Method and system for characterizing submarine fan based on general spectral decomposition and multi-attribute fusion

Abstract

The application provides a seabed fan delineation method and system based on general spectral decomposition and multi-attribute fusion, and belongs to the field of oil and gas exploration and development. The method comprises the following steps: firstly, determining a target layer and top and bottom interfaces of seabed fan development, establishing a three-dimensional chronological stratigraphic framework with the top and bottom interfaces as constraints, and performing three-dimensional automatic tracking on internal strata; then, using correlation calculation on seismic original data to obtain a main frequency value, and then using wavelet frequency division technology to perform frequency division processing on the main frequency value to obtain a series of single-frequency band frequency division data bodies; using the strata identified by three-dimensional automatic tracking to extract sensitive attribute bodies along the layer strata slices of the frequency division data bodies; and finally, fusing and displaying the results to delineate the seabed fan boundary. Through spectral decomposition and multi-attribute fusion, the application improves the precision of boundary delineation, and when tracking the strata interfaces, the method combines automatic tracking and manual intervention, thereby reducing the workload of interpretation and ensuring the accuracy of interface tracking.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of oil and gas exploration and development, and particularly relates to a seabed fan delineation method and system based on general spectral decomposition and multi-attribute fusion. BACKGROUND

[0002] The seabed fan is usually a composite sand body formed by a sediment gravity flow in a deep sea environment, such as a channel and a sheet sand.

[0003] Currently, the seabed fan delineation is mainly achieved by using the seismic attribute analysis technology, for example:

[0004] 1) The conventional amplitude attribute (maximum amplitude, root mean square, etc.) is used to delineate the fan body boundary according to the sensitive attribute of the seabed fan;

[0005] 2) The seabed fan is tracked by using the isochronous stratum slicing technology and impedance fusion, and the principle is that the resolution of the seabed fan in the vertical direction is better than that in the horizontal direction; the sandy hydrate reservoir prediction method disclosed in Chinese patent publication CN113341480A first selects a target area based on the "source-channel-sink" guiding ideology, calculates the hydrate stable zone bottom boundary in the study area based on temperature data, and establishes a chronostratigraphic framework on the basis of the chronostratigraphy; then, the three-dimensional stratum is automatically tracked within the stratum from the seabed to the set range on the basis of the three-dimensional stratum framework; secondly, the seismic data body is subjected to frequency division processing to obtain low, medium and high frequency data bodies; then, the maximum amplitude, minimum amplitude, root mean square amplitude and coherent attribute body are calculated for the three sets of data, and each layer attribute is extracted along the layer; the four kinds of layer attributes are fused and analyzed according to the three primary color principle, and the hydrate geological elements are identified and each abnormal area is superimposed to delineate the most abnormal area; finally, the software and the deterministic inversion technology are used to invert the hydrate impedance and the longitudinal wave velocity and other elastic parameters, and then the hydrate saturation body is inverted to realize the prediction of the hydrate enrichment area.

[0006] 3) The seabed fan is tracked by using the line dip angle curvature and RGB attribute fusion technology, and the principle is that the curvature is positive or negative when the stratum is uplifted or depressed to track different stratum morphologies;

[0007] 4) The fan bodies of each period are delineated based on the high-resolution reservoir prediction technology.

[0008] The seabed fan is usually a horizontally distributed composite channel sand body, the contact relationship between the sand bodies is complex, and it is a multi-period evolution. The conventional wave impedance inversion has low resolution, the conventional single attribute extraction is only sensitive to a specific sand body, the conventional attribute fusion technology is sensitive to the sand body at a specific frequency, the division precision of the single sand body boundary and the internal period is low, and it cannot meet the current exploration and development needs. SUMMARY

[0009] The application aims to solve the problems existing in the prior art, and provides a seabed fan delineation method and system based on general spectral decomposition and multi-attribute fusion.

