Method for quantitatively characterizing reducing capacity of grey sand body

Abstract

The invention relates to the technical field of prospecting, in particular to a method for quantitatively characterizing the reducing capacity of a grey sand body. The method comprises the following steps: determining a prospecting target layer in a basin uranium ore exploration area; the method comprises the following steps: selecting a drill hole for exposing a target layer, dividing gray sand bodies developed in the target layer in the field, and carrying out equidistant continuous grooving sampling on each set of sand bodies according to requirements to obtain a gray sandstone sample; the gray sandstone sample is crushed, and geochemical indexes of different environments are tested; taking the divided gray sand body as an object, solving an average value of different environmental geochemical indexes of each set of sand body based on actually measured geochemical data, and carrying out processing of a fuzzy mathematical evaluation method on the basis; according to the obtained comprehensive evaluation result, a weighted average method is adopted in a combined mode for quantitative characterization of the reducing capacity of the sand body, and the uranium metallogenic environment and potential of the target layer are objectively evaluated. The method overcomes the subjectivity of artificial experience qualitative judgment, and the evaluation result is more objective, accurate and comparable.

Description

Technical Field

[0001] The invention relates to the technical field of ore prospecting, and in particular to a method for quantitatively characterizing the reduction capacity of a gray sand body. Background Art

[0002] Redox reaction is the most fundamental mineralization mechanism of sandstone-type uranium deposits in the basin. The reduction capacity of the gray sand body in the target layer is an important indicator that determines whether the dissolved hexavalent uranium element in the uranium-containing and oxygen-containing fluid can be reduced and fixed, and then enriched into mineralization. It is also the main criterion for the prediction and evaluation of the prospecting prospects of this type of uranium deposits. Since the reduction capacity is a vague and imprecise concept, geologists have traditionally mainly used multiple environmental geochemical indicators (C 有 , S 全 , Eh, etc.) for qualitative evaluation of restoration capacity, which is subject to human subjectivity; that is, the same person will often make different evaluation results when facing the same batch of data, and different people will have different opinions on the same set of data.

[0003] At the same time, since the prospecting sand bodies usually have large heterogeneity, the environmental geochemical indicators of sandstones taken from different parts are generally quite different, with some data being high and some being low, and the results of different geochemical indicators of the same sample are often different, such as a high organic carbon content and a low total sulfur content; geologists simply organize and analyze these data based on experience, and often cannot accurately determine the true reduction capacity of the entire set of sand bodies, which in turn affects prospecting deployment. Therefore, it is very necessary to use appropriate technical methods to quantitatively and comprehensively process multiple environmental geochemical indicators of multiple samples based on the mineralization conditions and mineralization characteristics of the sandstone uranium ore itself, objectively evaluate the quality of the gray sand body reduction ability, prevent misjudgment or omission of effective prospecting target layers, and serve prospecting predictions. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for quantitatively characterizing the reduction capacity of gray sand bodies, realize the comprehensive quantitative evaluation of multiple geochemical indicators of multiple groups of sandstone samples in multiple sets of sand bodies, overcome the subjectivity of human experience-based qualitative judgment, and make the evaluation results more objective, accurate and comparable.

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

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

[0007] Step (2): selecting a borehole that exposes the target layer, dividing the gray sand bodies developed in the target layer in the field, and sampling each set of sand bodies by continuous groove cutting at equal intervals as required to obtain gray sandstone samples;

[0008] Step (3): crushing the gray sandstone sample and conducting tests on different environmental geochemical indicators;

[0009] Step (4): taking the gray sand body divided in step (2) as the object, based on the geochemical data measured in step (3), calculating the average value of different environmental geochemical indicators of each set of sand bodies, and carrying out fuzzy mathematical evaluation method processing 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 ability, and the uranium mineralization environment and potential of the target layer are objectively evaluated.

