Method and device for calculating a quality factor of a formation medium

Abstract

The embodiment of the application provides a quality factor calculation method and device of stratum medium, and belongs to the technical field of seismic exploration. The method comprises the following steps: obtaining simulated seismic wave experimental data based on a single-well micro-logging model, determining a proportional coefficient of the simulated seismic wave on different propagation paths according to the experimental data, and then establishing a calculation formula with the layer quality factor of each sub-layer as an unknown variable according to the proportional coefficient and the experimental data; in the process of solving the calculation formula to obtain the quality factor of the stratum medium, the calculation error caused by the inconsistency of the simulated seismic wave excitation wavelet and the geophone coupling effect is eliminated through the proportional coefficient, so that the calculation result precision of the quality factor calculation after the simulated seismic wave observation experiment is performed on the single-well micro-logging is improved, and the experimental result is optimized.

Description

Technical Field

[0001] This application relates to the field of seismic exploration technology, and in particular to a method, apparatus, electronic device, and computer-readable storage medium for calculating the quality factor of a formation medium. Background Technology

[0002] Simulated seismic waves are a commonly used technique in geological exploration. They are generated artificially from different angles, and the reflected wave data are collected. Multi-dimensional modeling is then used to analyze the geological structure of the target area. Among these parameters, the quality factor is a crucial parameter that quantitatively describes the ability of the formation medium to absorb and attenuate simulated seismic waves. It is of great significance for the analysis, calculation, compensation, and improvement of seismic data resolution.

[0003] In related technologies, the quality factor is generally obtained by micrologging observation. Commonly used observation models include single-well micrologging model, dual-well micrologging model, and well-ground combined micrologging model. Micrologging is drilled in a certain area through earthwork operations, and then corresponding excitation points are set to emit simulated seismic waves, which are received by detectors located at the receiver points.

[0004] However, in the existing technical solutions, the experimental method using a single-well micro-logging model has technical defects such as inconsistency in the excitation wavelet of simulated seismic waves and the coupling effect of the detector, which leads to low results in calculating the formation quality factor based on the acquired observation data. Summary of the Invention

[0005] This application provides a method and apparatus for calculating the quality factor of a formation medium, in order to solve the problem of insufficient accuracy of experimental results obtained by single-well micrologging models in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for calculating the quality factor of a formation medium, the method comprising:

[0007] The experimental data of the simulated seismic wave observation model are obtained. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave.

[0008] The proportionality coefficients of the simulated seismic waves on each propagation path are determined based on the experimental data. The propagation path is determined by the relative position of the excitation point and the receiver point.

[0009] Based on the aforementioned proportionality coefficient and the aforementioned experimental data, a calculation formula is established with the stratification quality factor of each sub-stratum as the unknown variable.

[0010] In the process of solving the formula to obtain the quality factor of the formation medium, the scaling factor is used to eliminate the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

[0011] Secondly, embodiments of this application provide a device for calculating the quality factor of a formation medium, the device comprising:

[0012] The acquisition module is used to acquire experimental data of a simulated seismic wave observation model. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave.

[0013] The scaling factor determination module is used to determine the scaling factor of the simulated seismic wave on each propagation path based on the experimental data, wherein the propagation path is determined by the relative position of the excitation point and the receiver point;

[0014] The calculation formula acquisition module establishes a calculation formula with the stratification quality factor of each sub-stratum as the unknown variable based on the proportional coefficient and the experimental data.

[0015] The quality factor determination module is used to eliminate calculation errors caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector through the scaling factor in the process of solving the calculation formula to obtain the quality factor of the formation medium. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

[0016] Thirdly, embodiments of this application provide an electronic device, including: a processor;

[0017] Memory used to store the processor's executable instructions;

[0018] The processor is configured to execute the instructions to implement the method.

[0019] Fourthly, embodiments of this application provide a computer-readable storage medium that, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform the method.

[0020] In this embodiment, after obtaining experimental data of simulated seismic waves based on a single-well micrologging model, the scaling factor of the simulated seismic waves on different propagation paths is first determined according to the experimental data. Then, a calculation formula is established with the layered quality factor of each sub-stratum as the unknown variable, based on the scaling factor and the experimental data. In the process of solving the calculation formula to obtain the quality factor of the formation medium, the scaling factor is used to eliminate the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector, thereby improving the accuracy of the calculation results of the quality factor after the simulated seismic wave observation experiment based on single-well micrologging and optimizing the experimental results.

