A method of porosity analysis of heap leach ores

Abstract

The application provides a heap leaching ore porosity analysis method and relates to the technical field of mineral processing and geological analysis. The analysis method associates material particle size composition, target element occurrence state and pore structure, can significantly improve the practicability of porosity evaluation, and thus overcomes the technical problem that the traditional method cannot reveal that the occurrence state and content distribution of target valuable elements in different particle sizes are significantly different, and then leads to the problem that different particle sizes do not contribute equally to the overall porosity.

Description

Technical Field

[0001] This invention relates to the field of mineral processing and geological analysis technology, specifically to a method for analyzing the porosity of heap leached ores. Background Technology

[0002] Porosity is a key physical parameter for evaluating the structural characteristics, fluid permeability, and reactivity of loose materials (such as ores, heap leaching residues, and tailings), and it has crucial applications in mineral processing, hydrometallurgy, environmental engineering, and geotechnical engineering. For example, in heap leaching processes, the porosity of the ore heap directly determines the uniformity of the leachate flow and the recovery efficiency of the target metal. Traditional porosity measurement methods (such as mercury intrusion porosimetry, density methods, and image analysis) typically treat the sample as a homogeneous whole, obtaining a macroscopic average porosity value. However, in actual industrial materials, especially in crushed ores, the material is a heterogeneous system composed of different particle sizes, and the occurrence state and content distribution of target valuable elements (such as copper, gold, lead, and zinc) vary significantly among different particle sizes. This difference leads to unequal contributions from different particle sizes to the overall porosity, and traditional methods cannot reveal this internal structural inhomogeneity.

[0003] Existing technologies have several drawbacks. First, they rely on macroscopic averaging, ignoring differences in particle size contribution: current methods cannot analyze the contribution weight of different particle size ranges to total porosity, failing to answer the crucial question of "whether coarse or fine particles dominate material permeability." Second, they are disconnected from target elements: traditional porosity measurement is a purely physical parameter measurement, unrelated to the distribution of the material's core value—the target valuable elements. This means it's impossible to assess the porosity of particle sizes enriched with the target elements, making it difficult to specifically optimize pretreatment processes such as crushing and classification. Third, they lack guidance: due to the lack of correlation data between porosity and element distribution, when permeability is poor or leaching rate is low, engineers struggle to accurately determine whether it's due to coarse particle pore blockage or excessive fine particle content, leading to inefficient, general adjustment measures.

[0004] In view of this, it is necessary to study a targeted porosity analysis method for heap leach ores to solve the above-mentioned technical problems. Summary of the Invention

[0005] In view of the technical problems existing in the background art, the present invention provides a porosity analysis method for heap leaching ore, which is a comprehensive evaluation method that correlates the particle size distribution, the occurrence state of target elements and pore structure of the material, and can significantly improve the practicality of porosity evaluation.

[0006] In a first aspect, embodiments of the present invention provide a method for analyzing the porosity of heap-leached ore, comprising the following steps:

[0007] S1, On-site sampling and particle size determination: On-site materials are sampled and sieved to obtain the mass yield Ei of each particle size, where i is the particle size number;

[0008] S2, Laboratory Sample Processing: On-site sampling and material crushing simulating on-site process to obtain laboratory samples, and determination of their particle size distribution Ei';

[0009] S3, Multiple combination sieving sample configuration: Take multiple laboratory samples and process them using different sequences of sieving combinations to obtain multiple sub-samples representing different particle size ranges;

[0010] S4, Automated mineralogical analysis and target element distribution coefficient calculation: Automated mineralogical analysis is performed on the subsamples representing different particle size ranges obtained in step S3 to determine the content of the target mineral or test the content of the target element, and the target element distribution coefficient Ti is calculated in different particle sizes based on the particle size mass yield Ei, the content of the target mineral and the content of the target element.

[0011] S5, Pore correction parameter determination: The porosity K1 of the sub-sample representing the fine-grained size is determined by microscopic image analysis, and / or the cracking rate K2 of the sub-sample representing the coarse-grained size is determined.

[0012] S6, Column packing volume measurement: Perform column packing experiments on the laboratory sample and the sub-samples representing different particle size ranges obtained in step S3, and measure their column packing height.

[0013] S7, Calculation of porosity for each particle size: Based on the mass yield Ei of step S1, the porosity correction parameters K1 and K2 of step S5, and the column packing height of step S6, calculate the porosity Wi for each particle size.

[0014] S8, Comprehensive porosity and particle size contribution analysis: Based on the elemental distribution coefficient Ti obtained in step S4 and the porosity Wi of each particle size obtained in step S7, calculate the weighted comprehensive porosity W, and further calculate the contribution Wi' of each particle size to the comprehensive porosity W.

[0015] As a further improvement of the present invention, in step S8, the formula for calculating the weighted comprehensive porosity W is: W = Σ(Ti×Wi);

[0016] The formula for calculating the contribution of each particle size to the overall porosity W, Wi', is: Wi' = (Ti×Wi) / W.

