Coal seam thickness prediction method and device, storage medium and electronic equipment
By selecting the apparent time difference method, amplitude method, or wave impedance inversion method according to the coal seam thickness range, the problem of insufficient prediction accuracy when the coal seam thickness is less than λ/8 in the existing technology is solved, and higher accuracy coal seam thickness prediction is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2024-10-10
- Publication Date
- 2026-04-10
AI Technical Summary
Existing methods for predicting coal seam thickness are not accurate enough when the coal seam thickness is less than λ/8, especially when the coal seam thickness and seismic reflection amplitude are not linearly related.
Based on the range of coal seam thickness, a suitable prediction method is selected: when the thickness is greater than λ/4, the apparent time difference method is used; when the thickness is between λ/8 and λ/4, the amplitude method is used; and when the thickness is less than λ/8, the wave impedance inversion method is used. By obtaining wavelets of different lengths and amplitude values, a suitable prediction method is determined and prediction is performed.
It improves the accuracy of coal seam thickness prediction, expands the application range of the amplitude method, and accurately predicts coal seam thicknesses less than λ/8 using the wave impedance inversion method, significantly improving prediction accuracy.
Smart Images
Figure CN121831891A_ABST
Abstract
Description
Technical Field
[0001] This disclosure belongs to the field of coal and rock gas exploration technology, and in particular to a method, apparatus, storage medium and electronic equipment for predicting coal seam thickness. Background Technology
[0002] In coal resource exploration or coalbed methane development, the prediction of coal seam thickness is of great significance. Typically, coal seam thickness varies considerably laterally, and drilling statistics and interpolation cannot accurately reflect the inter-well coal seam thickness.
[0003] Currently, commonly used methods for predicting coal seam thickness using seismic data include the apparent time difference method and the amplitude method. Both methods are based on Widess's thin-layer theory, which states that when the coal seam thickness is greater than λ / 4 (λ being the length), the apparent time difference of the seismic reflection formed by the top and bottom interfaces of the coal seam is linearly related to the coal seam thickness, increasing with thickness. When the coal seam thickness is less than λ / 4, the seismic reflection amplitude increases with thickness, reaching its strongest when the thickness equals λ / 4. Using the relationship between seismic time difference, amplitude properties, and coal seam thickness, coal seam thicknesses greater than λ / 4 and less than or equal to λ / 4 can be calculated. Wang Jianqing et al. (2017) proposed that when the coal seam thickness is less than λ / 8, the coal seam thickness is linearly related to the seismic reflection amplitude, further extending the coal thickness tuning theory. Figure 1 Application of ).
[0004] Currently, the apparent time difference and amplitude method has been applied to practical work areas with good results, accurately reflecting the changing trend of coal seam thickness across the entire area (Hao Zhiguo et al., 2014). However, the accuracy of the coal seam thickness predicted by the above two methods is still insufficient, especially when the coal seam thickness is less than λ / 8. The claim that the coal seam thickness has a linear relationship with the seismic reflection amplitude is debatable. Research has found that... Figure 2), when the thickness of the coal seam is less than λ / 8, the thickness and the seismic reflection amplitude are not in a linear relationship, and even not a simple monotonic increasing relationship that the seismic reflection amplitude strength increases with the increase of the thickness of the coal seam. The specific reason is analyzed as follows: the coal thickness tuning theoretical model is a simple model based on the widess theory, which only considers the "upper, middle and lower three layers", that is, the overlying mudstone or sandstone, the middle coal seam and the underlying mudstone or sandstone. The lithological combination in the actual stratum is more complex, and there may be sand and mud interbedding above and below the coal seam. Since the coal seam is a special rock layer with low velocity and low density, the wave impedance difference between the coal seam and the surrounding rock is large, and strong reflection interfaces are easily formed at the top and bottom. When the coal seam is thick enough, the seismic reflection of the complex combination of the upper and lower layers has little effect on it; but when the thickness of the coal seam decreases to a certain extent, the effect gradually increases, at this time, it no longer follows the widess thin layer theory, therefore, it is not suitable to directly use the amplitude method to obtain the thickness of the coal seam less than λ / 8.
[0005] Therefore, how to improve the prediction accuracy of the existing coal seam thickness prediction method is a technical problem to be solved. SUMMARY
[0006] Therefore, it is necessary to provide a coal seam thickness prediction method, device, storage medium and electronic equipment aiming at the low prediction accuracy of the existing coal seam thickness prediction method.
