Carbonate abutment edge structure depiction and abutment edge reef body distribution prediction method

Abstract

The invention relates to the field of reservoir prediction of petroleum and natural gas geological exploration and development, in particular to a carbonate rock abutment edge structure depiction and abutment edge reef body distribution prediction method, which comprises the following steps: S1, acquiring seismic data of a target area, and preprocessing the seismic data to obtain first seismic data; s2, calculating and processing the first seismic data according to a seismic attribute algorithm to obtain seismic information and a seismic imaging result; s3, performing seismic horizon interpretation on the seismic section based on the seismic information and the seismic imaging result to obtain seismic horizon data; s4, analyzing seismic horizon data through geological software, and depicting a carbonate rock bench edge structure; according to the carbonate abutment edge structure, prediction of abutment edge reef body distribution is achieved. The platform edge structure can be accurately analyzed, and the trap formed by the platform edge reef type reservoir and the distribution range and scale of the oil and gas reservoir can be effectively predicted in real time.

Description

Technical Field

[0001] The present invention relates to the field of reservoir prediction in oil and gas geological exploration and development, and particularly to a method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies. Background Art

[0002] The platform margin bioherm reef flat reservoir is a sedimentary environment with important oil and gas resource potential and has attracted much attention in recent years. Considerable progress has been made in the research on the platform margin bioherm reef flat reservoir in China.

[0003] Research results show that the reservoirs of platform margin bioherm reef flats usually have good physical properties and permeability, and the internal pore types and structures are relatively complex, including framework pores, bioclastic pores, and cement pores, etc. In addition, researchers have developed a series of reservoir description and prediction methods, providing important technical support for the exploration and development of oil and gas resources. At present, seismic interpretation is an important means in geological research. By the propagation and reflection of seismic waves, detailed information on underground geological structures can be obtained.

[0004] However, for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies, traditional seismic interpretation methods often cannot obtain sufficient details and accuracy. Therefore, a method based on fine seismic interpretation is needed to achieve the precise depiction of the carbonate platform margin structure and the reliable prediction of the distribution of platform margin reef flat bodies. Summary of the Invention

[0005] The present invention solves the problems of low efficiency and accuracy in depicting and predicting the platform margin by existing prediction methods, and high exploration and development costs, and provides a method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies, so as to achieve the precise depiction of the carbonate platform margin structure and the reliable prediction of the distribution of platform margin reef flat bodies.

[0006] The technical solution claimed by the present invention is as follows:

[0007] A method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies, comprising the following steps:

[0008] S1: Obtain seismic data of the target area, exclude seismic data of non-target areas, and then preprocess the seismic data to remove invalid and redundant seismic data, obtaining first seismic data; the seismic data includes waveform data, amplitude data, and phase data of seismic waves;

[0009] S2: Use seismic attribute algorithms to calculate the first seismic data obtained in S1 to obtain seismic information; perform prestack depth migration processing on the first seismic data obtained in S1 to obtain a seismic imaging result; the seismic information includes formation information, lithological characteristic information, and geological structure information; the seismic imaging result is a three-dimensional image of the subsurface geological structure.

[0010] S3: Based on the seismic information and seismic imaging result obtained in S2, perform seismic horizon interpretation on the seismic profile to obtain seismic horizon data.

[0011] S4: Use geological software to analyze the seismic horizon data obtained in S3 to depict the carbonate platform margin structure; based on the carbonate platform margin structure, predict the distribution of platform margin reef bank bodies.

[0012] Preferably, the preprocessing in S1 includes: successively performing data compression, interpolation, and extrapolation processing on the seismic data to remove invalid seismic data, removing noise through filtering techniques, reducing high-frequency noise through smoothing techniques, and performing correction operations; the correction includes time correction, phase correction, and amplitude correction.