[0021] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0022] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0023] Figure 1 This is a simplified flowchart of the implementation steps of a method for calculating the quality factor of a formation medium provided in an embodiment of this application;

[0024] Figure 2 This is a schematic diagram of data acquisition for a single-well micro-logging observation system provided in an embodiment of this application;

[0025] Figure 3 This is a schematic diagram of a common excitation point gather for simulating seismic waves provided in an embodiment of this application;

[0026] Figure 4 This is a complete implementation flowchart of a method for calculating the quality factor of a formation medium provided in this application embodiment;

[0027] Figure 5 This is a graph showing the relationship between surface depth and layer velocity of single-well micrologging data provided in an embodiment of this application;

[0028] Figure 6 This is a schematic diagram showing the comparison between layer quality factor and layer depth provided in the embodiments of this application;

[0029] Figure 7 This is a comparison chart of the effects of ground seismic data compensation processing provided in an embodiment of this application;

[0030] Figure 8 This is a schematic diagram of the functional modules of a device for calculating the quality factor of a formation medium provided in an embodiment of this application;

[0031] Figure 9 This is a functional component relationship diagram of an electronic device provided in an embodiment of this application;

[0032] Figure 10 This is a functional component relationship diagram of another electronic device provided in the embodiments of this application. Detailed Implementation

[0033] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0034] Reference Figure 1 , Figure 1 This is a simplified flowchart illustrating the implementation steps of a method for calculating the quality factor of a formation medium, as provided in an embodiment of this application. Figure 1 As shown, the steps of the method include:

[0035] Step 101: Obtain experimental data of the simulated seismic wave observation model. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave.

[0036] This application provides a method for calculating the quality factor of a formation medium, which is applied to a single-well micrologging observation model for simulated seismic waves. The method involves drilling a micrologging well in a certain area through earthwork operations, setting corresponding excitation points in the well to emit simulated seismic waves, and receiving the seismic waves through a geophone located at the receiver point.

[0037] Specific references Figure 2 This diagram illustrates a data acquisition schematic of a single-well micrologging observation system provided in an embodiment of this application. Figure 2 As shown, in the observation well set perpendicular to the ground, multiple excitation points, A1-A8, are arranged at regular intervals from shallow to deep to generate simulated seismic waves. Multiple receiver points, B1-B5, are set near the surface location of the observation wellhead to house geophones for receiving and recording the generated simulated seismic wave signals.

[0038] As described in step 101, in actual testing applications, whenever a simulated seismic wave is generated at the excitation point, the observation model generates an experimental data record for that excitation point. Correspondingly, whenever a receiver point receives the generated simulated seismic wave, it also generates an experimental data record for that excitation point. It should be noted that in... Figure 1 When a simulated seismic wave is emitted from any excitation point, a receiver point on the Earth's surface will receive the signal. The propagation path from the excitation point to the receiver point is called the channel. For example... Figure 1 As shown, the channel between excitation point A4 and detector point B2 is L1, and the channel between excitation point A7 and detector point B2 is L2.

[0039] Simultaneously, one excitation point can correspond to multiple detector points to generate multiple channels. (Refer to...) Figure 3 This illustration shows a common excitation point gather diagram of simulated seismic waves provided in an embodiment of this application. Signals emitted from the same excitation point correspond to 5 different channels, and waveforms are recorded under channels marked 1-5. Testers can selectively use the channel data according to test requirements.

[0040] Step 102: Determine the proportionality coefficients of the simulated seismic waves on each propagation path based on the experimental data. The propagation path is determined by the relative position of the excitation point and the receiver point.

[0041] This application provides a method for calculating the quality factor of a formation medium, which mainly addresses the problem in existing technologies for calculating the quality factor based on experimental data under a single-well micrologging observation model. This problem arises from the inconsistency of the excitation wavelet of simulated seismic waves and the coupling effect of the detector, leading to multiple solutions and decreased accuracy in the calculation results. Therefore, this solution improves the spectral ratio method to eliminate the computational impact caused by the inconsistency of the excitation wavelet and the coupling effect of the detector.

[0042] Since geological strata can be divided into multiple sub-strata due to different burial depths, this application introduces a proportional coefficient (or linear fitting coefficient) to eliminate the inconsistency of excitation wavelet and the coupling effect of the detector when calculating experimental data of different sub-strata. After eliminating the errors caused by the above-mentioned force majeure during the propagation of seismic waves in each sub-strata, the quality factor of the stratum medium is recalculated.

[0043] Specifically, this application analyzes experimental data from different seismic wave excitation and receiver points, simulates the propagation velocity of seismic waves in different geological strata, and calculates the propagation time of seismic waves on the surface of different geological layers using a conventional ray tracing algorithm. Then, it performs frequency domain transformation analysis based on the Futterman attenuation model and obtains the scaling factor after fitting.

[0044] Step 103: Based on the proportional coefficient and the experimental data, establish a calculation formula with the stratification quality factor of each sub-stratum as the unknown variable.

[0045] Following step 102, after obtaining the proportion coefficients of each sub-stratum, multiple sets of excitation points and receiver points are selected based on experimental data, and the propagation time of seismic waves at different strata surfaces is calculated according to the above method, to establish a calculation formula including propagation time, stratification quality factor and proportion coefficient.

[0046] In this embodiment of the application, the calculation formula is specifically a system of single-unknown-variable equations comprising multiple equations. Since only the stratification quality factor is an unknown variable among the calculation parameters in each equation, and the total number of stratification quality factors is equal to the number of strata, the least squares solution of the overdetermined system of equations, which has more equations than unknowns, can be obtained using the least squares method. That is, the specific value of the quality factor of the formation medium.

[0047] Specifically, in the implementation scheme of this application, an equation can be established by arbitrarily selecting two excitation points and two receiver points from the observation data of a single-well micrologging. For an observation model with M seismic wave excitation points, a total of [number] equations can be obtained. (Combined calculation formula) There are several ways to combine excitation points. Similarly, for an observation model with N seismic receivers, a total of... Various receiver point combinations can be used. This allows for the establishment of a system with a total number equal to... There are several equations, and these equations can form an overdetermined system of equations.

