Seismic signal energy compensation method and device, storage medium and processor

Abstract

The embodiment of the invention provides a seismic signal energy compensation method and device, a storage medium and a processor, and belongs to the technical field of geological survey. The seismic signal energy compensation method comprises the following steps: performing compensation scanning on a seismic signal of each typical position point in a target area, and analyzing a scanning result to determine a quality factor value of each typical position point; fitting the dominant frequency and the quality factor value of each typical position point, and calculating the quality factor value of each position point according to a calculation formula obtained by fitting and the dominant frequencies of other position points in the target area; and performing energy compensation on the seismic signals at the corresponding positions according to the quality factor value of each position point through an inverse Q filtering algorithm. For the seismic signal at the loose structure position in the near-surface low-deceleration zone stratum of the target area, the method can perform energy compensation on the condition that the seismic signal is absorbed to different degrees, greatly improve the working efficiency, enhance the transverse consistency of wavelets, and reduce the influence on the seismic signal of the underlying stratum.

Description

Technical Field

[0001] The present invention relates to the field of geological survey technology, and in particular to a method, device, storage medium and processor for compensating energy of seismic signals. Background Art

[0002] High-resolution seismic is a necessary means for today's fine oil and gas exploration, and ensuring a high frequency of received seismic waves is the basis for the effective implementation of this type of exploration method. However, the energy loss of seismic signals gradually accumulates during the propagation of the formation, especially in the near-surface low-velocity zone formation. Due to the low degree of compaction, the energy absorption of high-frequency signals is more serious, which affects the resolution of seismic data and the lateral consistency of sub-waves, resulting in insufficient energy resolution for deep seismic signals, which cannot meet the needs of later geological exploration.

[0003] There are currently three main solutions to this problem:

[0004] The first is the deterministic compensation method, which estimates the Q value of the near-surface formation (i.e., the formation quality factor) through field dual-well micro-logging data, obtains the Q value of the near-surface formation at the micro-logging point, and then obtains the Q value of the near-surface formation in the entire work area through plane interpolation, and then performs inverse Q filtering on the seismic data. This method requires field data collection, has a long construction period, is very expensive, and has limited points, so it is mostly used as a constraint condition;

[0005] The second is the relative compensation method, which mainly uses the main frequency information of the first-arrival wavelet or the reflected signal to perform frequency shift method or spectral ratio method to obtain the relative Q value, and then compensates through inverse Q filtering. This method is an algorithm based on field seismic data collection and is also the most commonly used algorithm. However, this method requires obtaining a lot of information such as surface travel time and the main frequency of a single-channel seismic signal. It requires special auxiliary software to implement, the amount of information statistics is huge, and the period is also long;

[0006] The third is the time-frequency analysis method, which performs time-frequency analysis on the original data and then uses deconvolution or other algorithms to compensate for different frequency bands. This method is based on the time-frequency analysis of typical guns and uses other frequency extension algorithms to eliminate the low-frequency phenomenon, and the physical meaning is unclear.

[0007] Therefore, in order to meet the needs of fast-paced exploration and effectively shorten the processing cycle, it is necessary to develop a more efficient compensation method with clear physical meaning. Summary of the invention

[0008] The purpose of the embodiment of the present invention is to provide a method for compensating the energy of seismic signals, which can quickly and clearly compensate for the inconsistent absorption of different frequency bands in the seismic signals.

[0009] In order to achieve the above object, an embodiment of the present invention provides an energy compensation method for seismic signals, comprising:

[0010] Perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0011] Fitting the main frequency and quality factor value of each typical location point, and calculating the quality factor value of each location point according to the calculation formula obtained by fitting and the main frequency of other location points in the target area; and

[0012] Through the inverse Q filtering algorithm, the energy compensation of the seismic signal at the corresponding position is performed according to the quality factor value of each position point.

[0013] Preferably, before performing the compensation scan, the data domain of the seismic signal is determined according to the following steps:

[0014] Obtain the plane distribution of the thickness of the low-velocity zone in the target area, including the thickness distribution of the weathered zone strata near the surface and the thickness distribution of the under-compacted strata;

[0015] Extract the main frequency of the seismic signal at each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area; and

[0016] Determine the degree of agreement between the main frequency plane distribution of different data domains and the thickness plane distribution of the low velocity reduction zone, and take the data domain with the highest agreement as the data domain of the seismic signal.

