Method, device, computer equipment and storage medium for determining mineral composition of igneous rocks

Abstract

The present invention provides a method, device, computer equipment and storage medium for determining the mineral composition of igneous rocks. According to the relative content of igneous rock formation elements in the original element logging / XRF data, pure minerals are used to establish a coefficient matrix between the mineral mass and the element content of the formation, and finally the weight content of the minerals in the igneous rock formation is calculated using an optimization algorithm, which can evaluate 14 igneous rock components. The inversion process realizes modular operation, which plays a positive role in forming element logging interpretation software with its own intellectual property rights to adapt to the rapid and efficient development of domestic igneous rocks.

Description

Technical Field

[0001] The present invention relates to the technical field of igneous rock stratum mineral type and content identification, and in particular to an igneous rock mineral composition determination method, device, computer equipment and storage medium. Background Art

[0002] Jin Yunzhi, Gao Chuqiao, et al. (2018). Based on the analysis of formation components, a relationship model between igneous rock formation element logging data and its various lithologies was established; the content of igneous rock lithology components was quantitatively calculated based on the content of formation elements such as Al, Ca, Fe, H, Si, S, and Ti in formation element logging using an optimization algorithm.

[0003] Chinese patent publication CN107194401 A discloses that on the basis of standard grayscale images such as QAPF of igneous rocks, the automatic classification and naming of igneous rocks can be quickly realized by projecting points of igneous rock mineral components, obtaining grayscale values ​​of projected point positions, and quickly obtaining igneous rock names based on hash table sets. Chinese patent publication CN107678072A discloses a method for predicting igneous rock reservoirs by comprehensively utilizing magnetic data, seismic data, core data, and logging data. It can not only reasonably utilize magnetic force to identify igneous rocks, but also utilize three-dimensional seismic grids to make up for the lack of spatial resolution, and achieve the best prediction effect of igneous rock reservoirs under the constraints of drilling data. Chinese patent document CN101520518 A discloses a method for identifying the lithology of igneous rocks by using the combined characteristics of gravity, magnetic and electrical anomalies. The method includes collecting and recording the physical characteristics of the core; clustering the density, magnetic susceptibility and resistivity of the rock using k-means clustering to obtain the core clustering code; performing gravity and magnetic anomaly stripping on the gravity and magnetic exploration results to obtain anomalies, and using the same clustering to perform three-dimensional spatial anomaly coding; and combining the rock physical property clustering code with the gravity, magnetic and electrical anomaly code to reflect the lithology of each igneous rock in the exploration area.

[0004] There are two interpretation methods for obtaining mineral mass content: one is the empirical interpretation method represented by Schlumberger, and the other is the optimization interpretation method represented by Halliburton. Schlumberger's interpretation method is to obtain the relative content of igneous rock formation elements and mineral mass content by empirical relationship; Halliburton's interpretation method is to directly invert the formation mineral mass content by using the optimization method from the formation element content. The interpretation method represented by Schlumberger relies on a large amount of regional experimental data. For some new formations, it may be necessary to re-establish the model. Moreover, the established model is not public, and its applicability needs further verification; Halliburton's interpretation method is more adaptable, but there is uncertainty in the inversion of minerals. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for determining the mineral composition of igneous rocks in response to the above technical problems.

[0006] A method for determining the mineral composition of igneous rocks, comprising:

[0007] Measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of acid and base radicals in the pure minerals;

[0008] Determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral;

[0009] Determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral;

[0010] The relative molecular weight of each of the main elements is calculated based on the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals;

[0011] Establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral;

[0012] According to each of the relationship equations, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient;

[0013] Detecting whether the value of the distribution coefficient meets a preset condition;

[0014] When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated;

[0015] Determining a mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral;

[0016] Calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral;

[0017] The mineral composition of the igneous rock is determined according to the content of the pure mineral.

[0018] In one embodiment, the step of calculating the mineral component content of the pure mineral according to the mineral coefficient matrix of the pure mineral comprises:

[0019] Determine the relationship between the main element and the pure mineral in the igneous rock formation and the error objective function according to the mineral coefficient matrix of the pure mineral;

[0020] According to the relationship between the main element and the pure mineral and the error objective function, the content of the pure mineral is calculated using an optimization method.

[0021] In one embodiment, after the step of detecting whether the value of the allocation coefficient meets the preset condition, the step further includes:

[0022] When the value of the distribution coefficient does not meet the preset condition, the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral is returned to be executed.

[0023] In one embodiment, the step of calculating the value of the distribution coefficient using an optimization algorithm according to each of the relationship equations includes:

[0024] According to each of the relationship equations, the value of the distribution coefficient is calculated using the least square method.

[0025] In one embodiment, when the value of the distribution coefficient meets the preset condition, the step of calculating the coefficient of the main element in the pure mineral includes:

[0026] When the value of the distribution coefficient meets the preset conditions, the coefficient of the main element in the pure mineral is calculated according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0027] In one embodiment, in the step of establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral,

[0028] The relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral is:

[0029] Y=ΣA i X i

[0030] Wherein, Y is the relative molecular weight of the main element, A is the molecular formula model, and X is the distribution coefficient of the main element in the molecular formula model.

[0031] In one embodiment, in the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral,

[0032] The molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element.

