A method for modeling and evaluating geological parameters of residual accumulation type scandium mineralization probability

Abstract

The present application relates to the technical field of mineral exploration, and discloses a kind of residual accumulation type scandium ore mineralization probability Geological parameter modeling evaluation method, comprising: determining multiple indexes related to scandium ore mineralization, constructing the estimation model of index standard determination submodel, index correlation submodel, mineralization stage judgment submodel;The mineralization process is divided into three stages of material supply, element release and element enrichment, the standard rule of each index is defined by submodel, basic coefficient and strong correlation coefficient, and the contribution degree benchmark value of each stage is determined;Calculate the mineralization probability of each stage, and the comprehensive mineralization probability P=P 阶1 ×P 阶2 ×P 阶3 , wherein P 阶1 , P 阶2 And P 阶3 It is the mineralization probability of three stages;According to the comprehensive mineralization probability, the potential classification is carried out, and the mineralization probability of specified target area is judged.According to the above technical scheme, the basic restriction effect of the previous stage on the next stage can be reflected in the estimation of scandium ore mineralization probability, and the synergistic value between the related multiple indexes can be highlighted.

Description

Technical Field

[0001] This invention relates to the field of mineral exploration technology, and more specifically, to a geological parameter modeling and evaluation method for the mineralization probability of residual slope scandium deposits. Background Technology

[0002] Scandium is a strategic mineral in my country. With the surge in domestic demand for scandium resources, residual slope scandium deposits have gradually become a key focus of exploration and development. However, the mineralization process of residual slope scandium deposits is controlled by a combination of multiple factors, including geological structure, parent rock properties, weathering intensity, geochemistry, and geophysics, exhibiting significant characteristics such as "surface weathering enrichment, strong carrier dependence, and complex index correlations." Specifically, the mineralization stage of residual slope scandium deposits involves "material supply (exposed scandium-rich parent rock) → element release (weathering and decomposition of scandium-bearing minerals) → element enrichment (Sc)." 3+ The process of "carrier adsorption and fixation" is a progressive one, where each stage is the foundation for the next, and the constraints between stages directly affect the probability of mineralization.

[0003] Early exploration of residual slope-type scandium deposits relied heavily on single indicators, such as defining target areas solely based on parent rock TiO2 content or whole-rock Sc grade. This neglected the synergistic effects between indicators at different stages of mineralization. For example, in some areas, although the initial scandium abundance in the parent rock met the standards, the deep burial of the parent rock due to a compressional tectonic environment or insufficient weathering intensity resulted in low Sc content. 3+ Without effective release, it is ultimately difficult to form an industrial ore deposit. In recent years, with the upgrading of exploration technology, technologies such as ground-penetrating radar, high-precision magnetic surveying, and geochemical profile analysis have been able to accurately measure indicators such as fault zone density, magnetic susceptibility, and the correlation between Sc and Al2O3, providing data support for the quantitative integration of multi-dimensional indicators. Multi-indicator comprehensive analysis methods have been gradually applied to scandium exploration, but they mostly adopt the simple logic of "indicator superposition" without considering the stages of mineralization and failing to conform to the staged mineralization law of residual slope scandium deposits, which follows the mineralization period of "material supply → element release → element enrichment." At the same time, existing technologies lack sufficient quantification of the correlation between indicators, such as... Distinguishing the synergistic contributions of strongly correlated indicators such as "tectonic environment and parent rock exposure" and "magnetic susceptibility and scandium loading in limonite," and calculating whole-rock Sc grade (representing "element enrichment") and parent rock type (representing "material supply") with equal weight, ignores the objective logic that "without material supply, subsequent enrichment is impossible." This leads to significant deviations between estimated results and actual mineralization. For example, some target areas were classified as "high-potential" despite failing to meet early-stage indicators, resulting in wasted exploration resources. Furthermore, existing technologies often fail to clearly define the core constraints on mineralization probability, such as not including "industrial boundary grade (whole-rock Sc ≥ 50 × 10⁻⁶)." -6The key threshold is that some methods still use other indicators to make the mineralization probability high when the whole rock Sc does not meet the standard, which is out of touch with the actual requirement that "there is no development value without industrial grade". At the same time, the transmission relationship between mineralization stages is ignored. For example, if the probability of the material supply stage is too low, even if the element release stage is optimal, it will not be able to form an effective deposit. This leads to fuzzy calculation boundary conditions and the estimation results lack practical guiding significance.

