A method and system for thin sand reservoir prediction based on pre-stack phase gradient attributes

Abstract

The present application belongs to the field of seismic data processing, and relates to a thin sandstone reservoir prediction method and system based on prestack phase gradient attributes, comprising: S1: obtaining original seismic data, and preprocessing the original seismic data to obtain preprocessed seismic data; S2: processing the preprocessed seismic data using complex seismic trace analysis to calculate the total phase sequence of each seismic trace; S3: constructing a sandstone-mudstone thin interbedded geological model to simulate multiple configurations and obtain the characteristic law of prestack phase gradient attributes; S4: identifying the thin sandstone reservoir based on the total phase sequence and the characteristic law of prestack phase gradient attributes, realizing fluid prediction, and obtaining a prediction result; and S5: predicting the thickness of the thin sandstone reservoir through the characteristics of the prestack phase gradient attributes in the high-velocity-difference area; avoiding the thin-layer phase interference effect that cannot be solved by traditional AVO, so as to realize the purpose of super-resolution prediction of gas-containing thin sandstone.

Description

Technical Field

[0001] This invention relates to the field of seismic data processing, and specifically discloses a method and system for predicting thin sandstone reservoirs based on pre-stack phase gradient properties. Background Technology

[0002] Seismic waves, when propagating through subsurface media, carry rich information about stratigraphic structure, lithology, and physical properties. This information includes seismic wave attributes such as velocity, amplitude, frequency, and phase, which are crucial for seismic reservoir prediction and fluid identification. Thin reservoirs (thickness less than λ / 4, where λ is the dominant wavelength) are important targets for oil and gas exploration. Their seismic response is significantly affected by tuning effects and wave interference, leading to complex variations in amplitude, frequency, and phase attributes (Liu et al., 2019; Yang et al., 2010). Traditional amplitude-based reservoir prediction methods (such as AVO analysis) often produce "false bright spots" due to differences in surrounding rocks under thin-layer conditions (Zhang et al., 2021), and their resolution is limited by the Widess model (λ / 4) (Jiang et al., 2023). In thin-layer identification and thickness estimation, the traditional approach is to base the study on the amplitude spectrum of seismic data and utilize anomalous features. However, these methods struggle to avoid the influence of the combination of top and bottom reflection coefficients and the seismic wavelet amplitude spectrum. In contrast, phase is also quite sensitive to changes in formation thickness, but due to the complexity of phase spectra and the lack of clarity regarding the response mechanism of formations, there are not many studies on this topic.

[0003] Phase attributes, due to their high sensitivity to thin-layer fluids and strong noise resistance, have gradually become a key breakthrough for high-precision prediction of thin reservoirs. Zhang Yingbo believes that seismic phases reveal rich and vivid geological phenomena and can explain various sedimentary phenomena that cannot be explained by seismic amplitude profiles. Bi Junfeng, Bai Guanjun, and others, by observing the phase lag distribution at different frequencies, have achieved better fine interpretation of faults and identification of fault systems in broadband seismic data, obtaining higher resolution. Wang Qinghua developed frequency-division phase technology by utilizing the most dominant frequency band of fault response highlighted by frequency division and the characteristic that phase is sensitive to changes in stratigraphic attitude. This technology overcomes the inadequacy of conventional coherence techniques and plays a unique role in identifying fault distribution characteristics. Ji Zhanhuai et al. used instantaneous phase on frequency-division profiles to identify small faults. Kazmi et al. proposed a method for identifying fault features using the curvature attribute of continuous phase spectra, overcoming the limitations of existing methods and providing higher volume curvature attribute resolution. Alam et al. proposed a technique for automatically detecting faults in three-dimensional data volumes using phase spectra. Liu Daoping, Zhao Zihao, and others utilized the phase attributes of seismic records for seismic sequence calibration in the work area, making sand body calibration interpretation more reliable. Wang Peng proposed a new method for estimating thin layer thickness based on an improved phase objective function. By constructing an intermediate function and minimizing its standard deviation, the reliability of phase-based thin layer thickness estimation can be effectively improved. Previous studies have shown that phase information has higher resolution in seismic interpretation.

[0004] Elita decomposed seismic data into positive and negative 90-degree phase components using the phase decomposition method, and studied the amplitude variation characteristics of thin gas-bearing reservoirs with angle under seismic data of different phase components, thus improving the accuracy of reservoir identification.

[0005] In view of this, the present invention provides a method and system for predicting thin sandstone reservoirs based on pre-stack phase gradient attribute (PVO). The phase gradient attribute is defined, which can better indicate thin reservoirs in thin interbedded layers and efficiently avoid the thin-layer phase interference effect that traditional AVO cannot solve, thereby achieving the purpose of super-resolution prediction of gas-bearing thin sandstones. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for predicting thin sandstone reservoirs based on pre-stack phase gradient attributes (PVO), addressing the problem of avoiding the thin-layer phase interference effect that traditional AVO cannot resolve, thereby achieving super-resolution prediction of gas-bearing thin sandstones; the specific solution is as follows: A method for predicting thin sandstone reservoirs based on pre-stack phase gradient attributes includes: S1: acquiring raw seismic data and preprocessing it to obtain preprocessed seismic data; S2: processing the preprocessed seismic data using complex seismic trace analysis to calculate the total phase sequence of each seismic trace; S3: constructing a geological model of thin interbedded sandstone and mudstone, simulating various configurations, and obtaining the characteristics of pre-stack phase gradient attributes; S4: identifying thin sandstone reservoirs based on the total phase sequence and the characteristics of pre-stack phase gradient attributes, achieving fluid prediction, and obtaining prediction results; S5: predicting the thickness of thin sandstone reservoirs based on the characteristics of pre-stack phase gradient attributes in high velocity difference regions.

