A method for quantitatively characterizing the reducing power of gray sand bodies

Abstract

This invention relates to the field of mineral exploration technology, and more particularly to a method for quantitatively characterizing the reducing power of gray sand bodies. The method comprises: determining the target stratum within a uranium exploration area of ​​a basin; selecting boreholes that expose the target stratum; dividing the gray sand bodies developed within the target stratum in the field; and taking equidistant, continuous grooved samples from each sand body as needed to obtain gray sandstone samples; fragmenting the gray sandstone samples and testing different environmental geochemical indicators; using the divided gray sand bodies as the object, calculating the average value of different environmental geochemical indicators for each sand body based on measured geochemical data; and then processing these values ​​using fuzzy mathematical evaluation methods; based on the obtained comprehensive evaluation results, using a weighted average method to quantitatively characterize the reducing power of the sand bodies, objectively evaluating the uranium mineralization environment and potential of the target stratum. This invention overcomes the subjectivity of qualitative judgments based on human experience, resulting in more objective, accurate, and comparable evaluation results.

Description

Technical Field

[0001] This invention relates to the field of mineral exploration technology, and in particular to a method for quantitatively characterizing the reducing power of gray sand bodies. Background Technology

[0002] Redox reactions are the most fundamental mineralization mechanism of sandstone-type uranium deposits in basins. The reducing power of the gray sandstone bodies in the target layer is a crucial indicator determining whether dissolved hexavalent uranium in uranium-bearing, oxygen-rich fluids can be reduced and fixed, thus enriching into mineral deposits. It is also a primary criterion for predicting and evaluating the prospective value of this type of uranium deposit. Because reducing power is a vague and imprecise concept, geologists traditionally rely primarily on multiple environmental geochemical indicators (C0.05) of sandstone samples. 有 S 全 Qualitative evaluation of the restoration capacity (such as Eh) is highly subjective; that is, the same person may make different evaluation results for the same set of data, and different people may have different opinions on the same set of data.

[0003] Meanwhile, due to the significant heterogeneity within prospecting sand bodies, the environmental geochemical indicators of sandstone samples from different locations generally vary considerably, with data ranging from high to low. Furthermore, different geochemical indicators from the same sample often show discrepancies; for example, a high organic carbon content may be accompanied by a low total sulfur content. Geologists, relying solely on experience to simply compile and analyze these data, often fail to accurately determine the true reducing capacity of the entire sand body, thus impacting prospecting deployment. Therefore, it is essential to start from the mineralization conditions and characteristics of sandstone uranium deposits themselves, employing appropriate technical methods to quantitatively and comprehensively process multiple environmental geochemical indicators from multiple samples. This objectively evaluates the reducing capacity of gray sand bodies, preventing misjudgment or omission of effective prospecting target strata, and ultimately serving prospecting prediction. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a method for quantitatively characterizing the reducing power of gray sand bodies, which realizes the comprehensive quantitative evaluation of multiple geochemical indicators of multiple sandstone samples in multiple sand bodies, overcomes the subjectivity of human experience in qualitative evaluation, and makes the evaluation results more objective, accurate and comparable.

[0005] This invention provides a method for quantitatively characterizing the reducing power of gray sand bodies, comprising the following steps:

[0006] Step (1): Determination of the target strata within the uranium exploration area of ​​the basin;

[0007] Step (2): Select the borehole that exposes the target layer, divide the gray sand bodies developed in the target layer in the field, and take samples of each sand body by continuous equidistant grooves as needed to obtain gray sandstone samples.

[0008] Step (3): The gray sandstone sample is crushed and tested for different environmental geochemical indicators;

[0009] Step (4): Taking the gray sand bodies divided in step (2) as the object, based on the geochemical data measured in step (3), calculate the average value of different environmental geochemical indicators for each sand body, and carry out fuzzy mathematical evaluation on this basis.

[0010] Step (5): Based on the comprehensive evaluation results obtained in step (4), the weighted average method is used to quantitatively characterize the sand body reduction capacity and objectively evaluate the uranium mineralization environment and potential of the target layer.

