CN112415601A - Method and device for determining surface quality factor Q value - Google Patents
Method and device for determining surface quality factor Q value Download PDFInfo
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Abstract
The invention provides a method and a device for determining a Q value of a surface quality factor, wherein the method comprises the following steps: establishing a surface horizontal layered geological model according to the micro-logging data of the target area; correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model; on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method; according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record; filtering by using a frequency wave number domain to remove interference waves to obtain a filtered micro-logging record; and determining the surface quality factor Q value of the target area according to the filtered micro-logging records. The method eliminates the interference waves by eliminating the seismic channels of the primary wave non-direct arrival waves and utilizing frequency wave number domain filtering, reduces the influence of the interference waves on the Q value calculation precision, and accordingly improves the precision of the Q value of the surface quality factor.
Description
Technical Field
The invention relates to the technical field of petroleum seismic exploration data processing, in particular to a method and a device for determining a surface quality factor Q value.
Background
When the seismic wave propagates in the stratum, the energy of the seismic wave is absorbed by the medium, so that the attenuation and dispersion of the seismic wave are generated. The quality factor Q is a basic parameter for describing the stratum absorption attenuation characteristic and has important significance for improving the seismic data resolution. The quality factor Q may be calculated from laboratory, surface seismic, VSP, interwell seismic data, and micro-log data. The calculation method of the quality factor Q can be divided into two main methods of direct estimation and inversion. The direct estimation method can be divided into three categories of time domain, frequency domain and time-frequency domain according to different calculation domains. The method for calculating the quality factor Q in the time domain mainly includes an amplitude attenuation method, a rise time method, an analytic signal method, a wavelet simulation method, a phase simulation method, an instantaneous frequency simulation method, and the like. The method for calculating the quality factor Q in the frequency domain mainly comprises a frequency spectrum simulation method, a spectrum ratio method, a centroid frequency shift method, a peak frequency method and the like. The theory of wavelet transform, Gabor transform and the like is widely introduced into the exploration field, and the time-frequency domain calculation method can avoid the average effect in the frequency domain method and more accurately describe the absorption attenuation characteristics of the stratum. The Q value calculation method of the inversion class mainly comprises Q tomography and Q waveform inversion.
However, the accuracy of the Q value calculation by the method depends on the quality of the calculation record. The middle and deep Q value calculation data usually adopts zero offset VSP downlink data. The zero offset VSP downlink wave data is less interfered by the environment, and the detector records waveforms at different depths and different times, so that the zero offset VSP downlink wave data is ideal data for calculating the quality factor Q. A large number of practices prove that the influence of the surface Q value on the seismic data resolution is far larger than that of the deep Q value. Therefore, the calculation accuracy of the surface Q is particularly important for improving the resolution of seismic data.
The surface quality factor Q calculation depends on the variable quantity of frequency components in the process of seismic wave propagation, is influenced by a plurality of factors, and is sensitive to the interference of noise and complex clutter fields. Factors influencing the calculation of the surface quality factor Q value include: (ii) exciting wavelet differences. In the micro-logging, due to the difference of factors such as surrounding rock excitation, compaction degree and the like, seismic source wavelets generated by excitation at different depth positions are different; second, the difference of coupling of the wave detection points. Coupling degree difference between the detector and the stratum in the embedding process causes different coupling responses of the detection points; ③ near field effects. The near-field component can generate apparent attenuation with the same dimension as the inherent attenuation, and the Q value calculation is seriously influenced; influence of interference waves; interference waves such as surface waves, shallow refracted waves and ghost reflections interfere with direct waves (transmitted waves) and affect the calculation accuracy of the Q value. Therefore, the accuracy of determining the Q value of the surface quality factor in the prior art is not high.
Disclosure of Invention
The embodiment of the invention provides a method for determining a surface quality factor Q value, which is used for improving the precision of the surface quality factor Q value and comprises the following steps:
acquiring micro-logging data of a target area; the micro-logging data comprises micro-logging collection records;
establishing a surface horizontal layered geological model according to the micro-logging data of the target area;
correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model;
on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method;
according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record;
filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records;
and determining the surface quality factor Q value of the target area according to the filtered micro-logging records.
The embodiment of the present invention further provides a device for determining a Q value of a surface quality factor, so as to improve the precision of the Q value of the surface quality factor, the device including:
the data acquisition module is used for acquiring micro-logging data of a target area; the micro-logging data comprises micro-logging collection records;
the geological model building module is used for building a surface layer horizontal layered geological model according to the micro-logging data of the target area;
the geological model correction module is used for correcting the low-speed stratum speed of the surface layer horizontal layered geological model to obtain a corrected surface layer horizontal layered geological model;
the direct wave identification module is used for forward playing the direct wave record by using a ray tracing method on the corrected surface layer horizontal layered geological model, identifying the position of the direct wave on the micro-logging acquisition record according to the forward playing direct wave record, and eliminating the seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record;
the interference wave suppression module is used for removing the interference waves in the micro-logging acquisition records behind the seismic trace of the first-arrival wave non-direct arrival wave by utilizing frequency wave number domain filtering to obtain filtered micro-logging records;
and the Q value calculating module is used for determining the surface quality factor Q value of the target area according to the filtered micro-logging records.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for determining the Q value of the surface quality factor when executing the computer program.
