Carbonate cluster isotope-based thermal history reconstruction method, device, equipment and medium

Abstract

The application discloses a carbonate cluster isotope-based thermal history reconstruction method, device, equipment and medium, relates to geothermology and geophysical technology, and comprises the following steps: obtaining an initial sample, determining the period of the initial sample by a preset test method, screening and analyzing the initial sample based on the period to determine a to-be-tested sample; obtaining an absolute crystallization age by using a laser ablation plasma mass spectrometry technology, testing cluster isotope abundance values of each to-be-tested sample, determining a measured temperature based on the cluster isotope abundance values, obtaining a target burial history, and obtaining an initial thermal history path based on a paleogeothermal gradient of a target marine facies series and a depth according to the target burial history; determining a sample of a preset thermal history period based on the absolute crystallization age of the to-be-tested sample, predicting a predicted temperature based on the initial thermal history path by using a preset kinetic model, reconstructing the initial thermal history path by fitting the predicted temperature and the measured temperature, and obtaining a target thermal history path. In this way, the application can improve the accuracy of predicting thermal history at each stage.

Description

Technical Field

[0001] This invention relates to geothermal and geophysical technologies, and particularly to methods, apparatus, equipment, and media for reconstructing thermal history based on carbonate cluster isotopes. Background Technology

[0002] Reconstructing the thermal history of sedimentary basins is crucial for revealing basin tectonic evolution and hydrocarbon resource distribution. Paleothermography is a commonly used method, but traditional approaches such as vitrinite reflectance and fission track face limitations in ancient marine carbonate strata—these strata often lack suitable minerals like vitrinite, apatite, and zircon. While equivalent vitrinite reflectance for carbonate rocks can record the highest paleotemperatures, it cannot reflect multi-stage thermal evolution; conodont color variation index is easily affected by subjective factors. Furthermore, overall inversion using mineral indicators from different sources and thermally sealed systems often results in signal averaging, making it difficult to identify multi-stage, especially short-term, thermal anomaly events.

[0003] The carbonate cluster isotope thermometry method, which has emerged in recent years, has provided a new approach for studying the thermal history of carbonate rocks. This method works well in simple areas that have experienced a single burial-uplift, but for ancient cratonic basins that have experienced multiple phases of tectonic-magmatic activity, the temperature of a single micritic matrix is ​​actually a comprehensive response of multiple thermal events, which is ambiguous and makes it difficult to accurately invert the thermal history of each stage.

[0004] In conclusion, improving the accuracy of predicting thermal history at each stage is a pressing issue that needs to be addressed. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, apparatus, device, and medium for reconstructing thermal history based on carbonate cluster isotopes, which can improve the accuracy of predicting thermal history at various stages. The specific solution is as follows: Firstly, this application provides a method for reconstructing the thermal history based on carbonate cluster isotopes, including: Initial samples are obtained from the target marine strata. The phase of the initial samples is determined by a preset testing method. Based on the phase of the initial samples, the initial samples are screened and analyzed to determine the test samples of the target phase. The absolute crystallization age of the sample to be tested is obtained by laser ablation plasma mass spectrometry. The cluster isotope abundance values ​​of each sample to be tested are measured. The corresponding measured temperature is determined based on the cluster isotope abundance values ​​of the sample to be tested. The target burial history of the target marine strata is obtained. The initial thermal history path is obtained based on the paleothermal gradient and depth of the target marine strata according to the target burial history. Based on the absolute crystallization age of the sample to be tested, a sample at a preset thermal history period is determined. A preset kinetic model is used to predict the predicted temperature of the sample at the preset thermal history period based on the initial thermal history path. The initial thermal history path is reconstructed by fitting the predicted temperature of the sample at each preset thermal history period with the corresponding measured temperature, and the target thermal history path is obtained.

[0006] Optionally, determining the period of the initial sample using a preset testing method includes: A preset thin-slice identification operation and a preset cathodic emission operation are performed on the initial sample to obtain the corresponding identification results and luminescence results; The initial sample's period is determined based on the identification and luminescence results.

[0007] Optionally, the step of screening and analyzing the initial sample based on its period to determine the target period sample includes: Based on the initial sample's period, the initial sample for the target period is selected; X-ray diffraction analysis was performed on the initial sample of the target period; Based on the obtained analysis results, determine whether the main mineral content of the initial sample is greater than a preset content threshold; If so, the initial sample with a main mineral content greater than a preset content threshold is determined as the sample to be tested.

[0008] Optionally, obtaining the target burial history of the target marine strata includes: Geological data of the target marine strata are obtained; wherein the geological data includes lithological composition, residual thickness and erosion amount during the preset key tectonic activity period; The target burial history of the target marine strata is obtained by using preset geological software based on the geological data of the target marine strata.

