Method for locating multi-hydrothermal centers in porphyry deposits using gypsum spectral characteristics

Abstract

This invention discloses a method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics. The method includes sample collection; sample pretreatment and testing; data interpretation and parameter calculation; model establishment; setting parameter ranges; model parameter optimization; and hydrothermal center location and delineation. This invention takes gypsum in porphyry deposits as the research object, using a portable shortwave infrared spectrometer to analyze parameters such as the absorption peak wavelength and absorption depth of various minerals in the sample. It extracts spectral parameter characteristics related to the distance to the hydrothermal center, establishes a mathematical model of the hydrothermal center, and combines this with the characteristics of the new area to establish a new area hydrothermal center location model and a quantitative model using exhaustive methods and other parameter optimization methods. This method determines the location and direction of the hydrothermal center in the new area, overcoming the complexity of geological and geochemical methods and the ambiguity and inefficiency of geophysical and drilling methods.

Description

Technical Field

[0001] This invention belongs to the field of mineral exploration technology, specifically relating to a method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics. Background Technology

[0002] Porphyry deposits are the world's most important sources of copper, molybdenum, and gold, accounting for approximately 75% of global copper production and over 95% of global molybdenum production. These deposits mainly occur as disseminated or fine-veined patterns near the hydrothermal center at the top of the porphyry body. Locating the hydrothermal center allows for rapid determination of the ore body's extent and location. While typical porphyry mineralization systems develop only one hydrothermal center, further research has revealed the possibility of multiple hydrothermal centers. For a single hydrothermal center, the spectral characteristics and major and trace element contents of alteration minerals such as chlorite and epidote vary spatially with temperature due to temperature differences. Therefore, the approximate location of the hydrothermal center can be traced through these spectral and trace element variations. However, for deposits with multiple hydrothermal centers, the superposition of hydrothermal fluids between different centers makes it difficult to identify multiple hydrothermal centers using alteration minerals. Therefore, there is an urgent need to develop a novel and efficient method for identifying and locating multiple hydrothermal centers in porphyry deposits to achieve rapid breakthroughs in porphyry mineral exploration.

[0003] Current methods for identifying hydrothermal centers primarily utilize geological, mineralogical, and spectroscopic approaches. Geological methods mainly involve geological mapping to determine alteration zoning and mineral assemblage relationships to pinpoint the location of hydrothermal centers. Mineralogical methods utilize spatial variations in the mineral geochemistry of altered minerals to identify hydrothermal centers. Alternatively, the location of hydrothermal centers can be identified by observing changes in the short-wave infrared spectra (such as wavelength and absorption peak characteristics) of mica, kaolinite, and other clay minerals due to temperature variations.

[0004] Geological methods, such as geological mapping, are time-consuming, require significant manpower and resources, are expensive, and demand highly specialized technical personnel. They also struggle to quantitatively determine the location of hydrothermal centers. Mineralogical and spectroscopic methods primarily utilize the spatial variations in mineral chemistry and spectral characteristics, such as wavelength and absorption peaks, caused by temperature changes in altered minerals. While these methods show promise in deposits with single hydrothermal centers, in deposits with multiple hydrothermal centers, the overlapping of different hydrothermal centers leads to a loss of spatial regularity in the mineral chemistry and spectral characteristics of altered minerals, making it impossible to accurately reflect the spatial location of the hydrothermal center. Therefore, reliable methods are currently lacking for determining the location of multiple hydrothermal centers.

[0005] Drilling is currently a reliable method for determining multiple hydrothermal centers. However, drilling is very expensive and requires highly skilled technicians, which poses a challenge to the identification and location of multiple hydrothermal centers in porphyry deposits. Therefore, few people use drilling to determine the location of multiple hydrothermal centers. Summary of the Invention

[0006] Gypsum is one of the most widely distributed minerals in porphyry deposits, representing porphyry mineralization systems characterized by high sulfur and high oxygen fugacity. During the conversion of magma into hydrothermal fluids, abundant gypsum forms at the hydrothermal center, while its content gradually decreases further away. This provides a possibility for identifying multiple hydrothermal centers by utilizing the spatial variation of gypsum. Studies have found that the absorption depth of gypsum in short-wave infrared spectra is stronger in areas with higher gypsum content. Therefore, this provides a possibility for determining hydrothermal centers by utilizing the spatial variation of gypsum's short-wave infrared spectrum. By establishing a quantitative mathematical model of the short-wave infrared absorption depth of gypsum and the distance to the hydrothermal center, the hydrothermal centers of porphyry mineralization can be quickly and quantitatively identified and located.