[0033] A device for determining the mineral composition of igneous rocks, comprising:

[0034] A pure mineral molecular weight calculation module is used to measure the mass of pure minerals contained in igneous rocks, calculate the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculate the relative molecular weight of the acid and base radicals in the pure minerals;

[0035] A molecular formula model determination module, used to determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral;

[0036] A main element determination module, used to determine at least one main element in the pure mineral according to the molecular formula model of the pure mineral;

[0037] A relative molecular weight calculation module, used to calculate the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals;

[0038] A distribution relationship establishment module, used to establish a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral;

[0039] A distribution coefficient calculation module, used to calculate the value of the distribution coefficient using an optimization algorithm according to each of the relationship equations;

[0040] A preset condition compliance detection module is used to detect whether the value of the allocation coefficient meets the preset condition;

[0041] An element coefficient calculation module, used for calculating the coefficient of each main element in the pure mineral when the value of the distribution coefficient meets the preset conditions;

[0042] A coefficient matrix determination module, used to determine the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral;

[0043] A mineral component content calculation module, used to calculate the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral;

[0044] The mineral composition determination module is used to determine the mineral composition contained in the igneous rock according to the content of the pure mineral.

[0045] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the following steps when executing the computer program:

[0046] Measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of acid and base radicals in the pure minerals;

[0047] Determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral;

[0048] Determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral;

[0049] The relative molecular weight of each of the main elements is calculated based on the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals;

[0050] Establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral;

[0051] According to each of the relationship equations, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient;

[0052] Detecting whether the value of the distribution coefficient meets a preset condition;

[0053] When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated;

[0054] Determining a mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral;

[0055] Calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral;

[0056] The mineral composition of the igneous rock is determined according to the content of the pure mineral.

[0057] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0058] Measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of acid and base radicals in the pure minerals;

[0059] Determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral;

[0060] Determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral;

[0061] The relative molecular weight of each of the main elements is calculated based on the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals;

[0062] Establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral;

[0063] According to each of the relationship equations, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient;

[0064] Detecting whether the value of the distribution coefficient meets a preset condition;

[0065] When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated;

[0066] Determining a mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral;

[0067] Calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral;

[0068] The mineral composition of the igneous rock is determined according to the content of the pure mineral.

[0069] The above-mentioned method, device, computer equipment and storage medium for determining the mineral composition of igneous rocks, based on the relative content of igneous rock formation elements from the original element logging / XRF data, use pure minerals to establish the coefficient matrix between the mineral mass and element content of the formation, and finally use the optimization algorithm to calculate the weight content of the minerals in the igneous rock formation, which can evaluate 14 kinds of igneous rock components. The inversion process realizes modular operation, which plays a positive role in forming element logging interpretation software with its own intellectual property rights to adapt to the rapid and efficient development of domestic igneous rocks. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A schematic diagram of a process for determining the mineral composition of igneous rocks in one embodiment;

[0071] Figure 2A The figure is a schematic diagram of the implementation process of a method for determining the mineral composition of igneous rocks in one embodiment;

[0072] Figure 2B A schematic diagram of the results of four mineral contents calculated by foreign software in one embodiment;

[0073] Figure 2C A schematic diagram of the igneous rock mineral content result obtained by calculation in one embodiment;

[0074] Figure 2D Inverting the mineral mass content map of the igneous rock formation for the element data of a well in a block in one embodiment;

[0075] Figure 3 It is a structural block diagram of an apparatus for determining mineral composition of igneous rocks in one embodiment;

[0076] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0078] It should be understood that the mineral types and contents of igneous formations are complex and are usually determined using element logging data. The present invention obtains the relative contents of formation elements based on original element logging data or XRF logging. However, due to the uncertainty in the relationship between the mineral mass and element content of igneous formations, it is necessary to determine the mineral content coefficient of the element based on different types of pure minerals, and finally calculate the mineral mass content of igneous formations using an optimization algorithm. The igneous rock mineral composition determination method of the present application can effectively determine the quantitative relationship between the igneous rock mineral content and the elements, and provides a modular system for identifying the mineral types and mass contents of igneous formations, which plays a positive role in accelerating the exploration and development of domestic igneous formations.

[0079] This method is based on the element content of igneous rock formations after spectrum analysis based on element logging or XRF data to determine the molecular formula of igneous minerals and the coefficient matrix of the main elements in the minerals they belong to, and inverts the igneous mineral content and type based on the optimization algorithm.

[0080] The specific implementation process is as follows:

[0081] Embodiment 1

[0082] In this embodiment, Figure 1 As shown, a method for determining the mineral composition of igneous rocks is provided, which comprises:

[0083] Step 101, measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of the acid and base radicals in the pure minerals.

[0084] Specifically, in this step, firstly, igneous pure minerals are obtained, the pure mineral mass of the igneous pure minerals is measured, and then the molar mass and relative molecular weight of the pure minerals are calculated according to the pure mineral mass, and the relative molecular weight of acid and base radicals is measured.

[0085] For example, select pure mineral types of igneous rocks, such as olivine, pyroxene, albite, calcium feldspar, amphibole, quartz, zircon, muscovite, biotite, apatite, zeolite, orthoclase, and nepheline.

[0086] Step 102: determining a molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral.

[0087] In this step, after the molar mass and relative molecular weight of the pure mineral are measured, the molecular formula model of the pure mineral is determined according to the molar mass and relative molecular weight of the pure mineral, and the molecular formula model may also become a molecular formula.

[0088] In this embodiment, the molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element. The main element is the element other than acid and alkali radicals in the igneous pure mineral, and the main element includes but is not limited to silicon, aluminum, iron, calcium, potassium, titanium, magnesium, manganese, sodium, phosphorus, zirconium and the like.