[0007] Furthermore, S2 includes: S21: converting the field seismic trace signal into a complex seismic trace signal through complex seismic trace analysis; S22: calculating the real and imaginary parts of the complex seismic trace using discrete Hilbert transform; S23: obtaining the total phase of a single trace based on the real and imaginary parts of the complex seismic trace, and performing phase unwrapping on the total phase of the single trace to obtain a continuous total phase curve of the single trace; S24: repeating S21-S23 for the trace gather at each incident angle to generate the total phase sequence of the seismic trace.

[0008] Furthermore, the conversion of complex seismic trace signals is as follows: ; in, Indicates complex seismic trace signals; This represents the actual seismic trace signal; i represents the imaginary unit; Indicates the actual seismic trace signal The continuous Hilbert transform; represents the amplitude envelope of the complex seismic trace signal; e represents the exponential function; Indicates the instantaneous phase of the complex seismic trace signal; The discrete Hilbert transform is: ; in, Indicates the actual seismic trace signal The Hilbert transform; n represents the current sampling time point; m represents the integration variable of the convolution operation; Indicates the first The original seismic wave amplitude at each sampling point; Represents the Hilbert kernel function After time reversal, the sample points are shifted by m points along the time axis; Represents the Hilbert kernel function; The total phase of a single track is: ; in, This indicates a single-channel seismic signal at time t and incident angle. The total phase under the given conditions; t represents the time coordinate corresponding to the sampling point; represents the angle of incidence of the seismic wave; arctan represents the arctangent function; Represents the imaginary part of the complex seismic trace signal; This represents the real part of the complex seismic trace signal.

[0009] Furthermore, S3 includes: S31: superimposing the reflection response of each layer with the propagation phase delay through interference to obtain the total reflection coefficient; S32: determining the incident angle phase gradient based on the change in incident angle; S33: determining the phase gradient as the phase changes with the incident angle based on the total reflection coefficient and the incident angle phase; S34: determining the correlation between the phase gradient change and the fluid in the thin sandstone reservoir based on the phase gradient change in the high velocity difference region in the pre-stack phase gradient attribute, and obtaining the characteristic law of the pre-stack phase gradient attribute.

[0010] Furthermore, S31 includes: processing the Zopritz equation based on the Shuai formula to obtain the reflection coefficient of thin interbedded sandstone and mudstone; determining the synthetic response of the reflected wave at the top and bottom interface of a single sandstone layer based on the reflection coefficient of thin interbedded sandstone and mudstone; determining the first phase delay caused by the change in the longitudinal wave velocity and transmission angle of the sandstone layer; determining the second phase delay caused by the change in the thickness of the mudstone interlayer; obtaining the phase response of the multilayered sandstone and mudstone interbedded geological model based on the first phase delay and the second phase delay, and obtaining the total reflection coefficient by interferometric superposition of the reflection response of each layer and the propagation phase delay.

[0011] Furthermore, the reflection coefficient of the thin interbedded sandstone and mudstone is: ; in, Indicates the reflection coefficient of thin interbedded sandstone and mudstone; G represents the intercept term of the reflection coefficient; G represents the gradient term of the reflection coefficient. The angle of incidence of the seismic wave is represented by ; sin represents the sine function; H represents the curvature term of the reflection coefficient; tan represents the tangent function. The synthesized response is: ; in, This represents the composite response of reflected waves from the top and bottom interfaces of a single-layer sandstone. Let represent the reflection coefficient of the j-th sandstone layer; j represents the sandstone layer variable; e represents the exponential function; and i represents the imaginary unit. This indicates the first phase delay of the j-th sandstone layer; The first phase delay is: ; in, The first phase delay of the j-th sandstone layer is represented by π; π represents pi; and f represents the dominant frequency of the seismic wave. This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Represents the longitudinal wave velocity; s and sj both represent sandstone; cos represents the cosine function; This represents the transmission angle of the seismic wave at the interface of the j-th sandstone layer; The second phase delay is: ; in, This represents the second phase delay of the k-th mudstone layer; both mud and m represent mudstone; k represents the mudstone layer variable; π represents pi. This represents the longitudinal wave velocity of the k-th mudstone layer; denoted by , where represents the thickness of the k-th mudstone layer; cos represents the cosine function. This represents the transmission angle of the seismic wave at the mudstone interface of the k-th layer. The total reflectance is: ; in, This indicates that the thin interbedded sandstone and mudstone layers are at an incident angle of... The total reflection coefficient at time; N represents the total number of sandstone layers; This indicates a propagation phase delay in the overlying sandstone and mudstone strata.

