Method for determining neutron porosity parameters in mineral inversion

Abstract

The invention discloses a mineral inversion neutron porosity parameter determination method, and the method comprises the steps: building an MCNP instrument parameter model based on a target instrument, which comprises instrument housing size parameters, near and far detector source distances and a shielding body; establishing a scale relation based on the limestone stratum, and calculating apparent limestone neutron porosity of different minerals according to the scale relation of the limestone stratum; and performing mineral inversion according to the calculated limestone neutron porosity of different minerals. According to the MCNP simulation-based mineral neutron porosity determination method, the number of unknown parameters in the mineral inversion process is reduced, the reference value of the neutron porosity of the special mineral limestone is expanded, the neutron porosity reference value different from that of part of enterprises is provided, and the mineral inversion efficiency and accuracy are improved.

Description

Technical Field

[0001] The invention relates to the field of well logging reservoir evaluation, and in particular to a method for determining a mineral inversion neutron porosity parameter. Background Art

[0002] With the rapid development of the global society and the continuous increase in energy demand, the status of oil and gas resources in national energy strategies and economic value has become increasingly prominent. In the key link of oil and gas exploration and development - reservoir evaluation, the accurate evaluation of core parameters such as reservoir development degree and porosity is crucial for accurately judging the storage capacity and exploitation potential of oil and gas reservoirs. The high accuracy of this evaluation process depends to a large extent on the high-precision quantitative analysis of the mineral composition and content in the formation.

[0003] However, currently widely used commercial software, such as CIFLog, Techlog, Geolog, etc., still face many challenges in the accurate inversion of mineral content. These software are often highly dependent on the professional experience and skill level of operators during the inversion process, and the measured values ​​of key parameters such as GR (natural gamma ray logging count), DEN (density logging count), CNL (neutron logging count) are easily affected by multiple factors such as formation complexity, instrument accuracy and environmental factors, showing great variability.

[0004] What is more complicated is that major domestic and foreign oilfield service companies often deliberately hide or obscure the key algorithms and limiting conditions in the software in order to protect their own patented technologies, making it difficult for users to obtain accurate reference values ​​of mineral parameters during use. Neutron porosity parameters are a typical example.

[0005] Through MCNP simulation, reference values ​​of apparent neutron porosity of different minerals can be given, thus effectively reducing the errors caused by empirical judgment in the mineral inversion process. This method not only improves the accuracy of mineral inversion, but also reduces the dependence on operator experience and the number of parameters that need to be adjusted in mineral inversion, providing a more reliable geological basis for oil and gas exploration and development. Summary of the invention

[0006] Accurate quantitative evaluation of reservoirs requires precise inversion of mineral composition and content. Some software has given default parameters for element logging or element logging based on the mineral element content in certain areas, and given conventional logging parameters for some minerals based on logging curves and geological knowledge. However, there is still great uncertainty in the accurate inversion of mineral composition and content. 1. The default parameters are mostly for sedimentary rock formations, and the inversion of igneous and metamorphic rock formations has large errors and lacks universality; 2. The neutron porosity of some special minerals is missing; 3. Commercial software hides limiting conditions, relies too much on experience in the parameter adjustment process, and lacks accurate standards. Compared with the above methods, the method for determining the apparent neutron porosity of minerals based on MCNP simulation can give the adjustment standard of neutron porosity, reduce the parameters that users need to adjust during the mineral inversion process, improve the parameter adjustment efficiency, and thus reduce the probability of erroneous results caused by incorrect parameters.

[0007] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions: The terms involved in the present invention are explained as follows: MCNP: It is a numerical calculation method guided by probability and statistics theory, which is used to analyze and solve the transport problems of neutrons and photons.

[0008] Ciflog: A third generation logging processing and interpretation system based on Java-NetBeans cutting-edge computer technology.

[0009] Techlog: Schlumberger's new generation of "wellbore data integration" solution software platform.

[0010] Geolog: A well data processing and analysis software package released by Paradigm, Israel.

[0011] GR: Natural gamma logging is a commonly used logging method in oil exploration and development.

[0012] DEN: Compensated density logging is an important logging method in oil exploration and development.

[0013] CNL: Compensated neutron logging is a commonly used logging method in oil exploration and development.