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

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

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

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

[0015] Among them, each sandstone sample is a mixed sample of sandstones of different grain sizes or sandstones of the same grain size.

[0016] Preferably, the thickness of the stable mudstone is above 10 m.

[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, the step (4) specifically comprises:

[0020] Step (4.1): Based on the measured environmental geochemical data, the average values ​​of different environmental geochemical indicators of the middle X set of gray sand bodies are calculated as the evaluation indicators;

[0021] Step (4.2): Establish the factor set (U) and level set (V) of the evaluation indicators, where U = {u1, u2, ..., u n}, n evaluation factors; according to the standard of favorable ore-bearing construction reduction capacity of sandstone-type uranium deposits, the corresponding m-level grade set is established, that is, V = {v1, v2, ..., v m};

[0022] Step (4.3): Establish the attribute function and construct the evaluation matrix R. Where i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij It represents the attribute of the i-th evaluation factor to the j-th evaluation level, which is calculated by the linear function μ(x) and is divided into the following two cases:

[0023] 1) For indicators with larger values ​​and stronger restoration ability, the attribute function is:

[0024]

[0025] Where: t i is the test result of the ith evaluation factor, s ij is the evaluation standard value of level j corresponding to the ith evaluation factor; for t i , take μ ij (t i )=1, the rest μ ij (t i )=0, for t≥s im , take μ im (t i )=1, the rest μ ij (t i )=0;

[0026] 2) For indicators whose values ​​are smaller and whose restoration ability is stronger, the form of the attribute function is exactly the opposite of the above situation;

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

[0028] Different weights are assigned to each participating factor to form the weight matrix W of the participating evaluation factors, which is [w1, w2, ..., w i ,…,w n ]; w i is the weight value of the i-th evaluation factor. The larger the value, the stronger the restoration ability. For indicators with smaller values, the restoration ability is stronger is the average value or reference standard value of the evaluation standard of the i-th evaluation factor,

[0029] The formula is as follows:

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

[0031] Step (4.5): Calculate the fuzzy evaluation set Y. Calculate the fuzzy evaluation set of each sand body. The formula is

[0032] Where: As fuzzy mathematical operators, model M2 is selected, namely Zadeh operators “·” and “⊕”; a·b=ab, which is a product operator, and a⊕b=(a+b)∧1, which is a closed addition operator.

[0033] Preferably, the step (5) is specifically:

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

[0035] Compared with the prior art, the present invention provides uranium geologists with a method for quantitatively evaluating the reduction capacity of gray sand bodies in the target layer during the exploration and research of sandstone uranium mines, thereby objectively evaluating the uranium mineralization environment and potential of the prospecting target layer. The fuzzy mathematical evaluation method based on environmental geochemical indicators provided this time quantitatively characterizes the reduction capacity of gray sand bodies, and realizes the comprehensive quantitative evaluation of multiple geochemical indicators of multiple groups of sandstone samples in multiple sets of sand bodies. The weighted method used takes into account the influence of all participating factors on the reduction capacity, overcomes the subjectivity of human experience qualitative judgment, and the evaluation results are more objective, accurate and comparable, thereby preventing misjudgment or omission of effective target layers, indicating the correct prospecting direction, and directly serving actual production needs. It has very important promotion and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart showing the method for quantitatively characterizing the reducing capacity of gray sand bodies according to the present invention. DETAILED DESCRIPTION

[0037] In order to further understand the present invention, the embodiments of the present invention are described below in conjunction with examples, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the present invention.

[0038] The embodiment of the present invention discloses a method for quantitatively characterizing the reducing capacity of gray sand bodies, such as Figure 1 As shown, the following steps are included:

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

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

[0041] Step (2): selecting a borehole that exposes the target layer, dividing the gray sand bodies developed in the target layer in the field, and sampling each set of sand bodies by continuous groove cutting at equal intervals as required to obtain gray sandstone samples;

[0042] Specifically include:

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

[0044] The thickness of stable mudstone is more than 10m;

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

[0046] Among them, each sandstone sample is a mixed sample of sandstones of different grain sizes or sandstones of the same grain size.

