A reservoir prediction and oil and gas detection method based on longitudinal and transverse wave spectrum decomposition

Abstract

This invention discloses a reservoir prediction and hydrocarbon detection method based on P-wave and S-wave spectral decomposition, comprising the following steps in sequence: S1. Obtaining P-wave data volume A and S-wave data volume B; S2. Decomposing P-wave data volume A and S-wave data volume B using P-wave seismic interpretation and S-wave seismic interpretation respectively, obtaining P-wave tuned volume X and S-wave tuned volume Y; S3. Picking the tuning frequencies of P-wave tuned volume X and S-wave tuned volume Y respectively; S4. Calculating the P-wave / S-wave velocity ratio and Poisson's ratio using the tuning frequencies of P-wave tuned volume X and S-wave tuned volume Y; S5. Performing reservoir prediction and hydrocarbon detection using the P-wave / S-wave velocity ratio and Poisson's ratio. This invention only uses P-wave and S-wave spectral decomposition technology to calculate the P-wave / S-wave velocity ratio and Poisson's ratio for reservoir prediction and hydrocarbon detection, without the need for complex procedures. The method is simple, low-cost, easy to master and promote, and still applicable to areas with low exploration levels.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology and relates to reservoir prediction and oil and gas detection. Specifically, it is a reservoir prediction and oil and gas detection method based on longitudinal and transverse wave spectrum decomposition. Background Technology

[0002] It is known that Poisson's ratio decreases after a reservoir contains oil and gas. Therefore, Poisson's ratio can be predicted using seismic data, thereby enabling reservoir prediction and oil and gas detection. Currently, there are three main methods for predicting Poisson's ratio using seismic data: 1. Using pre-stack P-wave data, S-wave logging, or rock physics modeling to generate S-wave logging data for pre-stack inversion prediction; 2. In multi-wave exploration with P-wave sources, using P-wave, converted S-wave, and S-wave logging data for pre-stack inversion prediction; 3. In multi-wave exploration with S-wave sources, a more complex wavefield is generated than in multi-wave exploration with P-wave sources, and the calculation of Poisson's ratio mainly refers to the pre-stack inversion method in multi-wave exploration with P-wave sources.

[0003] The above three methods have certain limitations: first, they all require shear wave logging data; second, they require precise matching of P-wave and shear wave data; and third, the pre-stack inversion workload and data volume are huge, the methods are complex, time-consuming, and difficult to master. Summary of the Invention

[0004] The purpose of this invention is to provide a reservoir prediction and oil and gas detection method based on longitudinal and transverse spectral decomposition, so as to achieve the goal of simple and efficient reservoir prediction and oil and gas detection.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A reservoir prediction and hydrocarbon detection method based on longitudinal and transverse wave spectral decomposition includes the following steps performed sequentially:

[0007] S1. Acquire P-wave data volume A and S-wave data volume B;

[0008] S2. Using P-wave seismic interpretation and S-wave seismic interpretation, the P-wave data volume A and the S-wave data volume B are decomposed to obtain the P-wave tuned volume X and the S-wave tuned volume Y, respectively.

[0009] S3. Pick up the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y respectively;

[0010] S4. Using the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y, calculate the longitudinal wave velocity ratio and the Poisson's ratio;

[0011] S5. Reservoir prediction and oil and gas detection are performed using the ratio of longitudinal and transverse wave velocities and Poisson's ratio.

[0012] As a limitation, in step S1:

[0013] If the obtained data volume sampling rate is 1ms, proceed to the next step; if the obtained data volume sampling rate is 4ms or 2ms, resample the data volume to 1ms.

[0014] As a further limitation, in step S2:

[0015] The decomposition method involves calculating the spectral decomposition along the interpretation strata using time windows to obtain the tuned body.

[0016] As a further limitation, the time window is determined according to the algorithm of spectral decomposition:

[0017] When using maximum entropy for spectral decomposition, the time window is less than 30ms; when using discrete Fourier transform for spectral decomposition, the time window is greater than 30ms.