[0010] The application is implemented by the following technical solutions:

[0011] In a first aspect, the application provides a seabed fan delineation method based on general spectral decomposition and multi-attribute fusion, comprising the following steps:

[0012] In a first step, well logging, geology and original seismic data of a three-dimensional target reservoir area are used to combine wells with seismic data, and a target layer and top and bottom interfaces H1 and H2 of the seabed fan are determined;

[0013] In a second step, a three-dimensional chronostratigraphic framework is established with the interfaces H1 and H2 as constraints;

[0014] In a third step, three-dimensional automatic tracking is performed on internal strata of the three-dimensional chronostratigraphic framework;

[0015] In a fourth step, main frequency values are obtained by correlation calculation on original seismic data, and then wavelet frequency division technology is used to perform frequency division processing on the main frequency values to obtain a series of single-frequency band frequency division data bodies;

[0016] In a fifth step, sensitive attribute bodies along strata are extracted from the frequency division data bodies by using the strata identified by three-dimensional automatic tracking;

[0017] In a sixth step, the results of the frequency division data bodies are fused and displayed to delineate the boundary of the seabed fan.

[0018] Further improvements of the application are as follows:

[0019] In the first step, the well-seismic combination is specifically as follows:

[0020] According to the surrounding drilled wells and sedimentary background information, the development period of the seabed fan is determined, and then the two isochronous sedimentary interfaces are determined as the top interface H1 and the bottom interface H2.

[0021] Further improvements of the application are as follows:

[0022] In the second step, the three-dimensional chronostratigraphic framework is established with the interfaces H1 and H2 as constraints, and the specific operations include:

[0023] On the seismic data, the interfaces H1 and H2 are interpreted and tracked to obtain the three-dimensional chronostratigraphic framework.

[0024] Further improvements of the application are as follows:

[0025] In the third step, the three-dimensional automatic tracking is performed on the internal strata of the three-dimensional chronostratigraphic framework, and the specific operations include:

[0026] For the strata within the bounded area of ​​the top and bottom of the three-dimensional chronostratigraphic framework, a global automatic seismic interpretation method based on an automatic stratigraphic model and a manually modified model is used to automatically track the strata in three dimensions in the study area.

[0027] During three-dimensional automatic tracking, the layer-by-layer slicing technique is used to divide the strata between H1 and H2 into N1, N2, N3...Nm strata interfaces, thereby accurately reflecting the geological characteristics and sedimentary reservoir variation of each inclined stratum and determining the extension direction of the submarine fan sedimentary body, where m is greater than 100.

[0028] Among them, the tracking feature is a peak, a trough, or a zero point. The selection of the tracking feature needs to be based on the well logging data to clarify the post-stack seismic response characteristics of the reservoir, so as to determine whether the final tracking feature is a peak, a trough, a zero point, or any combination thereof.

[0029] A further improvement of the present invention is that:

[0030] The fourth step involves using relevant calculations to obtain the dominant frequency value from the raw earthquake data. Specific operations include:

[0031] By designing different wavelet parameters from the raw seismic data and using correlation calculations to remove the negative correlation between the wavelet and the seismic trace, different dominant frequency values ​​are obtained. The wavelet parameters include frequency, period number, and phase.

[0032] The relevant calculations are as follows: the correlation coefficient between the wavelet and the seismic trace is calculated. The principle is to use the correlation coefficient between the two variables. Its value is equal to the covariance between the wavelet and the seismic trace divided by the standard deviation of the wavelet and the standard deviation of the seismic trace, which is also known as the Pearson correlation coefficient. The value range is -1 to 1. When the correlation coefficient is negative, it is removed and only the positive correlation is retained.

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

[0034] In the fourth step, wavelet frequency division technology is used to divide the main frequency value, resulting in a series of single-band frequency-divided data volumes. Specific operations include:

[0035] The frequency division processing function is constructed using wavelet transform. The mother wavelet of the wavelet transform,

[0036]

[0037] In the formula: t is the time corresponding to the target sampling point; a is the scaling factor, which controls the signal transformation frequency; b is the translation factor, which controls the time position of the signal analysis. The wavelet function is obtained by changing the values ​​of the two.

