Method and device for calculating quality factor of stratum medium

Abstract

The embodiment of the invention provides a stratum medium quality factor calculation method and device, and belongs to the technical field of seismic exploration. The method comprises the steps that simulated seismic wave experimental data based on a single well micro-logging model are obtained, proportionality coefficients of simulated seismic waves on different propagation paths are determined according to the experimental data, and then a calculation formula with layering quality factors of all sub-stratums as unknown variables is established according to the proportionality coefficients and the experimental data; in the process of solving the calculation formula to obtain the quality factor of the stratum medium, calculating errors caused by inconsistency of excitation wavelets of simulated seismic waves and the coupling effect of a detector are eliminated through the proportionality coefficient; therefore, the precision of a calculation result of quality factor calculation after a simulated seismic wave observation experiment is carried out by single-well micro-logging is improved, and an experiment result is optimized.

Description

Technical Field

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

[0002] Simulating seismic waves is a commonly used technical means in the field of geological exploration. It artificially stimulates simulated seismic waves from different angles and collects relevant data of reflected waves, and analyzes the geological structure of the target area through multi-dimensional modeling. Among them, the quality factor is an important parameter that quantitatively describes the absorption and attenuation ability of the formation medium for simulated seismic waves, which is of great significance for the analysis, calculation and compensation of seismic data and improving the resolution of seismic data.

[0003] In the related technology, the quality factor is generally obtained by micro-logging observation method. The more commonly used observation models include: single-well micro-logging model, double-well micro-logging model and well-ground combined micro-logging model. Micro-logging wells are drilled in a certain area through earthwork operations, and then corresponding excitation points are set to emit simulated seismic waves, and seismic waves are received by detectors located at the detection points.

[0004] However, in the existing technical solutions, the experimental method of the single-well micro-logging model has technical defects such as the inconsistency of the excited sub-waves of the simulated seismic waves and the coupling effect of the detector, which leads to lower results of calculating the formation quality factor through the acquired observation data. Summary of the invention

[0005] The embodiments of the present application provide a method and device for calculating the quality factor of a formation medium, so as to solve the problem of insufficient accuracy of experimental results of obtaining the formation quality factor through a single well micro-logging model in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for calculating a quality factor of a formation medium, the method comprising:

[0007] Acquire experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves;

[0008] Determining the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data, wherein the propagation path is determined by the relative position of the excitation point to the detection point;

[0009] According to the proportionality coefficient and the experimental data, a calculation formula is established with the stratified quality factor of each stratum as an unknown variable;

[0010] 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 excited sub-waves of the simulated seismic waves and the detector coupling effect is eliminated by the proportional coefficient. The quality factor is used to describe the absorption and attenuation ability of the formation medium to the simulated seismic waves.

[0011] In a second aspect, an embodiment of the present application provides a device for calculating a quality factor of a formation medium, the device comprising:

[0012] An acquisition module is used to acquire experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves;

[0013] A proportionality coefficient determination module, used to determine the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data, wherein the propagation path is determined by the relative position of the excitation point to the detection point;

[0014] A calculation formula acquisition module is used to establish a calculation formula with the stratified quality factor of each stratum as an unknown variable according to the proportional coefficient and the experimental data;

[0015] The quality factor determination module is used to eliminate the calculation error caused by the inconsistency of the excited sub-waves of the simulated seismic waves and the detector coupling effect through the proportional coefficient 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 the simulated seismic waves.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, including: a processor;

[0017] a memory for storing instructions executable by the processor;

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

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which, when 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 an embodiment of the present application, after obtaining the simulated seismic wave experimental data based on the single-well micro-logging model, the proportional coefficient of the simulated seismic wave on different propagation paths is first determined according to the experimental data, and then a calculation formula is established with the stratified quality factor of each sub-stratum 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 formation medium, the calculation error caused by the inconsistency of the excited sub-wave of the simulated seismic wave and the coupling effect of the detector is eliminated by the proportional coefficient, thereby improving the accuracy of the calculation results of the quality factor calculation after the simulated seismic wave observation experiment based on the single-well micro-logging, and optimizing the experimental results.