[0018] In the case of thin layers, the time window is selected to be less than 30ms.

[0019] As a second limitation, step S3 specifically includes:

[0020] Based on the longitudinal wave tuner X and the transverse wave tuner Y, the tuning frequencies of the longitudinal and transverse waves are automatically picked up by extracting the spectral peak frequency within the frequency range during tuning, or by assuming the tuner is time-domain data within the tuning range to extract the maximum peak time.

[0021] As a third limitation, step S4 specifically includes:

[0022] Substituting the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y into the following formula, we can obtain the longitudinal wave velocity ratio and the Poisson's ratio:

[0023] Formula I

[0024] Formula II

[0025] Where Vp is the longitudinal wave velocity, Vs is the transverse wave velocity, σ is Poisson's ratio, Pp is the longitudinal wave treble period, Ps is the transverse wave treble period, fp is the longitudinal wave tuning frequency, and fs is the transverse wave tuning frequency.

[0026] As a further limitation, Equations I and II are derived through the following derivation:

[0027] Based on the principle of spectral decomposition, the relationship between the frequency trapping period and the time thickness is as follows:

[0028] in, For frequency trap period, For time thickness;

[0029] because:

[0030] Where d is the thickness of the thin layer and v is the layer velocity;

[0031] therefore:

[0032] For P-wave data: For shear wave data: ;

[0033] Therefore, the ratio of P-wave to S-wave velocity is: ;

[0034] Poisson's ratio is: ;

[0035] The notch period is approximately equal to twice the tuning frequency, i.e.

[0036]

[0037] Substituting these values ​​into the formulas for the ratio of longitudinal and transverse wave velocities and the Poisson's ratio, respectively, yields Equations I and II.

[0038] As a fourth limitation, step S5 specifically includes:

[0039] When there is no logging data, the oil and gas-bearing range can be delineated directly based on the P-wave and S-wave velocity ratio and Poisson's ratio calculated in S4, and then the intersection can be obtained to determine the most likely oil and gas-bearing range.

[0040] When well logging data is available, the P-wave velocity ratio and Poisson's ratio calculated in S4 are normalized with the P-wave velocity ratio and Poisson's ratio statistically obtained from the well logging data to unify the numerical range. The numerical range is based on the well logging data. The P-wave velocity ratio and Poisson's ratio are delineated according to the oil and gas threshold values ​​determined by the well logging data, and the intersection is then calculated to determine the most likely oil and gas-bearing range.

[0041] By adopting the above technical solution, the technical progress achieved by this invention compared with the prior art is as follows:

[0042] ① This invention provides a reservoir prediction and hydrocarbon detection method based on P-wave and S-wave spectral decomposition. Since the P-wave and S-wave velocity ratio and Poisson's ratio will decrease after the reservoir contains hydrocarbons, the purpose of reservoir prediction and hydrocarbon detection can be achieved simply by constructing the P-wave and S-wave velocity ratio and Poisson's ratio properties based on the P-wave and S-wave spectral decomposition technology. It does not require complex processes such as rock physics modeling, accurate matching of P-wave and S-wave seismic data volumes, and pre-stack inversion. The method is simple, efficient, and greatly reduces costs. It is easy for researchers to master and promote.

[0043] ②The reservoir prediction and oil and gas detection method based on P-wave and S-wave spectral decomposition provided by this invention relies only on P-wave and S-wave seismic data and does not require well data to participate in the calculation, and is still applicable to areas with low exploration degree.