[0017] Furthermore, if the difference in the degree of consistency between the main frequency plane distribution and the low velocity reduction zone thickness plane distribution of different data domains is less than a preset range for two or more of the data domains that are ranked higher in the order of consistency, the surface morphology distribution in the target area is further obtained, and the degree of consistency between the main frequency plane distribution and the surface morphology distribution is determined from the data domain that is ranked higher in the order, and the data domain to which the one with the highest degree of consistency belongs is used as the data domain of the seismic signal, wherein the surface morphology distribution includes the distribution of surface type and surface elevation.

[0018] Preferably, if the data domain is determined to be a detection point domain, the seismic signal is a detection point gather;

[0019] If the data domain is determined to be a shot domain, the seismic signal is a shot point gather;

[0020] If the data domain is determined to be a common center point domain, the seismic signal is a common center point gather.

[0021] Optionally, the typical location points are location points representing different surface morphology types, surface elevations, and / or low velocity reduction zone thicknesses.

[0022] Optionally, a compensation scan is performed on the seismic signals of each typical location point in the target area, and the scan results are analyzed to determine the quality factor value of each typical location point, including:

[0023] Obtain seismic signals at each typical location;

[0024] Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values; and

[0025] When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

[0026] Furthermore, the predetermined screening condition is that the consistency of the spectrum distribution and the signal-to-noise ratio of the compensated seismic signal both reach a preset range.

[0027] Optionally, the fit is a polynomial fit.

[0028] Preferably, the calculation formula is: Q = a n F n +a n-1 F n-1 ...+a 1 F+a 0 (n>=1),

[0029] Where Q is the quality factor, F is the main frequency of the seismic signal, and a is n 、a n-1 、a 1 、a 0 is the partial coefficient obtained by fitting, and n is the number of terms in the obtained polynomial.

[0030] Optionally, energy compensation of the seismic signal at the corresponding position is performed according to the quality factor value of each position point, including:

[0031] The low velocity reduction zone formation is equivalent to a layer of medium. During the compensation process, only space-varying Q compensation is performed, and the Q value is a constant in the time direction.

[0032] The seismic signal is converted from the time domain to the frequency domain through Fourier transform, and the constant inverse Q filtering is performed using the e-exponential algorithm to compensate the seismic signal.

[0033] The seismic signal is converted from the frequency domain back to the time domain by inverse Fourier transform.

[0034] On the other hand, an embodiment of the present invention aims to provide an energy compensation device for seismic signals, comprising:

[0035] A compensation scanning module is used to perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0036] A fitting calculation module, used to fit the main frequency and quality factor value of each typical position point, and calculate the quality factor value of each position point according to the calculation formula obtained by fitting and the main frequency of other position points in the target area; and

[0037] The compensation calculation module is used to perform energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point through an inverse Q filtering algorithm.

[0038] Preferably, the energy compensation device for the seismic signal further comprises:

[0039] The data domain selection module is used to determine the data domain of the seismic signal according to the following steps before performing the compensation scan:

[0040] Obtain the plane distribution of the thickness of the low-velocity zone in the target area, including the thickness distribution of the weathered zone strata near the surface and the thickness distribution of the under-compacted strata;

[0041] Extract the main frequency of the seismic signal at each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area; and

[0042] Determine the degree of agreement between the main frequency plane distribution of different data domains and the thickness plane distribution of the low velocity reduction zone, and take the data domain with the highest agreement as the data domain of the seismic signal.

[0043] If the difference in the degree of coincidence between the main frequency plane distribution and the low velocity reduction zone thickness plane distribution of different data domains is less than the preset range in the ranking of the former, the surface morphology distribution in the target area is further obtained, and the degree of coincidence between the main frequency plane distribution and the surface morphology distribution is determined from the former in the ranking, and the data domain to which the one with the highest degree of coincidence belongs is used as the data domain of the seismic signal.

[0044] Among them, the surface morphology distribution includes the distribution of surface type and surface elevation.

[0045] Optionally, if the data domain selection module determines that the data domain is a detection point domain, the seismic signal is a detection point gather; if the data domain selection module determines that the data domain is a shot domain, the seismic signal is a shot point gather; if the data domain selection module determines that the data domain is a common center point domain, the seismic signal is a common center point gather.

[0046] Optionally, the typical location points are location points representing different surface morphology types, surface elevations, and / or low velocity reduction zone thicknesses.