[0014] Mineral inversion: It is a method to infer the mineral composition and content in the formation through well logging data. Commonly used logging data include GR, DEN, CNL, element logging or element logging, etc.

[0015] Neutron porosity logging: a type of neutron logging method that uses a point isotope neutron source to irradiate the formation, uses a neutron detector to measure the thermal neutron or epithermal neutron count rate, and converts the count rate into apparent limestone porosity.

[0016] Elastic scattering of fast neutrons: When a neutron collides with an atomic nucleus, the total momentum remains unchanged, but the neutron is slowed down. No gamma rays are generated in this process.

[0017] Radiative capture of thermal neutrons: The energy of thermal neutrons is in thermal equilibrium with the atomic nucleus. Neutrons diffuse from areas with high neutron density to areas with low neutron density like gas molecules until they are completely absorbed.

[0018] Hydrogen index: The hydrogen index of a substance is equal to the ratio of the number of hydrogen nuclei contained in the substance to the number of hydrogen nuclei contained in the same volume of fresh water, which can reflect the substance's ability to slow down fast neutrons.

[0019] Thermal neutron flux: the number of thermal neutrons passing through a unit area per unit time.

[0020] A method for determining a mineral inversion neutron porosity parameter, the method comprising: Step 1: Establish the MCNP instrument parameter model based on the target instrument, including the instrument shell size parameters, near and far detector source distances, shielding body and other information; Step 2: Establish a scale relationship based on limestone strata, and calculate the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone strata; Step 3: Perform mineral inversion based on the calculated neutron porosity of limestone of different minerals.

[0021] As a further technical solution of the present invention, in step 1, the step of establishing the MCNP instrument parameter model based on the target instrument includes: Build an ideal formation model for apparent neutron porosity for a specific tool: The ideal formation model of apparent neutron porosity includes two parts: formation and instrument. By using the energy spectrum data recorded by near and far detectors and changing the mineral composition of the formation, the neutron porosity characteristic values ​​of different minerals under ideal conditions can be studied. Formation part: The formation is composed of a single mineral and completely surrounds the instrument. The formation is a cylinder of 75×75×140cm, which is hollow inside and is regarded as an ideal infinitely uniform formation; Instrument part: mainly includes instrument shell, Am-Be source, shield, near detector and far detector. The instrument shell is a 2.15×2.15×100cm cylinder with a hollow interior. The Am-Be source is an ideal chemical source with an average energy of 4.5MeV. The shield is tungsten nickel iron. The near detector source distance is 39.83cm; the far detector source distance is 58.08cm. Recording information section: records thermal neutron counts in the range of 0~0.3eV; Principle of calculation of apparent neutron porosity: The deceleration capacity of the formation to fast neutrons mainly depends on the hydrogen content index of the formation, and there is a linear relationship between the hydrogen content index and the apparent neutron porosity; Based on a point source, the neutron flux of thermal neutrons at a distance r from it is: Formula 1: ; in: is the thermal neutron diffusion coefficient; Le is the epithermal neutron diffusion length; Lt is the thermal neutron diffusion length; Assume that the source distances of near and far detectors are r1 and r2 respectively; the count rates of near and far detectors are N1 and N2 respectively, then: Formula 2: ; The diffusion length of thermal neutrons is much shorter than the deceleration length of fast neutrons; ignoring the exponential term of Lt, we can get: Formula 3: ; Therefore, the ratio of the count rates of the near and far detectors depends only on ; That is, it depends on the hydrogen index.

[0022] As a further technical solution of the present invention, in step 2, the step of establishing a scale relationship based on the limestone stratum and calculating the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone stratum includes: Using the MCNP instrument parameter model set in step 1, the apparent limestone porosity calibration relationship is established by changing the formation components; Setting of formation parameters: calcite is set as the skeleton mineral of the formation, water is set as the formation fluid, calcite is considered to have a porosity of 0, and water is considered to have a porosity of 100%. 16 groups of calculation models are set in order, with limestone porosities of 0, 3, 6...39, 80, and 100%; Establishment of the calibration relationship of compensated neutron porosity: Use the ratio of the thermal neutron count rate of 0-0.3eV of the near detector and the far detector to calibrate the hydrogen index of the formation, and establish the relationship between the ratio of the near and far detector calculation rate and the porosity; The functional relationship between the ratio of thermal neutron count rates of near and far detectors and porosity was obtained by multiple linear regression method. Scale relationship: Formula 4: 8.65627+4.13707R+0.01814 + ; in: represents the apparent limestone neutron porosity, R represents the ratio of thermal neutron count rates of near and far detectors; Using the MCNP instrument parameter model set in step 1, by changing the formation composition, the neutron elastic scattering and radiation capture process under different mineral conditions is simulated to obtain the thermal neutron count rates of near and far detectors under this condition. Using the scaling relationship of formula 4, the apparent limestone neutron porosity of the mineral is calculated.

