Method and device for determining the main frequency value of seismic wavelet and generating synthetic seismic records

Abstract

The disclosed embodiments provide a method, apparatus, device, and medium for determining the dominant frequency value of a seismic wavelet. The method comprises: obtaining seismic data and extended spectrum seismic data of a target layer, wherein the extended spectrum seismic data is obtained by widening the frequency band of the seismic data; determining a high-cutoff frequency value and a dominant frequency value of the seismic data based on the seismic data; determining a high-cutoff frequency value of the extended spectrum seismic data based on the extended spectrum seismic data; and determining the dominant frequency value of the seismic wavelet based on the high-cutoff frequency value and the dominant frequency value of the seismic data and the high-cutoff frequency value of the extended spectrum seismic data. This method can improve the effectiveness of horizon calibration using synthetic seismic records generated by the seismic wavelet.

Description

Technical Field

[0001] The present disclosure relates to the field of reservoir geophysics, and in particular to a method, device, equipment and medium for determining a main frequency value of a seismic wavelet and generating a synthetic seismic record. Background Art

[0002] When using seismic methods for oil and gas exploration and development, synthetic seismograms are needed to calibrate the actual seismograms acquired, allowing for clearer identification of the various subsurface layers. Synthetic seismograms are generated based on seismic wavelets. Different synthetic seismograms can be generated based on seismic wavelets with different dominant frequency values.

[0003] In related technologies, conventional seismic data are rich in mid- and low-frequency components but lack high-frequency components. Therefore, the dominant frequency values ​​of the mid- and low-frequency components of the seismic data are usually directly used as the dominant frequency values ​​of the seismic wavelet.

[0004] For ultra-wideband seismic data, that is, seismic data that contains more high-frequency components than conventional seismic data, the above method is used to determine the main frequency value of the seismic wavelet without considering the high-frequency components in the ultra-wideband seismic data, so that the main frequency value of the determined seismic wavelet does not fully reflect the ultra-wideband seismic data, which in turn affects the layer calibration effect of the synthetic seismic record generated by the seismic wavelet on the actual seismic record. Summary of the Invention

[0005] The embodiments of the present disclosure provide a method, apparatus, device, and medium for determining the main frequency value of a seismic wavelet and generating a synthetic seismic record, which can improve the effect of performing horizon calibration using the synthetic seismic record generated by the seismic wavelet.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for determining the main frequency value of a seismic wavelet, the method comprising: acquiring seismic data and spread spectrum seismic data of a target layer, the spread spectrum seismic data being obtained by widening the frequency band of the seismic data; determining a high cutoff value and a main frequency value of the seismic data based on the seismic data; determining a high cutoff value of the spread spectrum seismic data based on the spread spectrum seismic data; determining the main frequency value of the seismic wavelet based on the high cutoff value and the main frequency value of the seismic data and the high cutoff value of the spread spectrum seismic data.

[0007] In one implementation of the embodiment of the present disclosure, the main frequency value of the seismic wavelet is determined based on the high cutoff value and main frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data, including: determining the main frequency value of the high frequency segment of the extended spectrum seismic data based on the high cutoff value of the seismic data and the high cutoff value of the extended spectrum seismic data; determining the main frequency value of the seismic wavelet based on the main frequency value of the seismic data and the main frequency value of the high frequency segment of the extended spectrum seismic data.

[0008] In one implementation of the embodiment of the present disclosure, the main frequency value of the high frequency segment of the spread spectrum seismic data is determined based on the high cutoff value of the seismic data and the high cutoff value of the spread spectrum seismic data, including: determining the difference between the high cutoff value of the spread spectrum seismic data and the high cutoff value of the seismic data; and determining the sum of 1 / 2 of the difference and the high cutoff value of the seismic data as the main frequency value of the high frequency segment of the spread spectrum seismic data.

[0009] In one implementation of the embodiment of the present disclosure, the main frequency value of the seismic wavelet is determined based on the main frequency value of the seismic data and the main frequency value of the high frequency band of the spread spectrum seismic data, including: dividing the sum of the main frequency value of the high frequency band of the spread spectrum seismic data and the main frequency value of the seismic data by 2 to determine the main frequency value of the seismic wavelet.

[0010] In one implementation of the embodiment of the present disclosure, based on the seismic data, the high cutoff value and the main frequency value of the seismic data are determined, and based on the extended spectrum seismic data, the high cutoff value of the extended spectrum seismic data is determined, including: generating a spectrum diagram based on the seismic data and the extended spectrum seismic data, the spectrum diagram including a seismic data curve and a extended spectrum seismic data curve, the seismic data curve is used to represent the relationship between the amplitude and frequency of the seismic waves contained in the seismic data, and the extended spectrum seismic data curve is used to represent the relationship between the amplitude and frequency of the seismic waves contained in the extended spectrum seismic data; taking the maximum frequency value corresponding to the intersection of the target amplitude line and the seismic data curve as the high cutoff value of the seismic data; based on the spectrum diagram, the main frequency value of the seismic data is determined; and taking the maximum frequency value corresponding to the intersection of the target amplitude line and the extended spectrum seismic data curve as the high cutoff value of the extended spectrum seismic data.

[0011] In a second aspect, an embodiment of the present disclosure provides a method for generating a synthetic seismic record, the method comprising: determining a main frequency value of a seismic wavelet according to any method described in the first aspect; and generating a synthetic seismic record based on the main frequency value of the seismic wavelet.

[0012] In a third aspect, an embodiment of the present disclosure provides a device for determining the primary frequency value of a seismic wavelet, the device comprising an acquisition module, a first determination module, a second determination module, and a third determination module. The acquisition module is configured to acquire seismic data and extended spectrum seismic data of a target layer, where the extended spectrum seismic data is obtained by widening the frequency band of the seismic data; the first determination module is configured to determine the high cutoff value and primary frequency value of the seismic data based on the seismic data; the second determination module is configured to determine the high cutoff value of the extended spectrum seismic data based on the extended spectrum seismic data; and the third determination module is configured to determine the primary frequency value of the seismic wavelet based on the high cutoff value and primary frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data.

