Evaluation method of narrow channel dominant sand body based on quantitative description of seismic root mean square amplitude attribute
Patent Information
- Application Number
- CN202510547295.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-28
- Publication Date
- 2026-10-30
AI Technical Summary
[0011]为了克服上述现有技术中存在的缺陷和不足，本发明提供了一种基于地震均方根振幅属性定量刻画的窄河道优势砂体评价方法，本发明的发明目的在于解决现有评价方法的实用性和可靠性不足无法真实反映优势砂体的特征的问题
[0033]更进一步优选的，S3步骤中，对单井识别砂体与地震识别砂体进行统计分析，计算井震预测匹配率。
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Abstract
Description
Technical Field
[0001] This invention relates to the field of oil and gas field exploration and development technology, and more specifically to a method for evaluating dominant sand bodies in narrow channels based on the quantitative characterization of seismic root mean square amplitude properties. Background Technology
[0002] Currently, the development of tight sandstone gas has become one of the hottest topics in the global oil and gas industry. my country has abundant tight gas resources, accounting for 10% of global tight gas resources, distributed across major basins. Large tight gas fields in my country are mainly located in the Ordos Basin, Sichuan Basin, and Tarim Basin, primarily situated in the Carboniferous, Permian, Triassic, Jurassic, Cretaceous, and Paleogene-Neogene strata. China's tight sandstone gas resources exhibit diverse geological characteristics, including thick fine-grained sandstone layers, widespread reservoir distribution, poor layer properties, strong heterogeneity, thin layers, poor continuity, complex post-construction structures, and complex groundwater and hydrogeological conditions. Traditional evaluation techniques often fail to accurately reflect the reserves and development potential of tight sandstone gas; therefore, developing new evaluation techniques for advantageous sandstone bodies is particularly important.
[0003] Channel sandbodies are considered excellent oil and gas reservoirs, making channel sandbody characterization a crucial research area in oil and gas exploration and development. Advances in geophysical techniques and geological modeling methods have significantly improved channel sandbody characterization. Typically, a combination of seismic exploration, well logging data, and high-resolution 3D geological modeling techniques is used to finely characterize channel sandbodies. Seismic attribute analysis provides strong support for identifying the boundaries and internal structure of channel sandbodies. Furthermore, the application of sedimentary facies analysis and stratigraphic correlation techniques has led to a deeper understanding of the formation environment and sedimentary processes of channel sandbodies. The evaluation techniques for tight sandstone gas-dominant sandbodies have undergone several stages of development.
[0004] Early research focused primarily on geological surveys and basic lithological analysis, obtaining the physical properties and geological characteristics of tight sandstone through drilling sampling and well logging data. With technological advancements, numerical simulation and geophysical exploration methods have been gradually introduced, especially in three-dimensional geological modeling and fluid dynamics simulation. These methods can help assess the distribution, permeability, and gas production potential of gas reservoirs.
[0005] For narrow channels, integrated geological and geophysical methods are typically used, combining dense well logging data to accurately analyze the longitudinal and lateral variations of sand bodies and their physical properties. High-resolution seismic technology is used to capture the fine structure of sand bodies in narrow channels, and small-scale seismic reflection profiles can help identify the boundaries and internal features of narrow channels to overcome challenges such as their small size and complex morphology.
[0006] Previous research primarily relied on geological surveys and basic lithological analysis, using drilling sampling and well logging data to obtain the physical properties and geological characteristics of tight sandstone. With technological advancements, numerical simulation and geophysical exploration methods have been gradually introduced, especially in three-dimensional geological modeling and fluid dynamics simulation. These methods can help assess the distribution, permeability, and gas production potential of gas reservoirs. As the exploration and development of tight gas reservoirs continues, and given the complex geological structures in some areas, traditional methods for identifying dominant sandstone bodies are no longer sufficient to meet the current needs of tight gas reservoir exploration and development. The main problems with dominant sandstone body evaluation techniques are as follows:
[0007] First, traditional methods often rely on drilling, geological surveys and single well logging data, which cannot fully reflect the characteristics of complex geological bodies, especially in tight sandstone gas reservoirs where geological structures and physical property changes are more complex.
[0008] Secondly, the indicator systems of many traditional evaluation methods are relatively simple and difficult to adapt to the needs of different geological conditions, resulting in insufficient applicability and reliability of the evaluation results.
[0009] Third, the traditional method does not combine well-seismic analysis closely enough, which affects the analysis of the spatial distribution, thickness variation and lithological characteristics of the reservoir, and cannot truly reflect the characteristics of the dominant sand bodies.
