offset signal and the far offset signal in each seismic channel signal of the pre-stack seismic data is calculated, and the oil-gas content of the target geological formation of the corresponding detection work area is detected based on the time-frequency energy difference, so that the weak change of the seismic signals caused by an oil-gas reservoir is highlighted, and the oil-gas content of the reservoir can be identified more accurately.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic block diagram of a data processing apparatus according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a hydrocarbon testing method provided in an embodiment of the present application;
FIG. 3 is a schematic illustration of a CDP gather according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of the substeps of step 24 of FIG. 2;
FIG. 5 is a schematic representation of a through-well near-offset seismic profile of well A in one example provided by the present embodiment;
FIG. 6 is a schematic cross-well offset seismic profile of well A provided in this embodiment;
fig. 7(a) to (d) are time-frequency spectrograms of the related signals of the well a calculated by the oil-gas detection method provided in this embodiment;
fig. 8(a) to (d) are time-frequency spectrograms of the related signals of the well B calculated by the oil-gas detection method provided in this embodiment;
fig. 9(a) to (d) are time-frequency spectrograms of the related signals of the well C calculated by the oil-gas detection method provided in this embodiment;
FIG. 10 is a schematic diagram of the time-frequency energy difference of the cross-well profile calculated by the oil-gas detection method provided in this embodiment;
FIG. 11 is a schematic diagram of a time-frequency energy difference calculated along a geological formation T2 and calculated by using the hydrocarbon detection method provided by this embodiment;
FIG. 12 is a schematic diagram illustrating the amplitude characteristics of the near offset signal calculated along the geological formation T2 using the hydrocarbon testing method provided in this embodiment;
FIG. 13 is a schematic diagram of the amplitude signature of the far offset signal calculated along the geological formation T2 using the hydrocarbon testing method provided in this embodiment;
fig. 14 is a functional block diagram of an oil and gas detection device provided in this embodiment.
Icon: 100-a data processing device; 110-a processor; 120-a machine-readable storage medium; 130-system bus; 200-an oil and gas detection device; 210-a data acquisition module; 220-a signal acquisition module; 230-a signal superposition module; 240-a calculation module; 250-detection module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, 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 some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Referring to fig. 1, fig. 1 is a block diagram of a data processing apparatus 100 according to an embodiment of the present disclosure. The data processing device 100 may be a server, a Personal Computer (PC) or any other electronic device having a data processing function.
The data processing device 100 includes a processor 110 and a machine-readable storage medium 120, the processor 110 and the machine-readable storage medium 120 being in data communication via a system bus 130. The hydrocarbon detection methods described below may be implemented by reading and executing instructions in the machine-readable storage medium 120 corresponding to the hydrocarbon detection logic.
In the present embodiment, the machine-readable storage medium 120 may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the machine-readable storage medium may be: a RAM (random Access Memory), a volatile Memory, a non-volatile Memory, a flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., a compact disk, a DVD, etc.), or similar storage medium, or a combination thereof.
It should be understood that the configuration shown in FIG. 1 is merely illustrative, and that data processing apparatus 100 may have more or fewer components than shown in FIG. 1, or a configuration that is completely different from that shown in FIG. 1.
In order to more accurately detect the oil and gas content of the geological reservoir, the embodiment provides an oil and gas detection method and device based on time-frequency energy difference, so that the difference of frequency domains of seismic signals generated by the oil and gas content of the reservoir can be better described through the time-frequency energy difference, and the oil and gas content of the geological reservoir can be detected based on the difference. This is described in detail below.
Referring to fig. 2, a schematic flow chart of an oil and gas detection method according to an embodiment of the present application is shown, where the method can be applied to the data processing apparatus 100 shown in fig. 1. The individual steps of the method are described below.
And step 21, acquiring pre-stack seismic data of the detection work area.
In practice, the prestack seismic data may be processed to obtain a plurality of seismic signals.
Wherein the corresponding tracks having a common depth reflection point constitute a common depth point (or common reflection point) gather. In other words, the seismic signals obtained in step 21 may belong to more than one CDP gather, and each CDP gather includes several seismic signals with different offsets.
In practical applications, the seismic signals in a CDP gather are usually superimposed to obtain a seismic trace signal, or three seismic signals with different offsets are extracted from a CDP gather for prestack inversion.
