Well seismic analysis system, method and equipment based on tight sandstone geology-mechanics coupling lithofacies system

Abstract

The invention discloses a well seismic analysis system, method and equipment based on a compact sandstone geology-mechanics coupling lithofacies system, and relates to the field of compact sandstone oil and gas exploitation and analysis. A compact sandstone reservoir geology-mechanics coupling lithofacies classification mode is constructed according to the information data through a classification mode construction module by adopting a four-element composite triangular diagram method; the integration module performs geomechanical coupling lithofacies division and multi-type lithofacies prediction result integration on the single well level according to the element difference data; and the analysis and determination module performs geology-mechanics coupling lithofacies feature extraction, lithofacies classification feedback adjustment and seismic attribute mapping based on the tight sandstone reservoir geology-mechanics coupling lithofacies well-seismic collaborative three-dimensional model, and determines tight sandstone geology-mechanics coupling lithofacies distribution information data. According to the method, the heterogeneity distribution rule of the rock mechanics and ground stress characteristics of the tight sandstone reservoir can be determined, and a basis is provided for improving the exploitation effect of tight sandstone oil and gas.

Description

Technical Field

[0001] The present application relates to the field of tight sandstone oil and gas production analysis, and in particular to a well seismic analysis system, method and equipment based on a tight sandstone geological-mechanical coupled lithofacies system. Background Art

[0002] Tight sandstone reservoirs have huge oil and gas resource potential and considerable reserves. In order to obtain the oil and gas resources enriched in tight sandstone reservoirs, in addition to using traditional geological lithofacies to find geological sweet spots, it is also necessary to find engineering sweet spots based on geomechanical characteristics to guide the drilling and artificial transformation of tight sandstone oil and gas reservoirs. Ultra-long horizontal wells + large-scale repeated fracturing are the necessary means for the current development of tight sandstone oil and gas. Both are essentially a kind of mechanical behavior. Only by relying on accurate rock mechanics and geostress parameter fields to optimize process parameters can the drilling and fracturing efficiency be improved. However, the current rock mechanics and geostress parameter field modeling uses deterministic or random interpolation methods. The modeling results obtained are quite different from the geomechanical characteristics of tight sandstone reservoirs and cannot effectively guide ultra-long horizontal wells + large-scale repeated fracturing.

[0003] Essentially, the dense sandstone rock mass in the reservoir is buried deep underground and is a unity of geological and mechanical characteristics. So, what kind of lithofacies system can be constructed to accurately characterize the dense sandstone rock mass that unifies geological and mechanical characteristics? This is a global problem that has not been solved so far. Summary of the invention

[0004] The purpose of this application is to provide a well seismic analysis system, method and equipment based on a tight sandstone geological-mechanical coupled lithofacies system, which can determine the heterogeneous distribution law of the rock mechanics and geostress characteristics of tight sandstone reservoirs, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a well seismic analysis system based on a tight sandstone geological-mechanical coupled lithofacies system, comprising:

[0007] The information data acquisition module is used to acquire information data; the information data includes: characteristic core data and rock mechanics data; the characteristic core data includes characteristic data acquired by using the three-dimensional nine-point method and parameter data determined based on mechanical experiments; the rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical tests, taking the influence of lithofacies changes on rock strength and crack extension behavior as the research object, and acquiring parameter data sensitive to the rock mechanics performance of different lithofacies;

[0008] A classification model construction module is connected to the information data acquisition module and is used to construct a geological-mechanical coupled lithofacies classification model of a tight sandstone reservoir according to information data by using a four-element composite triangular diagram method;

[0009] The integration module is connected with the classification mode construction module and is used to perform geomechanical coupled lithofacies division and integrate multi-type lithofacies prediction results based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs at the single well level according to the element difference data to obtain the integrated results; the element difference data includes: grain composition, grain size, brittleness index and horizontal stress difference;

[0010] The analysis and determination module is connected to the integration module and is used to extract the characteristics of the geological-mechanical coupling lithofacies, adjust the lithofacies classification feedback and map the seismic attributes based on the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir geological-mechanical coupling lithofacies according to the integration results, and determine the geological-mechanical coupling lithofacies distribution information data of the tight sandstone; the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupling lithofacies distribution information data of the tight sandstone is used to characterize the heterogeneous distribution law of the rock mechanics and geostress characteristics of the tight sandstone reservoir, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

[0011] In the second aspect, the present application provides a well-seismic analysis method based on a tight sandstone geological-mechanical coupled lithofacies system, which is implemented using the above-mentioned system; including:

[0012] Obtain information data; information data include: characteristic core data and rock mechanics data; characteristic core data include characteristic data obtained by three-dimensional nine-point method and parameter data determined based on mechanical experiments; rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical tests, taking the influence of lithofacies changes on rock strength and crack propagation behavior as the research object, and obtaining parameter data sensitive to the rock mechanics performance of different lithofacies;

[0013] The four-element composite triangulation method is used to construct a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on information data;

[0014] At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs, geomechanical coupled lithofacies division and multi-type lithofacies prediction results were integrated according to the element difference data to obtain the integrated results; the element difference data include: grain composition, grain size, brittleness index and horizontal stress difference;

[0015] Based on the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs, the characteristics of geological-mechanical coupled lithofacies are extracted, lithofacies classification feedback adjustment and seismic attribute mapping are carried out according to the integration results to determine the geological-mechanical coupled lithofacies distribution information data of tight sandstones; the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupled lithofacies distribution information data of tight sandstones is used to characterize the heterogeneous distribution law of rock mechanics and geostress characteristics of tight sandstone reservoirs, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

[0016] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system.

[0017] According to the specific embodiments provided in this application, this application has the following technical effects:

[0018] The present application provides a well seismic analysis system, method and equipment based on the tight sandstone geological-mechanical coupled lithofacies system. Based on the consideration of the petrological characteristics and transformation potential of the tight sandstone reservoir, the present application determines the factors affecting the horizontal drilling and artificial transformation potential of the reservoir, establishes a classification model of the tight sandstone reservoir geological-mechanical coupled lithofacies, realizes the quantitative identification and prediction of the tight sandstone reservoir geological-mechanical coupled lithofacies single well, characterizes the heterogeneous distribution characteristics of the tight sandstone reservoir geological-mechanical coupled lithofacies, and provides technical support for the modeling of the rock mechanics and geostress heterogeneity of the tight sandstone oil and gas phase-controlled rock, and then effectively implements ultra-long horizontal wells + large-scale repeated fracturing, and finally efficiently exploits the tight sandstone oil and gas. Therefore, the present application can determine the heterogeneous distribution law of the rock mechanics and geostress characteristics of the tight sandstone reservoir, so as to provide a basis for improving the exploitation effect of the tight sandstone oil and gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the isosceles triangle plate for lithology classification of tight sandstone reservoirs;