[0021] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

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

[0024] Figure 2 It is a data collection schematic diagram of a single well micro-logging observation system provided in an embodiment of the present application;

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

[0026] Figure 4 It is a complete implementation step flow chart of a method for calculating a quality factor of a formation medium provided in an embodiment of the present application;

[0027] Figure 5 It is a relationship diagram between surface depth and layer velocity of a single well micro-logging observation data provided by an embodiment of the present application;

[0028] Figure 6 is a schematic diagram of the comparison between the layered quality factor and the layer depth provided in the embodiment of the present application;

[0029] Figure 7 This is a comparison diagram of the effect of ground seismic data compensation processing provided by an embodiment of the present application;

[0030] Figure 8 It 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 the present application;

[0031] Fig. 9 is a functional component relationship diagram of an electronic device provided in an embodiment of the present application;

[0032] Fig.10 This is a functional component relationship diagram of another electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

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

[0035] Step 101, obtaining experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves.

[0036] A method for calculating the quality factor of a formation medium provided in an embodiment of the present application is applied to a single-well micro-logging observation model for simulating seismic waves. A micro-logging well is drilled in a certain area by means of earthwork operations, and then corresponding excitation points are set in the well to emit simulated seismic waves, and the seismic waves are received by a detector located at the detection point.

[0037] Specific reference Figure 2 , shows a data collection schematic diagram of a single well micro-logging observation system provided by an embodiment of the present application. Figure 2 As shown in the figure, in the observation well set vertically to the ground, multiple excitation points such as A1-A8 are arranged at certain intervals from shallow to deep, which are used to excite simulated seismic waves. Multiple detection points such as B1-B5 are set near the surface position of the observation well mouth, which are used to place detectors to receive and record the excited simulated seismic wave signals.

[0038] As for the experimental data described in step 101, in actual test applications, whenever the excitation point generates simulated seismic waves, the observation model will generate an experimental data record about the excitation point. Correspondingly, whenever the detection point receives the stimulated simulated seismic waves, an experimental data record about the excitation point will be generated. Figure 1 When any excitation point emits a simulated seismic wave, the detection point on the surface will respond with a received signal. The propagation path from the excitation point to the detection point is called a channel. Figure 1 As shown, the channel L1 corresponds to the excitation point A4 and the detection point B2, and the channel L2 corresponds to the excitation point A7 and the detection point B2.

[0039] At the same time, one excitation point can also generate multiple channels corresponding to multiple detection points. Figure 3 , shows a schematic diagram of a common excitation point channel set for simulating seismic waves provided in an embodiment of the present application. The signals emitted at the same excitation point correspond to 5 different channels, and there are waveform records under the channels marked with channel numbers 1-5. Testers can selectively use the channel data according to test requirements.

[0040] Step 102: Determine the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data, wherein the propagation path is determined by the relative position of the excitation point to the detection point.

[0041] The present application provides a method for calculating the quality factor of a formation medium, which mainly solves the problem that in the prior art, in the process of calculating the quality factor based on experimental data under a single well micro-logging observation model, the inconsistency of the excited wavelet of the simulated seismic wave and the coupling effect of the detector cause the calculation results to have multiple solutions and reduced accuracy. Therefore, in this solution, the spectral ratio method is improved to eliminate the calculation influence caused by the inconsistency of the excited wavelet and the coupling effect of the detector.

[0042] Since the geological medium can be divided into multiple sub-strata due to its different burial depths, in the present application, a proportional coefficient (or linear fitting coefficient) is introduced when calculating the experimental data of different sub-strata to eliminate the inconsistency of the excited sub-wave and the coupling effect of the detector. 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, in this application, by analyzing the experimental data of the excitation points and detection points of different seismic waves, by analyzing the propagation speed of the seismic waves simulated in different strata and the thickness parameters of the strata, the propagation time of the seismic waves in the surface of different geological layers is obtained through the conventional ray tracing algorithm, and the frequency domain transformation analysis is performed according to the Futterman attenuation model, and the proportional coefficient can be obtained after fitting.

[0044] Step 103: establishing a calculation formula with the stratified quality factor of each stratum as an unknown variable according to the proportional coefficient and the experimental data.

[0045] Continuing from step 102, after obtaining the proportionality coefficient of each sub-stratum, multiple groups of excitation points and detection points are selected in combination with experimental data and according to the above-mentioned method for calculating the propagation time of seismic waves in different stratum surfaces, a calculation formula including propagation time, stratification quality factor and proportionality coefficient is established.