[0038]

[0039] In the formula: for Fourier transform;

[0040] Based on the convolution formula, the wavelet transform formula for signal f(t) is defined as follows:

[0041]

[0042]

[0043] By applying wavelet frequency division technology, the original seismic data is decomposed and inversely transformed according to the x~y Hz and (yx) / z center frequencies, respectively, to obtain a series of single-band frequency-divided data volumes F1, F2...F (y-x) / z Where x represents the low-frequency end of the seismic data, y represents the high-frequency end of the seismic data, and the spacing is z Hz. The selection of x, y, and z is based on experience.

[0044] A further improvement of the present invention is that:

[0045] In the fifth step, using the 3D automatically tracked and identified strata, stratigraphic slices along the layers are extracted from the frequency division data volume to extract sensitive attribute volumes. Specific operations include:

[0046] First, select the sensitive attribute g, then calculate the amplitude value of this sensitive attribute, which is used as the corresponding attribute volume F. 1g F 2g ...F (y-x) / z g, at this point, the amplitude volume is the selected frequency division data volume F1, F2...F (y-x) / z The extracted sensitive properties show that each amplitude volume reflects or highlights the sedimentary facies in different phases of the seafloor fan;

[0047] F is extracted from the N1, N2, N3...Nm stratigraphic interfaces divided during 3D automatic tracking. 1g F 2g ...F (y-x) / z g Layer attributes of the attribute body.

[0048] A further improvement of the present invention is that:

[0049] The sixth step involves fusing and displaying the results of the frequency division data to depict the boundaries of the submarine fan more clearly. Specific operations include:

[0050] Multiple output attribute bodies F 1g F 2g ...F (y-x) / z The g-shaped display is mixed in a 3D window, ultimately providing a more intuitive view of the different phases of the submarine fan.

[0051] A second aspect of the present invention provides a system for characterizing seafloor fans based on general spectral decomposition and multi-attribute fusion, comprising:

[0052] The interface determination unit is used to combine well logging, geological and raw seismic data of the three-dimensional target reservoir area to determine the target layer and the top interface H1 and bottom interface H2 of the submarine fan development.

[0053] The stratigraphic framework building unit, connected to the interface defining unit, is used to establish a three-dimensional chronostratigraphic framework with interfaces H1 and H2 as constraints.

[0054] The three-dimensional automatic tracking unit is connected to the stratigraphic framework establishment unit and is used to perform three-dimensional automatic tracking of strata within the three-dimensional age stratigraphic framework.

[0055] The frequency division data volume acquisition unit is used to obtain the main frequency value from the original seismic data using relevant calculations, and then to perform frequency division processing on the main frequency value using wavelet frequency division technology to obtain a series of single-band frequency division data volumes.

[0056] The strata slice extraction unit is connected to the three-dimensional automatic tracking unit and the frequency division data volume acquisition unit, respectively. It is used to extract strata slices along the strata with sensitive attribute volumes from the frequency division data volume by using the strata identified by three-dimensional automatic tracking.

[0057] The fusion display unit, connected to the rock strata slice extraction unit, is used to fuse and display the results of the frequency division data volume, depicting the boundaries of the seafloor fan more clearly.

[0058] In a third aspect, the present invention provides a computer-readable storage medium storing at least one computer-executable program, wherein when executed by the computer, the at least one program causes the computer to perform the steps in the above-described method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion.

[0059] Compared with the prior art, the beneficial effects of the present invention are:

[0060] (1) Conventional submarine fan characterization often uses isochronous sections or layer-by-layer slices for seismic attribute extraction. The isochronous slice can select any time value to extract attribute slices and scan the data volume from shallow to deep sequentially. This technique is only suitable for sheet-like and horizontal parallel strata. Although the isochronous strata slice can extract seismic attributes along the layer, the number of layers tracked is limited, and it is impossible to track the target layer sequentially from the top to the bottom. This invention uses the layer-by-layer slice technique to accurately divide the target layer into m isochronous strata, which can scan the data volume sequentially from shallow to deep, and at the same time extract isochronous interface attribute information suitable for submarine fans with strong heterogeneity.

[0061] (2) When there are N1, N2, N3...Nm stratigraphic interfaces, the present invention adopts a combination of automatic tracking and manual intervention, which reduces the workload of interpretation and ensures the accuracy of stratigraphic interface tracking.