An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program for executing the method for determining the Q value of the surface quality factor.
In the embodiment of the invention, micro-logging data of a target area are acquired; the micro-logging data comprises micro-logging collection records; establishing a surface horizontal layered geological model according to the micro-logging data of the target area; correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model; on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method; according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record; filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records; and determining the surface quality factor Q value of the target area according to the filtered micro-logging records. The influence of excitation wavelet difference, demodulator probe coupling difference and near field influence on Q value precision in the calculation process is reduced by correcting the surface layer horizontal layered geological model. The method eliminates the interference waves by eliminating the seismic channels of the primary wave non-direct arrival waves and utilizing frequency wave number domain filtering, reduces the influence of the interference waves on the Q value calculation precision, and accordingly improves the precision of the Q value of the surface quality factor.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram illustrating a method for determining a Q value of a surface quality factor according to an embodiment of the invention.
Fig. 2 is a schematic diagram of a specific implementation method of step 103 in an embodiment of the present invention.
Fig. 3 is a schematic diagram of a specific implementation method of step 202 in an embodiment of the present invention.
Fig. 4 is a schematic diagram of a specific implementation method of step 105 in an embodiment of the present invention.
Fig. 5 is a schematic diagram of a specific implementation method of step 106 in an embodiment of the present invention.
Fig. 6 is a schematic diagram of a specific implementation method of step 107 in an embodiment of the present invention.
FIG. 7 is a schematic illustration of a surface-level layered geological model created and modified in accordance with an embodiment of the present invention.
FIG. 8 is a schematic diagram illustrating a process of identifying a direct wave in a micro log according to an embodiment of the present invention.
FIG. 9 is a diagram illustrating suppression of interference waves using frequency wavenumber domain according to an embodiment of the present invention.
FIG. 10 is a schematic diagram illustrating the filtering result in the domain of the frequency wave number of the micro-log according to an embodiment of the present invention.
FIG. 11 is a graphical representation of results of a comparison between a frequency wavenumber domain filtering utilized for acquiring micro logs excited at different depths in an embodiment of the present invention.
FIG. 12 is a schematic diagram of a micro log used for Q value calculation in accordance with an embodiment of the present invention.
FIG. 13 is a diagram illustrating the results of calculating the quality factor Q of the micro log before and after filtering in the frequency-wavenumber domain according to an embodiment of the present invention.
Fig. 14 is a schematic diagram of an apparatus for determining a Q value of a surface quality factor according to an embodiment of the present invention.
Fig. 15 is a schematic structural diagram of the geological model modification module 1403 in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides a method for determining a Q value of a surface quality factor, so as to improve the accuracy of the Q value of the surface quality factor, as shown in fig. 1, the method includes:
step 101: acquiring micro-logging data of a target area; wherein the micro-logging data comprises micro-logging collection records;
step 102: establishing a surface horizontal layered geological model according to the micro-logging data of the target area;
step 103: correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model;
step 104: on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method;
step 105: according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record;
step 106: filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records;
step 107: and determining the surface quality factor Q value of the target area according to the filtered micro-logging records.
As can be known from the process shown in fig. 1, in the embodiment of the present invention, micro-logging data of a target area is obtained; the micro-logging data comprises micro-logging collection records; establishing a surface horizontal layered geological model according to the micro-logging data of the target area; correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model; on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method; according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record; filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records; and determining the surface quality factor Q value of the target area according to the filtered micro-logging records. The influence of excitation wavelet difference, demodulator probe coupling difference and near field influence on Q value precision in the calculation process is reduced by correcting the surface layer horizontal layered geological model. The method eliminates the interference waves by eliminating the seismic channels of the primary wave non-direct arrival waves and utilizing frequency wave number domain filtering, reduces the influence of the interference waves on the Q value calculation precision, and accordingly improves the precision of the Q value of the surface quality factor.
In specific implementation, micro-logging data of a target area is obtained first. Wherein the micro-logging data comprises micro-logging collection records. In a specific embodiment, obtaining micro-log data of a target area includes: and acquiring micro-logging observation parameters, micro-logging acquisition records and micro-logging interpretation results of the target area. Wherein, the micro-logging observation parameters comprise: the depth of an underground excitation point and the distance between a ground detection point and a wellhead; the micro-logging interpretation results comprise: horizon speed and thickness are interpreted.
