A method for calculating the thickness of erosion of a formation

Abstract

The application discloses a stratum denudation thickness calculation method, comprising the following steps: obtaining geothermal data of different depths of a target stratum through a thermal advection coupled geothermal field inversion model, extracting paleotemperature data of fluid inclusions in a core sample by using a fluid inclusion paleotemperature scale denudation model, and determining the variation characteristics of a paleogeothermal gradient; subsequently, processing mudstone porosity data by using a mudstone compaction curve dynamic fitting algorithm, establishing a dynamic relationship between porosity and burial depth, and optimizing the compaction curve; inputting the data into a three-dimensional stratum denudation modeling analysis platform, constructing a three-dimensional space structure model of the target stratum, adjusting modeling parameters in combination with the variation of the geothermal gradient and the paleogeothermal evolution characteristics, and simulating the stratum denudation process; and finally, calculating the denudation thickness of different positions of the target stratum according to the simulation results and the mudstone compaction degree parameters. The method improves the accuracy of stratum denudation thickness calculation through the collaborative application of multiple models and algorithms.

Description

Technical Field

[0001] This invention relates to the field of geological erosion thickness calculation technology, and in particular to a method for calculating geological erosion thickness. Background Technology

[0002] In geological exploration, oil and gas resource assessment, and stratigraphic evolution research, accurate calculation of stratigraphic erosion thickness is crucial for revealing geological history and clarifying stratigraphic development patterns. As exploration targets extend into complex tectonic regions, traditional methods for calculating erosion thickness based on single geological indicators are insufficient to meet high-precision requirements. Currently, the influence of thermal advection on the geothermal field, the paleoenvironmental information contained in fluid inclusions, the dynamic changes in mudstone compaction processes, and the complexity of stratigraphic structures in three-dimensional space all place higher demands on erosion thickness calculation. Integrating multiple models and algorithms to establish a systematic calculation method has become an important direction for solving the problem of calculating stratigraphic erosion thickness in complex areas and improving the accuracy of geological interpretation, providing significant support for subsequent resource exploration deployment and geological theoretical research.

[0003] Existing technologies for calculating stratigraphic erosion thickness suffer from two significant drawbacks. Firstly, current methods often rely solely on one technique among geothermal field inversion, fluid inclusion analysis, or mudstone compaction curve fitting, failing to achieve deep coupling of multiple techniques. This results in the inability to fully integrate different types of geological parameters during the calculation, making the accuracy of the final erosion thickness result susceptible to deviations from a single parameter. Secondly, existing 3D stratigraphic modeling platforms lack dynamic adaptability to geological evolution history when simulating erosion processes. They struggle to adjust modeling parameters in real-time based on dynamic parameters such as paleothermal gradient changes and diagenetic stages, leading to discrepancies between simulation results and actual stratigraphic erosion processes. Consequently, they fail to accurately reflect the true changes in stratigraphic thickness across different geological periods. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a method for calculating the thickness of stratum erosion.

[0005] The technical solution adopted in this invention is a method for calculating the thickness of strata erosion, comprising the following steps: S1, obtaining geothermal data at different depths within the target stratum region through a thermal advection coupled geothermal field inversion model. This model is based on the coupling relationship between the heat conduction equation and the heat convection equation, integrating parameters such as the thermal conductivity of strata lithology, porosity, and underground fluid flow velocity to perform inversion calculations on the geothermal field of the target region; S2, analyzing fluid inclusions in the core samples of the target strata using a fluid inclusion paleotherm erosion model, extracting paleotherm temperature data at the time of inclusion formation. This model combines the homogenized temperature test results of inclusions with the burial evolution history of the strata to determine the paleotherm temperature gradient variation characteristics; S3, processing the porosity data of the mudstone samples of the target strata using a mudstone compaction curve dynamic fitting algorithm. This algorithm establishes a dynamic functional relationship between mudstone porosity and burial depth, introducing parameters such as compaction coefficient, initial porosity, and diagenetic stage to... S4. The geothermal data obtained in S1, the paleotemperature data extracted in S2, and the fitted mudstone compaction curve data in S3 are input into the three-dimensional stratigraphic erosion modeling and analysis platform. This platform, based on three-dimensional geological modeling technology, constructs a three-dimensional spatial structure model of the target stratum, integrating parameters such as stratigraphic interface depth, lithological distribution, and tectonic morphology. S5. The erosion process of the target stratum is simulated through the three-dimensional stratigraphic erosion modeling and analysis platform. The modeling parameters are adjusted by combining the geothermal gradient changes output by the thermal advection coupled geothermal field inversion model and the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model. S6. Based on the simulation results in S5, and combined with the mudstone compaction degree parameters obtained by the mudstone compaction curve dynamic fitting algorithm, the erosion thickness at different locations of the target stratum is calculated through the three-dimensional stratigraphic erosion modeling and analysis platform. The original thickness, current thickness, and erosion coefficient parameters of the stratum are introduced during the calculation process to complete the calculation of the stratigraphic erosion thickness.

[0006] Furthermore, in the aforementioned thermal advection coupled geothermal field inversion model, geothermal data inversion is achieved through the following formula: ,in, For depth At any time The ground temperature, The initial surface temperature, For depth At any time The thermal conductivity of the strata lithology, The velocity of underground fluid flow. For underground fluid density, The specific heat capacity of underground fluids. For formation permeability, For geological time, For integration variables, This is the time variable for integration.

[0007] Furthermore, in the fluid inclusion paleotherm erosion model, the paleothermal gradient is determined using the following formula: ,in, This is the paleothermal gradient. The homogenization temperature of the fluid inclusions. The surface temperature at which the inclusions formed. The burial depth at which the inclusions formed. This is the paleothermal gradient correction factor. The time when inclusions begin to form. This refers to the end time of inclusion formation. For a moment The temperature of the inclusion body, For a moment The ancient surface temperature.

[0008] Furthermore, in the dynamic fitting algorithm for the mudstone compaction curve, the dynamic functional relationship between mudstone porosity and burial depth is realized through the following formula: ,in, For depth At any time mudstone porosity, The initial porosity of mudstone. This is the compaction coefficient. The coefficient representing the influence of diagenesis. The decay coefficient of diagenesis time. For geological time, For integration time variable, This refers to the burial depth.

[0009] Furthermore, in the aforementioned three-dimensional stratum erosion modeling and analysis platform, the construction of the three-dimensional spatial structure model of the strata is achieved through the following formula: ,in, Three-dimensional spatial coordinates Stratigraphic model values ​​at the location, For the first The weighting coefficients of each stratum, The number of stratigraphic layers. Three-dimensional spatial coordinates The depth function of the stratigraphic interface at that location. For the first Lithological distribution function of strata, For the first Structural morphology correction function for strata. These are the horizontal, vertical, and depth coordinates in three-dimensional space, respectively.

[0010] Furthermore, the thickness of the eroded strata is calculated using the following formula: ,in, Two-dimensional plane coordinates The thickness of the eroded strata at that location. The original thickness of the strata. This represents the current thickness of the strata. Three-dimensional spatial coordinates The erosion correction factor at the location. Two-dimensional plane coordinates, These are depth coordinates.

[0011] Further, step S3 includes the following sub-steps: S31, collecting mudstone samples from different depths of the target stratum, performing porosity tests on each mudstone sample to obtain multiple porosity data points, and simultaneously recording the burial depth and sampling location information corresponding to each sample; S32, filtering the obtained porosity data, removing abnormal data points, and grouping the filtered data according to the lithological characteristics and diagenetic stage division results of the mudstone samples; S33, inputting the grouped porosity data and corresponding burial depth data into the mudstone compaction curve dynamic fitting algorithm, and setting the initial values ​​of the initial compaction coefficient, initial porosity, and diagenetic stage parameters; S34, running the mudstone compaction curve dynamic fitting algorithm, adjusting the parameter values ​​through iterative calculation to minimize the deviation between the fitted curve and the actual data points, and obtaining the optimized mudstone compaction curve and related parameters.

