Method and device for calculating paleo-pressure of sandstone stratum

Abstract

The embodiment of the invention relates to the technical field of sandstone paleo-pressure recovery, in particular to a sandstone stratum paleo-pressure calculation method and device, and the method comprises the steps: obtaining the paleo-burial depth data of a sandstone stratum; according to the paleo-burial depth data, calculating paleo-porosity data of the stratum by using a pore evolution model, coupling the pore evolution model with a sandstone pore reduction model and a sandstone pore increasing model, and representing nonlinear correlation among the stratum paleo-burial depth, the stratum paleo-burial time and the stratum creep by the sandstone pore reduction model; the sandstone pore-increasing model represents the correlation between the stratum paleo-temperature and the stratum corrosion pore-increasing effect; according to the ancient burial depth data and the ancient porosity data, carrying out inversion on ancient particle stress data of the sandstone stratum; acquiring paleo-overburden stress data of the sandstone stratum; according to the paleo-porosity data, the paleo-particle stress data and the paleo-overburden stress data, paleo-pressure evolution data of the sandstone stratum are calculated, and the paleo-pressure evolution data comprise the evolution relation between stratum paleo-pressure and paleo-burying time.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of sandstone paleopressure restoration technology, specifically to a method and apparatus for calculating paleopressure in sandstone strata. Background Technology

[0002] Existing sandstone paleopressure restoration techniques can be mainly categorized into two types: one centered on stratigraphic compaction (paleoporosity), and the other based on fluid inclusion techniques. Among these, the stratigraphic compaction method, such as basin simulation techniques, assumes that rock particle volume remains constant, and that the reduction in stratigraphic thickness is primarily caused by changes in porosity and pore fluid volume. It uses a layer-by-layer stripping method to restore the stratigraphic thickness from its present thickness to the thickness at the time of deposition or a specific burial period, and uses the present stratigraphic pressure as a constraint to invert the paleopressure of the corresponding historical period.

[0003] Basin simulation is currently the most widely used method, but it has two significant limitations: First, this method relies on a large number of geological parameters (such as paleotemperature, paleoheat flow, and paleowater depth), and the errors of these parameters accumulate during the simulation process, directly affecting the reliability of the results; Second, the Athy porosity model and the pore pressure model based on effective stress used in basin simulation have theoretical defects: the model does not consider the influence of time on porosity evolution, and effective stress is not the force actually borne by the rock skeleton, thus leading to a large deviation in the paleopressure recovery results.

[0004] Another type of paleopressure reconstruction method based on fluid inclusions can directly obtain paleopressure information, but its application is limited by the availability of samples. Especially in the early stages of exploration, drilling is rare, inclusion samples are scarce, and it is difficult to obtain them systematically. In addition, this method can only reconstruct the pressure at a single point during the period when the inclusions were captured, and cannot characterize the continuous evolution of the paleopressure field within the entire depression, resulting in a relatively one-sided paleopressure reconstruction result.

[0005] It is worth noting that although improved porosity evolution models exist that take into account the effects of time, these methods are mostly based on the assumption that porosity changes approximately linearly with depth and time. However, in actual geological processes, porosity evolution is extremely complex, and its compaction rate may accelerate or decelerate with time and increasing burial depth. Simple linear coupling is insufficient to accurately characterize such complex behavior, resulting in significant biases in paleopressure reconstruction results. Summary of the Invention

[0006] The purpose of the embodiments in this specification is to provide a method and apparatus for calculating paleopressure in sandstone formations, so as to overcome the problem that the paleopressure results in existing methods are one-sided and have large deviations.

[0007] To solve the above-mentioned technical problems, the specific technical solutions of the embodiments in this specification are as follows: On the one hand, the embodiments of this specification provide a method for calculating paleopressure in sandstone strata, including: Obtain paleoburial depth data of sandstone strata; Based on the paleoburial depth data, the paleoporosity data of the strata were calculated using a pore evolution model. The pore evolution model was coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model characterized the nonlinear relationship between the paleoburial depth, paleoburial time, and strata creep, while the sandstone porosity increase model characterized the relationship between the paleotemperature of the strata and the porosity increase effect of strata dissolution. Based on the paleoburial depth data and paleoporosity data, paleogranular stress data of sandstone strata were inverted. Obtain paleooverburden stress data for sandstone strata; Based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, paleopressure evolution data of sandstone strata were calculated. The paleopressure evolution data includes the evolution relationship between strata paleopressure and paleoburial time.

[0008] Furthermore, the construction of the pore evolution model includes: By coupling the sandstone porosity reduction model and the sandstone porosity increase model of the sandstone formation, the following porosity evolution model is obtained: ; In the formula, Indicates the length of time since then Paleoporosity corresponding to the burial time of the strata Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. When indicating the length of time since then The paleoporosity and secondary porosity at the ancient burial time point This represents the total amount of secondary porosity created by dissolution in the formation. Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0009] Furthermore, the construction of the sandstone porosity reduction model includes: Acquire sandstone data for a target section of sandstone strata; the target section is a compacted section of sandstone strata that has not been affected by dissolution and porosification; the sandstone data includes at least paleoburial depth data, paleoporosity data, and paleoburial time data for the target section; Based on the sandstone data of the target sandstone stratum, a multivariate nonlinear regression analysis was performed. Based on the results of the multivariate nonlinear regression analysis, a sandstone porosity reduction model for sandstone formations is constructed.

[0010] Furthermore, the step of constructing a sandstone porosity reduction model for sandstone strata based on the results of the multivariate nonlinear regression analysis includes: Based on the results of the multivariate nonlinear regression analysis, the following sandstone porosity reduction model for sandstone strata is constructed: ; In the formula, Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. Indicates the initial sedimentary paleoporosity. Indicates the length of time since then The ancient burial depth at a given time point. , , , These represent the regression coefficients determined based on the results of multivariate nonlinear regression analysis. It is a positive number less than 1.

[0011] Furthermore, the construction of the sandstone pore-enhancing model includes: Constructing a model of the burial history of sandstone strata; Based on the aforementioned burial history model, the paleoburial depth data of the sandstone strata were determined; Obtain paleotemperature data of sandstone strata; Based on the paleoburial depth and paleotemperature data, the start and end times of the dissolution and porosification process in the strata were determined. Based on the start and end times, the acidization window for dissolution and porosimetry in the formation is determined; Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed within the acidification window.

[0012] Further, the step of constructing a sandstone porosity model within the acidification window based on the total secondary porosity data from the dissolution porosity enhancement effect includes: Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed in the acidification window: ; In the formula, Indicates the length of time since then Secondary porosity increase corresponding to the paleoporosity at the burial time of the strata This indicates that dissolution and porosimetry in the formation occur within the acidization window. Total secondary porosity within, , Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0013] Furthermore, the step of retrieving paleoclimate stress data of sandstone strata based on the paleoburial depth data and paleoporosity data includes: Based on the paleoporosity data, the pore fluid acoustic transit time data of the formation, and the acoustic transit time data of the rock matrix, the rock acoustic transit time data corresponding to the paleoporosity data is inverted. Based on the rock acoustic transit time data and paleoburial depth data, paleoparticle stress data of the sandstone strata were calculated.

[0014] Furthermore, the acquisition of paleoverburden stress data for sandstone strata includes: Based on the paleoburial depth data, the paleooverburial stress data of the sandstone strata were calculated using the following formula: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleooverburial stress data at the time of burial. This represents the average density of sandstone strata. Represents gravitational acceleration. Indicates the length of time since the sandstone strata were formed. The ancient burial depth at the time of the ancient burial.

[0015] Furthermore, the calculation of paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburden stress data includes: Based on the paleoporosity, paleogranular stress, and paleooverburial stress corresponding to each paleoburial time point, the paleopressure of the sandstone strata at each paleoburial time point is calculated using the following formula: ; In the formula, Indicates the length of time since the sandstone strata were formed. The ancient pressure at the point in time of burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial stress at the time of burial Indicates the length of time since the sandstone strata were formed. Paleoporosity corresponding to the burial time of the strata Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point; Based on the paleopressure at each paleoburial time point of the sandstone strata, the paleopressure evolution data of the sandstone strata were determined.

[0016] On another front, embodiments of this specification provide a device for calculating paleopressure in sandstone strata, comprising: The first acquisition module is used to acquire ancient burial depth data of sandstone strata; The first calculation module is used to calculate the paleoporosity data of the strata using the pore evolution model based on the paleoburial depth data. The pore evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model represents the nonlinear relationship between the paleoburial depth of the strata, the paleoburial time of the strata and the creep of the strata. The sandstone porosity increase model represents the relationship between the paleotemperature of the strata and the porosity increase effect of the strata through dissolution. The inversion module is used to invert the paleoclimate stress data of sandstone strata based on the paleoburial depth data and paleoporosity data. The second acquisition module is used to acquire paleoverburden stress data of sandstone strata; The second calculation module is used to calculate the paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data. The paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time.

[0017] In another aspect, a computer device is provided, comprising: a memory for storing a computer program; and a processor for executing the computer program to implement the above-described method for calculating paleopressure in sandstone strata.

[0018] Furthermore, embodiments of this specification also provide a computer program product, which, when run by the processor of a computer device, executes instructions for any of the methods described above.

