Pumice source area geochemical analysis method and system based on zircon age and element content

Abstract

The application belongs to the technical field of earth material analysis, and discloses a volcanic ash source area geochemical analysis method and system based on zircon age and element content, which comprises the following steps: obtaining zircon age determination results and whole rock element content determination results of target volcanic ash layer samples and candidate volcanic source area samples, and establishing a volcanic ash source area analysis data set; performing kernel density estimation on the zircon age data of the candidate source area, combining the paleogeographic distance square reciprocal weight and the integral results of the target layer age range to obtain the age distance posterior contribution probability; performing standard score standardization on the whole rock element content determination results, and determining the element contribution probability based on the centroid distance; and fusing the two types of probabilities to output the source area contribution ranking. The application is used for geochemical quantitative analysis of volcanic ash source areas.

Description

Technical Field

[0001] This invention relates to the field of geomaterial analysis technology, specifically to a geochemical analysis method and system for volcanic ash source regions based on zircon age and elemental content. Background Technology

[0002] Volcanic ash layers are records of volcanic eruptions in sedimentary strata during geological history. Their provenance identification is often used for stratigraphic age constraints, analysis of volcanic activity processes, and regional tectonic evolution studies. The determination of volcanic ash source areas usually relies on geochemical analysis information such as zircon age determination results, whole-rock major and trace element content determination results obtained from target volcanic ash layer samples and candidate volcanic source area samples.

[0003] In existing geochemical analyses of volcanic ash source areas, zircon dating results are mostly used for intuitive comparisons of age spectrum morphology, while whole-rock elemental analysis results are mostly used for comparing scatter plots or elemental composition relationships. These methods can provide a basis for provenance identification, but when multiple candidate volcanic source areas have similar age distributions, overlapping elemental compositions, or significant paleogeographical differences between the target sedimentary area and candidate volcanic source areas, it is difficult to unify age evidence, distance constraints, and elemental evidence into comparable contribution probabilities.

[0004] Meanwhile, geochemical determination data of target volcanic ash layer samples and candidate volcanic source area samples often exhibit inconsistencies in sample size across different geological units, missing elemental sequences, and significant differences in the dimensions and numerical ranges of different elements. Without a unified workflow for data preprocessing, probabilistic modeling, distance priors, and elemental similarity calculations, inconsistencies in the basis for comparisons between different candidate volcanic source areas can easily arise, thereby affecting the stability and interpretability of the volcanic ash source area contribution ranking results.

[0005] Therefore, this application provides a geochemical analysis method for volcanic ash source regions based on zircon age and elemental content to solve the above-mentioned technical problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for geochemical analysis of volcanic ash source areas based on zircon age and elemental content, in order to solve the technical problems in the prior art where zircon age determination results, paleogeographic distance constraints, and whole-rock elemental content determination results are difficult to integrate under the same analytical framework, and where it is difficult to output geochemical analysis results of volcanic ash source areas with a unified comparative basis when there are missing elements, overlapping age spectra, and differences in distance between candidate source areas.

[0007] To address the aforementioned technical problems, this invention provides a geochemical analysis method for volcanic ash source regions based on zircon age and elemental content, including:

[0008] Samples of the target volcanic ash layer and multiple candidate volcanic source areas were obtained, and zircon age determination and whole-rock element content determination were performed respectively. The resulting geomaterial measurement data were used to establish a volcanic ash source area analysis dataset according to geological units. Age data of candidate volcanic source areas that meet the preset sample size conditions were retained, and element columns with missing values ​​were removed according to geological units. Kernel density estimation was performed based on zircon age data from each candidate volcanic source region to obtain the age probability density function; The paleogeographic distance and the square of the tectonic distance from the candidate volcanic source area to the target sedimentary area under the sedimentary age of the target volcanic ash layer are weighted and integrated into a prior probability. Integrate the age probability density function over the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, perform Bayesian weighting on each candidate volcanic source region to obtain the posterior contribution probability of age distance. The whole-rock element content determination results were standardized using standard fractions. The centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space was calculated, and the element contribution probability was determined based on the centroid distance. Evidence fusion is performed on the posterior contribution probability of the age distance and the contribution probability of the element according to the preset fusion weight to obtain the comprehensive contribution probability, and the geochemical analysis results of the volcanic ash source area are generated according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include the ranking of the contribution probabilities of the volcanic ash source area.

[0009] In some specific embodiments, zircon age data and whole-rock elemental content determination results of candidate volcanic source areas and target volcanic ash layers are extracted from geomaterials measurement data according to geological units, further including: Read the sample number, geological unit identifier, sample stratigraphic position, zircon age observation value, and elemental content measurement value from the Earth material measurement data; Records whose geological unit identification belongs to the candidate volcanic source area are aggregated into candidate source area data according to geological unit, and records whose sample layer belongs to the target volcanic ash layer are aggregated into target layer data. The age sample size in the candidate source region data is counted and the missing element column status is identified. Data that meet the preset sample size conditions and have the same missing element column as the target layer data are output as the volcanic ash source region data for calculation.

[0010] In some specific embodiments, kernel density estimation is performed based on zircon age data from each candidate volcanic source region, further including: For each candidate volcanic source region, the kernel function bandwidth is determined based on the zircon age sample size and age dispersion of the candidate volcanic source region. The Gaussian kernel function is applied to each zircon age observation value of the candidate volcanic source region, and normalized superposition is performed according to the zircon age sample size and the kernel function bandwidth to obtain the age probability density function. The age probability density function is sampled according to the age range of the target volcanic ash layer, and the age probability density sequence participating in the integration is output.

[0011] In some specific embodiments, based on the inverse square weight of the paleogeographic distance and tectonic distance from the candidate volcanic source region to the target sedimentary region during the depositional age of the target volcanic ash layer, the method further includes: Read the plate reconstruction location corresponding to the depositional age of the target volcanic ash layer; Calculate the paleogeographic distance between the reconstructed locations of candidate volcanic source regions and the target sedimentary region; The distance weights are obtained by performing a square inverse transformation on the paleogeographic distances; If paleogeographic distances are missing, the candidate volcanic source areas corresponding to the missing distances are removed, and the remaining candidate volcanic source areas are integrated into prior probabilities based on the inverse square weight of the distance. If there is no missing paleogeographic distance, then the prior probabilities are integrated within all candidate volcanic source regions based on the inverse square weight of the distance.