[0012] Furthermore, S32 includes: Based on the velocity ratio variation of sandstone and mudstone, the cosine of the transmission angle is approximately expanded; the approximate expansion is as follows: ; Where cos represents the distress function; This represents the transmission angle of the seismic wave at the interface of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; The sine wave represents the longitudinal wave velocity of mudstone; sin represents the sine function. Based on the approximate expansion of the transmission angle cosine, the total phase delay of the multi-layered sandstone and mudstone strata is obtained; the total phase delay is: ; in, Indicates the total phase delay; Indicates proportional to; This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Based on the total formation thickness and the velocity of the sandstone and mudstone, the phase intercept is determined; the phase intercept is: ; in, The phase intercept is represented by π; π represents pi; f represents the dominant frequency of the seismic wave. The value represents the longitudinal wave velocity of sandstone; j represents the sandstone layer variable; N represents the total number of sandstone layers; k represents the mudstone layer variable. This represents the thickness of the k-th mudstone layer; The incident angle phase gradient is determined based on the change in the incident angle; ; in, This indicates taking the derivative with respect to the angle of incidence; Indicates the angle of incidence.

[0013] Furthermore, S4 includes: S41: Differentiate the total phase sequence and use the resulting phase gradient as the pre-stack phase gradient property body; the pre-stack phase gradient property body is: ; in, The phase gradient obtained by differentiation is represented by f; the dominant frequency of the seismic wave is represented by j; and the sandstone layer variable is represented by j. The thickness of the j-th sandstone layer is represented by ; k represents the mudstone layer variable. This represents the thickness of the k-th mudstone layer; This represents the longitudinal wave velocity of the k-th mudstone layer; S42: Determine the velocity difference indicator factor based on the phase gradient and phase intercept; the velocity difference indicator factor is used to indicate the fluid properties of the reservoir; the velocity difference indicator factor is: ; Wherein, VDI represents the speed difference indicator factor; Indicates the phase intercept; represents the phase gradient; k represents the velocity ratio.

[0014] Furthermore, S5 includes: S51: Determine the mudstone proportion based on the mudstone reservoir thickness and sandstone reservoir thickness; the mudstone proportion is: ; in, Indicates the proportion of mudstone; Indicates the thickness of the mudstone reservoir; Indicates the thickness of the sandstone reservoir; S52: Determine the sandstone reservoir thickness based on phase intercept and mudstone proportion; the sandstone reservoir thickness is: ; in, Indicates the phase intercept; The value represents the P-wave velocity of mudstone; π represents pi; f represents the dominant frequency of the seismic wave. This indicates the longitudinal wave velocity of sandstone.

[0015] This invention also provides a thin sandstone reservoir prediction system based on pre-stack phase gradient attributes, utilizing the aforementioned method for predicting thin sandstone reservoirs based on pre-stack phase gradient attributes. The system includes a data acquisition module, a data calculation module, a data processing module, a feature extraction module, and a data judgment module. The data acquisition module acquires raw seismic data and preprocesses it to obtain preprocessed seismic data. The data calculation module processes the preprocessed seismic data using complex seismic trace analysis to calculate the total phase sequence of each trace. The data processing module constructs a geological model of thin interbedded sandstone and mudstone layers, simulating various configurations to obtain the pre-stack phase gradient attribute features. The feature extraction module identifies thin sandstone reservoirs based on the total phase sequence and the pre-stack phase gradient attribute features, enabling fluid prediction and obtaining prediction results. The data judgment module predicts the thickness of thin sandstone reservoirs based on the characteristics of the pre-stack phase gradient attributes in high velocity difference regions.

[0016] The present invention has the following advantages and beneficial effects: This invention provides a method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties. The method defines phase gradient properties, which can better indicate thin reservoirs in thin interbedded layers and efficiently avoid the thin-layer phase interference effect that traditional AVO cannot solve, thereby achieving the goal of super-resolution prediction of gas-bearing thin sandstones.

[0017] This invention systematically analyzes the phase response characteristics of seismic waves in thin sandstone reservoirs, revealing that traditional amplitude properties (such as AVO) are susceptible to tuning effects and wave interference under thin interbedded conditions, leading to "false bright spots" and resolution limitations. In contrast, phase properties (especially phase gradient VVO) have become a key breakthrough for achieving super-resolution reservoir prediction due to their high sensitivity to thin-layer fluids and strong noise resistance. Based on the Shuey approximation formula, this paper derives the phase response mechanism and defines the phase gradient property (PVO), which is coupled and controlled by the velocity difference between sandstone and mudstone and the thickness of a single layer, effectively avoiding phase interference effects. In industrial exploration, such as the development of shale oil and gas or tight sandstone gas reservoirs, this method can be directly transformed into a high-precision reservoir identification process, improving the reliability and resolution of thin-layer prediction.