[0062] (3) Submarine fans are usually developed in multiple phases and with multiple sand bodies. This invention uses general spectral decomposition to perform frequency division processing on seismic data. Geological targets at different scales have different sensitivities to different frequency components of seismic signals. After frequency division processing, the clarity of geological phenomena displayed by data in different frequency bands is significantly different. Therefore, different spectral amplitude bodies are selected to reflect or highlight different submarine fan sedimentary bodies. Attached Figure Description

[0063] Figure 1 This is a flowchart of the submarine fan characterization method based on general spectral decomposition and multi-attribute fusion in an embodiment of the present invention;

[0064] Figure 2 This is a schematic diagram of the general spectral decomposition technique;

[0065] Figure 3a This is a schematic diagram of isochronous stratigraphic slices;

[0066] Figure 3b This is a schematic diagram of a stratigraphic slice;

[0067] Figure 4 These are the top and bottom interfaces of the submarine fan development in the study area;

[0068] Figure 5 It is a submarine fan characterized by a single seismic attribute based on the original seismic data;

[0069] Figure 6a It is a submarine fan characterized by a single seismic attribute based on the frequency-division data volume F1;

[0070] Figure 6b It is a submarine fan characterized by a single seismic attribute based on the frequency-division data volume F2;

[0071] Figure 6c It is a submarine fan characterized by a single seismic attribute based on the frequency-division data volume F3;

[0072] Figure 7 It utilizes general spectral decomposition and multi-attribute fusion to depict the underwater fan effect. Detailed Implementation

[0073] The present invention will now be described in further detail with reference to the accompanying drawings:

[0074] This invention addresses the delineation of complex submarine fan boundaries and the division of internal phases, with the following objectives:

[0075] 1) To address the issue of low boundary delineation accuracy caused by using a single attribute and method in the process of delineating the boundary of the seafloor fan, the sensitive attributes and sensitive amplitude ranges of sand bodies vary in different regions, requiring the use of different frequency data volumes and multiple attributes for prediction.

[0076] 2) To solve the problem of multiple sand body superposition in the characterization of submarine fans, while fully respecting the original seismic data, the data volume after frequency division processing is used as the carrier to conduct seismic attribute and stratigraphic slice analysis. After giving different main frequency values, the corresponding tuning amplitude is output. Different amplitude volumes highlight and characterize the different stages of submarine fan deposition.

[0077] This invention determines the top interface H1 and bottom interface H2 of the target seafloor fan based on seismic and well logging data, establishes a three-dimensional chronostratigraphic framework constrained by interfaces H1 and H2, and performs three-dimensional automatic tracking on it; obtains the dominant frequency value based on the original seismic data, performs frequency subdivision processing on the dominant frequency value to obtain a series of single-band frequency subdivision data volumes; uses the strata identified by three-dimensional automatic tracking to extract stratigraphic slices along the layers of sensitive attribute volumes from the frequency subdivision data volumes, and finally fuses and displays the results of the frequency subdivision data volumes to depict the boundary of the seafloor fan more clearly.

[0078] This invention improves the accuracy of boundary characterization caused by single attributes and single methods through spectral decomposition and multi-attribute fusion. At the same time, when tracking stratigraphic interfaces, it adopts a combination of automatic tracking and manual intervention, which reduces the workload of interpretation and ensures the accuracy of interface tracking. Ultimately, this invention improves the accuracy of submarine fan prediction and promotes the efficient exploration and development of deep-sea and semi-deep-sea oil and gas reservoirs.

[0079] This invention provides a method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion. An embodiment of the method is as follows:

[0080] Example 1

[0081] like Figure 1 As shown, the method includes:

[0082] The first step is to use well logging, geological and raw seismic data of the three-dimensional target reservoir area to perform well-seismic combination and determine the target strata and the top interface H1 and bottom interface H2 of the submarine fan development;

[0083] The combination of well and seismic analysis, based on information from surrounding drilled wells and sedimentary background, can determine the development period of the submarine fan and identify two isochronous sedimentary interfaces as the top interface H1 and the bottom interface H2.