In practice, a near offset range (which may serve as the first specified range) and a far offset range (which may serve as the second specified range) may be determined from the CDP gather based on actual seismic profile characteristics and survey requirements. Specifically, in determining the first specified range and the second specified range, it is possible to preferentially select an offset range to which the offset of the seismic wave signal, which has a significant characteristic and is substantially horizontal on the time axis, has no clutter noise at the near end, and has no significant distortion at the far end, belongs. For example, the offset range of 200 meters to 900 meters in the CDP trace set shown in FIG. 3 may be determined as the first designated range and the range of 900 meters to 1800 meters may be determined as the second designated range according to this condition.
After the first designated range and the second designated range are determined, seismic signals with offset distances within the first designated range and seismic signals with offset distances within the second designated range may be extracted from the CDP gather, respectively.
And 23, superposing the seismic wave signals with the offset distance in the first specified range to obtain near offset distance signals, and superposing the seismic wave signals with the offset distance in the second specified range to obtain far offset distance signals.
The near offset signal is a signal obtained by superimposing all seismic wave signals having the offset in the first predetermined range, which are acquired in step 22. The far offset signal is a signal obtained by superimposing all the seismic wave signals having the offset within the second specified range acquired in step 22.
And 24, calculating the time-frequency energy difference according to the near offset signal and the far offset signal.
Through research, whether the geological reservoir contains oil and gas or not has larger difference on the frequency domain of the seismic wave signals transmitted by the geological reservoir, and particularly, the time-frequency energy difference of the seismic wave signals passing through the geological reservoir can be caused to be larger. Therefore, whether the geological reservoir contains oil gas or not is represented through the time-frequency energy difference, and the oil gas containing performance of the geological reservoir is more conveniently identified.
Optionally, in this embodiment, step 24 may include the steps shown in fig. 4.
And 41, performing time-frequency transformation on the near offset signal to obtain a first time-frequency spectrogram, and performing time-frequency transformation on the far offset signal to obtain a second time-frequency spectrogram.
In consideration of the fact that the generalized S transform has stronger noise immunity and higher resolution than conventional time-frequency analysis methods such as short-time fourier transform, Wigner-Ville distribution, and continuous wavelet transform, the time-frequency transform may be generalized S transform.
Optionally, the time-frequency transform may also be a modified generalized S-transform, whose calculation formula (1) may be as follows:
NGST (tau, f) represents a calculation result of time-frequency transformation, h (t) represents a window function, f represents frequency, t represents time, tau represents time of calculating the center position of the window function, s and r both represent adjusting factors, and s and r both are larger than 0.
The improved generalized S-transform provided by the embodiment has good local time-frequency characteristics, and compared with time-frequency analysis methods of Hilbert transform and conventional short-time Fourier transform, the improved generalized S-transform has better aggregation of time-frequency spectrums on a frequency axis and better resolution on a time axis.
And 42, calculating an energy difference according to the first time-frequency spectrogram and the second time-frequency spectrogram by taking the near offset signal as a reference signal and the far offset signal as a test signal.
In practice, the near offset signal may be used as a reference signal sBZ(t) using the far offset signal as a test signal sT(t) and obtaining reference signals s based on the above formula (1)BZ(t) corresponding first time spectrogram PBZ(t, f) obtaining a test signal sT(t) corresponding second spectrogram PT(t,f)。
Then, for the first time spectrogram PBZ(t, f) and a second time-frequency spectrum PT(t, f) making a difference to obtain the energy difference, namely: said energy difference Δ E (t, f) ═ PT(t,f)-PBZ(t,f)。
And 43, calculating the time-frequency energy difference according to the energy difference.
In detail, in this embodiment, step 43 can be implemented by the following calculation formula:
TFEM(t,f)＝ΔE(t,f)/max(PT(t,f))，
wherein TFEM (t, f) represents the time-frequency energy difference, Δ E (t, f) represents the energy difference, PT(t, f) represents the second spectrogram as a test signal.
It should be noted that, in this embodiment, for CDP gathers corresponding to other seismic trace signals, the foregoing steps 22 to 24 may be adopted to obtain corresponding near offset signals and far offset signals, and further obtain corresponding time-frequency energy differences based on the obtained near offset signals and far offset signals.
And 25, detecting whether the target geological formation of the detection work area contains oil gas or not according to the time-frequency energy difference.
The target geological formation is a predetermined geological formation which may contain oil gas, or a geological formation which has a higher possibility of containing oil gas and is determined by adopting other detection modes in advance.