[0012] In some specific embodiments, integrating the age probability density function over the age range of the target volcanic ash layer and converting it into a likelihood value further includes: The lower and upper age limits were determined based on zircon age data from the target volcanic ash layer. Numerical integration is performed on the age probability density function of each candidate volcanic source region between the lower age limit and the upper age limit; The probability value of the candidate volcanic source region is obtained by performing a probability transformation on the integration result using the interval width between the upper age limit and the lower age limit. Based on the likelihood value and the prior probability of the same candidate volcanic source region, Bayesian weighting is performed on each candidate volcanic source region to obtain the posterior contribution probability of the age distance.

[0013] In some specific embodiments, the standard fraction standardization of the whole-rock elemental content determination results further includes: In the common missing element list of the candidate volcanic source area and the target volcanic ash layer, the element mean and element standard deviation of each element in all the samples involved in the calculation were calculated. When the element standard deviation meets the preset valid conditions, the corresponding element content measurement value is centered and scaled according to the element mean and the element standard deviation to obtain standardized element data. When the standard deviation of an element does not meet the preset valid conditions, the corresponding element column is deleted, the common missing element column is re-determined, and the updated standardized element data is output.

[0014] In some specific embodiments, the centroid distance between the target volcanic ash layer and each candidate volcanic source region in the normalized element space is calculated, and the elemental contribution probability is determined based on the centroid distance, further including: The centroid vector of the target volcanic ash layer is obtained by averaging the standardized elemental data of the target volcanic ash layer along its elemental dimensions. The candidate centroid vector is obtained by averaging the standardized elemental data of each candidate volcanic source region along its elemental dimension. The centroid distance is calculated based on the difference between the target centroid vector and the candidate centroid vector in each element dimension. Perform a reciprocal transformation on the centroid distance, and determine the element contribution probability based on the reciprocal transformation result within the entire candidate volcanic source region.

[0015] In some specific embodiments, evidence fusion is performed on the posterior contribution probability of the age distance and the contribution probability of the element according to a preset fusion weight, further including: Read the age distance weight and element weight; When the difference in the posterior contribution probability of age distance between candidate volcanic source regions meets the preset proximity condition, the element weight is set to a weight value greater than the age distance weight, and weighted fusion is performed. When the difference in the posterior contribution probability of the age distance does not meet the preset proximity condition, the preset age distance weight and element weight are used to perform weighted fusion. The weighted fusion results are probabilistically integrated to obtain the comprehensive contribution probability.

[0016] In some specific embodiments, the ranking of volcanic ash source region contribution probabilities based on the comprehensive contribution probability further includes: Candidate volcanic source regions are sorted in descending order based on their overall contribution probability. When the difference in the comprehensive contribution probability of at least two candidate volcanic source areas meets the preset parallel conditions, the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance of the at least two candidate volcanic source areas are read in sequence, and the parallel candidate volcanic source areas are sorted in a second order according to the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance. If the preset parallel conditions are still met after secondary sorting, the output includes the geochemical analysis results of the volcanic ash source area, including parallel markers and corresponding probability data.

[0017] Based on the same concept, this invention also provides a geochemical analysis system for volcanic ash source regions based on zircon age and elemental content, including: The sample measurement data processing module is configured to acquire target volcanic ash layer samples and multiple candidate volcanic source area samples, and perform zircon age determination and whole-rock element content determination respectively. The resulting earth material measurement data establishes a volcanic ash source area analysis dataset according to geological units. The age data of candidate volcanic source areas that meet the preset sample size conditions are retained, and the element columns with missing values ​​are removed according to geological units. The age spectrum analysis module is configured to perform kernel density estimation based on zircon age data from each candidate volcanic source region to obtain the age probability density function. The paleogeographic distance analysis module is configured to use the inverse square weight of the paleogeographic distance from the candidate volcanic source area to the target sedimentary area under the depositional age of the target volcanic ash layer as the basis, and integrate it into a prior probability. The source region contribution probability calculation module is configured to integrate the age probability density function within the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, Bayesian weighted processing is performed on each candidate volcanic source region to obtain the posterior contribution probability of age distance. The elemental geochemical analysis module is configured to perform standard fraction standardization on the whole-rock element content determination results, calculate the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space, and determine the element contribution probability based on the centroid distance. The analysis results output module is configured to perform evidence fusion on the posterior contribution probability of the age distance and the contribution probability of the element according to a preset fusion weight, obtain a comprehensive contribution probability, and generate geochemical analysis results of the volcanic ash source area according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include a ranking of the contribution probabilities of the volcanic ash source area.

[0018] Compared with existing technologies, its advantages are as follows: This invention discloses a geochemical analysis method and system for volcanic ash source areas based on zircon age and elemental content. It obtains zircon age determination results and whole-rock elemental content determination results of target volcanic ash layer samples and candidate volcanic source area samples, and establishes a volcanic ash source area analysis dataset according to geological units. The sample size and common missing element columns are preprocessed to ensure that the data involved in the analysis have a unified comparative basis in terms of age samples and elemental dimensions, reducing the comparison bias of candidate volcanic source areas caused by missing element columns or insufficient samples.

[0019] Kernel density estimation is performed on zircon age data from each candidate volcanic source region, and the likelihood value is obtained by integrating within the age range of the target volcanic ash layer. The age spectrum morphology is transformed into a comparable probability quantity, enabling zircon age information to participate in subsequent posterior probability calculations.

[0020] The inverse square weight of the paleogeographic and tectonic distances under the depositional age of the target volcanic ash layer is used and integrated into a priori probability. This allows the spatial constraints between candidate volcanic source areas and target depositional areas to be incorporated into the geochemical analysis process of volcanic ash source areas, avoiding source area judgment based solely on age spectrum similarity.

[0021] By performing Bayesian weighting on the likelihood value obtained by integrating the age range and the prior distance probability, the posterior contribution probability of age and distance is obtained. This makes the degree of age matching and paleogeographic distance constraints correspond in the same probability calculation link, thus providing joint age and distance evidence for the ranking of candidate volcanic source areas.