[0047] Preferably, the compensation scanning module performs compensation scanning on the seismic signals of each typical position point in the target area, and analyzes the scanning results to determine the quality factor value of each typical position point, including:

[0048] Obtain seismic signals at each typical location;

[0049] Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values; and

[0050] When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

[0051] Furthermore, the predetermined screening condition is that the consistency of the spectrum distribution and the signal-to-noise ratio of the compensated seismic signal both reach a predetermined range.

[0052] Optionally, the fitting is a polynomial fitting, and the calculation formula is: Q = a n F n +a n-1 F n-1 ...+a 1 F+a 0 (n>=1),

[0053] Where Q is the quality factor, F is the main frequency of the seismic signal, and a is n 、a n-1 、a 1 、a 0 is the partial coefficient obtained by fitting, and n is the number of terms in the obtained polynomial.

[0054] Optionally, the compensation calculation module performs energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point, including:

[0055] The low velocity reduction zone formation is equivalent to a layer of medium. During the compensation process, only space-varying Q compensation is performed, and the Q value is a constant in the time direction.

[0056] The seismic signal is converted from the time domain to the frequency domain through Fourier transform, and the constant inverse Q filtering is performed using the e-exponential algorithm to compensate the seismic signal.

[0057] The seismic signal is converted from the frequency domain back to the time domain by inverse Fourier transform.

[0058] On the other hand, the present invention provides a machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the energy compensation method for seismic signals of the present application.

[0059] On the other hand, the present invention provides a processor, which is used to run a program, and when the program is run, it is used to execute the energy compensation method of the seismic signal of the present application.

[0060] Through the above technical scheme, when analyzing seismic signals between different strata, especially when analyzing seismic signals of near-surface low-velocity reduction zone strata with loose structures, the seismic signals of each typical position point are compensated and scanned to obtain the quality factor value of the corresponding position point, and then the frequency and quality factor data of multiple typical position points are polynomially fitted to obtain the corresponding relationship between the main frequency of the signal and the quality factor data, and then the quality factors of all position points are obtained, and the seismic signals of each position point are energy compensated. Therefore, energy compensation is performed for the different degrees of absorption in each signal frequency band of the seismic signal at the loosely structured position in the near-surface low-velocity reduction zone strata of the target area, which can enhance the lateral consistency of the sub-wave and reduce the impact on the seismic signal of the underlying strata. At the same time, the spectral distribution consistency and signal-to-noise ratio of the compensated seismic signal reach the preset range, and its physical meaning is clear, which is an efficient and reasonable energy compensation scheme.

[0061] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0063] Figure 1 is a flow chart of an embodiment of the method for compensating energy of seismic signals of the present invention;

[0064] Figure 2 is a flow chart of another embodiment of the method for compensating energy of seismic signals of the present invention;

[0065] Figure 3 yes Figure 2 Satellite images of the earth's surface of the embodiment;

[0066] Figure 4 yes Figure 2 An elevation plane distribution diagram of an embodiment;

[0067] Figure 5 yes Figure 2 Thickness distribution diagram of the low speed reduction belt of the embodiment;

[0068] Figure 6 yes Figure 2 A distribution diagram of main frequency information in the detection point domain of an embodiment;

[0069] Figure 7yes Figure 2 Single shot comparison diagram before and after surface absorption compensation of the embodiment;

[0070] Figure 8 is a structural diagram of an embodiment of the energy compensation device for seismic signals of the present invention; and

[0071] Fig. 9 It is a structural diagram of another embodiment of the energy compensation device for seismic signals of the present invention. DETAILED DESCRIPTION

[0072] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0073] The following combination Figure 1 An embodiment of the energy compensation method of the seismic signal of the present application is described, and its application scenarios include but are not limited to the gradual accumulation of energy loss of seismic signals during the propagation of the formation, especially in the near-surface low-velocity reduction zone formation. Due to the low degree of compaction, the energy absorption of high-frequency signals is more serious, resulting in insufficient energy resolution of deep seismic signals, which cannot meet the needs of later geological exploration. The energy compensation method of the seismic signal of the present application can be used to enhance the vertical resolution of seismic signals, the resolution of deep formations, the identification and characterization of thin reservoirs, and the tracking and identification of the spatial range of reservoir development. In addition, the energy compensation method of the seismic signal of the present application can also be used to assist in the setting of horizontal well targets and the design of well trajectories, thereby improving the drilling rate of horizontal wells. The implementation process is as follows:

[0074] Step 1: Perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0075] It should be noted that the quality factor value of a typical location point is called the Q value, and the absorption attenuation compensation factor value of the seismic signal at the location can be calculated through this parameter.

