CN116931080B - Fluid property detection method based on prestack frequency variation - Google Patents
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Abstract
The invention provides a fluid property detection method based on prestack frequency variation, which is characterized by comprising the following steps of: converting the three-dimensional seismic prestack gather data of the work area into an angle gather, and generating incident angle superposition data according to angle classification; performing time-frequency decomposition according to the incidence angle superposition data, and calculating to obtain time-frequency data; according to the time-frequency data, calculating a relative frequency attenuation coefficient of the incident angle superposition data; predicting a fluid property from the relative frequency attenuation coefficient. The invention solves the problem that the AVO false bright spot or dark spot is difficult to distinguish in the pre-stack reservoir prediction, namely, the fluid property is predicted by the change characteristic of the relative frequency attenuation coefficient along with the frequency and the incident angle due to the different absorption degrees of different fluids on different frequency energy, so as to achieve the purpose of distinguishing different fluids.
Description
Technical Field
The invention relates to the technical field of reservoir oil-gas prediction in petroleum exploration and development, in particular to a fluid property detection method based on prestack frequency variation.
Background
Reservoir fluid property detection is one of the key elements in oil and gas field exploration and development. The exploration of oil and gas fields through AVO anomalies has achieved tremendous success from the eighties of the last century to date, with a high success rate, and has been known as one of the most direct and effective reservoir exploration technologies. At present, hydrocarbon detection methods which are relatively commonly used based on seismic data comprise simultaneous inversion of pre-stack elastic parameters, pre-stack gradient intercept characteristics, pre-stack frequency domain AVO fluid identification, post-stack low-frequency accompanying shadows and the like. However, various reasons for the AVO abnormality are that if the AVO abnormality cannot be effectively discriminated, prediction failure is inevitably caused, and loss is caused. There are many cases of AVO technical failure, and technicians and scholars at home and abroad have made many summaries and methods of exploration to avoid AVO "traps".
Currently, there are three categories of achievements in similar research fields: firstly, detecting oil gas such as Castagna (Instantaneous spectral analysis：detection of low-frequency shadows associated with hydrocarbons：The Leading Edge,2003,VOL.22(2),120-127), Chen Xuehua and the like through a low-frequency shadow left after high frequency caused by oil gas-containing rock is absorbed (numerical simulation and detection of the low-frequency shadow, petroleum geophysical exploration, 2009, vol.44, no. 3); secondly, the frequency-dependent AVA/AVO inversion method developed based on Zeoppritz equation and the approximation thereof is developed, and because the elastic parameter inversion of Zeoppritz equation based on reflection coefficient does not consider frequency information, more uncertainty still exists in fluid identification, so that some scholars develop the frequency-dependent AVO inversion (FAVA) introducing velocity dispersion parameters. Such methods as Wilson, chapman et al (Frequency-dependent AVO inversion,SEG Houston 2009 International Exposition and Annual Meeting,2009),Kumar, (Frequency-dependent AVO analysis using the scattering response of a layered reservoir,Geophysics,2020,VOL.85,NO.2). consider that seismic velocities are frequency dependent, especially when oil and gas are contained in the rock. Therefore, the longitudinal and transverse wave velocity will vary with frequency, and when the rock contains oil and gas, the dispersion will be increased with increasing incidence angle, and thus the velocity will be decreased. Thirdly, a frequency attenuation and dispersion method based on frequency division AVO is used for examining the change of different fluids with different properties on the incidence angles of seismic waves with different frequencies, so that the purpose of distinguishing the fluids is achieved. Such as Chen Xiaohong et al (seismic frequency division AVO method research status and hope, sea-phase oil and gas geology, 2009, vol.14, no. 4).
According to the research results of the Chinese patent information network and the China patent office network, partial related patents and research results, such as Tian Renfei and the like, are found, and an oil gas detection method and device (patent number: CN 109991661A) are provided. The invention mainly calculates the time-frequency energy difference of near and far offset signals, does not convert the offset gather into an angle gather, only uses the time-frequency energy difference briefly as the basis of oil gas detection, and does not further calculate the relative attenuation relation between different frequencies and angles and the different fluid properties represented by the attenuation law.