[0017] As a further improvement of the present invention, the particle size is divided into three: coarse particle size (>d1), medium particle size (d2 to d1), and fine particle size (<d2).

[0018] In step S3, the multi-combination sieving process adopts a three-sequence sieving method, including: sieving the same three laboratory samples separately using the first sieve aperture d1 and the second sieve aperture d2;

[0019] The three-sequence screening includes:

[0020] First sequence: Using only d1 sieving, the oversize material B11 and the undersize material B12 are obtained;

[0021] Second sequence: Use d1 and d2 sieves together, mix the oversize of d1 with the undersize of d2 to form the first group B21, and mix the undersize of d1 with the oversize of d2 to form the second group B22.

[0022] Third sequence: Using only d2 sieving, the oversize material B31 and the undersize material B32 are obtained;

[0023] Among them, the sub-samples of different particle sizes include at least B11, B22, and B32.

[0024] As a further improvement of the present invention, in step S4, the sub-samples with different particle size characteristics are B11, B22 and B32, and automated mineralogical analysis samples are prepared respectively, denoted as Cn, where n is 1, 2 and 3 respectively representing the analysis samples of B11, B22 and B32.

[0025] The formula for calculating the target element allocation coefficient Ti is:

[0026] T1=(E1×Cnm×Cm') / Σ(Ei×Cnm×Cm');

[0027] T2=(E2×Cnm×Cm') / Σ(Ei×Cnm×Cm');

[0028] T3=(E3×Cnm×Cm') / Σ(Ei×Cnm×Cm');

[0029] Wherein, Cnm is the mass percentage of the m-th target mineral in the n-th sub-sample, and Cm' is the theoretical or measured content of the target element in the m-th target mineral.

[0030] As a further improvement of the present invention, when calculating the porosity Wi of each particle size, step S5 introduces a microstructure correction factor to correct the measurement results; including:

[0031] For the fine-grained sample B32, the porosity K1 obtained from scanning electron microscopy image analysis is introduced to correct for the damage to the original pores during the sample preparation process.

[0032] For coarse-grained sample B11, the fracture ratio K2 obtained from automated mineralogical analysis is introduced to correct for the contribution of internal fractures to porosity.

[0033] As a further improvement of the present invention, in step S7, the formula for calculating the particle size porosity Wi is:

[0034] W1 = 1 - E1 - [H1×(1 - K2) / H];

[0035] W2 = 1 - E2 - [H2×(1 - K1) × (1 - K2) / H];

[0036] W3 = 1 - E3 - [H3×(1 - K1) / H];

[0037] Among them, W1, W2, and W3 correspond to the porosity of coarse, medium, and fine particles, respectively;

[0038] E1, E2, and E3 represent the mass percentages of coarse, medium, and fine particle sizes, respectively.

[0039] H represents the total column packing height of the sample, and H1, H2, and H3 represent the column packing heights of subsamples B12, B21, and B31, respectively.

[0040] K1 is the porosity measured based on subsample B32, and K2 is the cracking rate measured based on subsample B11.

[0041] As a further improvement of the present invention, in step S6, the column height is obtained by comparing the column volume, specifically as follows:

[0042] Take a laboratory sample of mass M and pack it into a column, measuring the height as H.

[0043] Take a sample B12 with a mass of M × (1-E1) kg and pack it into a column. Measure the height as H1.

[0044] Take a sample B21 with a mass of M × (1-E2) kg and pack it into a column. Measure the height as H2.

[0045] Take a sample B31 with a mass of M×(1-E3) kg and pack it into a column. The height is measured to be H3.

[0046] As a further improvement of the present invention, the diameter of the first sieve hole d1 is 20 mm and the diameter of the second sieve hole d2 is 1 mm.

[0047] As a further improvement of the present invention, in step S2, the deviation between Ei' and Ei is controlled within the range of 0.95 to 1.05.

[0048] As a further improvement of the present invention, the target element is at least one of copper, gold, silver, lead, zinc, and molybdenum; the test material is ore, heap leaching residue, or tailings; and the target mineral includes, but is not limited to, pyrite, chalcopyrite, and galena.

[0049] Secondly, the present invention also provides a porosity analysis system for heap leaching ore, which is used to implement the above-mentioned analysis method, the system comprising:

[0050] The sample preparation module is used to perform sampling, sieving, and sample combination preparation operations from S1 to S3.

[0051] The mineral analysis module is used to perform automatic mineralogical analysis and target element allocation coefficient calculation in S4.

[0052] The porosity measurement module is used to perform the micro-porosity correction coefficient measurement in S5 and the macro-particle volume measurement in S6.

[0053] The data processing and calculation module is used to receive and process the data from the sample preparation module, mineral analysis module and porosity measurement module, perform calculations in S7 and S8, and output the weighted comprehensive porosity W and the contribution of each particle size Wi'.

[0054] Beneficial effects:

[0055] The porosity analysis method for heap leaching ore provided by this invention has the following technical advantages:

[0056] 1. A porosity model coupled with "elemental occurrence-particle size classification" was proposed: for the first time, the distribution coefficient of the target element in different particle sizes was used as a weight to calculate the weighted comprehensive porosity. This closely links the physical parameter of porosity with the core objective of the process (recovering the target element), achieving a leap from "physical porosity" to "effective process porosity".