[0084] The second step is to establish a three-dimensional chronostratigraphic framework using interfaces H1 and H2 as constraints.

[0085] The specific operations include:

[0086] By interpreting and tracing the H1 and H2 interfaces in seismic data, a three-dimensional chronostratigraphic framework can be obtained.

[0087] The third step is to perform automatic three-dimensional tracing of the strata within the three-dimensional chronostratigraphic framework.

[0088] For the strata within the bounded area of ​​the top and bottom of the three-dimensional chronostratigraphic framework, the global automatic seismic interpretation method based on the automatic stratigraphic model and the manually modified model is used to perform three-dimensional automatic tracking of the study area. The tracking features are peaks, troughs or zero points. The selection of tracking features needs to be based on well logging data to clarify the post-stack seismic response characteristics of the reservoir, so as to determine whether the final tracked features are peaks, troughs, zero points or any combination thereof.

[0089] During 3D automatic tracing, a layer-by-layer slicing technique is employed to divide the strata between H1 and H2 into N1, N2, N3...Nm stratigraphic interfaces. This accurately reflects the geological characteristics and sedimentary reservoir variations of each inclined stratum, determining the extension direction of the submarine fan sedimentary body. Here, m is generally greater than 100. Furthermore, during 3D automatic tracing, based on the automatic stratigraphic model tracking, seismic profiles are used to monitor the rationality of the sequence tracing in real time and make timely adjustments, thus combining automatic tracing with manual modification.

[0090] The automated stratigraphic model uses the H1 and H2 interfaces as constraints, tracing all peaks and troughs between H1 and H2 layer by layer. Its tracing mode is described in [link to tracing model]. Figure 2 Right; Manually modifying the model refers to situations where there is unconformity between upper and lower strata, such as over-over, under-over, or top-over phenomena. The automatic tracking interface cannot intelligently identify this contact relationship, so it can be adjusted manually.

[0091] The fourth step is to use relevant calculations to obtain the main frequency value from the original earthquake data, and then use wavelet frequency division technology to divide the main frequency value to obtain a series of single-band frequency division data volumes.

[0092] The main frequency values ​​are obtained from the raw earthquake data through relevant calculations. Specific operations include:

[0093] By designing different wavelet parameters from the raw seismic data and using correlation calculations to remove the negative correlation between the wavelet and the seismic trace, different dominant frequency values ​​are obtained. The wavelet parameters include frequency, period number, and phase.

[0094] The relevant calculations are as follows: the correlation coefficient between the wavelet and the seismic trace is calculated. The principle is to use the correlation coefficient between the two variables. Its value is equal to the covariance between the wavelet and the seismic trace divided by the standard deviation of the wavelet and the standard deviation of the seismic trace, which is also known as the Pearson correlation coefficient. The value range is -1 to 1. When the correlation coefficient is negative, it is removed, and only the positive correlation is retained.

[0095] Wavelet frequency division technology is used to divide the main frequency value to obtain a series of single-band frequency-divided data volumes. The specific operations include:

[0096] The frequency division processing function is constructed using wavelet transform. The mother wavelet of the wavelet transform,

[0097]

[0098] In the formula: t is the time corresponding to the target sampling point; a is the scaling factor, which controls the signal transformation frequency; b is the translation factor, which controls the time position of the signal analysis. The wavelet function is obtained by changing the values ​​of the two.

[0099]

[0100] In the formula: for Fourier transform;

[0101] Based on the convolution formula, the wavelet transform formula for signal f(t) is defined as follows:

[0102]

[0103]

[0104] By applying wavelet frequency division technology, the original seismic data is decomposed and inversely transformed according to the x~y Hz and (yx) / z center frequencies, respectively, to obtain a series of single-band frequency-divided data volumes F1, F2...F (y-x) / z Where x represents the low-frequency end of the seismic data, y represents the high-frequency end of the seismic data, and the spacing is z Hz. The selection of x, y, and z can also be based on experience.