[0013] In a fourth aspect, an embodiment of the present disclosure provides a device for generating synthetic seismic records, the device comprising: a determination module for determining the main frequency value of the seismic wavelet according to any method described in the first aspect; a generation module for generating synthetic seismic records based on the main frequency value of the seismic wavelet, the synthetic seismic records being used to perform layer calibration on the actual seismic records corresponding to the spread spectrum seismic data.

[0014] In a fifth aspect, an embodiment of the present disclosure provides a computer device, comprising a processor and a memory; wherein the memory is used to store a computer program; and the processor is used to execute the computer program stored in the memory to implement any one of the methods described in the first aspect or the method described in the second aspect.

[0015] In a sixth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, in which computer instructions are stored. When the stored computer instructions are executed by a processor, any method described in the first aspect or the method described in the second aspect can be implemented.

[0016] The beneficial technical effects brought about by the technical solution provided by the embodiment of the present disclosure include at least the following: the present disclosure determines the main frequency value of the seismic wavelet through the high cutoff value and main frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data, takes into account both the medium and low frequency components in the seismic data and the high frequency components in the extended spectrum seismic data to determine the main frequency value of the seismic wavelet, and makes full use of the high frequency components and medium and low frequency components of the ultra-wideband seismic data containing the seismic data and the extended spectrum seismic data. Therefore, the seismic wavelet corresponding to the main frequency value determined by the method of the present disclosure can fully reflect the ultra-wideband seismic data, so that the synthetic seismic record generated by the seismic wavelet has a better effect on the layer calibration of the actual seismic record. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 is a schematic diagram of a method for determining the main frequency value of a seismic wavelet provided by an embodiment of the present disclosure;

[0019] Figure 2 is a schematic diagram of a method for generating a synthetic seismic record provided by an embodiment of the present disclosure;

[0020] Figure 3is a spectrum diagram of seismic data and extended spectrum seismic data provided by an embodiment of the present disclosure;

[0021] Figure 4 is a comparative schematic diagram of calibration results of synthetic seismic records provided by an embodiment of the present disclosure;

[0022] Figure 5 is a comparative schematic diagram of another synthetic seismic record calibration result provided by an embodiment of the present disclosure;

[0023] Figures 6 to 8 is a basic overview diagram of an application area of ​​another example provided by an embodiment of the present disclosure;

[0024] Figure 9 is a comparison diagram of spectral characteristics of seismic data and frequency-spreading seismic data according to another example provided by an embodiment of the present disclosure;

[0025] Figure 10 is another example of seismic data and a spectrum diagram of extended spectrum seismic data provided by an embodiment of the present disclosure;

[0026] Figure 11 is a schematic diagram of a synthetic seismic record calibration result in another example provided by an embodiment of the present disclosure;

[0027] Figure 12 is a schematic diagram of another synthetic seismic record calibration result in another example provided by an embodiment of the present disclosure;

[0028] Figure 13 is another example of a spectrum-spreading seismic data profile reflection layer tracking diagram provided by an embodiment of the present disclosure;

[0029] Figure 14 is another example of a seismic data profile reflection layer tracking diagram provided by an embodiment of the present disclosure;

[0030] Figure 15 is another example of a reservoir inversion diagram of extended frequency seismic data provided by an embodiment of the present disclosure;

[0031] Figure 16 is another example of a reservoir inversion diagram of seismic data provided by an embodiment of the present disclosure;

[0032] Figure 17 1 is a schematic structural diagram of a device for determining the main frequency value of a seismic wavelet provided by an embodiment of the present disclosure;

[0033] Figure 18 is a schematic structural diagram of a device for generating synthetic seismic records provided by an embodiment of the present disclosure;

[0034] Figure 19 It is a structural diagram of a computer device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] In order to make the objectives, technical solutions and advantages of the present disclosure more clear, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.

[0036] When using seismic methods for oil and gas exploration and development, the complex underground conditions and energy loss caused by seismic waves reflected from strata boundaries can blur the boundaries of various layers in the actual seismic records. Therefore, synthetic seismic records are needed to demarcate the layers of the actual seismic records, allowing for clearer identification of the various layers.

[0037] Synthetic seismic records are generated by convolving a seismic wavelet with a reflection coefficient sequence. Different synthetic seismic records can be generated based on seismic wavelets with different dominant frequencies. The dominant frequency of a seismic wavelet refers to any frequency within a frequency band corresponding to the higher energy portion of the seismic wavelet. For example, if the frequency band corresponding to the higher energy portion of the seismic wavelet includes 65-75 Hz, the dominant frequency can be any frequency within 65-75 Hz.

[0038] In practical applications, wells are typically drilled in the study area, and then well logging methods are used to obtain formation data. Based on this data, a reflection coefficient sequence is calculated for the formation. This reflection coefficient sequence is then convolved with the seismic wavelet to generate a synthetic seismic record. Furthermore, a seismic trace (referred to as a wellside trace) is set up next to the well to obtain actual seismic records from the wellside trace. The synthetic seismic record is then used to calibrate the actual seismic records from the wellside trace.

[0039] Figure 1 is a schematic diagram of a method for determining the main frequency value of a seismic wavelet provided by an embodiment of the present disclosure, such as Figure 1 As shown, the method includes:

[0040] In step 101, seismic data and extended frequency seismic data of a target layer are acquired. The extended frequency seismic data is obtained by widening the frequency band of the seismic data.