[0057] 2. A multi-sequence combination sieving and column packing experiment was designed: A meticulously designed multi-particle-size three-sequence sieving scheme was used to cleverly separate samples representing different particle size ranges. Column packing measurements were then used to accurately calculate the independent porosity of each particle size range. This method avoids the damage to the macroscopic structure caused by microscopic analysis and preserves the original pore information.

[0058] 3. Automated mineralogical analysis was introduced for precise source tracing: By performing automated mineralogical analysis on key particle size samples, the target minerals and their elemental contents were accurately quantified, providing a reliable data basis for calculating elemental distribution coefficients and ensuring the scientific nature of the weighting factors.

[0059] 4. It provides refined process diagnostic capabilities: the final output not only includes a comprehensive porosity value but also the contribution of each particle size fraction to the total porosity. This provides direct guidance for process optimization. For example, if a particle size fraction enriched with the target element has a very low contribution to porosity, it indicates that the particle size fraction may be compacted or blocked, and the proportion or treatment method of that particle size fraction should be adjusted accordingly. Through this analytical method, a leap has been achieved from "knowing how much porosity there is" to "knowing where the porosity comes from and how to optimize it," providing strong technical support for precise and intelligent mineral processing.

[0060] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0061] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0062] Figure 1 This is a K2 fracture measurement and analysis diagram in the porosity analysis method for heap leached ore provided in this embodiment of the invention;

[0063] Figure 2 This is a k1 porosity analysis diagram in the porosity analysis method for heap leaching ore provided in this embodiment of the invention. Detailed Implementation

[0064] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the invention, are intended to cover non-exclusive inclusion.

[0066] In the description of the embodiments of this invention, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this invention, "multiple" means two or more, unless otherwise explicitly defined.

[0067] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0068] In the description of the embodiments of this invention, the term "and / or" 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 document generally indicates that the preceding and following related objects have an "or" relationship.

[0069] In the description of the embodiments of the present invention, the term "multiple" refers to two or more (including two), similarly, "multiple groups" refers to two or more (including two groups), and "multiple pieces" refers to two or more (including two pieces).

[0070] In the description of the embodiments of the present invention, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of the present invention.

[0071] In the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention according to the specific circumstances.

[0072] To address the technical problem that traditional methods cannot reveal the significant differences in the occurrence state and content distribution of target valuable elements (such as copper, gold, lead, and zinc) across different particle sizes, leading to unequal contributions from different particle sizes to overall porosity, this invention provides a porosity analysis method for heap leaching ores. This method is a comprehensive evaluation method that correlates material particle size distribution, the occurrence state of target elements, and pore structure, significantly improving the practicality of porosity evaluation. It introduces a two-dimensional microscopic correction mechanism: for fine-grained samples, the porosity K1 is measured using scanning electron microscopy (SEM) to correct for damage to native pores during sample preparation; for coarse-grained samples, the fracture rate K2 is measured using automated mineralogical analysis to correct for the contribution of internal fractures to porosity, improving measurement accuracy. A precise method for calculating elemental distribution coefficients is established. Automated mineralogical analysis quantifies the target mineral content and theoretical / measured element content, and combined with particle size yield, scientifically quantifies the contribution weight of each particle size to the target element, providing a reliable basis for weighted porosity calculation. This system enables visualized analysis of porosity contribution, outputting not only the overall porosity but also calculating the contribution percentage of each particle size to the total porosity using formulas. It identifies the "main contributing particle size" and provides precise guidance for optimizing mineral processing techniques (such as adjusting crushing particle size and removing fine slime). A "field-laboratory" sample consistency control system is constructed. By simulating field crushing processes, the deviation between the particle size distribution of laboratory samples and field samples is controlled within the range of 0.95 to 1.05, ensuring the applicability of the analysis results to industrial production.

[0073] This invention provides a method for porosity analysis of heap-leached ore, comprising the following steps:

[0074] S1, On-site sampling and particle size determination:

[0075] Take 5-20 kg of samples on site and perform particle size determination on the actual samples.

[0076] The preferred measurement range for the particle size determination is three ranges: greater than or equal to 20.00 mm, less than 20.00 mm but greater than or equal to 1.00 mm, and less than 1.00 mm.

[0077] The yield of each particle size is denoted as Ei, where i = 1, 2, and 3 represent particle sizes greater than or equal to 20.00 mm, less than 20.00 mm but greater than or equal to 1.00 mm, and less than 1.00 mm, respectively.

[0078] Wherein, the mass of each particle size is mi, and the total mass of the sample is M=Σmi. Then, the yield of each particle size after sieving is Ei, Ei=mi / M×100%.

[0079] S2, Laboratory Sample Processing:

[0080] Take 10-50 kg of sample and crush it using the same method and process parameters as on-site crushing to obtain laboratory sample B.