[0011] Preferably, in step (1), the standard for the target layer is that the target layer develops X sets, X≥1, and the thickness of a single sand body is more than 5m.

[0012] Preferably, step (2) specifically includes:

[0013] Step (2.1): Based on the distribution of stable mudstone, the target in the borehole is divided into X sets of gray sand bodies from top to bottom, where X≥1;

[0014] Step (2.2): For the X sets of gray sand bodies, each set of sand bodies is divided into equal sections and continuously grooved for sampling according to the actual sample requirement m. The sample numbers of the first set of sand bodies are sequentially set as: Sd 11 、Sd 12 ... Sd 1m The second set of sand body samples were numbered sequentially as follows: Sd 21 、Sd 22 ... Sd 2m And so on;

[0015] Each sandstone sample is either a mixture of sandstones of different grain sizes or sandstones of the same grain size.

[0016] Preferably, the thickness of the stabilized mudstone is more than 10m.

[0017] Preferably, in step (3), the gray sandstone sample is crushed into 200-mesh powder.

[0018] Environmental geochemical indicators include organic carbon content, total sulfur content, redox potential, valence iron ratio, acid-hydrolyzed hydrocarbons, and GOI.

[0019] Preferably, step (4) specifically includes:

[0020] Step (4.1): Based on the measured environmental geochemical data, calculate the average values ​​of different environmental geochemical indicators of the X-set gray sand bodies, and use them as evaluation indicators;

[0021] Step (4.2): Establish the factor set (U) and rank set (V) of the evaluation indicators, where U = {u1, u2, ..., u...} n}, n evaluation factors; based on the standard of reducing capacity of favorable ore-bearing formations in sandstone-type uranium deposits, establish a corresponding m-level set, i.e., V={v1、v2、…、v m};

[0022] Step (4.3): Establish membership functions and construct the evaluation matrix R. In the formula, i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij The membership degree of the i-th evaluation factor to the j-th evaluation level is represented by μ(x), which is calculated using a linear function μ(x) and can be divided into the following two cases:

[0023] 1) For indicators where a larger value indicates stronger restoration capability, the membership function is:

[0024]

[0025] In the formula: t i S represents the test result of the i-th evaluation factor. ij Let be the evaluation standard value of level j corresponding to the i-th evaluation factor;

[0026] 2) For indicators where smaller values ​​indicate stronger restoration capabilities, the membership function form is exactly the opposite of the above case;

[0027] Step (4.4): Determine the weights of the evaluation indicators and establish the weight matrix A;

[0028] Each evaluation factor is assigned a different weight, forming a weight matrix W of the evaluation factors, which is [w1, w2, ..., w...]. i ... w n ];w i This represents the weight value of the i-th evaluation factor; for indicators with larger values, the stronger the reproducibility. For indicators with smaller values, the stronger the restoration ability The average or reference standard value of the evaluation criteria for the i-th evaluation factor.

[0029] The formula is as follows:

[0030] At the same time, w needs to be normalized, as shown in the following formula: Finally, the normalized weight matrix A = [a1, a2, ..., a...] is obtained. n ];

[0031] Step (4.5): Calculate the fuzzy evaluation set Y, and calculate the fuzzy evaluation set for each sand body. The formula is as follows:

[0032] In the formula: For fuzzy mathematical operators, model M2 is selected, namely the Zadeh operators "·" and "⊕"; a·b=ab is a product operator, and a⊕b=(a+b)∧1 is a closed addition operator.

[0033] Preferably, step (5) specifically comprises:

[0034] Based on the fuzzy evaluation set Y obtained in step (4) above, Y = max(y) is obtained by the maximum membership principle. i ), i = 1, 2, ..., m; then, the weighted average principle is used to calculate the result. Take k=2; finally, based on the evaluation results Y and B values ​​of the n sets of sand bodies, rank the reduction capabilities according to their quality.