[0009] Optionally, the sample for determining the preset thermal history period based on the absolute crystallization age of the sample to be tested includes: Based on the refined requirements of the target thermal history reconstruction, the preset thermal history period is divided; the preset thermal history period includes any one or more of the preset thermal history late stage, preset thermal history middle stage, and preset thermal history early stage. Based on the absolute crystallization age of the test sample, a first sample that meets the preset youngest condition is selected from the test samples, and the duration of the first sample is determined as the preset late thermal history. Based on the absolute crystallization age of the sample to be tested, a second sample that meets the preset second young condition is selected from the sample to be tested, and the time period from the second sample to the first sample is determined as the preset mid-thermal history; wherein, the absolute crystallization age of the second sample is greater than the absolute crystallization age of the first sample; Based on the absolute crystallization age of the test sample, a third sample that meets the preset old sample conditions is selected from the test samples, and the time period from the third sample to the second sample is determined as the preset early thermal history; wherein, the absolute crystallization age of the third sample is greater than the absolute crystallization age of the second sample.

[0010] Optionally, the step of using a preset kinetic model to predict the predicted temperature of the sample at the preset thermal history period based on the initial thermal history path, and reconstructing the initial thermal history path by fitting the predicted temperature of the sample at each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path includes: Determine the first thermal history path to be adjusted in the initial thermal history path that corresponds to the duration of the first sample; The predicted temperature of the first sample is predicted based on the first thermal history path to be adjusted using a preset kinetic model. Determine whether the predicted temperature of the first sample is consistent with the corresponding measured temperature; If not, adjust the first thermal history path to be adjusted until the difference between the predicted temperature and the measured temperature of the first sample is less than a preset error threshold, and determine the first adjusted thermal history path for the preset late thermal history period. If so, the first thermal history path to be adjusted is directly determined as the first target adjusted thermal history path in the preset late thermal history period; Determine the second thermal history path to be adjusted in the initial thermal history path that corresponds to the time period from the second sample to the first sample; The predicted temperature of the second sample is predicted based on the second thermal history path to be adjusted using a preset kinetic model. Determine whether the predicted temperature of the second sample is consistent with the corresponding measured temperature; If not, adjust the second thermal history path to be adjusted until the difference between the predicted temperature and the measured temperature of the second sample is less than the preset error threshold, and determine the second adjusted thermal history path for the preset late thermal history period. If so, the second thermal history path to be adjusted is directly determined as the second adjusted thermal history path in the preset thermal history mid-term. The target thermal history path is obtained by integrating the determined adjusted thermal history paths.

[0011] Optionally, the method further includes: If the difference between the predicted temperature and the corresponding measured temperature of the sample during the preset thermal history period cannot be less than a preset error threshold, it is determined that the sample has a thermal anomaly during the preset thermal history period. The peak temperature and duration of the thermal pulse in the thermal history path corresponding to the preset thermal history period are then adjusted until the difference between the predicted temperature and the corresponding measured temperature of the sample is less than the preset error threshold.

[0012] Secondly, this application provides a thermal history reconstruction device based on carbonate cluster isotopes, comprising: The sample determination module is used to obtain initial samples in the target marine strata, determine the phase of the initial samples through a preset testing method, and screen and analyze the initial samples based on the phase of the initial samples to determine the test samples of the target phase. The first path acquisition module is used to obtain the absolute crystallization age of the sample to be tested using laser ablation plasma mass spectrometry, test the cluster isotope abundance value of each sample to be tested, determine the corresponding measured temperature based on the cluster isotope abundance value of the sample to be tested, obtain the target burial history of the target marine strata, and obtain the initial thermal history path based on the paleothermal gradient and depth of the target marine strata according to the target burial history. The second path acquisition module is used to determine the sample of the preset thermal history period based on the absolute crystallization age of the sample to be tested, predict the predicted temperature of the sample of the preset thermal history period based on the initial thermal history path using a preset kinetic model, and reconstruct the initial thermal history path by fitting the predicted temperature of the sample of each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path.

[0013] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is used to execute the computer program to implement the thermal history reconstruction method based on carbonate cluster isotopes as described above.

[0014] Fourthly, this application provides a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned method for thermal history reconstruction based on carbonate cluster isotopes.