[0010] The channel sandstone sediments of the Shaximiao Formation in Shunan are characterized by deltaic plain-front distributary facies. Channel development exhibits typical features of multiple vertical phases, complex lateral stacking, thin sand bodies in some areas, and significant variations in physical properties. Furthermore, the quality of seismic data is poor, and well logging data is lacking. Previous channel identification results based on conventional, single-attribute methods such as amplitude and coherence show low agreement with drilling data, resulting in an unclear understanding of the detailed characterization of channel sand bodies in the study area. However, the region currently exhibits good hydrocarbon shows and has significant exploration and development potential, necessitating efforts to address the aforementioned challenges. Summary of the Invention
[0011] To overcome the defects and shortcomings of the existing technologies, this invention provides a method for evaluating dominant sand bodies in narrow channels based on the quantitative characterization of seismic root-mean-square amplitude attributes. The purpose of this invention is to address the problem that existing evaluation methods lack practicality and reliability and cannot accurately reflect the characteristics of dominant sand bodies. This invention primarily uses a well-seismic combined approach to conduct dominant sand body evaluation research. First, sandstone on a single well is identified, and sandstone velocity is analyzed to clarify the sand body type. Seismic composite calibration clarifies the seismic reflection characteristics of different types of sand bodies. By identifying and numbering sand bodies on a single well, well-seismic calibration is performed based on the single well to clarify the longitudinal distribution characteristics of the sand bodies. Then, the planar distribution characteristics of channel sand bodies in different phases of the study area are characterized by seismic root-mean-square amplitude attributes, and corresponding seismic attribute parameters are extracted. Considering the planar distribution characteristics, corresponding seismic attribute parameters, and geological parameters, the distribution of dominant sand bodies in the study area is evaluated, and a dominant sand body evaluation standard is constructed. Based on the constructed dominant sand body evaluation standard, characteristic parameters such as sand body physical properties, thickness, and toothing rate are superimposed. SPSS software is used to analyze the correlation between various parameters, and a linear discriminant formula for reservoir type is established based on this. The evaluation of dominant sand bodies in narrow channels was finally completed. This invention not only provides a theoretical basis for the prediction of high-quality reservoirs, but also lays the theoretical foundation for the efficient development of tight gas.
[0012] To address the problems existing in the prior art, the present invention is achieved through the following technical solution.
[0013] The first aspect of this invention provides a method for evaluating dominant sand bodies in narrow channels based on the quantitative characterization of earthquake root-mean-square amplitude properties. This evaluation method includes the following steps:
[0014] S1. Identify and analyze sand bodies in individual wells, and determine the distribution of sand bodies in individual wells by combining well logging curves and core observations; analyze sand body velocities to clarify sand body types; and clarify the seismic reflection characteristics of different types of sand bodies through seismic synthetic calibration.
[0015] S2. Based on single wells, sand bodies are identified and numbered. Through well-seismic calibration, the seismic response characteristics and longitudinal distribution characteristics of various sand bodies are clarified.
[0016] S3. Utilize the root mean square properties of earthquakes to finely characterize the planar distribution characteristics of sand bodies in different secondary channels in the study area, and predict the planar distribution of sand bodies.
[0017] S4. Statistically analyze the absolute value of the root mean square amplitude of the sand body, the thickness of the sand body, and the toothing rate to determine whether the sand body is developed. Combine this with typical wells for verification and dissection to select well-developed sand bodies.
[0018] S5. Analyze the sand bodies selected in step S4, and statistically analyze the physical properties, thickness, serration rate and root mean square amplitude of each sand body. Perform cross-plot analysis on each pairwise to obtain the evaluation criteria for dominant sand bodies.
[0019] S6. Based on the evaluation criteria for advantageous sand bodies constructed in step S5, superimpose sand body physical properties, thickness, toothing rate and root mean square amplitude of seismic waves, analyze the correlation between the parameters, and establish a linear discriminant for reservoir type.
[0020] Further preferred, in step S6, the established linear discriminant for reservoir type is specifically as follows:
[0021] Class I sand:
[0022] Class II sand:
[0023] Class III sand
[0024] In the formula, D is the sand body thickness, G is the sand body serration rate, and RMS is the root mean square value of the seismic data. Porosity.
[0025] More preferably, the thickness of the sand body of Class I sand is between 11.375m and 31m, the serration rate is between 24.1% and 41.2%, the porosity is between 7% and 10.5%, and the root mean square amplitude value is between 2719 and 6420.
