Method for describing effective reservoir based on five-dimensional analysis of pre-stack seismic volume in OVT domain

Abstract

The application provides a method for describing effective reservoirs based on OVT domain pre-stack seismic body five-dimensional analysis, comprising the following steps: dividing a research area according to different source azimuth angles, different stratigraphic dip angles and different sedimentary facies belt distributions; establishing a five-dimensional quantitative interpretation chart to obtain five-dimensional seismic stacking optimization parameters of each division scheme; performing regional stacking on the pre-stack seismic body of the research area to obtain post-stack seismic bodies of each division, and performing seismic attribute analysis; selecting multiple seismic attributes with the highest correlation with sand body thickness in the post-stack seismic body of each division scheme to obtain sand thickness regression formulas of each division scheme; calculating sand body thickness distribution maps under different division schemes and weighted sand thickness formulas; and establishing a final sand body thickness plane distribution map to calculate and count the thickness of each sand body unit. The application can obtain post-stack seismic bodies which can effectively identify effective reservoirs based on the sand body characteristics of the research area, and then accurately and finely describe the effective reservoirs.

Description

Technical Field

[0001] This invention relates to the field of petroleum geophysical exploration, and in particular to a method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain. Background Technology

[0002] OVT domain seismic data is a type of data processing suitable for wide-azimuth data, yielding three types of seismic data attributes: omnidirectional migration data attributes, gather data attributes containing anisotropic information, and anisotropic information data attributes (such as fast and slow velocity volumes). The concept of OVT was proposed by Vermeer in 1998, and Cary also proposed it in 1999, calling it the Common Offset Tile (COV). In 2000, Starr proposed methods for creating and migrating OVT gathers based on this. In 2001, Jenner and Williams explained the advantages of azimuth-based studies. In 2005, Vermeer elaborated on the processing methods of OVT domain seismic data. In 2016, Xiong Xingyin et al. achieved good results using omnidirectional data for fracture prediction. In 2018, Yin Xingyao et al. summarized the current state of research on five-dimensional seismic data interpretation.

[0003] During sedimentation, reservoirs are influenced by sedimentation and diagenesis, resulting in spatially diverse geophysical characteristics. Seismic waves propagating within strata are affected by multiple factors, exhibiting complex physical properties with significant lateral and longitudinal variations, demonstrating strong anisotropy. Therefore, conventional seismic reservoir descriptions cannot fully account for the influence of reservoir heterogeneity. OVT domain seismic data, however, undergoes anisotropic velocity correction during the formation of its omnidirectional data volumes, resulting in higher resolution and signal-to-noise ratio compared to conventional pre-stack migration data volumes. Based on the fundamental theory of seismic anisotropy, utilizing the azimuth anisotropy information from wide-azimuth seismic data allows for better analysis of the azimuthal differences in seismic properties such as travel time, velocity, amplitude, frequency, and phase of seismic waves propagating in the subsurface medium, thus identifying the anisotropic characteristics of sand bodies.

[0004] Chinese patent application CN 201811564393.3 discloses a reservoir prediction method based on wide-azimuth seismic data. This method first compares the relationship between reservoir seismic reflection coefficients and reservoir seismic amplitudes based on the petrophysical characteristics of the target stratigraphic segment to determine sensitive parameters reflecting reservoir seismic information; then, it performs forward modeling to establish the relationship between each reservoir azimuth and the seismic sensitive parameters; finally, it weights and processes seismic data from all reservoir azimuths to obtain multi-azimuth amplitude fusion data; and finally, it uses this multi-azimuth amplitude fusion data to compile a multi-azimuth amplitude fusion reservoir prediction plan, thus obtaining the reservoir size and distribution. This invention comprehensively considers all-round, multi-azimuth seismic data and geological data from wide-azimuth seismic data, performing weighted processing of seismic data from different locations and azimuths of the reservoir to obtain reservoir seismic amplitude fusion data highlighting the sensitive azimuths of the reservoir, thereby improving the accuracy of reservoir prediction. The previous invention used sensitive parameters to obtain reservoir amplitude fusion data that highlighted the sensitive orientation of the reservoir, but only considered the influence of a single factor. In contrast, this invention comprehensively considers three factors—sand body dip angle, azimuth angle, and sedimentary facies zone—to divide the study area into zones, and accurately describes the effective reservoir through multi-attribute fitting and joint calculation.