[0020] Figure 2 The structural diagram of the well-seismic analysis system based on the tight sandstone geological-mechanical coupled lithofacies system;

[0021] Figure 3 This is a flow chart of the well-seismic analysis scheme based on the tight sandstone geological-mechanical coupled lithofacies system;

[0022] Figure 4 This is a schematic diagram of the three-dimensional nine-point sampling method for tight sandstone reservoirs;

[0023] Figure 5This is a schematic diagram of the three-dimensional nine-point sampling points in a tight sandstone reservoir example area in a certain production area;

[0024] Figure 6 is the intersection diagram of elastic modulus and Poisson’s ratio;

[0025] Figure 7 It is the intersection diagram of crack length and density with horizontal stress difference;

[0026] Figure 8 It is a composite isosceles triangle plate model diagram of tight sandstone geological-mechanical coupled lithofacies classification;

[0027] Fig. 9 This is a schematic diagram of the geological-mechanical coupled lithofacies classification results of tight sandstone reservoirs;

[0028] Fig.10 A comprehensive histogram of the quantitative identification results of geological-mechanical coupled lithofacies in tight sandstone gas wells;

[0029] Fig.11 This is the geological-mechanical coupled lithofacies P-wave impedance inversion profile of tight sandstone reservoir;

[0030] Fig.12 It is a schematic diagram of the 3D geological-mechanical coupled lithofacies model of tight sandstone reservoir;

[0031] Fig.13 It is the first distribution diagram of geological-mechanical coupled lithofacies of tight sandstone reservoir;

[0032] Fig.14 This is a schematic diagram of the second distribution of geological-mechanical coupled lithofacies in tight sandstone reservoirs;

[0033] Fig.15 It is a column scatter diagram of the production capacity distribution of tight sandstone reservoirs;

[0034] Fig.16 This is a schematic diagram of the brittleness index model for tight sandstone reservoirs;

[0035] Fig.17 This is a phase-controlled rock mechanics histogram of a control well in a tight sandstone reservoir;

[0036] Fig.18 A schematic diagram of the structure of a computer device. DETAILED DESCRIPTION

[0037] At present, many scholars have studied the main tight sandstone reservoirs in the world. By combining nuclear magnetic resonance logging with acoustic time difference logging, the reservoir porosity of low porosity and permeability gas reservoirs is jointly calculated and applied to actual production, which improves the calculation accuracy. Direct identification methods of tight sandstone gas reservoirs and quantitative identification methods. The traditional Stacking model has been improved to better learn the complex characteristics and changing laws of different reservoir types. A set of "double sweet spots" reservoir prediction methods for tight sandstone reservoirs integrates geological sweet spots with engineering sweet spots to objectively evaluate the production potential of low permeability reservoirs. Through a comprehensive study of reservoir sedimentary microfacies, pore structure, and diagenesis, the main controlling factors of tight sandstone reservoir development are clarified.

[0038] The current classification method for tight sandstone is to select the main minerals of tight sandstone reservoirs, quartz (Q), feldspar (F) and rock fragments (R), to form a mineral content triangle diagram ( Figure 1 ). According to the quartz content (q), the feldspar content (f) and the rock fragments content (r), four auxiliary lines are divided: q=0.75, r / (f+r)=0.25, r / (f+r)=0.5 and r / (f+r)=0.75, which correspond to q=0.75, r / f=1:3, r / f=1:1, r / f=3:1 respectively. When reading the values ​​in the phase diagram, X=r+q / 2 and Y=q.

[0039] Different minerals undergo different hydration reactions during diagenesis. Rocks containing clay minerals will expand and contract after absorbing water, thus affecting the pore structure, permeability and production capacity of the reservoir. During the flow of oil and gas fluids in reservoirs with different mineral compositions, their interactions will affect the distribution and preferential flow paths of oil and gas. High-strength sandstone may be more stable under high-pressure conditions, which helps maintain the structure and vertical connectivity of the reservoir and improve oil and gas production capacity.

[0040] Sedimentary rocks of different particle sizes (such as sandstone and mudstone) have an important impact on the characteristics of oil and gas reservoirs. Small-sized rocks may cause poor flow due to increased fluid resistance, thus affecting mining efficiency and production capacity. Larger particles tend to make the rock structure more stable and reduce engineering risks, thereby ensuring the normal operation of drilling and production equipment and maintaining continuous production capacity.

[0041] In the comprehensive study of geology and mechanics, different lithofacies have different rock mechanics and geostress characteristics due to their different sedimentary environments, burial depths, and petrological properties. In the coupled geology-mechanics lithofacies characterization and modeling, the geological characteristics and mechanical properties of rocks are usually considered, and lithofacies models are established to couple geological lithofacies with mechanical properties, analyze the mechanical characteristics of each lithofacies, and accurately predict the deformation, destruction, and stability of rocks.

[0042] Current research results are mainly focused on the specific study of the mechanical properties of different lithofacies. In rock mechanics research and three-dimensional modeling, the analysis is relatively independent, and the constraints of rock phases on rock mechanical parameters are relatively vague. The modeling results obtained are quite different from the geomechanical characteristics of tight sandstone reservoirs. There is no further subdivision of the coupled mechanical properties of geological lithofacies, and no further establishment of a set of geological-mechanical coupled lithofacies classification scheme, which has certain limitations.

[0043] For tight sandstone reservoirs, the current rock mechanics and geostress parameter field modeling adopts deterministic or random interpolation methods. The modeling results obtained are quite different from the geomechanical characteristics of tight sandstone reservoirs, and cannot effectively guide ultra-long horizontal wells + large-scale repeated fracturing, which will restrict the further production efficiency of tight sandstone reservoirs.

[0044] like Figure 2 As shown, the present application provides a well seismic analysis system based on a tight sandstone geological-mechanical coupled lithofacies system, comprising:

[0045] The information data acquisition module is used to acquire information data; the information data includes: characteristic core data and rock mechanics data; the characteristic core data includes characteristic data acquired by using the three-dimensional nine-point method and parameter data determined based on mechanical experiments; the rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical experiments, taking the influence of lithofacies changes on rock strength and crack extension behavior as the research object, and acquiring parameter data sensitive to the rock mechanics performance of different lithofacies.

[0046] The classification mode construction module is connected with the information data acquisition module and is used to construct a geological-mechanical coupled lithofacies classification mode of tight sandstone reservoirs according to the information data by adopting a four-element composite triangular diagram method.