[0026] The thickness of the Class II sand bodies ranges from 8.625 m to 18.36 m, the serration rate ranges from 30.8% to 40.9%, the porosity ranges from 5.9% to 7.9%, and the root mean square amplitude ranges from 2612 to 3251.
[0027] Class III sand bodies are the best, with a thickness between 4.45m and 10.8m, a toothing rate between 32.4% and 50.5%, a porosity between 5% and 7.1%, and a root mean square amplitude value between 290 and 3169.
[0028] In an even more preferred embodiment, in step S6, SPSS software is used to analyze the correlation between various parameters and establish a linear discriminant for reservoir type.
[0029] In a further preferred embodiment, in step S1, the sand bodies of a single well are identified and analyzed, and the distribution of the sand bodies in a single well is determined by combining the logging curves and core observations. Specifically, this means that the sand bodies of a single well are identified based on the characteristics of the logging curves of a single well and the description results of core observations of typical wells.
[0030] In a further preferred embodiment, step S1 identifies two types of sand bodies by analyzing the velocities of sandstone and mudstone: high-velocity sandstone and low-velocity sandstone.
[0031] In a further preferred embodiment, in step S2, the low-velocity sand body exhibits a "peak-valley-bottom-peak" seismic response characteristic, while the high-velocity sand body exhibits a "peak-valley" seismic response characteristic, through synthetic record calibration and forward modeling.
[0032] In a further optimized step, step S3 utilizes the root mean square seismic properties to finely characterize the planar distribution features of sand bodies in different secondary channels within the study area, and extracts the corresponding seismic attribute parameters. By combining the planar distribution features and the corresponding seismic attribute parameters, the planar distribution of sand bodies is predicted.
[0033] In a further preferred embodiment, step S3 involves statistical analysis of sand bodies identified in a single well and sand bodies identified by seismic activity to calculate the well-seismic prediction matching rate.
[0034] More preferably, the sand properties described in steps S5 and S6 include sand porosity.
[0035] More preferably, the tooth formation rate mentioned in steps S5 and S6 is characterized by three logging parameters, namely tooth amplitude, tooth distribution density, and tooth distribution frequency.
[0036] Compared with the prior art, the beneficial technical effects of the present invention are as follows:
[0037] This invention utilizes a combined well-seismic approach to study dominant sand bodies. First, sandstone on a single well is identified, and sandstone velocity analysis clarifies the sand body type. Seismic composite calibration identifies the seismic reflection characteristics of different sand body types. By identifying and numbering sand bodies on a single well, well-seismic calibration is performed to clarify the vertical distribution characteristics of the sand bodies. Then, the root mean square amplitude of the seismic waves is optimized to characterize the planar distribution characteristics of channel sand bodies in different phases of the Shaximiao Formation in the study area, and corresponding seismic attribute parameters are extracted. Considering the planar distribution characteristics, corresponding seismic attribute parameters, and geological parameters (sand body porosity, permeability, toothing rate, and sand body thickness), the distribution of dominant sand bodies in the Shunan Datachang Shaximiao Formation is evaluated, and a dominant sand body evaluation standard is constructed. Based on the constructed dominant sand body evaluation standard, sand body physical properties, thickness, toothing rate, and other characteristic parameters are superimposed, and the correlation between various parameters is analyzed using SPSS software. Based on this, a linear discriminant formula for reservoir type is established. Finally, the evaluation of narrow-channel dominant sand bodies is completed. The findings of this study not only provide a theoretical basis for predicting high-quality reservoirs, but also lay a theoretical foundation for the efficient development of tight gas. Attached Figure Description
[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0039] Figure 1 This is a velocity-depth intersection diagram of the T19-H1 low-velocity sandstone.
[0040] Figure 2 This is a velocity-depth intersection diagram of the T19-H1 high-speed sandstone;
[0041] Figure 3 This is a velocity-depth intersection diagram of low-velocity sandstone in the T17-H1 series.
[0042] Figure 4 This is a velocity-depth intersection diagram of the T17-H1 high-speed sandstone;
[0043] Figure 5 This is a velocity-depth intersection diagram of T23 low-velocity sandstone;
[0044] Figure 6 This is a velocity-depth intersection diagram of T23 high-speed sandstone.
[0045] Figure 7 This is a velocity-depth intersection diagram of T20 low-velocity sandstone.
[0046] Figure 8 This is a velocity-depth intersection diagram of T20 high-speed sandstone.
[0047] Figure 9 This is a velocity-depth intersection diagram of low-velocity sandstone in the T15-H1 series.
[0048] Figure 10 This is a velocity-depth intersection diagram of the T15-H1 high-speed sandstone.