[0047] Step (3): crushing the gray sandstone sample and conducting tests on 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 body divided in step (2) as the object, based on the geochemical data measured in step (3), calculating the average value of different environmental geochemical indicators of each set of sand bodies, and carrying out fuzzy mathematical evaluation method processing on this basis;

[0051] Specifically include:

[0052] Step (4.1): Based on the measured environmental geochemical data, the average values ​​of different environmental geochemical indicators of the middle X set of gray sand bodies are calculated as the evaluation indicators;

[0053] Step (4.2): Establish the factor set (U) and level set (V) of the evaluation indicators, where U = {u1, u2, ..., u n}, n evaluation factors; according to the standard of favorable ore-bearing construction reduction capacity of sandstone-type uranium deposits, the corresponding m-level grade set is established, that is, V = {v1, v2, ..., v m};

[0054] Step (4.3): Establish the attribute function and construct the evaluation matrix R. Where i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij It represents the attribute of the i-th evaluation factor to the j-th evaluation level, which is calculated by the linear function μ(x) and is divided into the following two cases:

[0055] 1) For indicators with larger values ​​and stronger restoration ability, the attribute function is:

[0056]

[0057] Where: t i is the test result of the ith evaluation factor, s ij is the evaluation standard value of level j corresponding to the ith evaluation factor; for t i , take μ ij (t i )=1, the rest μ ij (t i )=0, for t≥s im , take μ im (t i )=1, the rest μ ij (t i )=0;

[0058] 2) For indicators whose values ​​are smaller and whose restoration ability is stronger, the form of the attribute function is exactly the opposite of the above situation;

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

[0060] Different weights are assigned to each participating factor to form the weight matrix W of the participating evaluation factors, which is [w1, w2, ..., w i ,…,w n ]; w i is the weight value of the i-th evaluation factor. The larger the value, the stronger the restoration ability. For indicators with smaller values, the restoration ability is stronger is the average value or reference standard value of the evaluation standard of the i-th evaluation factor,

[0061] The formula is as follows:

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

[0063] Step (4.5): Calculate the fuzzy evaluation set Y. Calculate the fuzzy evaluation set of each sand body. The formula is

[0064] Where: As fuzzy mathematical operators, model M2 is selected, namely Zadeh operators “·” and “⊕”, a·b=ab, which is a product operator, and a⊕b=(a+b)∧1, which 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 ability, and the uranium mineralization environment and potential of the target layer are objectively evaluated.

[0066] Specifically include:

[0067] Based on the fuzzy evaluation set Y obtained in step (4), we can obtain Y=max(y i ), i = 1, 2, ..., m; then the weighted average principle is used to calculate Take k = 2, k is the unknown coefficient k (= 1 or k = 2), the purpose is to control the larger b j When k→∞, the weighted average principle is the maximum membership principle; finally, the evaluation grade results Y and B values ​​of n sets of sand bodies are combined to rank the reduction capabilities in order of priority.

[0068] The present invention can be widely used in the prospecting, prediction, evaluation and scientific research of sandstone-type uranium deposits in Mesozoic and Cenozoic sedimentary basins at home and abroad. The method provided by the present invention can objectively and accurately reflect the true reduction capacity of multiple sets of gray sand bodies in the prospecting target layer, comprehensively considers multiple geochemical indicators, reduces the subjectivity of personal qualitative judgment based on experience, and the obtained quantitative evaluation results provide accurate data reference for objectively evaluating the sandstone uranium mineralization environment and mineralization potential, directly serve the needs of prospecting deployment, and have important practical application and promotion value.

[0069] In order to further understand the present invention, the method for quantitatively characterizing the reducing ability of gray sand bodies provided by the present invention is described in detail below in conjunction with examples, and the protection scope of the present invention is not limited by the following examples.

