A Q value calculation method and system based on VSP and microlog seismic data

Abstract

This invention provides a method and system for calculating Q-values ​​based on VSP and micrologging seismic data. The extracted Q-values ​​have high accuracy and good calculation stability, facilitating subsequent Q-compensation processing of surface seismic data and improving the imaging resolution and accuracy of the seismic data. The method includes the following steps: acquiring surface seismic data, VSP data, and micrologging data; preprocessing the acquired surface seismic data; constructing a Q1 value objective function based on the preprocessed surface seismic data; preprocessing the acquired VSP data; constructing a Q2 value objective function based on the preprocessed VSP data; linearly combining the Q1 and Q2 value objective functions to obtain a Q3 value objective function; and preprocessing the acquired micrologging data to obtain the Q-value. 井 Value; in Q 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

Description

Technical Field

[0001] This invention relates to the field of seismic data processing technology for petroleum exploration, specifically to a method and system for calculating Q-values ​​based on VSP and micrologging seismic data. Background Technology

[0002] Due to the non-perfectly elastic characteristics of the geological formation, seismic waves undergo severe attenuation during propagation, especially with a significant loss of high-frequency energy, greatly reducing the imaging resolution and accuracy of seismic data. Furthermore, with the continuous advancement of oil and gas exploration, the complex near-surface conditions and severe weathering and erosion in these areas exacerbate the energy attenuation of seismic waves during propagation, making it one of the main reasons affecting the resolution of seismic data.

[0003] To quantitatively reflect the attenuation of seismic waves during propagation through strata, the quality factor Q-value is typically used as a quantitative evaluation parameter. By extracting the Q-value and using it for energy compensation, the effects of near-surface and stratum attenuation can be eliminated, improving the imaging resolution and accuracy of seismic data. There are many algorithms for extracting the Q-value, such as time-domain methods based on amplitude attenuation and rise time, frequency-domain methods based on spectral ratio and spectral simulation, and time-frequency domain methods based on Hilbert transform and S-transform. However, most current methods require a high signal-to-noise ratio from the seismic data, and they typically utilize relatively limited seismic data, resulting in low accuracy and poor computational stability in Q-value extraction. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a method and system for calculating Q-values ​​based on VSP and micrologging seismic data. The extracted Q-values ​​have high accuracy and good calculation stability, facilitating subsequent Q-compensation processing of ground seismic data and improving the imaging resolution and accuracy of seismic data.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for calculating the Q-value based on VSP and micrologging seismic data includes the following steps:

[0007] Collect surface seismic data, VSP data, and micrologging data;

[0008] Preprocess the collected ground seismic data;

[0009] A Q1 objective function is constructed based on the preprocessed ground seismic data;

[0010] Preprocess the collected VSP data;

[0011] Construct a Q2 objective function based on the preprocessed VSP data;

[0012] The objective function for Q1 and the objective function for Q2 are linearly combined to obtain the objective function for Q3.

[0013] After preprocessing the collected micro-logging data, Q is obtained. 井 value;

[0014] In Q 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

[0015] Preferably, the preprocessing of the acquired ground seismic data specifically involves: loading the preprocessed ground seismic data using an observation system.

[0016] Preferably, the step of constructing the objective function of Q1 value based on the preprocessed ground seismic data includes obtaining the adjacent trace amplitude calculation expression of the preprocessed ground seismic data according to the frequency spectrum ratio method;

[0017] Based on the principle of minimizing amplitude energy error, a Q1 value objective function is constructed according to the amplitude calculation expression of adjacent channels. The expression of the Q1 value objective function is as follows:

[0018]

[0019] Where C(Q1) is the attenuation coefficient of Q1, O1(Q1) is the objective function for Q1 value, Q1 is the quality factor of the ground seismic data, A1(f) and A2(f) are the amplitude spectra at time 1 and time 2 respectively, f is the amplitude, f1 is the amplitude value at time 1, f2 is the amplitude value at time 2, C is the attenuation coefficient, and x1, v1 and x2, v2 represent the trace spacing and velocity of adjacent traces in the amplitude spectrum respectively.