And after acquiring the micro-logging data of the target area, establishing a surface horizontal layered geological model according to the micro-logging data of the target area. In specific implementation, a surface horizontal layered geological model is established mainly according to the micro-logging interpretation result.
And correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain the corrected surface horizontal layered geological model. The specific implementation process, as shown in fig. 2, includes:
step 201: establishing a forward method of underground excitation and ground reception according to the micro-logging observation parameters, and forward recording of a direct wave, a refracted wave, a reflected wave and a multiple wave by adopting a ray tracing method;
step 202: and picking up the forward mixed wave record first arrival wave peak time, correcting the low-speed stratum velocity of the horizontal layered surface geological model according to the forward mixed wave record first arrival wave peak time, and obtaining the corrected horizontal layered surface geological model.
In step 202, as shown in fig. 3, the specific implementation process includes:
step 301: performing ray tracing forward at different corrected stratum speeds, and counting the simulated forward data first arrival time of all excitation points in the low-speed layer and the deceleration layer;
step 302: determining the sum of the difference between the forward evolution record first-arrival time and the actual record first-arrival time corresponding to each corrected stratum speed according to the forward evolution mixed wave record first-arrival wave peak time and the simulated forward evolution data first-arrival time;
step 303: and determining the corrected stratum speed corresponding to the minimum value in the sum of the forward record first arrival time and the actual record first arrival time as the stratum speed of the first stratum in the surface horizontal layered geological model, and correcting the low-speed layer stratum speed of the surface horizontal layered geological model to obtain the corrected surface horizontal layered geological model.
The low-speed layer (low velocity zone) is a deep geophysical layer with the propagation velocity of seismic P waves and S waves lower than that of an overlying layer and an underlying layer, and the surface medium near the surface is divided into a low-speed layer (the velocity is less than 1000m/S), a deceleration layer (the velocity is between 1000m/S and 2000 m/S) and a high-speed layer (the velocity is higher than 2000 m/S), namely a rock stratum, according to the velocity.
Specifically, because the speed of the surface layer low-speed layer has an artificial interpretation error, the surface layer horizontal layered geological model low-speed layer needs to be corrected, and the steps are as follows:
calculating a first layer L in the micro-logging interpretation result according to the formula (1)1The intersection position x of the fitted line of (2) and the time axis0. If x0Not equal to 0, adding a layer L on the surface layer horizontal lamellar geological model0，L0Horizon thickness H0Velocity V0And L1The layer thickness is calculated according to equation (2).
In the formula, D1Representing a first excitation point depth; t is1A vertical propagation time representing the depth of the first excitation point; v1Representing the first layer velocity in the microlog interpretation.
In the formula, X1Indicating the distance of the first receiving point from the wellhead; FB (full Fall Back)1,1Indicating first shot point first pass reception in actual recordingThe first arrival time of (c).
Given L1Formation velocity correction Range [ V ]1-ΔV V1+ΔV]Correcting the surface horizontal lamellar geological model L in 1m/s increment1Formation velocity V'kK is 1,2,3, …, NV, NV is L1The formation velocity corrected velocity total.
At different corrected speeds V'kAnd (4) performing ray tracing forward, counting forward data first arrival moments of all excitation points in the low-speed layer and the deceleration layer, and calculating the sum of the difference values of forward record first arrival moments and actual record first arrival moments according to a formula (3).
In the formula (I), the compound is shown in the specification,
the sum of the difference between the forward playing recorded first-arrival time and the actual recorded first-arrival time under the condition of the kth correction speed is represented;
indicates the corrected speed V 'of the ith excitation point and the jth receiving point'kForward playing the recorded first arrival moment under the condition; FB (full Fall Back)i,jRepresenting the actual recording first arrival time of the ith excitation point and the jth receiving point; n is the total number of excitation points in the low and speed reduction layer; m is the total number of ground receiving channels.
Will be provided with
Determining the correction speed corresponding to the minimum value as a surface geological model L1And (5) obtaining the corrected surface horizontal lamellar geological model by the stratum speed.
And on the corrected surface horizontal layered geological model, forward performing direct wave recording by using a ray tracing method, and picking up the peak time of the direct wave. According to the forward direct wave record, the direct wave position on the micro-logging acquisition record is identified, and the seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record are removed. In specific implementation, as shown in fig. 4, the method includes:
step 401: picking up the forward direct wave and recording the peak time of the direct wave;
step 402: recording the peak time of the direct wave according to the forward direct wave, and calculating the difference value between the first arrival time of different receiving channels excited by different depths in the micro-logging acquisition record and the forward direct wave time corresponding to the first arrival time;
step 403: and if the difference is less than one fourth of the period of the first-motion wave of the receiving channel, determining that the first-motion wave of the receiving channel is a direct wave.
In the specific embodiment, the first arrival time FB of different receiving channels excited by different depths and actually recorded is calculated according to the formula (4)i,jForward direct arrival time corresponding thereto
Difference value Δ FB ofi,j：
Wherein, i is 1,2,3, …, N represents excitation points with different depths, and N represents the total excitation point number; j is 1,2,3, …, M indicates different receiving channels, and M indicates the total number of receiving channels on the ground.