[0047] The integration module is connected to the classification model building module and is used to perform geomechanical coupled lithofacies division and integrate multi-type lithofacies prediction results based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs at the single well level according to the element difference data to obtain the integrated results; the element difference data include: particle composition, particle size, brittleness index and horizontal stress difference.

[0048] The analysis and determination module is connected to the integration module and is used to extract the characteristics of the geological-mechanical coupling lithofacies, adjust the lithofacies classification feedback and map the seismic attributes based on the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir geological-mechanical coupling lithofacies according to the integration results, and determine the geological-mechanical coupling lithofacies distribution information data of the tight sandstone; the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupling lithofacies distribution information data of the tight sandstone is used to characterize the heterogeneous distribution law of the rock mechanics and geostress characteristics of the tight sandstone reservoir, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

[0049] Classification mode building blocks include:

[0050] The brittle factor determination submodule is connected to the information data acquisition module and is used to determine the geological-mechanical coupled lithofacies brittle factor of dense sandstone by using the brittle boundary division method, visualizing the relationship between the elastic modulus and the Poisson's ratio according to the information data, and dividing the material properties through a negative slope straight line.

[0051] The geostress factor determination submodule is connected to the information data acquisition module and is used to determine the geostress factors of the tight sandstone geological-mechanical coupling lithofacies according to the information data based on the stress optimization identification model; the stress optimization identification model is a physical model of the influence of horizontal stress difference on crack expansion in tight sandstone reservoirs based on the influence of horizontal stress difference on the formation, expansion and connection of cracks in horizontal multi-stage fracturing operations.

[0052] The plate determination submodule is connected to the brittleness factor determination submodule and the ground stress factor determination submodule respectively, and is used to process the composite triangle map pattern based on the isosceles triangle map of the tight sandstone reservoir lithology classification, according to the tight sandstone geological-mechanical coupled lithofacies brittleness factor and the tight sandstone geological-mechanical coupled lithofacies ground stress factor, coupled grain size, horizontal stress difference and brittleness index, to obtain the composite isosceles triangle map of the tight sandstone geological-mechanical coupled lithofacies classification.

[0053] The classification pattern construction submodule is connected to the plate determination submodule and is used to name the geological-mechanical coupling lithofacies types based on the tight sandstone geological-mechanical coupling lithofacies classification composite isosceles triangle plate, using particle composition and particle size as the naming parts and horizontal stress difference and brittleness index as modification prefixes, so as to determine the geological-mechanical coupling lithofacies classification pattern of the tight sandstone reservoir.

[0054] The integrated modules include:

[0055] The single well identification result acquisition submodule is used to obtain the single well identification results of the geological lithofacies of the tight sandstone reservoir;

[0056] The division submodule is connected to the single well identification result acquisition submodule and the classification pattern construction module respectively, and is used to perform geomechanical coupled lithofacies division at the single well level based on the tight sandstone reservoir geological-mechanical coupled lithofacies classification pattern and the tight sandstone reservoir geological lithofacies single well identification results according to the element difference data to obtain the division results.

[0057] The integration processing submodule is connected to the division submodule and is used to perform numerical mapping, priority selection and classification processing according to the division results, so as to integrate the multi-type lithofacies prediction results and obtain the integrated results.

[0058] The present application also provides a well seismic analysis method based on a tight sandstone geological-mechanical coupled lithofacies system, which is implemented using the above system; the method includes:

[0059] Obtain information data; the information data include: characteristic core data and rock mechanics data; the characteristic core data include characteristic data obtained by using the three-dimensional nine-point method and parameter data determined based on mechanical experiments; the rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical tests, taking the influence of lithofacies changes on rock strength and crack propagation behavior as the research object, and obtaining parameter data that is sensitive to the rock mechanics performance of different lithofacies.

[0060] Characteristic data include: lithology, particle type and particle size. Parameter data include: elastic modulus, Poisson's ratio, brittleness, cohesion, fracture toughness, fracture pressure, internal friction angle, tensile strength, shear strength, maximum horizontal principal stress, minimum horizontal principal stress, vertical stress and horizontal stress difference.

[0061] A four-element composite triangulation method was used to construct a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on information data.

[0062] At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs, geomechanical coupled lithofacies division and integration of multi-type lithofacies prediction results are carried out according to the factor difference data to obtain the integrated results; the factor difference data include: particle composition, particle size, brittleness index and horizontal stress difference.

[0063] Based on the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs, the characteristics of geological-mechanical coupled lithofacies are extracted, lithofacies classification feedback adjustment and seismic attribute mapping are carried out according to the integration results to determine the geological-mechanical coupled lithofacies distribution information data of tight sandstones; the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupled lithofacies distribution information data of tight sandstones is used to characterize the heterogeneous distribution law of rock mechanics and geostress characteristics of tight sandstone reservoirs, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

[0064] In one embodiment, a four-element composite triangular diagram method is used to construct a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on information data, specifically including:

[0065] The brittle boundary division method is adopted to visualize the relationship between elastic modulus and Poisson's ratio according to the information data, and the material properties are divided by a negative slope straight line to determine the brittle factor of the geological-mechanical coupled lithofacies of tight sandstone.

[0066] Based on the stress optimization identification model, the geological-mechanical coupled lithofacies geostress factors of tight sandstone are determined according to information data; the stress optimization identification model is a physical model of the influence of horizontal stress difference on crack propagation in tight sandstone reservoirs, which is based on the influence of horizontal stress difference on crack formation, expansion and connection in horizontal multi-stage fracturing operations.

[0067] Based on the isosceles triangle plate of tight sandstone reservoir lithology classification, according to the tight sandstone geological-mechanical coupled lithofacies brittleness factor and tight sandstone geological-mechanical coupled lithofacies in-situ stress factor, the coupled grain size, horizontal stress difference and brittleness index are processed into a composite triangle map model to obtain the tight sandstone geological-mechanical coupled lithofacies classification composite isosceles triangle plate.

[0068] Based on the composite isosceles triangle plate of tight sandstone geological-mechanical coupled lithofacies classification, the geological-mechanical coupled lithofacies types are named with particle composition and particle size as the naming parts, and horizontal stress difference and brittleness index as modified prefixes, and the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs is determined.

[0069] At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs, geomechanical coupled lithofacies division and multi-type lithofacies prediction results were integrated according to the element difference data to obtain the integrated results, including:

[0070] Obtain the single-well identification results of the geological lithofacies of the tight sandstone reservoir; at the single-well level, based on the geological-mechanical coupled lithofacies classification model of the tight sandstone reservoir and the single-well identification results of the geological lithofacies of the tight sandstone reservoir, perform geomechanical coupled lithofacies division according to the element difference data to obtain the division results; based on the division results, perform numerical mapping, select priorities and classify processing to integrate the prediction results of multiple types of lithofacies to obtain integrated results.