[0048] It is worth noting that the number of equations obtained by this method will significantly exceed the number of strata (generally, the number of strata in a plan is around 3). Therefore, when performing the equation system calculation, it is also possible to choose not to apply all the equations. Some of the excitation points in the M excitation points and some of the detector points in N can be used in the calculation. Testers can appropriately remove points with unstable data according to the actual situation to ensure the accuracy of the results.

[0049] Step 104: In the process of solving the calculation formula to obtain the quality factor of the formation medium, the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector is eliminated by the scaling factor. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

[0050] Because of the viscoelasticity of the geological strata, seismic wave amplitude attenuation, dominant frequency reduction, bandwidth narrowing, and phase delay can occur, thereby reducing the resolution of seismic data. Surface layers, characterized by shallow burial, severe weathering and erosion, loose structure, and poor compaction, exhibit even more severe absorption and attenuation of seismic waves, becoming one of the main factors limiting the improvement of seismic data resolution. Therefore, solving for the quality factor Q, a crucial parameter for quantitatively describing seismic wave absorption and attenuation, and performing effective compensation processing on seismic data, is of great significance for improving seismic data resolution.

[0051] The method for calculating the quality factor of formation media provided in this application, after obtaining the scaling factor based on the observation system, analyzes the propagation time of the source wavelet generated at each excitation point in the experimental data to the detector point, transforms the amplitude spectrum into a frequency domain spectrum, and then performs a linear combination transformation. This process eliminates the influence of source wavelet inconsistencies on the calculation results. Simultaneously, spectral ratio calculation is performed on the frequency domain spectrum to eliminate the influence of detector coupling effects, thus eliminating the calculation errors caused by the above two factors in the quality factor calculation.

[0052] In summary, the method for calculating the quality factor of a formation medium provided in this application involves, after obtaining experimental data of simulated seismic waves based on a single-well micrologging model, first determining the scaling factor of the simulated seismic waves along different propagation paths based on the experimental data. Then, based on the scaling factor and the experimental data, a calculation formula is established with the layered quality factor of each sub-stratum as the unknown variable. In the process of solving the calculation formula to obtain the quality factor of the formation medium, the scaling factor eliminates the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic waves and the coupling effect of the detector, thereby improving the accuracy of the settlement result of the quality factor calculation after conducting simulated seismic wave observation experiments using single-well micrologging and optimizing the experimental results.

[0053] Reference Figure 4 , Figure 4 This is a complete flowchart of the implementation steps of a method for calculating the quality factor of a formation medium provided in an embodiment of this application. Figure 4 As shown, the steps of the method include:

[0054] Step 201: Obtain experimental data of the simulated seismic wave observation model. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave.

[0055] For details of this step, please refer to step 101 above. This embodiment will not repeat the details here.

[0056] In an optional embodiment, step 201 may specifically include:

[0057] Sub-step 2011: Based on the arrival time and relative position recorded in the experimental data, determine the number of sub-strata of the formation medium, the layer velocity of each sub-strata, and the layer thickness.

[0058] Experimental data based on a single-well micrologging observation model recorded the first arrival time and first arrival wavelet of simulated seismic waves from different excitation points to receiver points. The first arrival time characterizes the moment when the receiver first detects the proton vibration of the simulated seismic wave in the simulated seismic wave observation model. The first arrival wavelet is the first periodic signal extracted from the simulated seismic wave record received by the receiver after the first arrival time. During the construction of the single-well micrologging system, the specific burial depth was determined manually according to construction requirements, and the model's burial depth range was divided into multiple sub-strata.

[0059] Reference Figure 5 This diagram illustrates the relationship between surface depth and layer velocity in single-well micrologging data provided in an embodiment of this application. Figure 5 As shown, this includes the layer velocities of three different burial depths, V1-V3. Here, layer velocity represents the propagation speed of simulated seismic waves within that layer. V1 = 341 m / s, V2 = 413 m / s, V3 = 2213 m / s. For the layer thickness at which the layer velocity changes, the first layer H1 = 2.12 m, the second layer H2 = 5.13 m. It should be noted that... Figure 5 The relationship between surface depth and layer velocity shown in the observation data is the same as that between the two layers. Figure 2 The experimental results obtained from the observation model shown.

[0060] Sub-step 2012: Obtain the amplitude spectrum and vibration frequency of the simulated seismic wave through the experimental data.

[0061] Following sub-step 2011, randomly select two excitation points and the four seismic wave records received by the corresponding receiver points from the experimental data of single-well micro-logging (a transmission channel can be formed between a single excitation point and two receiver points), and extract a periodic signal after the first arrival time of the simulated seismic wave record as the first arrival wavelet.

[0062] By performing frequency domain transformation analysis (such as Fourier transform) on the time-domain waveform of the first arrival wavelet, the amplitude spectrum can be obtained. This spectrum specifically characterizes which fixed-frequency waveforms the first arrival wavelet is composed of, as well as the corresponding amplitude values ​​at each vibration frequency. Thus, the amplitude spectrum and vibration frequency of the simulated seismic wave can be obtained.