[0041] In step 102, the high cutoff frequency value and the main frequency value of the seismic data are determined based on the seismic data. The high cutoff frequency value of the seismic data is the maximum frequency value in the effective frequency band of the seismic data. For example, if the maximum frequency value corresponding to the amplitude of -20dB (the parallel line of the signal-to-noise ratio S / N=1 on the spectrum graph) of the seismic data is 60Hz, then the high cutoff frequency value of the seismic data is 60Hz.

[0042] In step 103, a high cutoff value of the spectrum spreading seismic data is determined based on the spectrum spreading seismic data.

[0043] In step 104, the main frequency value of the seismic wavelet is determined based on the high cutoff frequency value and the main frequency value of the seismic data and the high cutoff frequency value of the extended frequency seismic data.

[0044] The present invention determines the main frequency value of the seismic wavelet through the high cutoff value and main frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data, and takes into account the medium and low frequency components in the seismic data and the high frequency components in the extended spectrum seismic data to determine the main frequency value of the seismic wavelet, and makes full use of the high frequency components and medium and low frequency components of the ultra-wideband seismic data containing seismic data and extended spectrum seismic data, so that the synthetic seismic record generated by the seismic wavelet has a better effect on the layer calibration of the actual seismic record.

[0045] Figure 2 is a schematic diagram of a method for generating synthetic seismic records provided by an embodiment of the present disclosure, such as Figure 2 As shown, the method includes:

[0046] In step 201, seismic data and extended frequency seismic data of a target layer are acquired. The extended frequency seismic data is obtained by widening the frequency band of the seismic data.

[0047] The target layer is the stratum that one wants to study, for example, the target layer can be an oil and gas layer, a coal seam, etc.

[0048] For example, multiple detectors can be set up at different locations on the ground. The detectors are used to receive seismic wave signals reflected from various underground stratum interfaces, and then perform offset, superposition and other processing on the received seismic wave signals to obtain seismic data of the target layer.

[0049] Due to the absorption and attenuation effect of the strata, the strata absorb the high-frequency signals in the seismic waves, resulting in the loss of high-frequency components in the seismic waves received by the ground detectors. In other words, the acquired seismic data mainly consists of medium- and low-frequency seismic signals. The corresponding frequency band of the seismic data is smaller. Therefore, compared with seismic data with a larger frequency band, the ability of this seismic data to distinguish strata is poor, that is, the resolution of this seismic data is lower. The resolution of seismic data refers to the minimum thickness of the strata that can be distinguished using the seismic data. The smaller the thickness of the strata that can be distinguished, the higher the resolution of the seismic data.

[0050] Bandwidth expansion of seismic data involves restoring the missing high-frequency signals to a certain extent, thereby generating ultra-wideband extended-spectrum seismic data encompassing low-, medium-, and high-frequency bands. Alternatively, the seismic data can be decomposed using sequence modal decomposition and then fused using multi-frequency signal fusion to generate extended-spectrum seismic data.

[0051] In step 202, based on the seismic data, a high cutoff frequency value and a main frequency value of the seismic data are determined.

[0052] This step 202 may include:

[0053] In step 202a, a spectrum diagram is generated based on the seismic data and the extended spectrum seismic data. The spectrum diagram includes a seismic data curve and an extended spectrum seismic data curve. The seismic data curve is used to represent the relationship between the amplitude and frequency of the seismic waves contained in the seismic data, and the extended spectrum seismic data curve is used to represent the relationship between the amplitude and frequency of the seismic waves contained in the extended spectrum seismic data.

[0054] Figure 3 : is a spectrum diagram of seismic data and extended spectrum seismic data in an example provided by an embodiment of the present disclosure. Figure 3 As shown, the spectrum plot shows the relationship between seismic wave energy and frequency. The horizontal axis is frequency, measured in Hertz (Hz), and the vertical axis is amplitude, measured in decibels (dB). Seismic wave energy can be represented by the amplitude of the seismic wave. The larger the amplitude, the higher the seismic wave energy. 31 is the seismic data curve, and 32 is the extended spectrum seismic data curve. In this example, the signal-to-noise ratio of the seismic data is 1. The signal-to-noise ratio refers to the ratio of effective information to noise information in the seismic data.

[0055] Alternatively, a spectrum diagram may be generated based on the seismic data and the spread spectrum seismic data using software such as MATLAB, HRS, and VISTA.

[0056] In step 202b, the maximum frequency value corresponding to the intersection of the target amplitude line and the seismic data curve is used as the high cutoff frequency value of the seismic data.

[0057] The target amplitude line may include a straight line corresponding to the target amplitude value in the spectrum diagram. Optionally, the target amplitude value may be pre-set. For example, in this example, the target amplitude value is -20db, that is, the target amplitude line is a straight line corresponding to -20db. The maximum frequency value corresponding to the intersection of the target amplitude line and the seismic data curve is used as the high cutoff value of the seismic data. Figure 3 As shown, the frequency value corresponding to 311 is the high cutoff frequency value fh of the seismic data. In this example, fh is taken as 56 Hz.

[0058] In step 202c, the dominant frequency value of the seismic data is determined based on the frequency spectrum.

[0059] The main frequency value of seismic data refers to any frequency value in a frequency band corresponding to the larger energy portion of the seismic wave corresponding to the seismic data. Figure 3 As shown, the main frequency value fd of the seismic data can be any value in the frequency range corresponding to 312. In this example, fd is taken as 32 Hz.

[0060] In step 203, a high cutoff value of the spread spectrum seismic data is determined based on the spread spectrum seismic data.

[0061] The maximum frequency value corresponding to the intersection of the target amplitude line and the extended spectrum seismic data curve is used as the high cutoff value of the extended spectrum seismic data. Figure 3 As shown, the frequency value corresponding to 321 is the high cutoff value F of the extended spectrum seismic data. h In this example, take F h It is 152Hz.

[0062] In step 204, the main frequency value of the seismic wavelet is determined based on the high cutoff frequency value and the main frequency value of the seismic data and the high cutoff frequency value of the extended frequency seismic data.