[0071] The method for determining the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs specifically includes:

[0072] Obtain raw data; raw data is data containing geological, seismic and mechanical properties; raw data includes geological profiles, lithology data, seismic wave velocity, porosity and permeability; perform data preprocessing on raw data to obtain processed data; preprocessing includes: interpolation, denoising and normalization; construct a three-dimensional grid model; the three-dimensional network model is a physical model constructed according to the spatial distribution and characteristics of the geological body to characterize the relationship between geological and mechanical characteristics.

[0073] The processed data is subjected to geological-mechanical coupled lithofacies feature extraction to obtain extracted data; based on the geological attribute data and the extracted data, a geological-mechanical coupled lithofacies sensitive attribute analysis is performed to obtain analyzed data.

[0074] According to the analysis data, inversion is performed based on the three-dimensional grid model to determine the inversion information data; the inversion information data includes: seismic wave velocity and impedance; the inversion information data is compared with the actual downhole sampling results, and the inversion parameters of the three-dimensional grid model are trained and adjusted with the goal of minimizing the error of the comparison result to obtain the adjusted three-dimensional grid model.

[0075] The adjusted three-dimensional grid model is determined as a geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs.

[0076] like Figure 3 As shown, the core of the technical solution of the present application lies in the construction of a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on a four-element composite triangular diagram method, including multi-level three-dimensional nine-point method characteristic core sampling and parameter combing for tight sandstone reservoirs, rock mechanical parameter optimization based on lithofacies discretization and sensitivity analysis, determination of tight sandstone geological-mechanical coupled lithofacies brittleness factors based on brittle boundary division method, determination of tight sandstone geological-mechanical coupled lithofacies ground stress factors based on stress optimization identification model, division of a geomechanical coupled lithofacies composite triangular phase diagram of coupling four elements, and construction of a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs. On this basis, quantitative identification and prediction of single wells of geological-mechanical coupled lithofacies in tight sandstone reservoirs are carried out, including two links: single well identification of geological-mechanical coupled lithofacies in tight sandstone reservoirs based on intelligent lithofacies identification and construction of a three-step fusion prediction method for geological-mechanical coupled lithofacies. Finally, a three-dimensional visualization representation of the geological-mechanical coupled lithofacies and well-seismic coordination of the tight sandstone reservoir was carried out, including the feature extraction and visualization of the geological-mechanical coupled lithofacies based on the three-dimensional grid model and the lithofacies classification feedback adjustment and seismic attribute mapping based on three-dimensional modeling.

[0077] When studying tight sandstone reservoirs, it is very important to select representative sample points, because these samples will directly affect the understanding of geological and mechanical characteristics and the construction of models. Figure 4The three-dimensional nine-point method in the core sampling is used at a 45-degree angle. It helps to minimize the damage to the original structure of the rock during the sampling process. By tilting the sampling, stress concentration can be reduced when collecting the core, and the cracks or breakage that may occur when the sample is taken out can be reduced, thereby better preserving the natural state of the rock. By sampling the core with the three-dimensional nine-point method, information related to the development of cracks can be effectively captured. This oblique sampling makes it possible for the sample to contain microcrack data in multiple directions, which more realistically reflects the mechanical characteristics of the rock mass. Taking a spatially inclined sampling angle can increase the diversity and representativeness of the sample. Such sampling can cover a wider range of structural features, thereby providing a more comprehensive data basis for subsequent analysis. In addition, by sampling with the three-dimensional nine-point method, the stress distribution in different directions can be balanced to a certain extent, so that the obtained experimental data tends to more realistically reflect the mechanical properties of the rock.

[0078] The multi-level three-dimensional nine-point method characteristic core sampling and parameter combing of tight sandstone reservoirs specifically includes four steps:

[0079] First, nine potential study areas were selected using the three-dimensional nine-point method within the study area to maximize the representativeness of the sample. The sampling areas should include some special geological structures or abnormal areas, which usually show significant differences in mechanical properties. For example, selecting sampling points close to faults, folds or other geological structural influence areas can provide a more comprehensive understanding of the ground stress state and its impact on the mechanical properties of the reservoir. This method can help identify potential mechanical weak areas and their impact on horizontal drilling in the study.

[0080] Second, nine potential sampling points were selected again using the three-dimensional nine-point method in the sampling area. When selecting sampling points in the sampling area, it should be ensured that the distribution of the points can reflect the heterogeneity of the entire reservoir. Considering that tight sandstone reservoirs usually have different lithologies, grain types and pore structures, sample points at different depths and different geological units are selected in the region so that the sampling can cover various types of rock characteristics. Preliminary screening is carried out through geological profile analysis, existing drilling data and geophysical logging data to ensure the breadth and diversity of samples.

[0081] Third, adjust the angle and distance in space, and increase or decrease the sampling points according to the actual drilling situation. When selecting a specific sampling location, it is necessary to consider the feasibility and safety of the sampling technology, the current drilling and development level of the oil and gas field. It should be ensured that the selected location is convenient for drilling and collecting samples, while avoiding negative impacts on the environment and ecology.

[0082] Fourth, if necessary, the three-dimensional nine-point method can be used to further increase the number of samples based on the existing sampling points. If the study area is small, the three-dimensional nine-point method can be used only once to determine the sampling points.

[0083] Fifth, for the final samples, laboratory tests are conducted to obtain basic characteristic data such as lithology, particle type, and particle size. At the same time, through meticulous mechanical experiments, parameters such as elastic modulus, Poisson's ratio, brittleness, cohesion, fracture toughness, fracture pressure, internal friction angle, tensile strength, shear strength, maximum horizontal principal stress, minimum horizontal principal stress, vertical stress, and horizontal stress difference are measured.

[0084] Figure 5 The three-dimensional nine-point sampling points of a tight sandstone reservoir example area are shown. There are two stress singular points in the whole area, 8 sampling points are added, there is one risk point, and one sampling point is reduced. A total of 16 sampling points were selected.

[0085] When conducting rock mechanics sensitivity analysis, we can set up different lithofacies numerical tests to observe the impact of these lithofacies changes on rock strength and crack propagation behavior. This method can help identify parameters that are more sensitive to the rock mechanics performance of different lithofacies.

[0086] The sensitivity analysis of geological lithofacies rock mechanical parameters based on numerical simulation includes five steps:

[0087] First, based on the logging curve, the static results of rock mechanics measured indoors are calibrated, the rock mechanics curve of a single well is calculated, the dynamic rock mechanics of the core is obtained through wave velocity testing, the dynamic and static parameter conversion relationship is established, and the rock mechanics logging interpretation results are corrected.