[0081] The crushed sample is preferably measured in three ranges: greater than or equal to 20.00 mm, less than 20.00 mm and greater than or equal to 1.00 mm, and less than 1.00 mm. The yield of each particle size is denoted as Ei' (i = 1, 2, and 3, representing particle sizes greater than or equal to 20.00 mm, less than 20.00 mm and greater than or equal to 1.00 mm, and less than 1.00 mm, respectively).

[0082] It should be noted that the above particle size range can be adapted to the properties of the ore and is not limited to the specific particle size values ​​mentioned above.

[0083] As a further improvement of the present invention, the deviation of Ei' / Ei is controlled within the range of 0.95 to 1.05.

[0084] S3, Multiple combination sieving sample configuration:

[0085] Three portions (5 kg each) of laboratory sample B, namely B1, B2, and B3, were taken and sieved using 20.00 mm and 1.00 mm sieves, respectively, to obtain subsamples with different particle size compositions. The specific process is as follows:

[0086] Sample B1 was tested using a 20.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were recorded as B11 and B12, respectively.

[0087] Sample B2 was tested using 20.00 mm and 1.00 mm sieves. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were mixed and recorded as B21. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were recorded as B22.

[0088] Sample B3 was tested using a 1.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were recorded as B31 and B32, respectively.

[0089] S4, Automated Mineralogical Analysis and Target Element Distribution Coefficient Calculation:

[0090] Samples B11, B22 and B32 from step S3 were taken, finely ground to pass through a 200-mesh sieve, and then reduced to 3-5 g each to prepare automated mineralogical analysis samples, denoted as Cn (n is 1, 2 and 3, representing samples B11, B22 and B32 respectively).

[0091] Automated mineralogical analysis was performed on sample Cn to accurately determine the mass percentage content of the target mineral Cnm (m is 1, 2, and 3, representing the types of target minerals pyrite, chalcopyrite, and galena, respectively), and the content of the target element of the m-th target mineral species Cm'.

[0092] The target element distribution coefficient Ti for different particle sizes is calculated using the following formula:

[0093] T1=E1×Cnm×Cm' / Σ(Ei×Cnm×Cm'),

[0094] T2=E2×Cnm×Cm' / Σ(Ei×Cnm×Cm'),

[0095] T3=E3×Cnm×Cm' / Σ(Ei×Cnm×Cm').

[0096] The preparation of samples for automated mineralogical analysis specifically involves embedding and curing, polishing, and carbon spraying. This ensures the sample measurement surface is smooth and free of scratches, while also meeting the conductivity requirements of automated mineralogical analysis.

[0097] S5, Pore and void measurement (pore correction parameter measurement):

[0098] S51, please refer to Figures 1 to 2 As shown, for sample B32, a thin layer of sample was collected using conductive adhesive, and the sample floating on the surface was blown away with a syringe. The porosity was measured under a scanning electron microscope. The porosity, denoted as porosity K1, is the ratio of the area of ​​the measurement surface without minerals to the area of ​​the measurement surface. It is used to correct for the damage to the original pore structure during the fine grinding process.

[0099] S52, sample B11 and directly mount it to prepare an automated mineralogical analysis sample (vacuum mounting, polishing). Perform automated mineralogical analysis to measure the fracture area ratio (the percentage of fracture area on the measurement surface), i.e., the fracture rate, denoted as K2.

[0100] S6, Column volume measurement:

[0101] Take 1.0 kg of laboratory sample B and pack it into the column, measuring the height as H;

[0102] Take 1.0 × (1-E1) kg of sample B12 and pack it into the column, measuring the height as H1;

[0103] Take 1.0 × (1-E2) kg of sample B21 and pack it into the column. Measure the height as H2.

[0104] Take 1.0 × (1-E3) kg of sample B31 and pack it into the column. Measure the height as H3.

[0105] S7, Porosity calculation for each particle size:

[0106] The porosities W1, W2, and W3 of samples B12, B21, and B31 are calculated using the following formulas:

[0107] W1 = 1 - E1 - H1 × (1 - K2) / H;

[0108] W2=1-E2-H2×(1-K1)×(1-K2) / H;

[0109] W3 = 1 - E3 - H3 × (1 - K1) / H.

[0110] S8, Analysis of the combined contribution of porosity and particle size:

[0111] The porosity W is calculated using the following formula: W = Σ(Ti×Wi)=T1×W1+T2×W2+T3×W3;

[0112] The formula for calculating the contribution of each particle size to the overall porosity W, Wi', is: Wi' = (Ti×Wi) / W.

[0113] W1' = T1 × W1 / W;

[0114] W2'=T2×W2 / W;

[0115] W3' = T3 × W3 / W.

[0116] The evaluation of this invention has achieved a leap from "knowing how much porosity there is" to "knowing where porosity comes from and how to optimize it," providing strong technical support for precise and intelligent mineral processing.

[0117] Example 1

[0118] Embodiment 1 of the present invention provides a porosity analysis method for heap leaching ore, which is a comprehensive evaluation method that correlates the particle size distribution, the occurrence state of target elements and pore structure of the material, using in-situ heap leaching ore from a copper mine in Inner Mongolia Autonomous Region as a sample.