[0070] Example 1

[0071] like Figure 1 As shown, the present invention provides a method for quantitatively characterizing the reduction capacity of gray sand bodies in a sandstone-type uranium ore prospecting or ore-bearing target layer in a basin, and the method specifically comprises the following steps:

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

[0073] Beier Sag in Hailar Basin was selected as the research object, and the Lower Cretaceous Yimin Formation was selected as the prospecting target layer; this layer is a typical braided river phase deposit, with more sand and less mud, stable mud-sand-mud stratigraphic structure, and multiple sets of light gray and gray sand bodies developed. The thickness of a single layer is generally 20-40m, and the total thickness is about 120m.

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

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

[0076] (2.2) Two sets of stable sand bodies are developed in the target layer of the Yimin Formation in the ZKB7-7 borehole in the Beier Sag, separated by a layer of gray mudstone with a thickness of about 18m; the first set of sand bodies in the upper part is buried at a depth of 421-461m, and the second set of sand bodies in the lower part is buried at a depth of 479-504m. According to the requirements, 5 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); the second set of sandstone samples to be collected are 3 pieces, namely Sd 21 (479-487.3m), Sd 22 (483.3-491.6m), Sd 23 (491.6-504m); It is worth noting that the thin layer of mudstone in the middle of the sand body was ignored and not mixed into the sampling.

[0077] Step (3) is to crush the gray sandstone collected in the above step (2) into a 200-mesh powder sample indoors and then conduct an environmental geochemical index test. In this test, 8 gray sandstone powder samples collected from the ZKB7-7 borehole in the Beier Sag were tested for organic carbon content, total sulfur content, redox potential (Eh), valence iron ratio (Fe 3+ / Fe 2+ ) were measured, and the results of four environmental geochemical indicators of sandstone were obtained as shown in Table 1.

[0078] Table 1 Test results of environmental geochemical indicators of the Yimin Formation sand body in ZKB7-7 borehole in Beier Sag, Hailar Basin

[0079]

[0080] Correction formula: Fe 2+ / Fe 3+ =10(FeO+3FeS2% / 5) / 9(TFe-1.113FeO-0.6658FeS2%), FeS2%=15S% / 8

[0081] Step (4) fuzzy mathematical processing is performed on the sandstone environmental geochemical index data obtained in the above step (3) with the two sets of gray sand bodies in the above step (2) as objects;

[0082] The specific steps are as follows:

[0083] (4.1) Calculate the average values ​​of the two sets of environmental geochemical indicators of gray sand bodies in the above step (2) respectively.

[0084] The first set of gray sand bodies in the Yimin Formation in the ZKB7-7 borehole in the Beier Sag consists of five gray sandstone samples. 有 , S 全 , Fe 3+ / Fe 2+ The average values ​​are 12mv, 0.0778%, 0.0262%, and 5.014% respectively; the second set of gray sand bodies consists of 3 gray sandstone samples, and their Eh, C 有 , S 全 , Fe 3+ / Fe 2+ The average values ​​are 16.33mv, 0.0593%, 0.0336% and 1.646 respectively.

[0085] (4.2) Establish the factor set (U) and the level set (V).

[0086] The four environmental geochemical indicators of the gray sand body of the Yimin Formation in the Beier Sag were determined as the factor set U = {organic carbon content, total sulfur content, redox potential, Fe 3+ / Fe 2+}, n=4; the corresponding 5-level grade set V={strong (Grade I), relatively strong (Grade II), average (Grade III), relatively poor (Grade IV), poor (Grade V)}, m=5, and the standard values ​​are shown in Table 2.

[0087] Table 2 Evaluation grade standard of gray sand body reduction capacity in the target layer of mineral exploration in the basin

[0088] grade powerful Strong generally Poor Difference index Level I Level II Grade 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

[0089] (4.3) Establish the attribute function 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 ij Represents; the evaluation matrix (R) is the synthesis of all index attributes in the evaluation factor set U.