[0088] Second, the continuous single-well lithofacies data are discretized and specific codes are used to represent the same lithofacies. Lithofacies with similar mechanical properties use codes of similar sizes.

[0089] Third, correlation analysis. Use statistical methods (such as regression analysis) to examine the relationship between the lithofacies code and rock mechanical parameters. Identify the parameters with large fluctuations in mechanical parameters under different lithofacies.

[0090] Fourth, sensitivity analysis. Sensitivity analysis methods, such as analysis of variance (ANOVA) or local sensitivity analysis, are used to further reveal the degree of influence of changes in rock mechanical parameters in different lithofacies on the overall behavior. Quantify the response of different rock phases to different mechanical parameters.

[0091] Fifth, optimize sensitive parameters. Rank all rock mechanical parameters and select the top parameters with the largest changes under different lithofacies for further analysis. Use statistical methods such as paired t-tests to make multiple comparisons of candidate parameters to determine their significant differences in different lithofacies. Construct an optimization model between lithofacies and rock mechanical parameters to accurately predict the mechanical behavior under different lithofacies.

[0092] In the example area, the lithofacies are numbered as follows: siltstone phase: 1; fine sandstone phase: 2; medium sandstone phase: 3; coarse sandstone phase: 4; mudstone phase: 5; limestone phase: 6. After the optimization of rock mechanics parameters, the four most sensitive rock mechanics parameters, elastic modulus, Poisson's ratio, brittleness index, and horizontal stress difference, were selected. Table 1 is a thermodynamic table of the correlation between the lithofacies and rock mechanics of a tight sandstone reservoir in a certain production area.

[0093] Table 1 Thermodynamic table of correlation between tight sandstone reservoir lithofacies and rock mechanics in a certain production area

[0094] Relevance Siltstone facies Fine sandstone facies Middle sandstone facies Coarse sandstone facies Mudstone phase Limestone phase Elastic modulus 0.71 0.77 0.76 0.73 0.84 0.70 Poisson's ratio 0.79 0.82 0.75 0.76 0.84 0.77 Brittleness Index 0.61 0.74 0.76 0.66 0.7 0.72 Cohesion 0.73 0.79 0.57 0.52 0.56 0.57 Fracture toughness 0.63 0.68 0.34 0.54 0.5 0.4 Burst pressure 0.61 0.77 0.36 0.58 0.41 0.46 Internal friction angle 0.38 0.61 0.38 0.39 0.47 0.38 tensile strength 0.48 0.77 0.31 0.44 0.36 0.39 Shear strength 0.48 0.35 0.3 0.43 0.38 0.44 Maximum horizontal principal stress 0.4 0.5 0.53 0.59 0.41 0.58 Minimum horizontal principal stress 0.47 0.43 0.43 0.43 0.52 0.56 Vertical stress 0.34 0.35 0.31 0.21 0.36 0.21 Horizontal stress difference 0.88 0.83 0.86 0.71 0.85 0.9

[0095] Using the brittle boundary partitioning method, the relationship between the elastic modulus and Poisson's ratio is visualized and the material properties are effectively partitioned by a negative slope straight line. It includes two steps:

[0096] First, construct a cross plot, collect and select appropriate sample materials, measure the elastic modulus (E) and Poisson's ratio (v) of each material, and plot the measured data points in the Ev coordinate system to form a scatter plot.

[0097] Second, draw a boundary line: Use regression analysis or empirical rules to draw a straight line with the properties of a linear function, with the formula ν = -kE + b, where k is the positive slope and b is the bias. The brittleness index can comprehensively consider the elastic modulus and Poisson's ratio of the rock, and is usually used to measure whether the rock is more prone to brittle fracture or plastic deformation when subjected to stress. Determine appropriate parameters so that the straight line effectively divides the sample data into the brittle zone (lower left area) and the ductile zone (upper right area).

[0098] Figure 6 The figure shows the intersection diagram of elastic modulus and Poisson's ratio of tight sandstone reservoir in a certain production area. According to statistics, it is found that when μ c ≥-3.695E c ×10 -3 +0.425 is brittle lithofacies, μ c <-3.695E c ×10 -3 +0.425 is a ductile lithofacies, so the brittleness index is used to evaluate the strain characteristics of the lithofacies. The lithofacies with a higher brittleness index have a higher content of brittle minerals, are more likely to form a fracture network, and the fractures are more stable. They can maintain the open state of the fractures after the pressure is released, reduce the energy consumed in the fracturing process and the amount of horizontal fracturing fluid, and improve the construction efficiency.

[0099] The horizontal stress difference in tight sandstone reservoirs has an important influence on the expansion of cracks. In horizontal multi-stage fracturing operations, the size of the horizontal stress difference will affect the formation, expansion and connection of cracks, thereby affecting the oil and gas production effect. A larger stress difference can lead to more energy concentrated at the front of the crack, a single crack type, and thus the cracks extend to a deeper depth in the rock. A smaller horizontal stress difference helps control the direction of crack expansion, increase the complexity of the crack network, and reduce the risk of formation damage. The determination of tight sandstone geological-mechanical coupled lithofacies stress factors based on the stress optimization identification model specifically includes two steps:

[0100] First, the construction of the intersection diagram. The scattered data of crack length and crack density are plotted on the horizontal stress difference (x-axis) and crack length / density (y-axis) diagrams to form two types of scattered points. An intersection area is designed, which corresponds to the intersection of crack length and crack density, that is, the comprehensive area where crack length decreases and crack density increases.

[0101] Second, the public area is preferred. An intersection area in a balanced position is preferred, and the left and right boundaries of the area are determined by the actual situation. At this time, the fracture length and fracture density reach the most suitable state, which may correspond to the best fracture effect of the formation and reduce the risk of formation damage. The horizontal stress difference corresponding to this area is the optimal horizontal stress difference. At this time, the complexity of the fracture network can be increased while ensuring the fracture depth, so as to improve the fluidity and exchange of oil and gas.

[0102] Figure 7 The figure shows the intersection diagram of the fracture length and density of the tight sandstone reservoir and the horizontal stress difference in a certain production area. When the horizontal stress difference of the tight sandstone reservoir is less than 5MPa, it usually has the geological conditions for volume fracturing and is prone to form a complex far-well fracture network.

[0103] The four factors of tight sandstone particle composition, particle size, brittleness index and horizontal stress difference were screened out, which can not only represent the differences in the geological conditions of tight sandstone reservoirs, but also reflect the different effects of brittleness, stress difference and fracture network construction, thus becoming the main controlling factors for the differences in tight gas potential of tight sandstone reservoirs in production areas.