[0046] In the embodiment of the present application, the calculation formula is specifically a single unknown variable equation group including multiple equations. Since only the stratified quality factor is an unknown variable among the calculation parameters in each equation, and the total number of stratified quality factors is equal to the number of strata, the least squares solution of the equation group, i.e., the specific value of the quality factor of the stratum medium, can be obtained by using the least squares method from the overdetermined equation group in which the number of equations is greater than the number of unknowns.

[0047] Specifically, in the embodiment of the present application, an equation can be established by arbitrarily selecting two excitation points and two detection points from the observation data of single-well micro-logging. For an observation model with M seismic wave excitation points, a total of (Combination calculation formula) types of excitation point combinations. Similarly, for the observation model with N seismic wave detection points, a total of There are several combinations of detection points. Then we can establish a total number equal to equations, and these equations can form an overdetermined system of equations.

[0048] It is worth noting that the number of equations calculated by this method will obviously exceed the number of layers of the strata (the number of strata is generally planned to be around 3 layers). Therefore, in the process of solving the equation group, you can also choose not to apply all the equations. The ones involved in the calculation can be some of the M excitation points and some of the detection points in N. The tester can appropriately eliminate 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 excited sub-waves of the simulated seismic waves and the detector coupling effect is eliminated by the proportional coefficient. The quality factor is used to describe the absorption and attenuation capacity of the formation medium to the simulated seismic waves.

[0050] Since the stratum medium has viscoelasticity, it can cause the amplitude attenuation of seismic waves, the reduction of main frequency, the narrowing of frequency band, phase delay, etc., thus reducing the resolution of seismic data. The surface layer has the characteristics of shallow burial, severe weathering and erosion, loose structure, and poor compaction, which makes the absorption and attenuation of seismic waves more serious, becoming one of the main factors restricting the improvement of seismic data resolution. Therefore, solving the quality factor Q value, an important parameter used to quantitatively describe the absorption and attenuation of seismic waves, and effectively compensating the seismic data are of great significance to improving the resolution of seismic data.

[0051] The method for calculating the quality factor of the formation medium provided in the embodiment of the present application, after obtaining the proportional coefficient according to the observation system, analyzes the propagation time taken by the source wavelet generated by each excitation point in the experimental data to reach the detection point, transforms the amplitude spectrum into a frequency domain spectrum, and then performs a linear combination transformation. In this process, the influence of the calculation result caused by the inconsistency of the source wavelet can be eliminated. At the same time, the spectrum ratio of the frequency domain spectrum is calculated to eliminate the influence caused by the coupling effect of the detector, so as to eliminate the calculation error caused by the above two factors in the solution calculation of the quality factor.

[0052] In summary, a method for calculating the quality factor of a formation medium provided in an embodiment of the present application, after obtaining the simulated seismic wave experimental data based on a single-well micro-logging model, first determines the proportional coefficient of the simulated seismic wave on different propagation paths according to the experimental data, and then establishes a calculation formula with the stratified quality factor of each sub-stratum 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 formation medium, the calculation error caused by the inconsistency of the excited sub-wave of the simulated seismic wave and the coupling effect of the detector is eliminated by the proportional coefficient, thereby improving the accuracy of the settlement result of the quality factor calculation after the simulated seismic wave observation experiment based on the single-well micro-logging, and optimizing the experimental results.

[0053] Reference Figure 4 , Figure 4 1 is a complete implementation step flow chart of a method for calculating the quality factor of a formation medium provided in an embodiment of the present application. Figure 4 As shown, the steps of the method include:

[0054] Step 201, obtain experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points for simulated seismic waves and data of a second number of detection points.

[0055] This step may specifically refer to the above step 101, which will not be described in detail in this embodiment.

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

[0057] Sub-step 2011: Determine the number of layers of the formation medium, the layer velocity and layer thickness of each layer according to the first arrival time and relative position recorded in the experimental data.

[0058] In the experimental data based on the single-well micro-logging observation model, the first arrival time and first arrival wavelet of the simulated seismic wave from different excitation points to the detection point are recorded; among them, the first arrival time is used to characterize the moment when the detection point 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 intercepted after the first arrival time in the simulated seismic wave record received by the wave detection point. In the process of constructing a single-well micro-logging, its specific burial depth is determined by humans according to the construction requirements, and is divided into multiple sub-strata within the burial depth range of the model.