[0012] Further, step S4 includes the following sub-steps: S41, organizing the geothermal data obtained in S1, dividing the data according to depth intervals to form a geothermal data matrix, and simultaneously sorting the paleotemperature data extracted in S2 according to geological time to construct a paleotemperature evolution sequence; S42, converting the mudstone compaction curve fitted in S3 into digital data, extracting porosity values ​​corresponding to different depths, and establishing a porosity-depth database; S43, starting the three-dimensional stratigraphic erosion modeling and analysis platform, importing the basic geological data of the target area, including stratigraphic outcrop data, drilling data, and seismic exploration data, and constructing an initial three-dimensional geological framework; S44, importing the geothermal data matrix, paleotemperature evolution sequence, and porosity-depth database into the three-dimensional stratigraphic erosion modeling and analysis platform respectively, performing data matching and integration with the initial three-dimensional geological framework to form a complete three-dimensional spatial structure model of the target stratigraphy.

[0013] Further, S5 includes the following sub-steps: S51, in the three-dimensional stratigraphic erosion modeling and analysis platform, setting the time range and time step of the erosion simulation, and determining the start and end times of the erosion process based on the geological structural evolution history of the target area; S52, calling the output results of the thermal advection coupled geothermal field inversion model to obtain geothermal gradient data of different geological periods, and using them as the temperature boundary conditions for the erosion simulation; S53, combining the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model, adjusting the paleoenvironmental parameters in the three-dimensional stratigraphic erosion modeling and analysis platform, including paleoatmospheric temperature and paleowater temperature; S54, running the erosion simulation module of the three-dimensional stratigraphic erosion modeling and analysis platform, simulating the erosion process of the target stratum step by step according to the set time step, and recording the stratigraphic thickness change data in real time.

[0014] A method for calculating stratigraphic erosion thickness is implemented through different units, including: a thermal advection coupled geothermal field data acquisition and processing unit, which is connected to geothermal monitoring equipment in the target stratigraphic area to receive geothermal monitoring data and process the data using a thermal advection coupled geothermal field inversion model to output geothermal gradient data; a fluid inclusion paleothermometric analysis unit, which is connected to a fluid inclusion testing instrument to receive homogenized temperature test data of inclusions, analyze the data using a fluid inclusion paleothermometric erosion model, and output paleothermometric evolution data; and a mudstone compaction curve fitting and processing unit, which is connected to a mudstone porosity testing device to acquire mudstone porosity data, fit the data using a mudstone compaction curve dynamic fitting algorithm, and output the fitted mudstone compaction curve data. The system comprises: a 3D stratigraphic modeling data integration unit, which is connected to the thermal advection coupled geothermal field data acquisition and processing unit, the fluid inclusion paleotherm analysis unit, and the mudstone compaction curve fitting processing unit; a 3D stratigraphic erosion simulation calculation unit, which is connected to the 3D stratigraphic modeling data integration unit; a 3D stratigraphic erosion simulation calculation unit, which is connected to the 3D stratigraphic erosion simulation calculation unit; a stratigraphic erosion thickness calculation and output unit, which is connected to the 3D stratigraphic erosion simulation calculation unit; a 3D ... unit, which is connected to the 3D stratigraphic erosion simulation calculation unit; a 3D stratigraphic erosion thickness calculation unit, which is connected to the mudstone compaction parameters output by the mudstone compaction curve fitting processing unit; and a 3D stratigraphic erosion thickness calculation unit, which is connected to the 3D stratigraphic erosion simulation calculation unit; and a 3D stratigraphic erosion thickness calculation unit, which is connected to the mudstone compaction parameters output by the mudstone compaction curve fitting processing unit; and a 3D stratigraphic erosion thickness calculation unit, which outputs the calculation results in digital form.

[0015] Beneficial Effects: This invention proposes a method for calculating stratigraphic erosion thickness. By integrating a thermal advection coupled geothermal field inversion model, a fluid inclusion paleotherm erosion model, a mudstone compaction curve dynamic fitting algorithm, and a three-dimensional stratigraphic erosion modeling and analysis platform, it achieves deep coupling of multiple technologies. This systematically integrates various types of geological parameters, such as geothermal data, paleotherm data, and mudstone compaction curve data, avoiding the problem of insufficient parameter utilization caused by reliance on a single technology, and significantly improving the accuracy of erosion thickness calculation. Simultaneously, it incorporates dynamic geological evolution parameters into the three-dimensional stratigraphic erosion modeling and analysis platform, combined with thermal advection... The geothermal gradient changes output by the flow-coupled geothermal field inversion model, the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model, and the diagenetic stage parameters obtained by the mudstone compaction curve dynamic fitting algorithm can adjust the modeling parameters in real time, enhance the dynamic adaptability to geological evolution history, make the simulation results more consistent with the actual stratigraphic erosion process, accurately reflect the stratigraphic thickness changes in different geological periods, provide more reliable technical support for geological exploration, oil and gas resource assessment and stratigraphic evolution research, effectively solve the problem of calculating stratigraphic erosion thickness in complex tectonic areas, and improve the accuracy of geological interpretation. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method steps of the present invention; Figure 2 This is a diagram showing the unit composition for implementing the method of the present invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 As shown, a method for calculating the thickness of strata erosion includes the following steps: S1. Geothermal data at different depths within the target stratum are obtained through a thermal advection coupled geothermal field inversion model. This model is based on the coupling relationship between the thermal conduction equation and the thermal convection equation, and integrates the thermal conductivity, porosity, and underground fluid flow velocity parameters of the stratum lithology to perform inversion calculations on the geothermal field of the target area. Specifically, in step S1, the scope of the target geological region is first determined, typically a square area with sides of 5 to 10 kilometers. Within this area, geothermal monitoring points are deployed at intervals of 2 kilometers x 2 kilometers. Each monitoring point is drilled to a depth of 2000 to 5000 meters using a well. High-precision geothermal sensors are used to collect geothermal data at 100-meter depth intervals, collecting a total of 20 to 50 sets of data. Then, the thermal advection coupled geothermal field inversion model is activated, inputting the collected geothermal data and simultaneously importing existing stratigraphic lithology data for the region. The thermal conductivity of sandstone is set to 2.0 to 3.0 Kelvin per meter, and the thermal conductivity of mudstone is set to 1.5 to 2.5 Kelvin per meter. Porosity gradually decreases from 35% to 45% at the surface to 5% to 10% at a depth of 5000 meters. The underground fluid flow velocity is set to 0.01 to 0.1 meters per day based on regional hydrogeological data. The model performs calculations by coupling heat conduction and heat convection equations, with the number of iterations set to 50 to 100. In each iteration, the thermal conductivity and fluid flow velocity parameters are adjusted, and the final output is geothermal data at different depths in the region. This data can be used to analyze the temperature distribution of the formation and provide a basic temperature field support for the calculation of erosion thickness.

[0019] S2. The fluid inclusions in the core samples of the target strata were analyzed using the fluid inclusion paleotherm erosion model to extract the paleotherm temperature data at the time of inclusion formation. The model combined the homogenized temperature test results of inclusions with the burial evolution history of the strata to determine the characteristics of paleothermal gradient changes. Specifically, in step S2, samples are first selected from existing drill cores within the target stratigraphic region. Three to five core samples are selected from each well, with a length of 10 to 20 cm and a diameter of 5 to 10 cm, ensuring the samples are free of cracks and intact. The core samples are then sent to a laboratory where fluid inclusion microscopy is used to observe the samples, identify and mark fluid inclusions, marking 10 to 20 inclusions per sample. Subsequently, a microthermometry is used to perform homogenization temperature testing on the marked inclusions, with a testing accuracy controlled within ±0.1 degrees Celsius. The homogenization temperature data for each inclusion is recorded. Next, the fluid inclusion paleothermometric erosion model is activated, inputting the obtained homogenization temperature data, and simultaneously importing stratigraphic evolution data for the region, including stratigraphic thickness and deposition rate for each geological period. The Paleogene deposition rate is set to 0.1 to 0.2 mm per year, and the Neogene deposition rate is set to 0.2 to 0.3 mm per year. The model analyzes the relationship between the temperature at which inclusions formed and the burial depth of the strata to determine the characteristics of paleotemperature gradient changes and outputs paleotemperature gradient data for different geological periods such as the Paleogene and Neogene. These data can provide paleotemperature background support for subsequent simulations of strata erosion processes.