[0004] Therefore, a quantitative integration technology for multi-dimensional indicators is needed to achieve effective estimation of the mineralization probability of residual slope scandium deposits based on indicator combinations and stage division. Summary of the Invention

[0005] To achieve the above objectives, this application provides a geological parameter modeling and evaluation method for the mineralization probability of residual slope-type scandium deposits, comprising the following steps:

[0006] To determine the indices related to the mineralization conditions of residual-colluvial scandium deposits, a probability estimation model for residual-colluvial scandium deposits was constructed. These indices include: fault zone density, tectonic setting, parent rock type + TiO2, weathering intensity index, whole-rock Sc, correlation between Sc and Al2O3, magnetic susceptibility, and polarizability. The input parameters of the probability estimation model are these indices. The output of the model is the comprehensive mineralization probability P, which is determined based on the mineralization probability P0 of each mineralization stage. 阶 Calculations show that the mineralization period can be divided into three stages: material supply, element release, and element enrichment; the mineralization probability P of each stage is calculated. 阶 The determination is made based on indicators related to the mineralization conditions of residual slope-type scandium deposits;

[0007] Obtain mineralization characteristic indicators of residual slope-type scandium deposits in a specified target area;

[0008] Load the residual slope scandium mineralization probability estimation model, input the mineralization characteristic index of the residual slope scandium, and calculate the comprehensive mineralization probability;

[0009] Obtain comprehensive mineralization probability and potential classification to determine the mineralization probability of residual slope-type scandium deposits in a specified target area.

[0010] The mineralization probability estimation model includes a sub-model for determining index standards, a sub-model for index correlation, and a sub-model for judging mineralization stages.

[0011] The indicator standard determination sub-model is used to define the compliance rules for each indicator and calculate the compliance value S for each indicator;

[0012] The indicator correlation sub-model is used to define indicator combinations to reflect the synergistic relationship between indicators, classify the importance of each indicator, and define the basic coefficient L for each indicator.b And strong correlation coefficient L r The synergistic relationship refers to the mutually supportive effect that occurs during the mineralization process when two or more indicators within a combination of indicators meet the target; this mutually supportive effect is quantified by the strong correlation coefficient L between the indicators. r This is reflected in the strong correlation coefficient L of the indicators. r The value is greater than the basic coefficient L b The value;

[0013] The mineralization stage determination sub-model is used to determine the stage contribution benchmark value V for different mineralization stages. s The method for calculating the total contribution V of the definition stage; the mineralization stage corresponds to different indicative indicators.

[0014] The methods for calculating the overall mineralization probability P include:

[0015] Calculate the mineralization probability P for each mineralization stage. 阶 The calculation method is as follows: P 阶 =V / V s Where V is the sum of the stage contributions of each mineralization stage, and Vs is the baseline value of the stage contribution; if P 阶 If P ≥ 1.0, then P 阶 =1.0;

[0016] The overall mineralization probability P is calculated as follows:

[0017] P=P 阶1 ×P 阶2 ×P 阶3 , where P 阶1 For the mineralization probability during the material supply stage, P 阶2 For the ore formation probability during the element release phase, P 阶3 This represents the mineralization probability during the element enrichment stage.

[0018] The method for calculating the sum of stage contributions V for each mineralization stage is as follows:

[0019] V= ,

[0020] Where V represents the total contribution of each stage, i is the indicator number, and n is the number of indicative indicators. This represents the target value for indicator number i. Let be the coefficient of this indicator, and ,in, Based on the coefficient, This is a strong correlation coefficient.

[0021] Among them, the basic coefficient L bIt is a parameter that measures the contribution of a single indicator to mineralization when it acts independently, and is used to calculate the stage contribution when the combination of indicators does not meet all the standards.

[0022] Strong correlation coefficient L r Used to reflect the contribution of multiple related indicators to mineralization when they work synergistically, and used to calculate the stage contribution when all indicators meet the standards.

[0023] Furthermore, the results of classifying the importance of each indicator include core indicators, important indicators, and auxiliary indicators;

[0024] The core indicators include: parent rock type + TiO2, whole rock Sc; important indicators include: tectonic environment, weathering intensity index, correlation between Sc and Al2O3 and magnetic susceptibility; and auxiliary indicators include: fault zone density and polarizability.