[0063] This step 204 may include:

[0064] In step 204a, the main frequency value of the high frequency band of the extended spectrum seismic data is determined based on the high frequency cutoff value of the seismic data and the high frequency cutoff value of the extended spectrum seismic data.

[0065] Optionally, step 204a may include:

[0066] The difference between the high cutoff value of the extended frequency seismic data and the high cutoff value of the seismic data is determined.

[0067] The sum of 1 / 2 of the difference and the high cutoff value of the seismic data is determined as the main frequency value of the high frequency band of the spread spectrum seismic data.

[0068] For example, the main frequency value F of the high frequency band of the extended seismic data is d It can be calculated using formula (1):

[0069] F d =1 / 2(F h -f h )+f h (1)

[0070] In this example, the main frequency value F of the high frequency band of the extended spectrum seismic data is calculated. d =104 Hz. For explanations of other parameters, see steps 202 and 203.

[0071] In step 204b, the dominant frequency value of the seismic wavelet is determined based on the dominant frequency value of the seismic data and the dominant frequency value of the high frequency band of the spread spectrum seismic data.

[0072] Optionally, step 204b includes: dividing the sum of the main frequency value of the high frequency band of the spread spectrum seismic data and the main frequency value of the seismic data by 2 to determine the main frequency value of the seismic wavelet.

[0073] For example, the main frequency value F of the seismic wavelet w It can be calculated using formula (2):

[0074] Fw =1 / 2(F d +f d ) (2)

[0075] In this example, the main frequency value F of the seismic wavelet is calculated w =68Hz. For explanations of other parameters, see steps 202 and 204a.

[0076] The main frequency value of the seismic wavelet is determined through the above steps 201 to 204.

[0077] In step 205, a synthetic seismic record is generated based on the main frequency value of the seismic wavelet.

[0078] Synthetic seismic records are used to calibrate the horizon of actual seismic records, which are obtained based on seismic data or spread spectrum seismic data.

[0079] The step 205 includes: setting the main frequency value F w The corresponding seismic wavelet is convolved with the reflection coefficient sequence to generate a synthetic seismic record.

[0080] In some examples, the main frequency value F can be selected in software such as HRS, VISTA or GEOEAST. w The corresponding seismic wavelet, for example, can be selected from the main frequency value F w The corresponding Ricker wavelet is used as the seismic wavelet. Since the initial phases of the acquired seismic data and the extended spectrum seismic data are both 0 in actual work, the zero-phase Ricker wavelet is selected as the seismic wavelet to generate a synthetic seismic record, which can then be used to perform better horizon calibration.

[0081] In other examples, the main frequency value F can be extracted from the seismic data in the well bypass. w The corresponding actual seismic wave is used as the seismic wavelet. For example, the main frequency value F can be selected from the spectrum diagram of the seismic data in the well bypass. w The corresponding section of seismic waves is taken as seismic wavelet.

[0082] The reflection coefficient sequence is used to represent the properties of each stratum's reflection of seismic waves. Optionally, well logging methods, such as acoustic logging, natural gamma logging, and density logging, can be used to obtain formation data in the well; the reflection coefficient sequence is calculated based on this formation data.

[0083] The main frequency value F w The corresponding seismic wavelet is convolved with the reflection coefficient sequence to generate a synthetic seismic record. The synthetic seismic record is then used to calibrate the actual seismic record for horizon positions. Horizon calibration involves using the stratigraphic positions in the synthetic seismic record to calibrate the stratigraphic positions in the actual seismic record.

[0084] Figure 4 This is a schematic diagram of a synthetic seismic record calibration result provided by an embodiment of the present disclosure. Figure 4 The main frequency value of the seismic wavelet used to generate the synthetic seismic record is determined according to the method provided in the embodiment of the present disclosure, which is 70 Hz. Figure 4 Part (a) is the result of horizon calibration of the actual earthquake record corresponding to the earthquake data; Figure 4 Part (b) is the result of horizon calibration of the actual seismic records corresponding to the extended spectrum seismic data. Figure 4 As shown, 41 is a synthetic seismic record, 42 is an actual seismic record of seismic data, and 43 is an actual seismic record of spread spectrum seismic data.

[0085] In seismic exploration, multiple survey lines are laid out across the application area, with different lines assigned different line numbers. Each survey line is equipped with multiple geophones, which are used to detect data from multiple seismic channels. Different channels are assigned different channel numbers.

[0086] Seismic records are plotted on the horizontal axis with the trace number and the vertical axis with depth (in meters). Each black bar in the diagram, such as 411, 423, and 433, corresponds to a seismic reflection event. An event is a line connecting the parts of the seismic waves detected by each seismic trace in a seismic record with the same phase. Each event represents a stratum.

[0087] from Figure 4 It can be seen that the number of events in part (b) is greater than the number of events in part (a). For example, if regions 421 and 431 are actual seismic records corresponding to strata at the same depth, it can be seen that the stratigraphic boundary in region 431 of the actual seismic record of the extended spectrum seismic data is more obvious, including at least two events, i.e., it is divided into at least two strata; while in the actual seismic record of the seismic data, there is only one event in region 421, i.e., no obvious stratigraphic boundary can be seen. For another example, if regions 422 and 432 are actual seismic records corresponding to strata at the same depth, it can be seen that the stratigraphic boundary in region 432 of the actual seismic record of the extended spectrum seismic data is more obvious, including at least four events, i.e., it is divided into at least four strata; while in the actual seismic record of the seismic data, there are only two events.

[0088] Figure 4 The arrows in the figure indicate the strata determined after the horizon calibration, i.e. the calibration results. Figure 4 It can be seen that in the calibration results of part (b), the calibrated strata include not only all the strata calibrated by the calibration results of part (a) (e.g. Figure 4 The strata indicated by the arrows on the left side of part (b) of FIG. 1 ) also include a plurality of additional strata (e.g. Figure 4 The strata are indicated by the arrows on the right side of part (b).