[0044] This invention provides a reservoir prediction and oil and gas detection method based on longitudinal and transverse wave spectral decomposition. It can achieve the purpose of reservoir prediction and oil and gas detection simply by constructing the longitudinal and transverse wave velocity ratio and Poisson's ratio properties based on longitudinal and transverse wave spectral decomposition technology. It is simple, efficient and applicable to areas with low exploration degree. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method in the embodiment;

[0046] Figure 2 This is a seismic data profile in the embodiment, wherein, Figure 2 a represents the P-wave seismic data profile. Figure 2 b represents the shear wave seismic data profile;

[0047] Figure 3 In the embodiment, the spectral segmentation plane is described, wherein, Figure 3 a represents the segmentation plane of the P-wave data spectrum. Figure 3 b represents the dissection surface of the shear wave data spectrum;

[0048] Figure 4 It is the peak frequency picked up by spectral decomposition in the embodiment, wherein, Figure 4 'a' represents the peak frequency picked up by the spectral decomposition of the longitudinal wave data. Figure 4 b is the peak frequency picked up by the spectral decomposition of the shear wave data;

[0049] Figure 5 In this embodiment, the calculated P-wave and S-wave velocity ratio is used for reservoir prediction, wherein... Figure 5 Figure a in the diagram represents (1 - the ratio of P-wave to S-wave velocity). Figure 5 Figure b in the diagram shows P-wave seismic data;

[0050] Figure 6 In this embodiment, the calculated Poisson's ratio is used for reservoir prediction, wherein... Figure 6 Figure a in the diagram represents (1-Poisson's ratio). Figure 6 Figure b in the diagram shows P-wave seismic data. Detailed Implementation

[0051] The present invention will be further described in detail below through specific embodiments. It should be understood that the described embodiments are only for explaining the present invention and do not limit the present invention.

[0052] Example: A reservoir prediction and hydrocarbon detection method based on longitudinal and transverse wave spectrum decomposition

[0053] (I) Calculation of P-wave and S-wave velocity ratio and Poisson's ratio based on P-wave and S-wave spectral decomposition

[0054] The data volume obtained in this embodiment has a sampling rate of 1ms, so it can be used directly. The specific steps are as follows:

[0055] S1. Obtain P-wave and S-wave seismic interpretations, such as Figure 2 As shown, the interpretation horizons of the P-wave and S-wave data of the target layer in the study area were determined, a unified well-seismic stratigraphic framework was established, and preliminary structural interpretation was completed.

[0056] S2. Within the P-wave and S-wave data volumes, along the interpretation horizon, calculate the spectral decompositions of the P-wave and S-wave respectively within a time window of less than 30 ms to obtain the following results: Figure 3 The tuner shown;

[0057] S3. Based on the tuner for longitudinal and transverse waves, by extracting the spectral peak frequencies within the frequency range during tuning, the tuning frequencies of the longitudinal and transverse waves are automatically picked up, respectively, to obtain the longitudinal wave notch period Pp and the pure transverse wave notch period Ps, as shown below. Figure 4 As shown;

[0058] S4. Substitute the tuning frequency data of the longitudinal and transverse waves into the following formula:

[0059] Formula I

[0060] The P-wave to S-wave velocity ratio can then be obtained;

[0061] Where Vp is the longitudinal wave velocity, Vs is the transverse wave velocity; Pp is the longitudinal wave notch period, Ps is the transverse wave notch period; fp is the longitudinal wave tuning frequency, fs is the transverse wave tuning frequency.

[0062] S5. Substitute the tuning frequency data of the longitudinal and transverse waves into the following formula:

[0063] Formula II

[0064] Poisson's ratio can then be obtained;

[0065] Where σ is Poisson's ratio; Pp is the longitudinal wave notch period, Ps is the transverse wave notch period; fp is the longitudinal wave tuning frequency, and fs is the transverse wave tuning frequency.

[0066] (ii) Reservoir prediction based on the calculated P-wave and S-wave velocity ratios and Poisson's ratio.

[0067] This embodiment directly uses the calculated P-wave and S-wave velocity ratios and Poisson's ratio for reservoir prediction. Since both the P-wave and S-wave velocity ratios decrease after the reservoir contains oil and gas, the areas with the lowest P-wave and S-wave velocity ratios and Poisson's ratios are identified as potential oil and gas-bearing locations. However, because low values ​​are not clearly represented on the graph, therefore... Figure 5 and Figure 6 The figures shown are (1 - ratio of longitudinal and transverse wave velocities) and (1 - Poisson's ratio), which respectively delineate the locations of continuous high values ​​(the range that may contain oil and gas). Then, by finding the intersection, the range that is most likely to contain oil and gas can be determined.