[0076] Step 2: Fit the main frequency and quality factor value of each typical location point, and calculate the quality factor value of each location point according to the calculation formula obtained by fitting and the main frequency of other location points in the target area;

[0077] Step 3: Through the inverse Q filtering algorithm, the energy of the seismic signal at the corresponding position is compensated according to the quality factor value of each position point.

[0078] In this embodiment, a polynomial fitting is performed for the correlation between the main frequency and the absorption strength of the formation in the near-surface low-velocity reduction zone to obtain the formation quality factor in the entire target area, and surface absorption compensation is performed based on this. After surface absorption compensation, the energy of the high-frequency part of the effective signal is effectively compensated, and the deep seismic resolution ability is greatly improved.

[0079] Compared with the prior art, the technical advantage of this embodiment is that the correspondence between the main frequency and the quality factor is utilized, that is, there is a correspondence between the main frequency and the formation quality factor of the location point, the actual values ​​of the main frequency and the quality factor of the typical location point are obtained and fitted, and the quality factor value of each location point is calculated according to the calculation formula obtained by fitting and the main frequency of other location points in the target area, and energy compensation is performed accordingly, which can improve the consistency of the spectrum distribution and the signal-to-noise ratio parameters of the compensated seismic signal, has a clear physical meaning, and is an efficient and reasonable energy compensation scheme.

[0080] In some embodiments, step one may specifically be:

[0081] Obtain seismic signals at each typical location;

[0082] Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values;

[0083] When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

[0084] The predetermined screening condition is that the consistency of the spectrum distribution and the signal-to-noise ratio of the compensated seismic signal both reach a preset range.

[0085] In some implementations, in step 2, a calculation formula for the corresponding relationship between the main frequency and the quality factor value can be obtained by a polynomial fitting method.

[0086] In this embodiment, the calculation formula may be, for example: Q = a n F n +a n-1 F n-1 ...+a 1 F+a 0 (n>=1),

[0087] Where Q is the quality factor, F is the main frequency of the seismic signal, and a is n 、a n-1 、a 1 、a 0 is the partial coefficient obtained by fitting, and n is the number of terms in the obtained polynomial.

[0088] In some implementations, energy compensation of seismic signals at corresponding locations is performed according to the quality factor value of each location point, including:

[0089] The low velocity reduction zone formation is equivalent to a layer of medium. During the compensation process, only space-varying Q compensation is performed, and the Q value is a constant in the time direction.

[0090] The seismic signal is converted from the time domain to the frequency domain through Fourier transform, and the constant inverse Q filtering is performed using the e-exponential algorithm to compensate the seismic signal.

[0091] The seismic signal is converted from the frequency domain back to the time domain by inverse Fourier transform.

[0092] Compared with the existing technology, its technical advantage is that it can compensate for the different degrees of absorption in each signal frequency band of the seismic signal at the loosely structured position in the near-surface low-velocity reduction zone strata in the target area, thereby enhancing the lateral consistency of the wavelet and reducing the impact on the seismic signal of the underlying strata.

[0093] In the prior art, seismic signal data sets include different data domains, such as the shot domain, the detection point domain, and the common mid-point domain (or CMP domain). If it is possible to first screen out which data domain the seismic signal that better matches the stratigraphic characteristics of the current target area belongs to, the resolution of seismic data and the lateral consistency of wavelets can be further improved.

[0094] Therefore, the present application provides another preferred embodiment, in which the data domain of the seismic signal is first determined before performing the compensation scan. The flowchart of the preferred embodiment is as follows: Figure 2 As shown, in Figure 1 Based on the process shown in FIG. 1 , the following pre-implementation steps are added to determine the data domain of the seismic signal and perform the seismic data analysis based on the determined seismic data signal. Figure 1 Calculation shown.

[0095] Step S1: Obtaining the plane distribution of the thickness of the low-velocity reduction zone in the target area, including the thickness distribution of the weathered zone strata near the surface and the thickness distribution of the under-compacted strata;

[0096] The purpose of this step is to obtain the plane distribution of the thickness of the low velocity reduction zone, where the low velocity reduction zone is each stratum near the surface, including the near-surface weathering zone stratum and the under-compacted stratum. Among them, the near-surface weathering zone is the low velocity zone, and the near-surface under-compacted stratum is the velocity reduction zone. The thickness of the low velocity reduction zone can be obtained through micro-well logging and the first arrival information of single-shot data collected in the field.