[0013] Preferably, S2 includes:

[0014] S21: Use seismic attribute algorithms to calculate the first seismic data to obtain seismic information in the target area location; the seismic attribute algorithm is an algorithm that obtains special metric values from the waveform data, amplitude data, and phase data of seismic waves; the seismic information is in complex form and can describe the wavelength, amplitude, and phase characteristics of seismic waves.

[0015] S22: According to the pre-established geological model and the positions of shot points and receiving points of the seismic data, calculate the propagation path and offset of each seismic wave in the first seismic data through ray tracing method to obtain ray tracing results; based on the ray tracing results, perform depth migration processing on each seismic wave, and relocate each seismic wave to the actual formation depth position to obtain depth migration data; perform filtering and imaging processing on the depth migration data to obtain a seismic imaging result; the ray tracing method is a simulation method based on physical principles.

[0016] Preferably, the pre-established geological model is a model established according to the target area, including the distribution and velocity distribution of underground rock layers, and calculating the propagation path and offset of seismic waves according to the distribution and velocity distribution of underground rock layers.

[0017] The calculation formula of the seismic attribute algorithm is as follows:

[0018] X(f) = ∫x(t)e^(-2πift)dt (1);

[0019] x(t) = xr(t) + xi(t) (2);

[0020] Wherein, X(f) is the frequency-domain signal; f is the frequency; -2πi is the complex exponential function with an angular frequency of -2π, the imaginary part is -2π, and the real part is 0; i is the imaginary unit; d is the symbol in the integral function without actual meaning; x(t) represents the time-domain signal; t represents time; xr(t) represents the real part, including the amplitude data of seismic waves; xi(t) represents the imaginary part, including the phase data of seismic waves.

[0021] Preferably, the S3 includes the following steps:

[0022] S31: On the seismic section, analyze the seismic data through seismic attribute analysis technology to determine the distribution and characteristics of seismic horizons and different seismic horizons;

[0023] S32: According to the seismic horizons determined in S31, formulate a tracing and interpretation plan using the seismic information and seismic imaging results, and conduct tracing and interpretation on the seismic horizons. The seismic horizons are calibrated and verified to obtain seismic horizon data.

[0024] Preferably, the characterization of the carbonate platform margin structure in S4 includes the following steps:

[0025] S41: Obtain the seismic horizon data, perform three-dimensional visualization processing on the seismic horizon data using geological software to clarify the development characteristics of the seismic horizons, and determine the platform type; compile the residual thickness map of each layer group and reconstruct the paleogeomorphology; based on the reconstructed paleogeomorphology, identify the sedimentation pattern and sedimentation center of gravity to determine the specific location of the platform margin development;

[0026] S42: Conduct a detailed dissection of the platform margin whose specific development location is determined in S41 according to the seismic horizon data, establish the development models of different platform margin zones in different periods, analyze the development stages and superimposed styles of reef-bank bodies, and identify the development stages of the platform margin structure; determine the planar distribution characteristics of the platform margin and the development stages and scales of reef-bank bodies inside it, delimit the favorable reef-bank development zones of the platform margin, and characterize the carbonate platform margin structure according to the location and characteristics of the platform margin development.

[0027] Preferably, the prediction of the distribution of platform margin reef-bank bodies in S4 according to the carbonate platform margin structure includes: according to the carbonate platform margin structure, analyze the relationship between the platform margin reef-bank bodies and the platform to obtain the genetic origin, evolution law, formation and evolution of the platform, and the formation and distribution law of oil and gas resources, and realize the prediction of the distribution of platform margin reef-bank bodies.

[0028] Preferably, the method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies further includes: after predicting the platform margin reef flat bodies, updating seismic data in real time and continuously optimizing the interpretation method, and updating and optimizing the prediction results in real time.

[0029] A computer device includes a memory and a processor. When the processor executes a computer program stored in the memory, it executes the method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies.