[0119] Background: A porphyry copper deposit employs heap leaching. To improve the leaching rate, the pore structure of the crushed ore needs to be evaluated. This ore is a large, low-grade, easily mined polymetallic deposit, with copper as the main mineral and associated minerals such as molybdenum, silver, and gold. Due to the low copper grade in some resources, flotation is not economically viable; therefore, heap leaching is chosen.

[0120] Specifically, the steps include the following:

[0121] S1 & S2, 20 kg of raw ore was taken on site, and the particle size analysis results were: E1 (>20 mm) = 35.22%, E2 (1-20 mm) = 49.53%, E3 (<1 mm) = 15.25%.

[0122] A 50 kg sample was taken and subjected to simulated crushing in the laboratory to obtain laboratory sample B. The particle size distribution Ei' deviated from Ei within the allowable range.

[0123] Among them, E1' (>20 mm) = 34.92%, E2' (1-20 mm) = 49.48%, and E3' (<1 mm) = 15.60%.

[0124] S3. Take laboratory sample B and perform three-sequence sieving according to the method described to obtain B11, B12, B21, B22, B31, and B32.

[0125] The specific operation process is as follows:

[0126] Take three portions (5 kg each) of the same laboratory sample B, namely B1, B2 and B3, and sieve them using 20.00 mm and 1.00 mm sieves respectively.

[0127] specific:

[0128] Sample B1 was tested using a 20.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were recorded as B11 and B12, respectively.

[0129] Sample B2 was tested using 20.00 mm and 1.00 mm sieves. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were mixed and recorded as B21. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were recorded as B22.

[0130] Sample B3 was tested using a 1.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were designated as B31 and B32, respectively.

[0131] S4, automated mineralogical analysis samples of B11, B22, and B32 were prepared and analyzed. The results showed that the main copper-bearing mineral was chalcopyrite, followed by chalcocite. The contents of each particle size are detailed in the table below.

[0132] The calculated distribution coefficient for copper is approximately:

[0133] T1=E1×Cnm×Cm' / Σ(Ei×Cnm×Cm')

[0134] =0.3492×(0.84%×34.52%+0.21%×79.85%) / ((0.3492×(0.84%×34.52%+0.21%×79.85%+)+0.4948×(1.34%×34.52%+0.61%×79.85%)+0.1560×(0.52%×34.52%+0.15%×79.85%))=23.63%;

[0135] T2=E2×Cnm×Cm' / Σ(Ei×Cnm×Cm')=0.4948×(1.34%×34.52%+0.61%×79.85%) / ((0.3492×(0.84%×34.52%+0.2 1%×79.85%+)+0.4948×(1.34%×34.52%+0.61%×79.85%)+0.1560×(0.52%×34.52%+0.15%×79.85%))=69.47%;

[0136] T3=E3×Cnm×Cm' / Σ(Ei×Cnm×Cm')=0.1560×(0.52%×34.52%+0.15%×79.85%) / ((0.3492×(0.84%×34.52%+0.2 1%×79.85%+)+0.4948×(1.34%×34.52%+0.61%×79.85%)+0.1560×(0.52%×34.52%+0.15%×79.85%))=6.90%.

[0137] This indicates that most of the copper (69.47%) is present in the medium-sized grain size of 1-20 mm.

[0138] Table 1 shows the results of the automated mineralogical analysis.

[0139]

[0140] Among them, the copper content in chalcopyrite is C1'=34.52%, and the copper content in chalcocite is C2'=79.85%.

[0141] S5 & S6, measured by column packing experiments:

[0142] H = 20.60 cm;

[0143] H1 (>20 mm) = 9.06 cm;

[0144] H2 (1-20 mm) = 7.83 cm;

[0145] H3 (<1 mm) = 3.09 cm;

[0146] The measurements showed that K1 = 0.3241 and K2 = 0.1533.

[0147] S7, calculate the overall porosity and contribution.

[0148] W1=1-E1-H1×(1-K2) / H=1-0.3492-(1-0.1533)×0.4398=27.84%,

[0149] W2=1-E2-H2×(1-K1)×(1-K2) / H=1-0.4948-(1-0.1533)×(1-0.3241)×0.3801=28.77%,

[0150] W3=1-E3-H3×(1-K1) / H=1-0.1560-(1-0.3241)×0.1500=74.26%,

[0151] S8, contribution at each granularity level:

[0152] Calculate porosity W.

[0153] W=T1×W1+T2×W2+T3×W3=0.2781×0.2363+0.2877×0.6947+0.7426×0.0690=31.68%;

[0154] W1' = T1 × W1 / W = 20.74%;

[0155] W2' = T2 × W2 / W = 63.08%;

[0156] W3' = T3 × W3 / W = 16.18%.

[0157] The above data shows that the overall porosity of the ore is 31.68%, but its internal structure is extremely heterogeneous.