[0020] Preferably, the expression for calculating the amplitude of adjacent channels is:

[0021]

[0022] Preferably, the preprocessing of the collected VSP data includes,

[0023] The preprocessed VSP data was loaded using the observation system;

[0024] The loaded VSP data is processed to separate the uplink and downlink waves to obtain the downlink wave data.

[0025] Preferably, the step of constructing the Q2 objective function based on the preprocessed VSP data includes:

[0026] Based on the frequency spectrum ratio method and the principle of minimizing amplitude energy error, a Q2 value objective function is constructed from the acquired downwave data, and its expression is as follows:

[0027]

[0028] Where C(Q2) is the attenuation coefficient of Q2. O2(Q2) is the objective function for Q2 value, A1(f) and A2(f) are the amplitude spectra at time 1 and time 2 respectively, f is the amplitude, x1, v1 and x2, v2 represent the channel spacing and velocity of adjacent channels in the amplitude spectrum respectively, f1 is the amplitude value at time 1, and f2 is the amplitude value at time 2.

[0029] Preferably, the expression for obtaining the Q3 objective function by linearly combining the Q1 and Q2 objective functions is as follows:

[0030] O(Q) = αO1(Q) + βO2(Q);

[0031] Where O1(Q) is equivalent to O1(Q1), which is the objective function for Q1 value, and O2(Q) is equivalent to O2(Q2), which is the objective function for Q2 value. α and β are the weight coefficients of O1(Q) and O2(Q), respectively, and the values ​​of α and β are between 0 and 1.

[0032] Preferably, the preprocessing of the collected micrologging data includes decompiling the micrologging data and loading the preprocessed micrologging data using an observation system.

[0033] Preferably, the step in Q 井 The interpolation process for the objective function of Q3 under the constraint of the value is specifically performed by using triangular interpolation.

[0034] A Q-value calculation system based on VSP and micrologging seismic data includes,

[0035] The data acquisition module is used to acquire surface seismic data, VSP data, and micrologging data;

[0036] The ground seismic data preprocessing module is used to preprocess the acquired ground seismic data;

[0037] The Q1 value objective function construction module is used to construct the Q1 value objective function based on the preprocessed ground seismic data.

[0038] The VSP data preprocessing module is used to preprocess the collected VSP data.

[0039] The Q2 value objective function construction module constructs the Q2 value objective function based on the preprocessed VSP data.

[0040] The linear fitting module is used to linearly combine the objective functions for Q1 and Q2 to obtain the objective function for Q3.

[0041] The micro-logging data preprocessing module is used to preprocess the acquired micro-logging data to obtain Q. 井 value;

[0042] The Q-value calculation model building module is used to calculate the Q value. 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] This invention provides a method for calculating the Q-value based on VSP and micrologging seismic data. It constructs a Q1 objective function using adjacent traces of surface seismic data, and a Q2 objective function using downflow waves from VSP data. The Q1 and Q2 values ​​are linearly combined to obtain a high-precision Q3 value. Finally, the Q-value is calculated using micrologging data. 井 Under value constraints, Q3 interpolation is performed to obtain a high-precision Q-value model. This invention comprehensively utilizes VSP and micrologging seismic data for Q-value extraction and calculation. The extracted Q-values ​​have high accuracy and good calculation stability. Furthermore, it combines surface seismic data, VSP seismic data, and micrologging data for fusion modeling, improving the problem of the singularity of conventional seismic data and reducing the signal-to-noise ratio requirements of seismic data. The reliability of the Q-value distribution is significantly improved, the planar distribution is smoother, and the profile resolution is enhanced, facilitating subsequent Q-value compensation processing of seismic data, thereby improving the imaging resolution and accuracy of seismic data. Attached Figure Description

[0045] Figure 1 This is a flowchart of the Q-value calculation method of the present invention;

[0046] Figure 2 This is a schematic diagram of the framework of the Q-value calculation system of the present invention;

[0047] Figure 3 This is a diagram illustrating the implementation steps of Q-value calculation in an embodiment of the present invention;

[0048] Figure 4(a) is a schematic diagram of the Q value calculated by the conventional method in an embodiment of the present invention;

[0049] Figure 4(b) is a schematic diagram of the Q value calculated by the method of the present invention in an embodiment of the present invention;

[0050] Figure 5(a) is a cross-sectional view before processing in an embodiment of the present invention;

[0051] Figure 5(b) is a cross-sectional view after the conventional method for extracting Q values ​​is applied in an embodiment of the present invention;

[0052] Figure 5(c) is a cross-sectional view of the Q-value extraction method of the present invention applied in an embodiment of the present invention. Detailed Implementation

[0053] The present invention will be further described in detail below with reference to specific embodiments. These descriptions are for explanation purposes only and are not intended to limit the scope of the invention.

