Prediction method and system for tight sandstone gas sweet spot area under strong reflection coal seam

Abstract

The invention discloses a method and system for predicting a compact sandstone gas sweet spot area under a strong reflection coal seam, and the method comprises the steps: obtaining the geological data of a to-be-measured area, and building an isochronous stratigraphic framework and a geological configuration; loading post-stack seismic data, calibrating or calibrating the seismic data according to an isochronous stratigraphic framework and a geological configuration, and determining coal seam and seismic reflection characteristics; performing 90-degree phase shift conversion on the phase of the post-stack seismic data to obtain a corresponding relation between a 90-degree phase shift profile and lithology; based on the corresponding relation and the seismic reflection characteristics, identifying the compact sandstone river channel development area; obtaining spatial distribution information of the compact sandstone river channel development area by using parameter inversion of the gamma logging curve; the bottom interface of the tight sandstone stratum is used as a reference horizon, gradient values of upper and lower time window wavelet spectrum ratio attenuation are calculated, and a target sweet spot area is screened based on the gradient values. The tight sandstone gas sweet spot area is accurately identified, and the lithologic trap evaluation precision and the drilling success rate of the gas-bearing area are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and particularly to a prediction method and system for sweet spots of tight sandstone gas under a strong-reflection coal seam. Background Art

[0002] With the transformation of the energy structure, the exploration of clean energy natural gas has become increasingly important. Among them, the Upper Carboniferous-Permian coal-bearing formation tight gas (sandstone gas and shale gas) resources in the overseas S exploration area are rich, and the predicted geological resources are 10.4×10 12 m 3 However, coal seams are generally developed in the Upper Carboniferous-Permian tight sandstone formation in this exploration area. Affected by the strong seismic reflection shielding of the coal seam, it is often difficult to accurately identify the sweet spots of the underlying tight sandstone gas, resulting in poor exploration and development effects. Therefore, it is of great practical value and significance to develop a prediction technology for the sweet spots of tight sandstone gas under a strong-reflection coal seam to effectively improve the prediction accuracy of tight gas sweet spots and then improve the exploration and development effects of tight sandstone gas.

[0003] However, there are several difficulties in seismic prediction of sweet spots of tight sandstone gas under a strong-reflection coal seam:

[0004] (1) The upper part of the tight sandstone layer is covered by a strong-reflection coal seam. Affected by the strong seismic reflection shielding of the coal seam, the seismic resolution of the sandstone reservoir is significantly reduced.

[0005] (2) The tight sandstone reservoir often has a thin thickness, a dense lithology and a low porosity. These geological characteristics make the corresponding geophysical characteristics extremely weak and difficult to identify.

[0006] (3) Due to the characteristics of low-porosity and low-permeability reservoirs and the shielding interference of strong-reflection coal seams, conventional oil and gas detection methods such as AVO (Amplitude-Versus-Offset) have multiple solutions and cannot accurately determine the gas-bearing sweet spots.

[0007] Therefore, a prediction method and system for sweet spots of tight sandstone gas under a strong-reflection coal seam are needed to improve the accuracy of resource evaluation and target selection. Summary of the Invention

[0008] By providing a prediction method and system for sweet spots of tight sandstone gas under a strong-reflection coal seam, the embodiments of the present invention solve the technical problem that the gas-bearing sweet spots cannot be accurately determined in the prior art.

[0009] To solve the above technical problem, the present invention provides the following technical solutions:

[0010] In a first aspect, the present invention discloses a prediction method for sweet spots of tight sandstone gas under a strong-reflection coal seam, including:

[0011] Obtain seismic data, logging curves and interpretation data of the area to be measured, and establish an isochronous stratigraphic framework and geological configuration;

[0012] Load the post-stack seismic data to improve the resolution of the above seismic data; calibrate or calibrate the above seismic data according to the above isochronous stratigraphic framework and geological configuration, and determine the seismic reflection characteristics of coal seams and tight sandstone formations;

[0013] Perform a 90° phase shift conversion on the phase of the post-stack seismic data to obtain the corresponding relationship between the 90° phase shift profile and lithology; identify the developed areas of tight sandstone channels based on the above corresponding relationship and the above seismic reflection characteristics;

[0014] Use the parameter inversion of the gamma logging curve to obtain the spatial distribution information of the above developed areas of tight sandstone channels;

[0015] Take the bottom interface of the tight sandstone formation in the above spatial distribution information as the reference horizon, calculate the gradient value of the attenuation of the wavelet frequency spectrum ratio of the time windows above and below the above reference horizon, and screen the target sweet spots according to the corresponding relationship between the above gradient value and the gas-bearing reliability of the sweet spots.