[0089] Step 103: determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral.

[0090] In this step, the main elements contained in the pure mineral are determined based on the molecular formula model of the pure mineral in the above step.

[0091] Step 104, calculating the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0092] Specifically, the relative molecular weight of the main element is the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals. Therefore, in this step, the relative molecular weight Y of the main element is calculated by calculating the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0093] Step 105, establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral.

[0094] In this step, a relationship between the relative molecular weight of each main element and the distribution coefficient is established. Specifically, a relationship between the relative molecular weight Y of each main element and the distribution coefficient X in the molecular formula model A(X) of the pure mineral is established.

[0095] For example, the molecular formula model of pure mineral structure, such as zeolite, is:

[0096] A(x / q)[(AlO2)a(SiO2)b]·n(H2O), where: A is Ca, Na, K,

[0097] In one embodiment, the relationship is Y = ΣA i X i , where Y is the relative molecular weight of the main element, A is the molecular formula model, X is the distribution coefficient of the main element in the molecular formula model, and i identifies the i-th main element.

[0098] Step 106: According to each of the relationship expressions, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient.

[0099] In this embodiment, in the previous step, a relationship between the relative molecular weight and the distribution coefficient of each main element is established respectively, thereby obtaining relationship between the relative molecular weight and the distribution coefficient of multiple main elements. Based on these established relationship, an optimization algorithm is used to calculate the value of the distribution coefficient.

[0100] In one embodiment, the step of calculating the value of the distribution coefficient using an optimization algorithm according to each of the relationship formulas includes: calculating the value of the distribution coefficient using a least square method according to each of the relationship formulas. Specifically, the calculation formula of the least square method is:

[0101] E=(Y-ΣA i X i ) 2

[0102] Step 107: Detect whether the value of the allocation coefficient meets a preset condition.

[0103] In this embodiment, it is detected whether the value of E is less than a preset value. Specifically, when E<10 -5 , indicating that the error is small, therefore, the corresponding value of the distribution coefficient X meets the preset condition. Therefore, in this embodiment, the detection of whether the value of the distribution coefficient meets the preset condition is to detect whether the value of the distribution coefficient X meets E<10 -5 .

[0104] Step 108: When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated.

[0105] Specifically, the coefficient of the main element in the pure mineral is the coefficient of the proportion of the main element in the pure mineral.

[0106] In this embodiment, when the value of the distribution coefficient X meets the preset conditions, E<10 -5 , indicating that the error is small, then calculate the proportion coefficient of the main element in the pure mineral.

[0107] In one embodiment, when the value of the distribution coefficient meets the preset conditions, the step of calculating the coefficient of the main element in the pure mineral includes: when the value of the distribution coefficient meets the preset conditions, according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral, calculating the coefficient of the main element in the pure mineral.

[0108] In this embodiment, the coefficient of the main element in the pure mineral is calculated by the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0109] Step 109, determining the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral.

[0110] It should be understood that a pure mineral contains multiple main elements. Therefore, according to the different main elements, different main elements are calculated according to steps 104 to 108 to obtain the coefficients of the multiple main elements in the pure mineral. Therefore, a mineral coefficient matrix based on multiple coefficients can be established based on the obtained coefficients of the multiple main elements in the pure mineral.

[0111] Step 110, calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral.

[0112] In this embodiment, the mineral component content of the pure mineral is calculated by using the proportional coefficients of the plurality of main elements in the mineral coefficient matrix.

[0113] In one embodiment, the step of calculating the mineral component content of the pure mineral based on the mineral coefficient matrix of the pure mineral includes: determining the relationship between the main elements and pure minerals in the igneous rock formation and the error objective function based on the mineral coefficient matrix of the pure mineral; and calculating the content of the pure mineral using an optimization method based on the relationship between the main elements and pure minerals and the error objective function.

[0114] In this embodiment, the mineral coefficient matrix of the pure mineral is first used to determine the relationship between the main elements and the pure minerals in the igneous rock formation and the error objective function, and then the optimization algorithm is used again to calculate the mineral component content of the pure mineral based on the relationship between the main elements and the pure minerals and the error objective function.

[0115] It should be understood that the detailed process of calculating the mineral component content of the pure mineral using the optimization algorithm based on the relationship between the main element and the pure mineral and the error objective function can be found in Chinese Patent ZL201410318930.1. In this embodiment, this is not described in detail.

[0116] Step 111, determining the mineral composition of the igneous rock according to the content of the pure mineral.

[0117] Finally, the mineral composition of the igneous rock is determined based on the content of each mineral component of the pure mineral.

[0118] In the above embodiment, based on the relative content of igneous rock formation elements from the original element logging / XRF data, the coefficient matrix between the formation mineral mass and element content is established using pure minerals, and finally the weight content of igneous rock formation minerals is calculated using an optimization algorithm, which can evaluate 14 igneous rock components. The inversion process realizes modular operation, which plays a positive role in forming element logging interpretation software with its own intellectual property rights to adapt to the rapid and efficient development of domestic igneous rocks.

[0119] In one embodiment, the step of detecting whether the value of the distribution coefficient meets the preset conditions further includes: when the value of the distribution coefficient does not meet the preset conditions, returning to execute the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral.

[0120] In this embodiment, when it is detected that the value of the distribution coefficient does not meet the preset condition, that is, E ≥ 10 -5 , indicating that the error is large, therefore, the distribution coefficient of the main element does not meet the preset conditions, so the process returns to step 102 to calculate the distribution coefficient of the next main element, thereby ensuring that the error of the distribution coefficient of the calculated main element is small.