[0025] Different indicative indicators correspond to different mineralization stages:

[0026] Indicative indicators of the material supply stage include: tectonic environment, parent rock type, and TiO2.

[0027] Indicative indicators of the element release phase include: fault zone density and weathering intensity index;

[0028] Indicative indicators of element enrichment stages include: whole-rock Sc, correlation between Sc and Al2O3, magnetic susceptibility, and polarizability.

[0029] Furthermore, the residual slope type scandium mineralization probability estimation model also supports potential classification based on comprehensive mineralization probability, which includes: high potential, medium potential and low potential.

[0030] Furthermore, the residual slope scandium mineralization probability estimation model uses dimension abbreviations to encode indicators related to the mineralization conditions of residual slope scandium, including:

[0031] GZ-01: Fault zone density, GZ-02: Tectonic environment, FY-01: Parent rock type + TiO2, FY-02: Weathering intensity index, DH-01: Whole rock Sc, DH-02: Correlation between Sc and Al2O3, WL-01: Magnetic susceptibility, WL-02: Polarizability.

[0032] According to this invention, following the phased mineralization logic of residual slope scandium deposits—"material supply → element release → element enrichment"—eight core indicators are categorized by stage. The calculation method of the comprehensive mineralization probability reflects the fundamental constraint of the previous stage on the next stage. Simultaneously, based on data from typical domestic deposits, a combination of strongly correlated indicators (structural synergy combination, parent rock-weathering linkage combination, etc.) is constructed, and coefficient standards for full compliance and single compliance are set to highlight the synergistic value of multiple indicators, where 1+1 is greater than 2. Verified by typical deposits in Guizhou, Yunnan, Guangxi, and other regions, this design can improve the estimation accuracy of the mineralization probability of residual slope scandium deposits. Attached Figure Description

[0033] Figure 1 This is a schematic diagram illustrating the steps of a geological parameter modeling and evaluation method for the mineralization probability of residual slope scandium deposits provided in an embodiment of the present invention. Detailed Implementation

[0034] Residual slope scandium deposits are formed when scandium-rich basalt undergoes surface weathering, releasing scandium through the destruction of the primary mineral lattice. Scandium then accumulates in the residual slope layer via ion exchange adsorption from clay minerals and co-precipitation with limonite colloids, resulting in a weathering crust-type scandium deposit. This invention, targeting the characteristics of typical residual slope scandium deposits in China, categorizes multiple core indicators into stages, demonstrating the fundamental constraint of each stage on the next. Furthermore, it proposes the concept of a combination of strongly correlated indicators, designing a dual-parameter system of "basic coefficient + strong correlation coefficient": when all indicators within the combination meet the target, a higher strong correlation coefficient is used to calculate the contribution, accurately quantifying the synergistic effect.

[0035] The specific implementation of the present invention will now be described in detail with reference to the accompanying drawings.

[0036] Figure 1 The method and steps for estimating the mineralization probability of residual slope-type scandium deposits are provided, including:

[0037] Step S100: Determine the indicators related to the mineralization conditions of residual slope scandium deposits and construct a mineralization probability estimation model for residual slope scandium deposits;

[0038] The mineralization of residual slope-type scandium deposits is controlled by the coupling of four types of geological conditions: geological structural features, parent rock and weathering features, geochemical features, and geophysical features. These four types of geological conditions include different parameters, as detailed below:

[0039] 1) Geological structural features include parameters such as fault zone density and tectonic environment;

[0040] Fault zone density: Fault zones generate fissures through tectonic stress, increasing the specific surface area of ​​the parent rock, improving the permeability of weathering fluids (precipitation, CO2, groundwater, etc.), and accelerating the hydrolysis of scandium-bearing minerals. When the density is insufficient, the parent rock has a massive structure, weathering is limited to the shallow surface, and scandium is difficult to release. Therefore, a fault zone density greater than or equal to a specified threshold (such as 1.0 faults / square kilometer) is one of the conditions for judging the probability of mineralization.

[0041] The tectonic environment is an intraplate extensional environment: Tectonic environments include intraplate extensional environments and high-stress environments. The extensional environment causes crustal uplift, exposing deep scandium-rich basalts to the surface weathering zone, providing material carriers for subsequent weathering and enrichment processes. Although the high-stress environment may expose the parent rock due to thrusting, it easily destroys the interlayer adsorption structure of clay minerals, and the rapid circulation of groundwater caused by tectonic activity easily leads to the migration and loss of scandium. Therefore, the intraplate extensional environment is one of the conditions for judging the probability of mineralization.