[0089] It can be seen that the result of performing layer calibration on the actual seismic record of the topology seismic data using the synthetic seismic record generated by the method provided in the embodiment of the present disclosure is significantly better than the result of performing layer calibration on the actual seismic record of the seismic data using the synthetic seismic record generated by the method provided in the embodiment of the present disclosure.

[0090] Figure 4 The curve corresponding to 44 is the acoustic time difference curve, with the unit of microseconds / meter (us / m). The acoustic time difference is the inverse of the speed, so the acoustic speed curve can be obtained based on the acoustic time difference curve; the curve corresponding to 45 is the density curve, with the unit of grams / cubic centimeter (g / cm 3 ), the density curve can be determined by the density logging method; the curve corresponding to 46 is the acoustic velocity curve, and the unit is meter per second (m / s); the curve corresponding to 47 is the wave impedance curve, and the wave impedance is the product of density and velocity, so the wave impedance curve can be determined based on the acoustic velocity curve and the density curve; 48 is the reflection coefficient pulse, and the reflection coefficient pulse can be determined based on the reflection coefficient sequence; 49 is the formation label; 410 is the formation depth; 47' is the lithology curve, and for example, the lithology curve can be a natural potential logging curve, and the unit is millivolt (mv).

[0091] Figure 5 This is another schematic diagram of synthetic seismic record calibration results provided by an embodiment of the present disclosure. Figure 5 Part (a) is the result of horizon calibration of the actual earthquake record corresponding to the earthquake data; Figure 5 Part (b) is the result of horizon calibration of the actual seismic records corresponding to the extended spectrum seismic data. Figure 5 The synthetic seismic record is based on the main frequency value f of the seismic data. d The corresponding seismic wavelet is convolved. In order to facilitate the drawing and calculation, the main frequency value of the seismic wavelet is 35Hz. Figure 5 As shown, 51 is a synthetic seismic record, 52 is an actual seismic record of seismic data, and 53 is an actual seismic record of extended frequency seismic data. Figure 5 Other curves can be found in Figure 4 Corresponding embodiments.

[0092] contrast Figure 4 Part (a) and Figure 5 As can be seen from part (a) of the figure, the horizon calibration results of the two are the same. For actual seismic records of seismic data, whether the synthetic seismic record is obtained by using the dominant frequency value determined by the method provided by the embodiment of the present disclosure or the synthetic record is obtained by using the dominant frequency value determined by the method in the related art, it has little effect on the horizon calibration results.

[0093] contrast Figure 5 Part (a) and Figure 5 From part (b) of the figure, we can see that the horizon calibration results of the two are also the same. This is because, although the number of events displayed in the synthetic seismic record of the extended spectrum seismic data is large, the number of events in the synthetic seismic record is small, so it is impossible to calibrate all the horizons in the synthetic seismic record of the extended spectrum seismic data.

[0094] Therefore, by using the method for determining the main frequency of the seismic wavelet provided in the embodiment of the present disclosure to synthesize seismic records and perform horizon calibration on the actual seismic records of the spread spectrum seismic data, a better horizon calibration effect can be obtained.

[0095] For example, in actual applications, the basic profile of the application area must first be determined. For example, the approximate depth of the target layer in the application area can be determined. In seismic exploration, shot points are set in the application area to excite seismic waves. Optionally, artificial sources or explosive sources can be used to excite seismic waves at the shot points. Detection points are also set to receive the reflected waves that are reflected back to the ground when the seismic waves reach the stratum interface. The longer the reflection time of the reflected waves received by the detection points, the greater the depth of the stratum. The reflection time refers to the time it takes for the seismic wave to be excited from the shot point to be reflected back to the ground through a certain stratum interface and received by the detector. The longer the reflection time, the greater the depth of the stratum. Usually, the acquired seismic data is represented in the form of a spectrum, that is, the relationship between the amplitude and frequency of the seismic data.

[0096] Figures 6 to 8 is another example of a basic overview diagram of an application area provided by an embodiment of the present disclosure, such as Figure 6 As shown, the horizontal axis is the track number and the vertical axis is the depth in meters. In this example, the target layer 61 in the application area is the CP layer. The CP layer is a coal-bearing stratum rich in coalbed methane reservoirs and has a thin gas storage sand layer.

[0097] like Figure 7 As shown, the horizontal axis is the reflection time in milliseconds. The vertical axis is the depth in meters. In seismic exploration, shot points are set in the application area to excite seismic waves. Optionally, artificial sources or explosive sources can be used to excite seismic waves at the shot points. Reflection time refers to the time it takes for a seismic wave to be excited at the shot point and reflected back to the ground through a certain stratum interface and received by a detector. It should be noted that Figure 7 Only one line is used as an example for illustration. In fact, different well locations will correspond to different curves, and these curves show the same rule, that is, the longer the reflection time, the greater the formation depth.

[0098] like Figure 8As shown, the horizontal axis is frequency, in Hertz (Hz), and the vertical axis is amplitude, in decibel (dB). Curve 81 shows the relationship between the amplitude and frequency of seismic data of the target layer in the application area.

