A method, device and equipment for extracting a formation quality factor and a storage medium

Abstract

The application provides a stratum quality factor extraction method, device and equipment and a storage medium, and belongs to the technical field of oil seismic exploration data processing. The method comprises the following steps: extracting first arrival wave data from VSP well data, and performing velocity layering on the first arrival wave data; for each layer, performing an amplitude curve fitting process to obtain a fitting amplitude curve corresponding to each layer; determining a starting depth amplitude value and an ending depth amplitude value of the first arrival wave of the layer by using the fitting amplitude curve corresponding to the layer, and calculating an attenuation factor corresponding to the layer according to the starting depth amplitude value, the ending depth amplitude value, a depth interval of the layer and a layer velocity; and calculating a stratum quality factor of the layer according to each attenuation factor and main frequency information of the corresponding layer. The application combines multi-point amplitude curve fitting of each layer, an attenuation factor and an accurate calculation formula of a Q value, and realizes high-accuracy, high-stability and high-convenience Q value extraction.

Description

Technical Field

[0001] This invention belongs to the field of seismic data processing technology, and is particularly applicable to seismic exploration of petroleum. Specifically, it relates to a method, apparatus, equipment, and storage medium for extracting formation quality factors. Background Technology

[0002] Seismic waves experience energy loss during propagation through the Earth's medium. There are three main types of energy loss. The first is spherical diffusion, where the amplitude of a seismic wave decreases with distance. This energy loss is independent of the frequency of the seismic wave, depending only on the propagation distance, and does not cause a decrease in frequency during propagation. The second type is energy loss due to friction between media. This loss is frequency-dependent; high-frequency seismic waves attenuate faster than low-frequency waves, resulting in a decrease in the dominant frequency of the seismic wave with increasing propagation distance. The third type is scattering attenuation, which is very significant in strongly inhomogeneous media but is not a primary concern in the predominantly layered Earth. In the field of petroleum seismic exploration data processing, the focus is primarily on the second type of loss, absorption attenuation. To quantitatively reflect the attenuation strength of seismic waves during propagation through strata, the formation quality factor is typically used as a quantitative evaluation parameter. In geophysics, the absorption attenuation coefficient is equal to the reciprocal of the formation quality factor.

[0003] In typical surface seismic exploration, due to absorption attenuation, the dominant frequency of seismic waves gradually decreases with increasing reflection time (increasing propagation depth), leading to a gradual reduction in the resolution of deep seismic waves and hindering the identification of various deep geological strata. In the processing and interpretation of seismic exploration data, two methods are often used to overcome this resolution reduction: deconvolution and absorption attenuation compensation. Absorption attenuation compensation is a crucial step in seismic exploration data processing, and the most important aspect of this step is obtaining an accurate stratigraphic quality factor, i.e., the Q value. An accurate Q value is the cornerstone of absorption attenuation compensation.

[0004] There are generally three approaches to extracting formation quality factor Q values: the first is rock physics testing; the second is extraction from surface seismic data; and the third is extraction from VSP (vertical seismic profile) well data. The first method is relatively expensive and scarce (due to limited rock sampling); the second method suffers from low accuracy and reliability due to various reflections, multiple reflections, and overlapping reflection information from multiple layers; the third method is currently the most common and effective method for processing seismic exploration data.

[0005] Currently, methods for extracting formation quality factor Q values ​​based on VSP well data often employ peak frequency shift (PSFS), spectral ratio, and frequency centroid shift methods. The PSFS method, based on the fundamental principle that seismic wave frequency decreases with increasing propagation distance, has the following drawbacks: 1) The peak frequency is difficult to determine accurately due to the mixing of the first arrival wave and other waves; 2) Slight changes in the peak frequency can lead to large, even enormous, changes in the Q value; 3) The basic formula for Q value calculation using the PSFS method is approximate, resulting in significant errors for strongly absorbing and attenuating media (i.e., Q values ​​below 20). The spectral ratio method is based on the fundamental principle that the high-frequency band of seismic waves decreases as the propagation distance increases. The ratio on the amplitude spectrum approximates a linear function. This method has the following shortcomings: 1) Due to the mixing of the first arrival wave and other waves, the amplitude spectrum changes drastically with frequency, so a relatively clean amplitude spectrum is required; 2) The approximation of the linear function is often arbitrary and depends on the user's experience; 3) Similar to the approximation of the peak frequency shift method, the error is large for strongly absorbing and attenuating media (i.e., Q value below 20). The frequency centroid shift method is based on the characteristic that the centroid of the seismic wave spectrum shifts to lower frequencies as the propagation distance increases. This method has the following shortcomings: 1) It is computationally cumbersome and highly complex; 2) When the seismic data contains random noise, the method is limited by the selection of the integration frequency band, resulting in insufficient robustness. Different frequency bands often lead to significant differences in the estimated Q value; 3) This method is derived under the assumption that the amplitude or energy spectrum of the seismic wave conforms to the Gaussian type, etc. The actual shape of the seismic wave amplitude spectrum differs from this assumption, so the accuracy of the estimated Q value is relatively low. Figure 1 The peak frequency shift method, spectral ratio method and frequency centroid shift method were used to estimate the Q value when the speed was 800m / s and the frequency was 40Hz. When the Q value was less than 20, the above Q value estimation methods had large errors, with errors as high as 50% to 70% in extreme cases. Moreover, there were cases where the estimated Q value was lower than the minimum limit of 6.283.