[0022] The results of whole-rock elemental content determination were standardized using standard fractions, and the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized elemental space was calculated. The elemental contents of different dimensions and numerical ranges were converted to a unified scale for comparison, so that the elemental composition similarity could be converted into elemental contribution probability.

[0023] When the standard deviation of an element does not meet the preset valid conditions, the corresponding element column is deleted, and the number of valid samples in the remaining element column is used to determine whether the candidate volcanic source region is included in the element contribution probability calculation range. This allows the element contribution probability calculation to avoid candidate source regions with no change in the element column and insufficient sample quantity, thus maintaining the feasibility of the element statistical processing link.

[0024] Evidence fusion is performed on the posterior contribution probabilities of age and distance and the contribution probabilities of elements according to the preset fusion weights to obtain the comprehensive contribution probability. This allows age evidence, distance evidence, and element evidence to be expressed in a unified output form. When the posterior contribution probabilities of age and distance are close, the role of element evidence in the fusion result is enhanced, which is helpful in distinguishing candidate volcanic source regions with overlapping age spectra.

[0025] Geochemical analysis results containing the contribution probability ranking of volcanic ash source regions are generated based on the comprehensive contribution probability. When the comprehensive contribution probabilities are close, a secondary ranking is performed based on the posterior contribution probability of age distance, elemental contribution probability, and paleogeographic distance. This ensures that the analysis results include both probability ranking and parallel processing rules, facilitating the verification and interpretation of the contribution relationships of candidate volcanic source regions. Attached Figure Description

[0026] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating some specific embodiments of the geochemical analysis method for volcanic ash source areas based on zircon age and elemental content of the present invention; Figure 2 This is a schematic diagram of the structure of the geochemical analysis system for volcanic ash source areas based on zircon age and elemental content in some specific embodiments of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms "a," "the," and "the" as used in the embodiments of this application are also intended to include the plural forms, unless the context clearly indicates otherwise, and "multiple" generally includes at least two.

[0029] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can 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 article generally indicates that the preceding and following related objects have an "or" relationship.

[0030] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0031] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0032] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0033] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0034] Reference Figure 1 Geochemical analysis methods for volcanic ash source regions based on zircon age and elemental content include: S101. Obtain the target volcanic ash layer sample and multiple candidate volcanic source area samples, and perform zircon age determination and whole-rock element content determination respectively. The resulting earth material measurement data establishes a volcanic ash source area analysis dataset according to geological units. For candidate volcanic source areas that meet the preset sample size conditions, retain the age data and remove the element columns with missing values ​​according to geological units. S102, perform kernel density estimation based on zircon age data from each candidate volcanic source region to obtain the age probability density function; S103, based on the inverse square weight of the paleogeographic distance and tectonic distance from the candidate volcanic source area to the target sedimentary area under the depositional age of the target volcanic ash layer, and integrated into the prior probability; S104, Integrate the age probability density function within the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, perform Bayesian weighted processing on each candidate volcanic source region to obtain the posterior contribution probability of age distance. S105, standardize the whole-rock element content measurement results using standard fractions, calculate the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space, and determine the element contribution probability based on the centroid distance; S106, perform evidence fusion on the posterior contribution probability of the age distance and the contribution probability of the element according to the preset fusion weight to obtain the comprehensive contribution probability, and generate the geochemical analysis results of the volcanic ash source area according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include the ranking of the contribution probabilities of the volcanic ash source area.

[0035] To provide a clearer explanation, the steps in the embodiments of the present invention are described in detail below: S101. Obtain the target volcanic ash layer sample and multiple candidate volcanic source area samples, and perform zircon age determination and whole-rock element content determination respectively. The resulting earth material measurement data establishes a volcanic ash source area analysis dataset according to geological units. For candidate volcanic source areas that meet the preset sample size conditions, retain the age data and remove the element columns with missing values ​​according to geological units. S101 further includes: Read the sample number, geological unit identifier, sample stratigraphic position, zircon age observation value, and elemental content measurement value from the Earth material measurement data; Records whose geological unit identification belongs to the candidate volcanic source area are aggregated into candidate source area data according to geological unit, and records whose sample layer belongs to the target volcanic ash layer are aggregated into target layer data. The age sample size in the candidate source region data is counted and the missing element column status is identified. Data that meet the preset sample size conditions and have the same missing element column as the target layer data are output as the volcanic ash source region data for calculation.

[0036] Specifically, in this embodiment of the invention, the geomaterial measurement data is formed from the measurement results of the target volcanic ash layer sample and the candidate volcanic source area sample, and may include sample number, geological unit identifier, sample stratigraphy, zircon age observation value, whole-rock major element content, whole-rock trace element content, and data source identifier. When reading the geomaterial measurement data, the sample stratigraphy is matched with the name of the target volcanic ash layer, and the corresponding record of the target volcanic ash layer is written into the target layer data; the geological unit identifier is matched with a pre-set list of candidate volcanic source areas, and the successfully matched record is written into the candidate source area data. The zircon age observation value in the candidate source area data forms the input for subsequent kernel density estimation, and the whole-rock elemental content measurement value forms the input for subsequent elemental standardization and centroid distance calculation.

[0037] For each candidate volcanic source region, the number of zircon age observations is counted. For example, the preset sample size condition is that the age sample size is greater than 1. When a candidate volcanic source region has only one zircon age observation, it is removed from the age probability density function calculation range, and the reason for removal is recorded. When identifying missing element columns, after grouping by geological unit, each element column is checked for null values, abnormal non-numerical values, or invalid values ​​exceeding the detection range. Element columns with missing or invalid values ​​are removed, retaining only the element columns that have valid measurements shared by the candidate volcanic source region and the target volcanic ash layer. The output volcanic ash source region data for calculation includes at least the candidate volcanic source region identifier, zircon age data of the candidate volcanic source region, zircon age data of the target volcanic ash layer, common elements without missing values, and the element content matrix corresponding to the common elements without missing values.

[0038] S102, perform kernel density estimation based on zircon age data from each candidate volcanic source region to obtain the age probability density function; S102 further includes: For each candidate volcanic source region, the kernel function bandwidth is determined based on the zircon age sample size and age dispersion of the candidate volcanic source region. The Gaussian kernel function is applied to each zircon age observation value of the candidate volcanic source region, and normalized superposition is performed according to the zircon age sample size and the kernel function bandwidth to obtain the age probability density function. The age probability density function is sampled according to the age range of the target volcanic ash layer, and the age probability density sequence participating in the integration is output.