[0059] Reference Figure 5 , shows a graph showing the relationship between surface depth and layer velocity of a single well micro-logging observation data provided by an embodiment of the present application. Figure 5 As shown, it includes the layer velocities of three different buried depths V1-V3. Here, the layer velocity represents the propagation velocity of the simulated seismic wave in the layer. Among them, V1=341m / s, V2=413m / s, V1=2213m / s. For the thickness of the buried depth layer where the layer velocity changes, the first layer H1=2.12m, and the second layer H2=5.13m. It should be noted that Figure 5 The relationship between surface depth and layer velocity of the observation data shown is the same as Figure 2 Experimental results obtained with the observation model shown.

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

[0061] Continuing from sub-step 2011, four seismic wave records received by two excitation points and corresponding detection points are arbitrarily selected from the experimental data of single-well micro-logging (a transmission channel can be formed between a single excitation point and two detection points), and a periodic signal after the first arrival time of the simulated seismic wave record is intercepted as the first arrival sub-wave.

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

[0063] Optionally, the 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 detection points from the second number of seismic detection points to form a detection point data group.

[0065] In the single-well micro-logging observation model provided in the embodiment of the present application, assuming that a total of M excitation points and N detection points are set, M actually corresponds to the first number, and N corresponds to the second number.

[0066] It is worth noting that the selected excitation point data group can be some of the M excitation points, and the detection point data group can be some of the N detection points. The tester can appropriately eliminate points with unstable data according to the actual situation to ensure the accuracy of the results.

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

[0068] Following sub-step 20121, two of the M excitation points are selected to form an excitation point data set, and two of the N detection points are selected to form a detection point data set. According to the selection relationship described in sub-step 2012, there can be four seismic wave records in total for the two excitation points and the corresponding detection points.

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

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

[0071] Step 202: Determine the propagation time of the simulated seismic wave in each sub-stratum by using a ray tracing algorithm according to the layer velocity and layer thickness.

[0072] The propagation distance of the simulated seismic wave in the substratum can be determined by the layer velocity recorded in the experimental data and the relative position between each excitation point and the detection point. The following formula is used:

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

[0074] The propagation time of the seismic wave received by each detection point in each stratigraphic layer can be obtained, where i = 1, 2, ..., M is the serial number of the excitation point, and j = 1, 2, ..., N is the channel number corresponding to the detection point.

[0075] Step 203: Perform frequency domain transformation on the amplitude spectrum through the Footman attenuation model to obtain multiple frequency domain transformation expressions for the first-arrival wavelet, wherein the calculation parameters of the frequency domain transformation expressions include the propagation time.

[0076] Specifically, according to the Futterman 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 number of the excitation point, j is the channel number of the detection point, S i(f) is the source wavelet spectrum generated by the i-th excitation point, R i,j (f) is the frequency spectrum of the first arrival wave of the seismic signal excited by the i-th excitation point and received by the j-th detection point, G i,j is the frequency-independent attenuation experienced by the source wavelet generated by the i-th excitation point when it propagates to the j-th detection point, C j (f) is the sum of the response factors of the jth detection point including its own response characteristics and coupling effects, L i,j is the number of surface layers that the source wavelet generated by the i-th excitation point passes through when it propagates to the j-th detection point, Q k is the value of the quality factor of the kth surface layer, t i,j,k It is the time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th detection point in the k-th surface layer.

[0079] According to the above formula, a group of excitation points are selected from the experimental data as the excitation point data group, namely the corresponding excitation point i and excitation point i-1, and a group of detection points are selected as the detection point data group, namely the corresponding detection point j and detection point j-1 to establish the frequency domain transformation relationship:

[0080]

[0081]

[0082]

[0083]

[0084] Step 204: establish a frequency domain relationship expression about the vibration frequency according to the multiple frequency domain transformation expressions, wherein the frequency domain relationship expression is a linear function with the vibration frequency as an independent variable and the frequency domain value as a target value.

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

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

[0087]

[0088] Dividing formula (5) by formula (6), we have:

[0089]

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

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

[0092]

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

[0094] By taking logarithmic operations on both sides of formula (9), we can obtain the frequency domain relationship expression of the vibration frequency:

[0095]

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

[0097] Step 205: Obtain a function curve of the frequency domain relationship expression, and determine the proportionality coefficient according to the slope of the function curve.

[0098] Following the above step 205, the frequency domain relationship expression is plotted as a function graph, and the proportionality coefficient K can be directly obtained by the inclination angle of the function curve compared to the horizontal line. When the inclination angle of the function curve is θ, the proportionality coefficient K is the tangent value of the inclination angle, that is, K=tanθ.