[0121] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0122] Embodiment 2

[0123] In this embodiment, based on the element content of the igneous rock formation after spectrum analysis based on element logging or XRF data, the molecular formula of the igneous mineral and the coefficient matrix of the main elements in the corresponding mineral are determined, and the igneous mineral content and type are inverted according to the optimization algorithm.

[0124] like Figure 2A As shown, the steps are as follows:

[0125] (1) Select pure mineral types of igneous rocks, such as olivine, pyroxene, albite, anorthite, amphibole, quartz, zircon, muscovite, biotite, apatite, zeolite, orthoclase, nepheline, etc.

[0126] (2) Measure the mass of pure minerals and calculate their molar mass and relative molecular weight.

[0127] (3) Determine the molecular formula model A(X) of the pure mineral, where A is the main element contained in the mineral and X is the distribution coefficient of the main element.

[0128] (4) Determine the main element A contained in the mineral, A includes but is not limited to Si, Al, Fe, Ca, K, Ti, Mg, Mn, Na, P, Zr and other elements.

[0129] (5) Calculate the relative molecular weight Y of the main elements contained, where Y is equal to the relative molecular weight of the mineral minus the relative molecular weight of the acid and base radicals.

[0130] (6) Establish the relationship between Y and the distribution coefficient X, Y = ΣAiXi.

[0131] (7) Calculate the distribution coefficient X using an optimization algorithm and determine whether it is appropriate. If not, go to step (3).

[0132] (8) Determine the specific pure mineral formula, including the main elements and acid and base radicals.

[0133] (9) Calculate the coefficient of the element in the pure mineral, which is equal to the relative molecular weight of the element / the relative molecular weight of the mineral.

[0134] (10) Go to step (1), calculate the coefficients of other pure minerals, and finally determine the coefficient matrix of all minerals in igneous rocks.

[0135] (11) Determine the relationship between elements and minerals in igneous rock formations and the error objective function.

[0136] (12) Use optimization algorithms to calculate the mineral content of igneous rock formations.

[0137] (13) Determine the mineral composition of igneous rocks.

[0138] This application aims to solve the problem of igneous rock element interpretation software that currently relies mainly on foreign software and has no independent intellectual property rights. The mineral content coefficient of the element is determined according to different types of pure minerals, and the mineral mass content of the igneous rock formation is inverted from ECS logging or XRF data using an optimization method. The inversion process realizes modular operation, which plays a positive role in forming element logging interpretation software with independent intellectual property rights to adapt to the rapid and efficient development of domestic igneous rocks.

[0139] Example 1: Foreign software only calculates the contents of four minerals, corresponding to mud content, silica content, ash content, and pyrite, and cannot invert the mineral type and content of igneous rocks. Figure 2B The results shown are calculated using foreign software.

[0140] Example 2: Olivine is a mineral that often appears in igneous rocks. Assuming that the molecular formula of olivine is (MgFeCa)SiO4, but the distribution coefficients between the main elements Mg, Fe, and Ca are not determined, pure olivine is taken from the target layer, its molar mass (mass / molar volume) is calculated, and the relative molecular weight is determined based on the molar mass; the molecular formula of pure olivine is set to ASiO4, A is the main element, and the relative molecular weight X of A is determined based on the molecular weight of pure olivine; the elements in pure olivine other than Si and O are determined, and the main element A is Mg, Fe, and Ca, including other elements with higher contents; the sum Y of the mass content of the main elements is calculated, and the distribution coefficients of the main elements (C1, C2, C3) are determined using the element measurement results of pure olivine, Y=28*C1+56*C2+40*C3, and the distribution coefficients are determined by the least squares method based on the results of multiple measurement points. It is calculated that C1=0.6, C2=0.4, and C3=0, and finally its coefficients are determined based on the molecular formula of olivine.

[0141] Similarly, the coefficient matrix for all igneous minerals is determined as shown in Table 1.

[0142] Table 1 Relationship matrix between igneous rock elements and minerals

[0143] Si Al Fe Ca K Ti <![CDATA[M g ]]> Mn Na P Zr quartz 0.467 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Orthoclase 0.303 0.097 0.000 0.000 0.141 0.000 0.000 0.000 0.008 0.000 0.000 Sodium feldspar 0.321 0.103 0.000 0.000 0.000 0.000 0.000 0.000 0.088 0.000 0.000 Caustic feldspar 0.202 0.194 0.000 0.144 0.000 0.000 0.000 0.000 0.000 0.000 0.000 muscovite 0.212 0.191 0.013 0.000 0.078 0.000 0.001 0.001 0.005 0.000 0.000 Biotite 0.182 0.060 0.136 0.002 0.072 0.000 0.077 0.003 0.004 0.000 0.000 Pyroxene 0.112 0.216 0.223 0.160 0.000 0.000 0.097 0.000 0.000 0.000 0.000 Peridot 0.163 0.000 0.324 0.000 0.000 0.000 0.141 0.000 0.000 0.000 0.000 Hornblende 0.191 0.000 0.335 0.000 0.000 0.000 0.144 0.000 0.000 0.000 0.000 Ilmenite 0.000 0.000 0.368 0.000 0.000 0.316 0.000 0.000 0.000 0.000 0.000 Nepheline 0.199 0.191 0.000 0.000 0.000 0.000 0.000 0.000 0.156 0.000 0.000 Zeolite 0.278 0.133 0.000 0.000 0.000 0.000 0.000 0.000 0.114 0.000 0.000 Zircon 0.153 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.497 apatite 0.000 0.000 0.398 0.000 0.000 0.000 0.000 0.000 0.000 0.185 0.000