[0005] The journal article, "Sensitive Azimuth Sweet Spot Prediction Technology Based on OVT Domain Processing—Taking the Xiaoliangshan Depression in the Qaidam Basin as an Example," discusses an effective method for predicting the distribution of double sweet spots in dolomite using seismic attributes and fracture identification under sensitive azimuth. An azimuth-based stacking scheme is established based on the structural strike of the study area. Sensitive azimuth analysis is conducted using the stacked data, where the azimuth perpendicular to the fault strike is the sensitive azimuth for predicting small fault and fracture sweet spots, and the azimuth parallel to the fault strike is the sensitive azimuth for predicting the porosity properties of dolomite. Attribute analysis is then performed on the post-stack seismic data volumes with the selected sensitive azimuth to predict porosity and fractures. This technique only considers the sensitive information from a single azimuth, conducting attribute analysis and optimization to study reservoir size and distribution, lacking consideration of the influence of reservoir heterogeneity. This invention, however, comprehensively considers the influence of reservoir heterogeneity, obtaining the final sand body thickness planar distribution map through fitting calculations and regression analysis of seismic attributes from different scheme data volumes, thus characterizing the reservoir sand body boundaries.

[0006] The journal article, "Prediction Technology and Application of Dolomitic Reservoirs Based on OVT Domain Migration Data—Taking the Feng 3 Member in the Wuxia Area of ​​the Mahu Depression as an Example," discusses an effective method for quantitatively predicting the planar distribution of dolomitic "sweet spot" reservoirs using a combination of three geophysical techniques on OVT domain data volumes. A dynamic analysis and stacking method based on a shot-receiver offset-azimuth stacking template, driven by geological targets, is employed to generate pre-stack migration seismic data at different azimuth angles for predicting dolomitic reservoir thickness. Based on an elastic parameter cross-intersection analysis template, the increased ratio of Young's modulus (E) to Poisson's ratio (σ) is used to predict brittle development zones in slope-area dolomitic reservoirs. Starting from the wave equation, Hooke's law, and the definition of elastic parameters, the relationship between effective stress and P-wave and S-wave velocities is derived, and a new elastic parameter weighted method based on Young's modulus (E) and bulk modulus (K) is developed for predicting abnormal pressure zones, thereby improving the planar prediction accuracy of "sweet spot" reservoirs. This technology considers the weighted superposition of elastic parameters, conducts attribute analysis and optimization, and studies the reservoir distribution. However, it lacks consideration of the influence of reservoir heterogeneity. This invention comprehensively considers the influence of reservoir heterogeneity and derives the weighted sand thickness regression formula for each partition scheme through multivariate linear regression analysis, quantitatively calculating and statistically analyzing the thickness of each sand body unit.

[0007] The existing technologies described above are significantly different from this invention. A search reveals no literature in the XY category, indicating the innovativeness of this invention. Since no solution exists in the existing technologies to address the technical problem we seek, we have invented a novel method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic volumes in the OVT domain. Summary of the Invention

[0008] The purpose of this invention is to provide a method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, which can obtain post-stack seismic bodies that can effectively identify effective reservoirs based on the characteristics of sand bodies in the study area, and then perform accurate and detailed description of effective reservoirs.

[0009] The objective of this invention can be achieved through the following technical measures: a method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, wherein the method includes:

[0010] Step 1: Divide the study area into zones according to different provenance azimuths, different stratigraphic dips, and different sedimentary facies zones.

[0011] Step 2: Establish a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on source orientation, dip angle, and facies zone, and obtain the optimal parameters for five-dimensional seismic overlay for each zoning scheme;

[0012] Step 3: Perform pre-stack seismic bodies in the study area by region to obtain post-stack seismic bodies in each region and perform seismic attribute analysis.

[0013] Step 4: Select multiple seismic attributes with the highest correlation to sand body thickness from the post-stack seismic bodies of each partition scheme, and derive the sand thickness regression formula for each partition scheme.

[0014] Step 5: Calculate the sand body thickness distribution map under different zoning schemes, and the weighted sand thickness formula;

[0015] Step 6: Establish the final sand body thickness planar distribution map and calculate and statistically analyze the thickness of each sand body unit.

[0016] The objective of this invention can also be achieved through the following technical measures:

[0017] In step 1, the characteristics of sand bodies in the work area are analyzed. By summarizing the factors affecting the anisotropy of sand bodies on seismic reflection, the study area is divided into zones according to different source azimuths, different stratum dip angles, and different sedimentary facies zones.