[0007] The purpose of this invention is to provide a method for identifying multiple hydrothermal centers in porphyry deposits. Taking gypsum in porphyry deposits as the research object, a portable shortwave infrared spectrometer is used to analyze parameters such as the absorption peak wavelength and absorption depth of various minerals in the sample. Spectral parameter features related to the distance to the hydrothermal center are extracted, a mathematical model of the hydrothermal center is established, and combined with the characteristics of the new area, parameter optimization methods such as exhaustive search are used to establish a location model and a quantitative model of the hydrothermal center in the new area. The location and direction of the hydrothermal center in the new area are determined, overcoming the complexity of geological and geochemical methods and the problems of multiple solutions and inefficiency of geophysical exploration and drilling.

[0008] To achieve the above objectives, the following technical solution is adopted:

[0009] A method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics includes the following steps:

[0010] (1) Sample collection;

[0011] Collect representative gypsum samples from porphyry deposits;

[0012] (2) Sample pretreatment and sample testing;

[0013] After cleaning and drying the collected samples, three fresh sides of each sample were selected and tested using a short-wave infrared spectrometer.

[0014] (3) Data interpretation and parameter calculation;

[0015] The test data is analyzed and processed to obtain reasonable mineral absorption peak wavelengths and absorption depths x.

[0016] (4) Model establishment;

[0017] Substitute the absorption depth x into the logarithmic model D = aln(x) + b and the exponential model D = a(x)^b + c;

[0018] (5) Given the parameter range;

[0019] In the logarithmic model D=aln(x)+b, the parameters a∈[-10,10] are set with a step size of 0.5; b∈[-1000,1000] with a step size of 50;

[0020] In the exponential model D=a(x)^b+c, the parameters are set as follows: a∈[-1000,1000], step size is 50; b∈[-1000,1000], step size is 50; c∈[-1000,1000], step size is 50.

[0021] (6) Model parameter tuning;

[0022] The parameters of the two models are optimized using an exhaustive method; that is, by iteratively cyclically determining the optimization parameters a, b, and c of the two models with the constraint that R value ≤ 40.

[0023] Where R is the optimized buffer radius: Its threshold is <40m;

[0024] n is the number of samples; i is the i-th sampling point; D i The straight-line distance, in meters, between the location of the hydrothermal center determined for n samples and the location of the i-th sampling point; r i E represents the straight-line distance between the hydrothermal center and sampling point i, as determined by the parameter model for sampling point i, in meters; E represents D. i With r i The absolute value of the difference, in meters;

[0025] (7) Locating and delineating the hydrothermal center;

[0026] If there are two or more returned parameters a and b, it is determined to be a single hydrothermal center; if there is only one returned parameter a and b, it is determined to be a double hydrothermal center; in the case of double hydrothermal centers, the intersection of the minimum R value is taken as hydrothermal center 1, and the intersection of the second minimum R value is taken as hydrothermal center 2.

[0027] Using the above parameters, the optimal R values ​​for the dual hydrothermal centers and single hydrothermal centers of the two models are obtained respectively. The model with the smallest R value is taken as the optimal model. The data of all sampling points are brought into the optimal model to calculate the D value of each sampling point. A ring is drawn with the corresponding sampling point as the center and the D value as the radius. The intersection of all the rings is determined as the hydrothermal center coordinates (X,Y). The R value is used as a buffer zone for the hydrothermal center.

[0028] According to the above plan, the number of samples in step 1 shall not be less than 5; the sample information includes GPS coordinate data, field photos, lithology, alteration and mineralization characteristics.

[0029] According to the above plan, the cleaning process in step 2 includes using a brush to clean dust, dirt and other contaminants from the sample; the drying process includes exposing the sample to sunlight for 12 hours, then turning it over and exposing it to sunlight for another 12 hours.

[0030] According to the above scheme, step 3 includes importing the test data into TSG8 software, performing spectral comparison on each test data, setting the minimum content of the minerals involved in the interpretation, establishing a mineral mask according to the type of altered minerals, and using mathematical functions to enhance the spectral characteristic parameters of the absorption peak wavelength and absorption depth of the altered minerals to obtain reasonable mineral absorption peak wavelength and absorption depth x.