[0023] As a further technical solution of the present invention, in step 3, the step of performing mineral inversion based on the calculated neutron porosity of different mineral apparent limestones includes: Establish rock volume model: Based on the logging and rock physics experimental data of a certain area, minerals with a content greater than 5% are regarded as main minerals, minerals with a content less than 5% are regarded as secondary minerals, and minerals with a content greater than 5% are retained. Then, normalization is performed to obtain the rock volume model of the minerals in the area; Debugging of mineral inversion parameters: DEN, CNL, AC, Mg, Ca, Si, Fe of element logging are used as input data, clay minerals, quartz, feldspar, calcite, amorphous, porosity, etc. are used as output data, and the neutron porosity of different mineral limestones obtained by MCNP simulation is used as a fixed value input; Evaluation of mineral inversion results: Output the volume fraction and mass fraction of each mineral component, and compare the mineral inversion results with the core results; In order to evaluate the mean absolute error of the inversion results, Q is defined as the mean absolute error, then: Formula 5: ; in represents the mean absolute error of mineral i; i represents one of clay minerals, quartz, feldspar, and amorphous; represents the inversion result of mineral i; Represents the core results of mineral i.

[0024] Beneficial effects achieved by the present invention: 1. The method for determining the apparent neutron porosity of minerals based on MCNP simulation reduces the number of unknown parameters in the mineral inversion process; 2. The method for determining the apparent neutron porosity of minerals based on MCNP simulation expands the reference value of the apparent neutron porosity of special minerals in limestone; 3. The method for determining the apparent neutron porosity of minerals based on MCNP simulation recognizes that some companies keep the technical confidentiality of porosity parameters, and provides a reference value of apparent neutron porosity that is different from that of some companies; 4. The method for determining mineral apparent neutron porosity based on MCNP simulation improves the efficiency and accuracy of mineral inversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a diagram of an ideal formation model of apparent neutron porosity in an embodiment of the present invention.

[0026] Figure 2 A physical principle diagram of neutron porosity calculation in an embodiment of the present invention.

[0027] Figure 3 4 is a scale relationship diagram of apparent neutron porosity of limestone in an embodiment of the present invention.

[0028] Figure 4 This is a diagram of simulated apparent neutron porosity of silicate minerals in an embodiment of the present invention.

[0029] Figure 5 Graph showing simulated apparent neutron porosity values ​​of feldspar minerals in an embodiment of the present invention.

[0030] Figure 6 This is a diagram of simulated apparent neutron porosity of mica minerals in an embodiment of the present invention.

[0031] Figure 7 This is a diagram of simulated apparent neutron porosity values ​​of iron and titanium oxide minerals in an embodiment of the present invention.

[0032] Figure 8 This is a diagram of simulated apparent neutron porosity values ​​of sulfide and sulfate minerals in an embodiment of the present invention.

[0033] Fig. 9 This is a diagram of simulated apparent neutron porosity of carbonate minerals in an embodiment of the present invention.

[0034] Fig.10 Graph showing simulated apparent neutron porosity values ​​of kaolinite in an embodiment of the present invention.

[0035] Fig.11 Graph showing simulated values ​​of apparent neutron porosity of diopside in an embodiment of the present invention.

[0036] Fig.12 This is a diagram of simulated apparent neutron porosity values ​​of evaporite minerals in an embodiment of the present invention.

[0037] Fig.13 This is a rock volume model diagram in an embodiment of the present invention.

[0038] Fig.14 It is a cross-plot comparing the inversion result and the core result in the embodiment of the present invention.

[0039] Fig.15 It is a technical flow chart in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is described in detail below in conjunction with the specific drawings.