[0090] Where i = 1, 2, 3, 4, j = 1, 2, 3, 4, 5; r ij It represents the attribute of the i-th evaluation factor to the j-th evaluation level, which can be calculated by the linear function μ(x) and is divided into the following two cases:

[0091] 1) For indicators with larger values ​​and stronger restoration ability, the attribute function is:

[0092]

[0093] Where: t i is the test result of the ith evaluation factor, s ij is the evaluation standard value of level j corresponding to the ith evaluation factor; for t i , take μ ij (t i )=1, the rest μ ij (t i )=0, for t≥s im , take μ im (t i )=1, the rest μ ij (t i )=0. 2) For indicators whose values ​​are smaller and whose restoration ability is stronger, the form of the attribute function is exactly the opposite of the above situation.

[0094] According to the above descending semi-trapezoidal distribution function, the evaluation matrices R1 and R2 of gray sand body 1 and gray sand body 2 of Yimin Formation were calculated respectively:

[0095]

[0096] (4.4) Determine the weights of the evaluation indicators and establish the weight matrix A. Considering that the contribution rates of various environmental geochemical indicators to the reduction capacity are different and have different emphases, it is necessary to assign different weights to each participating factor to form the weight matrix W of the participating evaluation factors, which is [w1, w2, …, w i ,…,w n ]; w i is the weight value of the i-th evaluation factor. The larger the value, the stronger the restoration ability. For indicators with smaller values, the restoration ability is stronger is the average value or reference standard value of the evaluation standard of the i-th evaluation factor, and the formula is as follows:

[0097] At the same time, w needs to be normalized, the formula is as follows:

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

[0099] The Eh and C of the 5-level standard values 有 , S 全 , Fe 3+ / Fe 2+ The average values ​​are: -7mv, 0.372%, 0.302%, 0.94; according to the above w i The calculation formula is as follows: W1 of gray sand body 1 = (0.583, 0.209, 0.087, 0.187), and W2 of gray sand body 2 = (0.428, 0.159, 0.111, 0.571); According to 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 the 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 a reduction capacity evaluation model, and calculate the fuzzy evaluation set of each sand body. The formula is: Where: is a fuzzy mathematical operator, and model M2 is selected, namely, Zadeh operator “·” and “⊕”; Y is the comprehensive evaluation result, which is a fuzzy subset of the evaluation level set.

[0101] According to the above Y calculation formula, the gray sand body 1 of Yimin Formation in ZKB7-7 borehole in Beier Sag is obtained.

[0102] Gray sand body 2

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

[0104] According to the maximum recording principle, the Y1 of the gray sand body 1 of the Yimin Formation in the ZKB7-7 borehole of the Beier Sag is 0.921, and the Y2 of the gray sand body 2 is 0.548, both of which belong to grade IV, with poor restoration ability, but the two values ​​are large, and more information is lost; further, through the weighted average principle, it is calculated that 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 restoration ability of the gray sand body 2 is slightly stronger than that of the gray sand body 1.

[0105] The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, the present invention can also be improved and modified in several ways. For example, the environmental geochemical index data processing can also be combined with single factor and multi-level fuzzy comprehensive evaluation methods, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0106] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one 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 present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quantitatively characterizing the reducing capacity of gray sand bodies, characterized in that: The following steps are involved: Step (1): Determination of the prospecting target layer within the uranium exploration area of ​​the basin; Step (2): selecting a borehole that exposes the target layer, dividing the gray sand bodies developed in the target layer in the field, and sampling each set of sand bodies by continuous groove cutting at equal intervals as required to obtain gray sandstone samples; Step (3): crushing the gray sandstone sample and conducting tests on different environmental geochemical indicators; Step (4): taking the gray sand body divided in step (2) as the object, based on the geochemical data measured in step (3), calculating the average value of different environmental geochemical indicators of each set of sand bodies, and carrying out fuzzy mathematical evaluation method processing on this basis; 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 ability, and the uranium mineralization environment and potential of the target layer are objectively evaluated.