[0030] Beneficial effects:

[0031] The present invention provides a method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies. First, seismic data of a target area is obtained, and the obtained seismic data is preprocessed to remove a large amount of invalid and redundant seismic data, resulting in first seismic data. Compared with the prior art, it can greatly increase the amount of seismic data processing and analysis, shorten the exploration cycle, and reduce the exploration cost; the first seismic data is respectively calculated using a seismic attribute algorithm and subjected to prestack depth migration processing to obtain seismic information and a seismic imaging result. The seismic information includes formation information, lithological characteristic information, and geological structure information; the seismic imaging result is a three-dimensional image of the underground geological structure; specific characteristic information inside the formation is obtained by using the seismic attribute algorithm, and the prestack depth migration processing is used to perform noise reduction processing on the first seismic data to make the obtained three-dimensional image of the underground geological structure more accurate. Then, based on the seismic information and the seismic imaging result, seismic horizon interpretation is performed on the seismic profile to obtain seismic horizon data, further proving the accuracy of the seismic information and the three-dimensional image of the geological structure; through geological software, the seismic horizon data is analyzed to achieve the depiction of the carbonate platform margin structure and the prediction of the distribution of platform margin reef flat bodies, achieving the technical effects of accurately depicting the carbonate platform margin structure and quickly and accurately predicting the distribution of platform margin reef flat bodies, and solving the problem of low efficiency and accuracy of the existing prediction methods for depicting and predicting the platform margin. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies provided by the present invention is accurate, reduces unnecessary exploration and development, greatly reduces the exploration and development costs, and solves the problem of high exploration and development costs caused by low efficiency and accuracy of the existing prediction methods for depicting and predicting the platform margin. Description of the Drawings

[0032] Figure 1 It is a flowchart of the method of the present invention. Detailed Embodiments

[0033] The present invention will be further elaborated in detail below with reference to the drawings. It should be understood that the present invention is not limited to the following technical solutions.

[0034] The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies proposed in the embodiment of the present invention processes the received seismic data to obtain seismic information and seismic imaging results, obtains seismic horizon data based on the seismic information and seismic imaging results, and analyzes the seismic horizon data through geological software; realizes the depiction of the carbonate platform margin structure and the prediction of the distribution of platform margin reef flat bodies, and realizes the accurate depiction of the carbonate platform margin structure and the rapid and accurate prediction of the distribution of platform margin reef flat bodies.

[0035] This embodiment also provides a computer device, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program stored in the memory, it executes the method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies proposed in the embodiment of the present invention.

[0036] The first group of embodiments, Embodiment 1 of the method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies

[0037] This embodiment provides a method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies. It preprocesses the acquired seismic data to obtain the first seismic data; performs calculation and prestack depth migration processing on the first seismic data respectively to obtain seismic information and seismic imaging results, obtains seismic horizon data based on the seismic information and seismic imaging results, and analyzes the seismic horizon data through geological software to realize the depiction of the carbonate platform margin structure and the prediction of the distribution of platform margin reef flat bodies, thereby realizing the accurate depiction of the carbonate platform margin structure and the rapid and accurate prediction of the distribution of platform margin reef flat bodies. As Figure 1 shown, the method of this embodiment includes the following steps:

[0038] S1: Obtain the seismic data of the target area, preprocess the acquired seismic data, remove the invalid and redundant seismic data, and obtain the first seismic data; the seismic data includes waveform data, amplitude data, and phase data of seismic waves.

[0039] In a specific embodiment of the present invention, the target area is the position and scope where the carbonate platform margin structure needs to be depicted and the distribution of platform margin reef flat bodies needs to be predicted; the acquired seismic data is successively processed by data compression, interpolation, and extrapolation to remove invalid seismic data, noise is removed through filtering technology, high-frequency noise is reduced through smoothing technology, and correction operations are performed; the correction includes time correction, phase correction, and amplitude correction; the first seismic data is the seismic data after preprocessing.

[0040] S2: Calculate the first seismic data obtained in S1 using a seismic attribute algorithm to obtain seismic information; perform prestack depth migration processing on the first seismic data obtained in S1 to obtain a seismic imaging result; the seismic information includes formation information, lithological characteristic information, and geological structure information; the seismic imaging result is a three-dimensional image of the underground geological structure.