[0041] An embodiment of the present invention provides a method for determining a mineral inversion neutron porosity parameter, the method comprising: Step 1: Establish the MCNP instrument parameter model based on the target instrument, including the instrument shell size parameters, near and far detector source distances, shielding body and other information; Step 2: Establish a scale relationship based on limestone strata, and calculate the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone strata; Step 3: Perform mineral inversion based on the calculated neutron porosity of limestone of different minerals.

[0042] In this embodiment, in step 1, the step of establishing the MCNP instrument parameter model based on the target instrument includes: Build an ideal formation model for apparent neutron porosity for a specific tool: The Monte Carlo method is a numerical calculation method guided by probability and statistics theory, which is widely used in the fields of particle transport, radiation measurement, radiation protection and shielding optimization design, detector characteristics, etc. The front view of the ideal formation model of neutron porosity is as follows Figure 1 As shown in the figure, the model consists of two parts: the formation and the instrument. By using the energy spectrum data recorded by the near and far detectors and changing the mineral composition of the formation, the neutron porosity characteristic values ​​of different minerals under ideal conditions can be studied. Formation part: The formation is composed of a single mineral and completely surrounds the instrument. The formation is a cylinder of 75×75×140cm, which is hollow inside and is regarded as an ideal infinitely uniform formation; Instrument part: mainly includes instrument shell, Am-Be source, shield, near detector and far detector. The instrument shell is a 2.15×2.15×100cm cylinder with a hollow interior. The Am-Be source is an ideal chemical source with an average energy of 4.5MeV. The shield is tungsten nickel iron. The near detector source distance is 39.83cm; the far detector source distance is 58.08cm. Recording information section: records thermal neutron counts in the range of 0~0.3eV; Principle of Apparent Neutron Porosity Calculation: The deceleration capacity of the formation for fast neutrons mainly depends on the hydrogen content index of the formation, and there is a linear relationship between the hydrogen content index and the apparent neutron porosity. The physical principle of neutron porosity calculation is as follows: Figure 2 As shown; Based on a point source, the neutron flux of thermal neutrons at a distance r from it is: Formula 1: ; in: is the thermal neutron diffusion coefficient; Le is the epithermal neutron diffusion length; Lt is the thermal neutron diffusion length; Assume that the source distances of near and far detectors are r1 and r2 respectively; the count rates of near and far detectors are N1 and N2 respectively, then: Formula 2: ; The diffusion length of thermal neutrons is much shorter than the deceleration length of fast neutrons; ignoring the exponential term of Lt, we can get: Formula 3: ; Therefore, the ratio of the count rates of the near and far detectors depends only on ; That is, it depends on the hydrogen index.

[0043] In this embodiment, in step 2, the step of establishing a scale relationship based on the limestone stratum and calculating the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone stratum includes: Using the MCNP instrument parameter model set in step 1, the apparent limestone porosity calibration relationship is established by changing the formation components; Setting of formation parameters: calcite is set as the skeleton mineral of the formation, water is set as the formation fluid, calcite is considered to have a porosity of 0, and water is considered to have a porosity of 100%. 16 groups of calculation models are set in order, with limestone porosities of 0, 3, 6...39, 80, and 100%; Establishment of the calibration relationship of compensated neutron porosity: Use the ratio of the thermal neutron count rate of 0-0.3eV of the near detector and the far detector to calibrate the hydrogen index of the formation, and establish the relationship between the ratio of the near and far detector calculation rate and the porosity; The functional relationship between the ratio of thermal neutron count rate of near and far detectors and porosity is obtained by multivariate linear regression. The calibration relationship of apparent neutron porosity of limestone formation is as follows: Figure 3 As shown; Scale relationship: Formula 4: 8.65627+4.13707R+0.01814 + ; in: represents the apparent limestone neutron porosity, R represents the ratio of thermal neutron count rates of near and far detectors; Using the MCNP instrument parameter model set in step 1, by changing the formation composition, the neutron elastic scattering and radiation capture process under different mineral conditions is simulated to obtain the thermal neutron count rates of near and far detectors under this condition. Using the scale relationship of formula 4, the apparent limestone neutron porosity of the following 32 minerals is calculated. The comparison table of the simulated values ​​of the apparent neutron porosity of common mineral limestone and the company's recommended values ​​is shown in Table 1. The simulation results are consistent with the company's recommended values ​​as a whole. Some results, such as: ferro-titanium ore, siderite, pyrite, rock salt, potassium salt and other minerals, have large differences; Table 1- Comparison of simulated neutron porosity values ​​of common mineral limestones and company recommended values ; The above minerals are classified and compared, and the results are as follows Figure 4-Figure 12 As shown: From the above comparison results, we can know that: the apparent neutron porosity of feldspar minerals changes the least, about (-2.1~-1.5%); the apparent neutron porosity of sulfide and sulfate minerals changes the most, about (-2~65%); the apparent neutron porosity of limonite and goethite is abnormally high, and the presence of hydroxyl and iron elements may be the reason for the abnormality; crystal water, iron content, density, etc. will increase the apparent neutron porosity; from the elastic scattering process, elements such as hydrogen and iron have higher elastic scattering cross sections, which also theoretically explains the correctness of this conclusion.