[0020] S3. The porosity data of mudstone samples from the target formation are processed by a dynamic fitting algorithm for mudstone compaction curve. This algorithm establishes a dynamic functional relationship between mudstone porosity and burial depth, and introduces compaction coefficient, initial porosity and diagenetic stage parameters to fit and optimize the mudstone compaction curve. Specifically, in step S3, mudstone samples are first collected from wells within the target formation area. Two to three mudstone samples are collected from each well at different depths (e.g., 500 meters, 1000 meters, 1500 meters, etc.), with each sample weighing 50 to 100 grams. The samples are immediately sealed and preserved after collection to prevent moisture loss. The mudstone samples are then sent to a laboratory where a porosity meter is used to test their porosity. The testing method employs helium displacement, with a testing accuracy controlled within ±0.1%. Each sample is tested three times, and the average value is taken as the porosity data for that sample. A total of 30 to 50 sets of porosity data corresponding to the burial depth are obtained. Subsequently, a dynamic fitting algorithm for mudstone compaction curves was initiated. Porosity and burial depth data were input, and initial parameters were set. The initial porosity was set to 40% to 50% based on surface mudstone sample test results. The compaction coefficient was set to 0.0005 to 0.001 per meter, referencing regional geological data. The diagenetic stage parameters were divided by depth into early diagenetic stage (surface to 1000 meters), mid-diagenetic stage (1000 to 3000 meters), and late diagenetic stage (3000 to 5000 meters), with different parameter values ​​corresponding to different stages. The algorithm established a dynamic functional relationship between porosity and burial depth, performing iterative fitting calculations. The number of iterations was set to 30 to 50. Each iteration adjusted the compaction coefficient and diagenetic stage parameters to keep the deviation between the fitted curve and the actual test data within 5%. Finally, the optimized mudstone compaction curve and related parameters were output. This curve reflects the compaction variation law of mudstone with burial depth, providing a reference for subsequent calculations of stratum erosion thickness.

[0021] S4. Input the geothermal data obtained in S1, the paleotemperature data extracted in S2, and the mudstone compaction curve data fitted in S3 into the three-dimensional stratum erosion modeling and analysis platform. This platform is based on three-dimensional geological modeling technology to construct a three-dimensional spatial structure model of the target stratum and integrate stratum interface depth, lithological distribution, and structural morphology parameters. Specifically, in step S4, the geothermal data output from step S1 is first organized into a depth-geothermal data table at 100-meter depth intervals, totaling 20 to 50 rows. The paleotemperature data output from step S2 is categorized by geological period (Paleogene, Neogene, Quaternary) and organized into a period-paleothermal gradient data table. The mudstone compaction curve data output from step S3 is used to extract the porosity values ​​corresponding to each 100-meter depth and organized into a depth-porosity data table. Subsequently, the three-dimensional stratigraphic erosion modeling and analysis platform is launched, and the basic geological data of the target area is imported into the platform, including topographic data (resolution 10m × 10m), stratigraphic interface data (obtained through seismic exploration, with interface depth error controlled within ±5m), lithological distribution data (classified and labeled according to sandstone, mudstone, limestone, etc.), and structural morphology data (including fault location, fold morphology, etc.). Based on 3D geological modeling technology, the platform first constructs a 3D topographic framework of the target area. Then, according to stratigraphic interface data and lithological distribution data, stratigraphic information is added layer by layer. The thickness of each stratigraphic layer is set to 50 to 200 meters based on drilling data, and the lithological distribution is assigned according to actual exploration results. Next, the processed geothermal data, paleotemperature data, and mudstone compaction curve data are imported into the platform. A data matching algorithm is used to associate the data with corresponding locations in the 3D topographic framework, with the association error controlled within 10 meters. Finally, a 3D spatial structure model of the target stratigraphy, including parameters such as temperature and porosity, is constructed. This model can intuitively present the spatial distribution and parameter characteristics of the target stratigraphy, providing a basic model support for subsequent simulation of the erosion process.

[0022] S5. Simulate the erosion process of the target strata through a three-dimensional stratum erosion modeling and analysis platform. Combine the geothermal gradient changes output by the thermal advection coupled geothermal field inversion model and the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model, and adjust the modeling parameters. Specifically, in step S5, erosion simulation parameters are first set in the 3D stratigraphic erosion modeling and analysis platform. The simulation time range is set from the end of the Neogene to the Quaternary, a period of 23 to 26 million years, based on the geological evolution history of the target area. The time step is set to 100,000 years, meaning stratigraphic change data is recorded every 100,000 years. Then, the geothermal gradient data output in step S1 is used, with geothermal gradient values ​​at different depths serving as the simulation's temperature boundary conditions. The surface geothermal gradient is set to 0.03 to 0.05 degrees Celsius per meter, and the geothermal gradient at a depth of 5000 meters is set to 0.02 to 0.03 degrees Celsius per meter. Simultaneously, the paleothermal evolution data output in step S2 is imported. Based on the paleothermal gradients of different geological periods, the paleoenvironmental parameters in the platform are adjusted. For example, the paleoatmospheric temperature at the end of the Paleogene is set to 25 to 30 degrees Celsius, and the Quaternary paleoatmospheric temperature is set to 10 to 15 degrees Celsius. Next, the platform's erosion simulation module was activated. Based on the set time step and considering temperature boundary conditions and paleoenvironmental parameters, the module simulated the erosion process of strata under weathering and other effects. The erosion rate was set to 0.001 to 0.005 mm per year, referencing regional geological data. The erosion rate varied among different lithologies, with sandstone exhibiting a higher erosion rate than mudstone. During the simulation, the platform recorded real-time data on changes in stratum thickness and interface depth at each time step, generating 230 to 260 sets of simulation data. This data reflects the dynamic process of stratum erosion, providing process data support for subsequent calculations of erosion thickness.

[0023] S6. Based on the simulation results of S5, and combined with the mudstone compaction degree parameters obtained by the mudstone compaction curve dynamic fitting algorithm, the erosion thickness at different locations of the target stratum is calculated through the three-dimensional stratum erosion modeling and analysis platform. The original thickness, current thickness and erosion coefficient parameters of the stratum are introduced in the calculation process to complete the calculation of stratum erosion thickness.

[0024] Specifically, during the implementation of step S6, key information is first extracted from the simulation data output in step S5, including the original thickness and current thickness data of the target strata at different locations at each time step, as well as the depth change data of the strata interface, extracting relevant data from 50 to 100 locations. Then, the mudstone compaction parameters output in step S3 are imported, including the compaction coefficient and porosity change rate at different depths. The compaction coefficient is used to correct for deviations in strata thickness caused by compaction, and the porosity change rate is used to determine whether the strata have undergone erosion (areas with abnormally increased porosity are identified as potentially eroded). The erosion thickness calculation module is activated in the 3D stratigraphic erosion modeling and analysis platform. The module first calculates the initial erosion thickness based on the difference between the original and current thicknesses. Then, it corrects the initial value by incorporating mudstone compaction parameters. During the correction process, for areas with a porosity change rate greater than 10%, the initial erosion thickness value is multiplied by a correction factor of 1.1 to 1.2; for areas with a porosity change rate less than 5%, the initial erosion thickness value is multiplied by a correction factor of 0.9 to 1.0. After calculation, the platform outputs the final erosion thickness data at different locations in the target stratigraphic layer, with data accuracy controlled within ±10 meters. Simultaneously, it generates erosion thickness contour maps, clearly presenting the spatial distribution characteristics of the erosion thickness in the target area. This result can be directly used for geological exploration planning, oil and gas resource assessment, and other work, providing accurate stratigraphic erosion thickness data support for relevant decision-making.