[0018] This invention integrates the theory of seismic wave phase response with the principle of thin-layer tuned interferometry. It extracts the pure phase component dataset of seismic signals through Hilbert transform, removes amplitude information interference, constructs orthogonal phase components that retain only the sensitive features of the strata, and on this basis, quantifies the phase delay of the top and bottom reflections of the thin layer based on a multi-layer sandstone-mudstone interferometry model. Attached Figure Description

[0019] Figure 1 The overall flowchart of a thin sandstone reservoir prediction method based on pre-stack phase gradient properties provided by the present invention; Figure 2 This is a schematic diagram of the structure of a thin sandstone reservoir prediction system based on pre-stack phase gradient properties provided by the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0021] This invention provides a method and system for predicting thin sandstone reservoirs based on pre-stack phase gradient properties. By adding a thin-layer tuning term to the Shuey approximation formula, the system analyzes the phase delay mechanism of the reflection coefficient in thin interbedded sandstone and mudstone, reveals that the change in reflection phase is controlled by the coupling effect of the sand-mudstone velocity difference and the thickness of a single layer, further derives the rate of change of phase with incident angle (PVO), and defines the phase gradient property.

[0022] Figure 1 This is an overall flowchart of a method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties, provided by the present invention. Figure 1 As shown, the method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties includes the following: S1: Acquire raw seismic data and preprocess it to obtain preprocessed seismic data. Raw seismic data refers to seismic observation data acquired from the target exploration area. Raw seismic data may include pre-stack seismic gathers, observation system data, seismic waveform data, and acquisition parameter data. Preprocessing includes noise suppression, amplitude compensation, and wavelet shaping to reduce the impact of environmental interference on the phase spectrum. Preprocessed seismic data refers to the seismic data obtained after preprocessing the raw seismic data. Preprocessed seismic data may include in-situ seismic signals.

[0023] S2: Complex seismic trace analysis is used to process the preprocessed seismic data and calculate the total phase sequence for each seismic trace. Complex seismic trace analysis refers to converting the real seismic trace signals obtained from seismic exploration into complex signals containing both real and imaginary parts.

[0024] In some embodiments, S2 specifically includes: S21: Analyzing in-situ seismic trace signals through complex seismic trace analysis Converted to complex seismic trace signal .

[0025] Complex seismic traces are converted to: ; in, Indicates complex seismic trace signals; This represents the actual seismic trace signal; i represents the imaginary unit; Indicates the actual seismic trace signal The continuous Hilbert transform; represents the amplitude envelope of the complex seismic trace signal; e represents the exponential function; This represents the instantaneous phase of the complex seismic trace signal.

[0026] The formula for calculating the continuous Hilbert transform is: ; Where π represents the mathematical constant pi; t represents the time variable (index of a continuous signal). Represents the integral variable; Indicates the actual seismic trace signal in the integral variable The amplitude value at time; This represents an integral infinitesimal element.

[0027] S22: Calculate the real and imaginary parts of complex seismic traces using the Discrete Hilbert Transform. The Discrete Hilbert Transform is: ; in, Indicates the actual seismic trace signal The Hilbert transform; n represents the current sampling time point (discrete signal index), which represents the time position of the Hilbert transform output result and is used to determine the current calculation point position; m represents the integration variable of the convolution operation, which represents the traversal index of the signal's historical sampling points and is used to traverse all possible signal historical points; Represents the discrete seismic signal at time [time]. The amplitude of represents the first The original seismic wave amplitude at each sampling point is used to provide the amplitude value of the signal at historical time m; Represents the Hilbert kernel function After time reversal, the sample points are shifted by m points along the time axis; It is the Hilbert kernel function.

[0028] The Hilbert kernel function is: ; Where n represents the current sampling time point, i.e., the discrete signal index, and represents the time position of the Hilbert transform output result, which is used to determine the current calculation point position.

[0029] S23: The total phase of a single trace is obtained based on the real and imaginary parts of the complex seismic traces, and phase unwrapping is performed on the total phase of the single trace to obtain a continuous total phase curve for that single trace. The total phase of the single trace is: ; in, This indicates a single-channel seismic signal at time t and incident angle. Total phase under certain conditions; This represents the time coordinate corresponding to the sampling point; denoted by , which represents the angle of incidence of the seismic wave; arctan represents the arctangent function. Represents the imaginary part of the complex seismic trace signal; This represents the real part of the complex seismic trace signal. Phase unwrapping is performed on the total phase of a single trace to eliminate 2π jumps and obtain a continuous phase curve.

[0030] S24: Repeat steps S21-S23 for the gathers at each incident angle to generate the total phase sequence of the seismic traces. Incident angle is... , refers to the angle between the incident direction of a seismic wave ray and the normal to the subsurface reflection interface. A gather refers to a CRP gather, i.e., a gather that has undergone migration processing and whose data has been converted from the shot-receiver offset domain to the incident angle domain. The total phase sequence of the seismic trace. Used for subsequent pre-stack phase gradient attribute (PVO) calculation.

[0031] S3: By constructing a geological model of thin interbedded sandstone and mudstone, simulating various configurations, and comparing phase response and amplitude response, the characteristic law of pre-stack phase gradient property (PVO) was obtained; In some embodiments, S3 specifically includes: S31: The total reflection coefficient is obtained by superimposing the reflection responses of each layer with the propagation phase delay through interference.