[0041] In a specific embodiment of the present invention, the seismic attribute algorithm is an algorithm for obtaining special metric values from the waveform data, amplitude data, and phase data of seismic waves; the prestack depth migration processing is to perform migration on each common offset section in the depth domain to obtain a seismic imaging result; the seismic imaging result is an image obtained after processing, and the image is a three-dimensional image of the underground geological structure.

[0042] S3: Perform seismic horizon interpretation on the seismic profile based on the seismic information and seismic imaging result obtained in S2 to obtain seismic horizon data.

[0043] In a specific embodiment of the present invention, the seismic horizon interpretation is a process of interpreting the seismic structure of the target area; the seismic horizon data is used for planar analysis to infer the sedimentary environment and lithofacies after tracing and interpreting each seismic horizon.

[0044] S4: Analyze the seismic horizon data obtained in S3 through geological software to depict the carbonate platform margin structure; predict the distribution of platform margin reef bank bodies based on the carbonate platform margin structure.

[0045] In a specific embodiment of the present invention, the carbonate platform margin structure is a special geological structure and geomorphic form at the edge of the carbonate platform; the platform margin reef bank body is a special geomorphic form with high biological abundance and reserves.

[0046] This embodiment accurately analyzes the platform margin structure and real-time and effectively predicts the traps formed by the platform margin reef bank type reservoirs and the distribution range and scale of oil and gas reservoirs.

[0047] Embodiment 2

[0048] This embodiment provides a method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef bank bodies, as Figure 1 shown, including the following steps:

[0049] S1: Obtain the seismic data of the target area, preprocess the obtained seismic data, and remove invalid and redundant seismic data to obtain the first seismic data; the seismic data includes the waveform data, amplitude data, and phase data of seismic waves.

[0050] Specifically, seismic data from seismic monitoring stations set in the target area are received, and the acquired seismic data is preprocessed. The preprocessing refers to sequentially performing data compression, interpolation, and extrapolation on the acquired seismic data to remove invalid seismic data, removing noise through filtering techniques, reducing high-frequency noise through smoothing techniques, and performing correction operations; the correction includes time correction, phase correction, and amplitude correction; the first seismic data is the seismic data after preprocessing.

[0051] In a specific embodiment of the present invention, a seismic monitoring station is set in the target area for depicting the carbonate rock edge structure and predicting the distribution of platform margin reef banks. The station uses an advanced seismic recorder to collect data. The seismic data includes waveform data, amplitude data, and phase data of seismic waves.

[0052] In other embodiments of the present invention, seismic data is screened manually or automatically to remove invalid or low-quality data, such as abnormal data caused by equipment failures or environmental interferences. Filtering techniques are used to remove noise in the seismic data, such as environmental noise and instrument noise; the filtering techniques include frequency-domain filtering and time-domain filtering. Smoothing techniques are used to remove high-frequency noise in the seismic data, and then waveform correction, amplitude correction, and phase correction are performed on the seismic data; after the seismic waves are preprocessed, the first seismic data is obtained.

[0053] S2: The first seismic data obtained in S1 is calculated using a seismic attribute algorithm to obtain seismic information; the first seismic data obtained in S1 is subjected to prestack depth migration processing to obtain a seismic imaging result; the seismic information includes formation information, lithological characteristic information, and geological structure information; the seismic imaging result is a three-dimensional image of the underground geological structure; including:

[0054] S21: The seismic information in the target area position is calculated from the first seismic data using a seismic attribute algorithm; the seismic attribute algorithm is an algorithm for obtaining special metric values from the waveform data, amplitude data, and phase data of seismic waves; the seismic information is in complex form and can describe the wavelength, amplitude, and phase characteristics of seismic waves.