[0007] In a first aspect, an embodiment of the present application provides a coal seam thickness prediction method, which comprises:
[0008] obtaining a first length λ1 of a first wavelet and a second length λ2 of a second wavelet;
[0009] predicting a thickness range of a to-be-predicted coal seam according to the first length λ1 and the second length λ2;
[0010] determining a target prediction method for predicting the thickness of the to-be-predicted coal seam according to the thickness range of the to-be-predicted coal seam;
[0011] predicting the thickness of the to-be-predicted coal seam based on the target prediction method to obtain a predicted thickness of the to-be-predicted coal seam.
[0012] Optionally, the target prediction method comprises a moveout method, an amplitude method and a wave impedance inversion method.
[0013] Optionally, the determining of the target prediction method for predicting the thickness of the to-be-predicted coal seam according to the thickness range of the to-be-predicted coal seam comprises:
[0014] if the thickness range of the to-be-predicted coal seam is greater than λ1 / 4, the target prediction method is determined as the moveout method; or
[0015] if the thickness of the coal seam to be predicted is greater than λ1 / 8 and less than or equal to λ1 / 4, determining that the target prediction method is the amplitude method; or
[0016] if the thickness of the coal seam to be predicted is greater than λ2 / 8 and less than λ1 / 8, determining that the target prediction method is the amplitude method; or
[0017] if the thickness of the coal seam to be predicted is less than λ2 / 8, determining that the target prediction method is the wave impedance inversion method.
[0018] Optionally, after the first length λ1 of the first wavelet is obtained, the method further comprises:
[0019] obtaining a first amplitude value X1 of a first coal seam thickness;
[0020] determining a first amplitude distribution range S1 of amplitude values less than the first amplitude value X1 on a first amplitude attribute plane.
[0021] Optionally, after the second length λ2 of the second wavelet is obtained, the method further comprises:
[0022] obtaining a second amplitude value X2 of a second coal seam thickness;
[0023] determining a second amplitude distribution range S2 of amplitude values less than the second amplitude value X2 on a second amplitude attribute plane.
[0024] Optionally, before the first length λ1 of the first wavelet is obtained, the method further comprises:
[0025] obtaining a first dominant frequency F1 of a target layer;
[0026] According to a well control method, the dominant frequency of the target layer is raised from the first dominant frequency F1 to a second dominant frequency F2.
[0027] Optionally, after the dominant frequency of the target layer is raised from the first dominant frequency F1 to the second dominant frequency F2, the method further comprises:
[0028] obtaining updated seismic data corresponding to the second dominant frequency F2;
[0029] According to the updated seismic data, a corresponding relationship between the coal seam thickness and the seismic reflection amplitude is determined.
[0030] In a second aspect, an embodiment of the present application provides a device for predicting a coal seam thickness, and the device comprises:
[0031] an obtaining module, configured to obtain a first length λ1 of a first wavelet and a second length λ2 of a second wavelet;
[0032] a first prediction module, configured to predict a thickness range of the coal seam to be predicted according to the first length λ1 and the second length λ2;
[0033] a determination module, configured to determine a target prediction method for predicting the thickness of the coal seam to be predicted according to the thickness range of the coal seam to be predicted;
[0034] a second prediction module, configured to predict the thickness of the coal seam to be predicted based on the target prediction method, to obtain a predicted thickness of the coal seam to be predicted.
[0035] Optionally, the determination module is specifically configured to:
[0036] if the thickness range of the coal seam to be predicted is greater than the target prediction method is determined as the apparent time difference method; or
[0037] if the thickness range of the coal seam to be predicted is greater than and less than or equal to the target prediction method is determined as the amplitude method; or
[0038] if the thickness range of the coal seam to be predicted is greater than and less than the target prediction method is determined as the amplitude method; or
[0039] if the thickness range of the coal seam to be predicted is less than the target prediction method is determined as the wave impedance inversion method.
[0040] In a third aspect, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. When the computer program is executed in a computer, the computer program causes the computer to execute the method in the first aspect.
[0041] In a fourth aspect, an electronic device is provided, and the electronic device includes a memory and a processor. The memory stores executable code, and the processor executes the executable code to implement the method in the first aspect.