If the difference value is Delta FBi,jIf the period is less than one fourth of the period of the first-motion wave recorded in the channel, the first-motion wave recorded in the channel is a direct wave; on the contrary, the first-motion wave recorded in the track is not a direct wave.
And after the seismic channels of the primary wave non-direct arrival waves on the micro-logging acquisition records are removed, filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic channels of the primary wave non-direct arrival waves, and obtaining the filtered micro-logging records. The specific process, as shown in fig. 5, includes:
step 501: splicing the residual seismic channels in the micro-logging acquisition records after the seismic channels with the primary wave indirect arrival waves are removed into a data body, correcting the primary wave take-off time of all the seismic channels in the data body to the same time, and obtaining the micro-logging acquisition records after the primary wave is leveled;
step 502: calculating energy balance factors of all sample values in the micro-logging acquisition records after the first arrival wave is leveled, and applying the energy balance factors of all sample values to the micro-logging acquisition records after the first arrival wave is leveled to obtain micro-logging records after the energy balance;
step 503: and carrying out frequency wave number domain filtering operation on the micro-logging records after energy balance, and eliminating interference waves to obtain the filtered micro-logging records.
In the specific embodiment, seismic channels of primary wave indirect waves in the micro-logging record are removed, the rest seismic channels are spliced into a data body according to a formula (5), and the primary wave take-off time of all the seismic channels is corrected to the same time;
A(i-1)*M+j＝Si,j (5)
in the formula, Si,jRepresenting the micro-logging traces of the ith excitation point and the jth receiving point; a. the(i-1)*M+jRepresenting the spliced data volume; m is the total number of ground receiving channels.
And calculating and applying energy balance factors of all recorded sample values after the first-motion wave is leveled.
Calculating an energy balance factor recorded in a given time window on a single-channel record by adopting a formula (6), placing the energy balance factor at the midpoint of the time window, and then sliding the length of half of the time window to obtain the energy balance factor of the next time window;
in the formula, WiAn equalization coefficient representing an ith time window; AmpLevel represents the desired amplitude level; n represents the number of sample points in the calculation time window; xkRepresenting the sample value at time k.
Linearly interpolating energy balance factors of all sampling points on the single-channel record by adopting a formula (7);
Wk＝W2+(W2-W1)(T2-Tk)/(T2-T1)k＝1,2,...NS (7)
in the formula, WkRepresenting the balance coefficient corresponding to the kth sampling point; t iskRepresenting a time value corresponding to the kth sampling point; t is1And T2Representing the corresponding time values of the two time window central points closest to the kth sampling point; w1And W2Representing energy balance factors corresponding to central points of two time windows nearest to the kth sampling point; NS represents the number of single-pass recorded samples.
And thirdly, applying the energy balance factors of all the sampling points to the micro logging record according to the formula (8).
A′i＝Ai*Wi i＝1,2,3,…,NX (8)
Of formula (II) to'iRecording the micro-logging single-channel after energy equalization; a. theiThe method comprises the following steps of (1) carrying out single-channel recording on micro logging before energy balance; NX is the total number of data volume after splicing.
The method for suppressing the indirect arrival wave in the first arrival wave by adopting an amplitude-preserving frequency wave number domain filtering method comprises the following specific steps:
firstly, intercepting a first arrival wave in a micro-logging record as a calculation time window, and generating a frequency wave number spectrum by adopting two-dimensional Fourier transform;
artificially extracting energy values of energy cluster edges near zero wave number on the frequency wave number spectrum, and designing a filter for suppressing interference waves on the frequency wave number spectrum according to the energy values;
and thirdly, performing two-dimensional inverse Fourier transform to obtain micro-logging record first-motion waves after eliminating interference waves such as non-direct waves and the like.
The energy balance factor is removed.
And obtaining the micro logging record after the interference wave is finally removed by adopting a formula (9).
S″k,j＝FK(A′i)/Wi i＝1,2,3,…,NX (9)
In the formula, FK represents a frequency wavenumber domain filtering operation; s ″)k,jAnd (3) representing the micro-logging single-channel record of the jth receiving point of the kth excitation point after the energy balance factor is removed, wherein k is floor (i/M), j is i-k.M, floor represents an upward rounding operation, and M represents the total number of the receiving channels on the ground.
And after the filtered micro logging records are obtained, determining the surface quality factor Q value of the target area according to the filtered micro logging records. In specific implementation, as shown in fig. 6, the method includes:
step 601: picking up a complete period time of the first arrival wave on the micro logging records after filtering, reserving sample point amplitude values in the complete period of the first arrival wave, and enabling the residual sample point amplitude values to be zero to obtain micro logging data for calculating a Q value;
step 602: and determining the surface quality factor Q value of the target area according to the micro-logging data for calculating the Q value.