[0006] Given the shortcomings of the aforementioned algorithms, it is essential for those skilled in the art to research and implement an effective method for extracting the formation quality factor Q value. Summary of the Invention

[0007] The purpose of this invention is to provide a method, apparatus, device, and storage medium for extracting formation quality factors, in order to solve one or more defects of the peak frequency shift method, spectral ratio method, and frequency centroid shift method based on VSP well data proposed in the background art.

[0008] To achieve the above objectives, a first aspect of the present invention provides a method for extracting formation quality factors, the method comprising:

[0009] First arrival data were extracted from VSP well data, and velocity stratification was performed on the first arrival data. After velocity stratification, the layer velocity and depth interval of each layer were obtained.

[0010] For each layer, an amplitude curve fitting process is performed to obtain the fitted amplitude curve for each layer.

[0011] The initial depth amplitude and the final depth amplitude of the first arrival wave at each layer are determined by using the fitted amplitude curve corresponding to that layer. The attenuation factor corresponding to that layer is then calculated based on the initial depth amplitude, the final depth amplitude, the depth interval of that layer, and the layer velocity.

[0012] The formation quality factor of the stratum is calculated based on each attenuation factor and the dominant frequency information of the corresponding stratum.

[0013] The amplitude curve fitting process is as follows:

[0014] The first arrival data received at this layer is subjected to time-frequency transformation to obtain the amplitude values ​​of each acquisition depth in the first arrival data. The amplitude values ​​of the first arrival data in the frequency domain at the dominant frequency or in a narrow band near the dominant frequency are curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

[0015] Optionally, when calculating the attenuation factor corresponding to the layer based on the initial depth amplitude value, the final depth amplitude value, the depth interval of the layer, and the layer velocity, the following formula is used for calculation:

[0016]

[0017] Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

[0018] Optionally, when calculating the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, the following formula is used for calculation:

[0019] Where Q represents the formation quality factor, α represents the attenuation factor, and w represents the dominant frequency of the formation.

[0020] Optionally, the first arrival data received at this layer undergoes time-frequency transformation to obtain the amplitude values ​​at each acquisition depth in the first arrival data. The amplitude values ​​of the first arrival data at the dominant frequency or within a narrow band near the dominant frequency in the frequency domain are then curve-fitted according to the acquisition depth to obtain a fitted amplitude curve. Specifically:

[0021] Select the first arrival wave data received at this layer;

[0022] After performing Fourier transform on the first arrival wave data received at this layer, the frequency domain expression of the first arrival wave data at each acquisition depth within this layer is obtained;

[0023] For each acquisition depth, according to the frequency domain expression, determine the amplitude value of the main frequency single frequency of the first arrival wave data in the frequency domain, or the average value of each amplitude value within a narrow band range near the main frequency, and determine the amplitude value of the main frequency corresponding to this acquisition depth as the amplitude value of the main frequency single frequency or this average value. The narrow band range near the main frequency is w0 - Δw to w0 + Δw, where w0 represents the main frequency of the first arrival wave data of this layer, and Δw > 0;

[0024] Perform curve fitting on the amplitude values of the main frequency corresponding to each acquisition depth according to the acquisition depth to obtain a fitted amplitude curve.

[0025] Optionally, perform curve fitting on the amplitude values of the main frequency corresponding to each acquisition depth in a logarithmic coordinate system according to the acquisition depth.

[0026] Optionally, the value range of Δw is 2 to 5.

[0027] Optionally, when extracting the first arrival wave data from the VSP well data, perform first arrival wave amplitude picking and excision according to the first preset rule. The first preset rule is specifically:

[0028] After picking up the time t of the peak amplitude of the first arrival wave from the VSP well data, move upward according to the peak amplitude time t, and the moving time point is the second time point t1 of positive and negative change;

[0029] Move downward according to the peak amplitude time t, and the moving time point is the first or second time point t2 of positive and negative change;

[0030] Set a transition zone according to the time point t1 and the time point t2, and the transition zone interval is expressed as taper;

[0031] Set the amplitude of the first arrival wave within t < t1 - taper and t > t2 + taper to 0, keep the amplitude of the first arrival wave within t1 < t < t2 unchanged, multiply the amplitude of the first arrival wave within t1 < t < t1 by the coefficient k1, and multiply the amplitude of the first arrival wave within t2 < t < t + taper by the coefficient k2;

[0032] Where, k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

[0033] The second aspect of the embodiments of the present invention provides a formation quality factor extraction device, and the device includes:

[0034] A first arrival wave extraction module, configured to extract first arrival wave data from VSP well data;

[0035] The velocity stratification module is used to perform velocity stratification on the first arrival data extracted from VSP well data. After velocity stratification, the layer velocity and depth interval of each layer are obtained.