[0104] According to the above analysis, relying on the differences in four factors, namely, tight sandstone grain composition, grain size, brittleness index, and horizontal stress difference, the following steps are used to determine the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs.

[0105] On the basis of the isosceles triangle chart of tight sandstone reservoir lithology classification, the particle size, horizontal stress difference and brittleness index are further coupled into the triangle chart to form a composite triangle chart model. According to the particle size, it is divided into silt sand (0.002 mm ~ 0.0625 mm), fine sand (0.0625 mm ~ 0.25 mm), medium sand (0.25 mm ~ 0.5 mm), and coarse sand (greater than 0.5 mm). According to the brittleness index, it is divided into toughness (0 ~ 0.5), low brittleness (0.5 ~ 0.65), medium brittleness (0.5 ~ 0.75), and high brittleness (greater than 0.75). According to the horizontal stress difference, it is divided into low stress difference (less than or equal to 5MPa) and high stress difference (greater than 5MPa). Based on the above division method, the composite isosceles triangle chart model of tight sandstone geological-mechanical coupled lithofacies classification is drawn. See the figure. Figure 8 .

[0106] The main parts of the naming are particle composition and particle size, and the horizontal stress difference and brittleness index are used as modifying prefixes, see Table 2.

[0107] Table 2 Components of geological-mechanical coupled lithofacies classification for tight sandstone reservoirs

[0108]

[0109] The geological-mechanical coupled lithofacies types were named, and finally a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs was established (see Table 3).

[0110] Fig. 9 The results of geological-mechanical coupled lithofacies classification of tight sandstone reservoirs in a certain production area are shown. The tight sandstone reservoirs in a certain production area are mainly composed of feldspar lithic sandstone, whose content can be as high as 78%, followed by lithic feldspar sandstone and lithic sandstone, whose contents are 13% and 9%, respectively. The geological-mechanical coupled lithofacies classification of this group shows that the geological-mechanical coupled lithofacies with a large proportion in the reservoir phase are: A low stress difference and low brittle feldspar lithic fine sandstone, B low stress difference and low brittle lithic fine sandstone, C low stress difference and ductile feldspar lithic fine sandstone, D low stress difference and low brittle feldspar lithic medium sandstone, E low stress difference and low brittle quartz fine sandstone, F low stress difference and ductile feldspar lithic medium sandstone. Among them, A, B, D, and E lithofacies all show the characteristics of fine grains, low stress difference, and low brittleness, and are potential lithofacies for fracturing transformation of tight sandstone reservoirs in the production area.

[0111] Table 3 Geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs

[0112]

[0113] The single-well identification results of the geological lithofacies of tight sandstone reservoirs were obtained by using the method of "a method for intelligent identification and visualization of continental tight reservoir lithofacies" (patent number 202011393013.1). On this basis, considering the differences in four factors, namely, particle composition, particle size, brittleness index, and horizontal stress difference, further geomechanical coupled lithofacies division was carried out at the single-well level based on the already formed geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs.

[0114] Through the geological-mechanical coupled lithofacies prediction method, there are usually two or more results. At this time, the integration of multiple types of lithofacies prediction results can be completed through three steps: numerical mapping, priority selection and classification processing.

[0115] First, numerical mapping: merge the two columns of facies numerical codes into a new column using summation.

[0116] Second, select the priority: in the two columns of prediction results under different conditions, select one column according to the priority. For example, lithofacies 1 is selected first, and lithofacies 2 is selected if the value is 0.

[0117] Third, multi-category processing: If you need to perform multi-category processing after merging, you can create a new column and assign values ​​through conditional judgment.

[0118] Through the above method, the single well geological-mechanical coupled lithofacies single well phase control quantitative prediction was completed in the example area. Based on the prediction results, a comprehensive columnar diagram of the geological-mechanical coupled lithofacies quantitative identification results of a well in a certain production area was drawn. Fig.10 .

[0119] Feature extraction and visualization of geological-mechanical coupled lithofacies based on 3D mesh models:

[0120] First, data collection and preparation: Collect data on geological, seismic and mechanical properties, including geological profiles, lithology, seismic wave velocity, porosity, permeability, etc. Perform data preprocessing, such as interpolation, denoising and normalization, to ensure the accuracy and completeness of the data.

[0121] Second, construct a three-dimensional grid model: According to the spatial distribution and characteristics of the geological body, a three-dimensional grid model is established. Finite element grids or other types of grid models can be used. Different geological units are subdivided in the grid model to better express the geological-mechanical characteristics.

[0122] Third, geological-mechanical coupled lithofacies feature extraction: The geological characteristics of each lithofacies (such as physical properties, elastic modulus, etc.) are extracted based on geological data and assigned to the corresponding cells in the three-dimensional model.

[0123] Fourth, geological-mechanical coupled lithofacies sensitive attribute analysis: consider the impact of geological attributes (such as stress field, fracture distribution, etc.) on seismic wave propagation. Select sensitive attributes: determine the type of seismic sensitive attributes, which usually include the following categories:

[0124] Elastic wave velocity (P wave, S wave velocity): closely related to the elastic characteristics of the lithofacies.

[0125] Impedance: Calculated by multiplying density by wave velocity, it reflects the physical state of rock.

[0126] Amplitude: reflects the changes in reflection interface characteristics and material properties during the propagation of seismic waves.

[0127] Frequency characteristics: Different rock phases respond differently to the frequency of seismic waves, which can reflect the details of the rock strata.

[0128] Fifth, seismic data processing and visualization: Process seismic waveform data and perform inversion to obtain information such as seismic wave velocity and impedance. Visualize the relationship between seismic data and geological-mechanical models in a three-dimensional model to form a three-dimensional sculpture effect of geological-mechanical coupled lithofacies seismic.

[0129] Fig.11 What is shown is the longitudinal wave impedance inversion profile of the tight sandstone geological-mechanical coupled lithofacies in a certain production area, which is based on the feature extraction and visualization of the geological-mechanical coupled lithofacies of a three-dimensional grid model.

[0130] Lithofacies classification feedback adjustment and seismic attribute mapping based on 3D modeling:

[0131] Use geological modeling software, such as Petrel, to integrate well data, seismic inversion results, and lithofacies information.

[0132] First, 3D modeling: Establish a 3D framework based on known geological features such as structures and faults. Use interpolation, Kriging methods, etc. to model the distribution of single wells and seismic carving results of different lithofacies in 3D space. Compare the lithofacies distribution predicted by the model with the actual downhole sampling results to analyze the error. Use 3D visualization software to intuitively present the deviation between the model prediction and the actual value, which is convenient for analysis and adjustment.