[0019] As can be seen from the technical solutions provided in the embodiments of this specification above, the embodiments of this specification can obtain paleoburial depth data of sandstone strata; based on the paleoburial depth data, a porosity evolution model is used to calculate the paleoporosity data of the strata. The porosity evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model characterizes the nonlinear correlation between the paleoburial depth, the paleoburial time, and the creep of the strata, while the sandstone porosity increase model characterizes the correlation between the paleotemperature of the strata and the porosity increase effect of dissolution in the strata; based on the paleoburial depth data and the paleoporosity data, the paleogranular stress data of the sandstone strata is inverted; the paleooverburial stress data of the sandstone strata is obtained; based on the paleoporosity data, the paleogranular stress data, and the paleooverburial stress data, the paleopressure evolution data of the sandstone strata is calculated, and the paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time. The porosity evolution model, by coupling two opposing geological processes—porosity reduction and porosity increase—completely describes the dynamic evolution of sandstone strata properties, avoiding the systematic biases inherent in a single porosity reduction model. Furthermore, the introduction of paleoburial time and rock creep into the porosity reduction model helps characterize time-dependent nonlinear deformation behavior over long geological histories, improving the accuracy of compaction simulations of deep, ancient strata. Using paleotemperature as a control variable in the porosity increase model allows for close integration of dissolution simulations with geochemical processes such as basin thermal history and organic acid formation windows, enhancing the geological rationality of constructive diagenesis simulations. In addition, by abandoning the traditional effective stress principle and instead inverting paleoclimate stress data, combined with paleoporosity and paleoverburial stress data, the model outputs the evolutionary relationship between paleopressure and paleoburial time. This overcomes the limitation of methods such as fluid inclusions, which can only provide isolated time-point pressure snapshots, significantly improving the accuracy of paleopressure calculations and enhancing the credibility and interpretability of the final pressure evolution history. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below.

[0021] Figure 1 This is a flowchart illustrating a method for calculating paleopressure in sandstone formations, as provided in the embodiments of this specification. Figure 2 This is a schematic diagram of the structural composition of a sandstone formation paleopressure calculation device provided in the embodiments of this specification; Figure 3 This is a schematic diagram of the structural composition of the computer device provided in the embodiments of this specification. Detailed Implementation

[0022] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0023] It should be noted that the terms "first," "second," etc., used in this specification, claims, and the foregoing drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0024] In some embodiments, paleopressure evolution data of sandstone formations can be the evolution of pressure (oil, gas, water) on fluids (porosity) in the pore space of sandstone reservoirs over time during geological history. Reconstructing the paleopressure of sandstone formations is of crucial guiding significance for revealing hydrocarbon accumulation dynamics, clarifying the driving forces, directions, and timing of hydrocarbon migration, and predicting favorable hydrocarbon enrichment areas.

[0025] Figure 1 This is a flowchart illustrating a method for calculating paleopressure in sandstone strata, as provided in the embodiments of this specification. In practice, it includes the following steps: S10: Obtain paleoburial depth data of sandstone strata.

[0026] In some embodiments, step S10 may specifically include: constructing a single-well burial history model to obtain paleoburial depth data of the sandstone target layer; wherein, the construction of the burial history model includes: based on the current depth, residual thickness, time, lithology and stratigraphic contact relationship of each stratum in a single well, combined with parameters reflecting the compaction law of the strata, inverting the change process of the thickness and burial depth of each stratum since deposition over time using the stripping method; the paleoburial depth data includes the evolution relationship of the paleoburial depth of the sandstone target layer with burial time.

[0027] Based on the current depth, thickness, absolute geological age, and contact relationships of sandstone strata obtained from drilling, logging, and seismic data interpretation, and combined with parameters reflecting strata compaction patterns, stripping simulations can be performed to calculate the paleoburial depth data of the sandstone strata. Stratigraphic contact relationships can include conformable, erosion, and overburden, while parameters reflecting strata compaction patterns can include porosity-depth relationships, which will not be elaborated further here. Furthermore, when strata have undergone uplift and erosion, the erosion thickness can be reconstructed.

[0028] The back-stripping simulation is based on the principles of mass conservation and compaction. The process can include: keeping the thickness of each stratum unchanged (except for the eroded layer and the fault layer), starting from the surface, the overlying strata are stripped layer by layer in the order of geological age from newest to oldest. The paleothickness of each layer is restored after removing the compaction effect, so as to dynamically and continuously reconstruct the change of the burial depth of the sandstone strata from the time of deposition to the present, and finally form a burial history model.

[0029] The paleoburial depth data obtained by the burial history model constructed above is not a single or discrete data point, but a continuous evolution curve or time series dataset. It can include the paleoburial depth of sandstone strata at any paleoburial time point (or target geological history period), thus completely defining the corresponding change relationship between paleoburial depth and paleoburial time.

[0030] The continuous burial depth-time data restored by back-stripping simulation provides an indispensable temporal and spatial coordinate framework for the reconstruction of paleoporosity and paleopressure. This ensures the temporal accuracy and geological rationality of the entire evolutionary history simulation and enables subsequent porosity models to operate in a realistic and dynamic burial context, avoiding reliance on the simplified assumption of uniform burial. This effectively improves the accuracy and reliability of the paleoporosity and paleopressure reconstruction results.

[0031] S20: Based on the paleoburial depth data, the paleoporosity data of the strata are calculated using the pore evolution model. The pore evolution model is coupled with the sandstone porosity reduction model and the sandstone porosity increase model. The sandstone porosity reduction model represents the nonlinear relationship between the paleoburial depth of the strata, the paleoburial time of the strata and the creep of the strata. The sandstone porosity increase model represents the relationship between the paleotemperature of the strata and the porosity increase effect of the strata by dissolution.

[0032] In some embodiments, the paleoporosity data of the aforementioned sandstone strata can be data showing the change over time in the percentage of pore volume to total rock volume during geological history. This data can characterize the evolution of reservoir space under the combined influence of mechanical compaction, chemical cementation, and dissolution during burial.

[0033] In some embodiments, the input to the sandstone porosity reduction model can be paleo-burial depth data and paleo-burial time data of the sandstone strata. The model can include a nonlinear term characterizing the rock creep effect. The nonlinear term is used to characterize the porosity reduction process caused by the combined effects of mechanical compaction dominated by burial depth and creep compaction dominated by time in geological history.

[0034] Specifically, this model can use the paleoburial depth (the burial depth of the strata in geological history) and paleoburial time (the duration from the target geological moment to the present) as input parameters. By introducing a nonlinear term characterizing the rock creep effect, it achieves a fundamental improvement over traditional linear or exponential compaction models. The rock creep effect can be defined as the time-dependent plastic deformation behavior of rocks under long-term stress. Mathematically, the model couples burial depth and time variables, comprehensively describing two different mechanisms of porosity reduction: depth-dominated mechanical compaction, i.e., particle rearrangement and plastic deformation caused by the weight of overlying strata; and time-dominated creep compaction, i.e., the continuous reduction of porosity caused by slow rheology under sustained stress over long geological periods. Through these mechanisms, the model achieves a more physically accurate and quantitative simulation of the sandstone porosity reduction process.

[0035] In some embodiments, the input to the sandstone porosity enhancement model can be paleotemperature data of the sandstone strata. The model can include a correlation term that couples paleotemperature with the intensity of dissolution porosity enhancement. The correlation term is used to simulate the porosity increase process caused by the dissolution of the rock skeleton by organic acid fluid within a specific geothermal window.

[0036] Specifically, this model uses paleotemperature (the temperature at which the strata were in their geological history) as a control parameter. By establishing a mathematical correlation between paleotemperature and the intensity of dissolution and porosification, it simulates constructive diagenesis. The physical basis is that when basin thermal evolution causes the strata temperature to enter a specific geothermal window, organic acid fluids originating from source rocks effectively dissolve easily soluble components (such as feldspar and carbonate cements) in the sandstone framework, thereby generating secondary porosity and increasing overall porosity. This model can dynamically simulate the timing, rate, and total amount of secondary porosity formation within this temperature window. Specifically, the geothermal window can be set to 70℃ to 90℃, representing the range where organic acids are generated and active in large quantities. When the strata temperature is below 70℃, the lack of organic acids prevents the formation of numerous dissolution pores in the sandstone. When the strata temperature is above 90℃, the reduced concentration of organic acids and oil emplacement result in very weak dissolution, with virtually no secondary porosity generated.

[0037] In some embodiments, a sandstone porosity reduction model and a sandstone porosity enhancement model are coupled to obtain a porosity evolution model. The outputs of the sandstone porosity reduction model and the sandstone porosity enhancement model are superimposed in the time domain to obtain continuous paleoporosity evolution data.

[0038] The aforementioned sandstone porosity reduction and porosity increase models can be overlaid in the time domain to obtain a porosity evolution model. Specifically, in the time domain, the background porosity calculated by the porosity reduction model and the secondary porosity increment calculated by the porosity increase model can be algebraically superimposed. This process integrates both destructive and constructive geological forces, ultimately outputting a continuous and complete paleoporosity evolution data curve, quantitatively characterizing the dynamic evolution history of sandstone strata porosity from deposition to the present.