[0036] The amplitude curve fitting module is used to perform an amplitude curve fitting process for each layer to obtain the fitted amplitude curve for each layer.

[0037] The attenuation factor calculation module is used to determine the initial depth amplitude value and the final depth amplitude value of the first arrival wave of each layer using the fitted amplitude curve corresponding to each layer, and to calculate the attenuation factor corresponding to the layer based on the initial depth amplitude value, the final depth amplitude value, the depth interval of the layer and the layer velocity.

[0038] The formation quality factor calculation module is used to calculate the formation quality factor of a given stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum.

[0039] The amplitude curve fitting process is as follows:

[0040] The first arrival data received at this layer is subjected to time-frequency transformation to obtain the amplitude values ​​of each acquisition depth in the first arrival data. The amplitude values ​​of the first arrival data in the frequency domain at the dominant frequency or in a narrow band near the dominant frequency are curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

[0041] Optionally, when the attenuation factor calculation module calculates the attenuation factor corresponding to the layer based on the starting depth amplitude value, the ending depth amplitude value, the depth interval of the layer, and the layer velocity, it uses the following formula for calculation:

[0042] Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

[0043] Optionally, when the formation quality factor calculation module calculates the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, it uses the following formula for calculation:

[0044] Where Q represents the formation quality factor, α represents the attenuation factor, and w represents the dominant frequency of the formation.

[0045] Optionally, when the amplitude curve fitting module performs the amplitude curve fitting process, it performs time-frequency transformation on the first arrival data received at that layer to obtain the amplitude values ​​at each acquisition depth in the first arrival data. It then performs curve fitting on the amplitude values ​​of the first arrival data at the dominant frequency or within a narrow band near the dominant frequency in the frequency domain according to the acquisition depth to obtain the fitted amplitude curve. The specific process is as follows:

[0046] Select the first arrival wave data received at this layer;

[0047] After performing a Fourier transform on the first arrival data received at this layer, the frequency domain representation of the first arrival data at each acquisition depth within this layer is obtained.

[0048] For each acquisition depth, the amplitude value of the first arrival data at the dominant frequency in the frequency domain, or the average of the amplitude values ​​in a narrow band near the dominant frequency, is determined according to the frequency domain expression. The amplitude value of the dominant frequency or the average value is then determined as the dominant frequency amplitude value corresponding to the acquisition depth. The narrow band near the dominant frequency is w0-Δw to w0+Δw, where w0 represents the dominant frequency of the first arrival data at that layer, and Δw is greater than 0.

[0049] The dominant frequency amplitude value corresponding to each acquisition depth is curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

[0050] Optionally, when the amplitude curve fitting module performs the amplitude curve fitting process, it performs curve fitting on the main frequency amplitude value corresponding to each acquisition depth in a logarithmic coordinate system according to the acquisition depth.

[0051] Optionally, the value of Δw can be in the range of 2 to 5.

[0052] Optionally, when the first arrival extraction module extracts first arrival data from VSP well data, it performs first arrival amplitude picking and cutting according to a first preset rule. The first preset rule is specifically as follows:

[0053] After obtaining the peak amplitude time t of the first arrival wave from the VSP well data, the peak amplitude time t is moved upwards, and the moving time point is the second positive and negative change time point t1;

[0054] Based on the peak amplitude time t, move downwards, and the moving time point is the first or second time point of positive or negative change t2;

[0055] The transition zone is set based on time point t1 and time point t2, and the interval of the transition zone is represented by taper.

[0056] Set the amplitude of the first arrival wave within t < t1 - taper and t > t2 + taper to 0, keep the amplitude of the first arrival wave within t1 < t < t2 unchanged, multiply the amplitude of the first arrival wave within t1 - taper < t < t1 by the coefficient k1, and multiply the amplitude of the first arrival wave within t2 < t < t2 + taper by the coefficient k2;

[0057] where k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

[0058] In the third aspect of the embodiments of the present invention, there is also provided a device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements a method for extracting formation quality factor as described in the first aspect of the embodiments of the present invention.

[0059] In the fourth aspect of the embodiments of the present invention, there is also provided a storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a method for extracting formation quality factor as described in the first aspect of the embodiments of the present invention.