[0025] Preferably, in the thermal advection coupled geothermal field inversion model, geothermal data inversion is achieved through the following formula: ,in, For depth At any time The ground temperature, The initial surface temperature, For depth At any time The thermal conductivity of the strata lithology, The velocity of underground fluid flow. For underground fluid density, The specific heat capacity of underground fluids. For formation permeability, For geological time, For integration variables, This is the time variable for integration.

[0026] Specifically, when implementing the geothermal data inversion using the thermal advection coupled geothermal field inversion model, the specific value range and determination method of each parameter must first be clarified. The initial surface temperature is set based on the average surface temperature data of the target area over the past 50 years, typically between 10 and 25 degrees Celsius. If there are significant seasonal temperature differences in the area, the annual average value should be used to reduce errors. The thermal conductivity of the lithology needs to be determined in conjunction with the regional geological survey report. For sandstone strata, the value is 2.0 to 3.0 Kelvin per meter; for mudstone strata, it is 1.5 to 2.5 Kelvin per meter; and for limestone strata, it is 2.5 to 3.5 Kelvin per meter. Values ​​must be assigned segment by segment according to the lithological distribution at different depths. The underground fluid flow velocity is obtained through regional hydrological test data. The fluid velocity in porous reservoirs is typically 0.01 to 0.1 meters per day, while in fractured reservoirs, the velocity can be increased to 0.1 to 0.5 meters per day. Geological time parameters need to be determined based on isotopic dating data of the target strata, generally covering the complete geological period from the formation of the strata to the present, spanning millions to hundreds of millions of years. During implementation, the parameters are first input into the model, and the model is run for 50 to 100 iterations. In each iteration, the thermal conductivity and fluid velocity are adjusted until the deviation between the calculated geothermal data and the actual monitored data is less than 0.5 degrees Celsius. This inversion process accurately reflects the influence of thermal advection on the geothermal field. The output geothermal data at different depths and times can be used as temperature boundary conditions for subsequent stratum erosion simulations, improving the realism of the temperature field in the simulation process.

[0027] Preferably, in the fluid inclusion paleotherm erosion model, the paleothermal gradient is determined by the following formula: ,in, This is the paleothermal gradient. The homogenization temperature of the fluid inclusions. The surface temperature at which the inclusions formed. The burial depth at which the inclusions formed. This is the paleothermal gradient correction factor. The time when inclusions begin to form. This refers to the end time of inclusion formation. For a moment The temperature of the inclusion body, For a moment The ancient surface temperature.

[0028] Specifically, when determining the paleothermal gradient of the fluid inclusion paleotherm erosion model, strict control was exercised over the parameter acquisition and calculation process. The homogenization temperature of fluid inclusions was obtained using a microthermometer. Before testing, the core samples were sliced ​​and polished to ensure clear visibility of the inclusions. Each inclusion was measured three times, and the average value was used as the final data, with an accuracy controlled within ±0.1 degrees Celsius. Typically, 10 to 20 inclusions were tested for a single sample to ensure data representativeness. The surface temperature at the time of inclusion formation was determined with reference to regional paleoclimate research results: 25 to 30 degrees Celsius for warm and humid regions during the Paleogene, 20 to 25 degrees Celsius for the Neogene, and 10 to 15 degrees Celsius for regions affected by the Quaternary glaciation. The burial depth at the time of inclusion formation was determined based on the interpretation results of well stratigraphic columns and seismic profiles. Combined with the stratigraphic sedimentary sequence and contact relationships, the original burial depth of the strata where the inclusions formed was estimated, with an error controlled within ±50 meters. The paleotemperature gradient correction coefficient is set according to the intensity of regional tectonic activity, with values ​​ranging from 0.01 to 0.02 for tectonically stable regions and from 0.02 to 0.03 for tectonically active regions. The time range of inclusion formation is determined through stratigraphic isotope dating and fossil assemblage analysis, typically spanning 1 million to 5 million years. The initial paleotemperature gradient is obtained by substituting basic parameters into the calculation, and then adjusted using the correction coefficient. The final output paleotemperature gradient data accurately reflects the temperature variation patterns in different geological periods, providing key temperature parameter support for paleoenvironmental simulation of stratigraphic erosion processes.

[0029] Preferably, in the dynamic fitting algorithm for the mudstone compaction curve, the dynamic functional relationship between mudstone porosity and burial depth is realized through the following formula: ,in, For depth At any time mudstone porosity, The initial porosity of mudstone. This is the compaction coefficient. The coefficient representing the influence of diagenesis. The decay coefficient of diagenesis time. For geological time, For integration time variable, This refers to the burial depth.

[0030] Specifically, in the dynamic fitting algorithm for mudstone compaction curves, the establishment of the dynamic functional relationship between mudstone porosity and burial depth involves step-by-step parameter calculations. Initial mudstone porosity is obtained by collecting fresh mudstone samples from the surface using the helium displacement method. Each sample is tested five times, and the average value is taken, with an accuracy controlled within ±0.1%. Typically, three to five surface samples from different locations are tested, with values ​​generally ranging from 40% to 50%. The compaction coefficient needs to be determined based on existing mudstone compaction research data in the region, while also referencing measured porosity values ​​of mudstone at different depths in the well for correction. The compaction coefficient is 0.0008 to 0.001 per meter for shallow layers (surface to 1000 meters), 0.0005 to 0.0008 per meter for middle layers (1000 to 3000 meters), and 0.0003 to 0.0005 per meter for deep layers (3000 to 5000 meters). The diagenetic influence coefficient is set based on the mineral composition analysis of the mudstone. Mudstone with high clay mineral content is assigned a value of 0.02 to 0.03, while mudstone with high quartz and feldspar content is assigned a value of 0.01 to 0.02. The diagenetic time decay coefficient is determined by referencing the depositional rate and diagenetic age of the regional strata. Strata with fast depositional rates are assigned a value of 0.001 to 0.002 per year, while strata with slow depositional rates are assigned a value of 0.0005 to 0.001 per year. The geological time parameter covers the complete period from the beginning of mudstone deposition to the present and needs to be accurately set based on stratigraphic dating data. During calculation, initial parameters are first input to obtain a preliminary fitting curve. Then, the parameters are adjusted through 30 to 50 iterations to control the deviation between the fitted curve and the measured porosity data within 5%. The resulting dynamic function relationship can accurately reflect the compaction changes of mudstone at different burial depths and geological periods, providing a precise basis for subsequent calculations of stratigraphic erosion thickness.

[0031] Preferably, in the three-dimensional stratum erosion modeling and analysis platform, the three-dimensional spatial structure model of the stratum is constructed using the following formula: ,in, Three-dimensional spatial coordinates Stratigraphic model values ​​at the location, For the first The weighting coefficients of each stratum, The number of stratigraphic layers, Three-dimensional spatial coordinates The depth function of the stratigraphic interface at that location. For the first Lithological distribution function of strata, For the first Structural morphology correction function for strata. These are the horizontal, vertical, and depth coordinates in three-dimensional space, respectively.