[0031] According to the above scheme, the model establishment in step 4 includes the following steps:

[0032] Collect representative gypsum samples from porphyry deposits in known hydrothermal centers;

[0033] After cleaning and drying the collected samples, the fresh side was selected for testing using a short-wave infrared spectrometer.

[0034] Analyze the test data to obtain reasonable mineral absorption peak wavelengths and absorption depths x; calculate the distance D between the sampling point and the hydrothermal center coordinates, in meters;

[0035] Substituting the logarithmic value of the absorption depth x (lnx) and the distance D into the linear model y = ax + b, we obtain the logarithmic model D = aln(x) + b; substituting the logarithmic value of the absorption depth x (lnx) and the logarithmic value of the distance D (lnD) into the linear model y = ax + b, we obtain the exponential model D = a(x)^b + c.

[0036] According to the above scheme, if the R value is still greater than 40m after training in step 6, it is necessary to re-define the range of parameters a and b based on the parameters a and b returned by the iteration and reduce the step size until the returned R value is ≤ 40m.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0038] This invention proposes a novel method for identifying multiple ore-forming hydrothermal centers in porphyry deposits using gypsum. This method involves short-wave infrared spectroscopy analysis of gypsum developed in porphyry, using TSG8 software to create a mask and obtain parameters such as absorption depth. A mathematical model is then established relating the ore-forming hydrothermal center to the short-wave infrared spectral parameters of gypsum. Considering the variable parameters of different mineral types, the mathematical model is optimized using an exhaustive method. Ultimately, this method accurately determines the location, number, and possible buffer zones of ore-forming hydrothermal centers, enabling better exploration of porphyry mineralization systems and providing an economical and efficient new method for mineral exploration.

[0039] This invention establishes a mathematical model of the absorption depth of gypsum in shortwave infrared spectroscopy and optimizes the model using an exhaustive method, thus establishing a quantitative model of gypsum and the hydrothermal center in the porphyry mineralization system. The mathematical model includes D = a(x)^b, D = a(x)^b+c, and D = alan(x)+b. A parameter optimization algorithm is used with R ≤ 40m as the threshold to achieve precise location of the hydrothermal center. The number of optimal solutions (R) is used to determine single and double hydrothermal centers, providing crucial information for early-stage exploration of porphyry deposits and possessing strong guiding value in porphyry mineral exploration.

[0040] This invention utilizes a method and process for determining the location of multiple hydrothermal centers in porphyry deposits using gypsum, solving the international problem that traditional alteration minerals cannot identify multiple hydrothermal centers. Identifying hydrothermal mineralization centers is key to achieving breakthroughs in mineral exploration, saving more than 80% of funds and more than 70% of time compared to traditional exploration methods. Attached Figure Description

[0041] Figure 1 : Location model of the gypsum hydrothermal center of the Qulong deposit.

[0042] Figure 2 : Parameter tuning and optimization results of Model 1 (a,b) and Model 2 (c,d). Detailed Implementation

[0043] The following embodiments further illustrate the technical solution of the present invention, but are not intended to limit the scope of protection of the present invention.

[0044] A specific embodiment provides a method for establishing a model of multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics, including the following steps:

[0045] (1) Collect representative gypsum samples from porphyry deposits in known hydrothermal centers; specifically, select the Qulong porphyry copper-molybdenum deposit in Tibet, collect gypsum-bearing porphyry samples, with a length, width, and height of approximately 3cm*5cm*8cm, and at least 5 samples. Record the sampling information as shown in Table 1.

[0046] Table 1

[0047]

[0048]

[0049] (2) Clean the gypsum-containing porphyry samples with a brush to remove dust, dirt, and other contaminants, and expose them to sunlight for 24 hours. For samples that have passed the drying process, select three fresh surfaces on each sample and test them using a portable shortwave infrared spectrometer.

[0050] (3) Import the test data into TSG8 software, set the minimum content of the minerals involved in the interpretation, establish a mineral mask based on the type of alteration minerals, and use mathematical functions to enhance the spectral characteristic parameters to obtain reasonable mineral absorption peak wavelengths and absorption depths x. Simultaneously calculate the distance D between the sampling point and the hydrothermal center coordinates, in meters. See Table 2.