[0018] In step 2, different source azimuth zoning is selected as zoning scheme one. The optimal azimuth zoning interval of the study area is analyzed, and the study area is divided into several regions. Combining single-well logging and lithological information, the seismic line number and trace number of single wells and the reservoir sand body depth of the target layer are statistically analyzed in each region. Combining the time-depth relationship of single wells, the sand body depth is converted into seismic time statistics. Five-dimensional pre-stack analysis is performed to optimize the azimuth-offset parameter range of single-well sand body depth in each region. The mean value is calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate based on source azimuth is established. Cross plot analysis is performed according to different azimuth ranges to obtain the optimal five-dimensional seismic overlay parameters for each region of zoning scheme one.

[0019] In step 2, different strata dip angles are selected as zoning scheme two. The optimal dip angle zoning interval for the study area is determined, dividing the study area into several regions. Combining single-well logging and lithological information, single-well seismic line and trace numbers and reservoir sand body depth statistics are performed in each region. Based on the time-depth relationship of single wells, the sand body depth is converted into seismic time statistics. Five-dimensional pre-stack analysis is performed to optimize the azimuth-offset parameter range of single-well sand body depth in each region. The mean value is calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on dip angle is established. Cross plot analysis is performed according to different dip angle ranges to obtain the optimal five-dimensional seismic overlay parameters for each region in zoning scheme two.

[0020] In step 2, different sedimentary facies zones were selected as zoning scheme three. The sedimentary facies of the study area were analyzed. Based on the sand body distribution characteristics, different microfacies were divided. The planar distribution characteristics of sedimentary facies in the study area were studied and analyzed, and sedimentary facies zones were divided. The study area was divided into several regions. Combining single-well logging and lithological information, the seismic line and trace numbers of single wells and the depth of reservoir sand bodies in the target interval were statistically analyzed in each region. Combining the time-depth relationship of single wells, the sand body depth was converted into seismic time statistics, the mean was calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on facies zones was established. Cross-plot analysis was performed according to the range of different facies zones to obtain the optimal parameters for five-dimensional seismic overlay of each region in zoning scheme three.

[0021] In step 3, for the five-dimensional seismic stacking optimization parameters of each zoning scheme, pre-stack OVT domain seismic body regional gathers are stacked to obtain post-stack seismic bodies for different zoning schemes; for the post-stack seismic bodies of different zoning schemes, seismic attribute analysis is performed to extract several attributes of the seismic bodies.

[0022] In step 4, the seismic attributes of each partition scheme are intersected with the sand body thickness of a single well to obtain the linear relationship formula and correlation coefficient between the seismic body and the sand thickness. For each partition scheme, the seismic attributes with the highest correlation to the sand body thickness are selected from the post-stack seismic bodies.

[0023] In step 4, a multivariate linear regression analysis of various attributes is performed on the linear relationship formulas of sand thickness for various seismic attributes that are most correlated with sand body thickness under different zoning schemes to obtain the sand thickness regression formula for each zoning scheme.

[0024] In step 5, the seismic attributes are fitted to the sand thickness regression formula for each zoning scheme to calculate the sand body thickness distribution map under different zoning schemes; the sand thickness data of each zoning scheme is intersected with the actual sand body thickness of a single well to obtain the correlation coefficient between the regression formula of different zoning schemes and the actual sand thickness.

[0025] In step 5, the regression formula coefficients of each partition scheme are weighted according to the ratio of the correlation coefficients, and the sum of the weighted coefficients is 1, so as to calculate the weighted sand thickness formula.

[0026] In step 6, the weighted sand body thickness is calculated based on the weighted sand thickness formula and the sand body thickness distribution map under different zoning schemes. The final sand body thickness planar distribution map is established, sandstone data is extracted, reservoir sand body boundaries are delineated, and the thickness of each sand body unit is calculated and statistically analyzed.

[0027] The objective of this invention can also be achieved through the following technical measures: a system for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, wherein the system describes effective reservoirs using a method based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain.