[0035] Compared with existing technologies, this invention provides uranium geologists with a method for quantitatively evaluating the reducing capacity of gray sand bodies within target layers during sandstone uranium deposit exploration and research, thereby objectively evaluating the uranium mineralization environment and potential of the target layers. The fuzzy mathematical evaluation method based on environmental geochemical indicators provided here quantitatively characterizes the reducing capacity of gray sand bodies, achieving a comprehensive quantitative evaluation of multiple geochemical indicators from multiple sandstone samples across multiple sand bodies. The weighted method employed considers the influence of all evaluation factors on reducing capacity, overcoming the subjectivity of qualitative evaluation based on human experience. The evaluation results are more objective, accurate, and comparable, thus preventing misjudgment or omission of effective target layers, indicating the correct direction for mineral exploration, and directly serving actual production needs. It has significant value for widespread application. Attached Figure Description

[0036] Figure 1 The flowchart illustrates the method for quantitatively characterizing the reducing power of gray sand bodies according to the present invention. Detailed Implementation

[0037] To further understand the present invention, embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the present invention.

[0038] Embodiments of the present invention disclose a method for quantitatively characterizing the reducing power of gray sand bodies, such as... Figure 1 As shown, it includes the following steps:

[0039] Step (1): Determination of the target strata within the uranium exploration area of ​​the basin;

[0040] The standard for the target layer is that the target layer has X sets of sand bodies, X≥1, and the thickness of a single sand body is more than 5m.

[0041] Step (2): Select the borehole that exposes the target layer, divide the gray sand bodies developed in the target layer in the field, and take samples of each sand body by continuous equidistant grooves as needed to obtain gray sandstone samples.

[0042] Specifically, it includes:

[0043] Step (2.1): Based on the distribution of stable mudstone, the target in the borehole is divided into X sets of gray sand bodies from top to bottom, where X≥1;

[0044] The thickness of the stable mudstone is over 10m;

[0045] Step (2.2): For the X sets of gray sand bodies, each set of sand bodies is divided into equal sections and continuously grooved for sampling according to the actual sample requirement m. The sample numbers of the first set of sand bodies are sequentially set as: Sd 11 、Sd 12 ... Sd 1m The second set of sand body samples were numbered sequentially as follows: Sd 21 、Sd 22 ... Sd 2m And so on;

[0046] Each sandstone sample is either a mixture of sandstones of different grain sizes or sandstones of the same grain size.

[0047] Step (3): The gray sandstone sample is crushed and tested for different environmental geochemical indicators;

[0048] The gray sandstone sample was crushed into 200-mesh powder.

[0049] Environmental geochemical indicators include organic carbon content, total sulfur content, redox potential, valence iron ratio, acid-hydrolyzed hydrocarbons, and GOI.

[0050] Step (4): Taking the gray sand bodies divided in step (2) as the object, based on the geochemical data measured in step (3), calculate the average value of different environmental geochemical indicators for each sand body, and carry out fuzzy mathematical evaluation on this basis.

[0051] Specifically, it includes:

[0052] Step (4.1): Based on the measured environmental geochemical data, calculate the average values ​​of different environmental geochemical indicators of the X-set gray sand bodies, and use them as evaluation indicators;

[0053] Step (4.2): Establish the factor set (U) and rank set (V) of the evaluation indicators, where U = {u1, u2, ..., u...} n}, n evaluation factors; based on the standard of reducing capacity of favorable ore-bearing formations in sandstone-type uranium deposits, establish a corresponding m-level set, i.e., V={v1、v2、…、vm};

[0054] Step (4.3): Establish membership functions and construct the evaluation matrix R. In the formula, i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij The membership degree of the i-th evaluation factor to the j-th evaluation level is represented by μ(x), which is calculated using a linear function μ(x) and can be divided into the following two cases:

[0055] 1) For indicators where a larger value indicates stronger restoration capability, the membership function is:

[0056]

[0057] In the formula: t i S represents the test result of the i-th evaluation factor. ij Let be the evaluation standard value of level j corresponding to the i-th evaluation factor;

[0058] 2) For indicators where smaller values ​​indicate stronger restoration capabilities, the membership function form is exactly the opposite of the above case;

[0059] Step (4.4): Determine the weights of the evaluation indicators and establish the weight matrix A;

[0060] Each evaluation factor is assigned a different weight, forming a weight matrix W of the evaluation factors, which is [w1, w2, ..., w...]. i ... w n ];w i This represents the weight value of the i-th evaluation factor; for indicators with larger values, the stronger the reproducibility. For indicators with smaller values, the stronger the restoration ability The average or reference standard value of the evaluation criteria for the i-th evaluation factor.