[0051] Table 2

[0052]

[0053]

[0054] (4) Substituting the logarithmic value of the absorption depth x (lnx) and the distance D into the linear model y = ax + b, we obtain the logarithmic model D = aln(x) + b (Model 1); substituting the logarithmic value of the absorption depth x (lnx) and the logarithmic value of the distance D (lnD) into the linear model y = ax + b, we obtain the exponential model D = a(x)^b + c (Model 2). See Appendix. Figure 1 As shown.

[0055] A specific implementation also provides a method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics, including the following steps:

[0056] (1) Sample collection;

[0057] Representative gypsum samples were collected from porphyry.

[0058] (2) Sample pretreatment and sample testing;

[0059] The collected samples were cleaned and dried, and three fresh sides of each sample were selected for testing using a portable short-wave infrared spectrometer.

[0060] (3) Data interpretation and parameter calculation;

[0061] The test data was imported into the TSG8 software, the minimum content of the minerals involved in the interpretation was set, a mineral mask was established according to the type of altered minerals, and mathematical functions were used to enhance the spectral characteristic parameters to obtain reasonable parameters such as the wavelength of the mineral absorption peak and the absorption depth (x), as shown in Table 3.

[0062] Serial Number X(m) Y(m) Gypsum absorption depth (x) 1 171.4 237.4 0.12 2 473.9 102.6 0.27 3 385.5 299.7 0.68 4 377.0 208.3 0.69 5 279.3 353.6 0.39 6 627.4 387.2 0.21 7 571.2 468.1 0.88 8 431.4 115.7 0.49 9 259.9 201.9 0.79

[0063] (4) Model establishment;

[0064] Substitute the obtained gypsum absorption depth (x) into the logarithmic model D=aln(x)+b (model 1) and the exponential model D=a(x)^b+c (model 2);

[0065] (5) Set the parameter range;

[0066] In the logarithmic model 3D=aln(x)+b, the parameters a∈[-1000,1000] and step size is 50; b∈[-1000,1000] and step size is 50.

[0067] In the exponential model D=a(x)^b+c, the parameters are set as follows: a∈[-1000,1000], step size is 50; b∈[-1000,1000], step size is 50; c∈[-1000,1000], step size is 50.

[0068] (6) Model parameter tuning;

[0069] The parameters of the two models above are optimized using an exhaustive method. Through continuous iteration, with R value ≤ 40 as the constraint, the optimization parameters a, b, and c of the two models are determined.

[0070] Where R is the optimized buffer radius: Its threshold is ≤40m;

[0071] n is the number of samples; i is the i-th sampling point; D i The straight-line distance, in meters, between the location of the hydrothermal center determined for n samples and the location of the i-th sampling point; r i E represents the straight-line distance between the hydrothermal center and sampling point i, as determined by the parameter model for sampling point i, in meters; E represents D. i With r i The absolute value of the difference, in meters; It is the sum of E for n samples.

[0072] If the R value is still greater than 40m after training, then the range of parameters a, b, and c needs to be redefined and the step size reduced based on the parameters a, b, and c returned by the iteration, until the returned R value is ≤ 40m.

[0073] (7) Locating and delineating ore-forming rock masses;

[0074] After determining the optimization parameters for different models, the optimal R values ​​for the two models with dual hydrothermal centers and single hydrothermal centers were obtained respectively, such as... Figure 2 As shown. The minimum R value is 34.5 ( Figure 2d), the corresponding optimal model is model 2, and it is determined to be a single hydrothermal center porphyry mineralization system.

[0075] Input the data from all sampling points into the optimal model, calculate the D value for each sampling point, and draw an annulus with the sampling point as the center and the D value as the radius. The intersection of all annulus points is determined as the coordinates of the hydrothermal center (X = 435m, Y = 293m). Figure 2 d), that is, the positions of the two pentagrams, the shaded area is the buffer zone of the hydrothermal center, and the R value is used to delineate the buffer zone of the hydrothermal center.

[0076] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the implementation methods of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the present invention.

