A method and system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance

Abstract

The present invention provides a method and system for evaluating the brittleness of shale using T1-T2 two-dimensional nuclear magnetic resonance. The method includes: a sample preparation step, a nuclear magnetic resonance analysis step, an organic carbon content calculation step, a clay mineral content calculation step, and a shale brittleness evaluation step. By performing nuclear magnetic resonance analysis on the collected shale samples according to a set strategy, a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements is obtained. Based on the signal distribution of the spectrum, signal areas are selectively targeted, and the organic carbon content and the content of plastic minerals other than illite corresponding to the sample spectrum are calculated by combining the established calculation model. Furthermore, the accurate content and index of brittle minerals are calculated to achieve the brittleness evaluation of shale. The adoption of this solution overcomes the uncertainty in the characterization of shale TOC and clay minerals caused by different instrument parameters and different measurement parameters, and has the advantages of simple operation, high accuracy, and high practicality.

Description

Technical Field

[0001] The present invention relates to the technical field of oil engineering analysis and evaluation, and particularly to a method and system for evaluating shale brittleness by using T1-T2 two-dimensional nuclear magnetic resonance. Background Art

[0002] In practical applications, brittleness lacks a strict definition, and there are dozens of calculation formulas for evaluating brittleness, making it difficult to unify and accurately measure its accuracy. In the national standard "GB / T 31483-2015 Shale Gas Geological Evaluation Method", the brittleness is mainly characterized by the content of brittle minerals.

[0003] For shale formations, in addition to brittle minerals and clay minerals, the rock skeleton components also include organic matter; and with the deepening of practice and understanding, it is considered that illite in clay minerals is also compressible and should be classified as brittle minerals. Therefore, simply counting the content of traditional brittle minerals or using (100 - clay mineral content) to characterize brittleness is inappropriate.

[0004] T1-T2 two-dimensional nuclear magnetic resonance technology can identify multiple components in shale through one analysis and has become a hot technology for evaluating shale oil and shale gas reservoirs. If clay minerals other than organic matter and illite can be accurately identified, then the total amount of brittle minerals can be calculated to achieve brittleness evaluation. However, in fact, conventional T1-T2 measurements are affected by multiple factors such as instruments, samples, and operations, resulting in significant differences between the spectral effects and interpretation results. Instrument and operation factors include magnetic field strength, echo spacing, probe aperture, measurement parameters, inversion algorithms, etc.; sample factors include storage conditions, environmental conditions, analysis conditions, etc. Due to numerous influencing factors, the number of T1-T2 signal peaks measured varies greatly, and fluid signals and noise signals coexist, making it difficult to identify and verify the signal peaks. Therefore, the current understanding cannot accurately evaluate the content of clay minerals (excluding illite) and organic matter content, and thus cannot accurately evaluate the brittleness of shale.

[0005] The information disclosed in the background art section of the present invention is only intended to deepen the understanding of the general background art of the present invention and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0006] To solve the above problems, the present invention provides a method for evaluating shale brittleness by using T1-T2 two-dimensional nuclear magnetic resonance. In one embodiment, the method includes:

[0007] Sample preparation step: collecting a set number of fresh and well-preserved shale samples for the reservoir to be evaluated;

[0008] After the nuclear magnetic resonance analysis step and recording the weight, perform T1-T2 two-dimensional nuclear magnetic resonance analysis on each shale sample based on the set configuration parameters to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements;

[0009] Steps for calculating the organic carbon content, determine the range of the organic carbon signal interval, and calculate the organic carbon content corresponding to the shale sample using a pre-constructed organic carbon calculation model based on the percentage content corresponding to the area of the organic carbon signal within the interval;

[0010] Steps for calculating the clay mineral content, determine the range of the target clay mineral signal interval, and calculate the content of the target plastic clay minerals other than illite based on the signal area within the target interval;

[0011] Steps for evaluating the brittleness of shale, based on the obtained organic carbon content and the content of the target plastic clay minerals, calculate the brittle mineral content and brittle index of the shale sample, and perform a grading evaluation on the brittleness of the shale sample based on the calculation results;

[0012] Among them, the organic carbon calculation model is obtained by training based on the relative content percentage of the organic carbon analysis results of a set number of training shale samples and the signals in the corresponding interval of the two-dimensional nuclear magnetic resonance analysis spectrum in the model establishment step.

[0013] Preferably, in one embodiment, in the nuclear magnetic resonance analysis step, the magnetic field strength of the T1-T2 two-dimensional nuclear magnetic resonance analysis instrument is 20 ± 5Mhz, the probe diameter is not less than 15mm, the pulse sequence is the inversion recovery method (IR-CPMG), and the inversion method is the regularization method.