Optionally, when obtaining the time-frequency energy difference, the data processing device 100 may determine whether the time-frequency energy difference is greater than time-frequency energy differences of other geological layers of the detection work area, and whether the time-frequency energy difference is in a low frequency band, and if the determination result is yes, may determine that the target geological layer contains oil and gas.
The low frequency band is a frequency band below a frequency (namely, a main frequency) corresponding to the strongest amplitude in the seismic signal frequency spectrum.
The oil and gas detection method provided by the embodiment can be suitable for different scenes.
In one example, the hydrocarbon detection method provided by the present embodiments may be used for different wells under test. Referring to fig. 5-7 in combination, fig. 5 shows a near offset signal obtained from well a, and fig. 6 shows a far offset signal obtained from well a. In implementation, the time-frequency conversion is performed on the signal shown in fig. 5 according to the steps shown in fig. 4 to obtain a first time-frequency spectrogram shown in fig. 7(a), and the time-frequency conversion is performed on the signal shown in fig. 6 to obtain a second time-frequency spectrogram shown in fig. 7 (b). Then, a calculation may be performed according to the first time-frequency spectrogram shown in fig. 7(a) and the second time-frequency spectrogram shown in fig. 7(b), so as to obtain the time-frequency energy difference shown in fig. 7 (c). Of course, by calculating the difference between the signals shown in fig. 5 and fig. 6 and then performing time-frequency conversion on the obtained difference signal, a time-frequency diagram of the difference between the near offset signal and the far offset signal shown in fig. 7(d) can be obtained.
As can be seen from fig. 7(c), in the frequency band with time of 1.9s (second) and frequency of 15-30HZ, the time-frequency energy difference of the prestack seismic data changes the most, and through practical tests, the geological formation corresponding to the section of the well a is determined to be an oil production layer, and the daily maximum oil production reaches 57.5 tons.
To better illustrate the effectiveness of the present solution, in one example, seismic signals of well B and well C are processed according to the hydrocarbon detection method provided in the present embodiment. Referring to fig. 8 and 9, fig. 8(a) to 8(d) sequentially show a time-frequency spectrum of a near offset signal (which may serve as a first time-frequency spectrum), a time-frequency spectrum of a far offset signal (which may serve as a second time-frequency spectrum), a spectrum of time-frequency energy difference of the near offset signal and the far offset signal, and a time-frequency spectrum of difference of the near offset signal and the far offset signal obtained from the well B. Fig. 9(a) to 9(d) show, in sequence, a time-frequency spectrum of a near offset signal (which may serve as a first time-frequency spectrum), a time-frequency spectrum of a far offset signal (which may serve as a second time-frequency spectrum), a spectrum of the time-frequency energy difference of the near offset signal and the far offset signal, and a time-frequency spectrum of the difference between the near offset signal and the far offset signal obtained from well C.
As can be seen by comparing fig. 7(c), fig. 8(c) and fig. 9(c), the time-frequency energy difference of the prestack seismic data shown in fig. 7(c) is the largest and is close to the low frequency band; FIG. 8(c) shows that the time-frequency energy difference of the prestack seismic data is smaller than the time-frequency energy difference shown in FIG. 7 (c); the time-frequency energy difference of the prestack seismic data shown in fig. 9(c) is smaller than the time-frequency energy difference shown in fig. 8 (c).
Determining the water production of the well B through an actual drilling test; well C is not shown and the log is interpreted as a dry layer. Therefore, the oil-gas detection method provided by the embodiment can accurately and reliably detect the oil-gas content.
In yet another example, the time-frequency energy difference of all seismic trace signals may be calculated for the cross-well profile, and then the maximum time-frequency energy difference corresponding to each time axis is extracted, such as the calculation result shown in fig. 10, and the black line shown in fig. 10 represents a geological layer T2, which may serve as the target geological layer in this embodiment. It can be seen that the distribution range of the oil-gas in the longitudinal and transverse directions can be clearly distinguished from fig. 10, in other words, the position where the time-frequency energy difference of the pre-stack seismic data changes greatly can be considered to belong to the distribution range of the oil-gas.
In another example, the hydrocarbon detection method provided by this embodiment may be applied to all seismic trace signals of a detection work area, so as to obtain the time-frequency energy difference of the pre-stack seismic data of the whole detection work area. Then, as shown in FIG. 11, the time-frequency energy difference of the prestack seismic data is extracted along the target geological formation (e.g., T2) to be detected. It can be seen that the distribution range of the hydrocarbon-bearing layer can be clearly distinguished in fig. 11. It can also be seen that the wells A, B and C are very different in plan, especially the time-frequency energy difference of the prestack seismic data containing well A is significantly changed, while the amplitude characteristics of the near offset signal and the far offset signal of FIGS. 12 and 13 along the target geological formation T2 are not significantly changed. Therefore, the oil and gas detection method provided by the embodiment can accurately and reliably detect the oil and gas content.
