A fracture scale prediction method and system

Abstract

The present invention provides a method and system for predicting fault scale, belonging to the field of seismic data interpretation. Based on the frequency-dependent variation of the fractional coherent amplitude, the present invention calculates a fault scale indicator factor, establishes a relationship between the fault scale indicator factor and the fault scale, and predicts the fault scale based on this relationship. For the first time, based on the frequency-dependent variation of the fractional coherent amplitude, the present invention defines its slope as a parameter of the fault scale indicator factor, establishes a correlation between the fault scale and the indicator factor, and addresses the difficult problem of predicting fault scale from real-world data, providing new ideas and methods for quantitatively characterizing fault scale.

Description

Technical Field

[0001] The present invention belongs to the field of seismic data interpretation, and in particular relates to a fault scale prediction method and system. Background Art

[0002] The study of fault scale has always been a hot topic and a difficult problem in the field of geophysics. Fault scale analysis is of great significance for reservoir matching relationship analysis, fault development characteristics, well location design and optimization.

[0003] Conventional practice involves conducting fracture detection studies using different software and methods, and then comparing the results to investigate fracture scale characteristics. This approach ignores the inherent variability between software and methods. This variability significantly reduces the reliability of fracture scale studies, and most studies rely on qualitative assessments, with quantitative research remaining largely undeveloped.

[0004] Therefore, it is necessary to establish a more reliable quantitative prediction method for fault scale to lay the foundation for the study of fault scale characteristics and comprehensive reservoir analysis. Summary of the Invention

[0005] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art and to provide a fracture scale prediction method and system to quantitatively predict fractures.

[0006] By utilizing the differential characteristics of the fracture's frequency-decomposition coherence properties, the slope characteristic of the coherence varying with frequency is calculated and defined as the fault scale indicator (FSI). This is used to quantitatively parameterize the fracture scale and improve the accuracy of fracture characteristic research.

[0007] The present invention is achieved through the following technical solutions:

[0008] The first aspect of the present invention provides a method for predicting fracture scale, which calculates the fracture scale indicator factor based on the variation characteristics of the frequency-divided coherent amplitude with frequency, establishes the relationship between the fracture scale indicator factor and the fracture scale, and predicts the fracture scale based on the relationship between the two.

[0009] A further improvement of the present invention is:

[0010] The method comprises the following steps:

[0011] The first step is to establish geological models of different fault scales;

[0012] The second step is to carry out seismic forward modeling and migration imaging, and perform frequency division processing;

[0013] The third step is to perform coherence calculation on the frequency-divided seismic data and extract the coherence value attributes of the fracture respectively;

[0014] The fourth step is to calculate the slope, which is the rate of change of the coherence value with frequency, and define the slope as the fracture scale indicator factor;

[0015] The fifth step is to fit the indicator factor and the fracture scale with a power function to obtain a fitting curve, and predict the fracture scale based on the fitting curve.

[0016] A further improvement of the present invention is:

[0017] The first step is to establish geological models of different fault scales. The specific operations are as follows:

[0018] According to the research objectives, fault models with different vertical and transverse fault throws are established to represent faults of different scales.

[0019] A further improvement of the present invention is:

[0020] In the second step, seismic forward modeling and migration imaging are carried out. The specific operations are as follows: using the wave equation forward modeling technology, forward modeling is performed to obtain shot gather records, using the shot gather records, CMP gathers are extracted, and the pre-stack depth migration algorithm is used to accurately image them.

[0021] A further improvement of the present invention is:

[0022] The frequency division processing in the second step is specifically performed as follows: performing frequency division processing on the CMP gathers to obtain multiple frequency-divided CMP gathers, and then performing migration on these CMP gathers separately to obtain multiple frequency-divided seismic data.

[0023] A further improvement of the present invention is:

[0024] The fourth step is to calculate the rate of change of the coherence value with frequency, i.e. the slope, which is defined as the fracture scale indicator factor, and the expression is:

[0025]

[0026] Where ΔC is the change in coherence value, and ΔF is the change in frequency.