[0063] Optionally, sub-step 2012 may specifically include:

[0064] Sub-step 20121: Select any two excitation points from the first number of excitation points to form an excitation point data group, and select any two receiver points from the second number of seismic receiver points to form a receiver point data group.

[0065] In the single-well micrologging observation model provided in this application embodiment, it is assumed that a total of M excitation points and N detector points are set. M actually corresponds to the first quantity, and N corresponds to the second quantity.

[0066] It should be noted that the selected excitation point data set can be a subset of the M excitation points, and the detector point data set can be a subset of the N detector points. Testers can appropriately remove unstable data points according to the actual situation to ensure the accuracy of the results.

[0067] Sub-step 20122: Obtain multiple simulated seismic wave records between the excitation point data group and the detector point data group.

[0068] Following sub-step 20121, two excitation points are randomly selected from the M excitation points to form an excitation point data group, and two receiver points are randomly selected from the N receiver points to form a receiver point data group. According to the selection relationship described in sub-step 2012, a total of four seismic wave records can exist between the two excitation points and their corresponding receiver points.

[0069] Sub-step 20123: Extract multiple first arrival waves from multiple simulated seismic wave records, and obtain multiple amplitude spectra and multiple vibration frequencies of the multiple first arrival waves.

[0070] By performing a frequency domain transformation on the first arrival wavelet, the amplitude spectrum of the first arrival wavelet can be obtained. Specifically, a conventional Fourier transform can be used to characterize which fixed frequency waveforms the first arrival wavelet is composed of, and the corresponding amplitude values ​​at each vibration frequency. This yields the amplitude spectrum and vibration frequency of the simulated seismic wave.

[0071] Step 202: Based on the layer velocity and layer thickness, determine the propagation time of the simulated seismic wave in each sub-layer using a ray tracing algorithm.

[0072] The propagation distance of simulated seismic waves within a specific geological stratum can be determined from the layer velocities recorded in the experimental data and the relative positions between each excitation point and receiver point. This can be achieved using the following formula:

[0073] t i,j,k =l i,j,k / v k (1)

[0074] The propagation time of the seismic wave received by each detector point in each sub-stratum can be obtained, where i = 1, 2, ..., M is the excitation point sequence number, and j = 1, 2, ..., N is the channel number corresponding to the detector point.

[0075] Step 203: Perform frequency domain transformation on the amplitude spectrum using the Fordman attenuation model to obtain multiple frequency domain transformation expressions for the first arrival wavelet. The calculation parameters of the frequency domain transformation expressions include the propagation time.

[0076] Specifically, according to the Fordman attenuation model, the frequency domain expression of the first arrival wavelet signal of the seismic wave received by the ground detector is:

[0077]

[0078] Where f is the vibration frequency, i is the excitation point number, j is the detector point channel number, and S i(f) R is the source wavelet spectrum generated at the i-th excitation point. i,j (f) represents the spectrum of the first arrival wave of the seismic signal excited at the i-th excitation point and received at the j-th receiver point, G. i,j C represents the frequency-independent attenuation of the source wavelet generated at the i-th excitation point as it propagates to the j-th receiver point. j (f) represents the sum of the response factors of the j-th detector point, including its own response characteristics and coupling effects. i,j Q represents the number of surface layers traversed by the source wavelet generated at the i-th excitation point as it propagates to the j-th receiver point. k Let t be the quality factor value of the k-th surface layer. i,j,k The time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th receiver point and then to the surface of the k-th layer.

[0079] According to the above formula, select a set of excitation points from the experimental data as the excitation point data set, i.e., the corresponding excitation point i and excitation point i-1, and a set of detector points as the detector point data set, i.e., the corresponding detector point j and detector point j-1, and establish the frequency domain transformation relationship:

[0080]

[0081]

[0082]

[0083]

[0084] Step 204: Establish a frequency domain relationship expression for the vibration frequency based on the multiple frequency domain transformation expressions. The frequency domain relationship expression is a linear function with the vibration frequency as the independent variable and the frequency domain value as the target value.

[0085] Following step 203, the frequency domain relation expression for the vibration frequency can be obtained by performing linear elementary transformations on the transformation expressions (2)-(6) established by the selected excitation point and detector point.

[0086] Specifically, by dividing formula (3) by formula (4), we have:

[0087]

[0088] Dividing formula (5) by formula (6) gives:

[0089]

[0090] It should be noted that the influence of source wavelet inconsistency was eliminated in this process through formulas (7) and (8).

[0091] Furthermore, by dividing formula (7) by formula (8), we have:

[0092]

[0093] Here, the effect of detector coupling is eliminated by formula (9).

[0094] Taking the logarithm of both sides of equation (9), we can obtain the frequency domain expression for the vibration frequency:

[0095]

[0096] in, This equation is a function of the vibration frequency f, where G is a known constant, and the constant π is the ratio of π to π. The product of the parts is the proportionality coefficient K of the function.

[0097] Step 205: Obtain the function curve of the frequency domain relation expression, and determine the proportionality coefficient based on the slope of the function curve.