[0055] S22: According to the pre-established geological model and the positions of the shot points and receiving points of the seismic data, the propagation path and the offset amount of each seismic wave reaching the receiving point in the first seismic data are calculated by the ray tracing method to obtain a ray tracing result; based on the ray tracing result, depth migration processing is performed on each seismic wave to relocate each seismic wave to the actual formation depth position to obtain depth migration data; the depth migration data is filtered and imaged to obtain a seismic imaging result.

[0056] Specifically, the pre-established geological model is a model established according to the target area, including the distribution of underground rock formations and velocity distribution, and calculating the propagation path and offset of seismic waves based on the distribution of underground rock formations and velocity distribution.

[0057] Specifically, the ray tracing method is a simulation method based on physical principles.

[0058] The formation information, lithological characteristic information, and geological structure information in the target area position are obtained through calculation by the seismic attribute algorithm. The calculation formula is as follows:

[0059] X(f) = ∫x(t)e^(-2πift)dt (1);

[0060] x(t) = xr(t) + xi(t) (2);

[0061] Among them, X(f) is the frequency-domain signal; f is the frequency; -2πi is the complex exponential function with an angular frequency of -2π, the imaginary part is -2π, and the real part is 0; i is the imaginary unit; x(t) represents the time-domain signal; t represents time; xr(t) represents the real part, including the amplitude data of seismic waves; xi(t) represents the imaginary part, including the phase data of seismic waves; ∫f(x)dx is an integral function, and the formula represents the integral of the function x(t)e^(-2πift) with respect to the variable t. d is a symbol in the integral function and has no actual meaning.

[0062] In specific implementation, the amplitude spectrum and phase spectrum are selected as seismic attributes for calculation; the amplitude spectrum is used to reflect the change of the amplitude of seismic waves, and the phase spectrum is used to reflect the change of the phase of seismic waves.

[0063] After processing the amplitude data and phase data, the amplitude spectrum and phase spectrum are extracted; after performing Fourier transform on the processed amplitude data and phase data, the amplitude spectrum and phase spectrum are obtained; in the complex domain, the amplitude spectrum represents the modulus length of the complex number, and the phase spectrum represents the angle of the complex number.

[0064] By analyzing the amplitude spectrum and phase spectrum, the underground geological structure and lithological characteristic information are obtained. For example, the strong and weak changes in the amplitude spectrum may indicate the change in formation thickness or the difference in lithological composition, and the change in the phase spectrum may indicate the type and characteristics of the geological structure.

[0065] According to the objectives and regions of geological exploration, a pre-established geological model is established. The geological model includes information on the distribution of underground rock formations and velocity distribution. According to the needs of actual seismic exploration, the positions of shot points and receiving points are determined, and the above positions are set according to the geological model and actual exploration requirements. Using the linear tracing method, based on the geological model and the positions of shot points and receiving points, the propagation path of each seismic wave and the offset amount reaching the receiving point are calculated. Through ray tracing calculation, the propagation path of each seismic wave and the offset amount reaching the receiving point are obtained. Based on the ray tracing structure, depth migration processing is performed on the seismic waves to obtain depth migration data, which is used for further image processing and geological analysis.

[0066] Taking the depth migration data as the initial condition, the propagation situation of seismic waves in the underground rock formations is obtained through back-projection calculation, and filtering processing is performed on it to obtain the filtered data. Among them, during the filtering processing, a filtering method based on the wave equation is used to solve the wave equation. Different filter parameters are used to control the filtering effect.

[0067] Image processing is performed on the data after filtering processing based on the back-projection method. The propagation situation of seismic waves in the underground rock formations is obtained through back-projection calculation. During this process, different back-projection parameters can be used to control the imaging effect. The back-projection is a way to record how the pixel points in a given image adapt to the pixel distribution of the histogram model.

[0068] S3: Based on the seismic information and seismic imaging results obtained in S2, seismic horizon interpretation is performed on the seismic section to obtain seismic horizon data. The steps include:

[0069] S31: On the seismic section, the seismic data is analyzed through seismic attribute analysis technology to determine the distribution and characteristics of seismic horizons and different seismic horizons.