[0015] In summary, this application first obtains initial samples from the target marine strata, determines the phase of the initial samples using a preset testing method, and then screens and analyzes the initial samples based on their phases to determine the test samples for the target phase. It then uses laser ablation plasma mass spectrometry to obtain the absolute crystallization age of the test samples, tests the cluster isotope abundance values ​​of each test sample, determines the corresponding measured temperature based on the cluster isotope abundance values, obtains the target burial history of the target marine strata, and obtains the initial thermal history path based on the paleothermal gradient and depth of the target marine strata according to the target burial history. Based on the absolute crystallization age of the test samples, it determines the samples for a preset thermal history period, uses a preset kinetic model to predict the predicted temperature of the samples for the preset thermal history period based on the initial thermal history path, and reconstructs the initial thermal history path by fitting the predicted temperatures of the samples for each preset thermal history period with the corresponding measured temperatures to obtain the target thermal history path. As described above, this application first obtains initial samples from the target marine strata, determines their phases using a pre-defined testing method, and selects samples for the target phases. Then, it uses laser ablation plasma mass spectrometry to obtain the absolute crystallization age of the samples and simultaneously tests their cluster isotope abundance values ​​to determine the measured temperature. Next, it obtains the target burial history of the target marine strata and obtains the initial thermal history path based on its paleothermal gradient and depth. Then, based on the absolute crystallization age of the samples, it determines the samples for the pre-defined thermal history period. Using a pre-defined kinetic model, it predicts the temperature of the samples for that period based on the initial thermal history path. Finally, by fitting the predicted temperatures of samples for each pre-defined thermal history period with the corresponding measured temperatures, it reconstructs the initial thermal history path and obtains the target thermal history path. In this way, the continuous thermal history is divided into several defined time segments using U-Pb ageing, and the segmented locking strategy significantly reduces the ambiguity of traditional inversion methods. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 This is a flowchart of a thermal history reconstruction method based on carbonate cluster isotopes disclosed in this application; Figure 2 This is a flowchart of a specific thermal history reconstruction method based on carbonate cluster isotopes disclosed in this application; Figure 3 This is a schematic diagram of the thermal history before the specific adjustment disclosed in this application; Figure 4 This is a specific modified thermal history diagram disclosed in this application; Figure 5 This is a schematic diagram of a thermal history reconstruction device based on carbonate cluster isotopes disclosed in this application. Figure 6 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Currently, reconstructing the thermal history of sedimentary basins is crucial for revealing basin tectonic evolution and hydrocarbon resource distribution. Paleothermography is a commonly used method, but traditional approaches such as vitrinite reflectance and fission track face limitations in ancient marine carbonate strata—these strata often lack suitable minerals like vitrinite, apatite, and zircon. While equivalent vitrinite reflectance for carbonate rocks can record the highest paleotemperatures, it cannot reflect multi-stage thermal evolution; conodont color variation index is easily affected by subjective factors. Furthermore, overall inversion using mineral indicators from different sources and thermally sealed systems often results in signal averaging, making it difficult to identify multi-stage, especially short-term, thermal anomalies. In recent years, carbonate cluster isotope thermography has emerged, providing a new approach for studying the thermal history of carbonate rocks. This method works well in simple areas that have undergone a single burial-uplift event. However, for ancient cratonic basins that have experienced multiple phases of tectonic-magmatic activity, the temperature of a single micritic matrix is ​​actually a comprehensive response to the superposition of multiple thermal events, resulting in multiple interpretations and making it difficult to accurately invert the thermal history of each stage. To address these technical problems, this application discloses a method, apparatus, equipment, and medium for thermal history reconstruction based on carbonate cluster isotopes, which can improve the accuracy of predicting the thermal history of each stage.

[0020] See Figure 1 As shown, this embodiment of the invention discloses a method for reconstructing the thermal history based on carbonate cluster isotopes, comprising: Step S11: Obtain an initial sample from the target marine strata, determine the phase of the initial sample using a preset testing method, and screen and analyze the initial sample based on the phase to determine the test sample of the target phase.

[0021] In this embodiment, initial samples are collected from ancient marine strata such as the Cambrian system. Pre-defined thin-section identification and cathodoluminescence (CL) operations are then performed on these initial samples to obtain corresponding identification and luminescence results. The diagenesis of the initial samples is determined based on these results. Specifically, thin-section identification and CL are used to strictly distinguish carbonate components from different diagenetic stages, such as early diagenetic micritic matrix, calcite / dolomite veins filling multi-stage tectonic fractures, and cement, to avoid confusion between components from different stages in subsequent cluster isotope and U-Pb dating tests. Next, initial samples from the target diagenesis are selected based on the initial sample's diagenesis. X-ray diffraction analysis is performed on the initial samples from the target diagenesis. Based on the analysis results, it is determined whether the main mineral content of the initial samples is greater than a preset content threshold. If so, the initial samples with main mineral content greater than the preset content threshold are identified as samples to be tested. Specifically, initial samples from the same period are selected based on the consistent luminescence of cathodoluminescence, excluding samples with multiple crystallization events, and the initial sample from the target period is selected. To ensure testing accuracy, relatively clean carbonate minerals are selected as the research object. Therefore, X-ray diffraction analysis is performed on the samples, and samples with a main mineral content greater than a preset content threshold are selected as test samples. For example, samples with a main mineral content ≥95% are identified as test samples.

[0022] Step S12: Obtain the absolute crystallization age of the sample to be tested using laser ablation plasma mass spectrometry, test the cluster isotope abundance value of each sample to be tested, determine the corresponding measured temperature based on the cluster isotope abundance value of the sample to be tested, obtain the target burial history of the target marine strata, and obtain the initial thermal history path based on the paleothermal gradient and depth of the target marine strata according to the target burial history.