[0016] Optionally, the steps of identifying the developed areas of tight sandstone channels specifically include:

[0017] Identify the developed areas of tight sandstone channels through preset amplitude and reflection characteristics of lenticular downcut thickening.

[0018] Optionally, the steps of obtaining the spatial distribution information of the above developed areas of tight sandstone channels specifically include:

[0019] Equivalent the gamma curve to a wave impedance curve, and obtain the spatial distribution information of the above developed areas of tight sandstone channels based on the impedance inversion method.

[0020] Optionally, the steps of calculating the gradient value of the attenuation of the wavelet frequency spectrum ratio of the time windows above and below the above reference horizon specifically include:

[0021] Calculate the natural logarithmic function of the wavelet angular frequency of the upper time window and the lower time window of the above reference horizon;

[0022] Use the wavelet angular frequency of the above upper time window minus the above lower time window to obtain the logarithmic gradient value of the wavelet frequency spectrum ratio.

[0023] Optionally, the steps of calculating the natural logarithmic function of the wavelet angular frequency of the upper time window and the lower time window of the above reference horizon specifically include

[0024] Drift up and down each recorded sample point of the above reference horizon, and open time windows respectively;

[0025] Perform rematch spectrum sequence analysis on the records within any of the above time windows to obtain the rematch spectrum sequences corresponding to the upper and lower time windows;

[0026] Performing low-pass filtering on the above complex spectrum sequence to filter out the pulse complex spectrum component and obtain the wavelet complex spectrum component;

[0027] Perform Fourier transform on the above wavelet complex spectrum component to obtain the natural logarithm function of the wavelet angular frequency;

[0028] The wavelet of the lower time window is subtracted from the wavelet of the upper time window to obtain the logarithmic gradient value of the wavelet spectrum ratio.

[0029] Optionally, the corresponding relationship between the gradient value and the reliability of the gas content in the sweet spot area includes:

[0030] The above gradient value is proportional to the reliability of the gas content in the above sweet spot area.

[0031] In a second aspect, the present invention discloses a prediction system for tight sandstone gas sweet spots under highly reflective coal seams, comprising:

[0032] The stratigraphic structure analysis module acquires seismic data, well logging curves, and interpretation data of the area to be measured, and establishes an isochronous stratigraphic framework and geological configuration;

[0033] A seismic horizon interpretation module loads post-stack seismic data to improve the resolution of the seismic data; calibrates or calibrates the seismic data based on the isochronous stratigraphic framework and geological configuration to determine the seismic reflection characteristics of coal seams and tight sandstone formations;

[0034] The 90° phase shift conversion module performs a 90° phase shift on the phase of the post-stack seismic data to obtain the corresponding relationship between the 90° phase shift profile and the lithology. Based on this corresponding relationship and the above-mentioned seismic reflection characteristics, the tight sandstone channel development area is identified.

[0035] An inversion module is used to obtain the spatial distribution information of the tight sandstone channel development area by inverting the parameters of the gamma-ray logging curve;

[0036] The attenuation gradient calculation module is used to use the bottom interface of the tight sandstone formation in the above spatial distribution information as the reference layer, calculate the gradient value of the window wave spectrum ratio attenuation above and below the above reference layer, and screen the target sweet spot based on the correspondence between the above gradient value and the gas content reliability of the sweet spot.

[0037] Optionally, the above system further includes:

[0038] The central control module is used to integrate, store and display the data of the above-mentioned seismic layer interpretation module, the above-mentioned 90° phase shift transformation module, the above-mentioned inversion module, the above-mentioned attenuation gradient calculation module and the above-mentioned stratum structure analysis module.

[0039] In a third aspect, the present invention discloses an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps corresponding to the method in the first aspect are implemented.

[0040] In a fourth aspect, the present invention discloses a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps corresponding to the method in the first aspect are implemented.