[0097] Step S2: extracting the main frequency of the seismic signal of each location point according to different data domains, so as to obtain the main frequency plane distribution corresponding to the data domain in the target area;

[0098] Step S3: Determine the degree of fit between the main frequency plane distribution of different data domains and the plane distribution of the thickness of the low velocity reduction zone, and use the data domain with the highest degree of fit as the data domain of the seismic signal.

[0099] The absorption effect of each near-surface stratum, i.e., the low velocity reduction zone, on the seismic signal is the main consideration. Different thickness distributions result in different absorption of seismic signals. Therefore, in step S1, the plane distribution of the thickness of the low velocity reduction zone is first obtained, and it is examined which data domain in the target area has the highest consistency between the corresponding main frequency plane distribution and the plane distribution of the thickness of the low velocity reduction zone. This data domain is the seismic signal data domain to be adopted.

[0100] However, according to the actual surface morphology in the target area and the spatial distribution of the low-speed reduction zone, for different data domains, the ones with higher consistency may have a closer consistency. At this time, it is necessary to consider the influence of the surface morphology and select the one with the best consistency for the surface morphology distribution from the ones with higher consistency. Specifically, it can be:

[0101] On the basis of step S3, if the difference in the degree of consistency between the main frequency plane distribution and the low velocity reduction zone thickness plane distribution in different data domains is less than a preset range among the former ones in the ranking, the surface morphology distribution in the target area is further obtained, and the degree of consistency between the main frequency plane distribution and the surface morphology distribution is determined from the former ones in the ranking, and the data domain to which the one with the highest degree of consistency belongs is used as the data domain of the seismic signal.

[0102] In this embodiment, the surface morphology distribution is obtained through satellite images, surface elevation information and other seismic survey information, including the distribution of surface types and surface elevations.

[0103] The surface satellite image of this embodiment is as follows Figure 3 As shown in the figure, it is a satellite image of the surface of the Rehetai-Oulituozi area. The area in the red frame is the target area of ​​this embodiment, which is also the full coverage of field seismic acquisition. The area in the green frame is the maximum range of field seismic acquisition, and the bright blue curve is the river. The elevation plane distribution diagram of this embodiment is shown in the figure. Figure 4 The following is the elevation distribution map of the Rehetai-Oulituozi area. The colors of different points in the distribution map represent the elevation information of the points. The corresponding relationship between different colors and elevations is shown in Figure 4 The annotation on the right. Figure 3 and Figure 4 , it can be seen Figure 3 The surface topography in Figure 4 The color distribution of the low speed reduction belt in this embodiment is shown in FIG. Figure 5 As shown, the plane distribution and spatial variation of the thickness of the low deceleration zone can be reflected.

[0104] The main frequency information distribution of the detection point domain in this embodiment is as follows: Figure 6 As shown, in practice, it is also necessary to obtain the main frequency information distribution diagram (not shown) corresponding to the gun domain, the common center point domain, and other possible data domains to compare different data domains.

[0105] In this embodiment, compared with the main frequency information distribution in the gun domain and the common center point domain, as shown in FIG. Figure 6 The distribution of the main frequency information in the detection point domain shown in Figure 5 The thickness distribution of the low velocity reduction zone shown is more consistent, therefore, in this embodiment, the seismic signal of the detection point domain is used to perform the energy compensation of the seismic signal of the present application, that is, the seismic signal selects the detection point gather data. If the main frequency information distribution of the shot domain is more consistent with the thickness distribution of the low velocity reduction zone, the seismic signal selects the shot point gather data; if the main frequency information distribution of the common center point domain is more consistent with the thickness distribution of the low velocity reduction zone, the seismic signal selects the common center point gather data.

[0106] It should be noted that, according to Figure 3 The surface satellite images shown select location points representing different surface morphology types, surface elevations, and / or low velocity reduction zone thicknesses as typical location points.

[0107] After executing the above-mentioned pre-steps S1-S3, you can Figure 1 Steps 1 to 3 of the embodiment shown in the figure complete the energy compensation of the seismic signal, which will not be described in detail here. Figure 7 shown.