Claims

1. A method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics, characterized in that... Includes the following steps: (1) Sample collection; Collect representative gypsum samples from porphyry deposits; (2) Sample pretreatment and sample testing; After cleaning and drying the collected samples, three fresh sides of each sample were selected and tested using a short-wave infrared spectrometer. (3) Data interpretation and parameter calculation; The test data is analyzed and processed to obtain reasonable mineral absorption peak wavelengths and absorption depths x. Specifically, the test data is imported into TSG8 software, spectral comparison is performed on each test data, the minimum content of the minerals involved in the interpretation is set, a mineral mask is established according to the type of altered minerals, and the absorption peak wavelengths and absorption depths of the altered minerals are enhanced by mathematical functions to obtain reasonable mineral absorption peak wavelengths and absorption depths x. (4) Model building; Substitute the absorption depth x into the logarithmic model D=aln(x)+b and the exponential model D=a(x)^b+c; (5) Given the parameter range; In the logarithmic model D=aln(x)+b, the parameters a∈[-10,10] with a step size of 0.5; b∈[-1000,1000] with a step size of 50; In the exponential model D=a(x)^b+c, the parameters are set as follows: a∈[-1000,1000], step size is 50; b∈[-1000,1000], step size is 50; c∈[-1000,1000], step size is 50. (6) Model parameter tuning; The parameters of the two models are optimized using an exhaustive method; that is, by iteratively cyclically determining the optimization parameters a, b, and c of the two models with the constraint that R value ≤ 40. Where R is the optimized buffer radius: Its threshold is ≤40m; n Number of samples; i For the first i Sampling point number; D i for n The location of the hydrothermal center determined by the first sample is related to the first... i The straight-line distance between sampling points, in meters; r i for i The hydrothermal center determined by the parameter model at sampling point No. 1 and i The straight-line distance between sampling points is expressed in meters. E for D i and r i The absolute value of the difference, in meters; (7) Locating and delineating the hydrothermal center; If there are two or more returned parameters a and b, it is determined to be a single hydrothermal center; if there is only one returned parameter a and b, it is determined to be a double hydrothermal center; in the case of double hydrothermal centers, the intersection of the minimum R value is taken as hydrothermal center 1, and the intersection of the second minimum R value is taken as hydrothermal center 2. Using the above parameters, the optimal R values ​​for the dual hydrothermal centers and single hydrothermal centers of the two models are obtained respectively. The model with the smallest R value is taken as the optimal model. The data of all sampling points are brought into the optimal model, the D value of each sampling point is calculated, and a ring is drawn with the corresponding sampling point as the center and the D value as the radius. The intersection of all the rings is determined as the hydrothermal center coordinates (X,Y). The R value is used as the buffer zone of the hydrothermal center for delineation.

2. The method for locating multi-hydrothermal centers of porphyry deposits using gypsum spectral characteristics as described in claim 1, characterized in that... In step 1, the number of samples should be no less than 5; the sample information includes GPS coordinate data, field photos, lithology, alteration and mineralization characteristics.

3. The method for locating multiple hydrothermal centers in porphyry deposits using gypsum spectral characteristics as described in claim 1, characterized in that... Step 2 includes cleaning the sample with a brush to remove dust and dirt contaminants; the drying process includes exposing the sample to sunlight for 12 hours, then turning it over and exposing it to sunlight for another 12 hours.

4. The method for locating multi-hydrothermal centers of porphyry deposits using gypsum spectral characteristics as described in claim 1, characterized in that... Step 4, model building, includes the following steps: Collect representative gypsum samples from porphyry deposits in known hydrothermal centers; After cleaning and drying the collected samples, the fresh side was selected for testing using a short-wave infrared spectrometer. Analyze the test data to obtain reasonable mineral absorption peak wavelengths and absorption depths x; calculate the distance D between the sampling point and the hydrothermal center coordinates, in meters; Substituting the logarithmic value of the absorption depth x (lnx) and the distance D into the linear model y=ax+b, we obtain the logarithmic model D=aln(x)+b; substituting the logarithmic value of the absorption depth x (lnx) and the logarithmic value of the distance D (lnD) into the linear model y=ax+b, we obtain the exponential model D=a(x)^b+c.

5. The method for locating multi-hydrothermal centers of porphyry deposits using gypsum spectral characteristics as described in claim 1, characterized in that... If the R value is still greater than 40m after training in step 6, then the range of parameters a and b needs to be redefined and the step size reduced according to the parameters a and b returned by the iteration, until the returned R value is ≤ 40m.

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