[0042] In the embodiment of the present application, the first length λ1 of the first subwave is obtained, and the second length λ2 of the second subwave is obtained; the thickness range of the coal seam to be predicted is predicted according to the first length λ1 and the second length λ2; the target prediction method for predicting the thickness of the coal seam to be predicted is determined according to the thickness range of the coal seam to be predicted; and the thickness of the coal seam to be predicted is predicted based on the target prediction method to obtain the predicted thickness of the coal seam to be predicted. The prediction method for the thickness of the coal seam provided in the embodiment of the present application can accurately determine the target prediction method for predicting the thickness of the coal seam to be predicted according to the thickness range of the coal seam to be predicted, and predict the thickness of the coal seam to be predicted based on the target prediction method. Compared with a single prediction method, the prediction method can greatly improve the accuracy of the thickness of the coal seam. BRIEF DESCRIPTION OF DRAWINGS
[0043] The exemplary embodiments of this application can be more fully understood with reference to the following drawings in which:
[0044] Figure 1 is a schematic diagram of the thickness tuning effect of the coal seam in theory;
[0045] Figure 2 is a schematic diagram of the relationship between the thickness of the coal seam and the seismic amplitude intensity of the statistical well point in the work area;
[0046] Figure 3 is a flowchart of the prediction method for the thickness of the coal seam according to an exemplary embodiment of the present application;
[0047] Figure 4 is a coal seam seismic reflection root mean square amplitude plan;
[0048] Figure 5 is a schematic diagram of the well-controlled mixed phase subwave deconvolution processing of seismic data;
[0049] Figure 6 is a waveform indicating wave impedance inversion profile;
[0050] Figure 7 is a structural schematic diagram of the prediction device 700 for the thickness of the coal seam according to an exemplary embodiment of the present application. DETAILED DESCRIPTION
[0051] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.
[0052] It should be noted that the technical terms or scientific terms used in the present disclosure should be understood as their general meanings understood by those skilled in the art, unless otherwise specified.
[0053] In addition, the terms "first" and "second" and the like are used to distinguish different objects, rather than to describe a particular order. Furthermore, the terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or apparatus.
[0054] The present disclosure provides a coal seam thickness prediction method and device, a computer readable medium, and an electronic device, which will be described below with reference to the accompanying drawings.
[0055] Reference is made to Figure 3 which shows a flowchart of a coal seam thickness prediction method provided by some embodiments of the present disclosure, as shown in Figure 3 The coal seam thickness prediction method can include the following steps:
[0056] Step S301: Obtain a first length λ1 of a first wavelet, and obtain a second length λ2 of a second wavelet.
[0057] In an example, before obtaining the first length λ1, the first length λ1 needs to be determined first. The process of determining the first length λ1 can be: obtaining seismic data; analyzing the main frequency based on the seismic data to determine the main frequency F1 of the target layer; and based on the main frequency F1 of the target layer and the coal seam velocity v, the first length λ1 of the first wavelet is calculated and determined.
[0058] In an example, after obtaining the first length λ1 of the first wavelet, the prediction method provided by the embodiments of the present disclosure further includes the following steps:
[0059] Obtaining a first amplitude value X1 of the first coal seam thickness;
[0060] Determining a first amplitude distribution range S1 of the amplitude value less than the first amplitude value X1 on the first amplitude attribute plane.
[0061] In an actual application scenario, the first amplitude value X1 is read when the first coal seam thickness is Figure 2 The middle red trend line is drawn, and the first amplitude value X1 is read when the first coal seam thickness is The distribution range S1 of the amplitude value less than X1 is determined on the first amplitude attribute plane.
[0062] As shown in Figure 2 If the current coal seam thickness is less than The relationship between the coal seam thickness and the seismic amplitude intensity is not linear.
[0063] In an example, after the second length λ2 of the second wavelet is obtained, the prediction method provided by the embodiment of the present application further includes the following steps:
[0064] The second amplitude value X2 of the second coal seam thickness is obtained;
[0065] The second amplitude distribution range S2 of the amplitude value less than the second amplitude value X2 is determined on the second amplitude attribute plane.
[0066] In an actual application scenario, the second amplitude value X2 is read when the second coal seam thickness is The second amplitude distribution range S2 of the amplitude value less than the second amplitude value X2 is determined on the second amplitude attribute plane.
[0067] In an example, before the first length λ1 of the first wavelet is obtained, the prediction method provided by the embodiment of the present application further includes the following steps:
[0068] The first dominant frequency F1 of the target layer is obtained;
[0069] According to the well control method, the dominant frequency of the target layer is raised from the first dominant frequency F1 to the second dominant frequency F2; in this way, the resolution of the coal seam thin layer can be effectively improved.