[0061] The formula is as follows:

[0062] At the same time, w needs to be normalized, as shown in the following formula: Finally, the normalized weight matrix A = [a1, a2, ..., a...] is obtained. n ];

[0063] Step (4.5): Calculate the fuzzy evaluation set Y, and calculate the fuzzy evaluation set for each sand body. The formula is as follows:

[0064] In the formula: For fuzzy mathematical operators, model M2 is selected, namely the Zadeh operators "·" and "⊕", a·b=ab is a product operator, and a⊕b=(a+b)∧1 is a closed addition operator.

[0065] Step (5): Based on the comprehensive evaluation results obtained in step (4), the weighted average method is used to quantitatively characterize the sand body reduction capacity and objectively evaluate the uranium mineralization environment and potential of the target layer.

[0066] Specifically, it includes:

[0067] Based on the fuzzy evaluation set Y obtained in step (4) above, Y = max(y) is obtained by the maximum membership principle. i ), i = 1, 2, ..., m; then, the weighted average principle is used to calculate the result. Let k = 2, where k is an undetermined coefficient (k = 1 or k = 2), the purpose of which is to control for larger values ​​of b. j The role played is that, when k→∞, the weighted average principle becomes the maximum membership principle; finally, the reduction ability is ranked according to the evaluation results Y and B values ​​of n sets of sand bodies.

[0068] This invention can be widely used in the exploration, prediction, evaluation, and scientific research of sandstone-type uranium deposits in Mesozoic and Cenozoic sedimentary basins both domestically and internationally. The method provided by this invention can objectively and accurately reflect the true reduction capacity of multiple sets of gray sand bodies within the target stratum. It comprehensively considers multiple geochemical indicators, reduces the subjectivity of qualitative judgments based on personal experience, and provides accurate data references for objectively evaluating the mineralization environment and mineralization potential of sandstone uranium. It directly serves the needs of mineral exploration deployment and has important practical application and promotion value.

[0069] To further understand the present invention, the method for quantitatively characterizing the reducing ability of gray sand bodies provided by the present invention will be described in detail below with reference to embodiments. The scope of protection of the present invention is not limited by the following embodiments.

[0070] Example 1

[0071] like Figure 1 As shown, the present invention provides a method for quantitatively characterizing the reducing power of gray sand bodies within target strata of sandstone-type uranium deposits in basins. This method specifically includes the following steps:

[0072] Step (1) is to determine the target strata for uranium exploration in the uranium ore survey area; the specific steps are as follows:

[0073] The Beier Depression in the Hailar Basin was selected as the research object, and the Yimin Formation of the Lower Cretaceous was selected as the target layer for mineral exploration. This layer is a typical braided fluvial deposit with more sand and less mud. The mud-sand-mud strata have a stable structure and multiple sets of light gray and gray sand bodies. The thickness of a single layer is generally 20-40m, and the total thickness is about 120m.

[0074] Step (2) Collect gray sandstone samples from the target mineral layer in the borehole in the uranium ore survey area mentioned in Step (1) above; the specific steps are as follows:

[0075] (2.1) Based on the distribution of stable mudstone with a thickness of more than 10m, the target layer in the borehole is divided into two sets of gray sand bodies from top to bottom.

[0076] (2.2) The Yimin Formation prospecting target layer in borehole ZKB7-7 of the Beier Depression developed two sets of stable sand bodies, separated by a layer of gray mudstone approximately 18m thick. The upper first set of sand bodies is buried at a depth of 421-461m, and the lower second set is buried at a depth of 479-504m. Based on requirements, five sandstone samples are planned to be collected from the first set of sand bodies, namely Sd... 11 (421-429m), Sd 12 (429-437m), Sd 13 (437-445m), Sd 14 (445-453m), Sd 15 (453-461m); Three sandstone samples are planned to be collected from the second sand body, namely Sd 21 (479-487.3m), Sd 22 (483.3-491.6m), Sd 23 (491.6-504m); It is worth noting that the thin mudstone layers in the middle of the sand body were ignored and not included in the sampling.