[0099] Step 206, establish a plurality of frequency domain relationship expressions totaling a third number, wherein the frequency domain relationship expressions are calculation equations with propagation time and proportional coefficient as known variables and the stratified quality factor as an unknown variable, the propagation time is used to characterize the propagation time of simulated seismic waves passing through each sub-stratum, and the third number is determined by the first number and the second number.

[0100] Referring to the contents of step 203-step 204 above, according to the calculation process of formula (3) to formula (10), different excitation points and detection points are selected from the numerical research data in turn to form an experimental group. Figure 1 For example, A4+A5 is selected as the excitation point data set for the first time, and B2+B3 is selected as the detection point data set. After the calculation process from formula (3) to formula (10), a linear function expression (frequency domain relationship expression) about f can be obtained. Second, A5+A6 can be selected as the excitation point data set, and B3+B4 can be selected as the detection point data set. After the calculation process from formula (3) to formula (10), another linear function expression about f can be obtained. This process is repeated until the upper limit of the combination types that M and N can reach is reached.

[0101] In the embodiment of the present application, an equation can be established by arbitrarily selecting two excitation points and two detection points from the observation data of single-well micro-logging. For an observation model with M seismic wave excitation points, a total of (Combination calculation formula) types of excitation point combinations. Similarly, for the observation model with N seismic wave detection points, a total of There are several combinations of detection points. Then we can establish a total number equal to An expression.

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

[0103] Sub-step 2061: perform spectral ratio calculation on the multiple frequency domain transform expressions to obtain a spectral ratio calculation result, wherein the spectral ratio calculation result is an equation including the frequency domain value and the layered quality factor.

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

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

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

[0107]

[0108] Where L is the number of layers in the stratigraphic system, Q k Used to represent the quality factor of the kth layer, K m is the proportionality coefficient determined by the i-th and i-1-th excitation points, and the j-th and j-1-th detection points; t i-1,j,k is the time taken for the source wavelet generated by the i-1th excitation point to propagate to the jth receiver point in the kth surface layer, t i-1,j-1,k The time taken for the source wavelet generated by the i-1th excitation point to propagate to the j-1th detection point in the surface layer of the kth layer, t i,j-1,k is the time taken for the source wavelet generated by the ith excitation point to propagate to the j-1th detection point in the kth surface layer, t i,j,k It is the time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th detection point in the k-th surface layer.

[0109] It should be noted that K m It is determined by two sets of excitation points and detection points in the experimental data involved in each calculation. Figure 2 In the embodiment of the present application, when calculating the frequency domain relationship expression once, the propagation path between the i-th and i-1-th excitation points and the j-th and j-1-th detection points is selected to form a "two-shot two-path" observation data set. Figure 2 The specific value of m is the same as the number of frequency domain relationship expressions established, that is,

[0110] Step 207: combine the multiple frequency domain relationship expressions to obtain the calculation formula, which is a set of equations constructed by multiple frequency domain relationship expressions whose total number is equal to the third number.

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

[0112] Reference Figure 6 , which shows a schematic diagram of the comparison between the layered quality factor and the layer depth provided in the embodiment of the present application. Figure 6 As shown in FIG. 1 , as the surface depth changes, the corresponding stratification quality factor Q also changes accordingly.

[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 excited sub-waves of the simulated seismic waves and the detector coupling effect is eliminated by the proportional coefficient. The quality factor is used to describe the absorption and attenuation capacity of the formation medium to the simulated seismic waves.

[0114] This step may specifically refer to the above step 104, which will not be described in detail in this embodiment.

[0115] It should be noted that the quality factor of the stratum medium calculated by the embodiment of the present application plays an important role in the subsequent calculation and compensation processing of ground earthquakes. Figure 7 , shows a comparison diagram of the effect of ground seismic data compensation processing provided by an embodiment of the present application. Figure 7 As shown, it mainly shows the changes of time migration profile and spectrum parameters before and after the quality factor calculated by the embodiment of the present application is used to compensate the seismic wave data. After the quality factor calculation and compensation, the main frequency of the seismic data is improved, the frequency band is widened from 68Hz to 83Hz, and the quality of the seismic data is significantly improved.