[0049] Figure 11 This is a velocity-depth intersection diagram of T-New 6 low-velocity sandstone;
[0050] Figure 12 This is a velocity-depth intersection diagram of the T-Xin 6 high-speed sandstone.
[0051] Figure 13 Logging and seismic response characteristic maps of two types of sand bodies;
[0052] Figure 14 Seismic calibration maps for Sha-1 and Sha-2 sections;
[0053] Figure 15 A planar comparison diagram of different seismic attributes;
[0054] Figure 16 Root mean square attribute diagram of an earthquake in section 5;
[0055] Figure 17 Root mean square attribute map of the Sha-2 segment earthquake;
[0056] Figure 18 Planar prediction diagram of the sand body in section 1;
[0057] Figure 19 This is a plan view of the sand body in the second section of the Shahejie Formation.
[0058] Figure 20 Statistical chart of average sandstone thickness in three sets of sand bodies in Section 1 of the sandstone;
[0059] Figure 21 Statistical chart of average toothing rate of three sets of sand bodies in Section 1 of the sand;
[0060] Figure 22 A statistical chart showing the average sandstone thickness of nine sand bodies in the Sha-2 section;
[0061] Figure 23 A statistical chart showing the average toothing rate of the nine sand bodies in the second section of the Shahejie Formation.
[0062] Figure 24 This is a comprehensive columnar section of the No. 2 sand group of well T20;
[0063] Figure 25 This is a seismic profile of the T20-T23-T17-H1 wells.
[0064] Figure 26 This is a comprehensive columnar section of the No. 8 sand group in well T23;
[0065] Figure 27 Seismic profile of wells T23-TX6H1;
[0066] Figure 28 This is a comprehensive columnar section of the No. 10 sand group of well T15-H1;
[0067] Figure 29 Seismic calibration map of sand group No. 10 in well T15-H1;
[0068] Figure 30 This is a comprehensive columnar section of the No. 11 sand group of well TX6H1;
[0069] Figure 31 Seismic profile of wells T23-T17H-1-TX6H1;
[0070] Figure 32 This is a diagram showing the intersection of porosity and sand body thickness.
[0071] Figure 33 This is a diagram showing the intersection of serration rate and sand body thickness.
[0072] Figure 34 This is a cross-plot of porosity and root mean square amplitude. Detailed Implementation
[0073] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0074] Example 1
[0075] As a preferred embodiment of the present invention, this embodiment discloses a method for evaluating dominant sand bodies in narrow channels based on the quantitative characterization of earthquake root-mean-square amplitude attributes. The evaluation method includes the following steps:
[0076] S1. Identify and analyze sand bodies in individual wells, and determine the distribution of sand bodies in individual wells by combining well logging curves and core observations; and analyze sand body velocity to clarify the sand body type (refer to the appendix of the instruction manual). Figure 1 - Appendix Figure 12 As shown, two types of sand bodies were identified: high-velocity sandstone and low-velocity sandstone. Seismic reflection characteristics of different types of sand bodies were clarified through seismic synthesis calibration.
[0077] S2. Identify and number sand bodies based on a single well, and calibrate them using well-seismic calibration (as per the instruction manual). Figure 13 As shown in the figure), the seismic response characteristics and longitudinal distribution characteristics of various sand bodies are clearly defined (as shown in the appendix of the instruction manual). Figure 14 (As shown); Specifically, it was determined that three sets of sand bodies were longitudinally developed in the first section of the Shahejie Formation and nine sets of sand bodies were longitudinally developed in the second section of the Shahejie Formation.
[0078] S3. Utilize the root mean square properties of seismic data to finely characterize the planar distribution characteristics of different secondary channel sand bodies in the study area (as shown in the appendix to the instruction manual). Figure 15 Appendix Figure 16 and attached Figure 17 As shown in the diagram, the planar distribution of the sand body is predicted (as per the appendix of the instruction manual). Figure 18 and attached Figure 19 As shown, 12 sets of sand body planar predictions were completed in the study area;
[0079] S4. Calculate the absolute value of the root mean square amplitude of the sand body's seismic activity, the sand body thickness, and the serration rate to determine whether the sand body is developed (as per the instruction manual). Figure 20 Appendix Figure 21 Appendix Figure 22 and attached Figure 23 (as shown), and verified by dissection using typical wells (as per the instruction manual). Figure 24 Appendix Figure 25 Appendix Figure 26 Appendix Figure 27 Appendix Figure 28 Appendix Figure 29 Appendix Figure 30 and attached Figure 31 (As shown), select the well-developed sand bodies;
[0080] S5. Analyze the sand bodies selected in step S4, statistically analyze the physical properties, thickness, serration rate, and root mean square amplitude of each sand body, and perform pairwise cross plot analysis to obtain the evaluation criteria for dominant sand bodies (as shown in the appendix of the instruction manual). Figure 32 Appendix Figure 33 and attached Figure 34 (as shown);
[0081] S6. Based on the dominant sandbody evaluation criteria constructed in step S5, superimposed sandbody properties, thickness, toothing rate, and root mean square amplitude of seismic data are used. SPSS software is employed to analyze the correlation between these parameters, establishing a linear discriminant formula for reservoir type. The established linear discriminant formula for reservoir type is as follows:
[0082] Class I sand:
[0083] Class II sand:
[0084] Class III sand
[0085] In the formula, D is the sand body thickness, G is the sand body serration rate, and RMS is the root mean square value of the seismic data. Porosity.