[0054] like Figure 1 As shown, the present invention provides a method for calculating the Q-value based on VSP and micro-logging seismic data, comprising the following steps:

[0055] Collect surface seismic data, VSP data, and micrologging data;

[0056] Preprocess the collected ground seismic data;

[0057] A Q1 objective function is constructed based on the preprocessed ground seismic data;

[0058] Preprocess the collected VSP data;

[0059] Construct a Q2 objective function based on the preprocessed VSP data;

[0060] The objective function for Q3 is obtained by linearly combining the objective functions for Q1 and Q2.

[0061] After preprocessing the collected micro-logging data, Q is obtained. 井 value;

[0062] In Q 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

[0063] This invention provides a method for calculating the Q-value based on VSP and micrologging seismic data. It constructs a Q1 objective function using adjacent traces of surface seismic data, and a Q2 objective function using downflow waves from VSP data. The Q1 and Q2 values ​​are linearly combined to obtain a high-precision Q3 value. Finally, the Q-value is calculated using micrologging data. 井 Under value constraints, Q3 interpolation is performed to obtain a high-precision Q-value model. This invention comprehensively utilizes VSP and micrologging seismic data for Q-value extraction and calculation. The extracted Q-values ​​have high accuracy and good calculation stability. Furthermore, it combines surface seismic data, VSP seismic data, and micrologging data for fusion modeling, improving the problem of the singularity of conventional seismic data and reducing the signal-to-noise ratio requirements of seismic data. The reliability of the Q-value distribution is significantly improved, the planar distribution is smoother, and the profile resolution is enhanced, facilitating subsequent Q-value compensation processing of seismic data, thereby improving the imaging resolution and accuracy of seismic data.

[0064] like Figure 3As shown, the first step is to preprocess the acquired ground seismic data, including loading the ground seismic data using the observation system.

[0065] The second step involves constructing a Q1 objective function from the preprocessed ground seismic data from step one, using the amplitude of adjacent trace data.

[0066] The specific implementation steps of step two are as follows:

[0067] The expression for calculating the amplitude of adjacent traces in preprocessed ground seismic data is obtained based on the frequency spectrum ratio method. The expression is as follows:

[0068]

[0069] In the formula, Q1 is the quality factor of the ground seismic data, A1(f) and A2(f) are the amplitude spectra at different times, f is the amplitude, C is the attenuation coefficient, and x1, v1 and x2, v2 represent the trace spacing and velocity of adjacent traces in the amplitude spectrum, respectively.

[0070] Based on the principle of minimizing amplitude energy error, an objective function for calculating the most recent Q1 value can be constructed.

[0071]

[0072] Based on the principle of minimizing amplitude energy error, and in order to eliminate logarithmic calculation errors and improve the stability of the inversion solution, a new objective function for the Q1 value is constructed based on the amplitude calculation expressions of adjacent channels. Its expression is as follows:

[0073]

[0074] In the formula, C(Q1) is the attenuation coefficient of Q1. O1(Q1) is the objective function for Q1, f1 is the amplitude value at time 1, and f2 is the amplitude value at time 2.

[0075] The third step involves preprocessing the collected VSP data, including...

[0076] Load the observation system onto the collected VSP data;

[0077] The loaded VSP data is processed to separate the uplink and downlink waves, and the downlink wave data is obtained. The Q2 value is then calculated using the downlink wave data.

[0078] The specific implementation steps of step three are as follows:

[0079] The VSP downwave data can be directly calculated using the frequency domain amplitude spectrum at different times. Based on step two, the same objective function can be constructed.

