阅读说明：本技术 一种基于测井与地震数据的品质因子建模方法 (Quality factor modeling method based on logging and seismic data ) 是由 吴吉忠 王冬娜 吴吉厚 贾善坡 赵小青 柳波 于 2019-10-13 设计创作，主要内容包括：本发明涉及的是一种基于测井与地震数据的品质因子建模方法,它包括:利用VSP数据求取的Q值与事先给定的雷克子波、反射系数序列等参数生成VSP井位置的粘弹性合成地震记录,对粘弹性合成地震记录与井旁原始地震记录进行互相关计算求取最佳Q值；利用VSP井数据求取的最佳Q值对地震数据生成的Q场进行标定,得到最终Q场。本发明通过粘弹性合成地震记录与井旁地震数据匹配、大套地层时窗约束地震资料Q值计算、VSP数据与地震数据联合,实现了品质因子Q的最佳求取。利用本发明获取的Q场,可以补偿叠后地震数据由于地震波传播过程中能量耗散引起的高频信号衰减,拓宽地震资料的频带,有效提高地震数据的分辨率。(The invention relates to a quality factor modeling method based on logging and seismic data, which comprises the steps of generating a viscoelastic synthetic seismic record of a VSP well position by utilizing a Q value obtained by VSP data and parameters such as a preset Rake wavelet, a reflection coefficient sequence and the like, and carrying out cross-correlation calculation on the viscoelastic synthetic seismic record and a well-side original seismic record to obtain an optimal Q value; and calibrating the Q field generated by the seismic data by using the optimal Q value obtained by the VSP well data to obtain the final Q field. The best solution of the quality factor Q is realized by matching the viscoelastic synthetic seismic record with the well-side seismic data, calculating the Q value of the constrained seismic data of a large set of stratum time windows and combining the VSP data with the seismic data. The Q field obtained by the invention can compensate the high-frequency signal attenuation of the post-stack seismic data caused by energy dissipation in the seismic wave propagation process, broaden the frequency band of seismic data and effectively improve the resolution of the seismic data.)

1. A quality factor modeling method based on logging and seismic data is characterized by comprising the following steps:

step one, solving an initial Q value of VSP logging data in a work area by using a logarithmic spectrum ratio method;

step two, carrying out a large set of stratum horizon interpretation by using the numerical structure characteristics of the initial Q value obtained in the step one;

thirdly, the stratum horizon obtained by the second step is used as a calculation time window for solving the Q value of the quality factor of the ground reflection seismic data, and a log-spectral ratio method is adopted in the calculation time window to solve the Q field of the seismic data;

step four, taking the initial Q value obtained in the step one as an initial value, generating a viscoelastic synthetic seismic record, and continuously adjusting the initial Q value to enable the cross-correlation coefficient of the viscoelastic synthetic seismic record and the well-side seismic data trace to reach a preset threshold value A;

a. carrying out frequency spectrum analysis on shallow seismic data with a time window within 0.2s-0.8s to obtain a main frequency F of the seismic data;

b. generating a synthetic seismic record F (t) by utilizing a known reflection coefficient sequence r (t) and a Rake wavelet w (t) with a main frequency of F through convolution operation, wherein F (t) r (t) w (t) represents convolution operation;

c. using positive Q filtering formula for generated synthetic seismic record f (t)

d. Extracting seismic data trace beside well, and recording as f_side(t)；

e、f_Q(t) and f_side(T) the value of T is in the range of [0, T]Where T represents the time depth, Δ T represents the time sampling interval, i represents the discrete value, and N represents the discrete value corresponding to the maximum time depth, and f is established_Q(t) and f_side(t) cross-correlation objective function

f. Continuously adjusting and updating the initial Q value, repeating the steps c and e, stopping calculation when R (Q) is not less than A, and obtaining the adjusted initial Q value, wherein A is a preset threshold value;

step five, calibrating the Q field of the seismic data obtained in the step three by using the adjusted initial Q value obtained in the step four to obtain an optimal Q field;

and step six, carrying out high-resolution processing on the stacked seismic data volume by using the optimal Q field obtained in the step five.