Referring to fig. 14, the present embodiment further provides an oil and gas detection device 200, which can be applied to the data processing apparatus 100 shown in fig. 1. The apparatus includes at least one functional module that can be stored in the form of software in the machine-readable storage medium 120, and the apparatus can be functionally divided into a material acquisition module 210, a signal acquisition module 220, a signal superposition module 230, a calculation module 240, and a detection module 250.
The data acquiring module 210 is configured to acquire pre-stack seismic data of a detection work area.
The signal obtaining module 220 is configured to, for each seismic trace signal in the pre-stack seismic data, obtain, from a common depth point CDP gather corresponding to the seismic trace signal, a seismic wave signal with an offset distance in a first specified range and a seismic wave signal with an offset distance in a second specified range, respectively.
The signal superposition module 230 is configured to superpose the seismic wave signals with the offset distance in the first specified range to obtain a near offset distance signal, and superpose the seismic wave signals with the offset distance in the second specified range to obtain a far offset distance signal.
The calculation module 240 is configured to calculate a time-frequency energy difference according to the near offset signal and the far offset signal.
Optionally, the calculation module 240 may be specifically configured to: performing time-frequency transformation on the near offset signal to obtain a first time-frequency spectrogram, and performing time-frequency transformation on the far offset signal to obtain a second time-frequency spectrogram; calculating an energy difference according to the first time-frequency spectrogram and the second time-frequency spectrogram by taking the near offset signal as a reference signal and the far offset signal as a test signal; and calculating the time-frequency energy difference according to the energy difference.
Optionally, the specific manner of obtaining the time-frequency energy difference according to the energy difference by the calculation module is as follows:
calculating the time-frequency energy difference by the following calculation formula:
TFEM(t,f)＝ΔE(t,f)/max(PT(t,f))，
wherein TFEM (t, f) represents the time-frequency energy difference, Δ E (t, f) represents the energy difference, PT(t, f) represents the second spectrogram as a test signal.
Optionally, the time-frequency transform may be a modified generalized S-transform, which is implemented by the following calculation:
NGST (tau, f) represents a calculation result of time-frequency transformation, h (t) represents a window function, f represents frequency, t represents time, tau represents time of calculating the center position of the window function, s and r both represent adjusting factors, and s and r both are larger than 0.
The detection module 250 is configured to detect whether a target geological formation of the detection work area contains oil and gas according to the time-frequency energy difference.
Optionally, the detection module 250 may be specifically configured to: judging whether the time-frequency energy difference is larger than the time-frequency energy difference of other geological layers of the detection work area or not, and judging whether the time-frequency energy difference is in a low frequency band or not; and if the judgment results are yes, determining that the target geological formation contains oil gas. The low frequency band is a frequency band below a frequency (namely, a main frequency) corresponding to the strongest amplitude in the seismic signal frequency spectrum.
It is worth mentioning that, for the above description of the functional modules, reference may be made to the above detailed description of the relevant steps.
In summary, according to the oil and gas detection method and device provided by the embodiment of the application, the time-frequency energy difference of the near offset signal and the far offset signal in each seismic channel signal of the pre-stack seismic data is calculated, and the oil and gas content of the target geological formation of the corresponding detection work area is detected based on the time-frequency energy difference, so that the weak change of the seismic signal caused by an oil and gas reservoir is highlighted, the oil and gas content of the reservoir can be identified more accurately, and the oil and gas exploration of the detection work area can be guided better.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, 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.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only for various embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and all such changes or substitutions are included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of hydrocarbon testing, the method comprising:
acquiring pre-stack seismic data of a detection work area;
respectively acquiring seismic wave signals with the offset distance in a first specified range and seismic wave signals with the offset distance in a second specified range from a common depth point CDP gather corresponding to the seismic channel signals aiming at each seismic channel signal in the pre-stack seismic data;
superposing the seismic wave signals with the offset distance in a first specified range to obtain near offset distance signals, and superposing the seismic wave signals with the offset distance in a second specified range to obtain far offset distance signals;
calculating a time-frequency energy difference according to the near offset signal and the far offset signal;
and detecting whether the target geological formation of the detection work area contains oil gas or not according to the time-frequency energy difference.