Those skilled in the art can understand that the calculation of the surface quality factor Q value of the target region by using the micro-logging data belongs to the mature technology in the field, and therefore, the detailed description in the embodiment of the present invention is omitted.
The method adopts forward record first arrival time mapping to identify direct waves in micro-logging acquisition records, eliminates seismic channels of first arrival non-direct waves on the micro-logging acquisition records, adopts an amplitude-preserving frequency wave number domain filtering method to suppress and record interference waves such as shallow refraction waves, virtual reflection and the like interfered in the first arrival waves (direct waves), improves the precision of a quality factor Q calculated according to the micro-logging records, and provides a high-precision surface layer Q model for inverse Q filtering processing.
A specific example is given below to illustrate how embodiments of the present invention may be implemented. The quality factor Q is calculated by using the method in one micro-logging acquisition record in the west desert area of China.
FIG. 7 is a surface level stratigraphic geological model for creating and correcting the microlog locations based on the microlog interpretation. Part (a) of fig. 7 is a micro-log interpretation chart, and part (c) of fig. 7 is a surface level layered geological model created based on the micro-log interpretation result. As can be seen from part (a) of fig. 7, the intersection of the first layer fit line with the time axis in the interpretation result is 1.34ms, which is not zero. Correcting the surface horizontal lamellar geological model: adding horizon L at shallowest level0The speed is 230m/s, and the thickness is 0.52 m; l is1The horizon thickness correction is 2.78m and the velocity correction is 490m/s (as shown in part (d) of FIG. 7). The first arrival time of the corrected forward modeling record and the first arrival time of the actual data are maximumThe error is reduced from 8.25ms to 1.5ms (as shown in part (b) of fig. 7).
On the corrected surface horizontal layered geological model, a forward direct wave record is tracked by rays, and the first arrival time of the forward record is picked up and mapped to a micro-logging record (as shown in figure 8). And judging whether the first-motion wave in the micro-logging record is a direct wave or not, and rejecting the non-direct wave channel of the first-motion wave in the micro-logging record. And suppressing the indirect arrival wave in the first arrival wave by adopting an amplitude-preserving frequency wave number domain filtering method.
Fig. 9 is a schematic diagram of suppressing an interference wave using a frequency-wavenumber-domain method. The left graph of fig. 9 records the frequency-wavenumber spectrum after leveling for the forward direct wave. When the direct wave is horizontally in-phase, the direct wave appears as a bolus of energy concentrated near a null on the frequency wavenumber domain spectrum. The right diagram of fig. 9 shows the frequency wave number spectrum after the leveling of the first-arrival waves, and the filter is designed in the frequency wave number domain to eliminate the energy values outside the oval frame in the right diagram, so as to suppress the non-direct arrival waves in the first-arrival waves. The effect of the suppression of the indirect wave is shown in fig. 10. If the frequency wave number domain filtering method is adopted, amplitude preserving processing is not carried out, the amplitude of the seismic channel is greatly increased after filtering, the energy of an amplitude spectrum is also greatly increased, the absorption attenuation rule of the seismic channel before filtering is changed, and the method cannot be used for calculating the subsequent Q value. After the amplitude-preserving frequency wave number domain filtering is adopted, only interfered indirect waves are suppressed, the original absorption attenuation rule of the seismic channel is not changed, and the method can be used for calculating the subsequent Q value. FIG. 11 is a comparison of frequency-wavenumber domain filtering before and after acquisition of micro logs with different depth excitations. After frequency wave number domain suppression, the indirect waves interfered in the first-motion waves of the micro logging records are suppressed (shown in a rectangular frame in the figure).
Suppressing the non-direct wave in the first-motion wave, picking up a complete cycle time of the first-motion wave on the record, reserving an amplitude value in the complete cycle of the first-motion wave, and assigning zero values to the rest amplitude values for calculating the quality factor Q (as shown in fig. 12). FIG. 13 is the results of the micro log calculation quality factor Q before and after frequency wavenumber domain filtering. And selecting seismic channels excited at the well depth of 8 meters and excited at the well depth of 42 meters and received at a distance of 7 meters from the well mouth to calculate the quality factor Q. The Q value calculated by the frequency wave number domain pre-filtering seismic channel is-13.7. The quality factor Q is a parameter describing the absorption and attenuation characteristics of the seismic waves, and the value should be greater than zero, so the calculation result is wrong. The Q value calculated by the seismic channel after the frequency wave number domain filtering is 36.5, the Q value is larger than zero, accords with the absorption and attenuation rule of the seismic wave, and is close to the Q value calculated by an empirical formula.
The implementation of the above specific application is only an example, and the rest of the embodiments are not described in detail.