[0133] Second, feedback adjustment: According to the model verification results, adjust the lithofacies classification standards (such as adding new classification parameters), or optimize the parameter settings in the inversion algorithm. You can add more training samples or readjust the parameters to improve the accuracy of the model. Through continuous verification and correction, the optimal model is achieved. The data input and output of each step need to be recorded for easy tracking and improvement.

[0134] Third, result analysis: display the distribution characteristics of different lithofacies in three-dimensional space, and colors or shadows can represent different lithofacies types.

[0135] Fourth, seismic attribute mapping: combine seismic attributes (such as velocity and impedance) with lithofacies information using color mapping to analyze their correlation. Hierarchical analysis: define key levels in the model, identify major geological units and features, and help understand geological evolution and tectonic environment.

[0136] Fig.12 What is shown is a three-dimensional model of typical tight sandstone geological-mechanical coupling lithofacies in a certain production area after the feedback adjustment of lithofacies classification based on three-dimensional modeling and seismic attribute mapping. The six types of lithofacies that account for a relatively large volume in the three-dimensional space of the reservoir lithofacies in the statistical analysis area are: A low stress difference low brittle feldspar lithic fine sandstone, B low stress difference low brittle feldspar lithic fine sandstone, C low stress difference ductile feldspar lithic fine sandstone, D low stress difference low brittle feldspar lithic medium sandstone, E low stress difference low brittle quartz fine sandstone, F low stress difference ductile feldspar lithic medium sandstone. Among them, the more typical reservoir lithofacies are low stress difference low brittle feldspar lithic fine sandstone as the main reservoir lithofacies ( Figure 13-14 ), this type of lithofacies has good porosity and permeability, providing a basis for the storage and flow of fluids; the lower stress difference ensures that the rock is not easily damaged during hydraulic fracturing and other operations, and can better maintain its structural integrity and reduce unnecessary crack closure; the low brittleness allows the rock to form an effective fracture network when undergoing transformation, and can better withstand internal pressure, which helps to maintain the conductivity of the fracture. Statistics on the relationship between the tight gas production capacity and geological-mechanical coupled lithofacies of typical tight sandstone in a certain production area ( Fig.15 ), found that the corresponding production capacity of the four geological-mechanical coupled rock phases B, D, E, and F is much higher than that of other rock phases. Combined with geological and engineering factors, the B, D, E, and F rock phases have a higher production capacity due to their suitable particle size and particle composition, as well as reasonable stress difference and brittleness level. These four rock phases can effectively release their development potential under the typical geological environment and technical conditions of a certain production area.

[0137] In a typical tight sandstone reservoir in a production area, the established geomechanical coupled lithofacies model was used to establish a healthy rock mechanics parameter model. The brittleness index three-dimensional model before and after the geomechanical coupled lithofacies control was intercepted ( Fig.16 The results show that the brittle index distribution model after phase control better reflects the heterogeneity of sedimentary facies in terms of vertical and horizontal characteristics, which is better than the traditional Kriging or Gaussian interpolation 3D model. By projecting the rock mechanical parameters phase-controlled 3D model and the interpolation 3D model in a control well ( Fig.17), and found that the elastic modulus, Poisson's ratio, brittleness index, maximum and minimum horizontal principal stresses, and horizontal stress difference parameters all showed a distribution law consistent with the model, that is, the rock mechanical parameters after phase control all conformed to the parameter range in the geological-mechanical coupling lithofacies classification model table of tight sandstone reservoirs (Table 3). The heterogeneous distribution law of rock mechanics and geostress characteristics of tight sandstone reservoirs in the production area was accurately characterized, which provided technical support for the effective implementation of ultra-long horizontal wells + large-scale repeated fracturing of tight sandstone oil and gas in the area, and ultimately improved the production effect of tight sandstone oil and gas.

[0138] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig.18 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a well seismic analysis method based on a dense sandstone geological-mechanical coupled lithofacies system is implemented.

Claims

1. A well seismic analysis system based on tight sandstone geological-mechanical coupled lithofacies system, characterized in that: The well-seismic analysis system based on the tight sandstone geological-mechanical coupled lithofacies system includes: The information data acquisition module is used to acquire information data; the information data includes: characteristic core data and rock mechanics data; the characteristic core data includes characteristic data acquired by using the three-dimensional nine-point method and parameter data determined based on mechanical experiments; the rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical tests, taking the influence of lithofacies changes on rock strength and crack extension behavior as the research object, and acquiring parameter data sensitive to the rock mechanics performance of different lithofacies; A classification model construction module is connected to the information data acquisition module and is used to construct a geological-mechanical coupled lithofacies classification model of a tight sandstone reservoir according to information data by using a four-element composite triangular diagram method; The integration module is connected with the classification mode construction module and is used to perform geomechanical coupled lithofacies division and integrate multi-type lithofacies prediction results based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs at the single well level according to the element difference data to obtain the integrated results; the element difference data includes: grain composition, grain size, brittleness index and horizontal stress difference; The analysis and determination module is connected to the integration module and is used to extract the characteristics of the geological-mechanical coupling lithofacies, adjust the lithofacies classification feedback and map the seismic attributes based on the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir geological-mechanical coupling lithofacies according to the integration results, and determine the geological-mechanical coupling lithofacies distribution information data of the tight sandstone; the geological-mechanical coupling lithofacies well-seismic coordinated three-dimensional model of the tight sandstone reservoir is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupling lithofacies distribution information data of the tight sandstone is used to characterize the heterogeneous distribution law of the rock mechanics and geostress characteristics of the tight sandstone reservoir, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

2. The well seismic analysis system based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 1 is characterized in that: Classification mode building blocks include: The brittle factor determination submodule is connected to the information data acquisition module and is used to determine the geological-mechanical coupled lithofacies brittle factor of the dense sandstone by using the brittle boundary division method, visualizing the relationship between the elastic modulus and the Poisson's ratio according to the information data, and dividing the material properties through a negative slope straight line; The geostress factor determination submodule is connected to the information data acquisition module and is used to determine the geostress factors of the tight sandstone geological-mechanical coupling lithofacies according to the information data based on the stress optimization identification model; the stress optimization identification model is a physical model of the influence of horizontal stress difference on crack expansion in tight sandstone reservoirs, which is based on the influence of horizontal stress difference on the formation, expansion and connection of cracks in horizontal multi-stage fracturing operations; The plate determination submodule is connected to the brittleness factor determination submodule and the ground stress factor determination submodule respectively, and is used to process the composite triangle map mode based on the tight sandstone reservoir lithology classification isosceles triangle map, according to the tight sandstone geological-mechanical coupled lithofacies brittleness factor and the tight sandstone geological-mechanical coupled lithofacies ground stress factor, coupled grain size, horizontal stress difference and brittleness index, to obtain the tight sandstone geological-mechanical coupled lithofacies classification composite isosceles triangle map; The classification pattern construction submodule is connected to the plate determination submodule and is used to name the geological-mechanical coupling lithofacies types based on the tight sandstone geological-mechanical coupling lithofacies classification composite isosceles triangle plate, using particle composition and particle size as the naming parts and horizontal stress difference and brittleness index as modification prefixes, so as to determine the geological-mechanical coupling lithofacies classification pattern of the tight sandstone reservoir.