[0144] Example 3: Figure 2C To calculate the results of igneous rock mineral content, the first track in the figure is the formation depth; the second to tenth tracks are the relative content of logging elements, the reconstructed element response values ​​and the confidence interval of the inversion results; the eleventh track is the inversion error curve; the twelfth to seventeenth tracks are the inverted mineral contents, which are mud content, silica content, calcium content, iron content, gypsum mineral content and other mineral contents respectively; the eighteenth track is the inverted mineral mass content combined profile. Figure 2C As shown, XRF / elemental igneous rock evaluation of formation mineral content (3730-3760m).

[0145] Example 4: Figure 2D The mineral mass content map of the igneous rock formation is inverted for the element data of a well in the block. The processing depth is 5320-5350 meters. The meaning and Figure 2A Same as Figure 2D As shown, logging elements evaluate the mineral content of igneous rock formations (5320-5350m)

[0146] In the above embodiments, the mineral types and contents of igneous rock formations are complex. To accurately determine the mineral mass content of igneous rock formations, an igneous rock core experimental method is usually used to determine it, or a multi-mineral interpretation model is used to determine it. The number of cores in the experimental method is limited, and the experimental results are not obtained in a timely manner. The results of the multi-mineral interpretation model often do not match the mineral type, and the mineral content calculation results have large errors. The present invention uses pure minerals to establish a coefficient matrix between the mineral mass and the element content of the formation based on the relative content of the elements of the igneous rock formation according to the original element logging / XRF data, and finally uses an optimization algorithm to calculate the weight content of the minerals in the igneous rock formation, which can evaluate 14 igneous rock components.

[0147] Embodiment 3

[0148] In this embodiment, Figure 3 As shown, a device for determining the mineral composition of igneous rocks is provided, comprising:

[0149] The pure mineral molecular weight calculation module 301 is used to measure the mass of pure minerals contained in igneous rocks, calculate the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculate the relative molecular weight of the acid and base radicals in the pure minerals;

[0150] A molecular formula model determination module 302 is used to determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral;

[0151] A main element determination module 303 is used to determine at least one main element in the pure mineral according to the molecular formula model of the pure mineral;

[0152] A relative molecular weight calculation module 304 is used to calculate the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals;

[0153] A distribution relationship establishing module 305 is used to establish a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral;

[0154] A distribution coefficient calculation module 306 is used to calculate the value of the distribution coefficient using an optimization algorithm according to each of the relationship equations;

[0155] A preset condition compliance detection module 307 is used to detect whether the value of the allocation coefficient meets the preset condition;

[0156] An element coefficient calculation module 308 is used to calculate the coefficient of each main element in the pure mineral when the value of the distribution coefficient meets the preset conditions;

[0157] A coefficient matrix determination module 309 is used to determine the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral;

[0158] The mineral component content calculation module 310 is used to calculate the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral;

[0159] The mineral composition determination module 311 is used to determine the mineral composition contained in the igneous rock according to the content of the pure mineral.

[0160] In one embodiment, the mineral component content calculation module includes:

[0161] A relationship and objective function determination unit, used to determine the relationship between the main element and the pure mineral in the igneous rock formation and the error objective function according to the mineral coefficient matrix of the pure mineral;

[0162] The mineral component content calculation unit is used to calculate the content of the pure mineral using an optimization method according to the relationship between the main element and the pure mineral and the error objective function.

[0163] In one embodiment, the device for determining the mineral composition of igneous rock further comprises:

[0164] The preset condition not meeting module is used to return to the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral when the value of the distribution coefficient does not meet the preset condition.

[0165] In one embodiment, the allocation coefficient calculation module is used to calculate the value of the allocation coefficient using the least square method according to each of the relationship expressions.

[0166] In one embodiment, the element coefficient calculation module is used to calculate the coefficient of the main element in the pure mineral according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral when the value of the distribution coefficient meets the preset conditions.

[0167] In one embodiment, the relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral is:

[0168] Y=ΣA i X i

[0169] Wherein, Y is the relative molecular weight of the main element, A is the molecular formula model, and X is the distribution coefficient of the main element in the molecular formula model.

[0170] In one embodiment, the molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element.

[0171] The specific definition of the device for determining the mineral composition of igneous rocks can be found in the definition of the method for determining the mineral composition of igneous rocks mentioned above, which will not be repeated here. Each unit in the above-mentioned device for determining the mineral composition of igneous rocks can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned units.

[0172] Embodiment 4

[0173] In this embodiment, a computer device is provided. Its internal structure diagram can be shown as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices deployed with application software. When the computer program is executed by the processor, a method for determining the mineral composition of igneous rocks is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0174] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0175] Embodiment 5

[0176] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0177] Step 101, measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of the acid and base radicals in the pure minerals.

[0178] Specifically, in this step, firstly, igneous pure minerals are obtained, the pure mineral mass of the igneous pure minerals is measured, and then the molar mass and relative molecular weight of the pure minerals are calculated according to the pure mineral mass, and the relative molecular weight of acid and base radicals is measured.

[0179] For example, select pure mineral types of igneous rocks, such as olivine, pyroxene, albite, calcium feldspar, amphibole, quartz, zircon, muscovite, biotite, apatite, zeolite, orthoclase, and nepheline.