Claims

1. A reservoir prediction and hydrocarbon detection method based on longitudinal and transverse spectral decomposition, characterized in that, This includes the following steps performed sequentially: S1. Acquire P-wave data volume A and S-wave data volume B; S2. Using P-wave seismic interpretation and S-wave seismic interpretation, the P-wave data volume A and the S-wave data volume B are decomposed to obtain the P-wave tuned volume X and the S-wave tuned volume Y, respectively. S3. Pick up the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y respectively; S4. Using the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y, calculate the longitudinal wave velocity ratio and the Poisson's ratio; S5. Reservoir prediction and oil and gas detection are performed using the ratio of P-wave to S-wave velocity and Poisson's ratio; Step S4 specifically includes: Substituting the tuning frequencies of the longitudinal wave tuner X and the transverse wave tuner Y into the following formula, we can obtain the longitudinal wave velocity ratio and the Poisson's ratio: Formula I Formula II Among them, v p Let v be the longitudinal wave velocity. s σ is the transverse wave velocity, Pp is the longitudinal wave treble period, Ps is the transverse wave treble period, fp is the longitudinal wave tuning frequency, and fs is the transverse wave tuning frequency. Equations I and II are derived through the following derivation: Based on the principle of spectral decomposition, the relationship between the frequency trapping period and the time thickness is as follows: in, For frequency trap period, For time thickness; because: Where d is the thickness of the thin layer and v is the layer velocity; therefore: For P-wave data: For shear wave data: ; Therefore, the ratio of P-wave to S-wave velocity is: ; Poisson's ratio is: ; The notch period is approximately equal to twice the tuning frequency, i.e. Substituting these values ​​into the formulas for the ratio of P-wave to S-wave velocity and Poisson's ratio, respectively, yields Equations I and II. Step S5 specifically includes: When there is no logging data, the oil and gas-bearing range can be delineated directly based on the P-wave and S-wave velocity ratio and Poisson's ratio calculated in S4, and then the intersection can be obtained to determine the most likely oil and gas-bearing range. When well logging data is available, the P-wave velocity ratio and Poisson's ratio calculated in S4 are normalized with the P-wave velocity ratio and Poisson's ratio statistically obtained from the well logging data to unify the numerical range. The numerical range is based on the well logging data. The P-wave velocity ratio and Poisson's ratio are delineated according to the oil and gas threshold values ​​determined by the well logging data, and the intersection is then calculated to determine the most likely oil and gas-bearing range.

2. The reservoir prediction and hydrocarbon detection method based on longitudinal and transverse spectral decomposition according to claim 1, characterized in that, In step S1: If the obtained data volume sampling rate is 1ms, proceed to the next step; if the obtained data volume sampling rate is 4ms or 2ms, resample the data volume to 1ms.

3. The reservoir prediction and hydrocarbon detection method based on longitudinal and transverse spectral decomposition according to claim 2, characterized in that, In step S2: The decomposition method involves calculating the spectral decomposition along the interpretation strata using time windows to obtain the tuned body.

4. The reservoir prediction and hydrocarbon detection method based on longitudinal and transverse spectral decomposition according to claim 3, characterized in that, The time window is determined based on the spectral decomposition algorithm: When using maximum entropy for spectral decomposition, the time window is less than 30ms; when using discrete Fourier transform for spectral decomposition, the time window is greater than 30ms. In the case of thin layers, the time window is selected to be less than 30ms.

5. The reservoir prediction and hydrocarbon detection method based on longitudinal and transverse spectral decomposition according to claim 1, characterized in that, Step S3 specifically includes: Based on the longitudinal wave tuner X and the transverse wave tuner Y, the tuning frequencies of the longitudinal and transverse waves are automatically picked up by extracting the spectral peak frequency within the frequency range during tuning, or by assuming the tuner is time-domain data within the tuning range to extract the maximum peak time.

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