[0077] Step (3) involves crushing the gray sandstone collected in step (2) into 200-mesh powder samples indoors and then conducting environmental geochemical index tests. This time, eight gray sandstone powder samples collected from borehole ZKB7-7 in the Beier Depression were tested for organic carbon content, total sulfur content, redox potential (Eh), and valence iron ratio (Fe). 3+ / Fe 2+ The results of the determination of four environmental geochemical indicators of sandstone are shown in Table 1.

[0078] Table 1. Environmental geochemical index test results of the Yimin Formation sand bodies in borehole ZKB7-7, Beier Depression, Hailar Basin.

[0079] Correction formula: Fe 2+ / Fe 3+ =10(FeO+3FeS2% / 5) / 9(TFe-1.113FeO-0.6658FeS2%),FeS2%=15S% / 8 Step (4) The sandstone environmental geochemical index data obtained in step (3) above are processed by fuzzy mathematics with the two sets of gray sand bodies in step (2) above as the objects;

[0080] The specific steps are as follows:

[0081] (4.1) Calculate the average value of the two sets of gray sand body environmental geochemical indicators in step (2) above.

[0082] The first set of gray sand bodies in the Yimin Formation of borehole ZKB7-7 in the Beier Depression consists of 5 gray sandstone samples, with Eh and C... 有 S 全 Fe 3+ / Fe 2+ The average values ​​were 12 mv, 0.0778%, 0.0262%, and 5.014%, respectively; the second set of gray sand bodies consisted of three gray sandstone samples, with Eh and C... 有 S 全 Fe 3+ / Fe 2+ The average values ​​were 16.33mv, 0.0593%, 0.0336%, and 1.646, respectively.

[0083] (4.2) Establish the factor set (U) and the rank set (V).

[0084] Four environmental geochemical indicators of the Yimin Formation gray sandstone in the Beier Depression were determined as the factor set U = {organic carbon content, total sulfur content, redox potential, Fe...} 3+ / Fe 2+}, n=4; a corresponding 5-level set V={strong (Level I), relatively strong (Level II), average (Level III), relatively poor (Level IV), poor (Level V)} was constructed, m=5, and the standard values ​​are shown in Table 2.

[0085] Table 2 Evaluation Standards for the Reduction Capacity of Target Gray Sand Bodies in Mineral Exploration in Basins

[0086] grade powerful Strong generally Poor Difference index Level I Level II Level III Level IV Level V <![CDATA[C 有 / %]]> 1 0.5 0.25 0.1 0.01 <![CDATA[S 全 / %]]> 0.8 0.4 0.2 0.1 0.01 <![CDATA[Fe 3+ / Fe 2+ ]]> 0.2 0.5 0.8 1.2 2 Eh / mV -50 -20 -5 10 30

[0087] (4.3) Establish membership functions and construct the evaluation matrix R. Determine the degree to which each evaluation factor belongs to different evaluation levels in the evaluation level set, using r as the basis for the evaluation matrix R. ij The evaluation matrix (R) is the composite of the membership degrees of all indicators in the evaluation factor set U.

[0088] In the formula, i = 1, 2, 3, 4, j = 1, 2, 3, 4, 5; r ij The membership degree of the i-th evaluation factor to the j-th evaluation level can be calculated using the linear function μ(x), and can be divided into the following two cases:

[0089] 1) For indicators where a larger value indicates stronger restoration capability, the membership function is:

[0090]

[0091] In the formula: t i S represents the test result of the i-th evaluation factor. ij Let be the evaluation standard value of level j corresponding to the i-th evaluation factor;

[0092] When t i ≤S ij At that time, t i Membership degree μ of level i ij (t i ) = 1; when t i >S ij+1 When x has no membership degree to level j, μ ij (t i ) = 0; when S ij <t i ≤S ij+1 , t i It has a membership relationship with both i and j levels, μ ij (t i )=(S ij+1 -t i ) / (S ij+1 -S ij ).