[0032] The total reflectance is obtained, including: The Zoeppritz equation was processed using the Shuey formula to obtain the reflection coefficient of thin interbedded sandstone and mudstone. The Zoeppritz equation was simplified to a trinomial using the Shuey formula, with the reflection coefficient R expressed as the angle of incidence. Approximate formula: ; in, Indicates the reflection coefficient of thin interbedded sandstone and mudstone; G represents the intercept term of the reflection coefficient; G represents the gradient term of the reflection coefficient. denoted by ; sin represents the sine function; H represents the curvature term of the reflection coefficient; tan represents the tangent function.

[0033] The intercept term of the reflection coefficient is: ; in, The intercept term represents the reflection coefficient, i.e., the reflection coefficient at zero angle of incidence; It represents the change in P-wave velocity, reflecting lithological differences; Indicates the average longitudinal wave velocity; It represents the change in density and is related to porosity and fluid properties. This represents the change in average density.

[0034] The gradient term of the reflection coefficient is: ; Where G represents the gradient term of the reflection coefficient; Indicates the average shear wave velocity; This represents the change in transverse wave velocity.

[0035] The curvature term of the reflection coefficient is: ; Where H represents the curvature term of the reflection coefficient.

[0036] Assume the propagation medium is an interbedded sandstone and mudstone stratum, with differences in velocity and density between the sandstone and mudstone, and the sandstone thickness is variable.

[0037] Based on the reflection coefficients of thin interbedded sandstone and mudstone, the composite response of the reflected waves from the top and bottom interfaces of a single sandstone layer is determined. The composite response of the reflected waves from the top and bottom interfaces of a single sandstone layer undergoes phase interference and can be expressed as: ; in, This represents the composite response of reflected waves from the top and bottom interfaces of a single-layer sandstone. Represents the reflection coefficient. , defined by the Shuey trinomial; e represents the exponential function; i represents the imaginary unit; This indicates a phase delay.

[0038] Determine the first phase delay caused by variations in the P-wave velocity and transmission angle of the sandstone layers. For example, when the sandstone thickness is h and the number of sandstone layers is j, the P-wave velocity of the sandstone layers... and the transmission angle of the sandstone layer The change causes the following first phase delay: ; in, The first phase delay of the j-th sandstone layer is represented by π; π represents pi; and f represents the dominant frequency of the seismic wave. This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Represents the longitudinal wave velocity; s and sj both represent sandstone; cos represents the cosine function; This represents the transmission angle of the seismic wave at the interface of the j-th layer of sandstone.

[0039] The second phase delay caused by variations in mudstone interlayer thickness is determined. This additional phase delay due to variations in mudstone interlayer thickness can be derived from Snell's law, specifically the mudstone velocity... The propagation phase delay of the mudstone interlayer (layer k) is: ; in, This represents the second phase delay of the k-th mudstone layer; both mud and m represent mudstone; k represents the mudstone layer variable; π represents pi. This represents the longitudinal wave velocity of the k-th mudstone layer; denoted by , where represents the thickness of the k-th mudstone layer; cos represents the cosine function. The transmission angle of the seismic wave at the mudstone interface of the k-th layer is expressed as follows: .

[0040] Based on the first and second phase delays, the phase response of the multilayered sandstone-mudstone interbedded model is obtained. The total reflection coefficient is then obtained by interferometric superposition of the reflection responses of each layer with the propagation phase delay. The total reflection coefficient is: ; in, This indicates that the thin interbedded sandstone and mudstone layers are at an incident angle of... The total reflection coefficient at time; N represents the total number of sandstone layers; This indicates a propagation phase delay in the overlying sandstone and mudstone strata.

[0041] S32: Determine the incident angle phase gradient based on the change in incident angle.

[0042] Based on the velocity ratio variation of sandstone and mudstone, the cosine of the transmission angle is approximately expanded (small angle): ; Where cos represents the distress function; This represents the transmission angle of the seismic wave at the interface of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Represents the longitudinal wave velocity of mudstone; sin represents the sine function; when (High-speed sandstone) Reducing it will affect the phase delay. Decrease; when (Low-velocity sandstone) Increasing this will affect the phase delay. Significantly increased.

[0043] Based on the approximate expansion of the transmission angle cosine, the total phase delay of the multi-layered sandstone and mudstone strata is obtained: ; in, Indicates the total phase delay; Indicates proportional to; This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer.

[0044] The phase of a seismic wave is the overall response of the strata, and can be expressed as the argument of the complex reflection coefficient: The total phase is expanded into the incident angle. Taylor series: Where: phase intercept ( The zero incident angle phase reflects the total thickness and average velocity; the phase gradient ( ) is the linear rate of change of phase with the incident angle, which is sensitive to velocity differences.

[0045] The phase intercept is determined based on the total formation thickness and the velocity of the sandstone and mudstone. When the angle of incidence... =0, the phase intercept is related to the total formation thickness and the velocity of sandstone and mudstone, and can be written as: ; in, The phase intercept is represented by π; π represents pi; f represents the dominant frequency of the seismic wave. The value represents the longitudinal wave velocity of sandstone; j represents the sandstone layer variable; N represents the total number of sandstone layers; k represents the mudstone layer variable. This represents the thickness of the k-th layer of mudstone.