[0108] The present application also provides an embodiment of an energy compensation device for seismic signals, the composition structure of which is as follows: Figure 8 As shown, including:

[0109] A compensation scanning module is used to perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0110] A fitting calculation module, used to fit the main frequency and quality factor value of each typical position point, and calculate the quality factor value of each position point according to the calculation formula obtained by fitting and the main frequency of other position points in the target area; and

[0111] The compensation calculation module is used to perform energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point through an inverse Q filtering algorithm.

[0112] The technical advantages of this embodiment are Figure 1 The embodiments shown are the same and will not be described again here.

[0113] Before performing the compensation scan, the data domain of the seismic signal is first determined, which is a more preferred embodiment. The composition structure of this embodiment is as follows: Fig. 9 As shown, based on the previous embodiment, it also includes: a data domain selection module, which is used to determine the data domain of the seismic signal according to the following steps before performing the compensation scan:

[0114] Obtain the planar distribution of the thickness of the low velocity reduction zone in the target area, including the thickness of the weathering zone of the near-surface strata (low velocity zone) and the thickness of the under-compacted strata (undiagenetic part, velocity reduction zone);

[0115] Extract the main frequency of the seismic signal at each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area; and

[0116] Determine the degree of agreement between the main frequency plane distribution of different data domains and the thickness plane distribution of the low velocity reduction zone, and take the data domain with the highest agreement as the data domain of the seismic signal.

[0117] If the difference in the degree of coincidence between the main frequency plane distribution and the low velocity reduction zone thickness plane distribution of different data domains is less than the preset range in the ranking of the former, the surface morphology distribution in the target area is further obtained, and the degree of coincidence between the main frequency plane distribution and the surface morphology distribution is determined from the former in the ranking, and the data domain to which the one with the highest degree of coincidence belongs is used as the data domain of the seismic signal.

[0118] Among them, the surface morphology distribution includes the distribution of surface type and surface elevation.

[0119] In some embodiments, if the data domain selection module determines that the data domain is a detection point domain, the seismic signal is a detection point gather; if the data domain selection module determines that the data domain is a shot domain, the seismic signal is a shot point gather; if the data domain selection module determines that the data domain is a common center point domain, the seismic signal is a common center point gather.

[0120] In some embodiments, the typical location points are location points representing different types of surface morphology, surface elevations, and / or thicknesses of low velocity reduction zones.

[0121] In some implementations, the compensation scanning module performs compensation scanning on the seismic signals of each typical location point in the target area, and analyzes the scanning results to determine the quality factor value of each typical location point, specifically including the following process:

[0122] Obtain seismic signals at each typical location;

[0123] Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values; and

[0124] When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

[0125] Specifically, the above-mentioned predetermined screening conditions are: the consistency of the spectrum distribution and the signal-to-noise ratio of the compensated seismic signal both reach a predetermined range. For example, the high-frequency and low-frequency energy distribution of the seismic signal is basically consistent, and the signal-to-noise ratio is greater than or equal to 2.

[0126] The compensation calculation module performs energy compensation for the different degrees of absorption in each signal frequency band of the seismic signal at the loosely structured position in the near-surface low-velocity reduction zone strata of the target area, so as to enhance the lateral consistency of the wavelet and reduce the impact on the seismic signal of the underlying strata.

[0127] The present application also provides an embodiment of an energy compensation device for seismic signals, which includes a processor and a memory. The compensation scanning module, fitting calculation module and compensation calculation module are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.

[0128] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the energy compensation of the seismic signal is performed by adjusting the kernel parameters.

[0129] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0130] An embodiment of the present invention provides a storage medium on which a program is stored. When the program is executed by a processor, the energy compensation method of the seismic signal of the present application is implemented.

[0131] An embodiment of the present invention provides a processor, which is used to run a program, wherein the energy compensation method for seismic signals of the present application is executed when the program is running.

[0132] An embodiment of the present invention provides a device, the device including a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, the following steps are implemented:

[0133] Step 1: Combine the micro-well logging in the target area and the first arrival information of the single shot data collected in the field to obtain the thickness map of the low velocity reduction zone in the target area, where the thickness map of the low velocity reduction zone can reflect the plane distribution and spatial variation characteristics of the thickness of the low velocity reduction zone;

[0134] Step 2: extract the main frequency of the seismic signal of each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area;

[0135] Step 3: Compare the main frequency plane distribution of different data domains with the plane distribution of the thickness of the low velocity reduction zone to determine the data domain that best matches the plane distribution of the thickness of the low velocity reduction zone, and use the matching data domain as the data domain applicable to the seismic signal.