According to the research of the full-text database of the journal of China, partial related documents and research results, monametric and the like, (scientific technology and engineering, 2016, 16 (7): 139-145.) are found, and aiming at the characteristic of enrichment of coal bed gas of coal-based stratum, the frequency attenuation gradient attribute is applied to the detection of the coal bed gas content of the region. The method utilizes a time-frequency method for decomposing small wave spectrums to effectively extract the main frequency of the seismic signals; the analysis of the absorption and high-frequency attenuation of energy of seismic waves when the seismic waves propagate in the coal seam can effectively indicate the gas content of the coal seam. However, the method only uses the degree of frequency attenuation before far, medium and near-range collection, namely the total energy loss of the high-frequency part, does not consider the low-frequency energy loss or the increased part, and is only accurate to the air layer, and the analysis means are effective but relatively single. Qin Xilin, (university of petroleum, doctor's paper, 2019), is a quantitative feature of the energy attenuation intensity of high frequencies of seismic data according to the frequency attenuation gradient. It is believed that in pore medium reservoirs (sandstone reservoirs), high energy attenuation is generally indicative of hydrocarbon development zones; in fracture medium reservoirs (carbonate reservoirs), high energy decay is typically indicative of fracture-cavity development zones. The frequency attenuation gradient is obtained by determining the change rate of the amplitude spectrum in the high frequency range along with the frequency on the basis of time-frequency analysis. The method examines the attenuation degree of an amplitude spectrum at high frequency, uses two typical high-frequency energy attenuation gradients to represent attenuation frequency speeds, and predicts reservoir development areas according to the differences of attenuation speeds caused by different reservoirs on high-frequency energy. This method is somewhat ambiguous in terms of taking into account the variation of low frequency energy and not taking into account the differences between the spectra of the different incident angle gathers. Li Kun et al, (university of petroleum, university of China (Nature science edition), 2019, 43 (01): 23-32), according to the amplitude attenuation and velocity dispersion phenomena of different degrees which can occur when seismic waves propagate in a hydrocarbon reservoir, the propagation process of the seismic waves in complex media can be better simulated by considering the viscoelasticity of the media, and a frequency-dependent viscoelasticity fluid factor Fω is constructed to quantitatively characterize the dispersion degree caused by pore fluid. Deriving a viscoelastic frequency-dependent AVA (F-AVA) reflection coefficient approximation equation according to Futterman approximation constant Q model, wherein the equation has high coincidence degree with a viscoelastic medium accurate Zoeppritz equation, and systematically ascertains the accuracy of the equation and the feasibility of F-AVA inversion; in addition, continuous wavelet multi-scale spectrum decomposition, bayes estimation framework and prior model regularization are combined, a target functional of the viscoelastic medium pre-stack seismic F-AVA inversion is deduced, and the target functional is optimized by means of a repeated re-weighting least square algorithm. The model and the actual test result verify the noise immunity and the practicability of the inversion method, and compared with the application effect of the conventional dispersion attribute, the inversion result of the frequency-dependent viscoelastic fluid factor Fω has fewer false bright spot interference, and the method can be more effectively applied to reservoir pore fluid identification. The technology introduces Futterman approximate constant Q model in frequency-dependent AVO/AVA prestack seismic inversion, and provides a frequency-dependent viscoelastic fluid factor prediction method based on Bayes F-AVA inversion algorithm. The limiting condition is the accuracy of the prior model and the prior model is difficult to establish in the case of logging without longitudinal and transverse waves, and the limiting condition and other necessary conditions are ideal oil gas detection technology.