[0060] It is known that the physical definition of the formation quality factor Q value is the energy attenuation ratio of a single - frequency wave propagating one wavelength (i.e., the relative energy attenuation per unit wavelength). The traditional spectrum ratio method, peak frequency shift method, and frequency centroid shift method mentioned in the background art often use approximate formulas for the convenience of Q - value calculation. Such approximate formulas have large errors when estimating the Q value of a strongly absorbing attenuation medium. Through theoretical calculation, the error is as high as 50 - 70%. In addition, when estimating the Q value using methods such as the spectrum ratio method and peak shift method, there will be a situation where the estimated Q value is lower than the lowest limit of 6.283 during the near - surface absorption attenuation process, and this situation often occurs during near - surface Q - value estimation. However, the present invention uses an accurate calculation formula based on the physical definition of the Q value, with a theoretical error of 0. At the same time, the traditional spectrum ratio method, peak frequency shift method, and frequency centroid shift method mostly adopt the method of calculating point - by - point for each layer. The Q value calculated for each layer is very sensitive to the change of the data source, resulting in unstable Q values extracted. When calculating the Q value for each layer in the present invention, the technical concept of multi - point fitting is adopted to fit the amplitude curve, automatically eliminating the large - error data existing in the data source. The Q value obtained by this regression - statistics - based method is more robust;

[0061] In summary, the present invention uses VSP well data as the data source for extracting the formation quality factor, combines an accurate Q - value calculation formula and a regression - statistics method during extraction, and realizes high - precision, high - stability, and high - convenience Q - value extraction.

[0062] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0063] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0064] Figure 1 This is a schematic diagram illustrating the error generated by the conventional Q-value extraction method proposed in the background art, which uses an approximate formula to estimate the Q-value.

[0065] Figure 2 This is a schematic flowchart illustrating a formation quality factor extraction method implemented in an embodiment.

[0066] Figure 3 The image shows the first arrival extraction results without clutter removal.

[0067] Figure 4 The first arrival wave extraction result is shown when clutter removal is not precise.

[0068] Figure 5 This is a diagram showing the first arrival wave extraction result when performing fine excision based on the first preset rule;

[0069] Figure 6 A schematic diagram of velocity stratification;

[0070] Figure 7 This is a schematic diagram of the amplitude curve fitting results;

[0071] Figure 8 This is a comparison chart of the formation quality factors obtained in the example and those obtained using the peak frequency shift method.

[0072] Figure 9 This is a block diagram of a formation quality factor extraction device implemented in an embodiment. Detailed Implementation

[0073] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0074] Method Implementation Examples

[0075] Please see Figure 2 This invention proposes a method for extracting formation quality factors, which specifically includes the following implementation steps:

[0076] S100. Acquire VSP well data after loading the observation system, anomalous amplitude attenuation, and three-component azimuth rotation. Extract first arrival data from the P-component data of the VSP well data, and perform velocity stratification on the first arrival data. After velocity stratification, obtain the layer velocity and depth interval for each layer. The depth interval for each layer refers to the difference between the termination depth and the starting depth of that layer.

[0077] Among them, combined Figure 6 As shown, velocity stratification of the first-arrival wave data can be performed using a known velocity stratification model or algorithm module from a typical embodiment, for example:

[0078] S01. Calculate the layer velocity based on the first arrival wave data. The calculation formula is shown in Equation 1:

[0079] V=(Depth(i)-Depth(i-1)) / (t(i)-t(i-1))(Formula 1);

[0080] Where Depth(i) represents the acquisition depth i, Depth(i-1) represents the acquisition depth i-1, t(i) represents the time when the first arrival wave data is acquired at acquisition depth i, and t(i-1) represents the time when the first arrival wave data is acquired at acquisition depth i-1.

[0081] S02. Smooth the calculated layer velocity.

[0082] S03. Layering is performed based on the smoothed layer velocity, resulting in the depth interval of each layer. Layering can be performed automatically using methods such as interactive operations or methods utilizing intra-layer differences, ordered clustering, or extreme value variance clustering. This embodiment does not describe this part in detail.

[0083] In addition, when extracting first arrival data from the P component data of VSP well data, the interception and filtering of the first arrival can be performed using the first arrival preprocessing method in the general embodiment.

[0084] For example, in one embodiment, the first-arrival preprocessing method in the general embodiment is improved as follows:

[0085] S100. Acquire VSP well data after loading the observation system, anomalous amplitude attenuation, and three-component azimuth rotation. Extract first arrival data from the P component data of the VSP well data and perform velocity layering on the first arrival data. After velocity layering, obtain the layer velocity and depth interval of each layer.

[0086] Among them, when extracting the first arrival wave data from the P-component data of the VSP well data, the first arrival wave amplitude picking and excision are performed according to the first preset rule, and the first preset rule is a refined first arrival wave waveform intercepting and filtering rule. Specifically, the first preset rule specifically refers to:

[0087] After picking the first arrival wave peak amplitude time t from the VSP well data, move upward according to the peak amplitude time t, and the moving time point is the second positive and negative change time point t1;

[0088] Move downward according to the peak amplitude time t, and the moving time point is the first or second positive and negative change time point t2;

[0089] Set a transition band according to the time point t1 and the time point t2, and the transition band interval is expressed as taper;

[0090] Set the amplitude of the first arrival wave within t < t1 - taper and t > t2 + taper to 0, keep the amplitude of the first arrival wave within t1 < t < t2 unchanged, multiply the amplitude of the first arrival wave within t1 - taper < t < t1 by the coefficient k1, and multiply the amplitude of the first arrival wave within t2 < t < t2 + taper by the coefficient k2;

[0091] Among them, k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

[0092] Preferably, the value of the above-mentioned taper can be preset to 5 or 10.