[0070] S32: According to the seismic horizons determined in S31, a tracing and interpretation scheme is formulated using the seismic information and seismic imaging results, and the seismic horizons are traced and interpreted. After calibration and verification, seismic horizon data is obtained.

[0071] In a specific embodiment of the present invention, seismic information and seismic imaging structures obtained from seismic exploration are collected, and the first seismic data is analyzed using seismic data analysis technology to determine the distribution and characteristics of seismic horizons. The analyzed content includes: the strength changes of different horizons on the seismic section, as well as the angular relationship and structural form between strata.

[0072] Based on the identified seismic horizons above, select appropriate seed points for tracing, formulate a tracing and interpretation plan using the seismic information and seismic imaging results, and determine the formation and lithological characteristics to be traced. Among them, determine the tracing direction and scope according to the continuity and morphological characteristics of the formation, and determine the interpretation rules for tracing according to the geological structure information in the seismic imaging results.

[0073] According to the specified tracing and interpretation plan, use professional seismic interpretation software to carry out tracing and interpretation, gradually iterate and adjust to obtain a complete set of seismic horizon data; after obtaining the seismic horizon data, compare and analyze the seismic horizon data with the known geological data to evaluate the accuracy and precision of the data; conduct further geological analysis and interpretation of the seismic horizon data to evaluate the reliability and compliance of the data; if errors or problems are found in the data, the data can be corrected and adjusted. Common seismic attribute analysis techniques include seismic wave propagation simulation technology and seismic monitoring technology.

[0074] The seismic horizon data is a kind of seismic horizon information reflecting the underground geological structure, which can be used to determine information such as formation distribution, lithological characteristics, and geological history.

[0075] S4: Analyze the seismic horizon data obtained in S3 through geological software to depict the carbonate platform margin structure; based on the carbonate platform margin structure, realize the prediction of the distribution of platform margin reef-flat bodies; including the following steps:

[0076] S41: Obtain the seismic horizon data, perform three-dimensional visualization processing on the seismic horizon data using geological software to clarify the development characteristics of the seismic horizons, and determine the platform type; compile the residual thickness map of each layer group and reconstruct the paleogeomorphology; based on the reconstructed paleogeomorphology, identify the sedimentation pattern and sedimentation center of gravity to determine the specific location of platform margin development;

[0077] S42: Conduct a detailed dissection of the platform margin whose specific development location has been determined in S41 according to the seismic horizon data, establish the development models of different platform margin zones in different periods, analyze the development stages and superimposed styles of reef-flat bodies, and identify the development stages of the platform margin structure; determine the planar distribution characteristics of the platform margin and the development stages and scales of reef-flat bodies inside it, delimit the favorable reef-flat development zones of the platform margin, and depict the carbonate platform margin structure according to the location and characteristics of platform margin development.

[0078] For example, import the seismic horizon data into geological software, perform three-dimensional visualization processing to obtain the three-dimensional visualization processing structure, and analyze the development characteristics of the seismic horizons, such as the sequence of earthquakes, contact relationships, and formation attitudes; combine the known geological data and literature to determine the type of platform.

[0079] According to the processing results of seismic horizon data, draw the formation frame lines. On the drawn formation frame lines, use the measurement tool in the geological software to measure the remaining thickness of each formation group. Organize the measured remaining thickness data of each formation group into a table or chart form, compile the remaining thickness map of each formation group, and analyze and interpret the remaining thickness of each formation group.

[0080] Utilize the paleogeomorphology construction function in the geological software. Based on the processing results of seismic horizon data and relevant geological data, reconstruct the paleogeomorphology and analyze the formation and evolution process of the platform in the target area. Based on the reconstructed paleogeomorphology, identify the sedimentation pattern and sedimentation center of gravity according to geological data and literature. By analyzing the distribution of the sedimentation pattern and sedimentation center of gravity, combined with geological data and literature, determine the high-incidence areas of platform margin development. Use the image processing function in the geological software to display the specific location and morphology of platform margin development in three-dimensional space. The geological data and literature are stored in the geological software.