Patent and journal literature research shows that with the deep oil and gas exploration and development, the difficulty is increased continuously, the control requirements on exploration risks and cost are increased continuously, and besides the fact that bright spots and dark spots in seismic data are found through AVO technology and quantitative prediction is given, the fluid properties are required to be screened by as much information as possible. Although the AVO technology proves to be very effective, the failed case is also frequent, the fluid property is effectively detected, and the AVO technology has important significance for reducing uncertainty of fluid combined by rock in oil and gas reservoir prediction and reducing risk and cost of exploration and development, and particularly distinguishing different characteristics reflected by oil, gas and water on seismic data.
Disclosure of Invention
Aiming at the technical problems, the technical scheme of the invention provides a prediction method for predicting the oil-gas property of a reservoir by utilizing the frequency change characteristics among data of different prestack incidence angles and distinguishing the fluid properties according to the frequency attenuation differences caused by different fluid properties on the frequencies among data of a far angle gather and a near angle gather.
To achieve the above object, the present invention provides a method for detecting fluid properties based on prestack frequency variation, the method comprising the steps of:
s10, converting three-dimensional seismic prestack gather data of a work area into an angle gather, and generating incident angle superposition data according to angle classification;
S20, performing time-frequency decomposition according to the incidence angle superposition data, and calculating to obtain time-frequency data;
S30, calculating a relative frequency attenuation coefficient of the incident angle superposition data according to the time-frequency data; s40, predicting the fluid property according to the relative frequency attenuation coefficient.
Further, the step S10 includes:
s101, calculating an incident angle of each reflection point according to offset, time and speed in prestack gather data;
S102, classifying the incidence angles, and superposing the angle-dividing track sets of each type of incidence angle to generate the superimposed data of the type of incidence angle.
Further, the step S10 further includes:
S103, carrying out signal-to-noise ratio and spectrum analysis on the incident angle superposition data, and returning to S102 if the signal-to-noise ratio is lower, so as to reduce the number of angle classifications.
Further, in the step S20, time-frequency decomposition is performed through S transformation, where the formula is:
Where h (t) is a time signal, f is a frequency, τ is a time shift amount of the gaussian window, and t is a sampling point.
Further, in the S30, the formula for calculating the relative frequency attenuation coefficient of the incident angle superposition data is:
Wherein, Superimposing the center angle of the data for the incident angle, f is frequency,/>For reflected wave amplitude at frequency f and angle of incidence center of the reflection point,/>For incident wave amplitude,/>For the angle of reflection/>Relative reflection angle/>The relative frequency attenuation coefficient at frequency f, L i is the energy compensation coefficient due to geometric diffusion, ω is the angular frequency of the input.
Further, for sample point t, wave amplitude
Further, the energy compensation coefficient is calculated by statistics of the total near-far channel energy difference of the prestack data.
Further, in S30, the relative frequency attenuation coefficient is a difference between the high-band attenuation coefficient and the low-band attenuation coefficient.
Further, in the S40, the predicting the fluid property includes:
after the well vibration is calibrated, the time spectrum of the known well point is analyzed, and the time-frequency characteristic of drilling fluid is observed as a reference;
Fluid properties may be predicted from typical relative frequency decay factor characteristics of the fluid when the work area is well-free.
Preferably, the three-dimensional seismic pre-stack gather is a CMP gather.
The technical scheme of the invention has the beneficial effects that: the method has the advantages that the part which is not related to the oil gas detection technology by the conventional frequency attenuation method is supplemented, the accuracy of hydrocarbon detection is improved, the uncertainty or the polynosicity of detection is further reduced, and particularly, the urgent requirement of reducing drilling risks due to the fact that uncertainty is reduced in the oil gas detection process of the West Africa marine sandstone deposit reservoir is met, and the risks and the cost of exploration and development are rapidly and effectively reduced in oil gas exploration and development.