[0039] By separating and precisely quantifying the two opposing processes of porosity reduction and porosity increase, this model overcomes the limitation of traditional single models that can only partially describe porosity evolution. This binary coupled model provides a more complete and realistic dynamic description of sandstone formations.

[0040] In some embodiments, the paleoburial depth data can be input into a porosity evolution model to obtain paleoporosity data of the strata, which includes the evolutionary relationship between paleoporosity and paleoburial time.

[0041] Paleoburial depth data, i.e., the burial depth sequence of strata at different paleoburial time points (geological ages), can be used as input to drive the porosity evolution model to perform calculations, thereby outputting paleoporosity data of the strata. Paleoporosity data is not an isolated numerical value, but rather a complete definition of the evolutionary relationship between paleoporosity and paleoburial time. It can be represented as a continuous function curve or a high-resolution time series data sequence / set, clearly revealing the entire process of the dynamic evolution of porosity with geological age changes from the time of stratum deposition to the present.

[0042] By converting paleoburial depth curves of sandstone strata into paleoporosity evolution data, this method overcomes the limitation of traditional fluid inclusion methods, which can only reconstruct single-point pressure during the period of fluid inclusion capture. This enables continuous and dynamic observation of reservoir property changes throughout geological history, greatly deepening our understanding of reservoir development patterns.

[0043] S30: Based on the paleoburial depth data and paleoporosity data, invert the paleogranular stress data of the sandstone strata.

[0044] In some embodiments, the paleoparticle stress data of the aforementioned sandstone strata can be data on the actual effective stress borne between sandstone skeleton grains over time during geological history. This data can reflect the magnitude of stress transmitted at the rock grain contact surface, and its physical essence is the micromechanical response supporting the load of the overlying strata.

[0045] In some embodiments, step S30 may specifically include: inverting the rock acoustic transit time data corresponding to the paleoporosity data based on the paleoporosity data, the pore fluid acoustic transit time data of the strata, and the rock matrix acoustic transit time data; and calculating the paleogranular stress data of the sandstone strata based on the rock acoustic transit time data and the paleoburial depth data.

[0046] In some embodiments, based on the recovered paleoporosity data, combined with the acoustic transit time data of formation pore fluids and the acoustic transit time data of the rock matrix skeleton, an inversion calculation is performed based on the Willy time-averaging equation to obtain the rock acoustic transit time data corresponding to the paleoporosity data.

[0047] Specifically, based on the Willy time-averaging equation, recovered paleoporosity data, known pore fluid sonic transit time, and rock matrix sonic transit time can be used as input parameters to inversely calculate rock sonic transit time data that precisely corresponds to the paleoporosity at each paleoburial time point, thus achieving the conversion of physical quantities from the porosity domain to the sonic velocity domain. By introducing the Willy time-averaging equation, paleoporosity data, which is difficult to use directly for pressure calculations, can be reliably converted into sonic transit time data directly related to rock mechanical properties. This conversion provides high-quality, theoretically self-consistent input parameters for the pressure calculation model, laying the foundation for the reliability of the entire method.

[0048] In some embodiments, rock acoustic transit time data and their corresponding paleoburial depth data can be used as input parameters and substituted into the empirical function of grain stress established through core experiments and well logging data to calculate the paleograin stress data of sandstone strata.

[0049] Specifically, the paleoacoustic transit time data and their corresponding paleoburial depth data obtained in the previous step can be substituted into a pre-established empirical function for grain stress. This empirical function can be determined by fitting and regressing rock mechanics experiments on a large number of core samples in the study area, measured formation pressure data obtained during drilling, and well logging acoustic velocity data. Its form can be a multivariate function containing acoustic velocity and burial depth variables. Through calculation, the paleograin stress data of the sandstone strata at each paleoburial time point, i.e., each geological period, is finally output. By directly calculating the paleograin stress and using it as the key to calculating pore pressure, the theoretical controversy of the traditional effective stress concept and the difficulty of introducing empirical coefficients in application are completely bypassed, giving the paleopressure calculation model a more solid physical foundation and higher theoretical rigor. In addition, the empirical function for grain stress used can be specifically calibrated through core experiments and measured data of sandstone strata, rather than directly applying a general model. This means that the function has incorporated the specific mineral composition, cementation degree, and structural characteristics of sandstone strata, thereby greatly improving the model's prediction accuracy and applicability, and effectively avoiding systematic errors introduced by insufficient model universality.

[0050] S40: Obtain paleooverburden stress data for sandstone strata.

[0051] In some embodiments, the paleooverburden stress data of the aforementioned sandstone strata can be data on the change in vertical stress generated by the total gravity of the overlying rock column above the target sandstone strata over time during geological history. This data is determined by both the paleoburial depth and the density of the overlying rock mass.

[0052] In some embodiments, step S40 may specifically include: establishing a density model of the sandstone strata, the density model including density values ​​or density-depth relationships from the surface to each layer of the sandstone strata; substituting the paleoburial depth data of the sandstone strata into the overburial stress calculation model based on the density model to obtain the paleooverburial stress data acting on the top surface of the sandstone strata at each paleoburial time point.

[0053] Specifically, a comprehensive stratigraphic density model from the surface to the bottom boundary of sandstone strata can be established by systematically integrating density logging data, core laboratory data, and seismic velocity field data. This model can accurately characterize the volumetric density of rocks in each layer and establish a density-depth function relationship that considers lithological assemblage, diagenetic evolution, and burial depth effects, forming a complete stratigraphic density profile. By comprehensively utilizing multi-source heterogeneous data from well logging, core analysis, and seismic data for density modeling, both the vertical high resolution of the model and the spatial variation trend of density parameters are fully considered. This multi-scale data fusion strategy effectively reduces model uncertainty and significantly improves the reliability and engineering applicability of the results.

[0054] The paleoburial depth data sequence of sandstone strata obtained through burial history analysis can be used as input parameters and substituted into an overlying stress calculation model constructed based on a density model. This calculation model can dynamically calculate the total weight of the overlying rock column corresponding to each paleoburial time point using a vertical integration algorithm from the surface to the target stratum. Ultimately, it outputs a spatiotemporally corresponding paleooverlying stress dataset, accurately representing the vertical stress values ​​acting on the top surface of the sandstone strata at each paleoburial time point, i.e., during each geological history period. By organically combining the paleoburial depth data sequence with the density model, dynamic matching between overlying stress evolution and the strata burial process is achieved. This coupling mechanism enables stress reconstruction to accurately reflect the actual load conditions of the strata at various historical periods, significantly improving the spatiotemporal accuracy of paleopressure evolution history reconstruction.

[0055] S50: Based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, calculate the paleopressure evolution data of the sandstone strata. The paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time.

[0056] In some embodiments, step S50 may specifically include: calculating the paleopressure of the sandstone strata at each paleoburial time point using the rock static equilibrium equation based on the paleoporosity, paleogranular stress, and paleooverburial stress corresponding to each paleoburial time point; and determining the paleopressure evolution data of the sandstone strata based on the paleopressure at each paleoburial time point.

[0057] Specifically, based on the restored paleoporosity, paleoparticle stress, and paleoverburial stress data corresponding to each paleoburial time point, these data are used as input parameters and substituted into the rock static equilibrium equation based on micromechanical principles for solution. The rock static equilibrium equation follows the principle of porous media mechanical equilibrium, and can accurately calculate the paleopore fluid pressure value of sandstone strata at the corresponding paleoburial time point by quantifying the distribution relationship of paleoverburial stress between rock skeleton particles and pore fluids. By introducing a calculation equation based on micromechanical static equilibrium principles, the theoretical controversies and application limitations of the traditional effective stress principle are completely avoided, establishing a more rigorous physical model. This shifts paleopressure restoration from empirical calculation to theory-driven precise calculation, significantly improving the scientific rigor and reliability of the method.

[0058] By systematically integrating paleopressure calculation results from all paleoburial time points, a complete and continuous paleopressure evolution curve over time can be constructed, representing the paleopressure evolution data of sandstone strata. This data sequence can quantitatively and completely reproduce the entire pressure evolution process of sandstone strata from the initial depositional stage to the present, including dynamic processes such as normal pressure, overpressure formation, and depressurization. By independently calculating and serializing the data at each paleoburial time point to form a continuous evolution curve, a complete reconstruction of the strata's pressure history is achieved. This continuous and dynamic recovery capability enables the precise identification of key geological processes such as overpressure formation periods, pressure transition points, and depressurization events, providing unprecedented temporal resolution for hydrocarbon accumulation dynamics research.

[0059] Overall, by synergistically integrating three independently recovered parameter sequences—porosity evolution, grain stress variation, and overlying stress evolution—and achieving parameter coupling through rigorous physical equations, this multi-parameter synergistic computational framework significantly reduces the impact of uncertainties in individual parameters and substantially improves the overall accuracy of paleopressure reconstruction.

[0060] In some embodiments, the construction of the sandstone porosity reduction model in step S20 may specifically include: acquiring sandstone data of a target segment of the sandstone strata; the target segment is a normally compacted segment of the sandstone strata that has not been affected by dissolution and porosity enhancement; the sandstone data includes at least paleoburial depth data, paleoporosity data, and paleoburial time data of the target segment; performing multivariate nonlinear regression analysis based on the sandstone data of the target segment of the sandstone strata; and constructing a sandstone porosity reduction model of the sandstone strata based on the results of the multivariate nonlinear regression analysis.