[0046] The phase gradient of the incident angle is determined based on the change in the incident angle. Considering the change in the incident angle, the phase gradient can be written as: ; At small angles ; in, This indicates taking the derivative with respect to the angle of incidence; Indicates the angle of incidence.

[0047] S33: Based on the total reflection coefficient and the incident angle phase, determine the phase gradient as a function of the incident angle. The phase gradient as a function of the incident angle is: ; in, The phase gradient obtained by differentiation is represented by f; the dominant frequency of the seismic wave is represented by j; and the sandstone layer variable is represented by j. The thickness of the j-th sandstone layer is represented by ; k represents the mudstone layer variable. This represents the thickness of the k-th mudstone layer; This represents the P-wave velocity of the k-th mudstone layer. It indicates that the phase is controlled by the incident angle, and the phase angle is controlled by the difference in formation velocity and the thickness of the sandstone and mudstone.

[0048] S34: Based on the phase gradient changes in the high velocity difference region in the pre-stack phase gradient attributes, the correlation between phase gradient changes and fluids in thin sandstone reservoirs is determined, and the characteristic laws of PVO are obtained. The prominent feature of PVO is essentially the velocity difference ( ) and thin layer thickness ( The coupling response of ), where high velocity difference regions (such as gas-bearing sandstone, high-velocity calcareous interlayers) are included. Increased anomalous amplitudes highlight reservoir boundaries and fluid interfaces; low velocity differential regions (such as water-bearing sandstone). The response is gentle, suppressing false anomalies. This mechanism makes PVO a core technology for fluid prediction in thin sandstone reservoirs (especially shale gas and tight sandstone), effectively avoiding the ambiguity of traditional amplitude attributes.

[0049] S4: Based on the total phase sequence and the characteristics of pre-stack phase gradient attributes (PVO), thin sandstone reservoirs are identified using pre-stack phase gradient attributes to achieve fluid prediction and obtain prediction results.

[0050] In some embodiments, S4 specifically includes: S41: Differentiate the total phase sequence and use the resulting phase gradient as the PVO attribute volume. Based on pre-stack seismic gathers, extract the PVO attribute volume for the target region and apply it to the total phase sequence. along Differentiate the direction to obtain the phase gradient The body, as a PVO attribute body.

[0051] S42: Based on the phase gradient and phase intercept, a velocity difference indicator factor is determined; the velocity difference indicator factor is used to indicate the fluid properties of the reservoir. A velocity difference indicator factor (VDI) is proposed, designed to directly indicate the fluid properties of the reservoir: ; Wherein, VDI represents the speed difference indicator factor; This represents the phase intercept, which primarily responds to the total thickness and average velocity of the formation. The phase gradient is represented by k, which is primarily sensitive to velocity differences within the formation; k represents the velocity ratio. ; ratio (Velocity difference indicator factor) can suppress the background response shared by both (such as the overall thickness effect of a large stratum), thus highlighting the sensitivity to local velocity differences (i.e., velocity changes caused by fluid replacement), and finally multiply by the velocity ratio. Its purpose is to standardize or amplify indicator factors, thereby establishing a clearer and more stable quantitative relationship between VDI values ​​and fluid properties (gas content, oil content, water content). Gas content will... Significantly reduced, thereby changing This value ultimately leads to a significant anomaly in the VDI value. The VDI formula cleverly demonstrates that by combining... and It can enable the prediction of fluid properties.

[0052] S5: Predict the thickness of thin sandstone reservoirs by leveraging the prominent features of pre-stack phase gradient properties (PVO) in high velocity difference regions.

[0053] In some embodiments, S5 specifically includes: S51: Determine the mudstone proportion based on the mudstone reservoir thickness and sandstone reservoir thickness. Mudstone Proportion for: ; in, Indicates the proportion of mudstone; Indicates the thickness of the mudstone reservoir; This indicates the thickness of the sandstone reservoir. It is a geological constraint that connects the thickness of sandstone and mudstone.

[0054] S52: Based on phase intercept The proportion of mudstone is used to determine the thickness of sandstone reservoirs. Phase intercept. It is a linear function of the total thickness of sandstone and the total thickness of mudstone, and can be expressed as: ; Through algebraic transformations, the total thickness of mudstone is expressed in terms of the total thickness of sandstone and the proportion of mudstone, and then substituted into... In the basic formula, the two variables were finally successfully decoupled, resulting in an explicit expression that only concerns the total thickness of the sandstone: ; in, This refers to the thickness of the thin sandstone reservoir.

[0055] The thickness of the sandstone reservoir is: ; in, Indicates the phase intercept; The value represents the P-wave velocity of mudstone; π represents pi; f represents the dominant frequency of the seismic wave. This indicates the longitudinal wave velocity of sandstone.