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 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 invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for detecting fluid properties based on prestack frequency variation in accordance with an embodiment of the invention;
FIG. 2 is a schematic diagram of frequency attenuation characteristics of different incident angle gather superimposed data for different fluids according to an embodiment of the invention;
FIG. 3 (a) is a schematic cross-sectional view of a near angle gather overlay according to an embodiment of the invention;
FIG. 3 (b) is a schematic cross-sectional view of a far-angle gather overlay according to an embodiment of the present invention;
FIG. 3 (c) is a schematic cross-sectional view of the relative frequency attenuation coefficients according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the RMS near-far angle difference attribute (along the destination layer M1) according to an embodiment of the invention;
fig. 5 is a schematic diagram of the relative frequency attenuation coefficient (along the target layer M1) according to an embodiment of the present invention.
Detailed Description
The invention aims at uncertainty caused by similar AVO anomalies with different fluid properties in hydrocarbon reservoir prediction, calculates the change characteristics of each frequency energy along with the increase of the incident angle according to the difference of the frequency spectrum reflected by the different incident angles of seismic waves when different fluids are contained in the rock, and achieves the purpose of qualitatively predicting the fluid properties through frequency change. The method directly starts from the actually observed pre-stack data, has no well participation, directly detects the change characteristics of different frequency components, then calibrates each characteristic by the well, and can predict the fluid property according to the typical characteristics of different fluids when no well exists, thereby achieving the purpose of fluid detection.
The invention will be further described with reference to the accompanying drawings.
Example 1
As shown in fig. 1, the present invention provides a method for detecting fluid properties based on prestack frequency variation, wherein the fluid properties generally refer to whether oil, gas or water is used, and the method comprises the following steps:
S10, converting the three-dimensional seismic prestack gather data of the work area into an angle gather, and generating incident angle superposition data according to angle classification.
The seismic records may have a wide variety of trace gather patterns, such as CSP co-shot records, CRP co-received point gathers, CDP co-depth point gathers, CMP co-center point gathers.
Typically, the seismic process result data includes CMP gathers, which are gathers of different offsets. In the present invention, offset speeds are used to translate it into different angle of incidence gathers (i.e., angle of incidence gathers).
Sometimes, in order to save storage space or facilitate rapid pre-stack analysis, the processing department may provide data volumes superimposed by 3-5 different angle-of-incidence gathers, but typically the number of the 3-5 angle-of-incidence gathers is far from meeting the requirements, and the signal-to-noise ratio is low, which is not suitable for direct use.
Therefore, in the invention, three-dimensional seismic prestack gather data are converted to form an angle gather, and then superimposed data are generated according to angle classification, namely, a plurality of angle ranges are selected for superposition, specifically:
S101, calculating the incident angle of each reflection point according to different offset distances, time and speeds in the prestack gather data. The gather then switches the angle of incidence field from the offset field.
S102, classifying the incidence angles, and superposing the angle-divided track sets of each type of incidence angle to generate superposition data of the type of incidence angle track sets. For example, the incidence angles in the range of 15-25 degrees are used as a class, and the gathers are superimposed to form medium incidence angle gather superimposed data for subsequent use.
The different angles are classified and then overlapped to improve the signal to noise ratio and reduce the calculation time cost. For example, the incident angle trace set of 0-45 degrees is divided into three partial (near, intermediate, far) stacks, i.e., 0-15, 16-30, 31-45. Normally, the signal to noise ratio of the gather before superposition is lower, and the signal to noise ratio is improved through partial superposition, so that the gather can meet the requirement of use, but can be classified into a plurality of categories, such as 4-5 categories for superposition under the condition that the signal to noise ratio allows, so as to improve the calculation accuracy.
In one embodiment, the method further comprises the steps of performing signal-to-noise ratio and spectrum analysis on the superimposed data of different angles to ensure the feasibility of the seismic data, returning to S102 if the signal-to-noise ratio is low, reducing the number of angle classifications and ensuring a certain signal-to-noise ratio.
A number of formulas for the signal-to-noise ratio estimation may be used, as well as substantially visually resolving the quality of the data. Spectral analysis refers to estimating the signal bandwidth through the spectrum, and if the spectrum bandwidth is small due to data quality problems, the application requirements may not be met.