[0061] In some embodiments, sandstone data of a target segment in a sandstone formation can be acquired. The target segment can be a segment whose porosity evolution is mainly controlled by compaction and has not been affected by later dissolution and porosification during its burial history, so as to ensure that the data can truly reflect the pure compaction porosity reduction law. The sandstone data includes at least: paleoburial depth data of the target segment at different paleoburial time points, and paleoporosity data of the corresponding paleoburial time points obtained through experiments or well logging interpretation. Based on the above data, with paleoburial depth and paleoburial time as independent variables and paleoporosity as dependent variable, a multivariate nonlinear regression analysis is performed. According to the model form and fitting parameters determined by the regression analysis, a sandstone porosity reduction model that quantitatively describes the nonlinear decrease law of porosity with burial depth and time is constructed.

[0062] In some embodiments, a target sandstone stratum can be selected as the modeling basis. The target stratum satisfies the condition that it has not been affected by later dissolution and porosity enhancement during its burial history, and its porosity evolution process is entirely dominated by compaction. This selection aims to ensure that the acquired data accurately reflects the pure mechanical compaction and creep porosity reduction mechanisms, providing a reliable data foundation for establishing an accurate porosity reduction model. By specifically selecting a purely compacted stratum unaffected by dissolution as the modeling object, the mutual interference between compaction and dissolution is effectively isolated, ensuring that the model reflects a pure porosity reduction mechanism.

[0063] Sandstone data can include three elements: paleoburial depth data of the target section at different geological periods, paleoporosity data of the corresponding periods obtained through core experiment analysis and comprehensive interpretation of well logging data, and paleoburial time point data corresponding to each geological period. These data together constitute the complete dataset for model calibration. Based on the above dataset, with paleoburial depth and paleoburial time as independent variables and paleoporosity as the dependent variable, a multivariate nonlinear regression analysis method is used for model fitting. This regression analysis can establish a mathematical relationship that best characterizes the nonlinear decrease in porosity with burial depth and time. Using the multivariate nonlinear regression analysis method, the combined influence of the two key variables of burial depth and time on porosity evolution can be considered simultaneously, effectively capturing the nonlinear characteristics of the compaction process and overcoming the limitations of traditional univariate or linear models in describing complex geological processes.

[0064] Finally, based on the mathematical model form and its fitting parameters determined by regression analysis, a sandstone porosity reduction model was constructed. This model can quantitatively describe the porosity reduction law under the combined effects of mechanical compaction dominated by burial depth and creep effect dominated by time during geological history. The mathematical model established based on actual geological data can not only accurately fit known data points, but also has the ability to predict unknown sections, providing a reliable tool for porosity prediction of deep and ultra-deep sandstone reservoirs and significantly expanding the applicability of the model.

[0065] In some embodiments, the construction of a sandstone porosity reduction model for sandstone formations based on the results of the multivariate nonlinear regression analysis may specifically include: Based on the results of the multivariate nonlinear regression analysis, the following sandstone porosity reduction model for sandstone strata is constructed: ; In the formula, Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. Indicates the initial sedimentary paleoporosity. Indicates the length of time since then The ancient burial depth at a given time point. , , , These represent the regression coefficients determined based on the results of multivariate nonlinear regression analysis. It is a positive number less than 1.

[0066] The results indicate that the sandstone porosity reduction model does not simply add the effects of paleoburial depth (Z) and paleoburial time (t), but rather achieves a dynamic coupling between the two through their product. This accurately reflects geological reality: the compaction effect of deep strata (high Z value) continuously strengthens and accumulates over time. Furthermore, when s is between 0 and 1, it indicates that the compaction effect gradually slows down with increasing depth, which is more consistent with the actual burial process of sedimentary strata, especially the process of rapid early compaction followed by stabilization.

[0067] Going further, The term describes creep compaction, which is approximately linear with time, and characterizes the slow, continuous decrease in porosity under steady stress. The method introduces a nonlinear time effect, which can simulate the self-acceleration or decay characteristics of the creep process. This is crucial for simulating unsteady creep behavior under the influence of various factors such as temperature and mineral transformation over a long geological history, and can overcome the shortcomings of traditional models that ignore the time factor or only perform simple linear treatment.

[0068] Furthermore, by integrating depth exponential terms, depth-time coupling terms, linear time terms, and nonlinear time terms, a highly flexible model architecture is constructed. During multivariate nonlinear regression analysis, this structure can automatically find the best fit path for complex data by adjusting coefficients a, b, c, and s, thereby adapting to diverse compaction patterns in different basins and geological backgrounds, significantly improving the model's universality and the reliability of extrapolation predictions.

[0069] The calculation of paleopressure is highly dependent on the accuracy of paleoporosity reconstruction. Through the mechanism described above, a paleoporosity evolution curve or data evolution sequence with clear physical meaning and high consistency with geological dynamics can be output. Compared to models based on simplified assumptions, this result, as input for paleopressure calculation, fundamentally reduces error propagation, significantly improves the accuracy and reliability of the final paleopressure evolution history reconstruction, and provides a more solid scientific basis for subsequent hydrocarbon accumulation dynamics analysis.

[0070] Overall, the aforementioned sandstone porosity reduction model is a physically driven model that deeply integrates nonlinear compaction and time-dependent creep. It more realistically describes the core controlling factors of porosity evolution from a mechanistic perspective, thus achieving a substantial improvement over traditional models in terms of accuracy, applicability, and predictive ability.

[0071] In some embodiments, the construction of the sandstone porosity enhancement model in step S20 may specifically include: constructing a burial history model of the sandstone strata; determining the paleoburial depth data of the sandstone strata based on the burial history model; obtaining paleotemperature data of the sandstone strata; determining the start and end times of dissolution porosity enhancement in the strata based on the paleoburial depth data and paleotemperature data; determining the acidification window of dissolution porosity enhancement in the strata based on the start and end times; and constructing the sandstone porosity enhancement model within the acidification window based on the total secondary porosity enhancement data of the dissolution porosity enhancement.

[0072] In some embodiments, the aforementioned dissolution and porosification process can be a constructive diagenetic process, i.e., a geological process in which acidic fluids flow through sandstone reservoirs during geological history, chemically dissolving soluble mineral components such as feldspar, rock fragments, or carbonate cements, thereby forming new pore spaces or expanding existing pores, resulting in an increase in the total porosity of the sandstone.

[0073] In some embodiments, a burial history model of sandstone strata can be constructed through back-exfoliation simulation based on stratigraphic data and compaction patterns to determine its paleoburial depth data in various geological periods. Simultaneously, corresponding paleotemperature data is obtained through paleotemperature gradient reconstruction or basin thermal history simulation. Based on the correspondence between paleoburial depth data and paleotemperature data, the time point when the strata temperature first reaches the dissolution initiation temperature (e.g., 70°C) is determined as the start time point of dissolution porosification, and the time point when the strata temperature first reaches the dissolution termination temperature (e.g., 90°C) is determined as the end time point of dissolution porosification. Based on the start and end times, the effective time period of dissolution porosification in the strata is clearly defined, i.e., the acidification window. This window characterizes the main geological periods in which organic acids are generated in large quantities and effectively dissolve sandstone framework minerals. By using paleotemperature data as the main controlling factor of dissolution, a transformation from static parameter description to dynamic process simulation is achieved. The method of determining the acidification window based on temperature thresholds enables the model to accurately capture specific geological periods in which dissolution occurs, significantly improving the geological realism of diagenetic simulation. Furthermore, by clearly defining the start and end points of dissolution, the subjectivity and arbitrariness in determining the dissolution period in traditional methods are overcome. This precise time constraint lays the foundation for the temporal coupling of subsequent porosity evolution models, ensuring accurate matching of different geological processes in the time dimension.

[0074] Based on paleoporosity data obtained through core analysis or well logging interpretation, a sandstone porosity enhancement model was constructed within the defined acidizing window. This model, by establishing a functional relationship between porosity enhancement and effective dissolution time, quantitatively characterizes the contribution of dissolution to porosity. By combining porosity enhancement data with a defined acidizing window, a quantitative model of dissolution-induced porosity enhancement was achieved. This quantitative characterization enables accurate assessment of the actual contribution of dissolution to reservoir properties, providing a reliable basis for predicting high-quality reservoirs.

[0075] In some embodiments, constructing a sandstone porosity model in the acidification window based on the total secondary porosity data from the dissolution porosity enhancement effect may specifically include: Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed in the acidification window: ; In the formula, Indicates the length of time since then Secondary porosity increase corresponding to the paleoporosity at the burial time of the strata This indicates that dissolution and porosimetry in the formation occur within the acidization window. Total secondary porosity within, , Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0076] The aforementioned sandstone porosity-enhancing model accurately simulates the natural process of dissolution—slow-fast-slow—with high geological consistency. Specifically: Based on the cubic interpolation function design, the natural variation of the dissolution rate during geological processes can be accurately simulated. In the initial stage of the window ( The porosity initially increases from zero, simulating the gradual accumulation of organic acid concentration and the initial development of dissolution. In the middle of the window, the porosity reaches its peak, simulating the period of abundant organic acid concentration and the most active and efficient dissolution. In the later stage of the window… The porosity gradually decreases to zero, simulating the stage where organic acids decrease due to consumption or thermal decomposition, and the dissolution gradually ceases. This S-shaped evolution characteristic of slow start-fast growth-slow stop is highly consistent with the dynamic process of underground fluid-rock reaction, overcoming the rigidity and inaccuracy of linear or simple quadratic models in describing such processes.