[0086] Example 2
[0087] As another preferred embodiment of the present invention, this embodiment is a further detailed supplement and explanation of the technical solution of the present invention based on the above embodiment 1. In this embodiment, step S1 is further explained. In step S1, taking the Guanyin Data area as an example, the sand body of a single well is first identified based on the characteristics of the single-well logging curve and the observation and description results of typical well core samples. Because when seismic waves encounter the formation interface, reflection and refraction phenomena will occur. The strength of the reflected wave is closely related to the impedance difference on the interface. Therefore, the sandstone velocity of wells T19-H1, T17-H1, T23, T20, T15-H1 and T Xin 6 in the study area is statistically analyzed with the corresponding sandstone and nearby mudstone velocities, as shown in the appendix to the specification. Figure 1 To be continued Figure 12 As shown, the velocities of sandstone and mudstone in the study area are generally between 4000-5000 μm / s, increasing from deep to shallow. A small number of sandstone bodies have velocities higher than those of nearby mudstone, while most sandstone bodies have velocities higher than those of nearby mudstone. High-velocity sandstone is distributed from deep to shallow without any obvious pattern. Therefore, it is further clarified that the sandstone of the Shaximiao Formation in the study area is mainly of two types: low-velocity sandstone and high-velocity sandstone.
[0088] Example 3
[0089] As another preferred embodiment of the present invention, this embodiment further supplements and elaborates on the technical solution of the present invention based on the above embodiment 1 or embodiment 2. This embodiment further elaborates on step S2 based on the above embodiment 1 or embodiment 2. In step S2, through synthetic record calibration and forward modeling, it is clarified that low-resistivity sand bodies exhibit "top-valley-bottom-peak" seismic response characteristics, while high-resistivity sand bodies exhibit "top-peak-bottom-valley" seismic response characteristics. When seismic waves encounter a stratigraphic interface, reflection and refraction phenomena occur. The strength of the reflected wave is closely related to the impedance difference at the interface. The reflection coefficient (R) of the stratigraphic layer is a quantitative description of the seismic reflection intensity, usually determined by the impedance of the stratigraphic layer. If the impedance difference between the two stratigraphic layers is large, a strong reflected wave will be generated; conversely, if the impedance difference is small, the reflected wave will be weak. When seismic waves propagate from low-velocity mudstone to high-velocity sandstone, the amplitude of the reflected wave is usually large because the impedance difference between the low-velocity mudstone with lower wave velocity and the high-velocity sandstone with higher wave velocity is large. This interface reflection usually exhibits a strong reflection characteristic, manifested as a top-valley-bottom-peak. When seismic waves propagate from high-velocity sandstone to low-velocity sandstone, the amplitude of the reflected wave is also stronger due to the large difference in wave velocity. However, the polarity of the reflection changes; therefore, the seismic reflection characteristics of high-velocity sandstone are mainly characterized by peaks at the top and valleys at the bottom. (See attached image) Figure 14 As shown, the first section of the sand dune has three main sand bodies developed longitudinally, numbered 1, 2 and 3 from bottom to top; the second section of the sand dune has nine sand bodies developed longitudinally, numbered 4, 5, 6, 7, 8, 9, 10, 11 and 12 from bottom to top.