[0032] Specifically, in the 3D stratigraphic erosion modeling and analysis platform, the 3D spatial structure model of the stratigraphy integrates parameters and data processing. Weight coefficients are set according to the thickness and importance of each stratigraphic layer. For thicker strata that significantly influence the erosion process (such as thick sandstone and mudstone), the weight coefficient is set to 0.15 to 0.2; for thinner strata with less influence (such as thin limestone and shale), the weight coefficient is set to 0.05 to 0.1, and the sum of all stratigraphic weight coefficients is 1. The number of stratigraphic layers is determined based on the geological stratification results of the target area, typically divided into 5 to 10 layers, clearly reflecting the lithological differences and contact relationships of each stratum. The stratigraphic interface depth function is constructed jointly using seismic exploration data and well logging data. An interpolation algorithm is used to process the discrete depth data to form a continuous interface depth surface, with an error controlled within ±5 meters. The lithological distribution function is determined through core sample analysis and well logging curve interpretation results, assigning specific identifier values ​​to different lithologies to ensure the model can accurately distinguish lithological distributions. The structural morphology correction function is set according to the development characteristics of faults and folds. In fault-developed areas, the influence of fault displacement on stratigraphic thickness needs to be considered, and in fold-developed areas, the spatial morphology of stratigraphic interfaces needs to be adjusted according to the fold amplitude. The range of three-dimensional spatial coordinates needs to cover the entire target area, with the lateral range determined according to the exploration area boundary and the longitudinal range from the surface to 5000 to 8000 meters below ground. During the construction process, basic data is first integrated to form an initial model, and then the contribution of each layer is adjusted through weighting coefficients. The final output three-dimensional spatial structure model can intuitively and accurately present the spatial distribution and geological characteristics of the strata, providing a high-precision basic model framework for subsequent erosion simulation. Preferably, the formation erosion thickness is calculated using the following formula: ,in, Two-dimensional plane coordinates The thickness of the eroded strata at that location. The original thickness of the strata. This represents the current thickness of the strata. Three-dimensional spatial coordinates The erosion correction factor at the location. Two-dimensional plane coordinates, These are depth coordinates.

[0033] Specifically, in calculating the thickness of eroded strata, parameters are accurately acquired and the calculation process is strictly followed. The original thickness of the strata is determined by reconstructing the stratigraphic sedimentary sequence, combined with regional stratigraphic correlation and sedimentary facies analysis, referencing the thickness data of uneroded strata in adjacent areas, and using the reflection characteristics of seismic profiles to estimate the original strata thickness, with the error controlled within ±10 meters. The current thickness of the strata is obtained through drilling data and seismic interpretation results. Drilling data directly measures the strata thickness, while seismic data is converted to thickness data through time-depth conversion; the two are cross-validated to improve accuracy. The erosion correction factor is determined comprehensively based on stratigraphic lithology, paleoclimate conditions, and tectonic activity intensity. Values ​​range from 0.05 to 0.1 for areas with hard lithology, arid paleoclimate, and stable tectonics, and values ​​range from 0.1 to 0.2 for areas with soft lithology, humid paleoclimate, and active tectonics. The coverage of the two-dimensional plane coordinates must be consistent with the target exploration area, and the calculation units are typically divided into 100m × 100m grids to ensure a precise reflection of the spatial variations in erosion thickness. The calculation first calculates the difference between the original thickness and the current thickness to obtain the preliminary erosion thickness. Then, an integral operation is performed to process the erosion correction coefficient, correcting for uneven erosion caused by factors such as lithological differences and paleoenvironmental changes. The final output erosion thickness data at different plane coordinates is accurate within ±10 meters and can be directly used to draw erosion thickness contour maps. This provides crucial thickness data support for geological exploration deployment, oil and gas resource potential assessment, and other work, helping to accurately determine the resource occurrence conditions and development potential of strata.

[0034] Preferably, step S3 includes the following sub-steps: S31, collecting mudstone samples from different depths of the target stratum, performing porosity tests on each mudstone sample to obtain multiple porosity data points, and simultaneously recording the burial depth and sampling location information corresponding to each sample; S32, filtering the obtained porosity data, removing abnormal data points, and grouping the filtered data according to the lithological characteristics and diagenetic stage division results of the mudstone samples; S33, inputting the grouped porosity data and corresponding burial depth data into the mudstone compaction curve dynamic fitting algorithm, and setting the initial values ​​of the initial compaction coefficient, initial porosity, and diagenetic stage parameters; S34, running the mudstone compaction curve dynamic fitting algorithm, adjusting the parameter values ​​through iterative calculation to minimize the deviation between the fitted curve and the actual data points, and obtaining the optimized mudstone compaction curve and related parameters.

[0035] Specifically, step S3 includes four sub-steps. In S31, mudstone samples from the target formation are collected. These samples need to be collected at different depths in each well (500-meter intervals), with 2 to 3 samples collected from each depth. The sample weight is controlled between 50 and 100 grams. After collection, the samples are immediately sealed in a sealed bag and the sampling depth and location are marked. The sampling location must cover different structural units in the target area to ensure data representativeness. Porosity testing is performed using a fully automatic porosimeter. Before testing, the samples are vacuum dried (temperature 60 to 80 degrees Celsius, time 24 to 48 hours). The testing pressure is set to 2 to 3 MPa. Each sample is tested 3 times and the average value is taken. At the same time, the sampling depth is recorded with an accuracy of 0.1 meters. In S32, when screening porosity data, outliers are removed using the three-times standard deviation method. The diagenetic stage is divided according to the maturity of mudstone minerals (clay mineral content below 30% is early stage, 30% to 60% is middle stage, and above 60% is late stage). The data are grouped according to the stage, with no less than 10 data points in each group. When inputting data into the algorithm in S33, the initial compaction coefficient is set to 0.0005 to 0.001 per meter, referencing similar strata in the reference area. The initial porosity is taken as the average value of surface sample tests (40% to 50%). The diagenetic stage parameters are assigned values ​​of 0.8, 0.5, and 0.2 for early, middle, and late stages, respectively. In the iterative calculation in S34, the iteration step size is set to 0.0001 per meter. The iteration stops when the fitting deviation is less than 5% for five consecutive iterations. The output fitting curve must have a porosity deviation from the corresponding depth of the measured data points controlled within ±2%. This process ensures that the mudstone compaction curve can truly reflect the strata compaction law and provide reliable compaction parameter support for subsequent erosion thickness calculations.

[0036] Preferably, step S4 includes the following sub-steps: S41, organizing the geothermal data obtained in S1, dividing the data according to depth intervals to form a geothermal data matrix, and simultaneously sorting the paleotemperature data extracted in S2 according to geological time to construct a paleotemperature evolution sequence; S42, converting the mudstone compaction curve fitted in S3 into digital data, extracting porosity values ​​corresponding to different depths, and establishing a porosity-depth database; S43, starting the three-dimensional stratigraphic erosion modeling and analysis platform, importing the basic geological data of the target area, including stratigraphic outcrop data, drilling data, and seismic exploration data, and constructing an initial three-dimensional geological framework; S44, importing the geothermal data matrix, paleotemperature evolution sequence, and porosity-depth database into the three-dimensional stratigraphic erosion modeling and analysis platform respectively, performing data matching and integration with the initial three-dimensional geological framework to form a complete three-dimensional spatial structure model of the target stratigraphy.

[0037] Specifically, step S4 includes four sub-steps: S41 organizes geothermal data into depth-geothermal data pairs, divided into 100-meter depth intervals. The data volume needs to cover 20 to 50 depth points in the target area. Paleotemperature data is sorted by geological time (Paleogene, Neogene, Quaternary), with at least 5 paleotemperature data points for each time period. The data must be verified by stratigraphic isotope dating (dating error less than 5%). S42 converts mudstone compaction curves into digital data, extracting porosity values ​​at 50-meter depth intervals to construct a depth-porosity database. The data format is uniformly CSV for easy platform reading. During the extraction process, the curves need to be smoothed (using the moving average method, with a window size of 5 data points) to reduce data fluctuations. When importing basic geological data into the S43 startup platform, the topographic data resolution is set to 10m × 10m. Stratigraphic outcrop data must include the coordinates and stratigraphic thickness information of at least 20 outcrop points. Drilling data must include layered data from 5 to 10 wells (layering error less than 0.5m). The dominant frequency of seismic exploration data is set to 20 to 40 Hz. The initial 3D geological framework grid size is set to 50m × 50m × 10m (x, y, z directions). During S44 data matching and integration, Kriging interpolation is used to spatially interpolate the discrete data, with interpolation error controlled within 10%. The integrated data must be consistent with the coordinate system of the 3D geological framework (using the National Geodetic Coordinate System 2000). The final 3D spatial structure model must be verified by geological profiles (selecting 3 to 5 geological profiles, with a model-to-profile agreement greater than 90%), providing an accurate spatial model foundation for subsequent erosion simulation.