[0039] Specifically, in this embodiment of the invention, for the first When performing kernel density estimation on zircon age data from candidate volcanic source regions, the age observation value of that candidate volcanic source region is denoted as... The age sample size is denoted as Let the kernel function bandwidth be denoted as Let the age variable be denoted as Let the age probability density function be denoted as The age probability density function can be derived from the following equivalent calculation relationship: ; in, For the first The candidate volcanic source areas are at the age value The estimated probability density at; For the first Zircon age sample size of each candidate volcanic source region; For the first Kernel function bandwidth for each candidate volcanic source region; For the first The first candidate volcanic source region Individual zircon age observations; The Gaussian kernel function; The variable is age.

[0040] The kernel function bandwidth can be formed based on the age sample size and age standard deviation. For example, a bandwidth generation rule related to the sample standard deviation and sample size can be adopted. When the age sample size is small and the age dispersion is large, the bandwidth generation rule outputs a larger bandwidth to form a smooth age probability density function. When the age sample size is large and the age is concentrated, the bandwidth generation rule outputs a smaller bandwidth to preserve the age peak position.

[0041] The age range of the target volcanic ash layer is defined by the lower and upper limits of the zircon age data for the target volcanic ash layer. When sampling the age probability density function, sampling nodes are generated between the lower and upper age limits according to a preset number of integration nodes. Each sampling node is then substituted into... The age probability density sequence participating in the integration is obtained. For example, the preset number of integration nodes can be 200 nodes; when the age range of the target volcanic ash layer is narrow, 100 nodes can also be used; when the age range is wide or there are many peaks in the age probability density function, 500 nodes can be used.

[0042] S103, based on the inverse square weight of the paleogeographic distance and tectonic distance from the candidate volcanic source area to the target sedimentary area under the depositional age of the target volcanic ash layer, and integrated into the prior probability; S103 further includes: Read the plate reconstruction location corresponding to the depositional age of the target volcanic ash layer; Calculate the paleogeographic distance between the reconstructed locations of candidate volcanic source regions and the target sedimentary region; The distance weights are obtained by performing a square inverse transformation on the paleogeographic distances; If paleogeographic distances are missing, the candidate volcanic source areas corresponding to the missing distances are removed, and the remaining candidate volcanic source areas are integrated into prior probabilities based on the inverse square weight of the distance. If there is no missing paleogeographic distance, then the prior probabilities are integrated within all candidate volcanic source regions based on the inverse square weight of the distance.

[0043] Specifically, in this embodiment of the invention, the depositional age of the target volcanic ash layer can be determined by stratigraphic age, zircon age constraints of the volcanic ash layer, or a geological timeframe. The plate reconstruction location includes the paleolatitude, paleolongitude, or planar reconstruction coordinates of the candidate volcanic source region at the depositional age of the target volcanic ash layer, and also includes the paleolatitude, paleolongitude, or planar reconstruction coordinates of the target depositional region at the same age. After reading the plate reconstruction location, a set of distance calculation inputs is formed by combining the reconstruction location of each candidate volcanic source region with the reconstruction location of the target depositional region.

[0044] Paleogeographic distance can be determined using spherical distance formulas, reconstructed planar coordinate distances, or distances output by geological software. For example, when using paleolatitude and paleolongitude, the paleolatitude and paleolongitude differences between the candidate volcanic source area and the target sedimentary area are converted into spherical distances to obtain the paleogeographic distance. When using reconstructed planar coordinates, the Euclidean distance is calculated between the reconstructed coordinates of the candidate volcanic source area and the reconstructed coordinates of the target sedimentary area to obtain the paleogeographic distance. The paleogeographic distance , used to form distance weights.

[0045] Paleogeographic distance for each candidate volcanic source region Perform a square root transformation to obtain the distance weights. Let the total number of candidate volcanic source regions be . The distance weights are integrated to obtain the first... Prior probability of candidate volcanic source regions The integrated computational relationship can be expressed as: ; in, For the first The prior probability of each candidate volcanic source region; For the first Paleogeographic distances from candidate volcanic source areas to target sedimentary areas; For the first Paleogeographic distances from candidate volcanic source areas to target sedimentary areas; This represents the total number of candidate volcanic source regions.

[0046] The prior probability and the likelihood value together form the posterior contribution probability of the age distance.

[0047] When a candidate volcanic source region lacks a reconstructed location under the target sedimentary age or paleogeographic distance calculation fails, that candidate volcanic source region is removed from the prior probability integration range, and distance weight integration is re-executed within the remaining candidate volcanic source regions. If all candidate volcanic source regions lack paleogeographic distance, the missing paleogeographic distance status is written into the anomaly record, and a temporary prior probability is generated using an equal prior method. This temporary prior probability is only used for the complete operation of the process; when subsequently outputting the volcanic ash source region contribution probability ranking, this ranking is marked as a ranking result lacking paleogeographic distance constraints.

[0048] S104, Integrate the age probability density function within the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, perform Bayesian weighted processing on each candidate volcanic source region to obtain the posterior contribution probability of age distance. S104 further includes: The lower and upper age limits were determined based on zircon age data from the target volcanic ash layer. Numerical integration is performed on the age probability density function of each candidate volcanic source region between the lower age limit and the upper age limit; The probability value of the candidate volcanic source region is obtained by performing a probability transformation on the integration result using the interval width between the upper age limit and the lower age limit. Based on the likelihood value and the prior probability of the same candidate volcanic source region, Bayesian weighting is performed on each candidate volcanic source region to obtain the posterior contribution probability of the age distance.

[0049] Specifically, in this embodiment of the invention, the lower age limit is denoted as... The upper age limit is recorded as . and The age can be determined by the minimum and maximum age values ​​of the zircon age data for the target volcanic ash layer, or by the confidence range of the zircon age data for the target volcanic ash layer. For the first... Several candidate volcanic source areas, in to Between the probability density functions of age Perform numerical integration and transform the probability using the interval width to obtain the likelihood value. The equivalent calculation relationship is as follows: ； in, For the first Likelihood values ​​for candidate volcanic source regions; The lower limit of the zircon age of the target volcanic ash layer; The upper limit of the zircon age of the target volcanic ash layer; The age probability density function is formed; This represents the integral variable.