S20, performing time-frequency decomposition on various incident angle superposition data to obtain time-frequency data of superposition data of different angles. The superimposed data contains superimposed data of different incident angle units, and in the following formula, is input data h (t). The superimposed data of each type of incidence angle gather is used for respectively calculating a time spectrum and reflecting the spectrum characteristic of each time point. The time spectrum is used as an input to calculate the frequency attenuation coefficient in the following equation.
In one embodiment, the S-transform may be used for time-frequency decomposition, with the formula:
Where h (t) is the time signal, f is the frequency, and τ is the amount of time shift of the Gaussian window.
S30, calculating the relative frequency attenuation coefficient of each kind of incident angle superposition data by using the time frequency data calculated by the formula (1) by using the formula (2) with the time frequency data of each channel as an intermediate result.
One sample point corresponds to a certain actual reflection point below the ground, and each trace in the gather data has its corresponding reflection (sample point amplitude) data.
For a certain reflection point in the ground, the reflection angles of the reflection points are different, and the amplitudes of the reflection waves with different frequencies can be expressed asFor a certain sampling point t, a certain angle is superimposed (center angle/>) Amplitude of/> The amplitude of incident waves of different frequencies can be expressed as/>(It is generally assumed that the amplitude of the incident wave of the isotropic medium of the overlying non-reservoir is close, there is only a difference in geometric diffusion energy), between different reflection angles (/ >Relative/>) Relative frequency attenuation coefficient of different frequencies/>Can be expressed as:
The energy compensation coefficient caused by geometrical diffusion is Li, and can be obtained by statistics of total near-far channel energy difference of prestack data, for example, statistics of data amplitude energy of near-angle gather superposition data (L1) and far-angle gather superposition data (L2) of a whole region in a certain time range, and the theoretical amplitude is consistent, but the energy attenuation is caused by spherical diffusion and other reasons, so that the two are inconsistent, and at the moment, the two can be substituted into the formula, otherwise, the two can be ignored.
For the angle of incidence or reflection, ω is the angular frequency and for the input parameter, such as the angular frequency in the range from 1-50Hz, the relative attenuation coefficient at each frequency in this range is obtained.
Each type of incident angle superimposed data, referred to herein as superimposed data at a center angle of a range of angles, such as 30-40 degrees, is reduced to superimposed data at about 35 degrees or at a far angle.
Example two
The invention provides a fluid property detection method based on prestack frequency variation, which comprises the following steps except the step in the first embodiment: s40, predicting the fluid property according to the relative frequency attenuation coefficient.
For the end result, different frequency attenuation characteristics at a certain sampling point or range can be analyzed to distinguish between fluids. For example, in the frequency range of 30-35Hz, the far-angle data energy of the A area is increased (the frequency attenuation is small), and the B area is not, even the frequency attenuation is large, which generally indicates that the fluid properties of the two areas are different, because the absorption of the seismic wave energy is different by the different fluids, and the frequency attenuation characteristics of the far-angle and near-angle superimposed data in the frequency range of 10-15Hz can be observed, so that whether the existence of the fluid has influence on the attenuation coefficient or not can be perceived. For mudstones, the attenuation coefficients of different frequencies are small and can be basically ignored because the inside of the mudstone is almost free of fluid.
In one embodiment, after well vibration calibration, the time spectrum at a known well point is analyzed, and the time-frequency characteristic of drilling fluid is observed as a reference; if the well logging shows that the well is drilled and meets the oil layer, the frequency attenuation condition of the oil layer corresponding to the seismic channel can be observed, the attenuation characteristic is typical oil layer indication, and the area of the characteristic can be found in the whole area to predict the oil layer.