[0081] According to the processing results of seismic horizon data, establish the development models of different platform margins in different periods. Analyze the development stages and superimposed styles of reef-flat bodies to obtain the development stages of the platform margin structure, delimit the favorable reef-flat development zones of the platform margin, and verify and correct them by comparing the characteristics of the known favorable reef-flat development zones with the analysis results.

[0082] According to the delimited favorable reef-flat development zones of the platform margin, determine the positions and characteristics of the favorable reef-flat development zones. Through drawing three-dimensional model diagrams in the geological software, display the morphology and characteristics of the carbonate platform edge structure.

[0083] The geological software is Landmark or GeoFrame.

[0084] According to the carbonate platform edge structure described above, analyze the relationship between the platform margin reef-flat bodies and the platform, obtain the genesis, evolution law, formation and evolution of the platform, and the formation and distribution law of oil and gas resources, so as to realize the prediction of the distribution of platform margin reef-flat bodies. For example, after analyzing the relationship between the platform margin reef-flat bodies and the platform, use the prediction function in the geological software to show the predicted distribution of the platform margin reef-flat bodies by drawing contour lines or making the peaks of histograms, so as to realize the prediction of the distribution of platform margin reef-flat bodies.

[0085] In the specific embodiment of the present invention, the method for depicting the carbonate platform edge structure and predicting the distribution of platform margin reef-flat bodies further includes: after predicting the platform margin reef-flat bodies, update the seismic data in real time and continuously optimize the interpretation method, and update and optimize the prediction results in real time. For example, after obtaining new seismic data, update the seismic database storing the seismic data in real time, process and analyze the seismic data, continuously optimize the interpretation method and update and optimize the prediction and other steps to obtain more accurate prediction results.

[0086] This embodiment accurately analyzes the platform margin structure and predicts in real time and effectively the traps formed by the platform margin reef flat reservoirs and the distribution range and scale of the oil and gas reservoirs.

[0087] The second group of embodiments: A computer device

[0088] This embodiment also provides a computer device, including a memory and a processor. When the processor executes the computer program stored in the memory, it executes the method of any of the above first group of embodiments.

[0089] This embodiment integrates and uniformly analyzes various data, greatly enriches the sample set required for training, effectively improves the accuracy of classification, and also improves the processing speed and the accuracy of the algorithm, which has substantial significance for the subsequent research on the description of the carbonate platform margin structure and the prediction method of the distribution of platform margin reef flat bodies.

[0090] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for depicting the structure of carbonate platform margin and predicting the distribution of reef flat bodies on the platform margin, characterized in that, It includes the following steps: S1: Obtain seismic data of the target area, preprocess the obtained seismic data, remove invalid and redundant seismic data to obtain first seismic data; the seismic data includes waveform data, amplitude data, and phase data of seismic waves; S2: Use a seismic attribute algorithm to calculate the first seismic data obtained in S1 to obtain seismic information; perform prestack depth migration processing on the first seismic data obtained in S1 to obtain a seismic imaging result; the seismic information includes formation information, lithological characteristic information, and geological structure information; the seismic imaging result is a three-dimensional image of the underground geological structure; S3: Based on the seismic information and seismic imaging result obtained in S2, perform seismic horizon interpretation on the seismic profile to obtain seismic horizon data; S4: Analyze the seismic horizon data obtained in S3 through geological software to depict the carbonate platform margin structure; based on the carbonate platform margin structure, predict the distribution of platform margin reef banks.

2. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 1, characterized in that, The preprocessing in S1 includes: sequentially performing data compression, interpolation, and extrapolation processing on the seismic data to remove invalid seismic data, removing noise through filtering technology, reducing high-frequency noise through smoothing technology, and performing correction operations; the correction includes time correction, phase correction, and amplitude correction.

3. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 1, wherein S2 It includes: S21: Use a seismic attribute algorithm to calculate the first seismic data to obtain seismic information at the target area position; the seismic attribute algorithm is an algorithm that obtains special measurement values from waveform data, amplitude data, and phase data of seismic waves; the seismic information is in complex number form and can describe the wavelength, amplitude, and phase characteristics of seismic waves; S22: According to the pre-established geological model and the positions of shot points and receiving points of seismic data, calculate the propagation path and offset of each seismic wave in the first seismic data through ray tracing method to obtain a ray tracing result; based on the ray tracing result, perform depth migration processing on each seismic wave, relocate each seismic wave to the actual formation depth position to obtain depth migration data; perform filtering and imaging processing on the depth migration data to obtain a seismic imaging result; the ray tracing method is a simulation method based on physical principles.

4. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 3, characterized in that The pre-established geological model is a model established according to the target area, including the distribution and velocity distribution of underground rock layers, and calculating the propagation path and offset of seismic waves according to the distribution and velocity distribution of underground rock layers.

5. The method for carbonate platform margin structure characterization and platform margin reef flat body distribution prediction according to claim 3, wherein The calculation formula of the seismic attribute algorithm is as follows: X(f) = ∫x(t)e^(-2πift)dt (1); x(t) = xr(t) + xi(t) (2); Where, X(f) is the frequency domain signal; f is the frequency; -2πi is the complex exponential function with an angular frequency of -2π, the imaginary part is -2π, and the real part is 0; i is the imaginary unit; d is the symbol in the integral function and has no actual meaning; x(t) represents the time domain signal; t represents time; xr(t) represents the real part, including the amplitude data of seismic waves; xi(t) represents the imaginary part, including the phase data of seismic waves.

6. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 3, characterized in that, The S3 includes the following steps: S31: On the seismic profile, analyze the seismic data through seismic attribute analysis techniques to determine the distribution and characteristics of seismic horizons and different seismic horizons; S32: According to the seismic horizons determined in S31, formulate a tracing and interpretation plan using the seismic information and seismic imaging results, and perform tracing and interpretation on the seismic horizons. The seismic horizons are calibrated and verified to obtain seismic horizon data.

7. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 1, characterized in that, The characterization of the carbonate platform margin structure in S4 includes the following steps: S41: Obtain the seismic horizon data, perform three-dimensional visualization processing on the seismic horizon data using geological software, clarify the development characteristics of the seismic horizons, and determine the platform type; compile the residual thickness map of each formation group and reconstruct the paleogeomorphology; based on the reconstructed paleogeomorphology, identify the sedimentation pattern and sedimentation center of gravity to determine the specific location where the platform margin develops; S42: According to the seismic horizon data, conduct a detailed dissection of the platform margin whose specific development location is determined in S41, establish the development models of different platform margin zones in different periods, analyze the development stages and superimposed styles of reef-flat bodies, and identify the development stages of the platform margin structure; determine the planar distribution characteristics of the platform margin and the development stages and scales of reef-flat bodies within it, delimit the favorable reef-flat development zones of the platform margin, and characterize the carbonate platform margin structure according to the location and characteristics of the platform margin development.

8. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 1, wherein In S4, based on the carbonate platform margin structure, the prediction of the distribution of platform margin reef-flat bodies is realized, including: according to the carbonate platform margin structure, analyze the relationship between the platform margin reef-flat bodies and the platform to obtain the origin, evolution law, formation and evolution of the platform, and the formation and distribution law of oil and gas resources, and realize the prediction of the distribution of platform margin reef-flat bodies.

9. The method for depicting the carbonate platform margin structure and predicting the distribution of platform margin reef flat bodies according to claim 1, characterized in that The method further includes: after the prediction of the platform margin reef-flat bodies is realized, update the seismic data in real time and continuously optimize the interpretation method, and update and optimize the prediction results in real time.

10. A computer device, characterized in that, It includes a memory and a processor. When the processor executes the computer program stored in the memory, it executes the method for characterizing the carbonate platform margin structure and predicting the distribution of platform margin reef-flat bodies according to any one of claims 1 to 9.

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