[0099] Figure 9 is another example of a comparison diagram of the spectrum characteristics of seismic data and spectrum spreading seismic data provided by the embodiment of the present disclosure, such as Figure 9 As shown, 91 is the seismic data curve, 92 is the extended spectrum seismic data curve, and 93 is the curve obtained by shifting the phase of the extended spectrum seismic data curve in 92 by 90°. The frequency band of seismic data ranges from approximately 10Hz to 70Hz, which refers to medium- and low-frequency signals; the frequency band of extended spectrum seismic data ranges from approximately 7Hz to 192Hz, containing not only medium- and low-frequency signals in the seismic data but also more high-frequency signals. After processing and calculating the seismic data and extended spectrum seismic data, it is found that the thinnest vertical thickness that can be distinguished in the seismic data, i.e., the vertical resolution, is approximately 30m, and the narrowest horizontal range that can be distinguished, i.e., the horizontal resolution, is approximately 240m-260m; the thinnest vertical thickness that can be distinguished in the extended spectrum seismic data, i.e., the vertical resolution, is approximately 10m-12m, and the narrowest horizontal range that can be distinguished, i.e., the horizontal resolution, is approximately 140m-160m. It can be seen that extended spectrum seismic data has significantly improved both vertical and horizontal resolution compared to traditional seismic data.

[0100] Figure 10 is another example of seismic data and spectrum diagram of extended spectrum seismic data provided by the embodiment of the present disclosure, such as Figure 10 As shown. The horizontal axis is frequency, in Hertz (Hz), and the vertical axis is amplitude, in decibels (dB). 101 is the seismic data curve, and 102 is the extended spectrum seismic data curve. Optionally, software such as MATLAB, HRS, and VISTA can be used to obtain a spectrum diagram based on the seismic data and extended spectrum seismic data.

[0101] The frequency values ​​of the characteristic points on the spectrum include the high cutoff value f of the seismic data h , main frequency value f d and the high cutoff value F of the spread spectrum data h For example, Figure 10 As shown, in this example, -20db is used as the horizontal line to obtain the high cutoff value of the seismic data and the extended frequency seismic data. 1011 is the high cutoff value f of the seismic data h In this example, take f h is 70Hz; 1012 is the main frequency value f of the seismic data d In this example, take f d is 38Hz; 1021 is the high cutoff value F of the extended frequency seismic data h In this example, take F hIt is 170Hz.

[0102] The main frequency value F of the high frequency band of the extended spectrum seismic data d It can be calculated using formula (1). In this example, the calculated F d =120Hz. The main frequency value of the seismic wavelet F w It can be calculated using formula (2). In this example, the calculated F w =80Hz.

[0103] The main frequency value F w The corresponding seismic wavelet is convolved with the reflection coefficient sequence to obtain a synthetic seismic record, which is then used to calibrate the actual seismic record. Figure 11 FIG. 1 is a schematic diagram of a synthetic seismic record calibration result in another example provided by the embodiment of the present disclosure, wherein the main frequency value of the seismic wavelet is 80 Hz. Figure 11 As shown, 111 is a synthetic seismic record, and 112 is an actual seismic record of the spread spectrum seismic data.

[0104] Figure 12 FIG. 1 is another schematic diagram of calibration results of synthetic seismic records in another example provided by an embodiment of the present disclosure, such as Figure 12 As shown, the synthetic seismic record is made using the main frequency value f of the seismic data. d The corresponding seismic wavelet is convolved, and the main frequency value of the seismic wavelet is 40 Hz. 121 is a synthetic seismic record, and 122 is an actual seismic record of seismic data. Figure 11 The area 1111 in Figure 12 The area 1211 in the figure corresponds to the stratum at the same depth. It can be seen that the area 1111 in the synthetic seismic wavelet record with a main frequency value of 80 Hz contains at least two event axes, while the area 1211 in the synthetic seismic wavelet record with a main frequency value of 40 Hz contains only one event axis. Figure 11 Area 1121 and Figure 12 Region 1221 in the figure corresponds to the same stratum at the same depth. It can be seen that region 1121 contains at least two events, i.e., at least two strata, while region 1221 contains only one event, i.e., only one stratum. Therefore, using region 1111 to calibrate the horizon of region 1121 is more effective. In other words, using synthetic seismic records with a main frequency of 80 Hz for stratum calibration of extended spectrum seismic data allows for more precise demarcation of individual strata, resulting in better stratum calibration results. Figure 11 and Figure 12 Other curves in Figure 4 Corresponding embodiments.

[0105] Therefore, by using the method for determining the main frequency of the seismic wavelet provided in the embodiment of the present disclosure to synthesize seismic records and perform horizon calibration on the actual seismic records of the spread spectrum seismic data, a better horizon calibration effect can be obtained.

[0106] Figure 13 This is another example of a spectrum-spreading seismic data profile reflection layer tracking diagram provided by an embodiment of the present disclosure, such as Figure 13 As shown, Figure 13 is based on Figure 11 Alternatively, the result can be obtained in software such as HRS, VISTA or GEOEAST. Figure 13 The horizontal axis represents the channel number, indicating the different seismic channels. The vertical axis represents depth in meters. Figure 1301 is the natural gamma ray log, which measures the intensity of natural gamma rays along the wellbore to obtain data on each stratum. Figure 1302 is the true resistivity curve, which shows the resistivity variation at different depths.

[0107] Figure 14 This is another example of a seismic data profile reflection layer tracking diagram provided by the embodiment of the present disclosure, such as Figure 14 As shown, Figure 14 is based on Figure 12 Region 1303 and region 1401 correspond to strata at the same depth. It can be seen that the stratum boundary in region 1303 is more obvious than that in region 1401. That is, by synthesizing seismic records using the method for determining the main frequency of seismic wavelets provided in the embodiment of the present disclosure, calibrating the stratum of the actual seismic records of the spread spectrum seismic data, and then tracking the reflection layer using the stratum calibration results, more and more accurate information on each stratum and its structure can be obtained.

[0108] For example, a reservoir inversion map can be produced based on the horizon calibration results of the synthetic seismic record. This reservoir inversion map can be used for subsequent geological surveys, underground physical property exploration, and the like. The reservoir inversion map produced based on the horizon calibration structure of the synthetic seismic record in the embodiment of the present disclosure can more accurately reflect the underground situation. Inversion refers to the process of inferring the underground stratigraphic structure based on the horizon calibration results of the actual seismic record of the topology seismic data, thereby establishing a stratigraphic distribution model.