[0090] Example 4
[0091] As another preferred embodiment of the present invention, this embodiment is a further detailed supplement and explanation of the technical solution of the present invention based on the above-described embodiments 1, 2, or 3. This embodiment further elaborates on step S3 based on the above-described embodiments 1, 2, or 3. In step S3, root mean square attributes, maximum trough attributes, maximum peak attributes, mean amplitude attributes, mean absolute amplitude attributes, maximum amplitude attributes, minimum amplitude attributes, cubic difference attributes, amplitude slope attributes, and total absolute amplitude attributes are extracted based on the differences in seismic response characteristics. Through analysis of river channel planar morphology and continuity, the planar distribution maps of different attributes (as shown in the attached map) are compared. Figure 15 As shown in the attached diagram, the strong wave peaks at the bottom boundary of the low-resistivity channel are most prominent in the earthquake root-mean-square amplitude attribute planar map. Therefore, this study prioritizes earthquake root-mean-square amplitude attributes to predict the distribution of the Shaximiao Formation sand bodies. Furthermore, the root-mean-square attributes are used to finely characterize the planar distribution features of 12 sand groups (as shown in the attached diagram). Figure 16 Appendix Figure 17 Appendix Figure 18and attached Figure 19 As shown in Table 1, statistical analysis was performed on the sand bodies identified in single wells and the sand bodies identified by seismic activity to calculate the well-seismic prediction matching rate.
[0092] Table 1 shows the well-seismic matching rate statistics for sand body identification in the Shaximiao Formation.
[0093]
[0094]
[0095] As shown in Table 1 above, the root mean square amplitude attribute of earthquakes is preferred for predicting the distribution of sand bodies in the Shaximiao Formation, with an average prediction matching rate of 84%. The root mean square amplitude attribute of earthquakes has significant advantages over other seismic response characteristics.
[0096] Example 5
[0097] As another preferred embodiment of the present invention, this embodiment further supplements and elaborates on the technical solution of the present invention based on the above-described embodiments 1, 2, 3, or 4. This embodiment further elaborates on step S4 based on the above-described embodiments 1, 2, 3, or 4. In step S4, the development of the sand body is determined by comprehensively considering factors such as sand body thickness, serration rate, and sand body genetic type. (See attached specification.) Figure 20 Appendix Figure 21 Appendix Figure 22 and attached Figure 23As shown, the thickness of sand body No. 1 ranges from 6.17m to 30.625m, with an average thickness of 18.47m; the serration rate ranges from 28.5% to 6.2%, with an average serration rate of 37.9%; and the absolute value of the root mean square amplitude of earthquakes ranges from 500 to 5100. Sand body No. 2 ranges from 5.91m to 45.125m, with an average thickness of 20.38m; the serration rate ranges from 24.1% to 21.1%, with an average serration rate of 33.8%; and the absolute value of the root mean square amplitude of earthquakes ranges from 800 to 5500. Sand body No. 3 ranges from 4.91m to 20.02m, with an average thickness of 18.36m; the serration rate ranges from 24.1% to 50.2%, with an average serration rate of 36.8%; and the absolute value of the root mean square amplitude of earthquakes ranges from 8... 00–4500; Sand body No. 4 has a thickness of 5.625 m–23.625 m, an average thickness of 12.67 m, a serration rate of 24.1%–48.7%, an average serration rate of 36.6%, and an absolute value of the root mean square amplitude of earthquakes of 800–4000; Sand body No. 5 has a thickness of 6.125 m–36.5 m, an average thickness of 14.39 m, a serration rate of 24.1%–55.3%, an average serration rate of 36.4%, and an absolute value of the root mean square amplitude of earthquakes of 800–4000; Sand body No. 6 has a thickness of 5.5 m–31 m, an average thickness of 12.78 m, a serration rate of 24.1%–48.8%, an average serration rate of 38.54%, and an absolute value of the root mean square amplitude of earthquakes of 00–4500. The absolute values range from 800 to 4000; Sand body No. 7 has a thickness ranging from 4.46m to 34.5m, with an average thickness of 10.54m, a serration rate ranging from 24.1% to 43.3%, with an average serration rate of 35.4%, and an absolute value of the root mean square amplitude of seismic waves ranging from 800 to 3000; Sand body No. 8 has a thickness ranging from 5.91m to 30.5m, with an average thickness of 16.6m, a serration rate ranging from 24.1% to 41.1%, with an average serration rate of 34.8%, and an absolute value of the root mean square amplitude of seismic waves ranging from 800 to 3000; Sand body No. 9 has a thickness ranging from 4.59m to 35.375m, with an average thickness of 15.1m, a serration rate ranging from 24.1% to 66.2%, with an average serration rate of 39.5%, and an absolute value of the root mean square