2. The method of claim 1, wherein the method comprises: in the first step, the initial Q value is obtained by using a logarithmic spectrum ratio method, namely, a formula

3. The method of claim 2, wherein the method comprises: the second step is specifically as follows: and (3) interpolating and smoothing the plurality of initial Q values obtained in the step one to obtain a Q curve, interpreting the layer position of a large set of strata according to the change condition of the numerical value of the local range of the Q curve, interpreting the area with gentle numerical value change as one set of strata, interpreting the area with severe numerical value change as another set of strata, interpreting the Q curve as a plurality of sets of strata by analogy, and enabling the total number of strata to be not more than 5.

4. The method of claim 3, wherein the method comprises: the fifth step is specifically as follows: recording the adjusted Q value obtained in the step four as Q_wRecording the Q field of the seismic data obtained in the third step as Q_sIs mixing Q with_wQ corresponding to the time depth point_sDividing one by one to obtain the correction coefficient eta ═ Q_w/Q_sSmoothing eta by spatial interpolation and combining with Q_sThe multiplication results in the best Q field.

5. The method of claim 4, wherein the method comprises: the sixth step is specifically as follows: using formulas

The technical field is as follows:

the invention relates to the technical field of high-resolution processing in the seismic data processing process in the technical field of seismic exploration post-stack reflected wave seismic data processing, in particular to a quality factor modeling method based on logging and seismic data.

Background art:

in the process of seismic wave propagation, energy absorption attenuation and phase stretching distortion are caused by the viscoelasticity of the underground medium, and the integral resolution and signal-to-noise ratio of data are reduced. The inverse Q filtering processing can compensate and correct the seismic data in the aspects of amplitude attenuation and phase distortion, thereby greatly recovering the authenticity of the seismic data and improving the resolution. The inverse Q filtering requires the quality factor Q value of the formation, and its accuracy directly affects the accuracy of the inverse Q filtering. However, the underground structure is complex, and factors influencing seismic wave attenuation are very many, so the Q value is difficult to be solved, and the inverse Q filtering is inaccurate, so that the reasonable estimation of the quality factor Q has important significance for improving the data quality.

The estimation method of the quality factor Q can be divided into two categories according to the data source: seismic data estimated Q-values and well data estimated Q-values. The seismic data are wide in distribution range and high in coverage of a work area, the Q value can be conveniently estimated by using the seismic data, but the Q value is limited by signal-to-noise ratio and data quality, the estimated Q value precision is insufficient compared with the Q value estimated by well data, the well data estimated Q value is high in precision but limited by the fact that the number of wells is small, and the Q value of the position without the wells in the work area cannot be obtained. The method for solving Q mainly comprises a calculation method represented by a spectral ratio method and a scanning method for performing Q scanning through inverse Q filtering, wherein in the scanning method, different Q values are selected to perform inverse Q filtering processing, and the Q selection is considered to be reasonable when a processing result is close to an expected value. In the estimation of Q, the industry lacks objective criteria for how to evaluate the rationality of Q. The rationality of the quality factor Q depends on the purpose for which Q is applied, rather than on its proximity to the actual rock intrinsic quality factor Q. If the quality factor Q is used in an inverse Q filtering process to improve the resolution of the seismic data to serve subsequent reservoir prediction, then the evaluation principle for the best quality factor Q should be that the above-well viscoelastic synthetic seismic records most closely match the well-side seismic traces.

The invention content is as follows:

the invention aims to provide a quality factor modeling method based on logging and seismic data, which is used for solving the problem that the quality factor Q of the seismic data is difficult to solve in the prior art.

The technical scheme adopted by the invention for solving the technical problems is as follows: the quality factor modeling method based on the logging and the seismic data comprises the following steps:

step one, solving an initial Q value of VSP logging data in a work area by using a logarithmic spectrum ratio method;

step two, carrying out a large set of stratum horizon interpretation by using the numerical structure characteristics of the initial Q value obtained in the step one;

thirdly, the stratum horizon obtained by the second step is used as a calculation time window for solving the Q value of the quality factor of the ground reflection seismic data, and a log-spectral ratio method is adopted in the calculation time window to solve the Q field of the seismic data;

step four, taking the initial Q value obtained in the step one as an initial value, generating a viscoelastic synthetic seismic record, and continuously adjusting the initial Q value to enable the cross-correlation coefficient of the viscoelastic synthetic seismic record and the well-side seismic data trace to reach a preset threshold value A;

a. carrying out frequency spectrum analysis on shallow seismic data with a time window within 0.2s-0.8s to obtain a main frequency F of the seismic data;

b. generating a synthetic seismic record F (t) by utilizing a known reflection coefficient sequence r (t) and a Rake wavelet w (t) with a main frequency of F through convolution operation, wherein F (t) r (t) w (t) represents convolution operation;

c. using positive Q filtering formula for generated synthetic seismic record f (t)