[0070] In an example, after the dominant frequency of the target layer is raised from the first dominant frequency F1 to the second dominant frequency F2, the prediction method provided by the embodiment of the present application further includes the following steps:
[0071] The updated seismic data corresponding to the second dominant frequency F2 is obtained;
[0072] According to the updated seismic data, the corresponding relationship between the coal seam thickness and the seismic reflection amplitude is determined.
[0073] Step S302: predicting the thickness range of the coal seam to be predicted according to the first length λ1 and the second length λ2.
[0074] Step S303: determining the target prediction method for predicting the thickness of the coal seam to be predicted according to the thickness range of the coal seam to be predicted.
[0075] In an example, if the thickness of the coal seam to be predicted is greater than the target prediction method is determined to be the time migration method.
[0076] In another example, if the thickness of the coal seam to be predicted is greater than and less than or equal to the target prediction method is determined to be the amplitude method.
[0077] In yet another example, if the thickness of the coal seam to be predicted is greater than and less than the target prediction method is determined to be the amplitude method.
[0078] In another example, if the thickness of the coal seam to be predicted is less than the target prediction method is determined to be the wave impedance inversion method.
[0079] Step S304: Based on the target prediction method, the thickness of the coal seam to be predicted is predicted to obtain the predicted thickness of the coal seam to be predicted.
[0080] In this step S303, the target prediction method includes the time migration method, the amplitude method, and the wave impedance inversion method.
[0081] In an example, if the thickness of the coal seam to be predicted is greater than the target prediction method is determined to be the time migration method, and the thickness of the coal seam to be predicted is predicted based on the time migration method to obtain the predicted thickness of the coal seam to be predicted.
[0082] In another example, if the thickness of the coal seam to be predicted is greater than and less than or equal to the target prediction method is determined to be the amplitude method, and the thickness of the coal seam to be predicted is predicted based on the amplitude method to obtain the predicted thickness of the coal seam to be predicted.
[0083] In yet another example, if the thickness of the coal seam to be predicted is greater than and less than the target prediction method is determined to be the amplitude method, and the thickness of the coal seam to be predicted is predicted based on the amplitude method to obtain the predicted thickness of the coal seam to be predicted.
[0084] In another example, if the thickness of the coal seam to be predicted is less than the target prediction method is determined to be the wave impedance inversion method, and the thickness of the coal seam to be predicted is predicted based on the wave impedance inversion method to obtain the predicted thickness of the coal seam to be predicted.
[0085] The coal seam thickness prediction method provided in this invention adopts a step-by-step approach, predicting the coal seam thickness from large to small, and predicts the current coal seam thickness based on a prediction method that matches the current coal seam thickness, thereby greatly improving the accuracy of coal seam thickness prediction. The specific prediction method that matches the current coal seam thickness is described above and will not be repeated here.
[0086] In practical applications, the above-mentioned method for predicting coal seam thickness was applied in the Jurassic coal and gas exploration of the Baijiahai Uplift in Junggar. It accurately predicted the coal seam thickness and lateral variation trend, guided the sedimentary microfacies division, clarified the lithological trap type and hydrocarbon accumulation law, and provided an important basis for actual well location deployment.
[0087] The method for predicting coal seam thickness includes the following steps:
[0088] Step a1: Based on the well seismic calibration, conduct a detailed interpretation of the seismic reflection horizons at the coal seam top and bottom interfaces, and extract the root mean square amplitude along these horizons. Figure 4 ).
[0089] like Figure 4 As shown, the overall trend is: the stronger the amplitude, the thicker the coal seam; the blue area represents a thin coal seam.
[0090] Step a2: Calculate the relationship between the thickness of the coal seam at the drilled well points and the corresponding amplitude attributes.
[0091] Step a3: The dominant frequency of the target layer seismic data is determined to be 30 Hz by spectral analysis. The coal seam velocity is calculated to be 2400 m / s based on the well logging curves. The first length λ1 of the first wavelet is then determined to be 80 m. Figure 2 Statistical results show that when the coal seam thickness is less than approximately 10 meters... At that time, the traditional coal thickness tuning theory, which states that the amplitude increases with the coal seam thickness, no longer applies. Instead, the relationship between amplitude and coal seam thickness gradually becomes one-to-many.
[0092] Step a4: Based on the trend line fitted to the scatter plot, determine the amplitude attribute value corresponding to a coal seam thickness of 10 meters as 43, and determine the range S1 (less than 43) on the amplitude plane plot. Figure 4 (Middle blue section).