Based on the same inventive concept, embodiments of the present invention further provide a device for determining a Q value of a surface quality factor, where the principle of the problem solved by the device for determining a Q value of a surface quality factor is similar to that of the method for determining a Q value of a surface quality factor, so that the implementation of the device for determining a Q value of a surface quality factor can refer to the implementation of the method for determining a Q value of a surface quality factor, and repeated parts are not repeated, and the specific structure is as shown in fig. 14:
a data obtaining module 1401, configured to obtain micro-logging data of a target area; the micro-logging data comprises micro-logging collection records;
a geological model building module 1402, configured to build a surface horizontal stratiform geological model according to the micro-logging data of the target area;
a geological model correction module 1403, configured to correct the low-speed layer formation speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model;
a direct wave identification module 1404, configured to forward a direct wave record by using a ray tracing method on the modified surface-layer horizontal layered geological model, identify a direct wave position on the micro-logging acquisition record according to the forward direct wave record, and reject a seismic trace of a first arrival wave non-direct wave on the micro-logging acquisition record;
the interference wave suppression module 1405 is used for eliminating the interference waves in the micro-logging acquisition records after the seismic channels of the first-arrival wave non-direct arrival waves by utilizing frequency wave number domain filtering to obtain filtered micro-logging records;
and a Q value calculating module 1406, configured to determine a Q value of a surface quality factor of the target area according to the filtered micro-log.
In a specific embodiment, the data obtaining module 1401 is specifically configured to:
acquiring micro-logging observation parameters, micro-logging acquisition records and micro-logging interpretation results of a target area;
wherein, the micro-logging observation parameters comprise: the depth of an underground excitation point and the distance between a ground detection point and a wellhead;
the micro-logging interpretation results comprise: horizon speed and thickness are interpreted.
In a specific embodiment, the structure of the geological model modification module 1403, as shown in fig. 15, includes:
the forward full wave field recording unit 1501 is used for establishing a forward method of underground excitation and ground reception according to the micro-logging observation parameters, and performing forward record of mixed waves of direct waves, refracted waves, reflected waves and multiple waves by adopting a ray tracing method;
the geological model correcting unit 1502 is configured to pick up the forward mixing record first arrival peak time, correct the low-speed stratum velocity of the horizontal layered geological model of the surface layer according to the forward mixing record first arrival peak time, and obtain the corrected horizontal layered geological model of the surface layer.
In specific implementation, the geological model modification unit 1502 is specifically configured to:
performing ray tracing forward at different corrected stratum speeds, and counting the simulated forward data first arrival time of all excitation points in the low-speed layer and the deceleration layer;
determining the sum of the difference between the forward evolution record first-arrival time and the actual record first-arrival time corresponding to each corrected stratum speed according to the forward evolution mixed wave record first-arrival wave peak time and the simulated forward evolution data first-arrival time;
and determining the corrected stratum speed corresponding to the minimum value in the sum of the forward record first arrival time and the actual record first arrival time as the stratum speed of the first stratum in the surface horizontal layered geological model, and correcting the low-speed layer stratum speed of the surface horizontal layered geological model to obtain the corrected surface horizontal layered geological model.
In a specific embodiment, the direct wave identification module 1404 is specifically configured to:
picking up the forward direct wave and recording the peak time of the direct wave;
recording the peak time of the direct wave according to the forward direct wave, and calculating the difference value between the first arrival time of different receiving channels excited by different depths in the micro-logging acquisition record and the forward direct wave time corresponding to the first arrival time;
and if the difference is less than one fourth of the period of the first-motion wave of the receiving channel, determining that the first-motion wave of the receiving channel is a direct wave.
In a specific embodiment, the interference wave suppression module 1405 is specifically configured to:
splicing the residual seismic channels in the micro-logging acquisition records after the seismic channels with the primary wave indirect arrival waves are removed into a data body, correcting the primary wave take-off time of all the seismic channels in the data body to the same time, and obtaining the micro-logging acquisition records after the primary wave is leveled;
calculating energy balance factors of all sample values in the micro-logging acquisition records after the first arrival wave is leveled, and applying the energy balance factors of all sample values to the micro-logging acquisition records after the first arrival wave is leveled to obtain micro-logging records after the energy balance;
and carrying out frequency wave number domain filtering operation on the micro-logging records after energy balance, and eliminating interference waves to obtain the filtered micro-logging records.
In a specific embodiment, the Q value calculating module 1406 is specifically configured to:
picking up a complete period time of the first arrival wave on the micro logging records after filtering, reserving sample point amplitude values in the complete period of the first arrival wave, and enabling the residual sample point amplitude values to be zero to obtain micro logging data for calculating a Q value;
and determining the surface quality factor Q value of the target area according to the micro-logging data for calculating the Q value.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for determining the Q value of the surface quality factor when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program for executing the method for determining the Q value of the surface quality factor.