[0023] In this embodiment, the absolute crystallization age of the minerals at the target stage is obtained using LA-ICP-MS (Laser Ablation-Inductively Coupled Plasma Mass Spectrometry). Then, the cluster isotopic composition of each of the test samples was tested. The equilibrium temperature is represented by a preset calibration formula. ): ; in, This refers to the cluster isotopic composition of the sample, or the cluster isotopic abundance value. T or The apparent measured temperature of the sample is due to the transformation of cluster isotopic composition.

[0024] In this embodiment, since the reconstruction of sedimentary burial history is the foundation for conducting thermal history simulation, it is necessary to first obtain the target burial history of the target marine strata. Geological data of the target marine strata can be obtained; this geological data includes stratigraphic lithology, residual thickness, and erosion during preset key tectonic periods. The target burial history of the target marine strata is obtained using preset geological software based on the geological data of the target marine strata. Specifically, the geological data required for reconstructing the burial history includes stratigraphic lithology, residual thickness, and erosion during key tectonic periods. Erosion can be obtained through methods such as well logging data and seismic data. Using relevant geological software, by inputting this geological data, the target burial history of the target marine strata can be obtained using an inversion method. Based on the reconstructed target burial history, and combined with the publicly available paleothermal gradient of the study area, the depth of the target stratum is divided by the geothermal gradient to obtain the preset time-temperature path used for simulation, i.e., the initial thermal history path.

[0025] Step S13: Determine the sample for the preset thermal history period based on the absolute crystallization age of the sample to be tested, predict the predicted temperature of the sample for the preset thermal history period using a preset kinetic model based on the initial thermal history path, and reconstruct the initial thermal history path by fitting the predicted temperature of the sample for each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path.

[0026] In this embodiment, after obtaining the initial thermal history path, a solid-state rearrangement forward modeling simulation is performed, proceeding from newest to oldest and segmented locking. First, a preset thermal history period is defined based on the refined requirements of the target thermal history reconstruction. This preset thermal history period includes any one or more of the preset late thermal history, preset middle thermal history, and preset early thermal history periods. Based on the absolute crystallization age of the samples to be tested, a first sample meeting the preset youngest condition is selected, and the duration of the first sample is defined as the preset late thermal history period. Based on the absolute crystallization age of the samples to be tested, a second sample meeting the preset second youngest condition is selected, and the time period from the second sample to the first sample is defined as the preset middle thermal history period. The absolute crystallization age of the second sample is greater than that of the first sample. Based on the absolute crystallization age of the samples to be tested, a third sample meeting the preset old sample condition is selected, and the time period from the third sample to the second sample is defined as the preset early thermal history period. The absolute crystallization age of the third sample is greater than that of the second sample. Specifically, the sample with the youngest absolute crystallization age is selected, let its age be... The measured cluster temperature was During the duration of the sample's existence, i.e. This is currently considered to be in the late stage of the pre-set thermal history. Samples with the second youngest absolute crystallization age were selected, and their age was set as [age value missing]. ,and > ,Will to The timeframe was determined to be the mid-term of the preset thermal history. The above steps were repeated, tracing back to older samples sequentially, until the matrix sample from the depositional period (age...). ).

[0027] Furthermore, after defining the preset thermal history periods, it is necessary to reconstruct the thermal history of each preset thermal history period. First, determine the first thermal history path to be adjusted in the initial thermal history path corresponding to the duration of the first sample. Then, use a preset kinetic model to predict the predicted temperature of the first sample based on the first thermal history path to be adjusted. Determine whether the predicted temperature of the first sample is consistent with the corresponding measured temperature. If not, adjust the first thermal history path to be adjusted until the difference between the predicted temperature and the measured temperature of the first sample is less than a preset error threshold, and determine the first adjusted thermal history path for the late preset thermal history period. If yes, directly determine the first thermal history path to be adjusted as the first target adjustment for the late preset thermal history period. The process involves: determining a second thermal history path to be adjusted from the initial thermal history path, corresponding to the time interval from the second sample to the first sample; predicting the predicted temperature of the second sample based on the second thermal history path using a preset kinetic model; determining whether the predicted temperature of the second sample matches the corresponding measured temperature; if not, adjusting the second thermal history path until the difference between the predicted temperature and the measured temperature is less than a preset error threshold, and determining the second adjusted thermal history path for the late stage of the preset thermal history; if yes, directly determining the second adjusted thermal history path as the second adjusted thermal history path for the middle stage of the preset thermal history; and integrating the determined adjusted thermal history paths to obtain the target thermal history path. Specifically, in the late stage of the preset thermal history, the initial thermal history path from t1 to the present is input into the kinetic model for forward modeling to predict its... temperature( ).like ≠ Then adjust the maximum burial depth temperature from t1 to the present until the two are matched. The thermal history path remains fixed to date, and subsequent steps will not modify this segment. The simulated and predicted thermal paths of the samples will be arranged from most recent to oldest timescales. Comparison with measured values The thermal history path to date is fixed, and subsequent steps will not modify this segment. Then, for the preset mid-term of the thermal history, keeping the path from t1 to the present unchanged, the thermal history from t2 to t1 is adjusted using only the kinetic model until the simulated predicted value for the sample is reached. Compared with measured values Fitting. Repeat the above steps, adjusting... to The thermal history during this period allows for the fitting of cluster isotopic temperatures to the matrix sample.