[0044] In this embodiment, in step 3, the step of performing mineral inversion based on the calculated neutron porosity of limestone of different minerals includes: Establish rock volume model: Based on the logging and rock physics experimental data of a certain area, minerals with a content greater than 5% are regarded as main minerals, minerals with a content less than 5% are regarded as secondary minerals, and minerals with a content greater than 5% are retained. Then, normalization is performed to obtain the rock volume model of the minerals in the area; The schematic diagram of the rock volume model of the area is shown in Fig.13 shown.

[0045] Debugging of mineral inversion parameters: DEN, CNL, AC, Mg, Ca, Si, Fe (obtained from regional data) and other parameters of element logging are used as input data, clay minerals, quartz, feldspar, calcite, amorphous, porosity and other parameters are used as output data, and the neutron porosity of different mineral limestones obtained by MCNP simulation is input as a fixed value. The input results of neutron porosity parameters are shown in Table 2: Among them, the chemical composition of amorphous is variable, and the mineral composition is not unique, so it is not considered; Evaluation of mineral inversion results: Take the parameters in Table 2 as input, output the volume fraction and mass fraction of each mineral component, and compare the mineral inversion results with the core results. The intersection diagram of the inversion results and the core results at a depth of 100 meters in a well section is shown in Figure 2. Fig.14 As shown; Table 2 - Neutron Porosity Parameter Values ; In order to evaluate the mean absolute error of the inversion results, Q is defined as the mean absolute error, then: Formula 5: ; in represents the mean absolute error of mineral i; i represents one of clay minerals, quartz, feldspar, and amorphous; represents the inversion result of mineral i; represents the core result of mineral i; After calculation, the apparent limestone neutron porosity results obtained by MCNP simulation were used in the mineral inversion process, and the average absolute error of feldspar was 3.96%, clay minerals were 2.87%, quartz was 5.69%, and amorphous was 3.46%. The comprehensive average absolute error was 4.0%, which is lower than the average absolute error of common commercial software.

[0046] The present invention first establishes a specific instrument MCNP parameter model, then uses calcite as a standard mineral to establish a calibration relationship between calcite and neutron porosity. Then, the apparent neutron porosity of the relevant minerals is calculated based on the established calibration limestone apparent neutron porosity relationship. Finally, the calculated apparent neutron porosity is used as a CNL parameter for mineral inversion, and finally an inversion result of the reservoir mineral content that is closer to the actual situation of the formation is obtained. Please refer to Fig.15 .

[0047] It should be noted that, in this article, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0048] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for determining mineral inversion neutron porosity parameters, characterized in that: The method comprises: Step 1: Establish the MCNP instrument parameter model based on the target instrument, including the instrument housing size parameters, near and far detector source distances and shielding body; Step 2: Establish a scale relationship based on the limestone strata, and calculate the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone strata; Step 3: Perform mineral inversion based on the calculated neutron porosity of limestone of different minerals.