[0028] This invention presents a method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain. Addressing the lack of consideration for reservoir heterogeneity in existing technologies, this method incorporates analysis of multiple attributes, including source orientation, dip angle, and facies zone. Furthermore, this invention employs a multivariate linear regression fitting and joint calculation formula for these multiple attributes, comprehensively and quantitatively calculating the thickness of each sand body unit, thus avoiding the large errors associated with single-parameter optimization. Compared to existing technologies, this invention offers significant advantages: conventional methods for comprehensive reservoir description and reservoir thickness determination often suffer from large errors, frequently resulting in inconsistencies with the sandstone thickness in the well, and are inefficient. Conventional pre-stack seismic body attribute extraction methods for sand body identification can only roughly delineate sand body boundaries, leading to low accuracy in predicting sand body thickness. This invention's method, based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, provides post-stack seismic bodies that effectively identify effective reservoirs based on the sand body characteristics of the study area, enabling accurate and detailed descriptions of effective reservoirs. It is particularly effective in resolving uncertainties in reservoir description caused by sand body variations resulting from tectonic and sedimentary processes. Attached Figure Description

[0029] Figure 1 This is a plan view of a work area divided into groups at 60° intervals, based on an analysis of the azimuth angle in a specific embodiment of the present invention.

[0030] Figure 2 This is a cross-plot of a five-dimensional seismic azimuth-offset parameter optimization for wells within a work area, as shown in a specific embodiment of the present invention.

[0031] Figure 3 This is a plan view of a work area analyzed by tilt angle and grouped into sections at 10° intervals, according to a specific embodiment of the present invention.

[0032] Figure 4 This is a cross-plot of a five-dimensional seismic azimuth-offset parameter optimization for wells within a work area, as shown in a specific embodiment of the present invention.

[0033] Figure 5 This is a plan view showing the grouping and partitioning of sedimentary facies zones in a specific embodiment of the present invention.

[0034] Figure 6 This is a cross-plot of a five-dimensional seismic azimuth-offset parameter optimization for wells within a certain work area, as shown in a specific embodiment of the present invention.

[0035] Figure 7 This is a schematic diagram of the pre-stack OVT domain seismic body regional gather stacking window for each partitioning scheme in a specific embodiment of the present invention;

[0036] Figure 8 This is a map showing nine seismic attributes with the highest correlation to sand body thickness in a specific embodiment of the present invention;

[0037] Figure 9 This is a diagram illustrating the sand thickness regression formula for each partitioning scheme in a specific embodiment of the present invention;

[0038] Figure 10 This is a diagram showing the sand body thickness distribution calculated using the sand thickness regression formula for each partitioning scheme in a specific embodiment of the present invention.

[0039] Figure 11 This is a weighted sand thickness formula diagram in a specific embodiment of the present invention;

[0040] Figure 12 This is a weighted regression sand body thickness planar distribution diagram in a specific embodiment of the present invention;

[0041] Figure 13 This is a flowchart of a specific embodiment of the method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to the present invention. Detailed Implementation

[0042] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0043] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0044] Conventional reservoir seismic prediction methods often consider sensitive information from a single azimuth or involve weighted superposition of elastic parameters for attribute analysis and optimization. These methods fail to adequately account for the heterogeneity of the reservoir, resulting in insufficient clarity regarding internal reflection characteristics and only providing a rough delineation of sand body boundaries. Furthermore, they neglect multi-factor coupling analysis, leading to large errors and low accuracy in predicting effective reservoir thickness. This invention proposes a method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic volumes in the OVT domain.

[0045] The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain of this invention mainly includes:

[0046] 1. Establishing a five-dimensional quantitative interpretation map of sandstone and conglomerate bodies based on source azimuth, dip, and facies zones: This technique, under full stacking of source-receiver distances, fully extracts information on the variation of velocity, amplitude, frequency, and phase attributes with azimuth in OVT seismic data. The study area is grouped and analyzed according to dip, azimuth, and microfacies characteristics of sedimentary facies. The azimuth-offset parameter of sampling well sites is optimized for each zone. Virtual well sites are used for sampling in some areas to obtain sensitive stacking parameters for cross-plot analysis, resulting in optimized stacking maps for each zone. Combined with the characteristics of actual geological targets in the work area, OVT gathers are stacked as needed, improving some stacking effects and providing high-quality pre-stack seismic gathers for subsequent OVT domain seismic attribute analysis.