amplitude of seismic waves ranging from 800 to 4000. The absolute value of the root mean square amplitude of the earthquake ranges from 1400 to 4000; the thickness of sand body No. 10 ranges from 6m to 50.87m, with an average thickness of 15.4m, and the serration rate ranges from 24.1% to 49.3%, with an average serration rate of 35.9%, and the absolute value of the root mean square amplitude of the earthquake ranges from 1400 to 4000; the thickness of sand body No. 11 ranges from 7m to 23.87m, with an average thickness of 14.27m, and the serration rate ranges from 24.1% to 58.2%, with an average serration rate of 38.4%, and the absolute value of the root mean square amplitude of the earthquake ranges from 1500 to 4000; the thickness of sand body No. 12 ranges from 4.91m to 38.625m, with an average thickness of 10.95m, and the serration rate ranges from 24.1% to 64.7%, with an average serration rate of 38.The absolute value of the root mean square amplitude of the earthquake is between 500 and 5000. Based on the sand body planar distribution map characterized by the root mean square amplitude attribute, the No. 2 sand body of the first section of the Datachang area and the No. 8, 10, and 11 sand bodies of the second section of the sand are selected as having better development. Among them, the No. 1 sand body of the first section of the sand has a large thickness, with an average thickness of 20 meters. The serration rate is low, ranging from 24% to 44%, and the porosity and permeability are relatively high, with an average porosity of 10% and an average permeability of 10×10. -3 μm 2 The dominant sand bodies in the Sha-2 section are No. 8, 10, and 11. These dominant sand bodies are relatively thick, with an average thickness ranging from 10 to 17 meters. Their GR curve toothing rate is low, averaging between 34% and 38%. They also exhibit relatively high porosity and permeability, with an average porosity of 9%. The No. 2 sand body in the Sha-1 section is relatively thick and has a relatively stable lateral distribution. Specifically, the No. 2 sand group in well T20 has a thickness of 23 meters and a GR toothing rate of 41%. Seismic amplitude is strong, with root mean square seismic property values ranging from 3800 to 5000. The No. 8 sand body in the Sha-2 section is relatively thick and has a relatively stable lateral distribution. Specifically, the No. 8 sand body in well T23 is 18m thick with a GR toothing rate of 34%; the seismic amplitude is relatively strong, ranging from 1600 to 3000. The No. 10 sand body is also relatively thick and has a relatively stable lateral distribution with good continuity. Specifically, the No. 10 sand body in well T15-H1 is 14m thick with a GR toothing rate of 31%; the seismic amplitude is relatively strong, with root mean square attribute values ranging from 1700 to 4000. The No. 11 sand body is also relatively thick and has a relatively stable lateral distribution with good continuity. Specifically, the No. 11 sand body in well TX6H1 is 16m thick with a toothing rate of 45%; the seismic amplitude is relatively strong, with trough amplitude values ranging from 2500 to 4000.
[0098] Example 6
[0099] As another preferred embodiment of the present invention, this embodiment further supplements and elaborates on the technical solution of the present invention based on the above-described embodiments 1, 2, 3, 4, or 5. This embodiment further elaborates on step S5 based on the above-described embodiments 1, 2, 3, 4, or 5. In step S5, the sand bodies identified in S4 are analyzed. First, the porosity, thickness, serration rate, and root mean square amplitude of each sand body are statistically analyzed, and cross-plots are plotted pairwise. The results show that the identified sand bodies can be divided into three categories: Class I sand, Class II sand, and Class III sand. Among them, Class I sand bodies are the best, with a thickness ranging from 11.375m to 31m, a toothing rate ranging from 24.1% to 41.2%, a porosity ranging from 7% to 10.5%, and a root mean square amplitude value ranging from 2719 to 6420; Class II sand bodies are the best, with a thickness ranging from 8.625m to 18.36m, a toothing rate ranging from 30.8% to 40.9%, a porosity ranging from 5.9% to 7.9%, and a root mean square amplitude value ranging from 2612 to 3251; Class III sand bodies are the best, with a thickness ranging from 4.45m to 10.8m, a toothing rate ranging from 32.4% to 50.5%, a porosity ranging from 5% to 7.1%, and a root mean square amplitude value ranging from 290 to 3169. Based on the above analysis, a set of evaluation criteria for dominant sand bodies was established.
[0100] Example 7
[0101] As another preferred embodiment of the present invention, this embodiment further supplements and elaborates on the technical solution of the present invention based on the above-described embodiments 1, 2, 3, 4, 5, or 6. This embodiment further elaborates on step S6 based on the above-described embodiments 1, 2, 3, 4, 5, or 6. In step S6, SPSS software is used to analyze the correlation between various parameters, and a linear discriminant formula for reservoir type is established accordingly.