[0041] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0042] In the technical solution of the present invention, post-stack seismic data is adopted to improve the resolution of seismic data. Through a 90° phase shift transformation on the high-resolution seismic data, the seismic reflection isochrones can be compared with lithology, so that the formation resolution ability is higher, and the accuracy of seismic interpretation horizons is improved. After analyzing the multi-well sensitive parameters and electrical characteristics, it is found that the gamma log curve best characterizes the sandstone layer. Therefore, gamma parameter inversion is used to obtain the spatial distribution information of the dense sandstone channel development area. Then, taking the bottom interface of the dense sandstone formation in the spatial distribution information as the reference horizon, the interference effect of the strong reflection of the coal seam in the upper and lower time windows is eliminated, and the advantage of the weak reflection of the reservoir is highlighted. According to the corresponding relationship between the gradient value and the reliable degree of gas content in the sweet spot area, the target sweet spot area is screened to obtain an accurate gas-bearing sweet spot area. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is a flowchart of a method for predicting a gas-bearing sweet spot area of dense sandstone under a strong-reflection coal seam provided by the present invention;

[0045] Figure 2 It is a formation structure diagram in the present invention;

[0046] Figure 3 It is a conventional migration time seismic profile in the present invention;

[0047] Figure 4 It is a comparison diagram between the original seismic profile through the well and the 90° phase shift seismic profile in the present invention;

[0048] Figure 5 It is a comparison diagram between the cross-well formation correlation (upper) and the 90° phase shift seismic profile through the well (lower) in the present invention;

[0049] Figure 6 This is the cross - well model - constrained gamma inversion seismic profile in the present invention;

[0050] Figure 7 This is the seismic profile for predicting tight gas sweet spots using the wavelet spectrum ratio attenuation gradient attribute in the present invention;

[0051] Figure 8 This is the schematic structural diagram of a prediction system for tight sandstone gas sweet spots under a strong - reflection coal seam provided by the present invention. Detailed implementation manners

[0052] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Generally, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0053] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed present invention, but merely represents the selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0054] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0055] It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solutions of the present application, rather than limitations on the technical solutions of the present application. Without conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0056] The technical solution of the embodiment of the present invention is to solve the above - mentioned technical problems, and the general idea is as follows:

[0057] Based on the analysis of formation configuration and tight sandstone geological characteristics, relying on post - stack seismic data to improve its resolution, successively using 90° phase - shift conversion, gamma inversion and wavelet spectrum ratio attenuation gradient for prediction, and finally accurately identifying tight sandstone gas sweet spots, improving the evaluation accuracy of lithologic traps in gas - bearing areas and the drilling success rate, and significantly improving the exploration and development effect of tight sandstone gas.

[0058] In the embodiment of the present invention, there is provided as Figure 1A prediction method for sweet spots of tight sandstone gas under a strongly reflective coal seam as shown, the method comprising steps S101 to S103:

[0059] Step S101, obtain seismic data, logging curves and interpretation data of the area to be measured, and establish an isochronous stratigraphic framework and geological configuration. Among them, establishing an isochronous stratigraphic framework and geological configuration aims to analyze the stratigraphic structure, so as to accurately obtain the vertical superimposed relationship and geological configuration of the coal seam and tight sandstone formation, as Figure 2 shown.

[0060] Step S102, load the post-stack seismic data to improve the resolution of the seismic data; calibrate or calibrate the seismic data according to the isochronous stratigraphic framework and geological configuration, and determine the seismic reflection characteristics of the coal seam and tight sandstone formation.

[0061] It should be noted that there is a strongly reflective coal seam covering the tight sandstone formation, but the seismic reflection energy is weak and difficult to identify. Therefore, post-stack seismic data is used to increase the seismic main frequency to 45 Hz; among them, post-stack seismic data refers to that the seismic signal is migrated before stacking and then stacked. Thereby improving the resolution and clarity of the seismic data, enabling the seismic signal to better reflect the true situation of the underground medium. And calibrating or calibrating the seismic data according to the isochronous stratigraphic framework and geological configuration relies on the corresponding well logging data (such as well logging seismic data or well logging geological data) in it to calibrate or calibrate the seismic data to ensure the accuracy and reliability of the seismic data. Thereby determining the position and shape of the underground geological structure.

[0062] Step S103, perform a 90° phase shift conversion on the phase of the post-stack seismic data to obtain the corresponding relationship between the 90° phase shift profile and lithology; based on the corresponding relationship and seismic reflection characteristics, identify the developed area of tight sandstone channels.