In summary, the method and the apparatus for determining the Q value of the surface quality factor provided by the embodiments of the present invention have the following advantages:
acquiring micro-logging data of a target area; the micro-logging data comprises micro-logging collection records; establishing a surface horizontal layered geological model according to the micro-logging data of the target area; correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model; on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method; according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record; filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records; and determining the surface quality factor Q value of the target area according to the filtered micro-logging records. The influence of excitation wavelet difference, demodulator probe coupling difference and near field influence on Q value precision in the calculation process is reduced by correcting the surface layer horizontal layered geological model. The method eliminates the interference waves by eliminating the seismic channels of the primary wave non-direct arrival waves and utilizing frequency wave number domain filtering, reduces the influence of the interference waves on the Q value calculation precision, and accordingly improves the precision of the Q value of the surface quality factor.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (16)
1. A method for determining a Q value of a surface Quality Factor (QF), comprising:
acquiring micro-logging data of a target area; the micro-logging data comprises micro-logging collection records;
establishing a surface horizontal layered geological model according to the micro-logging data of the target area;
correcting the low-speed stratum speed of the surface horizontal layered geological model to obtain a corrected surface horizontal layered geological model;
on the corrected surface layer horizontal layered geological model, forward-acting direct wave recording by using a ray tracing method;
according to the forward direct wave record, identifying the direct wave position on the micro-logging acquisition record, and removing seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record;
filtering by using a frequency wave number domain to remove interference waves in the micro-logging acquisition records behind the seismic trace of the first-motion wave non-direct arrival wave, and obtaining filtered micro-logging records;
and determining the surface quality factor Q value of the target area according to the filtered micro-logging records.
2. The method of claim 1, wherein acquiring micro-log data of a target area comprises:
acquiring micro-logging observation parameters, micro-logging acquisition records and micro-logging interpretation results of a target area;
wherein the micro-logging observation parameters comprise: the depth of an underground excitation point and the distance between a ground detection point and a wellhead;
the micro-logging interpretation result comprises: horizon speed and thickness are interpreted.
3. The method of claim 2, wherein modifying the low velocity layer formation velocity of the surface-level layered geological model to obtain a modified surface-level layered geological model comprises:
establishing a forward method of underground excitation and ground reception according to the micro-logging observation parameters, and forward recording of a direct wave, a refracted wave, a reflected wave and a multiple wave by adopting a ray tracing method;
and picking up the forward mixed wave record first arrival wave peak time, correcting the low-speed stratum velocity of the horizontal layered surface geological model according to the forward mixed wave record first arrival wave peak time, and obtaining the corrected horizontal layered surface geological model.
4. The method of claim 3, wherein the step of correcting the low-velocity layer formation velocity of the surface-level layered geological model according to the first-arrival peak time of the forward-acting mixed wave record to obtain a corrected surface-level layered geological model comprises:
performing ray tracing forward at different corrected stratum speeds, and counting the simulated forward data first arrival time of all excitation points in the low-speed layer and the deceleration layer;
determining the sum of the difference value between the forward evolution record first-arrival time and the actual record first-arrival time corresponding to each corrected stratum speed according to the forward evolution mixed wave record first-arrival wave peak time and the simulated forward evolution data first-arrival time;
and determining the corrected stratum speed corresponding to the minimum value in the sum of the forward record first arrival time and the actual record first arrival time as the stratum speed of the first stratum in the surface horizontal layered geological model, and correcting the low-speed layer stratum speed of the surface horizontal layered geological model to obtain the corrected surface horizontal layered geological model.
5. The method of claim 1, wherein identifying the location of the direct wave on the micro-log acquisition record from the forward direct wave record comprises:
picking up the forward direct wave and recording the peak time of the direct wave;
recording the peak time of the direct wave according to the forward direct wave, and calculating the difference value between the first arrival time of different receiving channels excited by different depths in the micro-logging acquisition record and the forward direct wave time corresponding to the first arrival time;
and if the difference is less than one fourth of the period of the first-motion wave of the receiving channel, determining that the first-motion wave of the receiving channel is a direct wave.
6. The method of claim 1, wherein the obtaining of the filtered micro log record by filtering in the frequency wave number domain to remove interference waves in the micro log acquisition record after the seismic trace of the first arrival wave non-direct arrival wave comprises:
splicing the residual seismic channels in the micro-logging acquisition records after the seismic channels with the primary wave indirect arrival waves are removed into a data body, correcting the primary wave take-off time of all the seismic channels in the data body to the same time, and obtaining the micro-logging acquisition records after the primary wave leveling;
calculating energy balance factors of all sample values in the micro-logging acquisition records after the first arrival wave is leveled, and applying the energy balance factors of all sample values to the micro-logging acquisition records after the first arrival wave is leveled to obtain micro-logging records after the energy balance;
and carrying out frequency wave number domain filtering operation on the micro-logging records after energy balance, and eliminating interference waves to obtain the filtered micro-logging records.