[0093] 2) For indicators where smaller values ​​indicate stronger restoration capabilities, the membership function form is exactly the opposite of the above.

[0094] Based on the above-mentioned descending half-trapezoidal distribution function, the evaluation matrices R1 and R2 of gray sand body 1 and gray sand body 2 of the Yimin Formation are calculated respectively:

[0095]

[0096] (4.4) Determine the weights of the evaluation indicators and establish a weight matrix A. Considering that the contribution rates of each environmental geochemical indicator to reducing capacity are different, and therefore have different emphases, it is necessary to assign different weights to each participating factor to form a weight matrix W of the participating factors, which is [w1, w2, ..., w...]. i ... w n ];w i This represents the weight value of the i-th evaluation factor; for indicators with larger values, the stronger the reproducibility. For indicators with smaller values, the stronger the restoration ability The average or reference standard value of the evaluation criteria for the i-th evaluation factor is given by the following formula:

[0097] At the same time, w needs to be normalized, as shown in the following formula:

[0098] Finally, the normalized weight matrix A = [a1, a2, ..., a...] is obtained. n ].

[0099] The Eh and C values ​​of this Level 5 standard 有 S 全 Fe 3+ / Fe 2+ The average values ​​were -7mv, 0.372%, 0.302%, and 0.94, respectively; based on the above w i The calculation formula yields W1 = (0.583, 0.209, 0.087, 0.187) for gray sand body 1 and W2 = (0.428, 0.159, 0.111, 0.571) for gray sand body 2; based on the above a i After normalization of the calculation formula, the corresponding gray sand body 1 has A1 = (0.547, 0.196, 0.081, 0.175) and gray sand body 2 has A2 = (0.337, 0.125, 0.087, 0.450).

[0100] (4.5) Calculate the fuzzy evaluation set Y, that is, establish the reducibility evaluation model and calculate the fuzzy evaluation set for each sand body. The formula is as follows: In the formula: For fuzzy mathematical operators, model M2 is selected, namely the Zadeh operators "·" and "⊕"; Y is the comprehensive evaluation result, which is a fuzzy subset of the evaluation level set.

[0101] Based on the above calculation formula for Y, the gray sand body 1 of the Yimin Formation in borehole ZKB7-7 of the Bell Depression was obtained.

[0102] gray sand body 2

[0103] Step (5) Based on the fuzzy evaluation set Y calculated in step (4) above, take Y = max(y i ), i = 1, 2, 3, 4, 5, that is, the corresponding evaluation level is obtained by the maximum membership principle; then the weighted average principle is used to calculate the result. Take k=2; finally, rank the sand bodies according to the evaluation results Y and B values ​​of the two sets of sand bodies.

[0104] Based on the principle of maximum membership, the Y1 of gray sand body 1 in borehole ZKB7-7 of the Yimin Formation in the Bell Depression is 0.921, and the Y2 of gray sand body 2 is 0.548. Both belong to level IV, indicating poor reduction ability, but the two values ​​are relatively large, resulting in a significant loss of information. Further, using the weighted average principle, the corresponding values ​​are calculated as follows: B1 = (0.921×0.921×3+0.344×0.344×4) / (0.921×0.921+0.344×0.344) = 3.122, B2 = (0.548×0.548×3+0.478×0.478×4) / (0.548×0.548+0.478×0.478) = 3.432. Finally, it is concluded that the reduction ability of gray sand body 2 is slightly stronger than that of gray sand body 1.