[0080] The expression for the objective function of Q2 is:

[0081]

[0082] In the formula, C(Q2) is the attenuation coefficient of Q2. O2(Q2) is the objective function for Q2 value, Q1 is the quality factor of ground seismic data, Q2 is the quality factor of VSP downwave data, A1(f) and A2(f) are the amplitude spectra at different times, f is the amplitude, x1, v1 and x2, v2 represent the trace spacing and velocity of adjacent traces in the amplitude spectrum, respectively, f1 is the amplitude value at time 1, and f2 is the amplitude value at time 2.

[0083] The fourth step is to linearly combine the objective functions for Q1 and Q2 to obtain the expression for the objective function for Q3.

[0084] O(Q)=αO1(Q)+βO2(Q) (5);

[0085] Where O1(Q) is equivalent to O1(Q1), which is the objective function for Q1 value, and O2(Q) is equivalent to O2(Q2), which is the objective function for Q2 value. α and β are the weight coefficients of O1(Q) and O2(Q), respectively, and the values ​​of α and β are between 0 and 1.

[0086] Solving formula (5) by using the inversion algorithm can improve the stability of the inversion algorithm and the Q value extraction accuracy is higher, laying a solid foundation for Q value modeling.

[0087] The fifth step is to preprocess the collected micrologging data, including decompiling the micrologging data and loading the micrologging data using the observation system.

[0088] Based on the amplitude spectrum of data at different times, Q is obtained by formula (4) and calculated from the preprocessed micrologging data. 井 value.

[0089] Step 6, in Q 井 Under the constraint of the value, the objective function of Q3 is interpolated using the triangular interpolation method.

[0090] The specific implementation steps for step six are as follows:

[0091] The Q values ​​extracted in steps four and five are subjected to trigonometric interpolation within the coordinate grid of the work area to obtain a high-precision Q-value model, which facilitates the Q-compensation processing of subsequent ground seismic data and improves the imaging resolution and accuracy of seismic data.

[0092] like Figure 2 As shown, the present invention also provides a Q-value calculation system based on VSP and micro-logging seismic data, including,

[0093] The data acquisition module is used to acquire surface seismic data, VSP data, and micrologging data;

[0094] The ground seismic data preprocessing module is used to preprocess the acquired ground seismic data;

[0095] The Q1 value objective function construction module is used to construct the Q1 value objective function based on the preprocessed ground seismic data.

[0096] The VSP data preprocessing module is used to preprocess the collected VSP data.

[0097] The Q2 value objective function construction module constructs the Q2 value objective function based on the preprocessed VSP data.

[0098] The linear fitting module is used to linearly combine the objective functions for Q1 and Q2 to obtain the objective function for Q3.

[0099] The micro-logging data preprocessing module is used to preprocess the acquired micro-logging data to obtain Q. 井 value;

[0100] The Q-value calculation model building module is used to calculate the Q value. 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

[0101] Example

[0102] This invention provides a specific embodiment of a method and system for calculating Q-values ​​based on VSP and micrologging seismic data. The invention is further explained by comparing the Q-value calculation method described in this invention with other conventional methods.

[0103] like Figure 4a and 4b As shown, compared with conventional methods that do not use VSP and micrologging data and directly extract Q from seismic data, the technology and process of this invention can significantly improve the reliability of the Q value distribution and make the planar distribution smoother.

[0104] Depend on Figure 5a , 5b Figures 5c show the effect of profile application after extracting Q-values ​​using the method of the present invention. The profile resolution is higher after applying Q-values ​​according to the present invention.

[0105] To achieve the above objectives, the main technical means adopted in this invention are described clearly, completely, and accurately, and the substantive content of the invention is explained. The degree of disclosure is such that it is sufficient for a person skilled in the art to understand and implement the invention.

Claims

1. A method for calculating Q-values ​​based on VSP and micro-logging seismic data, characterized in that, Includes the following steps: Collect surface seismic data, VSP data, and micrologging data; Preprocess the collected ground seismic data; A Q1 objective function is constructed based on the preprocessed ground seismic data; Preprocess the collected VSP data; Construct a Q2 objective function based on the preprocessed VSP data; The objective function for Q1 and the objective function for Q2 are linearly combined to obtain the objective function for Q3. After preprocessing the collected micro-logging data, Q is obtained. 井 value; In Q 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

2. The method for calculating Q-value based on VSP and micrologging seismic data according to claim 1, characterized in that, The preprocessing of the acquired ground seismic data specifically involves loading the preprocessed ground seismic data using an observation system.