[0109] Figure 15 is another example of a reservoir inversion diagram of extended frequency seismic data provided by an embodiment of the present disclosure, such as Figure 15 As shown, the horizontal axis is the line number and track number, and the vertical axis is the depth, in meters. 1501 and 1502 are the well logging curves for different well locations, respectively. Each bulge or depression in the logging curve represents a change in the underground strata. Figure 15 is based on Figure 11 Alternatively, the result can be obtained in software such as HRS, VISTA or GEOEAST. Figure 15 .

[0110] Figure 16 is another example of a reservoir inversion diagram of seismic data provided by an embodiment of the present disclosure, such as Figure 16 As shown, Figure 16 is based on Figure 12 The result is obtained by calibrating the horizon of the actual earthquake record of the earthquake data in the . Figure 15 Area 1503 in Figure 16 The region 1601 in the figure corresponds to the stratum at the same depth. It can be seen that the region 1503 can distinguish more strata than the region 1601, that is, the resolution is higher. Figure 15 The boundary of the middle formation is compared with the convexity or concavity of the logging curves 1501 and 1502. Figure 16 A better correspondence can be made, that is, Figure 15 The inversion results in the above data can more accurately reflect the underground conditions. Therefore, by synthesizing seismic records using the method for determining the main frequency of seismic wavelets provided in the embodiments of the present disclosure, performing horizon calibration on the actual seismic records, and then performing reservoir inversion using the horizon calibration results, the underground conditions can be more accurately reflected.

[0111] Optionally, in the disclosed embodiment, a seismic tectonic comparison grid map can be generated based on the horizon calibration results of the synthetic seismic records. The seismic tectonic comparison grid map can be used for mineral resource exploration, geological surveys, and geological interpretation.

[0112] Furthermore, based on the horizon calibration results from synthetic seismic records, thin sand thickness distribution prediction maps can be generated for different strata. These maps can be used for reservoir prediction and reservoir property research, and are particularly suitable for the evaluation and development of unconventional oil and gas reservoirs. Field verification has shown that both the resulting seismic structural correlation framework and thin sand thickness distribution prediction maps are highly accurate, effectively meeting the demanding requirements for precise spatial prediction of thin sand reservoir distribution in the evaluation and development of unconventional oil and gas reservoirs.

[0113] Figure 17 FIG. 1 is a schematic diagram of a structure of a device for determining the main frequency value of a seismic wavelet provided by an embodiment of the present disclosure, such as Figure 17As shown, the apparatus 1700 includes an acquisition module 1701, a first determination module 1702, a second determination module 1703, and a third determination module 1704. The acquisition module 1701 is used to acquire seismic data and extended spectrum seismic data of a target layer, where the extended spectrum seismic data is obtained by widening the frequency band of the seismic data; the first determination module 1702 is used to determine a high cutoff value and a main frequency value of the seismic data based on the seismic data; the second determination module 1703 is used to determine a high cutoff value of the extended spectrum seismic data based on the extended spectrum seismic data; and the third determination module 1704 is used to determine a main frequency value of the seismic wavelet based on the high cutoff value and the main frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data.

[0114] In one implementation of the disclosed embodiment, the third determination module 1704 further includes a first determination submodule 1704a and a second determination submodule 1704b. The first determination submodule 1704a is configured to determine the dominant frequency value of the high frequency segment of the extended spectrum seismic data based on the high frequency cutoff value of the seismic data and the high frequency cutoff value of the extended spectrum seismic data; and the second determination submodule 1704b is configured to determine the dominant frequency value of the seismic wavelet based on the dominant frequency value of the seismic data and the dominant frequency value of the high frequency segment of the extended spectrum seismic data.

[0115] In one implementation of the embodiment of the present disclosure, the first determination submodule 1704a is also used to determine the difference between the high cutoff value of the spread spectrum seismic data and the high cutoff value of the seismic data; and the sum of 1 / 2 of the difference and the high cutoff value of the seismic data is determined as the main frequency value of the high frequency band of the spread spectrum seismic data.

[0116] In one implementation of the embodiment of the present disclosure, the second determining submodule 1704b is further configured to divide the sum of the main frequency value of the high frequency band of the spread spectrum seismic data and the main frequency value of the seismic data by 2 to determine the main frequency value of the seismic wavelet.

[0117] In one implementation of the disclosed embodiment, the first determination module 1702 includes a generation submodule 1702a and a third determination submodule 1702b. The generation submodule 1702a is configured to generate a frequency spectrogram based on the seismic data and the extended spectrum seismic data, the frequency spectrogram including a seismic data curve and an extended spectrum seismic data curve, the seismic data curve representing the relationship between the amplitude and frequency of the seismic waves contained in the seismic data, and the extended spectrum seismic data curve representing the relationship between the amplitude and frequency of the seismic waves contained in the extended spectrum seismic data; the third determination submodule 1702b is further configured to use the maximum frequency value corresponding to the intersection of the target amplitude line and the seismic data curve as the high-cutoff value of the seismic data; and to determine the dominant frequency value of the seismic data based on the frequency spectrogram; and the second determination module 1703 is further configured to use the maximum frequency value corresponding to the intersection of the target amplitude line and the extended spectrum seismic data curve as the high-cutoff value of the extended spectrum seismic data.

[0118] Figure 18FIG. 1 is a schematic diagram of a structure of a device for generating synthetic seismic records provided by an embodiment of the present disclosure. Figure 18 As shown, the device includes: a determination module 1801 and a generation module 1802. The determination module 1801 is used to determine the main frequency value of the seismic wavelet according to the method for determining the main frequency value of the seismic wavelet; the generation module 1802 is used to generate a synthetic seismic record based on the main frequency value of the seismic wavelet, and the synthetic seismic record is used to perform horizon calibration on the actual seismic record corresponding to the extended spectrum seismic data.