[0093] Figure 3-5 The figure of the first arrival wave extraction result without clutter excision, the figure of the first arrival wave extraction result with non-precise clutter excision, and the figure of the first arrival wave extraction result with precise excision based on the above first preset rule are successively shown. Compared with the prior art without clutter excision or non-precise clutter excision, picking and excising the first arrival wave according to the first preset rule filters out the clutter interference in the first arrival wave data and effectively supports the extraction accuracy of the subsequent formation quality factor.

[0094] S200. For each layer, perform an amplitude curve fitting process to obtain the fitting amplitude curve corresponding to each layer.

[0095] Among them, the amplitude curve fitting process is specifically as follows:

[0096] S20I. Perform time-frequency transformation on the first arrival wave data received at this layer to obtain the amplitude values of each acquisition depth in the first arrival wave data, and perform curve fitting on the amplitude values of the main frequency single frequency in the frequency domain of the first arrival wave data or the amplitude values within a narrow band near the main frequency according to the acquisition depth to obtain the fitting amplitude curve.

[0097] For example, in one embodiment, S201 specifically includes the following sub-steps:

[0098] S001. Select the first arrival wave data received at this layer.

[0099] S002. After performing a Fourier transform on the first arrival data received at this layer, the frequency domain representation of the first arrival data at each acquisition depth within this layer is obtained.

[0100] The expression for the Fourier transform is: f(x,t) represents the first arrival data received at this layer, and T_max represents the data collected at various depths x within this layer. i The maximum time interval between the received first arrival wave, w represents the frequency, F(x) i ,w) represents the frequency domain representation of f(x,t);

[0101] S003. For each acquisition depth, determine the amplitude value of the dominant single frequency of the first arrival data in the frequency domain, or the average of the amplitude values ​​within a narrow band near the dominant frequency, based on the frequency domain expression described above. The amplitude value of the dominant single frequency or this average value is then determined as the dominant frequency amplitude value corresponding to that acquisition depth. The narrow band near the dominant frequency is w0-Δw to w0+Δw, where w0 represents the dominant frequency of the first arrival data at that layer, and Δw is greater than 0. The amplitude values ​​within the narrow band near the dominant frequency are represented as A(x i ,w j )=|F(x i ,w j )|,j=1,2,...n,w j This represents a specific frequency within a narrow band near the main frequency, where n represents the number of such specific frequencies.

[0102] S004. For each acquisition depth, perform curve fitting on the corresponding main frequency amplitude value according to the acquisition depth to obtain the fitted amplitude curve. The fitted amplitude curve is the minimum error curve obtained based on, for example, the least squares method, and can be expressed as: fitness represents the fitting curve function, which is the relationship curve between the main frequency amplitude value and the acquisition depth at each acquisition depth.

[0103] Due to factors such as frequency shift, directly selecting the amplitude value of the dominant single frequency for amplitude curve fitting can lead to inaccurate fitting of the amplitude curve. By selecting an effective frequency band (narrow band near the dominant frequency) centered on the dominant frequency of the first arrival wave data, the above problem can be effectively overcome by calculating the mean amplitude value within the effective frequency band, thereby improving the accuracy of the fitted amplitude curve. The value of Δw can be empirically determined according to the specific application scenario. For example, the preferred range of Δw is 2 to 5, and Δw can be 2 or 5.

[0104] In one embodiment, for example:

[0105] S004. Perform curve fitting on the main frequency amplitude values ​​corresponding to each acquisition depth according to the acquisition depth to obtain the fitted amplitude curve;

[0106] Specifically, the dominant frequency amplitude values ​​corresponding to each acquisition depth are subjected to curve fitting in a logarithmic coordinate system according to the acquisition depth. For example... Figure 7 As shown, based on the characteristic that the amplitude value of the main frequency corresponding to each acquisition depth decreases exponentially with the acquisition depth, the amplitude value and the acquisition depth have a very obvious linear characteristic in the logarithmic coordinate system. By fitting in the logarithmic coordinate system, the amplitude anomaly points are effectively eliminated, and the accuracy of the amplitude curve fitting is improved.

[0107] S300. Use the fitted amplitude curve corresponding to each layer to determine the initial depth amplitude value and the final depth amplitude value of the first arrival wave of that layer, and calculate the attenuation factor corresponding to that layer based on the initial depth amplitude value, the final depth amplitude value, the depth interval of that layer and the layer velocity.

[0108] For example, in one embodiment, when calculating the attenuation factor corresponding to the layer based on the starting depth amplitude value, the ending depth amplitude value, the depth interval of the layer, and the layer velocity, Equation 2 is used for calculation:

[0109]

[0110] Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

[0111] S400. The formation quality factor of the corresponding stratum is calculated based on each attenuation factor and the dominant frequency information of the corresponding stratum.