[0042] 2) Parent rock and weathering characteristics include parameters: parent rock TiO2 content and weathering intensity index;

[0043] Parent rock TiO2 content: Basalt originates from partial melting of the mantle, scandium (Sc 3+ ) and titanium (Ti 4+ Due to similar geochemical properties (close ionic radii), they are synergistically enriched in dark minerals such as pyroxene and ilmenite during magma crystallization; in most cases, TiO2 ≥ 2% indicates that the initial scandium abundance of the parent rock meets the standard (≥ 30 × 10⁻⁶). -6 This provides a material basis for subsequent enrichment; therefore, the TiO2 content of the parent rock is one of the conditions for judging the probability of mineralization.

[0044] The weathering intensity index indicates the weathering stage. If the weathering intensity index is ≥0.6, meaning the ratio of clay minerals to parent rock debris is ≥0.6, it indicates that the parent rock has entered a stage of intense weathering, and the crystal lattice of scandium-bearing minerals is completely destroyed. 3+ Large amounts of scandium are released and enter the fluid phase; the parent rock is mainly subjected to physical weathering with only slight chemical decomposition. Scandium remains trapped in the primary mineral lattice and cannot participate in the subsequent adsorption and enrichment process. Therefore, a weathering intensity index greater than a specified threshold is one of the conditions for judging the probability of mineralization.

[0045] 3) Geochemical characteristics include whole-rock Sc conditions and the positive correlation coefficient between Sc and Al2O3;

[0046] The whole-rock Sc condition is the boundary value for industrial mining of residual slope-type scandium ore. If it is below the threshold, even if other conditions meet the standards, the economic threshold for mineral processing and recovery cannot be met, and it has no industrial value. Generally, the whole-rock Sc requirement is ≥50×10⁻⁶. -6 ;

[0047] The positive correlation between Sc and Al2O3: Al2O3 mainly originates from weathered clay minerals (kaolinite, montmorillonite). The high correlation between Sc and Al2O3 indicates that Sc... 3+ Stable adsorption within the clay mineral layers via ion exchange; when the correlation is insufficient, it indicates that Sc 3+ If not effectively fixed by clay, it is easily lost through horizontal migration or vertical leaching with groundwater; therefore, a positive correlation coefficient between Sc and Al2O3 greater than a specified threshold (e.g., ≥0.6) is one of the conditions for judging the probability of mineralization.

[0048] 4) Geophysical characteristics include magnetic susceptibility and polarizability;

[0049] The magnetic susceptibility in residual colluvial deposits is mainly influenced by limonite (a scandium-loaded mineral containing weakly magnetic Fe). 3+ The magnetic susceptibility is influenced by both the magnetic properties of the parent rock and residual magnetic minerals; the magnetic susceptibility is ≥300×10⁻⁶. -5 SI can comprehensively indicate the enrichment of magnetic scandium-loaded minerals and related associated magnetic minerals, indirectly reflecting the Sc 3+ The associated potential; below the threshold, the content of magnetic scandium-loaded minerals such as limonite is insufficient, and the probability of scandium enrichment is significantly reduced; therefore, magnetic susceptibility ≥300×10 -5 SI is one of the criteria for judging the probability of mineralization.

[0050] Clay minerals (with interlayer ionic conductivity) readily generate surface polarization effects, while limonite (with weak electronic conductivity) can generate electronic polarization effects; both contribute to the polarization signal. A polarizability higher than a threshold (e.g., 3%) indicates a sufficient total amount of scandium-loaded minerals (clay and limonite), providing a stable carrier basis for scandium adsorption. When the polarizability is lower than the threshold, scandium-loaded minerals are scarce, and scandium is difficult to effectively accumulate. Therefore, a polarizability ≥3% is one of the conditions for judging the probability of mineralization.

[0051] Once the parameters related to the mineralization probability judgment conditions are determined, the parameters of the mineralization probability judgment conditions can be used as input parameters to construct a mineralization probability estimation model for residual slope scandium deposits.