[0180] Step 102: determining a molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral.

[0181] In this step, after the molar mass and relative molecular weight of the pure mineral are measured, the molecular formula model of the pure mineral is determined according to the molar mass and relative molecular weight of the pure mineral, and the molecular formula model may also become a molecular formula.

[0182] In this embodiment, the molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element. The main element is the element other than acid and alkali radicals in the igneous pure mineral, and the main element includes but is not limited to silicon, aluminum, iron, calcium, potassium, titanium, magnesium, manganese, sodium, phosphorus, zirconium and the like.

[0183] Step 103: determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral.

[0184] In this step, the main elements contained in the pure mineral are determined based on the molecular formula model of the pure mineral in the above step.

[0185] Step 104, calculating the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0186] Specifically, the relative molecular weight of the main element is the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals. Therefore, in this step, the relative molecular weight Y of the main element is calculated by calculating the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0187] Step 105, establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral.

[0188] In this step, a relationship between the relative molecular weight of each main element and the distribution coefficient is established. Specifically, a relationship between the relative molecular weight Y of each main element and the distribution coefficient X in the molecular formula model A(X) of the pure mineral is established.

[0189] For example, the molecular formula model of pure mineral structure, such as zeolite, is:

[0190] A(x / q)[(AlO2)a(SiO2)b]·n(H2O), where: A is Ca, Na, K,

[0191] In one embodiment, the relationship is Y = ΣA i X i , where Y is the relative molecular weight of the main element, A is the molecular formula model, X is the distribution coefficient of the main element in the molecular formula model, and i identifies the i-th main element.

[0192] Step 106: According to each of the relationship expressions, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient.

[0193] In this embodiment, in the previous step, a relationship between the relative molecular weight and the distribution coefficient of each main element is established respectively, thereby obtaining relationship between the relative molecular weight and the distribution coefficient of multiple main elements. Based on these established relationship, an optimization algorithm is used to calculate the value of the distribution coefficient.

[0194] In one embodiment, the step of calculating the value of the distribution coefficient using an optimization algorithm according to each of the relationship formulas includes: calculating the value of the distribution coefficient using a least square method according to each of the relationship formulas. Specifically, the calculation formula of the least square method is:

[0195] E=(Y-ΣA i X i ) 2

[0196] Step 107: Detect whether the value of the allocation coefficient meets a preset condition.

[0197] In this embodiment, it is detected whether the value of E is less than a preset value. Specifically, when E<10 -5 , indicating that the error is small, therefore, the corresponding value of the distribution coefficient X meets the preset condition. Therefore, in this embodiment, the detection of whether the value of the distribution coefficient meets the preset condition is to detect whether the value of the distribution coefficient X meets E<10 -5 .

[0198] Step 108: When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated.

[0199] Specifically, the coefficient of the main element in the pure mineral is the coefficient of the proportion of the main element in the pure mineral.

[0200] In this embodiment, when the value of the distribution coefficient X meets the preset conditions, E<10 -5 , indicating that the error is small, then calculate the proportion coefficient of the main element in the pure mineral.

[0201] In one embodiment, when the value of the distribution coefficient meets the preset conditions, the step of calculating the coefficient of the main element in the pure mineral includes: when the value of the distribution coefficient meets the preset conditions, according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral, calculating the coefficient of the main element in the pure mineral.

[0202] In this embodiment, the coefficient of the main element in the pure mineral is calculated by the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0203] Step 109, determining the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral.

[0204] It should be understood that a pure mineral contains multiple main elements. Therefore, according to the different main elements, different main elements are calculated according to steps 104 to 108 to obtain the coefficients of the multiple main elements in the pure mineral. Therefore, a mineral coefficient matrix based on multiple coefficients can be established based on the obtained coefficients of the multiple main elements in the pure mineral.

[0205] Step 110, calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral.

[0206] In this embodiment, the mineral component content of the pure mineral is calculated by using the proportional coefficients of the plurality of main elements in the mineral coefficient matrix.

[0207] In one embodiment, the step of calculating the mineral component content of the pure mineral based on the mineral coefficient matrix of the pure mineral includes: determining the relationship between the main elements and pure minerals in the igneous rock formation and the error objective function based on the mineral coefficient matrix of the pure mineral; and calculating the content of the pure mineral using an optimization method based on the relationship between the main elements and pure minerals and the error objective function.

[0208] In this embodiment, the mineral coefficient matrix of the pure mineral is first used to determine the relationship between the main elements and the pure minerals in the igneous rock formation and the error objective function, and then the optimization algorithm is used again to calculate the mineral component content of the pure mineral based on the relationship between the main elements and the pure minerals and the error objective function.

[0209] Step 111, determining the mineral composition of the igneous rock according to the content of the pure mineral.

[0210] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0211] Determine the relationship between the main element and the pure mineral in the igneous rock formation and the error objective function according to the mineral coefficient matrix of the pure mineral;

[0212] According to the relationship between the main element and the pure mineral and the error objective function, the mineral component content of the pure mineral is calculated using an optimization algorithm.

[0213] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0214] When the value of the distribution coefficient does not meet the preset condition, the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral is returned to be executed.

[0215] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0216] According to each of the relationship equations, the value of the distribution coefficient is calculated using the least square method.