[0027] A second aspect of the present invention provides a fracture scale prediction system, the system comprising:

[0028] Model building unit, used to build geological models of different fault scales according to the target to be studied;

[0029] A frequency-division seismic data acquisition unit, connected to the model building unit, for performing seismic forward modeling and migration imaging, and performing frequency-division processing;

[0030] A fracture coherence value attribute acquisition unit is connected to the frequency-division seismic data acquisition unit and is used to perform coherence calculation on the frequency-division seismic data and extract the coherence value attributes of the fracture respectively;

[0031] a fracture scale indicator factor acquisition unit connected to the fracture coherence value attribute acquisition unit, for calculating a parameter of the coherence value changing rate with frequency, i.e., a slope, and defining the slope as a fracture scale indicator factor;

[0032] The fracture scale prediction unit is connected to the fracture scale indicator factor acquisition unit and is used to perform power function fitting on the indicator factor and the fracture scale to obtain a fitting curve, and perform fracture scale prediction according to the fitting curve.

[0033] A further improvement of the present invention is:

[0034] The fracture coherence value attribute acquisition unit includes:

[0035] The migration imaging unit is used to obtain shot gather records by forward modeling using the wave equation forward modeling technique, extract CMP gathers from the shot gather records, and accurately image them using the prestack depth migration algorithm;

[0036] The frequency division processing unit is connected to the migration imaging unit and is used to perform frequency division processing on the CMP gathers to obtain multiple frequency-divided CMP gathers, and then migrate these CMP gathers separately to obtain multiple frequency-divided seismic data.

[0037] A further improvement of the present invention is:

[0038] The expression of the fracture scale indicator factor in the fracture scale indicator factor acquisition unit is:

[0039]

[0040] Where ΔC is the change in coherence value, and ΔF is the change in frequency.

[0041] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the above-mentioned fracture scale prediction method.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention adopts the variation characteristics of the frequency-division coherence attribute with frequency to calculate the fracture scale indicator factor, constructs the correlation between the fracture scale and the indicator factor, realizes the quantitative prediction of the fracture scale, and improves the accuracy of fracture characteristic research. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of the method for calculating the fracture scale indicator factor of the present invention;

[0045] Figure 2 It is the geological model established;

[0046] Figure 3 These are migration imaging sections, a. Main frequency 15 Hz, b. Main frequency 23 Hz, c. Main frequency 30 Hz;

[0047] Figure 4a It is the scatter plot of the coherent amplitude of the 10×2m fracture frequency division;

[0048] Figure 4b It is the scatter plot of the coherent amplitude of the 20×4m fault frequency division;

[0049] Figure 4c It is a scatter plot of the coherent amplitude of the 30×6m fracture frequency division;

[0050] Figure 4d It is the scatter plot of the coherent amplitude of the 40×8m fault frequency division;

[0051] Figure 4e It is the scatter plot of the coherent amplitude of the 50×10m fracture frequency division;

[0052] Figure 5a It is a 10×2m fault slope calculation diagram;

[0053] Figure 5b It is a 20×4m fault slope calculation diagram;

[0054] Figure 5c It is a 30×6m fault slope calculation map;

[0055] Figure 5d It is a 40×8m fault slope calculation map;

[0056] Figure 5e This is a 50×10m fault slope calculation map;

[0057] Figure 6 This is a correlation diagram between fracture scale and indicator factor. DETAILED DESCRIPTION

[0058] The present invention is described in further detail below with reference to the accompanying drawings:

[0059] The innovation of this invention lies in that for the first time, based on the variation characteristics of the frequency-divided coherent amplitude with frequency, its slope is defined as the parameter of the fracture scale indicator factor, and the correlation between the fracture scale and the indicator factor is established, which solves the problem of fracture scale prediction in actual data and provides new ideas and methods for realizing the quantitative characterization of fracture scale.

[0060] The present invention provides a fracture scale prediction method. Based on the variation characteristics of the frequency-division coherent amplitude with frequency, a fracture scale indicator factor is calculated, a relationship between the fracture scale indicator factor and the fracture scale is established, and the fracture scale is predicted based on the relationship between the two.

[0061] The embodiments of the inventive method are as follows:

[0062] [Example 1]

[0063] The main contents of the present invention include five parts: geological model establishment, forward simulation and migration imaging, frequency division coherence attribute extraction, fracture scale indicator factor calculation, and fracture scale and indicator factor correlation construction.

[0064] like Figure 1 As shown, the method comprises the following steps:

[0065] The first step is to establish geological models of different fault scales according to the research objectives;

[0066] The specific operation is to establish fracture models with different vertical and transverse fault distances to represent fractures of different scales.