[0116] In summary, the method for calculating the quality factor of a formation medium provided in an embodiment of the present application, after obtaining the simulated seismic wave experimental data based on a single-well micro-logging model, first determines the relative position relationship between each excitation point and detection point, the number of excitation points and detection points, the first arrival time, and the first arrival wavelet according to the experimental data, and then infers the layer velocity, thickness, and number of layers of the surface layer. According to the conventional ray tracing algorithm, the propagation time of the seismic wave received by each detection point in each surface layer is obtained, and based on this, two excitation points and four seismic wave records corresponding to the same two detection points are randomly selected from the micro-logging record, and a periodic signal after the first arrival time of the seismic wave record is intercepted as the first arrival wavelet, and the amplitude spectrum of the four first arrival wavelets is obtained, the cubic spectrum ratio is calculated, and the logarithm and the frequency are fitted to obtain the proportionality coefficient K that eliminates the inconsistency of the excitation wavelet and the coupling of the detector. m , and then a calculation formula with the stratified quality factor of each stratum as the unknown variable is established according to the proportional coefficient, the Fordman attenuation model, and the experimental data; 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 excited sub-wave of the simulated seismic wave and the coupling effect of the detector is eliminated by the proportional coefficient, thereby improving the accuracy of the calculation results of the quality factor calculation after the simulated seismic wave observation experiment with single-well micro-logging, and optimizing the experimental results.

[0117] Reference Figure 8 , shows a schematic diagram of the functional modules of a device for calculating the quality factor of a formation medium provided in an embodiment of the present application. Figure 8 As shown, the device comprises:

[0118] An acquisition module is used to acquire experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves;

[0119] A proportionality coefficient determination module, used to determine the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data, wherein the propagation path is determined by the relative position of the excitation point to the detection point;

[0120] A calculation formula acquisition module is used to establish a calculation formula with the stratified quality factor of each stratum as an unknown variable according to the proportional coefficient and the experimental data;

[0121] The quality factor determination module is used to eliminate the calculation error caused by the inconsistency of the excited sub-waves of the simulated seismic waves and the detector coupling effect through the proportional coefficient 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 the simulated seismic waves.

[0122] Optionally, the acquisition module further includes:

[0123] The first acquisition submodule is used to determine the number of layers of the formation medium, the layer velocity and layer thickness of each layer according to the first 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] A data group determination unit, 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 detection points from the second number of seismic detection points to form a detection point data group;

[0127] A seismic wave record acquisition unit, used for acquiring a plurality of simulated seismic wave records between the excitation point data group and the detection point data group;

[0128] The first-arrival wavelet parameter acquisition unit is used to intercept a plurality of first-arrival wavelets from a plurality of the simulated seismic wave records, and to acquire a plurality of amplitude spectra and a plurality of vibration frequencies of the plurality of the first-arrival wavelets.

[0129] Optionally, the proportional coefficient determination module further includes:

[0130] The propagation time determination submodule is used to determine the propagation time of the simulated seismic wave in each sub-stratum according to the layer velocity and layer thickness through a ray tracing algorithm.

[0131] A frequency domain transformation expression determination submodule is used to perform frequency domain transformation on the amplitude spectrum through a Footman attenuation model to obtain a plurality of frequency domain transformation expressions for first-arrival wavelets, wherein the calculation parameters of the frequency domain transformation expressions include the propagation time;

[0132] A frequency domain relationship expression determination submodule, used to establish a frequency domain relationship expression about the vibration frequency according to a plurality of the frequency domain transformation expressions, wherein the frequency domain relationship expression is a linear function with the vibration frequency as an independent variable and the frequency domain value as a target value;

[0133] The proportionality coefficient determination submodule is used to obtain the function curve of the frequency domain relationship expression and determine the proportionality coefficient according to the slope of the function curve.

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

[0135] A frequency domain relationship expression construction submodule is used to establish a plurality of frequency domain relationship expressions with a total of a third number, wherein the frequency domain relationship expression is a calculation equation with a propagation time and a proportional coefficient as known variables and the layered quality factor as an unknown variable, wherein the propagation time is used to characterize the propagation time of the simulated seismic wave passing through each layer, and 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 relationship expressions to obtain the calculation formula, which is a set of equations constructed by multiple frequency domain relationship expressions whose total number is equal to the third number.

[0137] In summary, an embodiment of the present application provides a device for calculating the quality factor of a formation medium. After obtaining the simulated seismic wave experimental data based on a single-well micro-logging model, the proportional coefficient of the simulated seismic wave on each propagation path is first determined according to the experimental data, and then a calculation formula with the stratified quality factor of each sub-stratum as an unknown variable is established according to the proportional coefficient and the experimental data; 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 excited sub-wave of the simulated seismic wave and the coupling effect of the detector is eliminated by the proportional coefficient, thereby improving the accuracy of the calculation results of the quality factor calculation after the simulated seismic wave observation experiment based on the single-well micro-logging, and optimizing the experimental results.