[0014] Further, in one embodiment, in the nuclear magnetic resonance analysis step, the obtained effective T1-T2 spectrum satisfies: the signal-to-noise ratio is not less than 1000, and the number of signal peaks is not less than 3.

[0015] In one embodiment, in the model establishment step, the organic carbon calculation model is established through the following operations:

[0016] Prepare a set number of fresh and well-preserved shale samples as training shale samples;

[0017] After recording the weight, perform total organic carbon analysis on each training shale sample to obtain the corresponding organic carbon content data;

[0018] Perform T1-T2 two-dimensional nuclear magnetic resonance analysis on each training shale sample to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements;

[0019] Determine the range of the organic carbon signal interval, and calculate the relative content percentage corresponding to the area of the organic carbon signal of each training shale sample based on the signal area within the interval range;

[0020] An organic carbon calculation model is trained based on the relative content percentage of the organic carbon signal area and the analyzed organic carbon content data.

[0021] Specifically, in one embodiment, an organic carbon calculation model is established as shown in the following formula:

[0022]

[0023] In the formula, C TOC is the organic carbon content of the target shale sample, a and b are regression coefficients, and ∑A i is the sum of the effective signal areas of the corresponding shale samples.

[0024] Preferably, in one embodiment, in the step of calculating the clay mineral content, it includes:

[0025] Calculating the relative content percentage corresponding to the clay signal area of the shale sample based on the signal area within the target interval range;

[0026] Inputting the relative content percentage of the clay signal area into a pre-constructed plastic mineral calculation model to obtain the content of the target plastic clay minerals other than illite in the current shale sample.

[0027] Furthermore, in one embodiment, the relative content percentage corresponding to the clay signal area of the shale sample is calculated according to the following formula:

[0028]

[0029] In the formula, S cly-b represents the clay-bound water saturation, S cly-c represents the capillary-bound water saturation, A cly-b is the signal peak area of the clay-bound water; A cly-c is the signal peak area of the capillary-bound water, and ∑A i is the sum of the effective signal areas of the corresponding shale samples.

[0030] In one embodiment, in the model establishment step, it further includes:

[0031] Performing X-ray diffraction analysis on each training shale sample to obtain the corresponding mineral and clay mineral analysis data;

[0032] Determining the clay mineral signal interval range based on the T1-T2 spectrum of the training shale sample, and calculating the relative content percentage corresponding to the target clay mineral signal area other than illite in each training shale sample based on the signal area within the interval range;

[0033] The plastic mineral content data calculated based on the mineral and clay mineral analysis data, and a corresponding plastic mineral calculation model is trained based on the relative content percentage of the combined target clay mineral signal area.

[0034] Specifically, in one embodiment, the plastic mineral content data is calculated according to the following formula based on the mineral and clay mineral analysis data:

[0035]

[0036] In the formula, C P-clay is the total amount of plastic clay minerals; C I / S , C C , C K ,... are the contents of clay minerals other than illite, including the content of illite-smectite mixed layer (C I / S ), the content of chlorite (C C ), the content of kaolinite (C K ); C clay is the content of clay minerals.

[0037] In an alternative embodiment, in the brittleness evaluation step, the brittle mineral content of the shale sample is calculated according to the following formula:

[0038] C b = 100% - (C TOC + C p-clay )

[0039] In the formula, C b is the brittle mineral content of the target shale sample, C TOC is the organic matter content of the target shale sample, and C p-clay is the content of plastic clay minerals other than illite in the target shale sample.

[0040] Based on other aspects of the method described in any one or more of the above embodiments, the present invention also provides a storage medium, on which program codes for implementing the method described in any one or more of the above embodiments are stored.

[0041] Based on the application direction of the method described in any one or more of the above embodiments, the present invention also provides a system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance, and the system executes the method described in any one or more of the above embodiments.

[0042] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0043] A method and system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by the present invention. This method performs nuclear magnetic resonance analysis on the prepared shale samples according to a set strategy to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements, laying a foundation for accurately evaluating shale brittleness;

[0044] Furthermore, based on the signal distribution of the spectrum, signal areas are specifically selected, and combined with the established calculation model, the organic carbon content and the content of plastic minerals other than illite corresponding to the sample spectrum are calculated. Then, the accurate content and index of brittle minerals are calculated to achieve the evaluation of shale brittleness; it overcomes the deficiencies of regarding illite as a plastic mineral and organic matter as a brittle mineral, and realizes the evaluation of compressibility while evaluating the reservoir properties, oil content, and mobility of shale reservoirs through one technology without adding new technical means, with characteristics such as economic measurement and accurate evaluation.