[0098] Following step 205 above, the frequency domain relationship expression is plotted as a function graph. The scaling factor K can be directly obtained from the angle of inclination of the function curve relative to the horizontal line. When the angle of inclination of the function curve is θ, the scaling factor K is the tangent of the angle of inclination, i.e., K = tanθ.

[0099] Step 206: Establish multiple frequency domain relation expressions with a total of a third quantity. The frequency domain relation expressions are calculation equations with propagation time and scaling factor as known variables and the layer quality factor as unknown variables. The propagation time is used to characterize the propagation time of simulated seismic waves through each sub-layer. The third quantity is determined by the first quantity and the second quantity.

[0100] Referring to steps 203-204 above, and following the calculation process of formulas (3) to (10), different excitation and detection points are selected sequentially from the numerical research data to form experimental groups. Continue referring to... Figure 1 The distribution of points in the data can be illustrated as follows: For example, in the first case, A4+A5 are selected as the excitation point data group, and B2+B3 are selected as the detector point data group. After the calculation process of formulas (3) to (10), a linear function expression (frequency domain relationship expression) about f can be obtained. In the second case, A5+A6 can be selected as the excitation point data group, and B3+B4 can be selected as the detector point data group. After the calculation process of formulas (3) to (10), another linear function expression about f can be obtained. This process continues until the upper limit of the combination types that M and N can achieve is reached.

[0101] In the implementation scheme of this application, an equation can be established by arbitrarily selecting two excitation points and two receiver points from the observation data of a single-well micrologging. For an observation model with M seismic wave excitation points, a total of [number] equations can be obtained. (Combined calculation formula) There are several ways to combine excitation points. Similarly, for an observation model with N seismic receivers, a total of... Various receiver point combinations can be used. This allows for the establishment of a system with a total number equal to... An expression.

[0102] In an optional embodiment, sub-step 206 may specifically include:

[0103] Sub-step 2061: Perform spectral ratio calculation on multiple frequency domain transformation expressions to obtain spectral ratio calculation results, wherein the spectral ratio calculation results are equations including the frequency domain values ​​and the layered quality factors.

[0104] Referring to step 204 above, the frequency domain relationship expression established by formula (2) is subjected to three spectral ratio calculations. Specifically, the first spectral ratio calculation is performed by dividing formula (3) by formula (4), the second spectral ratio calculation is performed by dividing formula (5) by formula (6), and the third spectral ratio calculation is performed by dividing formula (7) by formula (8).

[0105] Sub-step 2062: Perform linear fitting on the spectral ratio calculation result to obtain the frequency domain relationship expression.

[0106] After performing a linear fit and inverse transformation on the logarithmic operation of the spectral ratio calculation result (formula (10)), the equation including the frequency domain value and the stratified quality factor can be obtained:

[0107]

[0108] Where L is the number of strata, Q k K is used to represent the quality factor of the k-th layer. m The scaling factor is determined by the i-th and (i-1)-th excitation points, and the j-th and (j-1)-th receiver points; t i-1,j,k t is the time taken for the source wavelet generated by the (i-1)th excitation point to propagate to the surface of the kth layer at the jth receiver point. i-1,j-1,k t is the time t takes for the source wavelet generated by the (i-1)th excitation point to propagate to the (j-1)th receiver point at the surface of the kth layer. i,j-1,k t is the time taken for the source wavelet generated by the i-th excitation point to propagate to the surface of the k-th layer at the (j-1)-th receiver point. i,j,k The time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th receiver point and then to the surface of the k-th layer.

[0109] It should be noted that K m It is determined by the two sets of excitation and detection points in the experimental data used in each calculation. (Continue referring to...) Figure 2 In this embodiment of the application, when calculating the above frequency domain relationship expression in a single operation, the propagation path between the i-th and (i-1)-th excitation points and the j-th and (j-1)-th receiver points is selected to form a "two-shot, two-track" observation data set. For example... Figure 2 The propagation paths L1 and L2 in the equation. The specific value of m is the same as the number of established frequency domain relation expressions, that is...

[0110] Step 207: Combine multiple frequency domain relation expressions to obtain the calculation formula, which is a system of equations constructed from multiple frequency domain relation expressions with a total number equal to the third number.

[0111] By obtaining different sets of excitation point data and sets of detector point data By simultaneously solving formula (11), an overdetermined system of equations can be established. The number of equations in the system is determined by the specific values ​​of M and N. The number of unknowns in the system is L (the number of strata). Since the number of equations is greater than the number of unknowns, this system of equations is overdetermined. The least squares solution of this system of equations can be obtained using the least squares method.

[0112] Reference Figure 6 This illustrates a schematic diagram comparing the layer quality factor and layer depth provided in an embodiment of this application. For example... Figure 6 As shown, the stratification quality factor Q changes accordingly with the change in surface depth.

[0113] Step 208: In the process of solving the calculation formula to obtain the quality factor of the formation medium, the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector is eliminated by the scaling factor. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

[0114] For details of this step, please refer to step 104 above. This embodiment will not repeat the details here.