[0050] Numerical integration can be performed using the trapezoidal integration method: the output age probability density sequence is divided into multiple small intervals based on adjacent sampling points; the mean probability density of the left and right endpoints of each interval is multiplied by the interval width; and the integral values ​​of all small intervals are summed. The likelihood value... Prior probability of output They jointly participated in Bayesian weighted processing.

[0051] Bayesian weighting was applied to each candidate volcanic source region, and the posterior contribution probability of age distance was denoted as... The equivalent calculation relationship can be expressed as: ; in, For the first The posterior contribution probability of the age distance of each candidate volcanic source region; For the first Likelihood values ​​for candidate volcanic source regions; For the first The prior probability of each candidate volcanic source region; and The first Likelihood values ​​and prior probabilities of candidate volcanic source regions; This represents the total number of candidate volcanic source regions.

[0052] Age Distance Posterior Contribution Probability Once formed, it serves as the fusion input. If the likelihood value of a candidate volcanic source region is 0, then the posterior contribution probability of the age distance of that candidate volcanic source region is 0; if the sum of the products of the likelihood values ​​and prior probabilities of all candidate volcanic source regions is 0, then an abnormal record of age range mismatch is output, and the posterior contribution probability of the age distance of all candidate volcanic source regions is set to an equal probability value to maintain the input integrity of subsequent fusion processes.

[0053] S105, standardize the whole-rock element content measurement results using standard fractions, calculate the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space, and determine the element contribution probability based on the centroid distance; S105 further includes: In the common missing element list of the candidate volcanic source area and the target volcanic ash layer, the element mean and element standard deviation of each element in all the samples involved in the calculation were calculated. When the element standard deviation meets the preset valid conditions, the corresponding element content measurement value is centered and scaled according to the element mean and the element standard deviation to obtain standardized element data. When the standard deviation of an element does not meet the preset valid conditions, the corresponding element column is deleted, the common missing element column is re-determined, and the updated standardized element data is output.

[0054] S105 further includes: The centroid vector of the target volcanic ash layer is obtained by averaging the standardized elemental data of the target volcanic ash layer along its elemental dimensions. The candidate centroid vector is obtained by averaging the standardized elemental data of each candidate volcanic source region along its elemental dimension. The centroid distance is calculated based on the difference between the target centroid vector and the candidate centroid vector in each element dimension. Perform a reciprocal transformation on the centroid distance, and determine the element contribution probability based on the reciprocal transformation result within the entire candidate volcanic source region.

[0055] Furthermore, after deleting the corresponding element columns, a new set of columns with no missing elements is determined, including: Count the number of valid samples for each candidate volcanic source region in the remaining element column; When the number of valid samples does not meet the preset elemental statistical conditions, the corresponding candidate volcanic source region is removed from the calculation range of elemental contribution probability, and the elemental mean and elemental standard deviation are recalculated. When the number of valid samples meets the preset elemental statistics conditions, the corresponding candidate volcanic source region is retained and the updated standardized elemental data is output.

[0056] Specifically, in this embodiment of the invention, let the first... The sample in the first The measured values ​​of the original element content of the element are , No. The elemental mean of the element in all samples involved in the calculation is The standard deviation of elements is Then the standardized element data It can be formed according to the following equivalent calculation relationship: ; in, For the first The first sample The standardized value of a species; For the first The first sample The original measured values ​​of the elements; For the first The arithmetic mean of all elements in the samples used for calculation; For the first The standard deviation of each element in all samples involved in the calculation.

[0057] The preset valid condition can be set to an element standard deviation greater than 0.0001; when the element content of a certain element is almost unchanged in all the samples involved in the calculation, the element has limited effect on distinguishing candidate volcanic source areas. After deleting the element column, a new common missing element column is determined.

[0058] The target centroid vector is obtained by averaging the standardized elemental data of all samples from the target volcanic ash layer along its elemental dimension. ; for the first The candidate centroid vectors are obtained by averaging the standardized elemental data of all samples from each candidate volcanic source region along their elemental dimensions. The centroid distance between the target centroid vector and the candidate centroid vector. It can be formed according to the following equivalent calculation relationship: ; in, The target volcanic ash layer centroid and the first Euclidean distance between the centroids of the candidate volcanic source regions; The centroid vector of the standardized elemental data of the target volcanic ash layer; For the first Centroid vectors of standardized elemental data for candidate volcanic source regions; The centroid vector of the target volcanic ash layer is at the th... Components in the dimension of an element; For the first The centroid vector of the candidate volcanic source region is at the... Components in the dimension of an element; The total number of elements involved in the calculation; This represents the L2 norm.

[0059] centroid distance After formation, on Perform a reciprocal transformation and determine the element contribution probability based on the result. Denote the element contribution probability as... The equivalent calculation relationship can be expressed as: ; in, For the first The contribution probability of each candidate volcanic source region based on elemental geochemical characteristics; For the first The centroid distance of each candidate volcanic source region; For the first The centroid distance of each candidate volcanic source region; This represents the total number of candidate volcanic source regions.

[0060] If a centroid distance is 0, replace it with a preset minimum distance to avoid reciprocal transformation anomalies; if all centroid distances cannot be calculated, output an insufficient element data flag and set the element contribution probability to an equal probability value or set the element weight to 0.

[0061] In this embodiment, the method further includes counting the number of valid samples for each candidate volcanic source region in the remaining element list; when the number of valid samples does not meet the preset element statistical conditions, the corresponding candidate volcanic source region is removed from the element contribution probability calculation range, and the element mean and element standard deviation are recalculated; when the number of valid samples meets the preset element statistical conditions, the corresponding candidate volcanic source region is retained and the updated standardized element data is output. The preset element statistical conditions can be set to ensure that each candidate volcanic source region has at least 2 valid samples in the remaining element list. When the number of valid samples meets the preset element statistical conditions, the standardized element data of the candidate volcanic source region is retained, and the sample mean of the candidate volcanic source region is used to form the candidate centroid vector; when the number of valid samples does not meet the preset element statistical conditions, removing the candidate volcanic source region can avoid a single sample outlier directly controlling the centroid distance. After removing the candidate volcanic source region, the element mean and element standard deviation need to be recalculated within the remaining candidate volcanic source region and the target volcanic ash layer range to ensure that the standardized element data comes from the same calculation range.