[0112] For example, in one embodiment, when calculating the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, Equation 3 is used for calculation:

[0113]

[0114] Where Q represents the formation quality factor, α represents the attenuation factor, and w represents the dominant frequency of the formation.

[0115] Based on the physical definition of the formation quality factor Q, the formula for calculating the formation quality factor Q is:

[0116]

[0117] Equation 4 is equivalent to:

[0118]

[0119] Equation 5 can be equivalent to:

[0120]

[0121] Based on the fitted amplitude curve, the formula for calculating the attenuation factor is:

[0122]

[0123] By combining the fitted amplitude curve and the formation quality factor extracted by Equations 2 and 3, a precise calculation method based on the physical definition of Q value is proposed, which achieves theoretical zero error compared to the approximate formulas used in traditional extraction methods in the background technology.

[0124] Combination Figure 8 As shown, the AmpFit curve is a schematic diagram of the Q value obtained by the formation quality factor extraction method implemented in this embodiment, and the PeakFreFit curve is a schematic diagram of the Q value obtained by the traditional peak frequency shift method in the background technology. The comparison shows that the AmpFit curve is more robust.

[0125] Device Examples

[0126] Please refer to Figure 9 The present invention also provides a formation quality factor extraction device, specifically including a first arrival wave extraction module, a velocity stratification module, an amplitude curve fitting module, an attenuation factor calculation module, and a formation quality factor calculation module. The velocity stratification module is connected to the first arrival wave extraction module and the amplitude curve fitting module, respectively, and the attenuation factor calculation module is connected to the amplitude curve fitting module and the formation quality factor calculation module, respectively.

[0127] Specifically, the first-arrival extraction module acquires VSP well data after loading by the observation system, anomalous amplitude attenuation, and three-component azimuth rotation, and extracts first-arrival data from the P-component data of the VSP well data. The velocity stratification module performs velocity stratification on the first-arrival data extracted from the VSP well data, obtaining the layer velocity and depth interval for each layer. The amplitude curve fitting module performs amplitude curve fitting for each layer, obtaining the fitted amplitude curve for each layer. The attenuation factor calculation module uses the fitted amplitude curve for each layer to determine the initial and final depth amplitude values ​​of the first-arrival for that layer, and calculates the attenuation factor corresponding to that layer based on the initial and final depth amplitude values, the depth interval, and the layer velocity. The formation quality factor calculation module calculates the formation quality factor for each layer based on each attenuation factor and the dominant frequency information of the corresponding layer. The amplitude curve fitting process is as follows: the first arrival wave data received at this layer is subjected to time-frequency transformation to obtain the amplitude value of each acquisition depth in the first arrival wave data. The amplitude value of the first arrival wave data in the frequency domain at the main frequency or in a narrow band near the main frequency is curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

[0128] Preferably, when the attenuation factor calculation module calculates the attenuation factor corresponding to the layer based on the initial depth amplitude value, the final depth amplitude value, the depth interval of the layer, and the layer velocity, it uses the following formula for calculation: Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

[0129] Preferably, when the formation quality factor calculation module calculates the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, it uses the following formula for calculation: Where Q represents the formation quality factor, α represents the attenuation factor, and w represents the dominant frequency of the formation.

[0130] Preferably, when the amplitude curve fitting module performs the amplitude curve fitting process, it performs time-frequency transformation on the first arrival data received at that layer to obtain the amplitude values ​​at each acquisition depth in the first arrival data. Then, it performs curve fitting on the amplitude values ​​of the first arrival data at the dominant frequency or within a narrow band near the dominant frequency in the frequency domain according to the acquisition depth to obtain the fitted amplitude curve. The specific process is as follows:

[0131] Select the first arrival wave data received at this layer;

[0132] After performing a Fourier transform on the first arrival data received at this layer, the frequency domain representation of the first arrival data at each acquisition depth within this layer is obtained.

[0133] For each acquisition depth, determine the amplitude value of the dominant frequency single frequency of the first arrival wave data in the frequency domain or the mean value of each amplitude value within a narrow band near the dominant frequency according to the frequency domain expression, and determine the amplitude value of the dominant frequency corresponding to this acquisition depth as the amplitude value of the dominant frequency single frequency or this mean value. The narrow band near the dominant frequency is w0 - Δw to w0 + Δw, where w0 represents the dominant frequency of the first arrival wave data of this horizon, and Δw > 0;

[0134] Perform curve fitting on the amplitude values of the dominant frequency corresponding to each acquisition depth according to the acquisition depth to obtain a fitted amplitude curve.

[0135] Preferably, when the amplitude curve fitting module performs the amplitude curve fitting process, perform curve fitting on the amplitude values of the dominant frequency corresponding to each acquisition depth in a logarithmic coordinate system according to the acquisition depth.

[0136] Preferably, the value range of Δw is 2 to 5.