[0052] The scandium ore mineralization probability estimation model includes an indicator standard determination sub-model, an indicator correlation sub-model, and a mineralization stage judgment sub-model. The specific construction process is as follows:

[0053] Step S101: The indicator standard determination sub-model is used to define the compliance rules for each indicator. The construction method is as follows:

[0054] 1) Eight measurable units were extracted from the four types of geological conditions, namely, the density of fault zones and tectonic environment in the geological structure category, the parent rock type + TiO2 and weathering intensity index in the parent rock and weathering category, the whole rock Sc and the correlation between Sc and Al2O3 in the geochemical category, and the magnetic susceptibility and polarizability in the geophysical category.

[0055] For ease of calculation, the measurable units are coded using the abbreviation of dimension number. The eight measurable units are coded as follows: GZ-01: fault zone density, GZ-02: tectonic environment, FY-01: parent rock type + TiO2, FY-02: weathering intensity index, DH-01: whole rock Sc, DH-02: correlation between Sc and Al2O3, WL-01: magnetic susceptibility, WL-02: polarizability.

[0056] 2) Define the criteria for measurable units to achieve the quantification of measurable unit indicators. When the value of each indicator meets the conditions, the indicator compliance value S is assigned to 1, otherwise it is assigned to 0.

[0057] The compliance rules are shown in Table 1:

[0058] Table 1 Standardization Comparison Table of Indicators

[0059]

[0060] In the indicator standard determination sub-model, the indicator compliance value S of each indicator is obtained based on the indicator values ​​of the eight measurable units input.

[0061] Step S102: Construct an indicator association sub-model; the indicator association sub-model defines indicator combinations to reflect the synergistic relationship between indicators, and classifies the importance of each indicator (i.e., measurable unit);

[0062] Synergistic relationships refer to the mutually reinforcing effects exhibited during mineralization when two or more indicators within a synergistic combination meet the required standards. When all synergistic indicators meet the standards, the combined effect of the two indicators on mineralization determination reaches a synergistic effect greater than the sum of its parts (1+1>2). Specifically, synergistic relationships reflect tectonic state, parent rock weathering state, scandium grade-adsorption capacity, and magnetic-polarization degree. Therefore, synergistic indicator combinations can be defined as: tectonic synergistic combinations, parent rock-weathering linkage combinations, scandium grade-adsorption correlation combinations, and magnetic-polarization synergistic combinations.

[0063] The specific indicators and their functions included in each indicator combination are shown in Table 2:

[0064] Table 2 Indicator Combinations

[0065]

[0066] Furthermore, the mutually beneficial effect can be seen through the basic coefficient L. b And strong correlation coefficient L r This is reflected in the strong correlation coefficient L of an indicator. r The value is greater than the basic coefficient L b The value of the basic coefficient L; b It is a parameter that measures the contribution of a single indicator to mineralization when acting independently; the strong correlation coefficient L rThis is used to reflect the contribution of multiple related indicators to mineralization through synergistic effects. In this step, the basic coefficient L for each indicator is defined. b And strong correlation coefficient L r The "basic coefficient + strong correlation coefficient" dual-parameter system designed in this step uses a higher strong correlation coefficient to calculate the contribution when all indicators within the combination meet the target, accurately quantifying the synergistic effect and reflecting the effectiveness of synergistic assistance.

[0067] The indicator correlation sub-model further categorizes indicators into core indicators, important indicators, and auxiliary indicators based on their importance. For each category, different influence coefficients are defined according to their importance to clarify the core constraint boundaries and enhance practical guidance value. For example, whole-rock Sc, which can represent the industrial boundary grade, is listed as a core indicator. If this indicator fails to meet the standard, the contribution of the element enrichment stage is directly reduced to avoid the situation of "being judged as having high potential but having no industrial value".

[0068] The classification of indicators and the definitions of their basic coefficients and strong correlation coefficients are shown in Table 3.

[0069] Table 3. Indicator Classification and Calculation Coefficients

[0070]

[0071] Step S103: Construct a sub-model for judging the mineralization stage. The sub-model for judging the mineralization stage is used to determine the calculation method of the stage contribution.

[0072] When calculating the contribution of a stage, first determine whether multiple indicators within the same indicator combination in Table 2 simultaneously meet the criteria. If they do, select the strong correlation coefficient L of the indicators. r To calculate the contribution of this indicator to the mineralization stage; if the criteria for meeting the standard are not met simultaneously, then the basic coefficient L of this indicator is selected. b The contribution of each indicator to the mineralization stage is calculated; finally, the contribution of each indicator is summed to obtain the stage contribution.