[0062] S106, perform evidence fusion on the posterior contribution probability of the age distance and the contribution probability of the element according to the preset fusion weight to obtain the comprehensive contribution probability, and generate the geochemical analysis results of the volcanic ash source area according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include the ranking of the contribution probabilities of the volcanic ash source area.

[0063] S106 further includes: Read the age distance weight and element weight; When the difference in the posterior contribution probability of age distance between candidate volcanic source regions meets the preset proximity condition, the element weight is set to a weight value greater than the age distance weight, and weighted fusion is performed. When the difference in the posterior contribution probability of the age distance does not meet the preset proximity condition, the preset age distance weight and element weight are used to perform weighted fusion. The weighted fusion results are probabilistically integrated to obtain the comprehensive contribution probability.

[0064] S106 further includes: Candidate volcanic source regions are sorted in descending order based on their overall contribution probability. When the difference in the comprehensive contribution probability of at least two candidate volcanic source areas meets the preset parallel conditions, the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance of the at least two candidate volcanic source areas are read in sequence, and the parallel candidate volcanic source areas are sorted in a second order according to the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance. If the preset parallel conditions are still met after secondary sorting, the output includes the geochemical analysis results of the volcanic ash source area, including parallel markers and corresponding probability data.

[0065] Furthermore, read the age distance weight and element weight, including: Age evidence assignment values ​​are generated based on the degree of overlap of age probability density functions among candidate volcanic source regions, and element evidence assignment values ​​are generated based on the degree of dispersion of centroid distances among candidate volcanic source regions. The age evidence allocation value and the element evidence allocation value are integrated into age distance weight and element weight, and the age distance weight and the element weight are written into the weighted fusion.

[0066] Specifically, in this embodiment of the invention, the age distance weight is denoted as... The element weight is denoted as ,and and The sum of them is 1. The first... The posterior contribution probability of the age distance of each candidate volcanic source region is: The contribution probability of an element is Overall contribution probability It can be formed according to the following equivalent calculation relationship: ; in, For the first The combined contribution probability of each candidate volcanic source region; Weighted by age distance; For element weights; and The first Age-distance posterior contribution probability and elemental contribution probability of each candidate volcanic source region; and The first Age-distance posterior contribution probability and elemental contribution probability of each candidate volcanic source region; This represents the total number of candidate volcanic source regions.

[0067] For example, when the posterior contribution probability difference of age distance between candidate volcanic source regions does not meet the preset proximity condition, 0.6 is acceptable. A value of 0.4 is acceptable; when the difference in the posterior contribution probability of age distance among multiple top-ranked candidate volcanic source regions is less than 0.1, the preset proximity condition is met. 0.4 is acceptable. A value of 0.6 can be chosen to increase the proportion of elemental contribution probability in the overall contribution probability. The above weights are exemplary implementation notes and can be set according to the geological background of the target volcanic ash layer, the degree of overlap in zircon age spectra, and the completeness of elemental data.

[0068] In this embodiment, the method further includes generating age evidence allocation values ​​based on the overlap of age probability density functions between candidate volcanic source areas, and generating element evidence allocation values ​​based on the dispersion of centroid distances between candidate volcanic source areas. The age evidence allocation values ​​and element evidence allocation values ​​are integrated into age distance weights and element weights, and these weights are then written into a weighted fusion process. The overlap of age probability density functions can be determined by the overlap area of ​​the age probability density functions of any two candidate volcanic source areas within the age range of the target volcanic ash layer. A larger overlap area between candidate volcanic source areas results in a lower age evidence allocation value; a smaller overlap area results in a higher age evidence allocation value. The dispersion of centroid distances can be determined by the standard deviation or coefficient of variation of the centroid distances between candidate volcanic source areas; a higher centroid distance dispersion results in a higher element evidence allocation value, indicating a stronger distinguishing effect of elemental data between candidate volcanic source areas. After integrating the age evidence allocation values ​​and element evidence allocation values, age distance weights and element weights are obtained, and these weights are then written into the weighted fusion process.

[0069] The output of the comprehensive contribution probability ranking can include candidate volcanic source area identifiers, posterior contribution probabilities of age distance, elemental contribution probabilities, comprehensive contribution probabilities, paleogeographic distance, and tie markers. When performing a secondary ranking of tied candidate volcanic source areas, the posterior contribution probabilities of age distance are compared first. If the difference in posterior contribution probabilities of age distance still meets the preset tie-breaking condition, then the elemental contribution probabilities are compared. If the difference in elemental contribution probabilities still meets the preset tie-breaking condition, then the paleogeographic distance is compared, and candidate volcanic source areas with smaller paleogeographic distances are ranked first. If all three conditions are met, the tie markers and corresponding probability data are output.

[0070] The above embodiments will be described below in conjunction with application scenarios.

[0071] For example, the target volcanic ash layer is the target layer. The candidate volcanic source regions include source region A, source region B, and source region C. Zircon age determination and whole-rock elemental analysis were performed on samples from the target layer, source region A, source region B, and source region C to obtain geomaterials analysis data. Source region A, source region B, source region C, and the target layer were then retrieved from this geomaterials analysis data. Zircon age observations were obtained, and the common elemental sequences of silicon, aluminum, and potassium were retained without missing values. Source regions A, B, and C all met the preset sample size conditions. Kernel density estimation was performed on the three source regions respectively, and the results were obtained in the target layer. Likelihood values ​​in the form of average probability density were obtained within the age range. For example, the likelihood values ​​for source region A, source region B, and source region C are 0.42, 0.35, and 0.18, respectively. The plate reconstructed locations were read, and paleogeographic distances were calculated. The paleogeographic distances from source region A, source region B, and source region C to the target sedimentary area are 100 km, 200 km, and 400 km, respectively. After performing a square inverse transformation on the distances and integrating them, the prior probabilities are approximately 0.762, 0.190, and 0.048. Bayesian weighting was performed on the likelihood values ​​and the prior probabilities, resulting in posterior contribution probabilities of age distance for source region A, source region B, and source region C of approximately 0.810, 0.168, and 0.022, respectively. Standardized fractions were applied to the contents of silicon, aluminum, and potassium. The centroid distances between the target centroid vector and the three candidate centroid vectors were calculated. For example, the centroid distances were 0.8, 1.6, and 2.4, respectively. Based on the inverse transformation results, the elemental contribution probabilities were determined to be approximately 0.545, 0.273, and 0.182. If the age distance weight was 0.6 and the element weight was 0.4, the combined contribution probabilities of source region A, source region B, and source region C were approximately 0.704, 0.210, and 0.086, respectively. The volcanic ash source region contribution probabilities, output according to the combined contribution probabilities, were ranked as source region A, source region B, and source region C.