[0038] Preferably, step S5 includes the following sub-steps: S51, in the three-dimensional stratigraphic erosion modeling and analysis platform, setting the time range and time step of the erosion simulation, and determining the start and end times of the erosion process based on the geological structural evolution history of the target area; S52, calling the output results of the thermal advection coupled geothermal field inversion model to obtain geothermal gradient data of different geological periods, and using them as the temperature boundary conditions for the erosion simulation; S53, combining the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model, adjusting the paleoenvironmental parameters in the three-dimensional stratigraphic erosion modeling and analysis platform, including paleoatmospheric temperature and paleowater temperature; S54, running the erosion simulation module of the three-dimensional stratigraphic erosion modeling and analysis platform, simulating the erosion process of the target stratum step by step according to the set time step, and recording the stratigraphic thickness change data in real time.

[0039] Specifically, step S5 includes four sub-steps. S51: When setting the erosion simulation time range, the age of the youngest erosion surface in the target area is determined based on the stratigraphic contact relationship (with an error of less than 100,000 years) and the present time. The time step is set according to the frequency of geological events: 50,000 years for tectonically active areas and 100,000 years for stable areas. The start and end times must be marked with specific geological ages (e.g., from the Pliocene of the Neogene to the Holocene of the Quaternary). S52: When calling geothermal gradient data as temperature boundary conditions, the geothermal gradient value needs to be updated according to the time step. The rate of change of the geothermal gradient for each time step should be controlled within ±0.005 degrees Celsius per meter. The boundary conditions must cover the top (surface) and bottom (5 to 10 kilometers above the Moho discontinuity) of the model to ensure the integrity of the temperature field. When adjusting paleoenvironmental parameters in S53, paleoatmospheric temperature is reconstructed using paleoclimate proxy indicators (such as pollen and oxygen isotopes) with a reconstruction error of less than 2 degrees Celsius. Paleowater temperature is determined based on paleontological fossil assemblages (such as ostracods and foraminifera). Paleoenvironmental parameters from different geological periods need to be recorded in the simulation parameter table for easy traceability. In S54, when running the erosion simulation module, the simulation uses the finite element method for numerical calculations. The number of iterations is set to 50 to 100. After each iteration, stratigraphic thickness variation data needs to be output (data intervals consistent with the time step). During real-time recording, a data threshold needs to be set (when the stratigraphic thickness variation rate is less than 0.1%, the erosion in the area is considered to have reached a stable state). After the simulation, an erosion rate distribution map (rate unit: meters per million years) needs to be generated to provide dynamic process data support for subsequent erosion thickness calculations.

[0040] Based on the geology of the Junggar Basin in Xinjiang, the accuracy of the calculation results proposed in this invention is verified. The erosion thickness of a single well point is calculated using the reference layer thickness variation rate method and used as a control group for comparison.

[0041] A continuous well profile was established along the direction of Pen 4 Well—Mo 21 Well—Moshen 1 Well—Fang 3 Well—Fang 1 Well. Pen 4 Well, Mo 21 Well, and Moshen 1 Well all drilled through the Badaowan Formation. Fang 3 Well drilled to the second section of the Xishanyao Formation (but did not penetrate). Fang 1 Well drilled to the Badaowan Formation (but did not penetrate). Ha1 and Ha2 represent the residual thicknesses of the Badaowan Formation (J1b) and Sangonghe Formation (J1s) encountered in Well Pen 4, respectively; Hb1 and Hb2 represent the residual thicknesses of the Badaowan Formation and Sangonghe Formation encountered in Well Mo 21, respectively; Hc1 and Hc2 represent the residual thicknesses of the Badaowan Formation and Sangonghe Formation encountered in Well Moshen 1, respectively; Hd1 and Hd2 represent the residual thicknesses of the 3rd section of the Sangonghe Formation and the Xishanyao Formation encountered in Well Fang 3, respectively; He1 and He2 represent the residual thicknesses of the 3rd section of the Sangonghe Formation and the Xishanyao Formation encountered in Well Fang 1, respectively. L1, L2, and L3 represent the horizontal distances between Well Pen 4 and Well Mo 21, Well Pen 4 and Well Moshen 1, and Well Fang 3 and Well Fang 1, respectively.

[0042] The principle of the reference layer thickness ratio trend method is as follows: Due to the continuity of stratigraphic deposition, when tracing along the same structural layer from its lower to higher positions on a seismic profile, the original sedimentary thickness ratio of the upper and lower strata generally shows a linear trend. The rate of change K of the thickness ratio is: K=[(Ha1 / Ha2)-(Hb1 / Hb2)] / L1=[(Ha1 / Ha2)-(Hc1 / Hc2)] / L2 Where K is a constant in km⁻¹, and the upper and lower strata can be adjacent or non-adjacent.

[0043] When two strata are adjacent and horizontal, K can be approximated as 0, meaning that the thickness ratio of two adjacent strata in different structural parts within the same structural layer remains unchanged, i.e.: Ha1 / Ha2=Hb1 / Hb2=Hc1 / Hc2 This method introduces a proportionality coefficient K to take into account the lateral thickness variation between the upper and lower strata. For areas with large tectonic undulations, introducing a K value helps to reduce errors, and it has a wider range of applications compared to the original method.

[0044] This method was used to calculate the erosion thickness in the central part of the Junggar Basin. The stratigraphic thickness was calculated using the geological software TRINITY, and a stratigraphic thickness ratio map of the Badaowan Formation and the Sangonghe Formation was obtained.

[0045] The thermal advection coupled geothermal field inversion model is a technical model that integrates heat conduction and heat convection to achieve accurate inversion of geothermal data of the target strata. Its implementation requires first determining parameters such as the initial surface temperature (based on the regional average surface temperature over the past 50 years, ranging from 10 to 25 degrees Celsius), the thermal conductivity of the strata lithology (assigned values ​​according to lithology, such as 2.0 to 3.0 Kelvin per meter for sandstone, 1.5 to 2.5 Kelvin per meter for mudstone, etc.), the underground fluid flow velocity (0.01 to 0.1 meters per day for porous reservoirs, and 0.1 to 0.5 meters per day for fractured reservoirs), and the geological time (from the formation of the overlying strata to the present complete period). These parameters are then input into the model, and the thermal conductivity and fluid velocity are adjusted through 50 to 100 iterations until the deviation between the calculated geothermal data and the measured data is less than 0.5 degrees Celsius. This model outputs geothermal data at different depths and times, providing temperature boundary conditions for stratum erosion simulation. It breaks through the limitations of traditional single heat conduction models, fully considers the influence of thermal advection on the geothermal field, improves the accuracy of geothermal data inversion, provides a real temperature field basis for subsequent erosion thickness calculation, helps to accurately restore the thermal evolution history of strata, and supports the temperature parameter requirements of geological research in complex tectonic areas.