[0093] Step a5: Within the S1 range, perform well-controlled hybrid phase wavelet deconvolution processing on the seismic data. Figure 5 The main frequency was increased from 30 Hz to 40 Hz; the minimum coal seam thickness that can be accurately identified by the amplitude method was reduced from 10 meters to 7.5 meters.
[0094] like Figure 5 As shown, the dominant seismic frequency before processing was 30 Hz, and after well control improved the resolution, the dominant frequency increased to 40 Hz, which matches the synthetic record better.
[0095] Step a6: for the coal seam thickness within 7.5 meters, the waveform indication inversion technology is used for prediction, and the prediction accuracy can reach 2 meters. Figure 6 ).
[0096] The coal seam thickness prediction method provided by the embodiment of the present application can accurately determine the target prediction method for predicting the thickness of the coal seam to be predicted according to the thickness range of the coal seam to be predicted, and predict the thickness of the coal seam based on the target prediction method. Compared with a single prediction method, the prediction method can greatly improve the accuracy of the coal seam thickness.
[0097] In addition, the coal seam thickness prediction method provided by the embodiment of the present application determines the lowest lower limit value of the coal seam thickness that can be recognized by the amplitude method, thereby expanding the application range of the amplitude method and greatly improving the prediction accuracy of the coal seam thickness. Correspondingly, the coal seam thickness less than the lowest lower limit value can be predicted by using the wave impedance inversion method.
[0098] In the above embodiment, a coal seam thickness prediction method is provided, and the present application also provides a coal seam thickness prediction device. The coal seam thickness prediction device provided by the embodiment of the present application can implement the coal seam thickness prediction method described above. The coal seam thickness prediction device can be realized by software, hardware or a combination of software and hardware. For example, the coal seam thickness prediction device can include integrated or separate functional modules or units to perform the corresponding steps in the above methods.
[0099] Please refer to Figure 7 , which shows a coal seam thickness prediction device provided by some embodiments of the present application. Since the device embodiment is basically similar to the method embodiment, it is described more simply, and the related parts refer to the part of the method embodiment. The device embodiment described below is only illustrative.
[0100] As shown in Figure 7 , the coal seam thickness prediction device 700 can include:
[0101] The acquisition module 701 is configured to acquire the first length λ1 of the first wavelet and the second length λ2 of the second wavelet.
[0102] The first prediction module 702 is configured to predict the thickness range of the coal seam to be predicted according to the first length λ1 and the second length λ2.
[0103] The determination module 703 is configured to determine the target prediction method for predicting the thickness of the coal seam to be predicted according to the thickness range of the coal seam to be predicted.
[0104] The second prediction module 704 is used to predict the thickness of the coal seam to be predicted based on the target prediction method, and obtain the predicted thickness of the coal seam to be predicted.
[0105] In some embodiments of the present invention, the target prediction method includes: apparent time difference method, amplitude method and wave impedance inversion method.
[0106] In some embodiments of the present invention, the determining module 703 is specifically used for:
[0107] If the thickness range of the coal seam to be predicted is: greater than Then the target prediction method is determined to be the apparent time difference method; or,
[0108] If the thickness range of the coal seam to be predicted is: greater than and less than or equal to Then the target prediction method is determined to be the amplitude method; or,
[0109] If the thickness range of the coal seam to be predicted is: greater than and less than Then the target prediction method is determined to be the amplitude method; or,
[0110] If the thickness range of the coal seam to be predicted is: less than Therefore, the target prediction method is determined to be the wave impedance inversion method.
[0111] In some embodiments of the present invention, the coal seam thickness prediction device 700 provided in the present invention may further include:
[0112] The first amplitude distribution range determination module (in) Figure 7 (not shown in the figure) is used to obtain the first amplitude value X1 of the first coal seam thickness after obtaining the first length λ1 of the first wavelet; and to determine the first amplitude distribution range S1 on the first amplitude attribute plane where the amplitude value is less than the first amplitude value X1.
[0113] In some embodiments of the present invention, the coal seam thickness prediction device 700 provided in the present invention may further include:
[0114] The second amplitude distribution range determination module (in) Figure 7 (not shown in the figure) is used to obtain the second amplitude value X2 of the second coal seam thickness after obtaining the second length λ2 of the second wavelet; and to determine the second amplitude distribution range S2 on the second amplitude attribute plane where the amplitude value is less than the second amplitude value X2.