[0072] For the purpose of simplicity, the method steps disclosed in the above embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0073] like Figure 2 As shown, this invention also provides a geochemical analysis system for volcanic ash source regions based on zircon age and elemental content, including: The sample measurement data processing module 201 is configured to acquire the target volcanic ash layer sample and multiple candidate volcanic source area samples, and perform zircon age determination and whole-rock element content determination respectively. The resulting earth material measurement data establishes a volcanic ash source area analysis dataset according to geological units. The age data of the candidate volcanic source areas that meet the preset sample size conditions are retained, and the element columns with missing values ​​are removed according to geological units. The age spectrum analysis module 202 is configured to perform kernel density estimation based on zircon age data from each candidate volcanic source region to obtain the age probability density function. The paleogeographic distance analysis module 203 is configured to integrate the inverse square weight of the paleogeographic distance from the candidate volcanic source area to the target sedimentary area under the depositional age of the target volcanic ash layer into a prior probability; The source region contribution probability calculation module 204 is configured to integrate the age probability density function within the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, Bayesian weighted processing is performed on each candidate volcanic source region to obtain the posterior contribution probability of age distance. The elemental geochemical analysis module 205 is configured to perform standard fraction standardization on the whole-rock element content determination results, calculate the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space, and determine the element contribution probability based on the centroid distance. The analysis result output module 206 is configured to perform evidence fusion on the posterior contribution probability of the age distance and the contribution probability of the element according to the preset fusion weight, obtain the comprehensive contribution probability, and generate the geochemical analysis result of the volcanic ash source area according to the comprehensive contribution probability. The geochemical analysis result of the volcanic ash source area includes the ranking of the contribution probability of the volcanic ash source area.

[0074] It is worth noting that although only some basic functional modules are disclosed in the embodiments of this invention, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be considered as the scope of protection of this invention being limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above devices are described separately according to their functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A geochemical analysis method for volcanic ash source regions based on zircon age and elemental content, characterized in that, include: Samples of the target volcanic ash layer and multiple candidate volcanic source areas were obtained, and zircon age determination and whole-rock element content determination were performed respectively. The resulting geomaterial measurement data were used to establish a volcanic ash source area analysis dataset according to geological units. Age data of candidate volcanic source areas that meet the preset sample size conditions were retained, and element columns with missing values ​​were removed according to geological units. Kernel density estimation was performed based on zircon age data from each candidate volcanic source region to obtain the age probability density function; The paleogeographic distance and the square of the tectonic distance from the candidate volcanic source area to the target sedimentary area under the sedimentary age of the target volcanic ash layer are weighted and integrated into a prior probability. Integrate the age probability density function over the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, perform Bayesian weighting on each candidate volcanic source region to obtain the posterior contribution probability of age distance. The whole-rock element content determination results were standardized using standard fractions. The centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space was calculated, and the element contribution probability was determined based on the centroid distance. Evidence fusion is performed on the posterior contribution probability of the age distance and the contribution probability of the element according to the preset fusion weight to obtain the comprehensive contribution probability, and the geochemical analysis results of the volcanic ash source area are generated according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include the ranking of the contribution probability of the volcanic ash source area. Among them, the age distance weight and element weight are read; When the difference in the posterior contribution probability of age distance between candidate volcanic source regions meets the preset proximity condition, the element weight is set to a weight value greater than the age distance weight, and weighted fusion is performed. When the difference in the posterior contribution probability of the age distance does not meet the preset proximity condition, the preset age distance weight and element weight are used to perform weighted fusion. The weighted fusion results are probabilistically integrated to obtain the comprehensive contribution probability; Specifically, age evidence allocation values ​​are generated based on the degree of overlap of age probability density functions among candidate volcanic source regions, and element evidence allocation values ​​are generated based on the degree of dispersion of centroid distances among candidate volcanic source regions. The age evidence allocation values ​​and element evidence allocation values ​​are integrated into age distance weights and element weights, and the age distance weights and element weights are written into a weighted fusion.

2. The geochemical analysis method for volcanic ash source regions based on zircon age and elemental content according to claim 1, characterized in that, Samples of the target volcanic ash layer and multiple candidate volcanic source areas were acquired, and zircon age determination and whole-rock elemental analysis were performed respectively. The resulting geomaterial analysis data were used to establish a volcanic ash source area analysis dataset based on geological units, which further includes: Read the sample number, geological unit identifier, sample stratigraphic position, zircon age observation value, and elemental content measurement value from the Earth material measurement data; Records whose geological unit identification belongs to the candidate volcanic source area are aggregated into candidate source area data according to geological unit, and records whose sample layer belongs to the target volcanic ash layer are aggregated into target layer data. The age sample size in the candidate source region data is counted and the missing element column status is identified. Data that meet the preset sample size conditions and have the same missing element column as the target layer data are output as the volcanic ash source region data for calculation.

3. The geochemical analysis method for volcanic ash source regions based on zircon age and elemental content according to claim 1, characterized in that, Based on zircon age data from each candidate volcanic source region, kernel density estimation was performed, further including: For each candidate volcanic source region, the kernel function bandwidth is determined based on the zircon age sample size and age dispersion of the candidate volcanic source region. The Gaussian kernel function is applied to each zircon age observation value of the candidate volcanic source region, and normalized superposition is performed according to the zircon age sample size and the kernel function bandwidth to obtain the age probability density function. The age probability density function is sampled according to the age range of the target volcanic ash layer, and the age probability density sequence participating in the integration is output.