[0063] Specifically, through 90° phase shift transformation of high-resolution seismic data, the seismic reflection coaxial can be compared with lithology, and the comparison relationship between seismic amplitude and sandstone thickness and physical properties is better, so the stratigraphic resolution ability is higher, improving the accuracy of seismic interpretation horizons. And in the research, through a large number of well-seismic combined analysis and time-depth conversion lithology calibration, it is found that there is a good corresponding relationship between the 90° phase shift profile and lithology, and the lithology identification ability is stronger than that of the normal polarity profile, as Figure 4 and Figure 5As shown. In addition, the tight sandstone layer and the strongly reflective coal seam belong to the same sedimentary isochronous stratigraphic unit. Its sedimentary microfacies is a distributary channel, located at the bottom of the stratigraphic unit. The bottom boundary of the stratum corresponds to the bottom shape of the channel. When the tight sandstone develops, it shows lenticular downcut thickening and polarity reversal reflection characteristics in the phase-shifted seismic profile. Therefore, by presetting the amplitude and the reflection characteristics of lenticular downcut thickening, the development area of the tight sandstone channel is identified; among them, the preset amplitude uses medium-weak amplitude, that is, the amplitude of the seismic wave is less than 12 seismic trace intervals in the time section.

[0064] Step S104, using the parameter inversion of the gamma logging curve, obtain the spatial distribution information of the development area of the tight sandstone channel, such as Figure 6 shown.

[0065] It should be noted that the possible channel development area is identified through the medium-weak amplitude and lenticular downcut thickening reflection characteristics in the 90° phase-shifted profile. However, due to the complexity of geological phenomena and the multi-solution nature of seismic data, there may be a channel reflection contour but there may not necessarily be channel sandstone developed. Whether sandstone is developed or how to define the thickness and scale of the sandstone still requires further identification; therefore, the parameters of the gamma logging curve are used for inversion.

[0066] Specifically, through the analysis of multi-well sensitive parameters and electrical characteristics, it is found that the gamma logging curve has the best characterization of the sandstone layer. And in the sandstone-shale formation, the gamma curve and the wave impedance curve have a good corresponding relationship, and also contain formation and lithology information. Therefore, it is feasible to use gamma pseudo-wave impedance inversion in terms of method. Therefore, the distribution of sand bodies can be predicted through gamma parameter inversion. That is, the gamma curve is equivalent to the wave impedance curve, and the spatial distribution information of the development area of the tight sandstone channel is obtained based on the impedance inversion method. The actually inverted gamma seismic profile can well reflect the longitudinal and lateral variation characteristics of the sandstone, has strong resolution ability for sand bodies, and high coincidence degree with wells, thereby more accurately predicting the development degree of sandstone in the well-free area.

[0067] Step S105, taking the bottom interface of the tight sandstone formation in the spatial distribution information as the reference horizon, calculate the gradient value of the attenuation of the wavelet spectrum ratio between the upper and lower time windows of the reference horizon, and screen the target sweet spots according to the corresponding relationship between the gradient value and the gas-bearing reliability degree of the sweet spots, such as Figure 7 shown.

[0068] It should be noted that the development of channel sandstone can be predicted by using 90° phase-shift conversion and gamma inversion. However, for whether the tight sandstone is a gas-bearing sweet spot, further evaluation and analysis are still needed. In this embodiment, the gradient value of the wavelet spectrum ratio attenuation is used to identify the gas-bearing sweet spots.

[0069] Specifically, when seismic waves propagate in underground rock formations, there is absorption attenuation of the seismic wave amplitude caused by non-perfect elasticity, resulting in continuous changes in the shape of the seismic wavelet. Different lithologies have different degrees of absorption of seismic waves, and their absorption properties mainly depend on the elastic properties of the rock skeleton, the porosity of the rock, and the fluid components in the pores, etc. Therefore, calculating the absorption properties of seismic waves and their lateral changes along the reflection horizon can be used to predict lithology and hydrocarbon-bearing properties. Most traditional post-stack hydrocarbon identification techniques utilize absorption attributes, but when calculating the formation absorption coefficient, the amplitude ratio above and below the sample point is used. At this time, the amplitude is significantly weakened by the interference of strong-reflection coal seams. Therefore, the signal-to-noise ratio of the absorption coefficient obtained by this method is relatively low, as Figure 3 shown.

[0070] Therefore, this embodiment adopts wavelet spectrum ratio attenuation gradient attribute analysis. By calculating the natural logarithm function of the wavelet angular frequency of the upper time window and the lower time window on the reference horizon; using the wavelet angular frequency of the upper time window minus the wavelet angular frequency of the lower time window, the logarithmic gradient value of the wavelet spectrum ratio is obtained. Through the subtraction transformation of the natural logarithm into the natural logarithm function of the wavelet angular frequency of the upper time window divided by the wavelet angular frequency of the lower time window, this embodiment can simultaneously eliminate the interference effects of strong reflections of coal seams in the upper and lower time windows and highlight the advantages of weak reflections of reservoirs, thereby evaluating the gas-bearing reliability of tight sandstone sweet spots. Among them, the gradient value is proportional to the gas-bearing reliability of the sweet spot, that is, the larger the gradient value, the greater the gas-bearing reliability, and the smaller the gradient value, the smaller the gas-bearing reliability; achieving the effect of accurately identifying the tight sandstone sweet spot under the strong-reflection coal seam and delineating the hydrocarbon enrichment area.