[0077] Furthermore, the aforementioned sandstone pore-enhancing model incorporates reasonable and accurate physical boundary conditions: when = hour, =0, meaning the dissolution process has not yet begun, and the porosity increase is zero. When = hour, = This means that the dissolution process ends, and the porosity increase reaches exactly the preset total porosity increase. Furthermore, in and At time, the rate of hole formation ( The values ​​approach 0, meaning that the dissolution process starts and ends smoothly without abrupt changes. These built-in mathematical constraints ensure that the model is physically sound, thus avoiding numerical abrupt changes at the endpoints or inconsistencies with geological common sense that may occur with empirical models.

[0078] The above sandstone pore-enhancing model It can be a parameter calibrated from current observational data such as core samples and well logs. It firmly binds the model's final amplitude to geological reality. Once determined through regression analysis or geostatistics... and Thus, the entire history of dissolution and porosimetry is uniquely determined. This makes the model no longer a purely mathematical deduction, but a quantitative tool with predictive capabilities constrained by actual data, significantly improving its reliability in unknown areas.

[0079] The aforementioned sandstone porosity-increasing model can output a continuous paleoporosity increase curve, which can be precisely algebraically superimposed in the time domain with the curve output by the equally continuous sandstone porosity-reducing model. This modular coupling method makes it efficient, accurate, and physically meaningful to construct a comprehensive porosity evolution model that can simultaneously reflect destructive and constructive diagenesis.

[0080] Overall, the sandstone porosity enhancement model described above dynamically and realistically reproduces the geological process of dissolution porosity enhancement through a geologically constrained mathematical function, thus providing crucial constructive genetic support for reconstructing a high-fidelity paleoporosity evolution history.

[0081] In some embodiments, obtaining the total secondary porosity data of the above-mentioned dissolution porosity enhancement effect may specifically include: determining the calibrated total secondary porosity data of the dissolution porosity enhancement effect based on the core data of the sandstone formation; extending the calibrated total secondary porosity data to the sandstone formation based on well logging interpretation data to obtain the statistical average total secondary porosity data; and conducting a rationality test on the statistical average total secondary porosity data based on diagenetic simulation to obtain the target total secondary porosity data of the dissolution porosity enhancement effect.

[0082] Specifically, secondary porosity, such as the proportion of intragranular dissolution pores and casting pores in the total rock area, can be directly identified, distinguished, and quantitatively statistically analyzed through microscopic imaging analysis of thin sections of drill core castings. The results serve as the most direct observational value of the total secondary porosity, i.e., the calibrated total secondary porosity data. Using logging sequences sensitive to mineral and pore structure, such as sonic-density logging combinations, combined with the calibrated total secondary porosity data, the total formation porosity can be calculated. Then, the theoretical primary porosity can be estimated by establishing a normal compaction trend line in the undissolved strata. Finally, the statistical average secondary porosity within the continuous profile is determined by the difference between the total porosity and the theoretical primary porosity, i.e., the statistical average total secondary porosity data. Based on burial history, thermal history, and formation water chemistry conditions, the dissolution kinetics of soluble minerals can be simulated using geochemical dynamics models, transforming the dissolution theory into secondary porosity increments, thus verifying the statistical average total secondary porosity data at the genetic mechanism level. The verified data can be used as the target total secondary porosity data for the dissolution porosimetry effect.

[0083] Using core data as benchmarks, statistically representative regional average values ​​were obtained through well logging interpretation, and the rationality of the mechanism was assessed using diagenetic simulation. This multi-source data fusion strategy ensures that the determination of total secondary porosity is geologically accurate, spatially representative, and theoretically reasonable, thus providing reliable parameter constraints for the paleoporosity-paleopressure evolution model.

[0084] In some embodiments, step S20 may further include: coupling a sandstone porosity reduction model and a sandstone porosity increase model of the sandstone formation to obtain the following porosity evolution model: ; In the formula, Indicates the length of time since then Paleoporosity corresponding to the burial time of the strata Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. When indicating the length of time since then The paleoporosity and secondary porosity at the ancient burial time point This represents the total amount of secondary porosity created by dissolution in the formation. Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0085] The aforementioned porosity evolution model achieves a seamless connection and complete characterization of porosity evolution throughout the entire geological history. Specifically: The aforementioned porosity evolution model constructs a comprehensive and uninterrupted history of porosity evolution by precisely defining three consecutive geological time domains: In At that time, i.e., the post-dissolution period: changes in porosity are determined by the sandstone porosity reduction model. The decision reflects the stage where, after dissolution ceases, the formation is only affected by compaction. At that time, i.e., the dissolution window period: porosity is + This dynamically couples destructive compaction-induced porosity reduction with constructive dissolution-induced porosity increase, simulating in real-time the competitive process of their ebb and flow. At time , i.e., the pre-dissolution period: porosity is... The porosity variation is determined solely by the sandstone porosity reduction model. This segmented structure overcomes the limitation of traditional single models in simultaneously describing different dominant mechanism stages, enabling a complete, continuous, and dynamic simulation of the reservoir.

[0086] The upper porosity evolution model accurately describes the dynamic coupling mechanism of constructive and destructive diagenesis, during the core dissolution window period ( The model does not simply statically add the results of the two processes together, but rather couples them dynamically and over time. At any given moment, the total porosity... Both are simultaneously affected by the degree of compaction and the rate of dissolution at that moment. This mechanism realistically recreates the complex process in geological history where compaction and dissolution, as two simultaneous but independent geological forces, jointly shape reservoir properties, significantly improving the simulation accuracy of the model.

[0087] In some embodiments, obtaining the rock acoustic transit time data corresponding to the paleoporosity data in step S20 above may specifically include: obtaining the rock acoustic transit time data corresponding to the paleoporosity data using the following formula based on the paleoporosity data, the pore fluid acoustic transit time data of the formation, and the acoustic transit time data of the rock matrix: ; In the formula, Indicates the length of time since the sandstone strata were formed. The time difference of sound waves from rocks at different points in time of ancient burial. This represents the acoustic transit time of pore fluids in sandstone formations. This represents the acoustic transit time of the sandstone matrix. Indicates the length of time since the sandstone strata were formed. Paleoporosity at the corresponding burial time of the strata.

[0088] The Willy time-averaging equation shows that the overall sound wave propagation time of a rock is a volume-weighted average of the propagation times of the pore fluid and the rock matrix. Therefore, using the above formula based on the Willy time-averaging equation ensures that the inversion process has a solid theoretical foundation and extremely high reliability, avoiding the regional limitations and uncertainties that may arise from using empirical regression formulas.

[0089] The acoustic velocity of rocks from geological history cannot be directly measured. Using the formula described above, and leveraging recoverable paleoporosity and fluid and matrix parameters that can be considered constants, the corresponding paleoacoustic transit times can be cleverly derived. This provides a simple and accurate method for solving the problem of obtaining paleoporotic physical parameters.

[0090] The above formula ensures that the acoustic data input into the particle stress model is completely synchronized and self-consistent with the paleoporosity evolution history. This avoids the systematic errors caused by directly using modern well logging acoustic transit time (which represents the final state after undergoing the entire historical evolution), thus laying a solid foundation for subsequent calculations of high-quality particle stress data and final paleopressure data.

[0091] In some embodiments, calculating the paleograin stress data of the sandstone strata in step S30 above may specifically include: calculating the paleograin stress data of the sandstone strata using the following formula based on the rock acoustic transit time data and paleoburial depth data: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point Indicates the length of time since the sandstone strata were formed. The time difference of sound waves from rocks at different points in time of ancient burial. Sandstone strata in terms of time elapsed since then The ancient burial depth at a given time point. , , This is an empirical constant.

[0092] The above formula uses burial depth as the macroscopic background field and acoustic transit time as a sensitive indicator reflecting the microscopic mechanical state of the rock. Through multi-parameter coupling, it achieves a direct and efficient estimation of the mechanical variable of particle stress. Among these parameters, the macroscopic background field (… The term directly reflects the influence of overlying strata load on increasing burial depth and is the dominant, linear contribution term controlling particle stress. Microscopic rock physical response ( The term quantifies the stiffness of rock by measuring the transit time of sound waves. The reciprocal of the transit time is positively correlated with the velocity of sound waves, and the velocity of sound is a sensitive indicator of the rock's elastic modulus and degree of compaction. The denser and harder the rock, the higher the velocity of sound waves and the smaller the transit time of sound waves.

[0093] Furthermore, the formula above uses The nonlinear term indicates that the increase in particle stress and the rise in sound wave velocity are not a simple linear relationship, but rather exhibit an accelerating intensification trend. This nonlinear relationship can more accurately describe the stress state of the rock skeleton in deep-ultra-deep strata under high pressure conditions, significantly improving the prediction accuracy of the model in complex high-stress environments and overcoming the shortcomings of linear models.