[0028] Furthermore, if the difference between the predicted temperature and the corresponding measured temperature of the sample during the preset thermal history period cannot be less than a preset error threshold, it is determined that the sample exhibits a thermal anomaly during the preset thermal history period. The peak temperature and duration of the thermal pulses in the thermal history path corresponding to the preset thermal history period are then adjusted until the difference between the predicted temperature and the corresponding measured temperature of the sample is less than the preset error threshold. Specifically, if conventional burial heating cannot explain the measured high temperature during a certain period... If the predicted value is obtained, a short-term thermal pulse, such as a thermal anomaly caused by magmatic activity, can be introduced into the range based on geological knowledge. By adjusting the peak temperature and duration of the thermal pulse, the predicted values ​​of all samples formed within the range can be matched with the measured values.

[0029] It's important to know that if the sample did not experience sufficiently high temperatures to trigger solid-state rearrangement of cluster isotopes after its formation, such as approximately 80-120°C for calcite and 120-150°C for dolomite, then the measured values ​​of the sample will be... The value records the formation temperature at the sample's age. The paleotemperature of the sample can be determined by directly projecting the time and temperature.

[0030] As described above, the embodiments of this application first obtain initial samples from the target marine strata, determine their phases using a preset testing method, and screen out samples to be tested for the target phases. Then, laser ablation plasma mass spectrometry is used to obtain the absolute crystallization age of the samples, while simultaneously testing their cluster isotope abundance values ​​to determine the measured temperature. Next, the target burial history of the target marine strata is obtained, and the initial thermal history path is derived based on its paleothermal gradient and depth. Then, samples for preset thermal history periods are determined based on the absolute crystallization age of the samples to be tested. A preset kinetic model is used to predict the predicted temperature of the samples for that period based on the initial thermal history path. Finally, by fitting the predicted temperature of samples for each preset thermal history period with the corresponding measured temperature, the initial thermal history path is reconstructed, and the target thermal history path is obtained. In this way, the continuous thermal history is divided into several defined time segments using U-Pb ageing, and the segmented locking strategy greatly reduces the ambiguity of traditional inversion methods.

[0031] As can be seen from the previous embodiment, this application discloses a thermal history reconstruction method based on carbonate cluster isotopes, which can improve the accuracy of predicting thermal history at various stages. Next, we will address methods such as... Figure 2 The thermal history reconstruction method based on carbonate cluster isotopes is explained in detail.

[0032] This application first selected the Cambrian B strata in Basin A as the research object, collecting calcite and dolomite samples from multiple diagenetic stages, including matrix, cement, and veins from various phases. Through hand specimen observation, thin section identification, and cathodoluminescence (CL) analysis, the diagenetic stages were finely divided based on the mineral cutting relationships and luminescence characteristics. XRD (X-ray diffraction analysis) was then used to screen single-stage samples with pure mineral composition as the subjects for further analysis.

[0033] Then, multiple diagenetic components from early to late were identified: dolomite matrix (S1), calcite cement (S2), early diagenetic dolomite veins (S3, S4), and late diagenetic calcite veins (S5, S6). In-situ U-Pb dating and cluster isotope analysis were performed on the same selected sample points to ensure that the time and temperature signals originated from the same geological fluid event; based on the proposed calibration formula, Value converted to apparent equilibrium temperature The test results are shown in Table 1: Table 1. U-Pb dating and Δ47 test results of samples from the study area

[0034] Next, the stratigraphic lithology and residual thickness of the study area were collected and organized, and the erosion volume during key tectonic periods was determined based on the contact relationships of regional unconformities. Combining paleothermal gradient data (e.g., using BasicMod software), the burial history of the target strata was inverted using stratigraphic stripping techniques to obtain a pre-defined thermal history path controlled only by burial depth, such as... Figure 3 As shown; Based on the obtained pre-defined thermal history path, forward modeling was performed using a carbonate cluster isotope exchange-diffusion model. The initial simulation time for each sample was its measured U-Pb age, and the initial temperature was the interpolated temperature along the thermal history path at that moment. The simulation strategy employed a "reverse time sequence" for piecewise fitting and locking. (1) Late thermal history locking (S6 constraint): First, the youngest U-Pb age sample, S6 (213±1 Ma), was selected. Simulations showed that, under the basic thermal history path from the Late Triassic to the present, the predicted TΔ47 of S6 fits well with the measured value (108±2°C). This indicates that the basin cooling / uplift history since the Late Triassic is reliable. The thermal history path for this time period (0-213 Ma) was locked, and no further adjustments were made in subsequent steps; (2) Mid-term thermal history retrospection and thermal anomaly identification (S5 constraint): The second youngest sample, S5 (287±5 Ma), was selected. Under the basic burial model, the paleotemperature during this period was low (approximately 100-130°C), and the model-predicted TΔ47 was much lower than the measured value (159±10°C), which could not be explained by adjusting the maximum burial depth temperature. In conjunction with the regional geological background, a short-term thermal pulse was introduced in the Early Permian (approximately 290-280 Ma). Keeping the 0-213 Ma path unchanged, the peak temperature of the thermal anomaly in the Early Permian was continuously adjusted. The results showed that when the peak temperature was set to approximately 200°C, the predicted value of the S5 sample perfectly matched the measured value. This thermal anomaly event and the Mesozoic thermal history path were identified. (3) Early thermal history reconstruction (S1-S4 constraints): The complete thermal history path including the 200°C thermal anomaly was applied to older samples (S1-S4) for validation. The results showed that the high thermal history of S3 and S4 was... The value (>140°C) is due to the superposition of solid-state rearrangement during this period of thermal anomaly; while S1 and S2, due to their very early formation, although they experienced high temperatures in the later period, the simulated predicted values ​​are consistent with the measured values ​​within the error range. Finally, through the above segmentation and verification, the sequence containing the short-duration magmatic thermal event of the Early Permian was determined. Figure 4 The detailed thermal history path shown successfully reconstructed the complex thermal evolution process of this ancient marine strata.