[0073] For example, if both GZ-01 and GZ-02 indicators for a certain target area meet the standards, the coefficient for GZ-01 is set to 0.7, and the coefficient for GZ-02 is set to 1.1; if FY-01 meets the standard but FY-02 does not, then the coefficient for FY-01 is set to 1.2, and the coefficient for FY-02 is set to... =0; DH-01 and DH-02, WL-01 and WL-02 all meet the standards, and the coefficients of these four parameters are 1.3, 1.1, 1.1 and 0.7 respectively.

[0074] The calculation method for stage contribution is expressed as follows:

[0075] V= ,

[0076] Where V represents the stage contribution, i is the indicator number, and n is the number of indicative indicators. This represents the target value for indicator number i. Let be the coefficient of this indicator, and ,in, Based on the coefficient, This is a strong correlation coefficient.

[0077] Among them, the number of indicative indicators is a necessary reference for judging the mineralization stage of residual slope scandium deposits.

[0078] In this invention, the mineralization stage of residual slope scandium can be divided into three stages: material supply, element release, and element enrichment. Different mineralization stages have different indicative indicators. Based on the stage contribution calculated from the different indicative indicators, the mineralization stage of residual slope scandium in the target area can be determined.

[0079] The relationship between the benchmark values ​​of the contribution of the mineralization stage, indicative indicators, and judgment stage is defined in Table 4:

[0080] Table 4. Indicative Indicators and Contribution Benchmark Values ​​for Different Mineralization Stages

[0081]

[0082] In the example above, the stage contribution V(material supply) of the target area material supply stage is 1.1 + 1.2 = 2.3, the stage contribution V(element release) of the element release stage is 0.7 + 0 = 0.7, and the stage contribution V(element enrichment) of the element enrichment stage is 1.3 + 1.1 + 1.1 + 0.7 = 4.2.

[0083] Step S104: Calculate the stage mineralization probability and the comprehensive mineralization probability, where the comprehensive mineralization probability is the output result of the residual slope type scandium mineralization probability estimation model;

[0084] 1) First, calculate the stage contribution V and the stage mineralization probability P for each stage. 阶 The calculation method is as follows:

[0085] P 阶 =V / V s Where V represents the total actual contribution of each stage, V s This serves as the baseline value for the contribution of a given stage.

[0086] If P 阶 If P ≥ 1.0, then P 阶 =1.0;

[0087] 2) Next, the comprehensive mineralization probability P is calculated, and the probability values ​​are classified.

[0088] The calculation method is: P = P 阶1 ×P 阶2 ×P 阶3 , where P 阶1 For the mineralization probability during the material supply stage, P 阶2 For the ore formation probability during the element release phase, P 阶3 This represents the mineralization probability during the element enrichment stage.

[0089] It is evident that the calculation of the overall mineralization probability P employs the multiplication of the stage probabilities across three stages, reflecting the stage division constraint. In practical applications, if P... 阶1 If the value is less than 0.5, even if all indicators are excellent, the impact of the deficiency should be considered to make the estimation results more consistent with the actual mineralization process. Compared with the existing "indiscriminate superposition" method, this method can effectively reduce logical errors.

[0090] Furthermore, the overall mineralization probability is classified into potential levels, including:

[0091] P ≥ 0.7 (high potential), 0.5 ≤ P < 0.7 (medium potential), P < 0.5 (low potential).

[0092] In a single mineralization practice, if the exploration area is a favorable region with mineralization potential, the P values ​​in the three stages... 阶 All are above 0.7.

[0093] Step S110: Obtain the mineralization characteristic indicators of residual slope deposits in the exploration area; the mineralization characteristic indicators of residual slope deposits are the corresponding parameters of geological structural characteristics, parent rock and weathering characteristics, geochemical characteristics and geophysical characteristics, namely: fault zone density, tectonic environment, parent rock type + TiO2, weathering intensity index, whole rock Sc, correlation between Sc and Al2O3, magnetic susceptibility and polarizability.