[0094] Overall, the above-mentioned paleoparticle stress calculation formula successfully transforms the available geophysical logging information (sonic transit time) and geological background information (burial depth) into mechanical parameters (particle stress) that are difficult to measure directly through an empirical function with a reasonable structure and calibrable parameters. This provides a reliable data foundation for subsequent high-precision and high-reliability paleopressure calculations based on the principle of static equilibrium.

[0095] The paleogranular stress calculation formulas described above assume that the overlying strata load is completely and linearly converted into granular stress, neglecting stress transmission losses caused by strata heterogeneity, faults, or the presence of plastic layers. This may lead to an overestimation of granular stress in complex tectonic zones. Furthermore, these formulas are purely elastic and transient, failing to consider the potential relaxation of skeletal stress due to high-temperature-driven rock creep on geological timescales. This results in a systematic overestimation of paleogranular stress in deep, high-temperature strata. Additionally, treating all sandstone as homogeneous materials and neglecting the fundamental influence of rigid minerals (such as quartz) and plastic minerals (such as clay) on the skeletal bearing capacity may lead to poor universality and low accuracy in stress prediction for sandstones of different lithologies.

[0096] Based on this, in some embodiments, the calculation of paleograin stress data of the sandstone strata in step S20 above may further include: calculating the paleograin stress data of the sandstone strata using the following formula based on the rock acoustic transit time data and paleoburial depth data: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point Indicates the length of time since the sandstone strata were formed. The time difference of sound waves from rocks at different points in time of ancient burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial time point paleostress data, E represents rock creep activation energy, R represents universal gas constant, T represents the length of time since the sandstone strata were buried. Paleotemperature at the point in time of ancient burial. This indicates the volume content of quartz in sandstone strata. This indicates the volume content of clay minerals in sandstone strata. , , , This is an empirical constant.

[0097] By introducing the load transfer efficiency coefficient By adjusting the theoretical overburden stress to the effective load actually acting on the sandstone skeleton, the accuracy of grain stress calculation in complex structural zones is significantly improved. This is achieved by increasing... This Arrhenius term quantifies the stress relaxation effect under the combined influence of temperature and time (implied in the temperature history). This enables a more realistic simulation of the stress state of ancient, deeply buried reservoirs, effectively solving the prediction bias problem of traditional elastic models in high-temperature deep strata. Furthermore, by adding... This method clearly distinguishes the different contributions of rigid and plastic minerals to grain stress, and can automatically adapt to reservoirs with different lithologies, from quartz sandstone to lithic sandstone, significantly improving the model's generalization ability and the physical rationality of the prediction results. Overall, the above formula organically integrates macroscopic loading, elastic wave response, thermodynamic processes, and petrological composition into a single mathematical framework, greatly enhancing the scientific rigor, accuracy, and universality of paleoparticle stress calculation.

[0098] In some embodiments, step S40 above, which substitutes the paleoburial depth data of the sandstone strata into the overlying stress calculation model based on the density model, to obtain the paleooverlying stress data acting on the top surface of the sandstone strata at each paleoburial time point, may specifically include: calculating the paleooverlying stress data of the sandstone strata using the following formula based on the paleoburial depth data: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleooverburial stress data at the time of burial. This represents the average density of sandstone strata. Represents gravitational acceleration. Indicates the length of time since the sandstone strata were formed. The ancient burial depth at the time of the ancient burial.

[0099] The paleoburial depth in the above formula is a dynamic parameter that varies over time, directly derived from the burial history model reconstructed in the preceding steps. This makes the calculation of overlying stress no longer static, but rather allows for a dynamic and continuous simulation of the overlying stress history that evolves with changes in burial depth. This seamless coupling is a key prerequisite for generating continuous paleopressure evolution curves.

[0100] Despite the complex basin structure, the above formula uses the concept of average density to simplify the complex layered strata into a uniform equivalent rock column. This simplification achieves a balance between computational efficiency and engineering accuracy, avoiding extremely complex layer-by-layer integration calculations and greatly reducing the computational burden on the model.

[0101] The aforementioned formula for calculating paleooverburden stress simplifies the overlying strata to a single average density, failing to accurately depict the compaction effect where density increases with depth in actual strata. This may lead to systematic errors in the overlying stress calculation. Furthermore, it neglects the dynamic evolution of rock density throughout geological history, ignoring the temporal changes in rock skeleton density during diagenetic compaction, potentially resulting in a lack of temporal accuracy in paleooverburden stress recovery. In addition, pure gravity models cannot reflect the additional vertical stress generated by tectonic activity, which may lead to a significant underestimation or overestimation of overlying stress in basins experiencing intense extensional or compressional forces.

[0102] Based on this, in some embodiments, step S40 above, which substitutes the paleoburial depth data of the sandstone strata into the overlying stress calculation model based on the density model, obtains the paleooverlying stress data acting on the top surface of the sandstone strata at each paleoburial time point. Specifically, this may include: substituting the paleoburial depth data of the sandstone strata into the overlying stress calculation model based on the density model to obtain the following paleooverlying stress data acting on the top surface of the sandstone strata at each paleoburial time point: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleooverburial stress data at the time of burial. This represents the length of time since the ancient burial depth z of the sandstone strata. Paleodensity at ancient burial time points Represents gravitational acceleration. Indicates the length of time since the sandstone strata were formed. The additional vertical stress component generated by regional tectonic activity at the paleoburial time point.

[0103] By establishing a dynamic functional relationship between density, depth, and time This accurately characterizes the nonlinear changes in density parameters during formation compaction. The integral calculation form more realistically reflects the actual weight distribution of the overlying rock column, significantly improving the accuracy of paleooverlying stress reconstruction. Furthermore, the added tectonic stress term... It effectively characterizes the contribution of tectonic activity to vertical stress at different stages of basin evolution, expanding the model's applicability from stable craton basins to active basins and significantly enhancing the universality of paleooverburden stress calculation.

[0104] In some embodiments, step S50 above, which calculates the paleopressure of the sandstone strata at each paleoburial time point using the rock static equilibrium equation based on the paleoporosity, paleogranular stress, and paleoverburial stress corresponding to each paleoburial time point, may specifically include: calculating the paleopressure of the sandstone strata at each paleoburial time point using the following formula based on the paleoporosity, paleogranular stress, and paleoverburial stress corresponding to each paleoburial time point: ; In the formula, Indicates the length of time since the sandstone strata were formed. The ancient pressure at the point in time of burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial stress at the time of burial Indicates the length of time since the sandstone strata were formed. Paleoporosity corresponding to the burial time of the strata Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point; Traditional paleopressure calculations are generally based on the Terzaghi or Biot effective stress principle, which raises theoretical controversies regarding whether effective stress is the actual force borne by the rock skeleton. The porosity coefficient is typically taken as 1. The formula above completely abandons this approach, instead starting from microscopic static equilibrium. It considers the total overlying stress to be borne jointly by the rock skeleton and pore fluid: the total force borne by the skeleton particle contact surface is... (The ratio of particle contact area to particle stress), while the total force borne by the pore fluid is (Pore area ratio multiplied by pore pressure). According to rock static equilibrium, we have The above formula is obtained after transformation.

[0105] In the above formula, paleoporosity is not only an input parameter but also a weighting coefficient for allocating the total overburden stress between the framework and the fluid. When porosity is high, the denominator of the formula increases, while the deduction for the framework support term decreases. This accurately reflects the tendency in high-porosity formations for more overburden load to be borne by pore fluids, potentially leading to higher pore pressure. Conversely, when porosity is low, more load is borne by the framework. This dynamic and nonlinear coupling relationship makes the model extremely sensitive to changes in porosity, enabling a more precise and realistic reflection of the control effect of porosity evolution on paleopressure, significantly improving calculation accuracy, especially in complex reservoirs that have undergone intense dissolution or compaction.

[0106] The above formula, applied to each paleoburial time point, generates a continuous and quantitative paleopressure evolution curve. This allows for the clear identification of key dynamic processes such as the formation of pressure reservoirs, peak overpressure periods, and pressure release events. Coupled analysis of this pressure curve with hydrocarbon generation and expulsion histories and tectonic activity histories can scientifically reveal the driving forces, dominant pathways, and key accumulation periods of hydrocarbons, providing direct evidence for effectively predicting hydrocarbon distribution.

[0107] The paleopressure calculation formulas described above treat all pore space as homogeneous fluid pressure transmission units, neglecting the immovable fluid pores present in actual reservoirs. This can lead to significant deviations from reality in pressure calculations for low-permeability tight reservoirs. Furthermore, pure single-phase flow models cannot accurately describe the complex pressure balance relationships during hydrocarbon accumulation when oil-gas-water multiphase fluids coexist, potentially ignoring the stress contribution of capillary forces to the rock skeleton. In addition, when total porosity approaches zero, the denominator of the original formula approaches zero, potentially resulting in non-physical infinite pressure values ​​in the calculations, lacking numerical stability in tight reservoir applications.