3. The well seismic analysis system based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 1 is characterized in that: The integrated modules include: The single well identification result acquisition submodule is used to obtain the single well identification results of the geological lithofacies of the tight sandstone reservoir; The division submodule is connected to the single well identification result acquisition submodule and the classification mode construction module respectively, and is used to perform geomechanical coupled lithofacies division at the single well level based on the tight sandstone reservoir geological-mechanical coupled lithofacies classification mode and the tight sandstone reservoir geological lithofacies single well identification result according to the element difference data to obtain the division result; The integration processing submodule is connected to the division submodule and is used to perform numerical mapping, priority selection and classification processing according to the division results, so as to integrate the multi-type lithofacies prediction results and obtain the integrated results.

4. A well-seismic analysis method based on tight sandstone geological-mechanical coupled lithofacies system, characterized in that: The method is implemented by the system described in any one of claims 1 to 3; the method comprises: Obtain information data; information data include: characteristic core data and rock mechanics data; characteristic core data include characteristic data obtained by three-dimensional nine-point method and parameter data determined based on mechanical experiments; rock mechanics data is based on the theory of lithofacies discretization and sensitivity analysis, by setting different lithofacies numerical tests, taking the influence of lithofacies changes on rock strength and crack propagation behavior as the research object, and obtaining parameter data sensitive to the rock mechanics performance of different lithofacies; The four-element composite triangulation method is used to construct a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on information data; At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs, geomechanical coupled lithofacies division and multi-type lithofacies prediction results were integrated according to the element difference data to obtain the integrated results; the element difference data include: grain composition, grain size, brittleness index and horizontal stress difference; Based on the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs, the characteristics of geological-mechanical coupled lithofacies are extracted, lithofacies classification feedback adjustment and seismic attribute mapping are carried out according to the integration results to determine the geological-mechanical coupled lithofacies distribution information data of tight sandstones; the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs is a physical model constructed based on the relationship between seismic data and geology-mechanics; the geological-mechanical coupled lithofacies distribution information data of tight sandstones is used to characterize the heterogeneous distribution law of rock mechanics and geostress characteristics of tight sandstone reservoirs, so as to provide a basis for improving the production effect of tight sandstone oil and gas.

5. The well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 4 is characterized in that: The four-element composite triangular diagram method is used to construct a geological-mechanical coupled lithofacies classification model for tight sandstone reservoirs based on information data, including: The brittle boundary division method is adopted to determine the geological-mechanical coupled lithofacies brittleness factor of tight sandstone based on information data, by visualizing the relationship between elastic modulus and Poisson's ratio, and dividing the material properties through a negative slope straight line; Based on the stress optimization identification model, the geological-mechanical coupled lithofacies stress factors of tight sandstone are determined according to information data; the stress optimization identification model is a physical model of the influence of horizontal stress difference on crack expansion in tight sandstone reservoirs, which is based on the influence of horizontal stress difference on crack formation, expansion and connection in horizontal multi-stage fracturing operations; Based on the isosceles triangle chart of tight sandstone reservoir lithology classification, according to the tight sandstone geological-mechanical coupled lithofacies brittleness factor and tight sandstone geological-mechanical coupled lithofacies in-situ stress factor, the coupled grain size, horizontal stress difference and brittleness index are processed into a composite triangle chart model to obtain a tight sandstone geological-mechanical coupled lithofacies classification composite isosceles triangle chart; Based on the composite isosceles triangle plate of tight sandstone geological-mechanical coupled lithofacies classification, the geological-mechanical coupled lithofacies types are named with particle composition and particle size as the naming parts, and horizontal stress difference and brittleness index as modified prefixes, and the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs is determined.

6. The well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 4 is characterized in that: At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs, geomechanical coupled lithofacies division and multi-type lithofacies prediction results were integrated according to the element difference data to obtain the integrated results, including: Obtain single-well identification results of tight sandstone reservoir geological lithofacies; At the single well level, based on the geological-mechanical coupled lithofacies classification model of tight sandstone reservoirs and the geological lithofacies single well identification results of tight sandstone reservoirs, the geomechanical coupled lithofacies division is carried out according to the element difference data to obtain the division results; According to the division results, numerical mapping, priority selection and classification processing are carried out to integrate the multi-type lithofacies prediction results and obtain the integrated results.

7. The well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 4 is characterized in that: The method for determining the geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs specifically includes: Obtaining raw data; raw data is data containing geological, seismic and mechanical properties; raw data includes geological profiles, lithology data, seismic wave velocity, porosity and permeability; Perform data preprocessing on the original data to obtain processed data; the preprocessing includes: interpolation, denoising and normalization; Construct a three-dimensional grid model; a three-dimensional network model is a physical model constructed based on the spatial distribution and characteristics of the geological body to characterize the relationship between geological and mechanical characteristics; Perform geological-mechanical coupled lithofacies feature extraction on the processed data to obtain extracted data; Based on geological attribute data and extracted data, geological-mechanical coupled lithofacies sensitive attribute analysis is performed to obtain analytical data; According to the analysis data, inversion is performed based on the three-dimensional grid model to determine the inversion information data; the inversion information data includes: seismic wave velocity and impedance; The inversion information data is compared with the actual downhole sampling results, and the inversion parameters of the three-dimensional grid model are trained and adjusted with the goal of minimizing the error of the comparison result to obtain the adjusted three-dimensional grid model; The adjusted three-dimensional grid model is determined as a geological-mechanical coupled lithofacies well-seismic coordinated three-dimensional model of tight sandstone reservoirs.

8. The well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 4 is characterized in that: Characteristic data include: lithology, grain type and grain size.

9. The well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system according to claim 4 is characterized in that: Parameter data include: elastic modulus, Poisson's ratio, brittleness, cohesion, fracture toughness, rupture pressure, internal friction angle, tensile strength, shear strength, maximum horizontal principal stress, minimum horizontal principal stress, vertical stress and horizontal stress difference.

10. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the well-seismic analysis method based on the tight sandstone geological-mechanical coupled lithofacies system as described in any one of claims 4 to 9.

Images