[0094] For example, the indicators for a certain target area include: a fault zone density of 1.2 faults / km², an intraplate extensional tectonic environment, a parent rock of basalt with TiO₂ ≥ 2.5%, a weathering intensity index of 0.8, and a whole-rock Sc of 68 × 10⁻⁶. -6 The correlation coefficient between Sc and Al2O3 is 0.6, and the magnetic susceptibility is 320 × 10⁻⁶. -5 SI, polarizability is 2.8%.

[0095] Step S120: Load the residual slope scandium mineralization probability estimation model and calculate the stage mineralization probability based on the residual slope scandium mineralization characteristic indicators;

[0096] The probability estimation model for residual slope-type scandium deposits includes a sub-model for determining index standards, a sub-model for index correlation, and a sub-model for judging the mineralization stage.

[0097] 1) In the indicator standard determination sub-model, determine the indicator number of the target area and the achievement status of the indicator, as shown in Table 5:

[0098] Table 5. Explanation of Indicator Compliance Rules

[0099]

[0100] 2) The indicator classification is determined in the indicator association sub-model, as shown in Table 6:

[0101] Table 6 Definition of Correlation Coefficients of Indicators

[0102]

[0103] 3) Calculate the probability P for each stage in the stage judgment sub-model. 阶 And the overall mineralization probability P;

[0104] Specifically,

[0105] The indicative indicators for the material supply stage are: GZ-02 and FY-01.

[0106] Then P 阶1 = (1 × 1.1 + 1 × 1.3) ÷ 2.2 = 1.09, value 1.0;

[0107] The indicative indicators for the element release phase are: GZ-01 and FY-02.

[0108] Then P 阶2 = (1 × 0.7 + 1 × 1.1) ÷ 1.6 = 1.13, value 1.0;

[0109] The indicative indicators of the element enrichment stage are: DH-01, DH-02, WL-01, and WL-02.

[0110] Then P 阶3 = (1×1.3+1×1.1+1×1.0+0×0.6)÷3.8=0.89.

[0111] Overall mineralization probability P=P 阶1 ×P 阶2 ×P 阶3 =0.89, meaning the overall mineralization probability of this target area is 0.89.

[0112] Step S130: Obtain the comprehensive mineralization probability and potential classification to determine the mineralization probability of residual slope type scandium deposits.

[0113] Based on the comprehensive mineralization probability and potential classification, the target area can be determined to be a high-potential target area.

[0114] This invention improves the estimation logic by designing a mineralization probability estimation model for residual slope scandium deposits, achieving a good fit between different mineralization stages. The model follows the staged mineralization logic of "material supply → element release → element enrichment," categorizing eight core indicators by stage and using a comprehensive calculation method to reflect the constraints of each stage. Furthermore, it designs a combination of strongly correlated indicators based on data from typical domestic deposits, setting coefficient standards for both full and single-standard compliance to highlight the synergistic value between multiple indicators. Verified in typical deposits in Guizhou, Yunnan, and Guangxi, this design improves the accuracy of estimating the mineralization probability of residual slope scandium deposits.

[0115] The estimation process employs index coding, standardized lookup tables, and probability calculations at each stage, forming a complete operational workflow of "data measurement → index standardization → coefficient selection → stage probability calculation → comprehensive probability grading." Each step is supported by clear parameters and formulas, allowing exploration personnel to quickly get started without complex professional knowledge. Compared to existing complex algorithms, this lowers the application threshold and can be quickly promoted to grassroots exploration teams.

[0116] The above-disclosed embodiments are merely a few specific examples of the present invention. However, the present invention is not limited thereto. Any adaptive adjustments and derivative designs made by those skilled in the art within the framework of the core principles of the present invention for specific application scenarios should fall within the protection scope of the present invention.