[0105] The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principle of the present invention. For example, the environmental geochemical index data processing can also combine single-factor and multi-level fuzzy comprehensive evaluation methods, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0106] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quantitatively characterizing the reducing power of gray sand bodies, characterized in that, Includes the following steps: Step (1): Determination of the target strata within the uranium exploration area of ​​the basin; Step (2): Select the borehole that exposes the target layer, divide the gray sand bodies developed in the target layer in the field, and take samples of each sand body by continuous equidistant grooves as needed to obtain gray sandstone samples. Step (3): The gray sandstone sample is crushed and tested for different environmental geochemical indicators; Step (4): Taking the gray sand bodies divided in step (2) as the object, based on the geochemical data measured in step (3), calculate the average value of different environmental geochemical indicators for each sand body, and carry out fuzzy mathematical evaluation on this basis. Specifically, it includes: Step (4.1): Based on the measured environmental geochemical data, calculate the average values ​​of different environmental geochemical indicators of the X-set gray sand bodies, and use them as evaluation indicators; Step (4.2): Establish the factor set U and the level set V of the evaluation indicators, where U = {u1, u2, ..., u...} n }, n evaluation factors; based on the standard of reducing capacity of favorable ore-bearing formations in sandstone-type uranium deposits, establish a corresponding m-level set, i.e., V={v1、v2、…、v m }; Step (4.3): Establish membership functions and construct the evaluation matrix R. In the formula, i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij The membership degree of the i-th evaluation factor to the j-th level is represented by μ(x), which is calculated using a linear function μ(x), and can be divided into the following two cases: 1) For indicators where a larger value indicates stronger restoration capability, the membership function is: In the formula: t i S represents the test result of the i-th evaluation factor. ij Let be the evaluation standard value of the j-th level corresponding to the i-th evaluation factor; 2) For indicators where smaller values ​​indicate stronger restoration capabilities, the membership function form is exactly the opposite of the above case; Step (4.4): Determine the weights of the evaluation indicators and establish the weight matrix A; Each evaluation factor is assigned a different weight, forming a weight matrix W of the evaluation factors, which is [w1, w2, ..., w...]. i ... w n ];w i This represents the weight value of the i-th evaluation factor; for indicators with larger values, the stronger the reproducibility. For indicators with smaller values, the stronger the restoration ability The average or reference standard value of the evaluation criteria for the i-th evaluation factor. The formula is as follows: At the same time, w needs to be normalized, as shown in the following formula: Finally, the normalized weight matrix A = [a1, a2, ..., a...] is obtained. n ]; Step (4.5): Calculate the fuzzy evaluation set Y, and calculate the fuzzy evaluation set for each sand body. The formula is as follows: In the formula: For fuzzy mathematical operators, model M2 is selected, namely the Zadeh operator "·" and a·b=ab is the product operator. It is a closed addition operator; Step (5): Based on the fuzzy evaluation set Y obtained in step (4) above, Y = max(y) is obtained by the maximum membership principle. i ), i = 1, 2, ..., m; then, the weighted average principle is used to calculate the result. Take k=2; finally, based on the evaluation results Y and B values ​​of the n sets of sand bodies, rank the reduction capabilities according to their quality.

2. The method for quantitatively characterizing the reducing power of gray sand bodies according to claim 1, characterized in that, In step (1), the standard for the target layer is that the target layer has X sets of sand bodies, X≥1, and the thickness of a single sand body is more than 5m.

3. The method for quantitatively characterizing the reducing power of gray sand bodies according to claim 2, characterized in that, Step (2) specifically includes: Step (2.1): Based on the distribution of stable mudstone, divide the target layer in the borehole into X sets from top to bottom, where X≥1; Step (2.2): For the X sets of gray sand bodies, each set of sand bodies is divided into equal sections and continuously grooved for sampling according to the actual sample requirement m. The sample numbers of the first set of sand bodies are sequentially set as: Sd 11 、Sd 12 ... Sd 1m The second set of sand body samples were numbered sequentially as follows: Sd 21 、Sd 22 ... Sd 2m And so on; Each sandstone sample is either a mixture of sandstones of different grain sizes or sandstones of the same grain size.

4. The method for quantitatively characterizing the reducing power of gray sand bodies according to claim 3, characterized in that, The thickness of the stabilized mudstone is more than 10m.

5. The method for quantitatively characterizing the reducing power of gray sand bodies according to claim 3, characterized in that, In step (3), the gray sandstone sample is crushed into 200-mesh powder. Environmental geochemical indicators include organic carbon content, total sulfur content, redox potential, valence iron ratio, acid-hydrolyzed hydrocarbons, and GOI.

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