[0035] See Figure 5 As shown, this embodiment of the invention discloses a thermal history reconstruction device based on carbonate cluster isotopes, comprising: The sample determination module 11 is used to obtain an initial sample in the target marine strata, determine the phase of the initial sample through a preset test method, and screen and analyze the initial sample based on the phase of the initial sample to determine the test sample of the target phase. The first path acquisition module 12 is used to obtain the absolute crystallization age of the sample to be tested using laser ablation plasma mass spectrometry, test the cluster isotope abundance value of each sample to be tested, determine the corresponding measured temperature based on the cluster isotope abundance value of the sample to be tested, obtain the target burial history of the target marine strata, and obtain the initial thermal history path based on the paleothermal gradient and depth of the target marine strata according to the target burial history. The second path acquisition module 13 is used to determine the sample of the preset thermal history period based on the absolute crystallization age of the sample to be tested, predict the predicted temperature of the sample of the preset thermal history period based on the initial thermal history path using a preset kinetic model, and reconstruct the initial thermal history path by fitting the predicted temperature of the sample of each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path.

[0036] As described above, this application first obtains initial samples from the target marine strata, determines their phases using a pre-defined testing method, and selects samples for the target phases. Then, it uses laser ablation plasma mass spectrometry to obtain the absolute crystallization age of the samples and simultaneously tests their cluster isotope abundance values ​​to determine the measured temperature. Next, it obtains the target burial history of the target marine strata and obtains the initial thermal history path based on its paleothermal gradient and depth. Then, based on the absolute crystallization age of the samples, it determines the samples for the pre-defined thermal history period. Using a pre-defined kinetic model, it predicts the temperature of the samples for that period based on the initial thermal history path. Finally, by fitting the predicted temperatures of samples for each pre-defined thermal history period with the corresponding measured temperatures, it reconstructs the initial thermal history path and obtains the target thermal history path. In this way, the continuous thermal history is divided into several defined time segments using U-Pb ageing, and the segmented locking strategy significantly reduces the ambiguity of traditional inversion methods.

[0037] In some specific embodiments, the sample determination module 11 may specifically include: The result acquisition unit is used to perform a preset thin-slice identification operation and a preset cathodoluminescence operation on the initial sample to obtain the corresponding identification results and luminescence results. The phase determination unit is used to determine the phase of the initial sample based on the identification results and luminescence results.

[0038] In some specific embodiments, the sample determination module 11 may specifically include: A sample screening unit is used to screen the initial sample for a target period based on the period of the initial sample; A sample analysis unit is used to perform X-ray diffraction analysis on the initial sample of the target period; The sample judgment unit is used to determine whether the main mineral content of the initial sample is greater than a preset content threshold based on the obtained analysis results. The sample determination unit is used to determine the initial sample whose main mineral content is greater than a preset content threshold as the sample to be tested if the sample is such that the initial ...

[0039] In some specific implementations, the first path acquisition module 12 may specifically include: The data acquisition unit is used to acquire geological data of the target marine strata; wherein the geological data includes stratigraphic lithology, residual thickness, and erosion amount during preset key tectonic periods; The burial history acquisition unit is used to acquire the target burial history of the target marine strata based on the geological data of the target marine strata using preset geological software.

[0040] In some specific implementations, the second path acquisition module 13 may specifically include: Period division unit is used to divide the preset thermal history period according to the refined requirements of the target thermal history reconstruction; the preset thermal history period includes any one or more of the preset thermal history late stage, preset thermal history middle stage, and preset thermal history early stage. The first time period determination unit is used to select a first sample that meets the preset youngest condition from the test samples based on the absolute crystallization age of the test sample, and to determine the duration of the first sample as the preset late thermal history. The second time period determination unit is used to select a second sample that meets the preset second young condition from the test samples based on the absolute crystallization age of the test sample, and to determine the time period from the second sample to the first sample as the preset mid-thermal history; wherein, the absolute crystallization age of the second sample is greater than the absolute crystallization age of the first sample; The third time period determination unit is used to select a third sample from the test samples that meets the preset second young condition based on the absolute crystallization age of the test sample, and to determine the time period from the third sample to the second sample as the preset early thermal history; wherein, the absolute crystallization age of the third sample is greater than the absolute crystallization age of the second sample.