Claims

1. A method for modeling and evaluating geological parameters of the probability of formation of a residual-scree type of scandium mineral, characterized in that, The method comprises the following steps: Determine the index related to the ore-forming conditions of residual slope type scandium ore, and construct a residual slope type scandium ore-forming probability estimation model; the index related to the ore-forming conditions of residual slope type scandium ore includes: fault zone density, tectonic environment, parent rock type+TiO2, weathering intensity index, whole rock Sc, Sc and Al2O3 correlation, magnetic susceptibility and polarization rate; the input parameters of the residual slope type scandium ore-forming probability estimation model are the indexes related to the ore-forming conditions of residual slope type scandium ore; the output of the residual slope type scandium ore-forming probability estimation model is the comprehensive ore-forming probability P; wherein the comprehensive ore-forming probability P is calculated according to the ore-forming probability P 阶 of the ore-forming period stage; the ore-forming period stage includes: material supply, element release and element enrichment; the ore-forming probability P 阶 of the ore-forming period stage is determined by the index related to the ore-forming conditions of scandium ore. obtaining a residual accumulation type scandium ore mineralization characteristic index of a specified target area; loading a residual accumulation type scandium ore mineralization probability estimation model, inputting the residual accumulation type scandium ore mineralization characteristic index, and calculating a comprehensive mineralization probability; obtaining a comprehensive mineralization probability and a potential classification, and judging the residual accumulation type scandium ore mineralization probability of the specified target area; The mineralization probability estimation model comprises an index standard determination sub-model, an index correlation sub-model, and a mineralization period stage judgment sub-model. The index standard determination sub-model is used to define the standard reaching rules of each index and calculate the index standard reaching value S of each index. The index correlation sub-model is used to define an index combination to embody the synergistic relationship between indexes, classify the importance of each index, and define a basic coefficient L of each index b and a strong correlation coefficient L r ; wherein the synergistic relationship refers to the mutual assistance effect embodied in the metallogenic process when two or more indexes in the index combination all meet the standard; the mutual assistance effect is embodied through the strong correlation coefficient L r of the index; wherein the value of the strong correlation coefficient L r of the index is greater than the value of the basic coefficient L b . The ore-forming period stage judgment sub-model is used for determining a stage contribution degree benchmark value V of different ore-forming period stages s , a calculation method of defining a stage contribution degree total V; the ore-forming period stages correspond to different indicative indexes, and the indicative indexes of the material supply stage include: tectonic environment, parent rock type + TiO2, the indicative indexes of the element release stage include: fracture zone density, weathering intensity index, and the indicative indexes of the element enrichment stage include: whole rock Sc, Sc and Al2O3 correlation, magnetic susceptibility and polarization rate; The method for calculating the comprehensive mineralization probability P comprises: Calculate the stage metallogenic probability P of each metallogenic stage 阶 The calculation method is: P 阶 =V / V s , wherein V is the total of the stage contribution degree of each metallogenic stage, and V s is the stage contribution degree reference value; if P 阶 ≥1.0, then P 阶 =1.0; The method for calculating the comprehensive mineralization probability P is as follows: P = P 阶1 × P 阶2 × P 阶3 where P 阶1 is the ore-forming probability of the material supply stage, P 阶2 is the ore-forming probability of the element release stage, and P 阶3 is the ore-forming probability of the element enrichment stage.

2. The method of claim 1, wherein the method further comprises: The calculation method of the stage contribution degree total V of each mineralization period stage is as follows: V= ， wherein V is the total of the stage contribution degrees, i is the index number, and n is the number of indicative indexes, is the index compliance value of the index with the serial number i, is the coefficient of the index, and wherein, is the base coefficient, is the strong correlation coefficient.

3. The method of claim 1, wherein: The base coefficient L b is a parameter for measuring the contribution degree of a single index when it acts independently, and is used to calculate the contribution degree of the stage when the index combination does not all meet the standards; The strong correlation coefficient L r For embodying the contribution of multiple correlation indicators to mineralization when they work together, for calculating the contribution degree of the indicators when all of them meet the requirements.

4. The method of claim 1, wherein: The classification results of the importance of each index include core indexes, important indexes, and auxiliary indexes. The core indexes include parent rock type + TiO2 and whole rock Sc, the important indexes include tectonic environment, weathering intensity index, Sc and Al2O3 correlation, and magnetic susceptibility, and the auxiliary indexes include fracture zone density and polarizability.

5. The method of claim 1, wherein: The residual accumulation type scandium ore mineralization probability estimation model also supports potential classification according to the comprehensive mineralization probability, and the potential classification includes high potential, medium potential, and low potential.

6. The method of claim 1, wherein: The residual accumulation type scandium ore mineralization probability estimation model encodes indexes related to residual accumulation type scandium ore mineralization conditions using dimension abbreviation serial numbers, including: GZ-01: fracture zone density, GZ-02: tectonic environment, FY-01: parent rock type + TiO2, FY-02: weathering intensity index, DH-01: whole rock Sc, DH-02: Sc and Al2O3 correlation, WL-01: magnetic susceptibility, and WL-02: polarizability.

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