In another embodiment, the characteristics of the changes of the relative frequency attenuation coefficients corresponding to different fluids are calibrated through real drilling, and the fluids with different properties can be predicted through the statistics of the relative frequency attenuation coefficients of a high frequency band or a low frequency band of a certain characteristic frequency, and the extraction of the attributes. In general, when rock is also oil, gas and water, the absorption degree is different at different frequency components, and thus the relative frequency attenuation coefficient is different at different frequency components. When the working area is not provided with a well, the fluid property can be predicted according to the characteristic of typical relative frequency attenuation coefficients of different fluids, so that the purpose of fluid detection is achieved. The attribute is that the attenuation coefficient at each frequency is obtained by the expression (2), for example, the attenuation coefficient of the far angle (assuming a range of about 26-35 degrees) superimposed data in a range of 30-40Hz is averaged, and the attenuation coefficient of the far angle data in a high frequency is the attribute which we want.
Example III
FIG. 2 is a graph showing frequency attenuation characteristics of three-dimensional seismic data of an oil field, superimposed data of different incidence angle gathers, for different fluids. The calculation process is as follows:
1) The prestack CMP gather data is divided into four angle ranges (3-13, 17-27, 30-40, 41-50) by using offset speed to be overlapped to obtain overlapped data of four different incident angle ranges, and the overlapped data are simplified and named by a center angle, namely 8, 22, 35 and 45 degrees respectively Overlapping the data body adjacent to the angle;
2) The four data volumes are respectively subjected to time-frequency analysis by using the formula (1), and only frequency screening characteristics caused by sandstone and mudstone containing different fluids are observed, so that only the side seismic channels of three known wells are selected for analysis, and the typical lithology of the drilling is as follows: air-bearing sandstones (1100 m,1050 ms), water-bearing sandstones (1170 m,1050 ms) and mudstones (900 m,935 ms), the three reflection time positions being each of four spectra obtained on four corner gather superimposed data
3) The value of L 2/L1 was estimated to be about 0.76 according to the method described above,The ratio of (2) is assumed to be about 1, and ω is set to a range of 1 to 100Hz; substituting (2) results in three angles of incidence as a function of the decay index of frequency for three lithologies.
It is obvious that on the far-angle superposition section, the absorption effect of the gas-containing sandstone on the frequency of about 30Hz (the higher the frequency attenuation coefficient is, the more serious the absorption is), and for the low frequency of about 12Hz, the gas-containing sandstone has a certain enhancement effect instead, because the wave impedance difference increases with the increase of the incidence angle, and the low-frequency energy is stronger at the far incidence angle because the gas-containing sandstone absorbs the low frequency weakly. The frequency attenuation characteristics of the water-containing sandstone are opposite, the water-containing sandstone has a certain attenuation effect on low frequency in a far path, and the attenuation is not obvious at high frequency, so that the high-frequency energy of the water-containing sandstone can be enhanced at the far path.
Example IV
The method is applied to the oil-gas property identification of the West African No block delta sandstone, the calculation process is the same as that in the description, the attached figures 3 (a), 3 (b) and 3 (c) are superposition data of different incidence angle gathers and relative frequency attenuation coefficient profiles, the relative attenuation coefficient is obtained by calculating the difference between a high-frequency band average attenuation coefficient and a low-frequency band attenuation coefficient, and from the comparison of the superposition data of a far-near angle gather, the A-E points are enhanced, only the enhancement degree is different, meanwhile, the frequency attenuation is different at each point, but only the reflection on the frequency attenuation coefficient profile is obvious, the part B, E is shown as non-oil-gas sandstone (the high-frequency attenuation degree is low), and the early-stage real drilling K2 is proved to be water sandstone, so that the method is changed into a water injection well.
FIG. 4 is the RMS near-far angle difference attribute along the destination layer M1, according to which the K1 well should be drilled against the main force reservoir, but actually drilled against the sand edge. The amplitude of the difference in the far and near angles of the K2 well RMS is shown as the edge of the oil layer, but the water layer is drilled on the layer, and the situation that the boundary of the oil-bearing layer is exceeded and the oil is not mixed is confirmed. The K3 well is oil-containing sandstone and is consistent with the prediction of the RMS difference amplitude, and the K4 well is outside the boundary of the oil layer, but actually drills into the main oil layer. In fig. 5, the relative frequency decay coefficients show that each well is in line, especially the K1 well is shown as the reservoir boundary, while the K2 well is far from the reservoir boundary.