[0115] It should be noted that the quality factor of the formation medium calculated through the embodiments of this application plays an important role in subsequent calculation and compensation processing for ground earthquakes. (Refer to...) Figure 7 The image shows a comparison of the effects of ground seismic data compensation processing provided in an embodiment of this application. Figure 7 As shown, this paper mainly illustrates the changes in time migration profiles and spectral parameters of seismic wave data before and after compensation calculation using the quality factor obtained through the embodiment of this application. After compensation by the quality factor calculation, the dominant frequency of the seismic data increases, and the frequency band widens from 68Hz to 83Hz, resulting in a significant improvement in the quality of the seismic data.

[0116] In summary, the method for calculating the quality factor of a formation medium provided in this application, after obtaining simulated seismic wave experimental data based on a single-well micrologging model, firstly determines the relative positional relationship between each excitation point and receiver point, the number of excitation and receiver points, the first arrival time, and the first arrival wavelet based on the experimental data, and then calculates the surface layer velocity, thickness, and number of layers. The propagation time of the seismic wave received at each receiver point in each surface layer is calculated using a conventional ray tracing algorithm. Based on this, four seismic wave records are randomly selected from the micrologging records, consisting of two excitation points and their corresponding two identical receiver points. A periodic signal after the first arrival time of the seismic wave record is extracted as the first arrival wavelet. The amplitude spectrum and cubic spectral ratio of the four first arrival waves are calculated, and the logarithm and frequency are fitted to obtain the proportionality coefficient K that eliminates the inconsistency of the excitation wavelet and the influence of receiver coupling. m Then, based on the scaling factor and the Fordman attenuation model, as well as the experimental data, a calculation formula was established with the stratified quality factor of each sub-stratum as the unknown variable. In the process of solving the calculation formula to obtain the quality factor of the formation medium, the scaling factor was used to eliminate the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector, thereby improving the accuracy of the calculation results of the quality factor after the simulated seismic wave observation experiment with single-well micro-logging and optimizing the experimental results.

[0117] Reference Figure 8 This diagram illustrates the functional module composition of a formation medium quality factor calculation device provided in an embodiment of this application. Figure 8 As shown, the device includes:

[0118] The acquisition module is used to acquire experimental data of a simulated seismic wave observation model. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave.

[0119] The scaling factor determination module is used to determine the scaling factor of the simulated seismic wave on each propagation path based on the experimental data, wherein the propagation path is determined by the relative position of the excitation point and the receiver point;

[0120] The calculation formula acquisition module establishes a calculation formula with the stratification quality factor of each sub-stratum as the unknown variable based on the proportional coefficient and the experimental data.

[0121] The quality factor determination module is used to eliminate calculation errors caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector through the scaling factor in the process of solving the calculation formula to obtain the quality factor of the formation medium. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

[0122] Optionally, the acquisition module further includes:

[0123] The first acquisition submodule is used to determine the number of sub-strata, the layer velocity and the layer thickness of each sub-strata based on the arrival time and relative position recorded in the experimental data.

[0124] The second acquisition submodule is used to acquire the amplitude spectrum and vibration frequency of the simulated seismic wave through the experimental data.

[0125] Optionally, the second acquisition submodule further includes:

[0126] The data group determination unit is used to sequentially select any two excitation points from the first number of excitation points to form an excitation point data group, and select any two receiver points from the second number of seismic receiver points to form a receiver point data group.

[0127] A seismic wave record acquisition unit is used to acquire multiple simulated seismic wave records between the excitation point data group and the receiver point data group;

[0128] The first arrival wavelet parameter acquisition unit is used to extract multiple first arrival waveslets from multiple simulated seismic wave records and acquire multiple amplitude spectra and multiple vibration frequencies of the multiple first arrival waveslets.

[0129] Optionally, the scaling factor determination module further includes:

[0130] The propagation time determination submodule is used to determine the propagation time of simulated seismic waves in each sub-layer using a ray tracing algorithm, based on the layer velocity and layer thickness.

[0131] The frequency domain transformation expression determination submodule is used to perform frequency domain transformation on the amplitude spectrum through the Fordman attenuation model to obtain multiple frequency domain transformation expressions for the first arrival wavelet. The calculation parameters of the frequency domain transformation expressions include the propagation time.

[0132] The frequency domain relation expression determination submodule is used to establish a frequency domain relation expression about the vibration frequency based on multiple frequency domain transformation expressions. The frequency domain relation expression is a linear function with the vibration frequency as the independent variable and the frequency domain value as the target value.

[0133] The scaling factor determination submodule is used to obtain the function curve of the frequency domain relationship expression and determine the scaling factor based on the slope of the function curve.

[0134] Optionally, the calculation formula acquisition module further includes:

[0135] The frequency domain relation expression construction submodule is used to establish multiple frequency domain relation expressions with a total number of three. The frequency domain relation expressions are calculation equations with propagation time and scale coefficient as known variables and the layer quality factor as unknown variables. The propagation time is used to characterize the propagation time of simulated seismic waves through each sub-layer. The third number is determined by the first number and the second number.

[0136] The calculation formula construction submodule is used to combine multiple frequency domain relational expressions to obtain the calculation formula, which is a system of equations constructed from multiple frequency domain relational expressions with a total number equal to a third number.