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

[0139] Reference Fig. 9 , the electronic device 600 may include one or more of the following components: a processing component 602 , a memory 604 , a power 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] The processing component 602 generally controls the overall operation of the electronic device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 602 may include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0141] The memory 604 is used to store various types of data to support the operation of the electronic device 600. Examples of such data include instructions for any application or method operating on the electronic device 600, contact data, phone book data, messages, pictures, multimedia, etc. The 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 memory, flash memory, magnetic disk or optical disk.

[0142] The power supply component 606 provides power to the various components of the electronic device 600. The 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 the electronic device 600.

[0143] The 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 touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the electronic device 600 is in an operating mode, such as a shooting mode or a multimedia mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0144] The audio component 610 is used to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC), and when the electronic device 600 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is used to receive an external audio signal. The received audio signal can be further stored in the memory 604 or sent via the communication component 616. In some embodiments, the 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: a home button, a volume button, a start button, and a lock button.

[0146] The sensor assembly 614 includes one or more sensors for providing various aspects of status assessment for the electronic device 600. For example, the sensor assembly 614 can detect the open / closed state of the electronic device 600, the relative positioning of the components, such as the display and keypad of the electronic device 600, and the sensor assembly 614 can also detect the position change of the electronic device 600 or a component of the electronic device 600, the presence or absence of contact between the user and the electronic device 600, the orientation or acceleration / deceleration of the electronic device 600, and the temperature change of the electronic device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0147] The communication component 616 is used to facilitate wired or wireless communication between the electronic device 600 and other devices. The electronic device 600 can access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G or 5G), or a combination thereof. In an exemplary embodiment, the communication component 616 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can 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 can 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 an embodiment of the present application.

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

[0150] Fig.10 is a block diagram of an electronic device 700 according to an exemplary embodiment. For example, the electronic device 700 may be provided as a server. Fig.10 The electronic device 700 includes a processing component 722, which further includes one or more processors, and a memory resource represented by a memory 732 for storing instructions executable by the processing component 722, such as an application. The application stored in the memory 732 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 722 is configured to execute instructions to perform a method for calculating a quality factor of a formation medium provided in an embodiment of the present application.

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

[0152] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0153] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present 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 comprises: Acquire experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves; Determining the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data, wherein the propagation path is determined by the relative position of the excitation point to the detection point; According to the proportionality coefficient and the experimental data, a calculation formula is established with the stratified quality factor of each stratum as an unknown variable; 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 excited sub-waves of the simulated seismic waves and the detector coupling effect is eliminated by the proportional coefficient. The quality factor is used to describe the absorption and attenuation ability of the formation medium to the simulated seismic waves.

2. The method according to claim 1, characterized in that The experimental data also includes: the relative position of the excitation point and the detection point; Determining the proportionality coefficient of the simulated seismic wave on each propagation path according to the experimental data includes: Determine the number of layers of the formation medium passed by the propagation path, the layer velocity and layer thickness of each layer according to the first arrival time and the relative position; According to the layer velocity and layer thickness, the propagation time of the simulated seismic wave in each sub-stratum is determined by 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 Determining the proportionality coefficient based on the propagation time and the experimental data comprises: Acquire the amplitude spectrum and vibration frequency of the simulated seismic wave through the experimental data; Performing frequency domain transformation on the amplitude spectrum through the Footman attenuation model to obtain a plurality of frequency domain transformation expressions for the first-arrival wavelet, wherein the calculation parameters of the frequency domain transformation expressions include the propagation time; Establishing a frequency domain relationship expression about the vibration frequency according to the plurality of frequency domain transformation expressions, wherein the frequency domain relationship expression is a linear function with the vibration frequency as an independent variable and the frequency domain value as a target value; A function curve of the frequency domain relationship expression is obtained, and the proportional coefficient is determined according to 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 detection point 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 wave detection point; The step of obtaining the amplitude spectrum and vibration frequency of the simulated seismic wave through the experimental data includes: Selecting any two excitation points from the first number of excitation points in sequence to form an excitation point data group, and selecting any two detection points from the second number of seismic detection points to form a detection point data group; Acquire a plurality of simulated seismic wave records between the excitation point data group and the detection point data group; A plurality of first-arrival wavelets are intercepted from a plurality of the simulated seismic wave records, and a plurality of amplitude spectra and a plurality of vibration frequencies of the plurality of the first-arrival wavelets are obtained.