[0217] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0218] When the value of the distribution coefficient meets the preset conditions, the coefficient of the main element in the pure mineral is calculated according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0219] In one embodiment, when the processor executes the computer program to implement the step of establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral,

[0220] The relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral is:

[0221] Y=ΣA i X i

[0222] Wherein, Y is the relative molecular weight of the main element, A is the molecular formula model, and X is the distribution coefficient of the main element in the molecular formula model.

[0223] In one embodiment, when the processor executes the computer program, in the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral,

[0224] The molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element.

[0225] Embodiment 6

[0226] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0227] Step 101, measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of the acid and base radicals in the pure minerals.

[0228] Specifically, in this step, firstly, igneous pure minerals are obtained, the pure mineral mass of the igneous pure minerals is measured, and then the molar mass and relative molecular weight of the pure minerals are calculated according to the pure mineral mass, and the relative molecular weight of acid and base radicals is measured.

[0229] For example, select pure mineral types of igneous rocks, such as olivine, pyroxene, albite, calcium feldspar, amphibole, quartz, zircon, muscovite, biotite, apatite, zeolite, orthoclase, and nepheline.

[0230] Step 102: determining a molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral.

[0231] In this step, after the molar mass and relative molecular weight of the pure mineral are measured, the molecular formula model of the pure mineral is determined according to the molar mass and relative molecular weight of the pure mineral, and the molecular formula model may also become a molecular formula.

[0232] In this embodiment, the molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element. The main element is the element other than acid and alkali radicals in the igneous pure mineral, and the main element includes but is not limited to silicon, aluminum, iron, calcium, potassium, titanium, magnesium, manganese, sodium, phosphorus, zirconium and the like.

[0233] Step 103: determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral.

[0234] In this step, the main elements contained in the pure mineral are determined based on the molecular formula model of the pure mineral in the above step.

[0235] Step 104, calculating the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0236] Specifically, the relative molecular weight of the main element is the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals. Therefore, in this step, the relative molecular weight Y of the main element is calculated by calculating the difference between the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals.

[0237] Step 105, establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral.

[0238] In this step, a relationship between the relative molecular weight of each main element and the distribution coefficient is established. Specifically, a relationship between the relative molecular weight Y of each main element and the distribution coefficient X in the molecular formula model A(X) of the pure mineral is established.

[0239] For example, the molecular formula model of pure mineral structure, such as zeolite, is:

[0240] A(x / q)[(AlO2)a(SiO2)b]·n(H2O), where: A is Ca, Na, K,

[0241] In one embodiment, the relationship is Y = ΣA i X i , where Y is the relative molecular weight of the main element, A is the molecular formula model, X is the distribution coefficient of the main element in the molecular formula model, and i identifies the i-th main element.

[0242] Step 106: According to each of the relationship expressions, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient.

[0243] In this embodiment, in the previous step, a relationship between the relative molecular weight and the distribution coefficient of each main element is established respectively, thereby obtaining relationship between the relative molecular weight and the distribution coefficient of multiple main elements. Based on these established relationship, an optimization algorithm is used to calculate the value of the distribution coefficient.

[0244] In one embodiment, the step of calculating the value of the distribution coefficient using an optimization algorithm according to each of the relationship formulas includes: calculating the value of the distribution coefficient using a least square method according to each of the relationship formulas. Specifically, the calculation formula of the least square method is:

[0245] E=(Y-ΣA i X i ) 2

[0246] Step 107: Detect whether the value of the allocation coefficient meets a preset condition.

[0247] In this embodiment, it is detected whether the value of E is less than a preset value. Specifically, when E<10 -5, indicating that the error is small, therefore, the corresponding value of the distribution coefficient X meets the preset condition. Therefore, in this embodiment, the detection of whether the value of the distribution coefficient meets the preset condition is to detect whether the value of the distribution coefficient X meets E<10 -5 .

[0248] Step 108: When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated.

[0249] Specifically, the coefficient of the main element in the pure mineral is the coefficient of the proportion of the main element in the pure mineral.

[0250] In this embodiment, when the value of the distribution coefficient X meets the preset conditions, E<10 -5 , indicating that the error is small, then calculate the proportion coefficient of the main element in the pure mineral.

[0251] In one embodiment, when the value of the distribution coefficient meets the preset conditions, the step of calculating the coefficient of the main element in the pure mineral includes: when the value of the distribution coefficient meets the preset conditions, according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral, calculating the coefficient of the main element in the pure mineral.

[0252] In this embodiment, the coefficient of the main element in the pure mineral is calculated by the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0253] Step 109, determining the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral.

[0254] It should be understood that a pure mineral contains multiple main elements. Therefore, according to the different main elements, different main elements are calculated according to steps 104 to 108 to obtain the coefficients of the multiple main elements in the pure mineral. Therefore, a mineral coefficient matrix based on multiple coefficients can be established based on the obtained coefficients of the multiple main elements in the pure mineral.

[0255] Step 110, calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral.

[0256] In this embodiment, the mineral component content of the pure mineral is calculated by using the proportional coefficients of the plurality of main elements in the mineral coefficient matrix.

[0257] In one embodiment, the step of calculating the mineral component content of the pure mineral based on the mineral coefficient matrix of the pure mineral includes: determining the relationship between the main elements and pure minerals in the igneous rock formation and the error objective function based on the mineral coefficient matrix of the pure mineral; and calculating the content of the pure mineral using an optimization method based on the relationship between the main elements and pure minerals and the error objective function.