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

3. The method for quantitatively characterizing the reducing ability of gray sand bodies according to claim 2, characterized in that: The step (2) specifically comprises: Step (2.1): According to the distribution of stable mudstone, the target in the borehole is divided into X sets of gray sand bodies from top to bottom, X ≥ 1; Step (2.2): For the X sets of gray sand bodies, each set of sand bodies is divided into equal parts and continuously grooved for sampling according to the actual sample quantity m required. The sample numbers of the first set of sand bodies are set as follows: Sd 11 , Sd 12 ,……,Sd 1m , the second set of sand body sample numbers are set as: Sd 21 , Sd 22 ,……,Sd 2m； And so on; Among them, each sandstone sample is a mixed sample of sandstones of different grain sizes or sandstones of the same grain size.

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

5. The method for quantitatively characterizing the reducing ability of gray sand bodies according to claim 3, characterized in that: In the 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.

6. The method for quantitatively characterizing the reducing ability of gray sand bodies according to claim 5, characterized in that: The step (4) specifically comprises: Step (4.1): Based on the measured environmental geochemical data, the average values ​​of different environmental geochemical indicators of the middle X set of gray sand bodies are calculated as the evaluation indicators; Step (4.2): Establish the factor set (U) and level set (V) of the evaluation indicators, where U = {u1, u2, ..., u n }, n evaluation factors; according to the standard of favorable ore-bearing construction reduction capacity of sandstone-type uranium deposits, the corresponding m-level grade set is established, that is, V = {v1, v2, ..., v m }; Step (4.3): Establish the attribute function and construct the evaluation matrix R. Where i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., m; r ij It represents the attribute of the i-th evaluation factor to the j-th evaluation level, which is calculated by the linear function μ(x) and is divided into the following two cases: 1) For indicators with larger values ​​and stronger restoration ability, the attribute function is: Where: t i is the test result of the ith evaluation factor, s ij is the evaluation standard value of level j corresponding to the ith evaluation factor; for t i , take μ ij (t i )=1, the rest μ ij (t i )=0, for t≥s im , take μ im (t i )=1, the rest μ ij (t i )=0;s im is the evaluation standard value of the mth level corresponding to the ith evaluation factor; 2) For indicators whose values ​​are smaller and whose restoration ability is stronger, the form of the attribute function is exactly the opposite of the above situation; Step (4.4): Determine the weights of the evaluation indicators and establish the weight matrix A; Different weights are assigned to each participating factor to form the weight matrix W of the participating evaluation factors, which is [w1, w2, ..., w i ,…,w n ]; w i is the weight value of the i-th evaluation factor. The larger the value, the stronger the restoration ability. For indicators with smaller values, the restoration ability is stronger is the average value or reference standard value of the evaluation standard of the i-th evaluation factor, The formula is as follows: At the same time, w needs to be normalized, the formula is as follows: Finally, the normalized weight matrix A = [a1, a2, ..., a n ]; Step (4.5): Calculate the fuzzy evaluation set Y. Calculate the fuzzy evaluation set of each sand body. The formula is Where: As fuzzy mathematical operators, model M2 is selected, namely Zadeh operators "·" and "⊕"; a·b=ab, which is a product operator, and a⊕b=(a+b)∧1, which is a closed addition operator.

7. The method for quantitatively characterizing the reducing ability of gray sand bodies according to claim 6, characterized in that: The step (5) is specifically as follows: Based on the fuzzy evaluation set Y obtained in step (4), we can obtain Y=max(y i ), i = 1, 2, ..., m; then the weighted average principle is used to calculate Take k=2; finally, rank the reduction capabilities of the n sets of sand bodies according to their evaluation grade results Y and B values.

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