[0067] The second step is to carry out seismic forward modeling and migration imaging, and perform frequency division processing;

[0068] Carry out seismic forward modeling and migration imaging. The specific operations are: use wave equation forward modeling technology to obtain shot gather records, use the shot gather records to extract CMP gathers, and use pre-stack depth migration algorithm to accurately image them.

[0069] The specific operation of frequency division processing is: performing frequency division processing on the CMP gather to obtain multiple frequency-divided CMP gathers, and then independently performing migration on the frequency-divided CMP gathers to obtain multiple frequency-divided seismic data.

[0070] The prestack depth migration algorithm is an existing algorithm and will not be described in detail here.

[0071] The third step is to perform coherence calculation on the frequency-divided seismic data and extract the coherence value attributes of the fracture respectively;

[0072] Extracting the coherence value attribute of the fracture is to extract the coherence value corresponding to the fracture after calculating the coherence body. This coherence value represents the coherence feature of the fracture position.

[0073] The coherent calculation adopts the existing calculation method, which will not be described here.

[0074] The fourth step is to calculate the rate of change of the coherence value with frequency, i.e. the slope, which is defined as the fracture scale indicator factor, and the expression is:

[0075]

[0076] Where ΔC is the change in coherence value, and ΔF is the change in frequency;

[0077] Defining this relationship and parameters is the core innovation of this patent, which is used to reflect the characteristics of the fracture. No related research has been found in the existing literature.

[0078] The fifth step is to fit the indicator factor and the fracture scale with a power function to obtain a fitting curve, and predict the fracture scale based on the fitting curve.

[0079] For example, there are five faults, and the scale is defined as 1-5. For each fault, an FSI parameter can be calculated. This forms the relationship between the FSI and the fault scale. The fitting relationship between the two is: y = a × (-x) b

[0080] y is the fracture scale, x is the fracture scale indicator FSI, and a and b are the two parameters of the power function. Assuming the fitting parameters a = 14.26 and b = 0.3183, the final expression is y = 14.26 × (-x) 0.3183 .

[0081] The specific operation of fracture scale prediction is as follows: for a fracture of unknown scale, frequency division imaging is performed, coherence is calculated, and FSI is calculated, which is then substituted into the expression y = 14.26 × (-x) 0.3183 In the example, assuming that the FSI of a certain fault is -0.02, and the calculated value is y = 4.1, then the fault scale is level 4, representing a 40x8m fault (or close to it), and finally the fault scale prediction is achieved.

[0082] The method of the present invention is further illustrated below through an application example.

[0083] [Example 2]

[0084] The specific process is as follows:

[0085] (1) First, a geological model with different fault scales was established. Five faults with different vertical and horizontal fault distances were designed for the model. The vertical fault distances ranged from 10m to 50m, the horizontal widths ranged from 2m to 10m, and the fault angle was about 80°, representing the fault characteristics of different scales from small to large, namely, the fault scales were 10x2m, 20x4m, 30x6m, 40x8m and 50x10m, as shown in the attached figure. Figure 2 shown.

[0086] (2) Through the wave equation forward modeling technology, 23Hz main frequency wavelet is used for forward modeling to obtain the shot gather record. Using the shot gather record, CMP gathers are extracted and accurately imaged using the prestack depth migration algorithm. At the same time, prestack frequency division processing is carried out for the model. The original CMP gathers are used for frequency division processing, and then a separate prestack depth migration is performed on them. Three groups of frequency division parameters are set from low to high, namely, main frequency 15Hz, bandwidth 5-25Hz; main frequency 23Hz, bandwidth 13-33Hz; main frequency 30Hz, bandwidth 20-40Hz. The imaging results are shown in the attached figure. Figure 3 shown.

[0087] (3) In order to carry out quantitative research on fracture detection, the fracture site ( Figure 3 The coherent attributes of the pre-stack frequency-divided seismic data (indicated by the arrows) are superimposed and displayed, as shown in the attached figure. Figures 4a to 4e As shown in the figure, it can be seen that the frequency-division data has obvious change characteristics for fracture imaging, and high-frequency data can improve the imaging effect of fractures. In order to further analyze the characteristics of the rate of change of the frequency-division coherence attribute with frequency, the slope of the scattered points was calculated, and it can be seen that the slopes of fractures of different scales are different. After normalizing the frequency, the slopes of the three-point straight line fitting of fractures of different scales (from small to large) are accurately calculated as -0.0004618, -0.002171, -0.006152, -0.01627 and -0.04065 respectively. It can be seen that the slope of small-scale fractures is relatively large, and as the fracture scale increases, the slope decreases significantly, as shown in the attached figure. Figures 5a to 5e .