[0137] Preferably, when the first arrival wave extraction module extracts the first arrival wave data from the VSP well data, pick up and cut the amplitude of the first arrival wave according to the first preset rule. The first preset rule is specifically:

[0138] After picking up the time t of the peak amplitude of the first arrival wave from the VSP well data, move upward according to the peak amplitude time t, and the moving time point is the second time point t1 of positive and negative change;

[0139] Move downward according to the peak amplitude time t, and the moving time point is the first or second time point t2 of positive and negative change;

[0140] Set a transition zone according to the time point t1 and the time point t2, and the transition zone interval is expressed as taper;

[0141] Set the amplitude of the first arrival wave within t < t1 - taper and t > t2 + taper to 0, keep the amplitude of the first arrival wave within t1 < t < t2 unchanged, multiply the amplitude of the first arrival wave within t1 - taper < t < t1 by the coefficient k1, and multiply the amplitude of the first arrival wave within t2 < t < t2 + taper by the coefficient k2. Here, k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement without creative efforts.

[0143] On the other hand, the present invention also provides an apparatus, specifically including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it can implement the formation quality factor extraction method mentioned in the method embodiments.

[0144] On the other hand, the present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, can implement the formation quality factor extraction method mentioned in the method embodiments.

[0145] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for extracting formation quality factors, characterized in that, include: First arrival data were extracted from VSP well data, and velocity stratification was performed on the first arrival data. After velocity stratification, the layer velocity and depth interval of each layer were obtained. For each layer, an amplitude curve fitting process is performed to obtain the fitted amplitude curve for each layer. The initial depth amplitude and the final depth amplitude of the first arrival wave at each layer are determined by using the fitted amplitude curve corresponding to that layer. The attenuation factor corresponding to that layer is then calculated based on the initial depth amplitude, the final depth amplitude, the depth interval of that layer, and the layer velocity. The formation quality factor of the stratum is calculated based on each attenuation factor and the dominant frequency information of the corresponding stratum. The amplitude curve fitting process is as follows: The first arrival data received at this layer is subjected to time-frequency transformation to obtain the amplitude values ​​of each acquisition depth in the first arrival data. The amplitude values ​​of the first arrival data in the frequency domain at the dominant frequency or in a narrow band near the dominant frequency are curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

2. The method for extracting formation quality factors according to claim 1, characterized in that, When calculating the attenuation factor corresponding to the layer based on the initial depth amplitude value, the final depth amplitude value, the depth interval of the layer, and the layer velocity, the following formula is used: Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

3. The method for extracting formation quality factors according to claim 1, characterized in that, When calculating the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, the following formula is used: Where Q represents the formation quality factor, α represents the attenuation factor, and w represents the dominant frequency of the formation.

4. The method for extracting formation quality factors according to claim 1, characterized in that, The process involves performing a time-frequency transformation on the first arrival data received at this layer to obtain the amplitude values ​​at each acquisition depth in the first arrival data. Then, the amplitude values ​​of the first arrival data at the dominant frequency or within a narrow band near the dominant frequency in the frequency domain are curve-fitted according to the acquisition depth to obtain a fitted amplitude curve. Specifically: Select the first arrival wave data received at this layer; After performing a Fourier transform on the first arrival data received at this layer, the frequency domain representation of the first arrival data at each acquisition depth within this layer is obtained. For each acquisition depth, the amplitude value of the first arrival data at the dominant frequency in the frequency domain, or the average of the amplitude values ​​in a narrow band near the dominant frequency, is determined according to the frequency domain expression. The amplitude value of the dominant frequency or the average value is then determined as the dominant frequency amplitude value corresponding to the acquisition depth. The narrow band near the dominant frequency is w0-Δw to w0+Δw, where w0 represents the dominant frequency of the first arrival data at that layer, and Δw is greater than 0. The dominant frequency amplitude value corresponding to each acquisition depth is curve-fitted according to the acquisition depth to obtain the fitted amplitude curve.

5. The method for extracting formation quality factors according to claim 4, characterized in that, The dominant frequency amplitude values ​​corresponding to each acquisition depth are fitted with curves in a logarithmic coordinate system according to the acquisition depth.

6. The method for extracting formation quality factors according to claim 4, characterized in that, The value of Δw ranges from 2 to 5.

7. The method for extracting formation quality factors according to claim 1, characterized in that, When extracting first arrival data from VSP well data, the first arrival amplitude is picked up and cut off according to a first preset rule. The first preset rule is as follows: After obtaining the peak amplitude time t of the first arrival wave from the VSP well data, the peak amplitude time t is moved upwards, and the moving time point is the second positive and negative change time point t1; Based on the peak amplitude time t, move downwards, and the moving time point is the first or second time point of positive or negative change t2; The transition zone is set based on time point t1 and time point t2, and the interval of the transition zone is represented by taper. Set the amplitudes of the first arrival waves within t < t1 - taper and t > t2 + taper to 0, keep the amplitudes of the first arrival waves within t1 < t < t2 unchanged, multiply the amplitudes of the first arrival waves within t1 - taper < t < t1 by the coefficient k1, and multiply the amplitudes of the first arrival waves within t2 < t < t2 + taper by the coefficient k2; where k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