2. The method of claim 1, wherein the step of calculating the time-frequency energy difference from the near offset signal and the far offset signal comprises:
performing time-frequency transformation on the near offset signal to obtain a first time-frequency spectrogram, and performing time-frequency transformation on the far offset signal to obtain a second time-frequency spectrogram;
calculating an energy difference according to the first time-frequency spectrogram and the second time-frequency spectrogram by taking the near offset signal as a reference signal and the far offset signal as a test signal;
and calculating the time-frequency energy difference according to the energy difference.
3. The method according to claim 2, wherein the step of deriving the time-frequency energy difference from the energy difference comprises:
calculating the time-frequency energy difference by the following calculation formula:
TFEM(t,f)＝ΔE(t,f)/max(PT(t,f))，
wherein TFEM (t, f) represents the time-frequency energy difference, Δ E (t, f) represents the energy difference, PT(t, f) represents the second spectrogram as a test signal.
4. The method according to claim 2 or 3, wherein the time-frequency transform is a modified generalized S-transform, and wherein the modified generalized S-transform is implemented by the following calculation:
NGST (tau, f) represents a calculation result of time-frequency transformation, h (t) represents a window function, f represents frequency, t represents time, tau represents time of calculating the center position of the window function, s and r both represent adjusting factors, and s and r both are larger than 0.
5. The method according to any one of claims 1-3, wherein the step of detecting the oil-gas content of the target geological formation of the detection work area according to the time-frequency energy difference comprises:
judging whether the time-frequency energy difference is larger than the time-frequency energy difference of other geological layers of the detection work area or not, and judging whether the time-frequency energy difference is in a low frequency band or not, wherein the low frequency band is a frequency band below a frequency corresponding to the strongest amplitude in a seismic signal frequency spectrum;
and if the judgment results are yes, determining that the target geological formation contains oil gas.
6. An oil and gas detection device, the device comprising:
the data acquisition module is used for acquiring pre-stack seismic data of the detection work area;
a signal acquisition module, configured to acquire, for each seismic trace signal in the pre-stack seismic data, a seismic wave signal with an offset distance in a first specified range and a seismic wave signal with an offset distance in a second specified range from a common depth point CDP gather corresponding to the seismic trace signal;
the signal superposition module is used for superposing the seismic wave signals with the offset distance in a first specified range to obtain near offset distance signals and superposing the seismic wave signals with the offset distance in a second specified range to obtain far offset distance signals;
the calculation module is used for calculating a time-frequency energy difference according to the near offset signal and the far offset signal;
and the detection module is used for detecting whether the target geological formation of the detection work area contains oil gas or not according to the time-frequency energy difference.
7. The apparatus of claim 6, wherein the computing module is specifically configured to:
performing time-frequency transformation on the near offset signal to obtain a first time-frequency spectrogram, and performing time-frequency transformation on the far offset signal to obtain a second time-frequency spectrogram;
calculating an energy difference according to the first time-frequency spectrogram and the second time-frequency spectrogram by taking the near offset signal as a reference signal and the far offset signal as a test signal;
and calculating the time-frequency energy difference according to the energy difference.
8. The apparatus according to claim 7, wherein the specific way for the computing module to obtain the time-frequency energy difference according to the energy difference is as follows:
calculating the time-frequency energy difference by the following calculation formula:
TFEM(t,f)＝ΔE(t,f)/max(PT(t,f))，
wherein TFEM (t, f) represents the time-frequency energy difference, Δ E (t, f) represents the energy difference, PT(t, f) represents the second spectrogram as a test signal.
9. The apparatus according to claim 7 or 8, wherein the time-frequency transform is a modified generalized S-transform, and wherein the modified generalized S-transform is implemented by the following calculation:
NGST (tau, f) represents a calculation result of time-frequency transformation, h (t) represents a window function, f represents frequency, t represents time, tau represents time of calculating the center position of the window function, s and r both represent adjusting factors, and s and r both are larger than 0.
10. The apparatus according to any one of claims 6 to 8, wherein the detection module is specifically configured to:
judging whether the time-frequency energy difference is larger than the time-frequency energy difference of other geological layers of the detection work area or not, and judging whether the time-frequency energy difference is in a low frequency band or not, wherein the low frequency band is a frequency band below a frequency corresponding to the strongest amplitude in a seismic signal frequency spectrum;
and if the judgment results are yes, determining that the target geological formation contains oil gas.
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