7. The method of claim 1, wherein determining a surface quality factor Q value for the target region from the filtered microbolograms comprises:
picking up a complete period time of the first arrival wave on the micro logging records after filtering, reserving sample point amplitude values in the complete period of the first arrival wave, and enabling the residual sample point amplitude values to be zero to obtain micro logging data for calculating a Q value;
and determining the surface quality factor Q value of the target area according to the micro-logging data for calculating the Q value.
8. An apparatus for determining a Q value of a surface quality factor, comprising:
the data acquisition module is used for acquiring micro-logging data of a target area; the micro-logging data comprises micro-logging collection records;
the geological model building module is used for building a surface layer horizontal layered geological model according to the micro-logging data of the target area;
the geological model correction module is used for correcting the low-speed stratum speed of the surface layer horizontal layered geological model to obtain a corrected surface layer horizontal layered geological model;
the direct wave identification module is used for forward playing the direct wave record by using a ray tracing method on the corrected surface layer horizontal layered geological model, identifying the position of the direct wave on the micro-logging acquisition record according to the forward playing direct wave record, and eliminating the seismic channels of the first arrival wave non-direct waves on the micro-logging acquisition record;
the interference wave suppression module is used for removing the interference waves in the micro-logging acquisition records behind the seismic trace of the first-arrival wave non-direct arrival wave by utilizing frequency wave number domain filtering to obtain filtered micro-logging records;
and the Q value calculating module is used for determining the surface quality factor Q value of the target area according to the filtered micro-logging records.
9. The apparatus of claim 8, wherein the data acquisition module is specifically configured to:
acquiring micro-logging observation parameters, micro-logging acquisition records and micro-logging interpretation results of a target area;
wherein the micro-logging observation parameters comprise: the depth of an underground excitation point and the distance between a ground detection point and a wellhead;
the micro-logging interpretation result comprises: horizon speed and thickness are interpreted.
10. The apparatus of claim 9, wherein the geological model modification module comprises:
the forward full wave field recording unit is used for establishing a forward method of underground excitation and ground reception according to the micro-logging observation parameters, and forward mixed wave records of direct waves, refracted waves, reflected waves and multiple waves by adopting a ray tracing method;
and the geological model correcting unit is used for picking up the forward mixing record first arrival wave peak time, correcting the low-speed stratum speed of the horizontal layered geological model of the surface layer according to the forward mixing record first arrival wave peak time, and obtaining the corrected horizontal layered geological model of the surface layer.
11. The apparatus of claim 10, wherein the geological model modification unit is specifically configured to:
performing ray tracing forward at different corrected stratum speeds, and counting the simulated forward data first arrival time of all excitation points in the low-speed layer and the deceleration layer;
determining the sum of the difference value between the forward evolution record first-arrival time and the actual record first-arrival time corresponding to each corrected stratum speed according to the forward evolution mixed wave record first-arrival wave peak time and the simulated forward evolution data first-arrival time;
and determining the corrected stratum speed corresponding to the minimum value in the sum of the forward record first arrival time and the actual record first arrival time as the stratum speed of the first stratum in the surface horizontal layered geological model, and correcting the low-speed layer stratum speed of the surface horizontal layered geological model to obtain the corrected surface horizontal layered geological model.
12. The apparatus of claim 8, wherein the direct wave identification module is specifically configured to:
picking up the forward direct wave and recording the peak time of the direct wave;
recording the peak time of the direct wave according to the forward direct wave, and calculating the difference value between the first arrival time of different receiving channels excited by different depths in the micro-logging acquisition record and the forward direct wave time corresponding to the first arrival time;
and if the difference is less than one fourth of the period of the first-motion wave of the receiving channel, determining that the first-motion wave of the receiving channel is a direct wave.
13. The apparatus of claim 8, wherein the interference wave compression module is specifically configured to:
splicing the residual seismic channels in the micro-logging acquisition records after the seismic channels with the primary wave indirect arrival waves are removed into a data body, correcting the primary wave take-off time of all the seismic channels in the data body to the same time, and obtaining the micro-logging acquisition records after the primary wave leveling;
calculating energy balance factors of all sample values in the micro-logging acquisition records after the first arrival wave is leveled, and applying the energy balance factors of all sample values to the micro-logging acquisition records after the first arrival wave is leveled to obtain micro-logging records after the energy balance;
and carrying out frequency wave number domain filtering operation on the micro-logging records after energy balance, and eliminating interference waves to obtain the filtered micro-logging records.
14. The apparatus of claim 8, wherein the Q value calculation module is specifically configured to:
picking up a complete period time of the first arrival wave on the micro logging records after filtering, reserving sample point amplitude values in the complete period of the first arrival wave, and enabling the residual sample point amplitude values to be zero to obtain micro logging data for calculating a Q value;
and determining the surface quality factor Q value of the target area according to the micro-logging data for calculating the Q value.
15. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.
16. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.
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