Generating viscoelastic synthetic seismic records f_Q(t)；

d. Extracting seismic data trace beside well, and recording as f_side(t)；

e、f_Q(t) and f_side(T) the value of T is in the range of [0, T]Where T represents the time depth, Δ T represents the time sampling interval, i represents the discrete value, and N represents the discrete value corresponding to the maximum time depth, and f is established_Q(t) and f_side(t) cross-correlation objective function

f. Continuously adjusting and updating the initial Q value, repeating the steps c and e, stopping calculation when R (Q) is not less than A, and obtaining the adjusted initial Q value, wherein A is a preset threshold value;

step five, calibrating the Q field of the seismic data obtained in the step three by using the adjusted initial Q value obtained in the step four to obtain an optimal Q field;

and step six, carrying out high-resolution processing on the stacked seismic data volume by using the optimal Q field obtained in the step five.

In the first step of the scheme, the initial Q value is obtained by using a logarithmic spectrum ratio method, namely, a formula

Finding an initial Q, where f is the frequency value, τ is the time depth, pi is 3.14, a₁(f) Is the amplitude value of the overburden, a₂(f) Is the amplitude value of the current formation.

The second step in the scheme is specifically as follows: and (3) interpolating and smoothing the plurality of initial Q values obtained in the step one to obtain a Q curve, interpreting the layer position of a large set of strata according to the change condition of the numerical value of the local range of the Q curve, interpreting the area with gentle numerical value change as one set of strata, interpreting the area with severe numerical value change as another set of strata, interpreting the Q curve as a plurality of sets of strata by analogy, and enabling the total number of strata to be not more than 5.

The fifth step in the scheme is specifically as follows: recording the adjusted initial Q value obtained in the step four as Q_wRecording the Q field of the seismic data obtained in the third step as Q_sIs mixing Q with_wQ corresponding to the time depth point_sDividing one by one to obtain the correction coefficient eta ═ Q_w/Q_sSmoothing eta by spatial interpolation and combining with Q_sThe multiplication results in the best Q field.

The sixth step in the scheme is specifically as follows: using formulas

Subjecting the seismic data to high resolution processing, wherein U (t) represents seismic data amplitude, U (ω) is a Fourier transform result of the seismic data, ω is angular frequency, t is time depth,

representing the inverse fourier transform, Q is the quality factor.

The invention has the following beneficial effects:

1. the quality factor Q value is jointly obtained by utilizing the VSP logging data and the ground reflection seismic data, so that key data are provided for obtaining a seismic section with higher resolution, and the method has important application value for oil and gas exploration and development.

2. The best solution of the quality factor Q is realized by matching the viscoelastic synthetic seismic record with the well-side seismic data, calculating the Q value of the constrained seismic data of a large set of stratum time windows and combining the VSP data with the seismic data.

3. The invention can compensate the attenuation of high-frequency signals of the seismic data after the stack by using the acquired Q field, broaden the frequency band of the seismic data and effectively improve the resolution of the seismic data.

Drawings

FIG. 1 is a flow chart of the technical solution of the present invention.

FIG. 2 is a plot of a large set of stratigraphic horizon interpretations using Q values obtained for VSP wells.

FIG. 3 is a seismic original section.

FIG. 4 is a seismic section after high resolution processing.

Detailed Description

The invention is further illustrated below:

the quality factor modeling method based on the logging and the seismic data comprises the following steps: firstly, carrying out interpretation of a large set of stratum positions by using numerical structural characteristics of a Q value on a VSP well, then using the interpreted large set of stratum positions as a calculation time window of a quality factor Q value obtained by using ground reflection seismic data, using the Q value obtained on the VSP well as an initial value, generating a viscoelasticity synthetic seismic record by using positive Q filtering, continuously updating the Q value to enable a viscoelasticity synthetic seismic record waveform to approach a seismic data channel beside the well, and finally calibrating the Q value obtained by the seismic data to obtain an optimal Q field by using the updated Q value on the VSP well. The high-resolution processing of the post-stack seismic data can be carried out by utilizing the obtained Q field, the attenuation of high-frequency signals caused by energy dissipation in the seismic wave propagation process is compensated, and the underground structure image with improved resolution is obtained.