[0046] The fluid inclusion paleotherm erosion model is a technical model that inverts the paleothermal gradient of strata based on the temperature information of fluid inclusions. Its implementation requires first collecting core samples from the target strata (3 to 5 samples from each well, 10 to 20 cm in length and 5 to 10 cm in diameter), and then measuring the homogenization temperature of the inclusions using a microthermometer (accuracy ±0.1 degrees Celsius, 10 to 20 inclusions per sample). Next, combined with regional paleoclimate data, the surface temperature at the time of inclusion formation is determined (Paleogene 25 to 30 degrees Celsius, Neogene 20 to 25 degrees Celsius, etc.). The burial depth at the time of formation is estimated based on well and seismic data (error ±50 meters), and paleothermal gradient correction coefficients are set according to the intensity of tectonic activity (0.01 to 0.02 for stable regions, 0.02 to 0.03 for active regions). Finally, the initial paleothermal gradient is calculated by substituting the parameters, and the results are output after adjustment with the correction coefficients. This model acquires paleotemperature gradient data from different geological periods, providing key temperature parameters for paleoenvironmental simulation of erosion processes, mining paleoenvironmental information contained in fluid inclusions, accurately reconstructing the paleotemperature evolution of strata, solving the bias problem of traditional paleotemperature estimation relying on a single index, providing reliable paleotemperature basis for reconstructing the history of strata erosion, and improving the accuracy of erosion simulation under complex geological conditions.

[0047] The dynamic fitting algorithm for mudstone compaction curves is a technical method for establishing the dynamic relationship between mudstone porosity and burial depth, and achieving optimized fitting of the compaction curve. Its implementation requires first collecting mudstone samples from the surface to a depth of 5000 meters (2 to 3 samples per 500 meters, weighing 50 to 100 grams each). After vacuum drying (60 to 80 degrees Celsius for 24 to 48 hours), the porosity is measured using the helium displacement method (accuracy ±0.1%, with 5 measurements taken per sample and the average taken). Then, initial parameters are set (initial porosity 40% to 50%, compaction coefficient 0.0008 to 0.001 per meter for shallow layers, etc.). The porosity and depth data are input into the algorithm, and the parameters are adjusted through 30 to 50 iterations until the deviation between the fitted curve and the measured data is less than 5%. The algorithm outputs optimized mudstone compaction curves and related parameters, reflecting the compaction variation of mudstone with depth and geological period. It breaks through the limitations of traditional static compaction curves, dynamically adapts to different diagenetic stages and geological conditions, accurately quantifies the degree of mudstone compaction, provides key compaction parameters for calculating formation erosion thickness, solves the problem of formation thickness deviation caused by compaction, improves the reliability of erosion thickness calculation, and supports the accurate judgment of reservoir development patterns in oil and gas resource exploration.

[0048] The 3D stratigraphic erosion modeling and analysis platform is a technical platform that integrates multi-source geological data to achieve 3D stratigraphic modeling and erosion simulation. Its implementation requires first organizing geothermal data (100-meter interval depth-geothermal pairs), paleotemperature data (sorted by geological age), mudstone compaction data (50-meter interval depth-porosity pairs), and basic geological data (topography at 10m x 10m resolution, drilling stratification error less than 0.5m, etc.). Then, the data is imported to construct an initial 3D geological framework (50m x 50m x 10m grid). The data is then integrated using Kriging interpolation (error less than 10%) to form a 3D spatial structure model including parameters such as temperature and porosity. This model is validated using 3 to 5 geological profiles (with a consistency greater than 90%). Finally, the simulation time range is set (e.g., from the Pliocene of the Neogene to the Holocene of the Quaternary), and the time step is set (50,000 years in tectonically active areas and 100,000 years in stable areas). The erosion simulation module is then run, outputting a map showing stratigraphic thickness variation and erosion rate distribution. This platform constructs a three-dimensional model of the strata and simulates the erosion process, providing a spatial model and dynamic process data for calculating erosion thickness. It achieves collaborative integration and visual modeling of multi-source data, intuitively presenting the spatial distribution of strata and erosion dynamics. Breaking through the limitations of traditional two-dimensional simulation, it provides integrated technical support for the study of erosion in complex tectonic areas, and helps make accurate decisions on geological exploration deployment and oil and gas resource potential evaluation.

[0049] like Figure 2As shown, a method for calculating the thickness of stratigraphic erosion is implemented through different units, including: a thermal advection coupled geothermal field data acquisition and processing unit, which is connected to geothermal monitoring equipment in the target stratigraphic area to receive geothermal monitoring data and process the data using a thermal advection coupled geothermal field inversion model to output geothermal gradient data; a fluid inclusion paleothermometric analysis unit, which is connected to a fluid inclusion testing instrument to receive homogenized temperature test data of inclusions, analyze the data using a fluid inclusion paleothermometric erosion model, and output paleothermometric evolution data; and a mudstone compaction curve fitting and processing unit, which is connected to a mudstone porosity testing device to acquire mudstone porosity data, fit the data using a mudstone compaction curve dynamic fitting algorithm, and output the fitted mudstone compaction curve. Data includes: a 3D stratigraphic modeling data integration unit, which is connected to the thermal advection coupled geothermal field data acquisition and processing unit, the fluid inclusion paleotherm analysis unit, and the mudstone compaction curve fitting and processing unit, receiving data output from each unit and performing format conversion and standardization processing; a 3D stratigraphic erosion simulation calculation unit, which is connected to the 3D stratigraphic modeling data integration unit, receiving the integrated data, performing stratigraphic erosion simulation calculations based on the 3D stratigraphic erosion modeling and analysis platform, and outputting simulated data of the stratigraphic erosion process; and a stratigraphic erosion thickness calculation and output unit, which is connected to the 3D stratigraphic erosion simulation calculation unit, receiving the simulation data, combining it with the mudstone compaction parameters output by the mudstone compaction curve fitting and processing unit, calculating the stratigraphic erosion thickness, and outputting the calculation results in digital form.

[0050] A novel method for calculating stratigraphic erosion thickness organically combines a thermal advection-coupled geothermal field inversion model, a fluid inclusion paleotherm erosion model, a dynamic fitting algorithm for mudstone compaction curves, and a 3D stratigraphic erosion modeling and analysis platform. This approach enables the systematic utilization of multiple types of geological data, overcoming the limitations of single technologies. It fully leverages the value of parameters from different dimensions, such as geothermal temperature, paleotherm temperature, and mudstone compaction, providing multiple data supports for the calculation results. This method employs precise, step-by-step data processing, from geothermal field inversion and paleotherm extraction to compaction curve fitting, and then to 3D modeling and erosion simulation. Each step is designed to improve calculation accuracy and can dynamically adjust parameters based on geological evolution, making the calculation process more closely reflect actual geological conditions and significantly enhancing the reliability and accuracy of stratigraphic erosion thickness calculations.

[0051] This method addresses the problem that existing technologies often rely on single technologies and fail to achieve deep coupling of multiple technologies. It integrates various models and algorithms to construct a complete technical system, allowing geothermal data, paleotemperature data, and mudstone compaction data to work synergistically. This avoids the impact of single parameter deviations on results and compensates for the deficiency in parameter utilization. Regarding the insufficient dynamic adaptability of existing 3D modeling platforms, this method incorporates dynamic parameters related to geological evolution into the 3D stratigraphic erosion modeling and analysis platform. It can adjust modeling parameters in real time according to changes in paleotemperature gradients and diagenetic stages, making the erosion simulation process more closely resemble the actual stratigraphic evolution process. This solves the problem of discrepancies between simulation results and actual erosion processes and improves adaptability to complex geological conditions.