[0137] In summary, the formation medium quality factor calculation device provided in this application, after acquiring simulated seismic wave experimental data based on a single-well micrologging model, first determines the scaling factor of the simulated seismic wave on each propagation path according to the experimental data. Then, based on the scaling factor and the experimental data, a calculation formula is established with the layered quality factor of each sub-layer as the unknown variable. In the process of solving the calculation formula to obtain the formation medium quality factor, the scaling factor eliminates the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector, thereby improving the accuracy of the calculation results of the quality factor calculation after the simulated seismic wave observation experiment using single-well micrologging and optimizing the experimental results.

[0138] Figure 9This is a block diagram illustrating an electronic device 600 according to an exemplary embodiment. For example, the electronic device 600 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0139] Reference Figure 9 The electronic device 600 may include one or more of the following components: a processing component 602, a memory 604, a power supply component 606, a multimedia component 608, an audio component 610, an input / output (I / O) interface 612, a sensor component 614, and a communication component 616.

[0140] Processing component 602 typically controls the overall operation of electronic device 600, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 602 may include one or more processors 620 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 602 may include one or more modules to facilitate interaction between processing component 602 and other components. For example, processing component 602 may include a multimedia module to facilitate interaction between multimedia component 608 and processing component 602.

[0141] Memory 604 is used to store various types of data to support the operation of electronic device 600. Examples of such data include instructions for any application or method operating on electronic device 600, contact data, phonebook data, messages, pictures, multimedia, etc. Memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0142] Power supply component 606 provides power to various components of electronic device 600. Power supply component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 600.

[0143] Multimedia component 608 includes a screen that provides an output interface between the electronic device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 608 includes a front-facing camera and / or a rear-facing camera. When the electronic device 600 is in an operating mode, such as a shooting mode or a multimedia mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0144] Audio component 610 is used to output and / or input audio signals. For example, audio component 610 includes a microphone (MIC) used to receive external audio signals when electronic device 600 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 604 or transmitted via communication component 616. In some embodiments, audio component 610 also includes a speaker for outputting audio signals.

[0145] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0146] Sensor assembly 614 includes one or more sensors for providing state assessments of various aspects of electronic device 600. For example, sensor assembly 614 can detect the on / off state of electronic device 600, the relative positioning of components such as the display and keypad of electronic device 600, changes in position of electronic device 600 or a component of electronic device 600, the presence or absence of user contact with electronic device 600, orientation or acceleration / deceleration of electronic device 600, and temperature changes of electronic device 600. Sensor assembly 614 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 614 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0147] Communication component 616 facilitates wired or wireless communication between electronic device 600 and other devices. Electronic device 600 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or combinations thereof. In one exemplary embodiment, communication component 616 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 616 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0148] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to implement a method for calculating the quality factor of a formation medium provided in this application embodiment.

[0149] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, which can be executed by a processor 620 of an electronic device 600 to perform the above-described method. For example, the non-transitory storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0150] Figure 10 This is a block diagram illustrating an electronic device 700 according to an exemplary embodiment. For example, the electronic device 700 may be provided as a server. (Refer to...) Figure 10 The electronic device 700 includes a processing component 722, which further includes one or more processors, and memory resources represented by a memory 732 for storing instructions, such as application programs, that can be executed by the processing component 722. The application programs stored in the memory 732 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 722 is configured to execute instructions to perform a method for calculating the quality factor of a formation medium provided in embodiments of this application.

[0151] Electronic device 700 may also include a power supply component 726 configured to perform power management of electronic device 700, a wired or wireless network interface 750 configured to connect electronic device 700 to a network, and an input / output (I / O) interface 758. Electronic device 700 may operate on an operating system stored in memory 732, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0152] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0153] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for calculating the quality factor of a formation medium, characterized in that, The method includes: The experimental data of the simulated seismic wave observation model are obtained. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave. The proportionality coefficients of the simulated seismic waves on each propagation path are determined based on the experimental data. The propagation path is determined by the relative position of the excitation point and the receiver point. Based on the aforementioned proportionality coefficient and the aforementioned experimental data, a calculation formula is established with the stratification quality factor of each sub-stratum as the unknown variable. In the process of solving the formula to obtain the quality factor of the formation medium, the scaling factor is used to eliminate the calculation error caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

2. The method according to claim 1, characterized in that, The experimental data also includes the relative positions of the excitation point and the detector point; The determination of the scaling factors of the simulated seismic waves along each propagation path based on the experimental data includes: Based on the initial arrival time and the relative position, determine the number of sub-strata, the layer velocity of each sub-strata, and the layer thickness of the geological medium traversed by the propagation path; Based on the layer velocity and layer thickness, the propagation time of the simulated seismic wave in each sub-layer is determined using a ray tracing algorithm; The proportionality coefficient is determined based on the propagation time and the experimental data.

3. The method according to claim 2, characterized in that, The determination of the proportionality coefficient based on the propagation time and the experimental data includes: The amplitude spectrum and vibration frequency of the simulated seismic wave were obtained using the experimental data. The amplitude spectrum is transformed in the frequency domain using the Fordman attenuation model to obtain multiple frequency domain transformation expressions for the first arrival wavelet. The calculation parameters of the frequency domain transformation expressions include the propagation time. A frequency domain relationship expression about the vibration frequency is established based on multiple frequency domain transformation expressions. The frequency domain relationship expression is a linear function with the vibration frequency as the independent variable and the frequency domain value as the target value. Obtain the function curve of the frequency domain relation expression, and determine the proportionality coefficient based on the slope of the function curve.