[0158] Based on the calculations and analysis of Example 1, the core finding is that the medium-sized particle size (1-20 mm), which accounts for about 50% of the ore weight, is enriched with nearly 70% of the copper element and contributes about 70% of the total porosity. This means that this particle size is the "main layer" in the leaching process, and the stability of its pore structure is crucial.

[0159] In this embodiment, the process is recommended as follows:

[0160] During heap leaching, special attention should be paid to protecting and maintaining the loose state of 1-20mm particles to prevent them from being squeezed by fine mud and reducing their porosity.

[0161] It is advisable to control the crushing particle size and appropriately increase the proportion of this main particle size.

[0162] Fine particles (<1mm) contribute very little to porosity and copper recovery, and are prone to migration and clogging of pores. Therefore, some of them should be removed before crushing by means of washing or screening.

[0163] Example 2

[0164] Example 2 of this invention provides a method for analyzing the porosity of heap leaching ore. This method is a comprehensive evaluation method that correlates the particle size distribution, the occurrence state of target elements, and the pore structure of the material. The sample used is an ore from an in-situ heap leaching process at a gold mine in Inner Mongolia Autonomous Region. This gold ore from Inner Mongolia Autonomous Region has a low gold grade and low content of metallic sulfides, mainly pyrite, with small amounts of galena and sphalerite; the main metallic oxide is magnetite, with small amounts of hematite and limonite; the main precious metal mineral is native gold; the gangue minerals are mainly plagioclase, orthoclase, and quartz, and the ore has a low oxidation rate.

[0165] S1 & S2, 20 kg of raw ore was taken on site, and the particle size analysis results were: E1 (>20 mm) = 18.74%, E2 (1-20 mm) = 51.33%, E3 (<1 mm) = 29.93%.

[0166] A 60 kg sample was taken and subjected to simulated crushing in the laboratory to obtain laboratory sample B. The particle size distribution Ei' deviated from Ei within the allowable range.

[0167] Among them, E1' (>20 mm) = 18.67%, E2' (1-20 mm) = 51.28%, and E3' (<1 mm) = 30.05%.

[0168] S3. Take laboratory sample B and perform three-sequence sieving according to the method described to obtain B11, B12, B21, B22, B31, and B32.

[0169] The specific operation process is as follows:

[0170] Take three portions (5 kg each) of the same laboratory sample B, namely B1, B2 and B3, and sieve them using 20.00 mm and 1.00 mm sieves respectively.

[0171] specific:

[0172] Sample B1 was tested using a 20.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were recorded as B11 and B12, respectively.

[0173] Sample B2 was tested using 20.00 mm and 1.00 mm sieves. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were mixed and recorded as B21. The sample that passed through the 20.00 mm sieve and the sample that passed through the 1.00 mm sieve were recorded as B22.

[0174] Sample B3 was tested using a 1.00 mm sieve. The samples that passed through the sieve and those that passed through the sieve were designated as B31 and B32, respectively.

[0175] S4. Automated mineralogical analysis samples were prepared and analyzed for B11, B22, and B32. The automated mineralogical analysis did not detect a sufficient amount of gold minerals; therefore, laboratory analysis was used to determine the gold grade. The content of gold in each particle size fraction is detailed in the table below.

[0176] The calculated distribution coefficient for gold is approximately:

[0177] T1=E1×Cnm×Cm' / Σ(Ei×Cnm×Cm')=(0.1867×(1.22×0.9212)) / ((0.1867×(1) .22×0.9212)+0.5128×(1.30×0.9212)+0.3005×(1.53×0.9212))=16.82%;

[0178] T2=E2×Cnm×Cm' / Σ(Ei×Cnm×Cm')=(0.5128×(1.30×0.9212)) / ((0.1867×(1) .22×0.9212)+0.5128×(1.30×0.9212)+0.3005×(1.53×0.9212))=49.23%;

[0179] T3=E3×Cnm×Cm' / Σ(Ei×Cnm×Cm')=(0.3005×(1.53×0.9212)) / ((0.1867×(1) .22×0.9212)+0.5128×(1.30×0.9212)+0.3005×(1.53×0.9212))=33.95%.

[0180] This indicates that a large amount of gold minerals (83.18%) are present in grain sizes smaller than 20 mm.

[0181] Table 2 shows the chemical analysis results (g / t).

[0182]

[0183] Among them, the gold content (gold fineness) C1' in the gold mineral is 92.12%.

[0184] S5 & S6, measured by column packing experiments:

[0185] H = 25.33 cm;

[0186] H1 (>20 mm) = 5.44 cm;

[0187] H2 (1-20 mm) = 10.12 cm;

[0188] H3 (<1 mm) = 7.46 cm;

[0189] The measurements showed that K1 = 0.2677 and K2 = 0.1820.

[0190] S7, calculate the overall porosity and contribution.