3. The method for calculating Q-value based on VSP and micrologging seismic data according to claim 1, characterized in that, The construction of the Q1 objective function based on the preprocessed ground seismic data includes, The expression for calculating the amplitude of adjacent traces in preprocessed ground seismic data is obtained based on the frequency spectrum ratio method; Based on the principle of minimizing amplitude energy error, a Q1 value objective function is constructed according to the amplitude calculation expression of adjacent channels. The expression of the Q1 value objective function is as follows: Where C(Q1) is the attenuation coefficient of Q1, O1(Q1) is the objective function for Q1 value, Q1 is the quality factor of the ground seismic data, A1(f) and A2(f) are the amplitude spectra at time 1 and time 2 respectively, f is the amplitude, f1 is the amplitude value at time 1, f2 is the amplitude value at time 2, C is the attenuation coefficient, and x1, v1 and x2, v2 represent the trace spacing and velocity of adjacent traces in the amplitude spectrum respectively.

4. The method for calculating Q-value based on VSP and micro-logging seismic data according to claim 3, characterized in that, The expression for calculating the amplitude of adjacent channels is as follows:

5. The method for calculating Q-value based on VSP and micrologging seismic data according to claim 1, characterized in that, The preprocessing of the collected VSP data includes, The preprocessed VSP data was loaded using the observation system; The loaded VSP data is processed to separate the uplink and downlink waves to obtain the downlink wave data.

6. The method for calculating the Q-value based on VSP and micro-logging seismic data according to claim 5, characterized in that, The step of constructing the Q2 objective function based on the preprocessed VSP data includes, Based on the frequency spectrum ratio method and the principle of minimizing amplitude energy error, a Q2 value objective function is constructed from the acquired downwave data, and its expression is as follows: Where C(Q2) is the attenuation coefficient of Q2. O2(Q2) is the objective function for Q2 value, A1(f) and A2(f) are the amplitude spectra at time 1 and time 2 respectively, f is the amplitude, x1, v1 and x2, v2 represent the channel spacing and velocity of adjacent channels in the amplitude spectrum respectively, f1 is the amplitude value at time 1, and f2 is the amplitude value at time 2.

7. The method for calculating Q-value based on VSP and micro-logging seismic data according to claim 1, characterized in that, The expression for obtaining the Q3 objective function by linearly combining the Q1 and Q2 objective functions is as follows: O(Q) = αO1(Q) + βO2(Q); Where O1(Q) is equivalent to O1(Q1), which is the objective function for Q1 value, and O2(Q) is equivalent to O2(Q2), which is the objective function for Q2 value. α and β are the weight coefficients of O1(Q) and O2(Q), respectively, and the values ​​of α and β are between 0 and 1.

8. The method for calculating Q-value based on VSP and micrologging seismic data according to claim 1, characterized in that, The preprocessing of the collected micrologging data includes decompiling the micrologging data and loading the preprocessed micrologging data using an observation system.

9. The method for calculating Q-value based on VSP and micrologging seismic data according to claim 1, characterized in that, The above in Q 井 The interpolation process for the objective function of Q3 under the constraint of the value is specifically performed by using triangular interpolation.

10. A Q-value calculation system based on VSP and micro-logging seismic data, characterized in that, The Q-value calculation method based on any one of claims 1-9 includes, The data acquisition module is used to acquire surface seismic data, VSP data, and micrologging data; The ground seismic data preprocessing module is used to preprocess the acquired ground seismic data; The Q1 value objective function construction module is used to construct the Q1 value objective function based on the preprocessed ground seismic data. The VSP data preprocessing module is used to preprocess the collected VSP data. The Q2 value objective function construction module constructs the Q2 value objective function based on the preprocessed VSP data. The linear fitting module is used to linearly combine the objective functions for Q1 and Q2 to obtain the objective function for Q3. The micro-logging data preprocessing module is used to preprocess the acquired micro-logging data to obtain Q. 井 value; The Q-value calculation model building module is used to calculate the Q value. 井 Under the constraint of the value, interpolation processing is performed on the objective function of Q3 to obtain the Q-value calculation model, and the Q-value is calculated based on the Q-value calculation model.

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