[0088] (4) Intersect and analyze the slope value and the fracture scale, as shown in the attached figure. Figure 6 As shown in the figure, the slope is defined as the Fault Scale Indicator (FSI), with the FSI on the horizontal axis and the fault scale on the vertical axis. The ordinate values ​​range from 1 to 5, with 1 representing a 10x2m fault, 2 representing a 20x4m fault, 3 representing a 30x6m fault, 4 representing a 40x8m fault, and 5 representing a 50x10m fault. It can be seen that the FSI for small-scale faults is larger, and the closer the value is to 0, the smaller the FSI for large-scale faults. There is a clear positive correlation between fault scale and the FSI. This establishes a power function fitting relationship between fault scale and the FSI. Using the FSI parameter, the fault scale characteristics can be calculated, achieving a parameterized quantitative representation of the fault scale, providing new ideas and methods for the study of fault scale characteristics.

[0089] The present invention also provides a fracture scale prediction system, the embodiments of which are as follows:

[0090] [Example 3]

[0091] The system comprises:

[0092] Model building unit, used to build geological models of different fault scales according to the target to be studied;

[0093] The frequency-division seismic data acquisition unit is connected to the model building unit and is used to carry out seismic forward modeling and migration imaging, as well as frequency-division processing;

[0094] The specific operation is to establish fracture models with different vertical and transverse fault distances to represent fractures of different scales.

[0095] The fracture coherence value attribute acquisition unit is connected to the frequency-division seismic data acquisition unit and is used to perform coherence calculation on the frequency-division seismic data and extract the coherence value attributes of the fracture respectively;

[0096] The fracture coherence value attribute acquisition unit includes an offset imaging unit and a frequency division processing unit.

[0097] The migration imaging unit is used to obtain shot gather records by forward modeling using the wave equation forward modeling technology, extract CMP gathers using the shot gather records, and accurately image them using the pre-stack depth migration algorithm.

[0098] The prestack depth migration algorithm is an existing algorithm and will not be described in detail here.

[0099] The frequency division processing unit is connected to the migration imaging unit and is used to perform frequency division processing on the CMP gathers to obtain multiple frequency-divided CMP gathers, and then migrate these CMP gathers separately to obtain multiple frequency-divided seismic data.

[0100] The fracture scale indicator factor acquisition unit is connected to the fracture coherence value attribute acquisition unit and is used to calculate the slope, which is the rate of change of the coherence value with frequency. The slope is defined as the fracture scale indicator factor.

[0101] The expression of the fracture scale indicator factor in the fracture scale indicator factor acquisition unit is:

[0102]

[0103] Where ΔC is the change in coherence value, and ΔF is the change in frequency.

[0104] The fracture scale prediction unit is connected to the fracture scale indicator factor acquisition unit and is used to perform power function fitting on the indicator factor and the fracture scale to obtain a fitting curve, and perform fracture scale prediction based on the fitting curve.

[0105] For example, there are five faults, and the scale is defined as 1-5. For each fault, an FSI parameter can be calculated. This forms the relationship between the FSI and the fault scale. The fitting relationship between the two is: y = a × (-x) b

[0106] y is the fracture scale, x is the fracture scale indicator FSI, and a and b are the two parameters of the power function. Assuming the fitting parameters a = 14.26 and b = 0.3183, the final expression is y = 14.26 × (-x) 0.3183 .

[0107] The specific operation of fracture scale prediction is as follows: for a fracture of unknown scale, frequency division imaging is performed, coherence is calculated, and FSI is calculated, which is then substituted into the expression y = 14.26 × (-x) 0.3183 In the example, assuming that the FSI of a certain fault is -0.02, and the calculated value is y = 4.1, then the fault scale is level 4, representing a 40x8m fault (or close to it), and finally the fault scale prediction is achieved.

[0108] The present invention also provides a computer-readable storage medium, and embodiments of the computer-readable storage medium are as follows:

[0109] [Example 4]

[0110] The computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer is caused to perform the steps in the above-mentioned fracture scale prediction method.