[0191] W1=1-E1-H1×(1-K2) / H=1-0.1867-5.44×(1-0.1820) / 25.33=63.76%,

[0192] W2=1-E2-H2×(1-K1)×(1-K2) / H=1-0.5128-10.12(1-0.2677)×(1-0.1820) / 25.33=24.79%,

[0193] W3=1-E3-H3×(1-K1) / H=1-0.3005-7.46×(1-0.2677) / 25.33=48.38%,

[0194] S8, contribution at each granularity level:

[0195] The porosity W is calculated using the following formula:

[0196] W=T1×W1+T2×W2+T3×W3=16.82%×63.76%+49.23%×24.79%+33.95%×48.38%=39.35%;

[0197] W1' = T1 × W1 / W = 27.25%;

[0198] W2' = T2 × W2 / W = 31.01%;

[0199] W3' = T3 × W3 / W = 41.74%.

[0200] The above data shows that the finest-grained pores contribute the most.

[0201] Example 3

[0202] Embodiment 3 of the present invention provides a porosity analysis system for heap leaching ore, which is used to implement the porosity analysis method for heap leaching ore described in the above embodiments. The system includes:

[0203] The sample preparation module is used to perform sampling, sieving, and sample combination preparation operations from S1 to S3.

[0204] The mineral analysis module is used to perform automatic mineralogical analysis and target element allocation coefficient calculation in S4.

[0205] The porosity measurement module is used to perform the micro-porosity correction coefficient measurement in S5 and the macro-particle volume measurement in S6.

[0206] The data processing and calculation module is used to receive and process the data from the sample preparation module, mineral analysis module and porosity measurement module, perform calculations in S7 and S8, and output the weighted comprehensive porosity W and the contribution of each particle size Wi'.

[0207] In summary, this invention provides a porosity analysis method for heap leaching ores, relating to the fields of mineral processing and geological analysis. This method correlates the particle size distribution, the occurrence state of target elements, and the pore structure, proposing a coupled porosity model of "element occurrence-particle size classification." The distribution coefficient of the target element in different particle sizes is used as a weight to calculate the weighted comprehensive porosity. This closely links the physical parameter of porosity to the core objective of the process (recovering the target element), achieving a leap from "physical porosity" to "effective process porosity." Furthermore, a multi-sequence combined sieving and column packing experiment was designed. Through a carefully designed multi-particle size three-sequence sieving scheme, samples representing different particle size ranges are cleverly separated, and the independent porosity of each particle size range is accurately calculated through column packing measurements. This method avoids the destruction of the macroscopic structure by microscopic analysis, preserving the original pore information. Furthermore, automated mineralogical analysis was introduced for precise source tracing: by performing automated mineralogical analysis on key particle size samples, the target minerals and their elemental contents were accurately quantified, providing a reliable data foundation for calculating elemental distribution coefficients and ensuring the scientific validity of weighting factors. The final output not only includes a comprehensive porosity value but also the contribution of each particle size to the total porosity. This overcomes the technical problem of traditional methods failing to reveal significant differences in the occurrence state and content distribution of target valuable elements (such as copper, gold, lead, and zinc) in different particle sizes, leading to unequal contributions from different particle sizes to the overall porosity.

[0208] It should be noted that the present invention is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments that have the same structure and perform the same effects as the technical concept within the scope of the present invention are included within the scope of the present invention. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of the present invention, are also included within the scope of the present invention.

Claims

1. A method of analysing the porosity of a heap leach ore, characterised by, The method comprises the following steps: S1, on-site sampling and particle size determination: sampling and particle size screening of on-site materials to obtain mass yield Ei of each particle size, wherein i is the particle size sequence number; S2, laboratory sample processing: on-site sampling, and crushing the materials to obtain laboratory samples and determine the particle size distribution Ei'; S3, multi-combination screening sample configuration: taking multiple laboratory samples, and processing them by using different sequences of screening combinations to obtain multiple sub-samples representing different particle size intervals; S4, automatic mineralogical analysis and target element distribution coefficient calculation: performing automatic mineralogical analysis on the sub-samples representing different particle size intervals obtained in step S3 to determine the content of target minerals or the content of target elements, and calculating the target element distribution coefficient Ti in different particle sizes based on the particle size mass yield Ei, the content of target minerals and the content of target elements; S5, pore correction parameter determination: determining the porosity K1 of the sub-sample representing the fine particle size and / or determining the fissure rate K2 of the sub-sample representing the coarse particle size by micro-image analysis; S6, column packing volume measurement: performing column packing experiments on the sub-samples representing different particle size intervals obtained in step S3 to measure the column packing height; S7, particle size porosity calculation: calculating the particle size porosity Wi based on the mass yield Ei in step S1, the pore correction parameters K1 and K2 in step S5, and the column packing height in step S6; S8, comprehensive porosity and particle size contribution analysis: calculating the weighted comprehensive porosity W based on the element distribution coefficient Ti obtained in step S4 and the particle size porosity Wi obtained in step S7, and further calculating the contribution Wi' of each particle size to the comprehensive porosity W.

2. A method of porosity analysis of heap leaching ore according to claim 1, characterised in that, In step S8, the calculation formula of the weighted comprehensive porosity W is: W = Σ(Ti×Wi); The calculation formula of the contribution Wi' of each particle size to the comprehensive porosity W is: Wi' = (Ti×Wi) / W.