[0136] Step 4: Perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0137] Step 5: Fit the main frequency and quality factor value of each typical location point, and calculate the quality factor value of each location point according to the calculation formula obtained by fitting and the main frequency of other location points in the target area;

[0138] Step 6: Through the inverse Q filtering algorithm, the energy of the seismic signal at the corresponding position is compensated according to the quality factor value of each position point.

[0139] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0140] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing the following method steps:

[0141] Step 1: Combine the micro-well logging in the target area and the first arrival information of single shot data collected in the field to obtain the thickness map of the low velocity reduction zone in the target area, where the thickness map of the low velocity reduction zone can reflect the plane distribution and spatial variation characteristics of the thickness of the low velocity reduction zone;

[0142] Step 2: extract the main frequency of the seismic signal of each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area;

[0143] Step 3: Compare the main frequency plane distribution of different data domains with the plane distribution of the thickness of the low velocity reduction zone to determine the data domain that best matches the plane distribution of the thickness of the low velocity reduction zone, and use the matching data domain as the data domain applicable to the seismic signal.

[0144] Step 4: Perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point;

[0145] Step 5: Fit the main frequency and quality factor value of each typical location point, and calculate the quality factor value of each location point according to the calculation formula obtained by fitting and the main frequency of other location points in the target area;

[0146] Step 6: Through the inverse Q filtering algorithm, the energy of the seismic signal at the corresponding position is compensated according to the quality factor value of each position point.

[0147] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0148] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0151] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0152] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0153] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0154] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0155] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for compensating seismic signal energy, comprising: Perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point; Fitting the main frequency of each typical position point with the quality factor value, and calculating the quality factor value of each position point according to the calculation formula obtained by fitting and the main frequency of other position points in the target area; and Through the inverse Q filtering algorithm, the energy compensation of the seismic signal at the corresponding position is performed according to the quality factor value of each position point.

2. The method according to claim 1, characterized in that Before performing the compensation scan, the data domain of the seismic signal is determined according to the following steps: Obtaining the plane distribution of the thickness of the low velocity reduction zone in the target area, including the thickness distribution of the weathered zone strata near the surface and the thickness distribution of the under-compacted strata; Extract the main frequency of the seismic signal at each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area; and The degree of agreement between the main frequency plane distribution of different data domains and the thickness plane distribution of the low velocity reduction zone is determined, and the data domain to which the highest degree of agreement belongs is used as the data domain of the seismic signal.

3. The method according to claim 2, characterized in that If the difference in the degree of coincidence between the main frequency plane distribution of different data domains and the plane distribution of the thickness of the low velocity reduction zone is less than a preset range in the ranking of the former, the surface morphology distribution in the target area is further obtained, and the degree of coincidence between the main frequency plane distribution and the surface morphology distribution is determined from the former in the ranking, and the data domain to which the one with the highest degree of coincidence belongs is used as the data domain of the seismic signal, The surface morphology distribution includes the distribution of surface types and surface elevations.

4. The method according to claim 2, characterized in that: If it is determined that the data domain is a detection point domain, then the seismic signal is a detection point gather; If it is determined that the data domain is a shot domain, then the seismic signal is a shot point gather; If it is determined that the data domain is a common center point domain, then the seismic signal is a common center point gather.

5. The method according to any one of claims 2 to 4, characterized in that: The typical location points are location points representing different types of surface morphology, surface elevations, and / or thicknesses of low velocity reduction zones.

6. The method according to claim 1, characterized in that The compensating scanning of the seismic signals of each typical location point in the target area and analyzing the scanning results to determine the quality factor value of each typical location point include: Obtain seismic signals at each typical location; Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values; and When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

7. The method according to claim 6, characterized in that The predetermined screening condition is that the spectrum distribution consistency and signal-to-noise ratio of the compensated seismic signal both reach a preset range.

8. The method according to claim 1, characterized in that: The fit is a polynomial fit.

9. The method according to claim 8, characterized in that The calculation formula is: Q = a n F n +a n-1 F n-1 ...+a1F+a0(n>=1), Where Q is the quality factor, F is the main frequency of the seismic signal, and a is n 、a n-1 , a1, a0 are the partial coefficients obtained by fitting, and n is the number of terms in the obtained polynomial.