2. The method for determining the neutron porosity parameters of a mineral by inversion according to claim 1, characterized in that: In step 1, the step of establishing the MCNP instrument parameter model based on the target instrument includes: Build an ideal formation model for apparent neutron porosity for a specific tool: The ideal formation model of apparent neutron porosity includes two parts: formation and instrument. By using the energy spectrum data recorded by near and far detectors and changing the mineral composition of the formation, the neutron porosity characteristic values ​​of different minerals under ideal conditions are studied. Formation part: The formation is composed of a single mineral and completely surrounds the instrument. The formation is a cylinder of 75×75×140cm, which is hollow inside and is regarded as an ideal infinitely uniform formation; Instrument part: mainly includes instrument shell, Am-Be source, shield, near detector and far detector. The instrument shell is a 2.15×2.15×100cm cylinder with a hollow interior. The Am-Be source is an ideal chemical source with an average energy of 4.5MeV. The shield is tungsten nickel iron. The near detector source distance is 39.83cm; the far detector source distance is 58.08cm. Recording information section: records thermal neutron counts in the range of 0~0.3eV; Calculation principle of apparent neutron porosity: The deceleration capacity of the formation to fast neutrons mainly depends on the hydrogen content index of the formation, and there is a linear relationship between the hydrogen content index and the apparent neutron porosity; Based on a point source, the neutron flux of thermal neutrons at a distance r from it is: Formula 1: ; in: is the thermal neutron diffusion coefficient; Le is the epithermal neutron diffusion length; Lt is the thermal neutron diffusion length; Assume that the source distances of near and far detectors are r1 and r2 respectively; the count rates of near and far detectors are N1 and N2 respectively, then: Formula 2: ; The diffusion length of thermal neutrons is much shorter than the deceleration length of fast neutrons; ignoring the exponential term of Lt, we can get: Formula 3: ; Therefore, the ratio of the count rates of the near and far detectors depends only on ; That is, it depends on the hydrogen index.

3. The method for determining the neutron porosity parameters of a mineral inversion according to claim 2, characterized in that: In step 2, the step of establishing a scale relationship based on the limestone stratum and calculating the apparent limestone neutron porosity of different minerals according to the scale relationship of the limestone stratum includes: Using the MCNP instrument parameter model set in step 1, the apparent limestone porosity calibration relationship is established by changing the formation components; Setting of formation parameters: calcite is set as the skeleton mineral of the formation, water is set as the formation fluid, calcite is regarded as having a porosity of 0; water is regarded as having a porosity of 100%, and 16 groups of calculation models are set in order, with limestone porosity of 0, 3, 6...39, 80, 100%; Establishment of the calibration relationship of compensated neutron porosity: Use the ratio of the thermal neutron count rate of 0-0.3eV of the near detector and the far detector to calibrate the hydrogen index of the formation, and establish the relationship between the ratio of the near and far detector calculation rate and the porosity; The functional relationship between the ratio of thermal neutron count rates of near and far detectors and porosity was obtained by multiple linear regression method. Scale relationship: Formula 4: 8.65627+4.13707R+0.01814 + ; in: represents the apparent limestone neutron porosity, R represents the ratio of thermal neutron count rates of near and far detectors; Using the MCNP instrument parameter model set in step 1, by changing the formation composition, the neutron elastic scattering and radiation capture process under different mineral conditions is simulated to obtain the thermal neutron count rates of near and far detectors under this condition. Using the scaling relationship of formula 4, the apparent limestone neutron porosity of the mineral is calculated.

4. The method for determining the neutron porosity parameters of a mineral by inversion according to claim 2, characterized in that: In step three, the step of performing mineral inversion based on the calculated neutron porosity of different mineral limestones includes: Establish rock volume model: Based on the logging and rock physics experimental data of a certain area, minerals with a content greater than 5% are regarded as main minerals, minerals with a content less than 5% are regarded as secondary minerals, and minerals with a content greater than 5% are retained. Then, normalization is performed to obtain the rock volume model of the minerals in the area; Debugging of mineral inversion parameters: DEN, CNL, AC, Mg, Ca, Si, Fe of element logging are used as input data, clay minerals, quartz, feldspar, calcite, amorphous, and porosity are used as output data, and the neutron porosity of limestone of different minerals obtained by MCNP simulation is used as a fixed value input; Evaluation of mineral inversion results: Output the volume fraction and mass fraction of each mineral component, and compare the mineral inversion results with the core results; In order to evaluate the mean absolute error of the inversion results, Q is defined as the mean absolute error, then: Formula 5: ; in represents the mean absolute error of mineral i; i represents one of clay minerals, quartz, feldspar, and amorphous; represents the inversion result of mineral i; Represents the core results of mineral i.

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