5. The method according to claim 3, characterized in that: The frequency domain transformation of the amplitude spectrum is performed by the Footman attenuation model to obtain multiple frequency domain transformation expressions for the first-arrival wavelet, including: According to the following formula, the frequency domain transformation is performed on the multiple first arrival wavelets to obtain the frequency domain transformation expression: Where f is the frequency, i is the number of the excitation point, j is the channel number of the detection point, S i (f) is the source wavelet spectrum generated by the i-th excitation point, R i,j (f) is the frequency spectrum of the first arrival wave of the seismic signal excited by the i-th excitation point and received by the j-th detection point, G i,j is the frequency-independent attenuation experienced by the source wavelet generated by the i-th excitation point when it propagates to the j-th detection point, C j (f) is the sum of the response factors of the jth detection point including its own response characteristics and coupling effects, L i,j is the number of surface layers that the source wavelet generated by the i-th excitation point passes through when it propagates to the j-th detection point, Q k is the value of the quality factor of the kth surface layer, t i,j,k It is the time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th detection point in the k-th surface layer.

6. The method according to claim 3, characterized in that The step of establishing a frequency domain relationship expression about the vibration frequency according to the plurality of frequency domain transformation expressions comprises: Performing spectral ratio calculation on a plurality of the frequency domain transform expressions to obtain a spectral ratio calculation result, wherein the spectral ratio calculation result is an equation including the frequency domain value and the hierarchical quality factor; The spectrum ratio calculation result is linearly fitted to obtain the frequency domain relationship expression.

7. The method according to claim 1, characterized in that The calculation formula established according to the proportional coefficient and the experimental data with the stratified quality factor of each stratum as an unknown variable includes: Establishing a plurality of frequency domain relationship expressions with a total of a third number, wherein the frequency domain relationship expressions are calculation equations with propagation time and a proportional coefficient as known variables and the layered quality factor as an unknown variable, wherein the propagation time is used to characterize the propagation time of the simulated seismic wave passing through each layer, and the third number is determined by the first number and the second number; The plurality of frequency domain relationship expressions are combined to obtain the calculation formula, which is a set of equations constructed by a plurality of frequency domain relationship expressions whose total number is equal to the third number.

8. The method according to claim 7, characterized in that The experimental data also includes: measuring the number of layers in the strata; The step of establishing a third number of frequency domain relationship expressions comprises: The frequency domain relationship expression is established according to the following formula: Where L is the number of layers in the stratigraphic system, Q k Used to represent the quality factor of the kth layer, K m is the proportionality coefficient determined by the i-th and i-1-th excitation points, and the j-th and j-1-th detection points; t i-1,j,k is the time taken for the source wavelet generated by the i-1th excitation point to propagate to the jth receiver point in the kth surface layer, t i-1,-1, The time taken for the source wavelet generated by the i-1th excitation point to propagate to the j-1th detection point in the surface layer of the kth layer, t i,j-1,k is the time taken for the source wavelet generated by the ith excitation point to propagate to the j-1th detection point in the kth surface layer, i i,j,k It is the time taken for the source wavelet generated by the i-th excitation point to propagate to the j-th detection point in the k-th surface layer.

9. A device for calculating the quality factor of a formation medium, characterized in that: The device comprises: An acquisition module is used to acquire experimental data of a simulated seismic wave observation model, wherein the simulated seismic wave observation model is an observation model established along the depth direction of the formation based on single-well micro-logging, and the experimental data includes: data of a first number of excitation points and data of a second number of detection points for simulated seismic waves; A proportionality coefficient determination module, used to determine the proportionality coefficient of the simulated seismic wave in each sub-stratum according to the experimental data; A calculation formula acquisition module is used to establish a calculation formula with the stratified quality factor of each stratum as an unknown variable according to the proportional coefficient and the experimental data; The quality factor determination module is used to eliminate the calculation error caused by the inconsistency of the excited sub-waves of the simulated seismic waves and the detector coupling effect through the proportional coefficient 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 the simulated seismic waves.

10. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to 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 a processor of an electronic device, the electronic device is enabled to perform the method as claimed in any one of claims 1 to 8.

Images