[0108] Based on this, in some embodiments, step S50 above calculates the paleopressure of the sandstone strata at each paleoburial time point using the rock static equilibrium equation based on the paleoporosity, paleogranular stress, and paleoverburial stress corresponding to each paleoburial time point. Specifically, this may include: calculating the paleopressure of the sandstone strata at each paleoburial time point using the following formula based on the paleoporosity, paleogranular stress, and paleoverburial stress corresponding to each paleoburial time point: ; In the formula, Indicates the length of time since the sandstone strata were formed. The ancient pressure at the point in time of burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial stress at the time of burial Indicates the length of time since the sandstone strata were formed. Paleoporosity corresponding to the burial time of the strata Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point This indicates the porosity occupied by immobile fluids in sandstone formations. This represents the capillary pressure in sandstone formations.

[0109] By introducing immovable porosity The model divides total porosity into effective flowing porosity and immovable porosity, enabling precise quantification of the bound fluid effect in low-permeability tight reservoirs and significantly improving the geological accuracy of pressure calculations. Furthermore, the capillary pressure term refines the static equilibrium relationship under multiphase fluid conditions, allowing the model to accurately describe the contribution of capillary forces to framework stress during hydrocarbon charging, providing more reliable pressure field data for hydrocarbon accumulation dynamics research. In addition, effective flowing porosity (… This avoids the numerical divergence problem of the denominator approaching zero under low porosity conditions, and enhances the applicability of the model in unconventional tight reservoirs and the physical rationality of the calculation results.

[0110] As can be seen from the calculation method of paleopressure in sandstone strata provided in the embodiments of this specification above, the embodiments of this specification can obtain paleoburial depth data of sandstone strata; based on the paleoburial depth data, the paleoporosity data of the strata is calculated using a porosity evolution model. The porosity evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model characterizes the nonlinear correlation between the paleoburial depth, the paleoburial time of the strata, and the creep of the strata, while the sandstone porosity increase model characterizes the correlation between the paleotemperature of the strata and the porosity increase effect of dissolution in the strata; based on the paleoburial depth data and paleoporosity data, the paleogranular stress data of the sandstone strata is inverted; the paleoverburial stress data of the sandstone strata is obtained; based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, the paleopressure evolution data of the sandstone strata is calculated, and the paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time. The porosity evolution model, by coupling two opposing geological processes—porosity reduction and porosity increase—completely describes the dynamic evolution of sandstone strata properties, avoiding the systematic biases inherent in a single porosity reduction model. Furthermore, the introduction of paleoburial time and rock creep into the porosity reduction model helps characterize time-dependent nonlinear deformation behavior over long geological histories, improving the accuracy of compaction simulations of deep, ancient strata. Using paleotemperature as a control variable in the porosity increase model allows for close integration of dissolution simulations with geochemical processes such as basin thermal history and organic acid formation windows, enhancing the geological rationality of constructive diagenesis simulations. In addition, by abandoning traditional effective stress algorithms and instead inverting paleoclimate stress data, combined with paleoporosity and paleoverburial stress data, the model outputs the evolutionary relationship between paleopressure and paleoburial time. This overcomes the limitation of methods such as fluid inclusions, which can only provide isolated time-point pressure snapshots, significantly improving the accuracy of paleopressure calculations and enhancing the credibility and interpretability of the final pressure evolution history.

[0111] Based on the above-described method for calculating paleopressure in sandstone strata, this specification also provides embodiments of a device for calculating paleopressure in sandstone strata. For example... Figure 2 As shown, the calculation device 200 for paleopressure in the sandstone strata may specifically include the following modules: The first acquisition module 201 is used to acquire ancient burial depth data of sandstone strata.

[0112] The first calculation module 202 is used to calculate the paleoporosity data of the strata using the pore evolution model based on the paleoburial depth data. The pore evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model represents the nonlinear relationship between the paleoburial depth of the strata, the paleoburial time of the strata and the creep of the strata. The sandstone porosity increase model represents the relationship between the paleotemperature of the strata and the porosity increase effect of the strata by dissolution.

[0113] The inversion module 203 is used to invert the paleoclimate stress data of the sandstone strata based on the paleoburial depth data and paleoporosity data.

[0114] The second acquisition module 204 is used to acquire paleooverburden stress data of sandstone strata.

[0115] The second calculation module 205 is used to calculate the paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data and paleoverburial stress data. The paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time.

[0116] In some embodiments, the first computing module 202 described above can be specifically used for: By coupling the sandstone porosity reduction model and the sandstone porosity increase model of the sandstone formation, the following porosity evolution model is obtained: ; In the formula, Indicates the length of time since then Paleoporosity corresponding to the burial time of the strata Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. When indicating the length of time since then The paleoporosity and secondary porosity at the ancient burial time point This represents the total amount of secondary porosity created by dissolution in the formation. Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0117] In some embodiments, the first computing module 202 described above can also be used for: Acquire sandstone data for a target section of sandstone strata; the target section is a compacted section of sandstone strata that has not been affected by dissolution and porosification; the sandstone data includes at least paleoburial depth data, paleoporosity data, and paleoburial time data for the target section; Based on the sandstone data of the target sandstone stratum, a multivariate nonlinear regression analysis was performed. Based on the results of the multivariate nonlinear regression analysis, a sandstone porosity reduction model for sandstone formations is constructed.

[0118] In some embodiments, the first computing module 202 described above can also be used for: Based on the results of the multivariate nonlinear regression analysis, the following sandstone porosity reduction model for sandstone strata is constructed: ; In the formula, Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. Indicates the initial sedimentary paleoporosity. Indicates the length of time since then The ancient burial depth at a given time point. , , , These represent the regression coefficients determined based on the results of multivariate nonlinear regression analysis. It is a positive number less than 1.

[0119] In some embodiments, the first computing module 202 described above can also be used for: Constructing a model of the burial history of sandstone strata; Based on the aforementioned burial history model, the paleoburial depth data of the sandstone strata were determined; Obtain paleotemperature data of sandstone strata; Based on the paleoburial depth and paleotemperature data, the start and end times of the dissolution and porosification process in the strata were determined. Based on the start and end times, the acidization window for dissolution and porosimetry in the formation is determined; Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed within the acidification window.

[0120] In some embodiments, the first computing module 202 described above can also be used for: Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed in the acidification window: ; In the formula, Indicates the length of time since then Secondary porosity increase corresponding to the paleoporosity at the burial time of the strata This indicates that dissolution and porosimetry in the formation occur within the acidization window. Total secondary porosity within, , Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

[0121] In some embodiments, the inversion module 203 described above can be specifically used for: Based on the paleoporosity data, the pore fluid acoustic transit time data of the formation, and the acoustic transit time data of the rock matrix, the rock acoustic transit time data corresponding to the paleoporosity data is inverted. Based on the rock acoustic transit time data and paleoburial depth data, paleoparticle stress data of the sandstone strata were calculated.

[0122] In some embodiments, the second acquisition module 204 described above can be specifically used for: Based on the paleoburial depth data, the paleooverburial stress data of the sandstone strata were calculated using the following formula: ; In the formula, Indicates the length of time since the sandstone strata were formed. Paleooverburial stress data at the time of burial. This represents the average density of sandstone strata. Represents gravitational acceleration. Indicates the length of time since the sandstone strata were formed. The ancient burial depth at the time of the ancient burial.

[0123] In some embodiments, the second computing module 205 described above can be specifically used for: Based on the paleoporosity, paleogranular stress, and paleooverburial stress corresponding to each paleoburial time point, the paleopressure of the sandstone strata at each paleoburial time point is calculated using the following formula: ; In the formula, Indicates the length of time since the sandstone strata were formed. The ancient pressure at the point in time of burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial stress at the time of burial Indicates the length of time since the sandstone strata were formed. Paleoporosity corresponding to the burial time of the strata Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point; Based on the paleopressure at each paleoburial time point of the sandstone strata, the paleopressure evolution data of the sandstone strata were determined.

[0124] As can be seen from the above embodiments of this specification, the apparatus for calculating paleopressure in sandstone strata can acquire paleoburial depth data of sandstone strata; based on the paleoburial depth data, it uses a porosity evolution model to calculate the paleoporosity data of the strata. The porosity evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model characterizes the nonlinear correlation between the paleoburial depth, the paleoburial time, and the creep of the strata, while the sandstone porosity increase model characterizes the correlation between the paleotemperature of the strata and the porosity increase effect of dissolution in the strata; based on the paleoburial depth data and paleoporosity data, it inverts the paleogranular stress data of the sandstone strata; it acquires the paleoverburial stress data of the sandstone strata; and based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, it calculates the paleopressure evolution data of the sandstone strata, which includes the evolutionary relationship between the paleopressure of the strata and the paleoburial time. The porosity evolution model, by coupling two opposing geological processes—porosity reduction and porosity increase—completely describes the dynamic evolution of sandstone strata properties, avoiding the systematic biases inherent in a single porosity reduction model. Furthermore, the introduction of paleoburial time and rock creep into the porosity reduction model helps characterize time-dependent nonlinear deformation behavior over long geological histories, improving the accuracy of compaction simulations of deep, ancient strata. Using paleotemperature as a control variable in the porosity increase model allows for close integration of dissolution simulations with geochemical processes such as basin thermal history and organic acid formation windows, enhancing the geological rationality of constructive diagenesis simulations. In addition, by abandoning the traditional effective stress principle and instead inverting paleoclimate stress data, combined with paleoporosity and paleoverburial stress data, the model outputs the evolutionary relationship between paleopressure and paleoburial time. This overcomes the limitation of methods such as fluid inclusions, which can only provide isolated time-point pressure snapshots, significantly improving the accuracy of paleopressure calculations and enhancing the credibility and interpretability of the final pressure evolution history.