[0111] This paper establishes a method for calculating a fracture scale indicator factor based on frequency-fraction coherence attributes. First, a geological model of fractures of varying scales is established. Forward modeling and migration imaging are then performed to obtain a frequency-fraction data volume. The coherence attribute values ​​of the frequency-fraction data volume are calculated, and the coherence attribute values ​​at the fracture locations are extracted to produce a scatter plot. The slope, a parameter characteristic of the rate of change of the frequency-fraction coherence attribute with frequency, is calculated and defined as the fracture scale indicator factor. A correlation is established between fracture scale and the indicator factor, enabling parameterized quantitative characterization of fracture scale, improving the accuracy of fracture scale characterization studies and promising application prospects.

[0112] Finally, it should be noted that the above technical solution is only one embodiment of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the application methods and principles disclosed in the present invention, and it is not limited to the method described in the above specific embodiment of the present invention. Therefore, the method described above is only preferred and does not have a restrictive meaning.

Claims

1. A fracture scale prediction method, characterized in that: The method calculates the fracture scale indicator factor based on the variation characteristics of the frequency-divided coherent amplitude with the frequency, establishes the relationship between the fracture scale indicator factor and the fracture scale, and predicts the fracture scale based on the relationship between the two. The following steps are involved: The first step is to establish geological models of different fault scales; The second step is to carry out seismic forward modeling and migration imaging, and perform frequency division processing; The third step is to perform coherence calculation on the frequency-divided seismic data and extract the coherence value attributes of the fracture respectively; The fourth step is to calculate the slope, which is the rate of change of the coherence value with frequency, and define the slope as the fracture scale indicator factor; The fifth step is to fit the fracture scale indicator factor and the fracture scale with a power function to obtain a fitting curve, and then predict the fracture scale based on the fitting curve.

2. The prediction method according to claim 1, characterized in that The first step is to establish geological models of different fault scales. The specific operations are as follows: According to the research objectives, fault models with different vertical and transverse fault throws are established to represent faults of different scales.

3. The prediction method according to claim 1, wherein: In the second step, seismic forward modeling and migration imaging are carried out. The specific operations are as follows: using the wave equation forward modeling technology, forward modeling is performed to obtain shot gather records, using the shot gather records, CMP gathers are extracted, and pre-stack depth migration algorithm is used to accurately image them.

4. The prediction method according to claim 3, characterized in that The frequency division processing in the second step is specifically performed as follows: performing frequency division processing on the CMP gathers to obtain multiple frequency-divided CMP gathers, and then performing migration on these CMP gathers separately to obtain multiple frequency-divided seismic data.

5. The prediction method according to claim 4, characterized in that The fourth step is to calculate the slope, which is the rate of change of the coherence value with frequency and is defined as the fracture scale indicator factor. The expression is: Where ΔC is the change in coherence value, and ΔF is the change in frequency.

6. A fracture scale prediction system, characterized in that: The system comprises: Model building unit, used to build geological models of different fault scales according to the target to be studied; The frequency-division seismic data acquisition unit is connected to the model building unit and is used to carry out seismic forward modeling and migration imaging, as well as frequency-division processing; The fracture coherence value attribute acquisition unit is connected to the frequency-division seismic data acquisition unit and is used to perform coherence calculation on the frequency-division seismic data and extract the coherence value attributes of the fracture respectively; The fracture scale indicator factor acquisition unit is connected to the fracture coherence value attribute acquisition unit and is used to calculate the slope, which is the rate of change of the coherence value with frequency. The slope is defined as the fracture scale indicator factor. The fracture scale prediction unit is connected to the fracture scale indicator factor acquisition unit and is used to perform power function fitting on the fracture scale indicator factor and the fracture scale to obtain a fitting curve, and perform fracture scale prediction based on the fitting curve.

7. The prediction system according to claim 6, characterized in that The fracture coherence value attribute acquisition unit includes: The migration imaging unit is used to obtain shot gather records by forward modeling using the wave equation forward modeling technique, extract CMP gathers from the shot gather records, and accurately image them using the prestack depth migration algorithm; The frequency division processing unit is connected to the migration imaging unit and is used to perform frequency division processing on the CMP gathers to obtain multiple frequency-divided CMP gathers, and then migrate these CMP gathers separately to obtain multiple frequency-divided seismic data.

8. The prediction system according to claim 7, characterized in that The expression of the fracture scale indicator factor in the fracture scale indicator factor acquisition unit is: Where ΔC is the change in coherence value, and ΔF is the change in frequency.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps of the fracture scale prediction method according to any one of claims 1 to 5.

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