10. The method according to claim 1, characterized in that The energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point includes: The low velocity reduction zone formation is equivalent to a layer of medium. During the compensation process, only space-varying Q compensation is performed, and the Q value is a constant in the time direction. The seismic signal is converted from the time domain to the frequency domain by Fourier transform, and the seismic signal is compensated by constant inverse Q filtering using an e-exponential algorithm; The seismic signal is converted from the frequency domain back to the time domain by inverse Fourier transformation.

11. An energy compensation device for seismic signals, comprising: A compensation scanning module is used to perform compensation scanning on the seismic signals of each typical location point in the target area, and analyze the scanning results to determine the quality factor value of each typical location point; A fitting calculation module, used to fit the main frequency of each typical position point with the quality factor value, and calculate the quality factor value of each position point according to the calculation formula obtained by fitting and the main frequency of other position points in the target area; and The compensation calculation module is used to perform energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point through an inverse Q filtering algorithm.

12. The device according to claim 11, characterized in that Also includes: The data domain selection module is used to determine the data domain of the seismic signal according to the following steps before performing the compensation scan: Obtaining the plane distribution of the thickness of the low velocity reduction zone in the target area, including the thickness distribution of the weathered zone strata near the surface and the thickness distribution of the under-compacted strata; Extract the main frequency of the seismic signal at each location point according to different data domains to obtain the main frequency plane distribution corresponding to the data domain in the target area; and Determine the degree of agreement between the main frequency plane distribution of different data domains and the thickness plane distribution of the low velocity reduction zone, and use the data domain to which the highest degree of agreement belongs as the data domain of the seismic signal. If the difference in the degree of coincidence between the main frequency plane distribution of different data domains and the plane distribution of the thickness of the low velocity reduction zone is less than a preset range in the ranking of the former, the surface morphology distribution in the target area is further obtained, and the degree of coincidence between the main frequency plane distribution and the surface morphology distribution is determined from the former in the ranking, and the data domain to which the one with the highest degree of coincidence belongs is used as the data domain of the seismic signal, The surface morphology distribution includes the distribution of surface types and surface elevations.

13. The device according to claim 12, characterized in that If the data domain selection module determines that the data domain is a detection point domain, the seismic signal is a detection point gather; If the data domain selection module determines that the data domain is a shot domain, the seismic signal is a shot point gather; If the data domain selection module determines that the data domain is a common center point domain, the seismic signal is a common center point gather.

14. The device according to any one of claims 11 to 13, characterized in that The typical location points are location points representing different types of surface morphology, surface elevations, and / or thicknesses of low velocity reduction zones.

15. The device according to claim 11, characterized in that The compensation scanning module performs compensation scanning on the seismic signals of each typical position point in the target area, and analyzes the scanning results to determine the quality factor value of each typical position point, including: Obtain seismic signals at each typical location; Acquire different compensation factor sampling values ​​within a predetermined threshold range, and perform compensation scanning in ascending order of the sampling values; and When the compensated seismic signal obtained by scanning meets the predetermined screening condition, the corresponding sampling value is determined as the compensation factor value, thereby determining the quality factor value of the position point.

16. The device according to claim 15, characterized in that The predetermined screening condition is that the spectrum distribution consistency and signal-to-noise ratio of the compensated seismic signal both reach a predetermined range.

17. The device according to claim 11, characterized in that The fitting is a polynomial fitting, and the calculation formula is: Q = a n F n +a n-1 F n-1 ...+a1F+a0(n>=1), Where Q is the quality factor, F is the main frequency of the seismic signal, and a is n 、a n-1 , a1, a0 are the partial coefficients obtained by fitting, and n is the number of terms in the obtained polynomial.

18. The device according to claim 11, characterized in that The compensation calculation module performs energy compensation of the seismic signal at the corresponding position according to the quality factor value of each position point, including: The low velocity reduction zone formation is equivalent to a layer of medium. During the compensation process, only space-varying Q compensation is performed, and the Q value is a constant in the time direction. The seismic signal is converted from the time domain to the frequency domain by Fourier transform, and the seismic signal is compensated by constant inverse Q filtering using an e-exponential algorithm; The seismic signal is converted from the frequency domain back to the time domain by inverse Fourier transformation.

19. A machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute: the energy compensation method for seismic signals as described in any one of claims 1 to 10.

20. A processor, characterized in that: Used to run a program, wherein the program, when run, is used to execute: the energy compensation method for seismic signals as described in any one of claims 1-10.

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