The technology has good effect in fluid identification application of the third-line delta of the Nile in the West Africa or the shallow sandstone reservoir, and the sandstone containing oil and gas and the sandstone containing water can be obviously distinguished on a predicted result data body, so that the method can effectively avoid the sandstone containing water when a development well and a new zone block exploratory well are deployed in the next step, and can describe the aggregation range of the hydrocarbon sandstone reservoir, thereby providing basis for accurately establishing an oil reservoir model.
The invention is based on fully utilizing pre-stack frequency information and predicting fluid properties through relative frequency attenuation coefficient characteristics, and provides support for further realizing oil-gas property and distinguishing the fluid properties and reducing exploration risks. The hydrocarbon detection method based on prestack frequency variation solves the problem that AVO false bright spots or dark spots are encountered in prestack hydrocarbon reservoir prediction, and fluid properties are difficult to distinguish, namely, the fluid properties are predicted through the change characteristics of relative frequency attenuation coefficients along with frequency and incidence angle due to different absorption degrees of different fluids on different frequency energy, so that the purpose of distinguishing different fluids is achieved.
It will be apparent to those skilled in the art that various modifications in form, use and details of implementation may be made without undue burden without departing from the principles and concepts of the present invention, and the invention is therefore defined in the appended claims.
Claims (8)
1. The method for detecting the fluid property based on the prestack frequency variation is characterized by comprising the following steps of:
s10, converting three-dimensional seismic prestack gather data of a work area into an angle gather, and generating incident angle superposition data according to angle classification;
S20, performing time-frequency decomposition according to the incidence angle superposition data, and calculating to obtain time-frequency data;
s30, calculating a relative frequency attenuation coefficient of the incident angle superposition data according to the time-frequency data;
The formula for calculating the relative frequency attenuation coefficient of the incident angle superposition data is as follows:
Wherein, Superimposing the center angle of the data for the incident angle, f is frequency,/>For reflected wave amplitude at frequency f and angle of incidence center of the reflection point,/>Respectively incident wave amplitude,/>For the angle of reflection/>Relative reflection angle/>Relative frequency attenuation coefficient at frequency f,/>The energy compensation coefficients caused by the geometrical diffusion,Is the angular frequency of the input;
s40, predicting the fluid property according to the relative frequency attenuation coefficient.
2. The fluid property detection method according to claim 1, wherein S10 comprises:
s101, calculating an incident angle of each reflection point according to offset, time and speed in prestack gather data;
S102, classifying the incidence angles, and superposing the angle-dividing track sets of each type of incidence angle to generate the superimposed data of the type of incidence angle.
3. The method for detecting the property of the fluid according to claim 2, wherein the step S10 further comprises:
S103, carrying out signal-to-noise ratio and spectrum analysis on the incident angle superposition data, and returning to S102 if the signal-to-noise ratio is lower, so as to reduce the number of angle classifications.
4. The method for detecting the property of a fluid according to claim 2, wherein in S20, the time-frequency decomposition is performed by S-transformation, and the formula is:
（1）
Wherein, Is a time signal,/>For frequency,/>The time shift amount of the Gaussian window is represented by t, the sampling point is represented by i, and the imaginary unit is represented by i.
5. The method of claim 4, wherein for the sampling pointAmplitude of reflected waveS phi (t, f) represents the S-transformation for the angle of incidence phi.
6. The method of claim 1, wherein the energy compensation factor is calculated from a difference in energy of a prestack data statistical population near-far path.
7. The fluid property detection method according to claim 5, wherein in S40, the predicting the fluid property includes:
after the well vibration is calibrated, the time spectrum of the known well point is analyzed, and the time-frequency characteristic of drilling fluid is observed as a reference;
Fluid properties may be predicted from typical relative frequency decay factor characteristics of the fluid when the work area is well-free.
8. The method of claim 1, wherein the three-dimensional seismic pre-stack trace set is a CMP trace set.
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