[0071] Among them, the specific calculation steps for calculating the natural logarithm function of the wavelet angular frequency of the upper time window and the lower time window on the reference horizon are as follows:

[0072] Drift up and down for each recorded sample point on the reference horizon and open time windows respectively. Specifically, first determine the bottom interface of the tight sandstone layer as the reference seismic time horizon, and open time windows by drifting up and down for each recorded sample point at this horizon.

[0073] Perform complex spectrum sequence analysis on the records within any time window to obtain the complex spectrum sequences corresponding to the upper and lower time windows. Specifically, the complex spectrum of the upper time window is: The complex spectrum of the lower time window is: Among them i = 1, 2 is the wavelet complex spectrum sequence; i = 1, 2 is the impulse complex spectrum sequence.

[0074] Perform low-pass filtering on the complex spectrum sequence to filter out the impulse complex spectrum components Obtain the wavelet complex spectrum components

[0075] For the wavelet complex spectrum components and Perform Fourier transform to obtain the natural logarithm functions of the wavelet angular frequency lnS1(w) and lnS2(w), where w represents the angular frequency (unit: rad / s).

[0076] Subtract the lower time window wavelet from the upper time window wavelet to obtain the logarithmic gradient value of the wavelet spectrum ratio. That is:

[0077]

[0078] Equivalent to the slope, the slope value represents the attenuation degree of the wavelet, which has the same physical meaning as the formation absorption coefficient and can be used to detect oil and gas in the sweet spot area of tight sandstone. Compared with the existing technology, Evaluation can eliminate the strong reflection of coal seam energy and highlight the advantages of weak reflection of sweet reservoir, making the prediction results stable. When predicting the sweet spot area of tight sandstone using seismic prediction profiles, the larger the value, the greater the reliability of the gas content in the sweet spot area; conversely, the smaller the value, the lower the reliability of the gas content.

[0079] Based on the same inventive concept, the embodiment of the present invention provides a prediction system for tight sandstone gas sweet spots under strong reflective coal seams, such as Figure 8 As shown, including:

[0080] The stratigraphic structure analysis module acquires seismic data, well logging curves, and interpretation data of the area to be measured, and establishes an isochronous stratigraphic framework and geological configuration;

[0081] The seismic horizon interpretation module loads post-stack seismic data to improve the resolution of seismic data; calibrates or calibrates seismic data based on the isochronous stratigraphic framework and geological configuration to determine the seismic reflection characteristics of coal seams and tight sandstone formations;

[0082] The 90° phase shift conversion module converts the phase of the post-stack seismic data by 90° to obtain the corresponding relationship between the 90° phase shift profile and lithology. Based on the corresponding relationship and seismic reflection characteristics, it identifies the development area of tight sandstone channel.

[0083] The inversion module is used to obtain the spatial distribution information of tight sandstone channel development areas by inverting the parameters of gamma-ray logging curves;

[0084] The attenuation gradient calculation module is used to use the bottom interface of the tight sandstone formation in the spatial distribution information as the reference layer, calculate the gradient value of the window wave spectrum ratio attenuation above and below the reference layer, and screen the target sweet spot based on the correspondence between the gradient value and the gas content reliability of the sweet spot.

[0085] Furthermore, the system also includes:

[0086] The central control module is used to integrate, store, and display the data from the seismic horizon interpretation module, 90° phase shift transformation module, inversion module, attenuation gradient calculation module, and formation structure analysis module, facilitating the users to read and access the data.

[0087] Based on the same inventive concept, this embodiment provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the method for predicting the sweet spot area of tight sandstone gas under a strong reflection coal seam.

[0088] Based on the same inventive concept, this embodiment provides a computer-readable storage medium, on which a computer program is stored. The program, when executed by a processor, implements the method for predicting the sweet spot area of tight sandstone gas under a strong reflection coal seam.