[0115] In some embodiments of the present invention, the coal seam thickness prediction device 700 provided in the present invention may further include:
[0116] Clock speed boosting module (in)Figure 7 (not shown in the diagram) is used to obtain the first dominant frequency F1 of the target layer before obtaining the first length λ1 of the first wavelet; according to the well control method, the dominant frequency of the target layer is increased from the first dominant frequency F1 to the second dominant frequency F2.
[0117] In some embodiments of the present invention, the coal seam thickness prediction device 700 provided in the present invention may further include:
[0118] The correspondence determination module (in) Figure 7 (Not shown in the image) is used to obtain updated seismic data corresponding to the second dominant frequency F2 after the dominant frequency of the target layer is increased from the first dominant frequency F1 to the second dominant frequency F2; and to determine the correspondence between coal seam thickness and seismic reflection amplitude based on the updated seismic data.
[0119] In some embodiments of the present invention, the coal seam thickness prediction device 700 provided in the present invention is based on the same inventive concept and has the same beneficial effects as the coal seam thickness prediction method provided in the foregoing embodiments of the present invention.
[0120] According to another embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed in a computer, causes the computer to perform a combination Figure 3 The method described.
[0121] According to another embodiment, an electronic device is also provided, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements a combination... Figure 3 The method described.
[0122] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium.
[0123] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for predicting coal seam thickness, characterized in that, The method includes: Obtain the first length λ1 of the first wavelet and the second length λ2 of the second wavelet; Based on the first length λ1 and the second length λ2, predict the thickness range of the coal seam to be predicted; Based on the thickness range of the coal seam to be predicted, a target prediction method for predicting the thickness of the coal seam to be predicted is determined; Based on the target prediction method, the thickness of the coal seam to be predicted is predicted to obtain the predicted thickness of the coal seam to be predicted.
2. The prediction method according to claim 1, characterized in that, The target prediction methods include: apparent time difference method, amplitude method and wave impedance inversion method.
3. The prediction method according to claim 2, characterized in that, The method for determining the target prediction method for predicting the thickness of the coal seam based on the thickness range of the coal seam to be predicted includes: If the thickness range of the coal seam to be predicted is: greater than Then the target prediction method is determined to be the time difference method; or, If the thickness range of the coal seam to be predicted is: greater than and less than or equal to Then the target prediction method is determined to be the amplitude method; or, If the thickness range of the coal seam to be predicted is: greater than and less than Then the target prediction method is determined to be the amplitude method; or, If the thickness range of the coal seam to be predicted is: less than Then the target prediction method is determined to be the wave impedance inversion method.
4. The prediction method according to claim 1, characterized in that, After obtaining the first length λ1 of the first wavelet, the method further includes: Obtain the first amplitude value X1 of the first coal seam thickness; On the first amplitude attribute plane, a first amplitude distribution range S1 with an amplitude value less than the first amplitude value X1 is determined.
5. The prediction method according to claim 1, characterized in that, After obtaining the second length λ2 of the second wavelet, the method further includes: Obtain the second amplitude value X2 of the second coal seam thickness; On the second amplitude attribute plane, determine a second amplitude distribution range S2 where the amplitude value is less than the second amplitude value X2.
6. The prediction method according to claim 1, characterized in that, Before obtaining the first length λ1 of the first wavelet, the method further includes: Obtain the first main frequency F1 of the target layer; According to the well control method, the main frequency of the target layer is increased from the first main frequency F1 to the second main frequency F2.
7. The prediction method according to claim 6, characterized in that, After increasing the target layer's clock frequency from the first clock frequency F1 to the second clock frequency F2, the method further includes: Obtain the updated seismic data corresponding to the second dominant frequency F2; Based on the updated seismic data, the correspondence between coal seam thickness and seismic reflection amplitude was determined.
8. A device for predicting coal seam thickness, characterized in that, The device includes: The acquisition module is used to acquire the first length λ1 of the first wavelet and the second length λ2 of the second wavelet; The first prediction module is used to predict the thickness range of the coal seam to be predicted based on the first length λ1 and the second length λ2. The determination module is used to determine a target prediction method for predicting the thickness of the coal seam to be predicted based on the thickness range of the coal seam to be predicted. The second prediction module is used to predict the thickness of the coal seam to be predicted based on the target prediction method, so as to obtain the predicted thickness of the coal seam to be predicted.
9. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method described in any one of claims 1 to 7.
10. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores executable code, and the processor executes the executable code to implement the method according to any one of claims 1 to 7.