[0105] Step 5: Using the strata identified by three-dimensional automatic tracking, extract stratigraphic slices along the layers of sensitive attribute volumes from the frequency division data volume;

[0106] The specific operations include:

[0107] First, select a sensitive attribute g (such as amplitude, RMS, dessert value, etc.), then calculate the amplitude value of this sensitive attribute (such as maximum amplitude, maximum root mean square amplitude, maximum dessert value, etc.), and use it as the corresponding attribute volume F. 1g F 2g ...F (y-x) / z g, at this point, the amplitude volume is the selected frequency division data volume F1, F2...F (y-x) / z The extracted sensitive attributes (the identified sensitive attribute g) show that each amplitude volume reflects or highlights the sedimentary facies in different phases of the seafloor fan.

[0108] F is extracted from the N1, N2, N3...Nm stratigraphic interfaces divided during 3D automatic tracking. 1g F 2g ...F (y-x) / z g Layer attributes of the attribute body.

[0109] Step 6: Merge and display the results of the frequency division data to depict the boundaries of the submarine fan more clearly;

[0110] The specific operations include:

[0111] Multiple output attribute bodies F 1g F 2g ...F (y-x) / z The g-shaped display is mixed in a 3D window, ultimately providing a more intuitive view of the different phases of the submarine fan.

[0112] Examples of applying the method of the present invention are as follows:

[0113]

Example 2

[0114] Influenced by multiple factors such as different sediment sources, paleogeography, and the timing of hydrodynamic changes, submarine fans in the study area develop in multiple phases within the target strata, exhibiting complex sand body distribution and stacking relationships, and strong lateral heterogeneity of the reservoirs. This geological condition directly leads to the formation of isochronous bodies and lithological transchronous bodies on seismic profiles. Furthermore, due to differences in sand body thickness and cyclic combinations, submarine fans of different phases generate seismic signals with varying frequencies, resulting in differences in their tuning amplitudes. Therefore, characterizing submarine fan boundaries and phases by selecting only seismic bodies of a single frequency and attribute often provides limited insights.

[0115] In the embodiment, a general spectral decomposition method is used ( Figure 2 The original seismic data underwent spectral decomposition, and three amplitude volumes with different frequencies (F1 (10Hz), F2 (20Hz), and F3 (30Hz)) were selected. Multi-attribute fusion technology was used to fuse F1 (10Hz), F2 (20Hz), and F3 (30Hz). Then, the stratigraphic time-section of the fused data volume was analyzed to determine sedimentary body characteristics. Two common methods for creating stratigraphic slices are isochronous stratigraphic slices and stratigraphic slices along bedding planes. Figure 3a and Figure 3b In this embodiment, stratigraphic slices were selected, and the top and bottom interfaces H1 and H2 of the submarine fan development were defined by artificial interpretation. Figure 4 Based on this, software is used to automatically track the internal layers of the submarine fan, combined with manual intervention, to interpret each internal layer. The root mean square amplitude attributes of each layer are extracted from the aforementioned frequency-divided data volume, and then fused and analyzed layer by layer. For example... Figure 5As shown, this result describes a submarine fan based on a single seismic attribute from the original seismic data. The fan boundary is blurred, and the internal sedimentary continuity is poor. Figure 6a , Figure 6b and Figure 6c Comparing the submarine fans characterized by single seismic attributes based on frequency-division data volumes F1 (10Hz), F2 (20Hz), and F3 (30Hz), it can be seen that the fan boundaries are relatively clear, but there are some differences in the internal structure. However, by fusing the results of the frequency-division data volumes, the outline boundaries of the submarine fans are more clearly depicted. Figure 7 ).

[0116] This invention also provides a system for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion, and an embodiment of the system is as follows:

[0117]

Example 3

[0118] The system includes:

[0119] The interface determination unit is used to utilize well logging, geological and raw seismic data of the three-dimensional target reservoir area to perform well-seismic combination and determine the target layer and the top interface H1 and bottom interface H2 of the submarine fan development.

[0120] The stratigraphic framework building unit, connected to the interface defining unit, is used to establish a three-dimensional chronostratigraphic framework with interfaces H1 and H2 as constraints.