8. A formation quality factor extraction device, characterized in that, It includes: A first arrival wave extraction module for extracting first arrival wave data from VSP well data; A velocity layering module for performing velocity layering on the first arrival wave data extracted from VSP well data, and obtaining the layer velocity and depth interval of each layer after velocity layering; An amplitude curve fitting module for performing an amplitude curve fitting process for each layer and obtaining the corresponding fitting amplitude curve for each layer; An attenuation factor calculation module for determining the starting depth amplitude value and ending depth amplitude value of the first arrival wave of the layer using the fitting amplitude curve corresponding to each layer, and calculating the attenuation factor corresponding to the layer according to the starting depth amplitude value, ending depth amplitude value, depth interval and layer velocity of the layer; A formation quality factor calculation module for calculating the formation quality factor of the layer according to each attenuation factor and the main frequency information of the corresponding layer; The amplitude curve fitting process is specifically as follows: Perform time-frequency transformation on the first arrival wave data received at this layer to obtain the amplitude values of each acquisition depth in the first arrival wave data, and perform curve fitting on the amplitude values of the main frequency single frequency in the frequency domain of the first arrival wave data or the amplitude values within a narrow band near the main frequency according to the acquisition depth to obtain the fitting amplitude curve.

9. The formation quality factor extraction device according to claim 8, characterized in that, When the attenuation factor calculation module calculates the attenuation factor corresponding to the layer according to the starting depth amplitude value, ending depth amplitude value, depth interval and layer velocity of the layer, the following formula is used for calculation: Where α represents the attenuation factor and v represents the layer velocity. Indicates the termination depth amplitude value. Δx represents the initial depth amplitude value, and Δx represents the depth interval of that layer.

10. The formation quality factor extraction device according to claim 8, characterized in that, When the formation quality factor calculation module calculates the formation quality factor of a stratum based on each attenuation factor and the dominant frequency information of the corresponding stratum, it uses the following formula for calculation: where Q represents the formation quality factor, α represents the attenuation factor, and w represents the main frequency of this layer.

11. The formation quality factor extraction device according to claim 8, characterized in that, When the amplitude curve fitting module performs the amplitude curve fitting process, it performs time-frequency transformation on the first arrival wave data received at this layer to obtain the amplitude values of each acquisition depth in the first arrival wave data, and performs curve fitting on the amplitude values of the main frequency single frequency in the frequency domain of the first arrival wave data or the amplitude values within a narrow band near the main frequency according to the acquisition depth to obtain the fitting amplitude curve. The specific process is as follows: Select the first arrival wave data received at this layer; Perform Fourier transform on the first arrival wave data received at this layer to obtain the frequency domain expression of the first arrival wave data at each acquisition depth within this layer; For each acquisition depth, determine the amplitude value of the main frequency single frequency in the frequency domain of the first arrival wave data or the mean value of each amplitude value within a narrow band near the main frequency according to the frequency domain expression, and determine the amplitude value of the main frequency single frequency or the mean value as the main frequency amplitude value corresponding to this acquisition depth. The narrow band near the main frequency is w0 - Δw ∼ w0 + Δw, w0 represents the main frequency of the first arrival wave data of this layer, and Δw > 0; Perform curve fitting on the main frequency amplitude values corresponding to each acquisition depth according to the acquisition depth to obtain the fitting amplitude curve.

12. The formation quality factor extraction device according to claim 11, characterized in that, When the amplitude curve fitting module performs the amplitude curve fitting process, the main frequency amplitude values corresponding to each acquisition depth are curve-fitted in a logarithmic coordinate system according to the acquisition depth.

13. The formation quality factor extraction device according to claim 11, characterized in that, The value range of the said Δw is 2 to 5.

14. The formation quality factor extraction device according to claim 8, characterized in that, When the first arrival wave extraction module extracts the first arrival wave data from the VSP well data, the first arrival wave amplitude picking and excision are carried out according to the first preset rule, and the specific content of the first preset rule is as follows: After picking up the first arrival wave peak amplitude time t from the VSP well data, move upward according to the peak amplitude time t, and the moving time point is the second positive and negative change time point t1; Move downward according to the peak amplitude time t, and the moving time point is the first or second positive and negative change time point t2; Set a transition zone according to the time point t1 and the time point t2, and the transition zone interval is expressed as taper; Set the amplitude of the first arrival wave within t < t1 - taper and t > t2 + taper to 0, keep the amplitude of the first arrival wave within t1 < t < t2 unchanged, multiply the amplitude of the first arrival wave within t1 - taper < t < t1 by the coefficient k1, and multiply the amplitude of the first arrival wave within t2 < t < t2 + taper by the coefficient k2; Where, k1 = (t - t1 + taper) / taper; k2 = (t2 - t + taper) / taper.

15. An apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the said program, it realizes a method for extracting formation quality factor as described in any one of claims 1 to 7.

16. A storage medium having a computer program stored thereon, characterized in that, When the said computer program is executed by the processor, it realizes a method for extracting formation quality factor as described in any one of claims 1 to 7.

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