[0258] In this embodiment, the mineral coefficient matrix of the pure mineral is first used to determine the relationship between the main elements and the pure minerals in the igneous rock formation and the error objective function, and then the optimization algorithm is used again to calculate the mineral component content of the pure mineral based on the relationship between the main elements and the pure minerals and the error objective function.

[0259] Step 111, determining the mineral composition of the igneous rock according to the content of the pure mineral.

[0260] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0261] Determine the relationship between the main element and the pure mineral in the igneous rock formation and the error objective function according to the mineral coefficient matrix of the pure mineral;

[0262] According to the relationship between the main element and the pure mineral and the error objective function, the mineral component content of the pure mineral is calculated using an optimization algorithm.

[0263] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0264] When the value of the distribution coefficient does not meet the preset condition, the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral is returned to be executed.

[0265] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0266] According to each of the relationship equations, the value of the distribution coefficient is calculated using the least square method.

[0267] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0268] When the value of the distribution coefficient meets the preset conditions, the coefficient of the main element in the pure mineral is calculated according to the ratio of the relative molecular weight of the main element to the relative molecular weight of the pure mineral.

[0269] In one embodiment, in the step of establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral, the computer program is executed by the processor.

[0270] The relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral is:

[0271] Y=ΣA i X i

[0272] Wherein, Y is the relative molecular weight of the main element, A is the molecular formula model, and X is the distribution coefficient of the main element in the molecular formula model.

[0273] In one embodiment, in the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral executed by the processor, the computer program

[0274] The molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element.

[0275] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0276] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0277] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for determining the mineral composition of igneous rocks, characterized in that: include: Measuring the mass of pure minerals contained in the igneous rock, calculating the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculating the relative molecular weight of acid and base radicals in the pure minerals; Determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral; Determining at least one main element in the pure mineral according to the molecular formula model of the pure mineral; The relative molecular weight of each of the main elements is calculated based on the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals; Establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral; According to each of the relationship equations, an optimization algorithm is used to calculate and obtain the value of the distribution coefficient; Detecting whether the value of the distribution coefficient meets a preset condition; When the value of the distribution coefficient meets the preset condition, the coefficient of each of the main elements in the pure mineral is calculated; Determining a mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral; Calculating the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral; The mineral composition of the igneous rock is determined according to the content of the pure mineral.

2. The method according to claim 1, characterized in that The step of calculating the mineral component content of the pure mineral according to the mineral coefficient matrix of the pure mineral comprises: Determine the relationship between the main element and the pure mineral in the igneous rock formation and the error objective function according to the mineral coefficient matrix of the pure mineral; According to the relationship between the main element and the pure mineral and the error objective function, the content of the pure mineral is calculated using an optimization method.

3. The method according to claim 1, characterized in that After the step of detecting whether the value of the distribution coefficient meets the preset condition, the following step is further included: When the value of the distribution coefficient does not meet the preset condition, the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral is returned to be executed.

4. The method according to claim 1, characterized in that: The step of calculating the value of the distribution coefficient using an optimization algorithm according to each of the relationship equations comprises: According to each of the relationship equations, the value of the distribution coefficient is calculated using the least square method.

5. The method according to claim 1, characterized in that: When the value of the distribution coefficient meets the preset condition, the step of calculating the coefficients of all the main elements in the pure mineral comprises: When the value of the distribution coefficient meets the preset condition, the coefficients of all the main elements in the pure mineral are calculated according to the ratio of the relative molecular weight of all the main elements to the relative molecular weight of the pure mineral.

6. The method according to any one of claims 1 to 5, characterized in that: In the step of establishing a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral, The relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral is: Y=ΣA i X i Wherein, Y is the relative molecular weight of the main element, A is the molecular formula model, and X is the distribution coefficient of the main element in the molecular formula model.

7. The method according to any one of claims 1 to 5, characterized in that In the step of determining the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral, The molecular formula model of the pure mineral is A(X), wherein A is the main element contained in the pure mineral, and X is the distribution coefficient of the main element.

8. A device for determining the mineral composition of igneous rocks, characterized in that: include: A pure mineral molecular weight calculation module is used to measure the mass of pure minerals contained in igneous rocks, calculate the molar mass and relative molecular weight of the pure minerals according to the mass of the pure minerals, and calculate the relative molecular weight of the acid and base radicals in the pure minerals; A molecular formula model determination module, used to determine the molecular formula model of the pure mineral according to the molar mass and relative molecular weight of the pure mineral; A main element determination module, used to determine at least one main element in the pure mineral according to the molecular formula model of the pure mineral; A relative molecular weight calculation module, used to calculate the relative molecular weight of each of the main elements according to the relative molecular weight of the pure mineral and the relative molecular weight of the acid and base radicals; A distribution relationship establishment module, used to establish a relationship between the relative molecular weight of each of the main elements and the distribution coefficient in the molecular formula model of the pure mineral; A distribution coefficient calculation module, used to calculate the value of the distribution coefficient using an optimization algorithm according to each of the relationship equations; A preset condition compliance detection module is used to detect whether the value of the allocation coefficient meets the preset condition; An element coefficient calculation module, used for calculating the coefficient of each main element in the pure mineral when the value of the distribution coefficient meets the preset conditions; A coefficient matrix determination module, used to determine the mineral coefficient matrix of the pure mineral according to the coefficients of each of the main elements in the pure mineral; A mineral component content calculation module, used to calculate the content of the pure mineral using an optimization method according to the mineral coefficient matrix of the pure mineral; The mineral composition determination module is used to determine the mineral composition contained in the igneous rock according to the content of the pure mineral.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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