[0102] The discriminant for Class I sand bodies is:
[0103] The discriminant for Class II sand bodies is:
[0104] The discriminant for Class III sand bodies is:
[0105] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.
Claims
1. A method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of earthquake root-mean-square amplitude attributes, characterized by: The evaluation method includes the following steps: S1. Identify and analyze sand bodies in individual wells, and determine the distribution of sand bodies in individual wells by combining well logging curves and core observations; analyze sand body velocities to clarify sand body types; and clarify the seismic reflection characteristics of different types of sand bodies through seismic synthetic calibration. S2. Based on single wells, sand bodies are identified and numbered. Through well-seismic calibration, the seismic response characteristics and longitudinal distribution characteristics of various sand bodies are clarified. S3. Utilize the root mean square properties of earthquakes to finely characterize the planar distribution characteristics of sand bodies in different secondary channels in the study area, and predict the planar distribution of sand bodies. S4. Statistically analyze the absolute value of the root mean square amplitude of the sand body, the thickness of the sand body, and the toothing rate to determine whether the sand body is developed. Combine this with typical wells for verification and dissection to select well-developed sand bodies. S5. Analyze the sand bodies selected in step S4, and statistically analyze the physical properties, thickness, serration rate and root mean square amplitude of each sand body. Perform cross-plot analysis on each pairwise to obtain the evaluation criteria for dominant sand bodies. S6. Based on the evaluation criteria for advantageous sand bodies constructed in step S5, superimpose sand body physical properties, thickness, toothing rate and root mean square amplitude of seismic waves, analyze the correlation between the parameters, and establish a linear discriminant for reservoir type.
2. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude attributes as described in claim 1, characterized in that: In step S6, the established linear discriminant for reservoir type is as follows: Class I sand: Class II sand: Class III sand In the formula, D is the sand body thickness, G is the sand body serration rate, and RMS is the root mean square value of the seismic data. Porosity.
3. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of earthquake root-mean-square amplitude attributes as described in claim 2, characterized in that: The thickness of Class I sand ranges from 11.375m to 31m, the serration rate ranges from 24.1% to 41.2%, the porosity ranges from 7% to 10.5%, and the root mean square amplitude value ranges from 2719 to 6420. The thickness of the Class II sand bodies ranges from 8.625 m to 18.36 m, the serration rate ranges from 30.8% to 40.9%, the porosity ranges from 5.9% to 7.9%, and the root mean square amplitude ranges from 2612 to 3251. Class III sand bodies are the best, with a thickness ranging from 4.45m to 10.8m, a toothing rate ranging from 32.4% to 50.5%, a porosity ranging from 5% to 7.1%, and a root mean square amplitude value ranging from 290 to 3169.
4. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in any one of claims 1-3, characterized in that: In step S6, SPSS software is used to analyze the correlation between various parameters and establish a linear discriminant for reservoir type.
5. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in any one of claims 1-3, characterized in that: In step S1, the sand bodies in a single well are identified and analyzed. The distribution of sand bodies in a single well is determined by combining well logging curves and core observations. Specifically, the sand bodies in a single well are identified based on the characteristics of the well logging curves and the descriptions of core observations from typical wells.
6. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in claim 5, characterized in that: In step S1, by analyzing the velocities of sandstone and mudstone, two types of sand bodies were identified: high-velocity sandstone and low-velocity sandstone.
7. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in claim 6, characterized in that: In step S2, through synthetic record calibration and forward modeling, it was determined that low-velocity sand bodies exhibit "peak-valley-bottom-peak" seismic response characteristics, while high-velocity sand bodies exhibit "peak-valley" seismic response characteristics.
8. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in any one of claims 1-3, characterized in that: In step S3, the root mean square seismic properties are used to finely characterize the planar distribution features of sand bodies in different secondary channels in the study area, and the corresponding seismic attribute parameters are extracted. By combining the planar distribution features and the corresponding seismic attribute parameters, the planar distribution of sand bodies is predicted.
9. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of earthquake root-mean-square amplitude attributes as described in claim 8, characterized in that: In step S3, statistical analysis is performed on the sand bodies identified in a single well and the sand bodies identified by seismic activity to calculate the well-seismic prediction matching rate.
10. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in any one of claims 1-3, characterized in that: The sand properties described in steps S5 and S6 include sand porosity.
11. The method for evaluating dominant sand bodies in narrow channels based on quantitative characterization of seismic root-mean-square amplitude properties as described in claim 10, characterized in that: The tooth formation rate mentioned in steps S5 and S6 is characterized by three logging parameters: tooth amplitude, tooth distribution density, and tooth distribution frequency.