4. The geochemical analysis method for volcanic ash source regions based on zircon age and elemental content according to claim 1, characterized in that, Based on the inverse square weight of the paleogeographic and tectonic distances from the candidate volcanic source region to the target sedimentary region during the depositional age of the target volcanic ash layer, the following further components are included: Read the plate reconstruction location corresponding to the depositional age of the target volcanic ash layer; Calculate the paleogeographic distance between the reconstructed locations of candidate volcanic source regions and the target sedimentary region; The distance weights are obtained by performing a square inverse transformation on the paleogeographic distances; If paleogeographic distances are missing, the candidate volcanic source areas corresponding to the missing distances are removed, and the remaining candidate volcanic source areas are integrated into prior probabilities based on the inverse square weight of the distance. If there is no missing paleogeographic distance, then the prior probabilities are integrated within all candidate volcanic source regions based on the inverse square weight of the distance.

5. The geochemical analysis method for volcanic ash source areas based on zircon age and elemental content according to claim 1, characterized in that, Integrating the age probability density function over the age range of the target volcanic ash layer and converting it into a likelihood value further includes: The lower and upper age limits were determined based on zircon age data from the target volcanic ash layer. Numerical integration is performed on the age probability density function of each candidate volcanic source region between the lower age limit and the upper age limit; The probability value of the candidate volcanic source region is obtained by performing a probability transformation on the integration result using the interval width between the upper age limit and the lower age limit. Based on the likelihood value and the prior probability of the same candidate volcanic source region, Bayesian weighting is performed on each candidate volcanic source region to obtain the posterior contribution probability of the age distance.

6. The geochemical analysis method for volcanic ash source regions based on zircon age and elemental content according to claim 1, characterized in that, The results of whole-rock elemental content determination were standardized using standard fractions, which further included: In the common missing element list of the candidate volcanic source area and the target volcanic ash layer, the element mean and element standard deviation of each element in all the samples involved in the calculation were calculated. When the element standard deviation meets the preset valid conditions, the corresponding element content measurement value is centered and scaled according to the element mean and the element standard deviation to obtain standardized element data. When the standard deviation of an element does not meet the preset valid conditions, the corresponding element column is deleted, the common missing element column is re-determined, and the updated standardized element data is output.

7. The geochemical analysis method for volcanic ash source areas based on zircon age and elemental content according to claim 1, characterized in that, Calculating the centroid distance between the target volcanic ash layer and each candidate volcanic source region in the normalized element space, and determining the elemental contribution probability based on the centroid distance, further includes: The centroid vector of the target volcanic ash layer is obtained by averaging the standardized elemental data of the target volcanic ash layer along its elemental dimensions. The candidate centroid vector is obtained by averaging the standardized elemental data of each candidate volcanic source region along its elemental dimension. The centroid distance is calculated based on the difference between the target centroid vector and the candidate centroid vector in each element dimension. Perform a reciprocal transformation on the centroid distance, and determine the element contribution probability based on the reciprocal transformation result within the entire candidate volcanic source region.

8. The geochemical analysis method for volcanic ash source areas based on zircon age and elemental content according to claim 1, characterized in that, The generation of geochemical analysis results for the volcanic ash source region further includes: Candidate volcanic source regions are sorted in descending order based on their overall contribution probability. When the difference in the comprehensive contribution probability of at least two candidate volcanic source areas meets the preset parallel conditions, the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance of the at least two candidate volcanic source areas are read in sequence, and the parallel candidate volcanic source areas are sorted in a second order according to the posterior contribution probability of age distance, the element contribution probability, and the paleogeographic distance. If the preset parallel conditions are still met after secondary sorting, the output includes the geochemical analysis results of the volcanic ash source area, including parallel markers and corresponding probability data.

9. A geochemical analysis system for volcanic ash source regions based on zircon age and elemental content, characterized in that, include: The sample measurement data processing module is configured to acquire target volcanic ash layer samples and multiple candidate volcanic source area samples, and perform zircon age determination and whole-rock element content determination respectively. The resulting earth material measurement data establishes a volcanic ash source area analysis dataset according to geological units. The age data of candidate volcanic source areas that meet the preset sample size conditions are retained, and the element columns with missing values ​​are removed according to geological units. The age spectrum analysis module is configured to perform kernel density estimation based on zircon age data from each candidate volcanic source region to obtain the age probability density function. The paleogeographic distance analysis module is configured to use the inverse square weight of the paleogeographic distance from the candidate volcanic source area to the target sedimentary area under the depositional age of the target volcanic ash layer as the basis, and integrate it into a prior probability. The source region contribution probability calculation module is configured to integrate the age probability density function within the age range of the target volcanic ash layer and convert it into a likelihood value. Based on the likelihood value and the prior probability, Bayesian weighted processing is performed on each candidate volcanic source region to obtain the posterior contribution probability of age distance. The elemental geochemical analysis module is configured to perform standard fraction standardization on the whole-rock element content determination results, calculate the centroid distance between the target volcanic ash layer and each candidate volcanic source area in the standardized element space, and determine the element contribution probability based on the centroid distance. The analysis results output module is configured to perform evidence fusion on the posterior contribution probability of the age distance and the contribution probability of the element according to a preset fusion weight, to obtain a comprehensive contribution probability, and generate geochemical analysis results of the volcanic ash source area according to the comprehensive contribution probability. The geochemical analysis results of the volcanic ash source area include a ranking of the contribution probabilities of the volcanic ash source area. Among them, the age distance weight and element weight are read; When the difference in the posterior contribution probability of age distance between candidate volcanic source regions meets the preset proximity condition, the element weight is set to a weight value greater than the age distance weight, and weighted fusion is performed. When the difference in the posterior contribution probability of the age distance does not meet the preset proximity condition, the preset age distance weight and element weight are used to perform weighted fusion. The weighted fusion results are probabilistically integrated to obtain the comprehensive contribution probability; Specifically, age evidence allocation values ​​are generated based on the degree of overlap of age probability density functions among candidate volcanic source regions, and element evidence allocation values ​​are generated based on the degree of dispersion of centroid distances among candidate volcanic source regions. The age evidence allocation values ​​and element evidence allocation values ​​are integrated into age distance weights and element weights, and the age distance weights and element weights are written into a weighted fusion.

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