[0047] 2. Multi-attribute fitting + joint calculation reservoir prediction method: The pre-stack seismic bodies of the study area are superimposed on the optimized maps established in Method 1 for each zone, and post-stack seismic bodies of each zone are obtained for seismic attribute analysis. Seismic attribute analysis technology can be summarized as extracting hidden information from seismic data using seismic attributes as a carrier, and converting this information into information related to lithology, physical properties, or reservoir parameters that can directly serve geological interpretation or reservoir engineering. Seismic data is extracted from the post-stack seismic bodies of each zone. By fitting single-well data with sand body thickness, multiple attribute bodies with the highest correlation to sand thickness are selected, and multiple linear regression is performed to obtain multiple linear regression formulas for sand body thickness under different zoning schemes in the study area. Sand body thickness distribution maps obtained from different zoning schemes are calculated using these formulas. By comparing the correlation coefficients between sand thickness distribution maps of different zoning schemes and actual sand thickness on the well, the weighted combination of formula coefficients is used to derive the final weighted sand thickness formula. The sand thickness is then calculated using the formula on the sand thickness maps obtained from each zoning scheme, and the final sand thickness planar distribution map is established to delineate the reservoir sand body boundary. The thickness of each sand body unit is calculated and statistically analyzed to accurately describe the effective reservoir.

[0048] The following are several specific embodiments of the application of the present invention.

[0049] Example 1

[0050] In a specific embodiment 1 of the present invention, such as Figure 13 As shown, Figure 13 This is a flowchart of the method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, according to the present invention. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain includes:

[0051] Step 1: Analyze the characteristics of sand bodies in the work area, summarize the factors affecting the anisotropy of sand bodies on seismic reflection, and divide the study area into zones according to different source azimuths, different stratum dip angles, and different sedimentary facies zones.

[0052] Step 2: Select different source azimuth zoning as Zoning Scheme 1, analyze the optimal azimuth zoning interval of the study area, and divide the study area into several regions. Combining single-well logging and lithological information, perform single-well seismic line and trace number statistics and target layer reservoir sand body depth statistics in each region. Combining the time-depth relationship of single wells, convert the sand body depth into seismic time statistics, and perform five-dimensional pre-stack analysis to optimize the azimuth-offset parameter range of single-well sand body depth in each region, calculate the mean value, and perform cross plot analysis according to different azimuth ranges to obtain the optimal five-dimensional seismic overlay parameters for each region of Zoning Scheme 1.

[0053] Step 3: Select different formation dip angles as zoning scheme two, and optimize the dip angle zoning interval of the study area, dividing the study area into several regions. Combining single-well logging and lithological information, perform single-well seismic line and trace number statistics and target layer reservoir sand body depth statistics in each region. Combine the time-depth relationship of single wells to convert sand body depth into seismic time statistics, and perform five-dimensional pre-stack analysis to optimize the azimuth-offset parameter range of single-well sand body depth in each region, calculate the mean value, and perform cross plot analysis according to different dip angle ranges to obtain the optimized five-dimensional seismic overlay parameters for each region of zoning scheme two.

[0054] Step 4: Selecting different sedimentary facies zones as zoning scheme three, analyze the sedimentary facies of the study area, divide different microfacies according to the sand body distribution characteristics, study and analyze the planar distribution characteristics of sedimentary facies in the study area, and divide the study area into several regions. Combining single-well logging and lithological information, perform single-well seismic line and trace number statistics and target layer reservoir sand body depth statistics in each region. Combining the time-depth relationship of single wells, convert the sand body depth into seismic time statistics, calculate the mean, and perform cross plot analysis according to different facies zone ranges to obtain the optimal five-dimensional seismic overlay parameters for each region of zoning scheme three.

[0055] Step 5: For the optimal parameters of five-dimensional seismic stacking for each zoning scheme, perform pre-stack OVT domain seismic body regional gather stacking to obtain post-stack seismic bodies for different zoning schemes.

[0056] Step 6: Extract several attributes of the post-stack seismic bodies for different zoning schemes.

[0057] Step 7: Perform cross-plots between the seismic attributes and sand body thickness of each zoning scheme and the single-well top sand body thickness to derive the linear relationship formula and correlation coefficient between the seismic body and sand thickness. For each zoning scheme, select 9 seismic attributes with the highest correlation to sand body thickness from the post-stack seismic body. These seismic attributes include: mean positive peak value, geometric mean, lower loop region, cycle symmetry, harmonic mean, mean duration of positive cycle, dip angle seismic body extract value, interval mean arithmetic, mean cycle duration, minimum cycle duration, mean negative wave trough value, mean roughness value, mean roughness value between zero crosses, upper loop region, mean amplitude, mean peak value between zero crosses, sum of negative amplitudes, and most... Minimum amplitude, upper loop skew, average magnitude, arc length, total magnitude, number of zero crosses, average duration of negative cycles, average investment, number of positive zero crosses, number of negative zero crosses, average negative amplitude, standard deviation of amplitude, RMS amplitude, average positive amplitude, maximum quantity, maximum amplitude, average energy, duration of upper cycle, sum of positive amplitudes, median, total energy at maximum amplitude, total amplitude, duration of maximum cycle, average instantaneous phase, isochron thickness window length, cycle kurtosis, standard deviation of loop duration, ratio of positive to negative of reduced operation duration, average instantaneous frequency, average peak value, half energy, threshold greater than 0, time at minimum amplitude.