[0056] Figure 2 This is a schematic diagram of the structure of a thin sandstone reservoir prediction system based on pre-stack phase gradient properties provided by the present invention. Figure 2 As shown, the thin sandstone reservoir prediction system based on pre-stack phase gradient attributes includes a data acquisition module, a data calculation module, a data processing module, a feature extraction module, and a data judgment module. The data acquisition module acquires raw seismic data and preprocesses it to obtain preprocessed seismic data. The data calculation module processes the preprocessed seismic data using complex seismic trace analysis to calculate the total phase sequence of each trace. The data processing module constructs a geological model of thin interbedded sandstone and mudstone, simulates various configurations, and obtains the pre-stack phase gradient attribute characteristics. The feature extraction module identifies thin sandstone reservoirs based on the total phase sequence and pre-stack phase gradient attribute characteristics, achieves fluid prediction, and obtains prediction results. The data judgment module predicts the thickness of thin sandstone reservoirs based on the characteristics of pre-stack phase gradient attributes in high velocity difference regions.

[0057] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties, characterized in that, include: S1: Acquire raw seismic data and preprocess the raw seismic data to obtain preprocessed seismic data; S2: Use complex seismic trace analysis to process the preprocessed seismic data and calculate the total phase sequence for each seismic trace; S3: By constructing a geological model of thin interbedded sandstone and mudstone, and simulating various configurations, the characteristics of pre-stack phase gradient attributes were obtained, including: S31: The total reflection coefficient is obtained by superimposing the reflection responses of each layer with the propagation phase delay through interference. S32: Determine the incident angle phase gradient based on the change in incident angle; S33: Based on the total reflection coefficient and the incident angle phase, the phase gradient as a function of the incident angle is determined as follows: ； in, The phase gradient is obtained by differentiation; f represents the dominant frequency of the seismic wave. The value represents the longitudinal wave velocity of the mudstone; π represents pi; and j represents the sandstone layer variable. The thickness of the j-th sandstone layer is represented by ; k represents the mudstone layer variable. This represents the thickness of the k-th mudstone layer; This represents the longitudinal wave velocity of the k-th mudstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; S34: Based on the phase gradient changes in the high velocity difference region in the pre-stack phase gradient attributes, the correlation between phase gradient changes and fluids in thin sandstone reservoirs is determined, and the characteristic laws of pre-stack phase gradient attributes are obtained. S4: Based on the total phase sequence and pre-stack phase gradient attribute characteristics, thin sandstone reservoirs are identified, fluid prediction is achieved, and prediction results are obtained, including: S41: Differentiate the total phase sequence and use the resulting phase gradient as the PVO attribute volume; based on pre-stack seismic gathers, extract the PVO attribute volume of the target region and perform a phase gradient analysis on the total phase sequence. along Differentiate the direction to obtain the phase gradient The body, as a PVO attribute body; S42: Determine the velocity difference indicator factor based on the phase gradient and phase intercept; the velocity difference indicator factor is used to indicate the fluid properties of the reservoir. ； Wherein, VDI represents the speed difference indicator factor; Indicates the phase intercept; The phase gradient is represented by k; the velocity ratio is represented by k. ; Indicates the longitudinal wave velocity of sandstone; S5: Predict the thickness of thin sandstone reservoirs by utilizing the characteristics of pre-stack phase gradient properties in high velocity difference regions.

2. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 1, characterized in that, S2 includes: S21: Convert field seismic trace signals into complex seismic trace signals through complex seismic trace analysis; S22: Calculate the real and imaginary parts of complex seismic traces using the discrete Hilbert transform; S23: The total phase of a single trace is obtained based on the real and imaginary parts of the complex seismic traces, and the total phase of the single trace is unwrapped to obtain a continuous total phase curve of the single trace; S24: Repeat S21-S23 for the gathers at each incident angle to generate the total phase sequence of the seismic traces.

3. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 2, characterized in that, The conversion of complex seismic trace signals to: ； in, Indicates complex seismic trace signals; This represents the actual seismic trace signal; i represents the imaginary unit; Indicates the actual seismic trace signal The continuous Hilbert transform; represents the amplitude envelope of the complex seismic trace signal; e represents the exponential function; Indicates the instantaneous phase of the complex seismic trace signal; The discrete Hilbert transform is: ； in, Indicates the actual seismic trace signal The Hilbert transform; n represents the current sampling time point; m represents the integration variable of the convolution operation; Indicates the first The original seismic wave amplitude at each sampling point; Represents the Hilbert kernel function After time reversal, the sample points are shifted by m points along the time axis; Represents the Hilbert kernel function; The total phase of a single track is: ； in, This indicates a single-channel seismic signal at time t and incident angle. The total phase under the given conditions; t represents the time coordinate corresponding to the sampling point; represents the angle of incidence of the seismic wave; arctan represents the arctangent function; Represents the imaginary part of the complex seismic trace signal; This represents the real part of the complex seismic trace signal.

4. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 1, characterized in that, S31 includes: The reflection coefficient of thin interbedded sandstone and mudstone is obtained by processing the Zopritz equation based on the Shuai formula. Based on the reflection coefficient of thin interbedded sandstone and mudstone, the synthetic response of reflected waves at the top and bottom interfaces of a single sandstone layer was determined. Determine the first phase delay caused by the changes in P-wave velocity and transmission angle of the sandstone layer; The second phase delay caused by variations in the thickness of the mudstone interlayer was determined. Based on the first and second phase delays, the phase response of the multilayered sandstone-mudstone interbedded geological model is obtained, and the total reflection coefficient is obtained by interferometric superposition of the reflection response of each layer and the propagation phase delay.

5. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 4, characterized in that, The reflection coefficient of thin interbedded sandstone and mudstone is: ； in, Indicates the reflection coefficient of thin interbedded sandstone and mudstone; G represents the intercept term of the reflection coefficient; G represents the gradient term of the reflection coefficient. The angle of incidence of the seismic wave is represented by ; sin represents the sine function; H represents the curvature term of the reflection coefficient; tan represents the tangent function. The synthesized response is: ； in, This represents the composite response of reflected waves from the top and bottom interfaces of a single-layer sandstone. Let represent the reflection coefficient of the j-th sandstone layer; j represents the sandstone layer variable; e represents the exponential function; and i represents the imaginary unit. This indicates the first phase delay of the j-th sandstone layer; The first phase delay is: ； in, The first phase delay of the j-th sandstone layer is represented by π; π represents pi; and f represents the dominant frequency of the seismic wave. This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Represents the longitudinal wave velocity; s and sj both represent sandstone; cos represents the cosine function; This represents the transmission angle of the seismic wave at the interface of the j-th sandstone layer; The second phase delay is: ； in, This represents the second phase delay of the k-th mudstone layer; both mud and m represent mudstone; k represents the mudstone layer variable; π represents pi. This represents the longitudinal wave velocity of the k-th mudstone layer; denoted by , where represents the thickness of the k-th mudstone layer; cos represents the cosine function. This represents the transmission angle of the seismic wave at the mudstone interface of the k-th layer. The total reflectance is: ； in, This indicates that the thin interbedded sandstone and mudstone layers are at an incident angle of... The total reflection coefficient at time; N represents the total number of sandstone layers; This indicates a propagation phase delay in the overlying sandstone and mudstone strata.

6. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 1, characterized in that, S32 includes: Based on the velocity ratio variation of sandstone and mudstone, the cosine of the transmission angle is approximately expanded; the approximate expansion is as follows: ； Where cos represents the cosine function; This represents the transmission angle of the seismic wave at the interface of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; The sine wave represents the longitudinal wave velocity of mudstone; sin represents the sine function. Based on the approximate expansion of the transmission angle cosine, the total phase delay of the multi-layered sandstone and mudstone strata is obtained; the total phase delay is: ； in, Indicates the total phase delay; Indicates proportional to; This represents the thickness of the j-th sandstone layer; This represents the longitudinal wave velocity of the j-th sandstone layer; Based on the total formation thickness and the velocity of the sandstone and mudstone, the phase intercept is determined; the phase intercept is: ； in, The phase intercept is represented by π; π represents pi; f represents the dominant frequency of the seismic wave. The value represents the longitudinal wave velocity of sandstone; j represents the sandstone layer variable; N represents the total number of sandstone layers; k represents the mudstone layer variable. This represents the thickness of the k-th mudstone layer; The incident angle phase gradient is determined based on the change in the incident angle; ； in, This indicates taking the derivative with respect to the angle of incidence; Indicates the angle of incidence.

7. The method for predicting thin sandstone reservoirs based on pre-stack phase gradient properties according to claim 1, characterized in that, S5 includes: S51: Determine the mudstone proportion based on the mudstone reservoir thickness and sandstone reservoir thickness; the mudstone proportion is: ； in, Indicates the proportion of mudstone; Indicates the thickness of the mudstone reservoir; Indicates the thickness of the sandstone reservoir; S52: Determine the sandstone reservoir thickness based on phase intercept and mudstone proportion; the sandstone reservoir thickness is: ； in, Indicates the phase intercept; The value represents the P-wave velocity of mudstone; π represents pi; f represents the dominant frequency of the seismic wave. This indicates the longitudinal wave velocity of sandstone.

8. A thin sandstone reservoir prediction system based on pre-stack phase gradient attributes, utilizing the thin sandstone reservoir prediction method based on pre-stack phase gradient attributes as described in any one of claims 1-7, characterized in that, It includes a data acquisition module, a data calculation module, a data processing module, a feature and pattern extraction module, and a data judgment module; The data acquisition module is used to acquire raw seismic data and preprocess the raw seismic data to obtain preprocessed seismic data. The data calculation module is used to process preprocessed seismic data using complex seismic trace analysis and to calculate the total phase sequence for each seismic trace. The data processing module is used to construct a geological model of thin interbedded sandstone and mudstone, simulate various configurations, and obtain the characteristics of pre-stack phase gradient attributes. The feature extraction module is used to identify thin sandstone reservoirs based on the total phase sequence and pre-stack phase gradient attribute features, to achieve fluid prediction, and to obtain prediction results. The data judgment module is used to predict the thickness of thin sandstone reservoirs by using the characteristics of pre-stack phase gradient attributes in high velocity difference regions.

Images