[0125] This specification also provides a computer device for calculating paleopressure in sandstone strata, including a processor and a memory for storing processor-executable instructions. Specifically, the processor can perform the following tasks according to the instructions: acquiring paleoburial depth data of the sandstone strata; calculating paleoporosity data of the strata using a porosity evolution model based on the paleoburial depth data, wherein the porosity evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model, the sandstone porosity reduction model characterizing the nonlinear correlation between paleoburial depth, paleoburial time, and strata creep, and the sandstone porosity increase model characterizing the correlation between paleotemperature and the porosity increase effect of strata dissolution; inverting paleogranular stress data of the sandstone strata based on the paleoburial depth data and paleoporosity data; acquiring paleoverburial stress data of the sandstone strata; and calculating paleopressure evolution data of the sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, wherein the paleopressure evolution data includes the evolutionary relationship between paleopressure and paleoburial time.

[0126] To execute the above instructions more accurately, please refer to... Figure 3 As shown in the embodiments of this specification, another specific computer device 300 is also provided, wherein the computer device 300 includes a network communication port 301, a processor 302 and a memory 303, and the above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0127] The processor 302 can specifically be used to: acquire paleoburial depth data of sandstone strata; calculate paleoporosity data of strata using a porosity evolution model based on the paleoburial depth data, wherein the porosity evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model, wherein the sandstone porosity reduction model characterizes the nonlinear correlation between paleoburial depth, paleoburial time, and strata creep, and the sandstone porosity increase model characterizes the correlation between paleotemperature and dissolution porosity increase in strata; invert paleogranular stress data of sandstone strata based on the paleoburial depth data and paleoporosity data; acquire paleoverburden stress data of sandstone strata; and calculate paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburden stress data, wherein the paleopressure evolution data includes the evolution relationship between paleopressure and paleoburial time.

[0128] The memory 303 can be used to store the corresponding instruction program.

[0129] In this embodiment, the network communication port 301 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0130] In this embodiment, the processor 302 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0131] In this embodiment, the memory 303 includes volatile memory and non-volatile memory. The memory 303 can include multiple layers. In digital systems, anything that can store binary data can be a memory; in integrated circuits, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0132] This specification also provides a computer program product, including at least one instruction or at least one program segment, wherein the at least one instruction or the at least one program segment is loaded and executed by a processor to achieve the following: Figure 1 The method shown.

[0133] It should be understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this specification.

[0134] It should also be understood that, in the embodiments of this specification, the terms and / or are merely descriptions of the relationships between related objects, indicating that three relationships may exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this specification generally indicates that the preceding and following related objects have an "or" relationship.

[0135] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0137] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational tasks to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The task is a function specified in one or more boxes.

[0139] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for calculating paleopressure in sandstone strata, characterized in that, include: Obtain paleoburial depth data of sandstone strata; Based on the paleoburial depth data, the paleoporosity data of the strata were calculated using a pore evolution model. The pore evolution model was coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model characterized the nonlinear relationship between the paleoburial depth, paleoburial time, and strata creep, while the sandstone porosity increase model characterized the relationship between the paleotemperature of the strata and the porosity increase effect of strata dissolution. Based on the paleoburial depth data and paleoporosity data, paleogranular stress data of sandstone strata were inverted. Obtain paleooverburden stress data for sandstone strata; Based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data, paleopressure evolution data of sandstone strata were calculated. The paleopressure evolution data includes the evolution relationship between strata paleopressure and paleoburial time.

2. The method according to claim 1, characterized in that, The construction of the pore evolution model includes: By coupling the sandstone porosity reduction model and the sandstone porosity increase model of the sandstone formation, the following porosity evolution model is obtained: ； In the formula, Indicates the length of time since then Paleoporosity corresponding to the burial time of the strata Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. When indicating the length of time since then The paleoporosity and secondary porosity at the ancient burial time point This represents the total amount of secondary porosity created by dissolution in the formation. Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

3. The method according to claim 1, characterized in that, The construction of the sandstone porosity reduction model includes: Acquire sandstone data for a target section of sandstone strata; the target section is a compacted section of sandstone strata that has not been affected by dissolution and porosification; the sandstone data includes at least paleoburial depth data, paleoporosity data, and paleoburial time data for the target section; Based on the sandstone data of the target sandstone stratum, a multivariate nonlinear regression analysis was performed. Based on the results of the multivariate nonlinear regression analysis, a sandstone porosity reduction model for sandstone formations is constructed.

4. The method according to claim 3, characterized in that, The step of constructing a sandstone porosity reduction model for sandstone formations based on the results of the multivariate nonlinear regression analysis includes: Based on the results of the multivariate nonlinear regression analysis, the following sandstone porosity reduction model for sandstone strata is constructed: ； In the formula, Indicates the length of time since then The remaining paleoporosity after compaction and pore reduction at the paleoburial time point. Indicates the initial sedimentary paleoporosity. Indicates the length of time since then The ancient burial depth at a given time point. , , , These represent the regression coefficients determined based on the results of multivariate nonlinear regression analysis. It is a positive number less than 1.

5. The method according to claim 1, characterized in that, The construction of the sandstone pore-enhancing model includes: Constructing a model of the burial history of sandstone strata; Based on the aforementioned burial history model, the paleoburial depth data of the sandstone strata were determined; Obtain paleotemperature data of sandstone strata; Based on the paleoburial depth and paleotemperature data, the start and end times of the dissolution and porosification process in the strata were determined. Based on the start and end times, the acidization window for dissolution and porosimetry in the formation is determined; Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed within the acidification window.

6. The method according to claim 5, characterized in that, The step of constructing a sandstone porosity model within the acidification window based on the total secondary porosity data from the dissolution porosity enhancement effect includes: Based on the total secondary porosity data of the dissolution porosity enhancement effect, a sandstone porosity enhancement model is constructed in the acidification window: ； In the formula, Indicates the length of time since then Secondary porosity increase corresponding to the paleoporosity at the burial time of the strata This indicates that dissolution and porosimetry in the formation occur within the acidization window. Total secondary porosity within, , Indicates the starting point of dissolution and porosimetry in the formation. This indicates the point in time when the dissolution and porosimetry process in the formation ends.

7. The method according to claim 1, characterized in that, The process of inverting paleoclimate stress data of sandstone strata based on the paleoburial depth data and paleoporosity data includes: Based on the paleoporosity data, the pore fluid acoustic transit time data of the formation, and the acoustic transit time data of the rock matrix, the rock acoustic transit time data corresponding to the paleoporosity data is inverted. Based on the rock acoustic transit time data and paleoburial depth data, paleoparticle stress data of the sandstone strata were calculated.

8. The method according to claim 1, characterized in that, The acquisition of paleoverburden stress data for sandstone strata includes: Based on the paleoburial depth data, the paleooverburial stress data of the sandstone strata were calculated using the following formula: ； In the formula, Indicates the length of time since the sandstone strata were formed. Paleooverburial stress data at the time of burial. This represents the average density of sandstone strata. Represents gravitational acceleration. Indicates the length of time since the sandstone strata were formed. The ancient burial depth at the time of the ancient burial.

9. The method according to claim 1, characterized in that, The calculation of paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburden stress data includes: Based on the paleoporosity, paleogranular stress, and paleooverburial stress corresponding to each paleoburial time point, the paleopressure of the sandstone strata at each paleoburial time point is calculated using the following formula: ； In the formula, Indicates the length of time since the sandstone strata were formed. The ancient pressure at the point in time of burial. Indicates the length of time since the sandstone strata were formed. Paleooverburial stress at the time of burial Indicates the length of time since the sandstone strata were formed. Paleoporosity corresponding to the burial time of the strata Indicates the length of time since the sandstone strata were formed. Paleogranular stress at the paleoburial time point; Based on the paleopressure at each paleoburial time point of the sandstone strata, the paleopressure evolution data of the sandstone strata were determined.

10. A device for calculating paleopressure in sandstone strata, characterized in that, The device includes: The first acquisition module is used to acquire ancient burial depth data of sandstone strata; The first calculation module is used to calculate the paleoporosity data of the strata using the pore evolution model based on the paleoburial depth data. The pore evolution model is coupled with a sandstone porosity reduction model and a sandstone porosity increase model. The sandstone porosity reduction model represents the nonlinear relationship between the paleoburial depth of the strata, the paleoburial time of the strata and the creep of the strata. The sandstone porosity increase model represents the relationship between the paleotemperature of the strata and the porosity increase effect of the strata through dissolution. The inversion module is used to invert the paleoclimate stress data of sandstone strata based on the paleoburial depth data and paleoporosity data. The second acquisition module is used to acquire paleoverburden stress data of sandstone strata; The second calculation module is used to calculate the paleopressure evolution data of sandstone strata based on the paleoporosity data, paleogranular stress data, and paleoverburial stress data. The paleopressure evolution data includes the evolution relationship between the paleopressure of the strata and the paleoburial time.

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