3. A method of porosity analysis of heap leaching ore according to claim 2, characterised in that, The particle size is divided into three: the coarse particle size is greater than d1, the medium particle size is greater than or equal to d2 and less than or equal to d1, and the fine particle size is less than d2; In step S3, the multi-combination screening processing uses a three-sequence screening method, which comprises: using a first screen hole d1 and a second screen hole d2 to screen the same three laboratory samples to obtain sub-samples with different particle size compositions; The three-sequence screening comprises: First sequence: only using d1 to screen to obtain the screen oversize B11 and the screen undersize B12; Second sequence: jointly using d1 and d2 to screen, taking the screen oversize of d1 and the screen undersize of d2 to mix as the first group B21, and taking the screen undersize of d1 and the screen oversize of d2 to mix as the second group B22; Third sequence: only using d2 to screen to obtain the screen oversize B31 and the screen undersize B32.

4. A method of porosity analysis of heap leaching ore according to claim 3, characterised in that, In step S4, the sub-samples with different particle size characteristics are B11, B22 and B32, and automatic mineralogical analysis samples are prepared therefrom, denoted as Cn, wherein n is 1, 2 and 3 respectively representing the analysis samples of B11, B22 and B32; The calculation formula of the target element distribution coefficient Ti is: T1 = (E1 x Cnm x Cm') / ∑(Ei x Cnm x Cm'); T2 = (E2 x Cnm x Cm') / ∑(Ei x Cnm x Cm'); T3 = (E3 x Cnm x Cm') / ∑(Ei x Cnm x Cm'); Wherein, Cnm is the mass percentage content of the mth target mineral in the nth sub-sample, and Cm' is the theoretical content or measured content of the target element in the mth target mineral.

5. A method of porosity analysis of heap leaching ore according to claim 3, characterised in that, In the calculation of the porosity Wi of each particle size fraction, step S5 introduces a microstructure correction factor to correct the measurement results; including: For the fine particle size fraction sample B32, the porosity K1 obtained by scanning electron microscope image analysis is introduced to correct the damage to the original pores during the sample preparation process; For the coarse particle size fraction sample B11, the fissure porosity K2 obtained by automatic mineralogy analysis is introduced to correct the contribution of the internal fissures of the ore block to the porosity.

6. A method of porosity analysis of heap leaching ore according to claim 5, characterised in that, In step S7, the calculation formula of the particle size porosity Wi is: W1 = 1 - E1 - [H1 x (1 - K2) / H]; W2 = 1 - E2 - [H2 x (1 - K1) x (1 - K2) / H]; W3 = 1 - E3 - [H3 x (1 - K1) / H]; Wherein, W1, W2, W3 respectively correspond to the porosities of coarse, medium and fine particle size fractions; E1, E2, E3 are the mass percentage contents of coarse, medium and fine particle size fractions, respectively; H is the total sample column height, and H1, H2, H3 are the column heights of sub-samples B12, B21 and B31, respectively; K1 is the porosity measured based on sub-sample B32, and K2 is the fissure porosity measured based on sub-sample B11.

7. A method of analysing the porosity of heap leaching ore according to claim 6, characterised in that, In step S6, the column height is obtained by the column volume comparison method, specifically: Take the laboratory sample mass M to column, and measure the height H, Take the sub-sample B12 mass M x (1 - E1) kg to column, and measure the height H1, Take the sub-sample B21 mass M x (1 - E2) kg to column, and measure the height H2, Take the sub-sample B31 mass M x (1 - E3) kg to column, and measure the height H3.

8. A method of porosity analysis of heap leaching ore according to claim 3, characterised in that, The first sieve hole d1 has a diameter of 20 mm, and the second sieve hole d2 has a diameter of 1 mm.

9. A method of analysing the porosity of heap leaching ore according to claim 1, characterised in that, In step S2, the deviation of Ei' and Ei is controlled within the range of 0.95-1.05; The target element is at least one of copper, gold, silver, lead, zinc and molybdenum; the on-site material is ore, heap leaching residue or tailings; and the target mineral includes but is not limited to pyrite, chalcopyrite and galena.

10. A system for analysing the porosity of a heap leaching ore, characterised by, A system for implementing the porosity analysis method of the heap leaching ore according to any one of claims 1-9, the system comprising: A sample preparation module for performing the sampling, sieving and sample preparation operations of steps S1 to S3; A mineral analysis module for performing the automatic mineralogy analysis and target element distribution coefficient calculation of S4; A porosity and column volume measurement module for performing the micro-pore correction coefficient measurement of step S5 and the macro-column volume measurement of step S6; A mineral analysis module for performing the automatic mineralogy analysis and target element distribution coefficient calculation of S4; A data processing and calculation module is configured to receive and process data from the sample preparation module, the mineral analysis module, and the pore and packing volume measurement module, perform the calculations of steps S7 and S8, and output the weighted bulk porosity W and the contribution of each size fraction Wi’.

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