[0119] Figure 19 This is a schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure. Figure 19 As shown, the computer device 1900 includes a memory 1901 and a processor 1902. Those skilled in the art will understand that Figure 19 The structure of the computer device 1900 shown in the figure does not constitute a limitation to the computer device 1900. In actual applications, the computer device 1900 may include more or fewer components than shown in the figure, or some components may be combined, or the components may be arranged differently.

[0120] Memory 1901 can be used to store computer programs and modules. Memory 1901 may primarily include a program storage area and a data storage area. The program storage area may store an operating system, at least one application required for a function, and the like. Memory 1901 may include high-speed random access memory (RAM) and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state memory device. Accordingly, memory 1901 may also include a memory controller to provide processor 1902 with access to memory 1901.

[0121] The processor 1902 executes various functional applications and data processing by running software programs and modules stored in the memory 1901, such as executing the method for determining the main frequency value of the seismic wavelet provided in the embodiment of the present disclosure, or the method for generating a synthetic record.

[0122] In an exemplary embodiment, a computer-readable storage medium is also provided. The computer-readable storage medium is a non-volatile storage medium. A computer program is stored in the computer-readable storage medium. When the computer program in the computer-readable storage medium is executed by a processor, the method for determining the main frequency value of the seismic sub-wave provided in the embodiment of the present disclosure, or the method for generating a synthetic record can be executed.

[0123] In an exemplary embodiment, a computer program product is also provided, which stores instructions. When the computer program product is run on a computer, it enables the computer to execute the method for determining the main frequency value of the seismic sub-wave or the method for generating a synthetic record provided in the embodiment of the present disclosure.

[0124] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0125] The above description is merely an optional embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure shall be included in the scope of protection of the present disclosure.

Claims

1. A method for determining the main frequency value of a seismic wavelet, characterized in that: The method comprises: Acquire seismic data and extended frequency seismic data of a target layer, wherein the extended frequency seismic data is obtained by broadening a frequency band of the seismic data; Based on the seismic data, determining a high cutoff frequency value and a main frequency value of the seismic data; Determining a high frequency cutoff value of the extended spectrum seismic data based on the extended spectrum seismic data; Determine a difference between a high cutoff value of the extended frequency seismic data and a high cutoff value of the seismic data; Determine the sum of 1 / 2 of the difference and the high cutoff value of the seismic data as the main frequency value of the high frequency band of the spread spectrum seismic data; The sum of the main frequency value of the high frequency band of the spectrum spreading seismic data and the main frequency value of the seismic data is divided by 2 to determine the main frequency value of the seismic wavelet.

2. The method according to claim 1, characterized in that The step of determining a high frequency cutoff value and a main frequency value of the seismic data based on the seismic data, and determining a high frequency cutoff value of the extended frequency seismic data based on the extended frequency seismic data, comprises: Generate a spectrum diagram based on the seismic data and the extended spectrum seismic data, the spectrum diagram including a seismic data curve and an extended spectrum seismic data curve, the seismic data curve being used to represent the relationship between the amplitude and frequency of the seismic waves contained in the seismic data, and the extended spectrum seismic data curve being used to represent the relationship between the amplitude and frequency of the seismic waves contained in the extended spectrum seismic data; The maximum frequency value corresponding to the intersection of the target amplitude line and the seismic data curve is used as the high cutoff frequency value of the seismic data; Determining a dominant frequency value of the seismic data based on the frequency spectrum; The maximum frequency value corresponding to the intersection of the target amplitude line and the extended spectrum seismic data curve is used as the high cutoff frequency value of the extended spectrum seismic data.

3. A method for generating synthetic seismic records, characterized in that The method comprises: Determine the main frequency value of the seismic wavelet according to the method of claim 1 or 2; A synthetic seismic record is generated based on the main frequency value of the seismic wavelet, and the synthetic seismic record is used to perform horizon calibration on the actual seismic record corresponding to the extended spectrum seismic data.

4. A device for determining the main frequency value of a seismic wavelet, characterized in that: The device comprises: An acquisition module, configured to acquire seismic data and extended frequency seismic data of a target layer, wherein the extended frequency seismic data is obtained by broadening the frequency band of the seismic data; A first determining module is configured to determine a high cutoff frequency value and a main frequency value of the seismic data based on the seismic data; A second determining module is configured to determine a high cutoff value of the extended spectrum seismic data based on the extended spectrum seismic data; The third determination module is used to determine the main frequency value of the seismic wavelet based on the high cutoff value and main frequency value of the seismic data and the high cutoff value of the extended spectrum seismic data. The third determination module includes a first determination submodule and a second determination submodule. The first determination submodule is used to determine the difference between the high cutoff value of the extended spectrum seismic data and the high cutoff value of the seismic data; and the sum of 1 / 2 of the difference and the high cutoff value of the seismic data is determined as the main frequency value of the high frequency segment of the extended spectrum seismic data. The second determination submodule is used to divide the sum of the main frequency value of the high frequency segment of the extended spectrum seismic data and the main frequency value of the seismic data by 2 to determine the main frequency value of the seismic wavelet.

5. A device for generating synthetic seismic records, characterized in that The device comprises: A determination module, configured to determine the main frequency value of the seismic wavelet according to the method of claim 1 or 2; A generating module is used to generate a synthetic seismic record based on the main frequency value of the seismic wavelet, and the synthetic seismic record is used to perform horizon calibration on the actual seismic record corresponding to the extended spectrum seismic data.

6. A computer device, characterized in that: The computer device includes a processor and a memory; The memory is used to store a computer program; the processor is used to execute the computer program stored in the memory to implement the method according to claim 1 or 2, or to implement the method according to claim 3.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and when the stored computer instructions are executed by a processor, they can implement the method according to claim 1 or 2, or implement the method according to claim 3.

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