4. The method according to claim 3, characterized in that, The experimental data also includes: the first arrival time and the first arrival wavelet of the simulated seismic wave; wherein, the first arrival time is used to characterize the moment when the receiver first detects the proton vibration of the simulated seismic wave in the simulated seismic wave observation model; the first arrival wavelet is the first periodic signal after the first arrival time in the simulated seismic wave record received by the receiver. The process of obtaining the amplitude spectrum and vibration frequency of the simulated seismic wave from the experimental data includes: Randomly select any two excitation points from the first number of excitation points to form an excitation point data group, and randomly select any two receiver points from the second number of seismic receiver points to form a receiver point data group; Acquire multiple simulated seismic wave records between the excitation point data group and the receiver point data group; Multiple first-arrival wavelets are extracted from multiple simulated seismic wave records, and multiple amplitude spectra and multiple vibration frequencies of the multiple first-arrival wavelets are obtained.

5. The method according to claim 3, characterized in that, The frequency domain transformation of the amplitude spectrum using the Fordman attenuation model yields multiple frequency domain transformation expressions for the first-arrival wavelet, including: The frequency domain transformation expression is obtained by performing a frequency domain transformation on the multiple first-arrival wavelets according to the following formula: Where f is the frequency, i is the excitation point number, j is the detector channel number, and S i (f) represents the source wavelet spectrum generated at the i-th excitation point, R i,j (f) represents the spectrum of the first arrival wave of the seismic signal excited at the i-th excitation point and received at the j-th receiver point, G. i,j C represents the frequency-independent attenuation of the source wavelet generated at the i-th excitation point as it propagates to the j-th receiver point. j (f) represents the sum of the response factors of the j-th detector point, including its own response characteristics and coupling effects. i,j Q represents the number of surface layers traversed by the source wavelet generated at the i-th excitation point as it propagates to the j-th receiver point. k Let t be the quality factor value of the k-th surface layer. i,j,k The time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th receiver point and then to the surface of the k-th layer.

6. The method according to claim 3, characterized in that, The step of establishing a frequency domain relationship expression for the vibration frequency based on multiple frequency domain transformation expressions includes: The spectral ratio is calculated for multiple frequency domain transform expressions to obtain a spectral ratio calculation result, which is an equation including the frequency domain value and the layered quality factor; The frequency domain relationship expression is obtained by linearly fitting the spectral ratio calculation results.

7. The method according to claim 1, characterized in that, The step of establishing a calculation formula based on the proportionality coefficient and the experimental data, with the stratification quality factor of each sub-stratum as the unknown variable, includes: Establish multiple frequency domain relational expressions with a total of a third quantity. The frequency domain relational expressions are calculation equations with propagation time and scale coefficient as known variables and the layered quality factor as unknown variables. The propagation time is used to characterize the propagation time of simulated seismic waves through each sub-layer. The third quantity is determined by the first quantity and the second quantity. The calculation formula is obtained by combining multiple frequency domain relation expressions. The calculation formula is a system of equations constructed by multiple frequency domain relation expressions with a total number equal to a third number.

8. The method according to claim 7, characterized in that, The experimental data also includes: the number of strata measured by the stratigraphic sequence; The establishment of multiple frequency domain relation expressions, totaling a third number, includes: The frequency domain relation expression is established according to the following formula: Where L represents the number of strata. Used to represent the quality factor of the k-th layer It is a proportionality coefficient jointly determined by the i-th and (i-1)-th excitation points, and the j-th and (j-1)-th detector points; The time taken for the source wavelet generated by the (i-1)th excitation point to propagate to the surface of the kth layer at the jth receiver point. The time taken for the source wavelet generated by the (i-1)th excitation point to propagate to the (j-1)th receiver point at the surface of the kth layer. The time taken for the source wavelet generated at the i-th excitation point to propagate to the (j-1)-th receiver at the k-th layer surface is given. The time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th receiver point and then to the surface of the k-th layer.

9. A device for calculating the quality factor of a formation medium, characterized in that, The device includes: The acquisition module is used to acquire experimental data of a simulated seismic wave observation model. The simulated seismic wave observation model is an observation model established based on single-well micrologging along the depth direction of the formation. The experimental data includes: data of a first number of excitation points and data of a second number of receiver points for the simulated seismic wave. The scaling factor determination module is used to determine the scaling factor of the simulated seismic wave in each sub-stratum based on the experimental data. The calculation formula acquisition module establishes a calculation formula with the stratification quality factor of each sub-stratum as the unknown variable based on the proportional coefficient and the experimental data. The quality factor determination module is used to eliminate calculation errors caused by the inconsistency of the excitation wavelet of the simulated seismic wave and the coupling effect of the detector through the scaling factor in the process of solving the calculation formula to obtain the quality factor of the formation medium. The quality factor is used to describe the absorption and attenuation ability of the formation medium to simulated seismic waves.

10. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is enabled to perform the method as described in any one of claims 1 to 8.

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