[0089] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0090] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0091] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A method for predicting tight sandstone gas sweet spots under strongly reflective coal seams, characterized in that: The method comprises: Obtain seismic data, well logging curves and interpretation data of the area to be tested, and establish isochronous stratigraphic framework and geological structure; loading post-stack seismic data to improve the resolution of the seismic data; calibrating or calibrating the seismic data according to the isochronous stratigraphic framework and geological configuration to determine seismic reflection characteristics of coal seams and tight sandstone formations; Performing a 90° phase shift conversion on the post-stack seismic data to obtain a corresponding relationship between the 90° phase shift profile and the lithology; and identifying a tight sandstone channel development area based on the corresponding relationship and the seismic reflection characteristics. Obtaining spatial distribution information of the tight sandstone channel development zone by using parameter inversion of the gamma-ray logging curve; The bottom interface of the tight sandstone formation in the spatial distribution information is used as the reference layer, and the gradient value of the window wave spectrum ratio attenuation above and below the reference layer is calculated. The target sweet spot is screened according to the corresponding relationship between the gradient value and the gas content reliability of the sweet spot.

2. The prediction method according to claim 1, wherein: The step of identifying the tight sandstone channel development area specifically includes: Tight sandstone channel development areas can be identified by preset amplitude and lens-shaped incision and thickening reflection characteristics.

3. The prediction method according to claim 1, wherein: The step of obtaining the spatial distribution information of the tight sandstone channel development area specifically includes: The gamma curve is equivalent to a wave impedance curve, and the spatial distribution information of the tight sandstone channel development area is obtained based on the impedance inversion method.

4. The prediction method according to any one of claims 1 to 3, wherein: The step of calculating the gradient value of the window wave spectrum ratio attenuation when the reference layer is above and below the reference layer specifically includes: Calculating the natural logarithm function of the wavelet angular frequency of the upper time window and the lower time window of the reference layer; The wavelet angular frequency of the lower time window is subtracted from the upper time window to obtain a wavelet spectrum ratio logarithmic gradient value.

5. The prediction method according to claim 4, wherein: The step of calculating the natural logarithm function of the wavelet angular frequency of the upper time window and the lower time window of the reference layer specifically includes: Each record sample point of the reference layer is drifted up and down, and a time window is opened respectively; Perform rematch spectrum sequence analysis on the records within any of the time windows to obtain rematch spectrum sequences corresponding to the upper and lower time windows; performing low-pass filtering on the complex spectrum sequence to filter the pulse complex spectrum component to obtain the wavelet complex spectrum component; Performing Fourier transform on the wavelet complex spectrum component to obtain a natural logarithm function of the wavelet angular frequency; The lower time window wavelet is subtracted from the upper time window wavelet to obtain a wavelet spectrum ratio logarithmic gradient value.

6. The prediction method according to claim 4, wherein: The corresponding relationship between the gradient value and the reliability of gas content in the sweet spot area includes: The gradient value is proportional to the reliability of the gas content in the sweet spot.

7. A prediction system for tight sandstone gas sweet spots under strong reflective coal seams, characterized by: The system comprises: The stratigraphic structure analysis module acquires seismic data, well logging curves, and interpretation data of the area to be measured, and establishes an isochronous stratigraphic framework and geological configuration; a seismic horizon interpretation module that loads post-stack seismic data to improve the resolution of the seismic data; calibrates or calibrates the seismic data based on the isochronous stratigraphic framework and geological configuration to determine seismic reflection characteristics of coal seams and tight sandstone formations; A 90° phase shift conversion module performs a 90° phase shift on the phase of the post-stack seismic data to obtain a corresponding relationship between the 90° phase shift profile and the lithology; based on the corresponding relationship and the seismic reflection characteristics, the tight sandstone channel development area is identified; an inversion module for obtaining spatial distribution information of the tight sandstone channel development zone by inverting parameters of the gamma-ray logging curve; The attenuation gradient calculation module is used to use the bottom interface of the tight sandstone formation in the spatial distribution information as the reference layer, calculate the gradient value of the window wave spectrum ratio attenuation above and below the reference layer, and select the target sweet spot based on the correspondence between the gradient value and the gas content reliability of the sweet spot.

8. The prediction system according to claim 7, wherein: The system further comprises: The central control module is used to integrate, store and display the data of the seismic layer interpretation module, the 90° phase shift transformation module, the inversion module, the attenuation gradient calculation module and the stratum structure analysis module.

9. An electronic device, characterized in that: The electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method steps described in any one of claims 1 to 5 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps corresponding to the method according to any one of claims 1 to 5 are implemented.

Images