[0121] The three-dimensional automatic tracking unit is connected to the stratigraphic framework establishment unit and is used to perform three-dimensional automatic tracking of strata within the three-dimensional age stratigraphic framework.

[0122] The frequency division data volume acquisition unit is used to obtain the main frequency value from the original seismic data using relevant calculations, and then to perform frequency division processing on the main frequency value using wavelet frequency division technology to obtain a series of single-band frequency division data volumes.

[0123] The strata slice extraction unit is connected to the three-dimensional automatic tracking unit and the frequency division data volume acquisition unit, respectively. It is used to extract strata slices along the strata with sensitive attribute volumes from the frequency division data volume by using the strata identified by three-dimensional automatic tracking.

[0124] The fusion display unit, connected to the rock strata slice extraction unit, is used to fuse and display the results of the frequency division data volume, depicting the boundaries of the seafloor fan more clearly.

[0125] The present invention also provides a computer-readable storage medium, embodiments of which are as follows:

[0126]

Example 4

[0127] The computer-readable storage medium stores at least one computer-executable program, which, when executed by the computer, causes the computer to perform the steps in the above-described method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion.

[0128] The above technical solution is only one embodiment of the present invention. For those skilled in the art, based on the principles disclosed in the present invention, it is easy to make various types of improvements or modifications, and not limited to the technical solutions described in the specific embodiments of the present invention. Therefore, the foregoing description is only a preferred option and is not restrictive.

Claims

1. A method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion, characterized in that, Includes the following steps: The first step is to use well logging, geological and raw seismic data of the three-dimensional target reservoir area to perform well-seismic combination and determine the target strata and the top interface H1 and bottom interface H2 of the submarine fan development; The second step is to establish a three-dimensional chronostratigraphic framework using interfaces H1 and H2 as constraints. The third step is to perform automatic three-dimensional tracing of the strata within the three-dimensional chronostratigraphic framework. The fourth step is to use relevant calculations to obtain the main frequency value from the original earthquake data, and then use wavelet frequency division technology to divide the main frequency value to obtain a series of single-band frequency division data volumes. Step 5: Using the strata identified by three-dimensional automatic tracking, extract stratigraphic slices along the layers of sensitive attribute volumes from the frequency division data volume; Step 6: Combine and display the results of the frequency division data to delineate the boundaries of the seafloor fan.

2. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 1, characterized in that, The first step of the well-seismic integration is as follows: Based on information from surrounding drilled wells and sedimentary background, the development period of the submarine fan was determined, and two isochronous sedimentary interfaces were identified as the top interface H1 and the bottom interface H2.

3. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 2, characterized in that, The second step involves establishing a three-dimensional chronostratigraphic framework using interfaces H1 and H2 as constraints. Specific operations include: In seismic data, the H1 and H2 interfaces are interpreted and traced to obtain a three-dimensional chronostratigraphic framework.

4. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 3, characterized in that, The third step involves automatic three-dimensional tracing of the strata within the three-dimensional chronostratigraphic framework. Specific operations include: For the strata within the bounded area of ​​the top and bottom of the three-dimensional chronostratigraphic framework, a global automatic seismic interpretation method based on an automatic stratigraphic model and a manually modified model is used to automatically track the strata in three dimensions in the study area. During three-dimensional automatic tracking, the layer-by-layer slicing technique is used to divide the strata between H1 and H2 into N1, N2, N3...Nm strata interfaces, thereby accurately reflecting the geological characteristics and sedimentary reservoir variation of each inclined stratum and determining the extension direction of the submarine fan sedimentary body, where m is greater than 100. Among them, the tracking feature is a peak, a trough, or a zero point. The selection of the tracking feature needs to be based on the well logging data to clarify the post-stack seismic response characteristics of the reservoir, so as to determine whether the final tracking feature is a peak, a trough, a zero point, or any combination thereof.

5. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 4, characterized in that, The fourth step involves using relevant calculations to obtain the dominant frequency value from the raw earthquake data. Specific operations include: By designing different wavelet parameters from the raw seismic data and using correlation calculations to remove the negative correlation between the wavelet and the seismic trace, different dominant frequency values ​​are obtained. The wavelet parameters include frequency, period number, and phase. The relevant calculations are as follows: the correlation coefficient between the wavelet and the seismic trace is calculated. The principle is to use the correlation coefficient between the two variables. Its value is equal to the covariance between the wavelet and the seismic trace divided by the standard deviation of the wavelet and the standard deviation of the seismic trace, which is also known as the Pearson correlation coefficient. The value range is -1 to 1. When the correlation coefficient is negative, it is removed and only the positive correlation is retained.

6. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 5, characterized in that, In the fourth step, wavelet frequency division technology is used to divide the main frequency value, resulting in a series of single-band frequency-divided data volumes. Specific operations include: The frequency division processing function is constructed using wavelet transform. The mother wavelet of the wavelet transform, In the formula: t is the time corresponding to the target sampling point; a is the scaling factor, which controls the signal transformation frequency; b is the translation factor, which controls the time position of the signal analysis. The wavelet function is obtained by changing the values ​​of the two. In the formula: for Fourier transform; Based on the convolution formula, the wavelet transform formula for signal f(t) is defined as follows: By applying wavelet frequency division technology, the original seismic data is decomposed and inversely transformed according to the x~y Hz and (yx) / z center frequencies, respectively, to obtain a series of single-band frequency-divided data volumes F1, F2...F (y-x) / z Where x represents the low-frequency end of the seismic data, y represents the high-frequency end of the seismic data, and the spacing is z Hz. The selection of x, y, and z is based on experience.

7. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 6, characterized in that, In the fifth step, using the 3D automatically tracked and identified strata, stratigraphic slices along the layers are extracted from the frequency division data volume to extract sensitive attribute volumes. Specific operations include: First, select the sensitive attribute g, then calculate the amplitude value of this sensitive attribute, which is used as the corresponding attribute volume F. 1g F 2g ...F (y-x) / z g, at this point, the amplitude volume is the selected frequency division data volume F1, F2...F (y-x) / z The extracted sensitive properties show that each amplitude volume reflects or highlights the sedimentary facies in different phases of the seafloor fan; F is extracted from the N1, N2, N3...Nm stratigraphic interfaces divided during 3D automatic tracking. 1g F 2g ...F (y-x) / zg Layer attributes of the attribute body.

8. The method for characterizing submarine fans based on general spectral decomposition and multi-attribute fusion according to claim 7, characterized in that, The sixth step involves fusing and displaying the results of the frequency division data to depict the boundaries of the submarine fan more clearly. Specific operations include: Multiple output attribute bodies F 1g F 2g ...F (y-x) / z The g-shaped display is mixed in a 3D window, ultimately providing a more intuitive view of the different phases of the submarine fan.

9. A system for characterizing submarine fans based on universal spectral decomposition and multi-attribute fusion, characterized in that, include: The interface determination unit is used to combine well logging, geological and raw seismic data of the three-dimensional target reservoir area to determine the target layer and the top interface H1 and bottom interface H2 of the submarine fan development. The stratigraphic framework building unit, connected to the interface defining unit, is used to establish a three-dimensional chronostratigraphic framework with interfaces H1 and H2 as constraints. The three-dimensional automatic tracking unit is connected to the stratigraphic framework establishment unit and is used to perform three-dimensional automatic tracking of strata within the three-dimensional age stratigraphic framework. The frequency division data volume acquisition unit is used to obtain the main frequency value from the original seismic data using relevant calculations, and then to perform frequency division processing on the main frequency value using wavelet frequency division technology to obtain a series of single-band frequency division data volumes. The strata slice extraction unit is connected to the three-dimensional automatic tracking unit and the frequency division data volume acquisition unit, respectively. It is used to extract strata slices along the strata with sensitive attribute volumes from the frequency division data volume by using the strata identified by three-dimensional automatic tracking. The fusion display unit, connected to the rock strata slice extraction unit, is used to fuse and display the results of the frequency division data volume, depicting the boundaries of the seafloor fan more clearly.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer-executable program, which, when executed by the computer, causes the computer to perform the steps in the submarine fan characterization method based on general spectral decomposition and multi-attribute fusion as described in any one of claims 1-8.

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