[0041] In some specific implementations, the second path acquisition module 13 may specifically include: The first thermal history path determination unit is used to determine the first thermal history path to be adjusted in the initial thermal history path that corresponds to the duration of the first sample. The first temperature prediction unit is used to predict the temperature of the first sample based on the first thermal history path to be adjusted using a preset kinetic model. The first temperature judgment unit is used to determine whether the predicted temperature of the first sample is consistent with the corresponding measured temperature. The first adjusted thermal history path determination unit is used to adjust the first thermal history path to be adjusted if not, until the difference between the predicted temperature and the measured temperature of the first sample is less than a preset error threshold, and to determine the first adjusted thermal history path of the preset late thermal history period. The second adjusted thermal history path determination unit is used to directly determine the first thermal history path to be adjusted as the first target adjusted thermal history path of the preset late thermal history if the condition is met. The second thermal history path determination unit is used to determine the second thermal history path to be adjusted in the initial thermal history path corresponding to the time period from the second sample to the first sample. The second temperature prediction unit is used to predict the temperature of the second sample based on the second thermal history path to be adjusted using a preset kinetic model. The second temperature judgment unit is used to determine whether the predicted temperature of the second sample is consistent with the corresponding measured temperature. The third adjusted thermal history path determination unit is used to adjust the second thermal history path to be adjusted if not, until the difference between the predicted temperature and the measured temperature of the second sample is less than a preset error threshold, and to determine the second adjusted thermal history path of the preset late thermal history period. The fourth adjusted thermal history path determination unit is used to directly determine the second thermal history path to be adjusted as the second adjusted thermal history path in the preset thermal history mid-term if the condition is met. The target thermal history path acquisition unit is used to integrate the determined adjusted thermal history paths to obtain the target thermal history path.

[0042] In some specific embodiments, the thermal history reconstruction device based on carbonate cluster isotopes may further include: The thermal history path adjustment module is used to determine that the sample has a thermal anomaly during the preset thermal history period if the difference between the predicted temperature and the corresponding measured temperature of the sample during the preset thermal history period cannot be less than a preset error threshold. The module then adjusts the peak temperature and duration of the thermal pulse in the thermal history path corresponding to the preset thermal history period until the difference between the predicted temperature and the corresponding measured temperature of the sample is less than the preset error threshold.

[0043] Furthermore, embodiments of this application also disclose an electronic device, Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0044] Figure 5 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the thermal history reconstruction method based on carbonate cluster isotopes disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0045] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0046] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0047] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the carbonate cluster isotope-based thermal history reconstruction method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0048] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed method for thermal history reconstruction based on carbonate cluster isotopes. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0049] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0050] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0051] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0052] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0053] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reconstructing the thermal history based on carbonate cluster isotopes, characterized in that, include: Initial samples are obtained from the target marine strata. The phase of the initial samples is determined by a preset testing method. Based on the phase of the initial samples, the initial samples are screened and analyzed to determine the test samples of the target phase. The absolute crystallization age of the sample to be tested is obtained by laser ablation plasma mass spectrometry. The cluster isotope abundance values ​​of each sample to be tested are measured. The corresponding measured temperature is determined based on the cluster isotope abundance values ​​of the sample to be tested. The target burial history of the target marine strata is obtained. The initial thermal history path is obtained based on the paleothermal gradient and depth of the target marine strata according to the target burial history. Based on the absolute crystallization age of the sample to be tested, a sample at a preset thermal history period is determined. A preset kinetic model is used to predict the predicted temperature of the sample at the preset thermal history period based on the initial thermal history path. The initial thermal history path is reconstructed by fitting the predicted temperature of the sample at each preset thermal history period with the corresponding measured temperature, and the target thermal history path is obtained.

2. The method for reconstructing the thermal history based on carbonate cluster isotopes according to claim 1, characterized in that, The step of determining the initial sample's period using a preset testing method includes: A preset thin-slice identification operation and a preset cathodic emission operation are performed on the initial sample to obtain the corresponding identification results and luminescence results; The initial sample's period is determined based on the identification and luminescence results.

3. The method for reconstructing the thermal history based on carbonate cluster isotopes according to claim 1, characterized in that, The process of screening and analyzing the initial sample based on its period to determine the target period sample includes: Based on the initial sample's period, the initial sample for the target period is selected; X-ray diffraction analysis was performed on the initial sample of the target period; Based on the obtained analysis results, determine whether the main mineral content of the initial sample is greater than a preset content threshold; If so, the initial sample with a main mineral content greater than a preset content threshold is determined as the sample to be tested.