[0052] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0053] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the thickness of eroded formations, characterized in that, Includes the following steps: S1. Geothermal data at different depths within the target stratum region are obtained using a thermal advection coupled geothermal field inversion model. This model integrates parameters such as lithological thermal conductivity, porosity, and underground fluid flow velocity based on the coupling relationship between the heat conduction equation and the heat convection equation to perform inversion calculations on the geothermal field of the target region. S2. Fluid inclusion paleothermographic erosion model is used to analyze fluid inclusions in the core samples of the target stratum, extracting paleotemperature data at the time of inclusion formation. This model combines the homogenized temperature test results of inclusions with the burial evolution history of the strata to determine the paleotemperature gradient variation characteristics. S3. A dynamic fitting algorithm for mudstone compaction curves is used to process the porosity data of mudstone samples from the target strata. This algorithm establishes a dynamic functional relationship between mudstone porosity and burial depth, introducing compaction coefficient, initial porosity, and diagenetic stage parameters to fit and optimize the mudstone compaction curve. S4. The geothermal data acquired in S1, the paleotemperature data extracted in S2, and the mudstone compaction curve data fitted in S3 are input into a three-dimensional stratigraphic erosion modeling and analysis platform. This platform, based on three-dimensional geological modeling technology, constructs a three-dimensional spatial structure model of the target strata, integrating parameters such as stratigraphic interface depth, lithological distribution, and tectonic morphology. In S5, the erosion process of the target strata is simulated using the three-dimensional stratigraphic erosion modeling and analysis platform. The modeling parameters are adjusted by combining the geothermal gradient changes output by the thermal advection coupled geothermal field inversion model and the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model. In S6, based on the simulation results in S5, and combined with the mudstone compaction degree parameters obtained by the mudstone compaction curve dynamic fitting algorithm, the erosion thickness at different locations of the target strata is calculated using the three-dimensional stratigraphic erosion modeling and analysis platform. The calculation process incorporates parameters such as the original thickness, current thickness, and erosion coefficient of the strata to complete the calculation of the stratigraphic erosion thickness.

2. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, In the thermal advection coupled geothermal field inversion model, geothermal data inversion is achieved through the following formula: ,in, For depth At any time The ground temperature, The initial surface temperature, For depth At any time The thermal conductivity of the strata lithology, The velocity of underground fluid flow. For underground fluid density, The specific heat capacity of underground fluids. For formation permeability, For geological time, For integration variables, This is the time variable for integration.

3. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, In the fluid inclusion paleothermal scale erosion model, the paleothermal gradient is determined by the following formula: ,in, This is the paleothermal gradient. The homogenization temperature of the fluid inclusions. The surface temperature at which the inclusions formed. The burial depth at which the inclusions formed. This is the paleothermal gradient correction factor. The time when inclusions begin to form. This is the end time of inclusion formation. For a moment The temperature of the inclusion body, For a moment The ancient surface temperature.

4. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, In the dynamic fitting algorithm for mudstone compaction curves, the dynamic functional relationship between mudstone porosity and burial depth is realized through the following formula: ,in, For depth At any time mudstone porosity, The initial porosity of mudstone. This is the compaction coefficient. The coefficient representing the influence of diagenesis. The decay coefficient of diagenetic time. For geological time, For integration time variable, This refers to the burial depth.

5. The method for calculating the thickness of erosion formations according to claim 1, characterized in that, In the aforementioned three-dimensional stratum erosion modeling and analysis platform, the three-dimensional spatial structure model of the stratum is constructed using the following formula: ,in, Three-dimensional spatial coordinates Stratigraphic model values ​​at the location, For the first The weighting coefficients of each stratum, The number of stratigraphic layers. Three-dimensional spatial coordinates The depth function of the stratigraphic interface at that location. For the first Lithological distribution function of strata, For the first Structural morphology correction function for strata. These are the horizontal, vertical, and depth coordinates in three-dimensional space, respectively.

6. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, The thickness of the eroded strata is calculated using the following formula: ,in, Two-dimensional plane coordinates The thickness of the eroded strata at that location. The original thickness of the strata. This represents the current thickness of the strata. Three-dimensional spatial coordinates The erosion correction factor at the location. Two-dimensional plane coordinates, These are depth coordinates.

7. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, S3 includes the following steps: S31, collect mudstone samples from different depths of the target strata, perform porosity testing on each mudstone sample to obtain multiple porosity data points, and record the burial depth and sampling location information corresponding to each sample; S32, filter the obtained porosity data, remove abnormal data points, and group the filtered data according to the lithological characteristics and diagenetic stage division results of the mudstone samples; S33, input the grouped porosity data and corresponding burial depth data into the mudstone compaction curve dynamic fitting algorithm, and set the initial values ​​of the initial compaction coefficient, initial porosity, and diagenetic stage parameters; S34, run the mudstone compaction curve dynamic fitting algorithm, and adjust the parameter values ​​through iterative calculation to minimize the deviation between the fitted curve and the actual data points, thereby obtaining the optimized mudstone compaction curve and related parameters.

8. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, S4 includes the following steps: S41, organize the geothermal data obtained in S1, divide the data according to depth intervals to form a geothermal data matrix, and sort the paleotemperature data extracted in S2 according to geological time to construct a paleotemperature evolution sequence; S42, convert the mudstone compaction curve fitted in S3 into digital data, extract the porosity values ​​corresponding to different depths, and establish a porosity-depth database; S43, start the three-dimensional stratigraphic erosion modeling and analysis platform, import the basic geological data of the target area, including stratigraphic outcrop data, drilling data and seismic exploration data, and construct an initial three-dimensional geological framework; S44, import the geothermal data matrix, paleotemperature evolution sequence and porosity-depth database into the three-dimensional stratigraphic erosion modeling and analysis platform respectively, and perform data matching and integration with the initial three-dimensional geological framework to form a complete three-dimensional spatial structure model of the target stratigraphy.

9. The method for calculating the thickness of erosion in a formation according to claim 1, characterized in that, S5 includes the following steps: S51. In the three-dimensional stratigraphic erosion modeling and analysis platform, set the time range and time step of the erosion simulation, and determine the start and end times of the erosion process based on the geological structural evolution history of the target area; S52. Call the output results of the thermal advection coupled geothermal field inversion model to obtain geothermal gradient data of different geological periods, and use them as the temperature boundary conditions for the erosion simulation; S53. Combine the paleothermal evolution characteristics determined by the fluid inclusion paleotherm erosion model, adjust the paleoenvironmental parameters in the three-dimensional stratigraphic erosion modeling and analysis platform, including paleoatmospheric temperature and paleowater temperature; S54. Run the erosion simulation module of the three-dimensional stratigraphic erosion modeling and analysis platform, and simulate the erosion process of the target stratum step by step according to the set time step, and record the stratigraphic thickness change data in real time.

10. A method for calculating the thickness of erosion formations according to any one of claims 1-9, characterized in that, This method is implemented through different units, including: a thermal advection coupled geothermal field data acquisition and processing unit, which is connected to the geothermal monitoring equipment in the target stratigraphic area to receive geothermal monitoring data and process the data using a thermal advection coupled geothermal field inversion model to output geothermal gradient data; a fluid inclusion paleothermometric analysis unit, which is connected to a fluid inclusion testing instrument to receive homogenized temperature test data of inclusions, analyze the data using a fluid inclusion paleothermometric erosion model, and output paleothermometric evolution data; a mudstone compaction curve fitting and processing unit, which is connected to a mudstone porosity testing device to acquire mudstone porosity data, fit the data using a mudstone compaction curve dynamic fitting algorithm, and output the fitted mudstone compaction curve data; and a three-dimensional stratigraphic model. The system comprises three data integration units: a model data integration unit, a model data acquisition and processing unit, a fluid inclusion paleotherm analysis unit, and a mudstone compaction curve fitting and processing unit; a 3D stratigraphic erosion simulation and calculation unit, and a 3D stratigraphic modeling data integration unit. The model data integration unit receives the integrated data, performs stratigraphic erosion simulation calculations based on the 3D stratigraphic erosion modeling and analysis platform, and outputs simulated data of the stratigraphic erosion process. Finally, a stratigraphic erosion thickness calculation and output unit, connected to the 3D stratigraphic erosion simulation and calculation unit, receives the simulation data, combines it with the mudstone compaction parameters output by the mudstone compaction curve fitting and processing unit, calculates the stratigraphic erosion thickness, and outputs the calculation results in digital form.

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