[0058] Step 8: Perform multivariate linear regression analysis on the linear relationship formulas of sand thickness for the nine seismic attributes that are most correlated with sand body thickness for different zoning schemes, and derive the sand thickness regression formula for each zoning scheme.

[0059] Step 9: For the sand thickness regression formula of each zoning scheme, perform seismic attribute fitting calculation to calculate the sand body thickness distribution map under different zoning schemes.

[0060] Step 10: Cross the sand thickness data of each zoning scheme with the actual sand body thickness of a single well to obtain the correlation coefficient between the regression formula of different zoning schemes and the actual sand thickness.

[0061] Step 11: According to the ratio of the correlation coefficients, the regression formula coefficients of each partition scheme are weighted, and the sum of the weighted coefficients is 1, so as to calculate the weighted sand thickness formula.

[0062] Step 12: Calculate the weighted sand body thickness based on the weighted sand thickness formula and the sand body thickness distribution map under different zoning schemes, establish the final sand body thickness planar distribution map, extract sandstone data, delineate reservoir sand body boundaries, and calculate and statistically analyze the thickness of each sand body unit.

[0063] Example 2

[0064] In a specific embodiment 2 of the present invention, the invention is applied. Figure 1The map shows the regional division of a certain area based on azimuths of different source directions at 60° intervals. Different legend colors are used to delineate the area range.

[0065] Figure 2 This is a plot showing the optimal azimuth-offset parameters for dividing a region into zones based on different azimuth ranges. The inner frame boundary in the plot represents the optimal range for each zone.

[0066] Figure 3 The map shows the division of a region into areas at 15° intervals with different tilt angles, using different legend colors to delineate the area boundaries.

[0067] Figure 4 This is a plot showing the optimal azimuth-offset parameters for dividing a region into zones based on different tilt angles. The inner frame boundaries in the plot represent the optimal range for each zone.

[0068] Figure 5 The map shows the regional division of a certain area based on the distribution of different sedimentary facies zones, using different legend colors to delineate the area range.

[0069] Figure 6 This is a cross-plot of preferred azimuth-offset parameters for dividing a region into zones based on different sedimentary facies. The inner frame boundary in the plot represents the preferred range for each zone.

[0070] Figure 7 Pre-stack OVT domain seismic volume regional gather stacking windows are used to optimize the five-dimensional seismic stacking parameters for each partition scheme.

[0071] Figure 8 These are images of nine seismic attributes that are most correlated with sand body thickness.

[0072] Figure 9 Here is the regression formula for sand thickness in each partition scheme.

[0073] Figure 10 Calculate the sand body thickness distribution map using the sand thickness regression formula for each partition scheme.

[0074] Figure 11 This is a diagram of the weighted sand thickness formula. The letter values ​​illustrate the weighting process and calculations.

[0075] Figure 12 This is a planar distribution map of the thickness of the sand body based on weighted regression. The black dashed line represents the boundary line of the sand body.

[0076] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0077] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, characterized in that, The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain includes: Step 1: Divide the study area into zones according to different provenance azimuths, different stratigraphic dips, and different sedimentary facies zones; Step 2: Establish a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on source orientation, dip angle, and facies zone, and obtain the optimal parameters for five-dimensional seismic overlay for each zoning scheme; Step 3: Perform pre-stack seismic bodies in the study area by region to obtain post-stack seismic bodies in each region and perform seismic attribute analysis. Step 4: Select multiple seismic attributes with the highest correlation to sand body thickness from the post-stack seismic bodies of each partition scheme, and derive the sand thickness regression formula for each partition scheme. Step 5: Calculate the sand body thickness distribution map under different zoning schemes, and the weighted sand thickness formula; Step 6: Establish the final sand body thickness planar distribution map and calculate and statistically analyze the thickness of each sand body unit.

2. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 1, the characteristics of sand bodies in the work area are analyzed. By summarizing the factors affecting the anisotropy of sand bodies on seismic reflection, the study area is divided into zones according to different source azimuths, different stratum dip angles, and different sedimentary facies zones.

3. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 2, different source azimuth zoning is selected as zoning scheme one. The optimal azimuth zoning interval of the study area is analyzed, and the study area is divided into several regions. Combining single-well logging and lithological information, the seismic line number and trace number of single wells and the reservoir sand body depth of the target layer are statistically analyzed in each region. Combining the time-depth relationship of single wells, the sand body depth is converted into seismic time statistics. Five-dimensional pre-stack analysis is performed to optimize the azimuth-offset parameter range of single-well sand body depth in each region. The mean value is calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate based on source azimuth is established. Cross plot analysis is performed according to different azimuth ranges to obtain the optimal five-dimensional seismic overlay parameters for each region of zoning scheme one.

4. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 3, characterized in that, In step 2, different strata dip angles are selected as zoning scheme two. The optimal dip angle zoning interval for the study area is determined, dividing the study area into several regions. Combining single-well logging and lithological information, single-well seismic line and trace numbers and reservoir sand body depth statistics are performed in each region. Based on the time-depth relationship of single wells, the sand body depth is converted into seismic time statistics. Five-dimensional pre-stack analysis is performed to optimize the azimuth-offset parameter range of single-well sand body depth in each region. The mean value is calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on dip angle is established. Cross plot analysis is performed according to different dip angle ranges to obtain the optimal five-dimensional seismic overlay parameters for each region in zoning scheme two.

5. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 4, characterized in that, In step 2, different sedimentary facies zones were selected as zoning scheme three. The sedimentary facies of the study area were analyzed. Based on the sand body distribution characteristics, different microfacies were divided. The planar distribution characteristics of sedimentary facies in the study area were studied and analyzed, and sedimentary facies zones were divided. The study area was divided into several regions. Combining single-well logging and lithological information, the seismic line and trace numbers of single wells and the depth of reservoir sand bodies in the target interval were statistically analyzed in each region. Combining the time-depth relationship of single wells, the sand body depth was converted into seismic time statistics, the mean was calculated, and a five-dimensional quantitative interpretation chart of sandstone and conglomerate bodies based on facies zones was established. Cross-plot analysis was performed according to the range of different facies zones to obtain the optimal parameters for five-dimensional seismic overlay of each region in zoning scheme three.

6. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 3, for the five-dimensional seismic stacking optimization parameters of each zoning scheme, pre-stack OVT domain seismic body regional gathers are stacked to obtain post-stack seismic bodies for different zoning schemes; for the post-stack seismic bodies of different zoning schemes, seismic attribute analysis is performed to extract several attributes of the seismic bodies.

7. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 4, the seismic attributes of each partition scheme are intersected with the sand body thickness of a single well to obtain the linear relationship formula and correlation coefficient between the seismic body and the sand thickness. For each partition scheme, the seismic attributes with the highest correlation to the sand body thickness are selected from the post-stack seismic bodies.

8. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 7, characterized in that, In step 4, a multivariate linear regression analysis of various attributes is performed on the linear relationship formulas of sand thickness for various seismic attributes that are most correlated with sand body thickness under different zoning schemes to obtain the sand thickness regression formula for each zoning scheme.

9. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 5, the seismic attributes are fitted to the sand thickness regression formula for each zoning scheme to calculate the sand body thickness distribution map under different zoning schemes; the sand thickness data of each zoning scheme is intersected with the actual sand body thickness of a single well to obtain the correlation coefficient between the regression formula of different zoning schemes and the actual sand thickness.

10. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 9, characterized in that, In step 5, the regression formula coefficients of each partition scheme are weighted according to the ratio of the correlation coefficients, and the sum of the weighted coefficients is 1, so as to calculate the weighted sand thickness formula.

11. The method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain according to claim 1, characterized in that, In step 6, the weighted sand body thickness is calculated based on the weighted sand thickness formula and the sand body thickness distribution map under different zoning schemes. The final sand body thickness planar distribution map is established, sandstone data is extracted, reservoir sand body boundaries are delineated, and the thickness of each sand body unit is calculated and statistically analyzed.

12. A system for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain, characterized in that, The system for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain uses the method for describing effective reservoirs based on five-dimensional analysis of pre-stack seismic bodies in the OVT domain as described in any one of claims 1-11.

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