4. The method for reconstructing the thermal history based on carbonate cluster isotopes according to claim 1, characterized in that, The acquisition of the target marine strata's burial history includes: Geological data of the target marine strata are obtained; wherein the geological data includes lithological composition, residual thickness and erosion amount during the preset key tectonic activity period; The target burial history of the target marine strata is obtained by using preset geological software based on the geological data of the target marine strata.

5. The method for reconstructing the thermal history based on carbonate cluster isotopes according to any one of claims 1 to 4, characterized in that, The sample for determining the preset thermal history period based on the absolute crystallization age of the sample to be tested includes: Based on the refined requirements of the target thermal history reconstruction, the preset thermal history period is divided; the preset thermal history period includes any one or more of the preset thermal history late stage, preset thermal history middle stage, and preset thermal history early stage. Based on the absolute crystallization age of the test sample, a first sample that meets the preset youngest condition is selected from the test samples, and the duration of the first sample is determined as the preset late thermal history. Based on the absolute crystallization age of the sample to be tested, a second sample that meets the preset second young condition is selected from the sample to be tested, and the time period from the second sample to the first sample is determined as the preset mid-thermal history; wherein, the absolute crystallization age of the second sample is greater than the absolute crystallization age of the first sample; Based on the absolute crystallization age of the test sample, a third sample that meets the preset old sample conditions is selected from the test samples, and the time period from the third sample to the second sample is determined as the preset early thermal history; wherein, the absolute crystallization age of the third sample is greater than the absolute crystallization age of the second sample.

6. The method for reconstructing the thermal history based on carbonate cluster isotopes according to claim 5, characterized in that, The method involves using a preset kinetic model to predict the sample temperature for a preset thermal history period based on the initial thermal history path, and reconstructing the initial thermal history path by fitting the predicted temperature of the sample for each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path, including: Determine the first thermal history path to be adjusted in the initial thermal history path that corresponds to the duration of the first sample; The predicted temperature of the first sample is predicted based on the first thermal history path to be adjusted using a preset kinetic model. Determine whether the predicted temperature of the first sample is consistent with the corresponding measured temperature; If not, adjust the first thermal history path to be adjusted until the difference between the predicted temperature and the measured temperature of the first sample is less than a preset error threshold, and determine the first adjusted thermal history path for the preset late thermal history period. If so, the first thermal history path to be adjusted is directly determined as the first target adjusted thermal history path in the preset late thermal history period; Determine the second thermal history path to be adjusted in the initial thermal history path that corresponds to the time period from the second sample to the first sample; The predicted temperature of the second sample is predicted based on the second thermal history path to be adjusted using a preset kinetic model. Determine whether the predicted temperature of the second sample is consistent with the corresponding measured temperature; If not, adjust the second thermal history path to be adjusted until the difference between the predicted temperature and the measured temperature of the second sample is less than the preset error threshold, and determine the second adjusted thermal history path for the preset late thermal history period. If so, the second thermal history path to be adjusted is directly determined as the second adjusted thermal history path in the preset thermal history mid-term. The target thermal history path is obtained by integrating the determined adjusted thermal history paths.

7. The method for reconstructing the thermal history based on carbonate cluster isotopes according to claim 6, characterized in that, Also includes: If the difference between the predicted temperature and the corresponding measured temperature of the sample during the preset thermal history period cannot be less than a preset error threshold, it is determined that the sample has a thermal anomaly during the preset thermal history period. The peak temperature and duration of the thermal pulse in the thermal history path corresponding to the preset thermal history period are then adjusted until the difference between the predicted temperature and the corresponding measured temperature of the sample is less than the preset error threshold.

8. A thermal history reconstruction device based on carbonate cluster isotopes, characterized in that, include: The sample determination module is used to obtain initial samples in the target marine strata, determine the phase of the initial samples through a preset testing method, and screen and analyze the initial samples based on the phase of the initial samples to determine the test samples of the target phase. The first path acquisition module is used to obtain the absolute crystallization age of the sample to be tested using laser ablation plasma mass spectrometry, test the cluster isotope abundance value of each sample to be tested, determine the corresponding measured temperature based on the cluster isotope abundance value of the sample to be tested, obtain the target burial history of the target marine strata, and obtain the initial thermal history path based on the paleothermal gradient and depth of the target marine strata according to the target burial history. The second path acquisition module is used to determine the sample of the preset thermal history period based on the absolute crystallization age of the sample to be tested, predict the predicted temperature of the sample of the preset thermal history period based on the initial thermal history path using a preset kinetic model, and reconstruct the initial thermal history path by fitting the predicted temperature of the sample of each preset thermal history period with the corresponding measured temperature to obtain the target thermal history path.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the thermal history reconstruction method based on carbonate cluster isotopes as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer programs; wherein, when the computer programs are executed by a processor, they implement the thermal history reconstruction method based on carbonate cluster isotopes as described in any one of claims 1 to 7.

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