[0045] Other features and advantages of the present invention will be described in the following specification, and partly become obvious from the specification, or are understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the specification and the drawings. Brief Description of the Drawings

[0046] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0047] Figure 1 is an example diagram of the results of existing nuclear magnetic resonance for interpreting shale properties provided by an embodiment of the present invention;

[0048] Figure 2 is a schematic flowchart of a method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of T1-T2 two-dimensional nuclear magnetic resonance analysis data of a method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by another embodiment of the present invention;

[0050] Figure 4 is a schematic diagram of the comparison of the analysis results of brittle minerals and clay minerals of a method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by an embodiment of the present invention;

[0051] Figure 5 is a schematic structural diagram of a system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by an embodiment of the present invention. Detailed Embodiments

[0052] The embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments, so that those skilled in the art can fully understand how to apply technical means to solve technical problems and achieve the process of realizing technical effects, and specifically implement the present invention according to the above implementation process. It should be noted that as long as there is no conflict, the various embodiments in the present invention and the various features of each embodiment can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0053] Although the flowchart describes the operations as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. The order of the operations can be rearranged. The process can be terminated when its operations are completed, but there may also be additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0054] Computer devices include user devices and network devices. Among them, user devices or clients include, but are not limited to, computers, smartphones, PDAs, etc.; network devices include, but are not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing. Computer devices can run independently to implement the present invention, or can be connected to the network and implement the present invention through interactive operations with other computer devices in the network. The network where the computer device is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0055] Here, terms such as "first" and "second" may be used to describe various units, but these units should not be limited by these terms. These terms are only used to distinguish one unit from another. The term "and / or" used here includes any and all combinations of one or more of the listed associated items. When a unit is referred to as being "connected" or "coupled" to another unit, it can be directly connected or coupled to the other unit, or there may be an intermediate unit.

[0056] The terms used here are only for describing specific embodiments and are not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "a" and "an" used here are also intended to include the plural. It should also be understood that the terms "comprises" and / or "comprising" used here specify the presence of the stated features, integers, steps, operations, units, and / or components, and do not preclude the presence or addition of one or more other features, integers, steps, operations, units, components, and / or their combinations.

[0057] Brittleness lacks a strict definition, and there are dozens of calculation formulas for evaluating brittleness, making it difficult to unify and accurately measure its accuracy. In the national standard "GB / T 31483-2015 Shale Gas Geological Evaluation Method", brittleness is mainly characterized by the content of brittle minerals.

[0058] For shale formations, in addition to brittle minerals and clay minerals, the rock skeleton components also include organic matter; and with the deepening of practice and understanding, it is considered that illite in clay minerals is also compressible and should be classified as brittle minerals. Therefore, simply counting the content of traditional brittle minerals or using (100 - clay mineral content) to characterize brittleness is inappropriate.

[0059] The T1-T2 two-dimensional nuclear magnetic resonance technology can identify multiple components in shale through one analysis and has become a hot technology for the evaluation of shale oil and shale gas reservoirs. If it can accurately identify clay minerals other than organic matter and illite, then the total amount of brittle minerals can be calculated to achieve brittleness evaluation. However, in fact, conventional T1-T2 measurements are affected by multiple factors such as instruments, samples, and operations, resulting in significant differences between the spectral effects and interpretation results. Instrument and operation factors include magnetic field strength, echo interval, probe aperture, measurement parameters, inversion algorithms, etc.; sample factors include preservation conditions, environmental conditions, analysis conditions, etc. Due to numerous influencing factors, the number of T1-T2 signal peaks measured varies greatly, and fluid signals and noise signals coexist, making it difficult to identify and verify the signal peaks. For the T1-T2 spectrum of shale oil reservoirs, the non-oil signals that existing technologies can interpret mainly include the following: (1) kerogen / solid bitumen, structural water, adsorbed water, mobile water (attached Figure 1 [a]: Jinbu Li, 2020); (2) kerogen or organic matter, structural water, pore water, fracture water (attached Figure 1 [b], [c]: Marc Fleury, 2016; Han Jiang, 2019; Xinhua Ma, 2020); (3) high-viscosity hydrocarbons, clay-bound water, capillary-bound water, free water (Andrew C. Johnson, 2021); (4) kerogen (invisible in low-field NMR), bitumen (partially visible), clay-bound water, water in inorganic pores (Ravinath Kausik, 2015); (5) kerogen, water (Mohammad Sadegh Zamiri, 2021); (6) kerogen, water (crystalline water, clay-bound water, shale pore water, free water) (attached Figure 1 [d]: Pengfei Zhang, 2019). The analysis schematic diagram of the existing shale T1-T2 spectrum interpretation model is as Figure 1As shown, in Figure [a], the magnetic field frequency used is 21.36 MHz, and there is a peak shape superposition in the T1-T2 spectrum. The non-oil signals include kerogen, structural water, mobile water, and adsorbed water. In Figure [b], the magnetic field frequency used is 12 MHz, and the non-oil signals in the T1-T2 spectrum include kerogen, structural water, pore water, and fracture water, without adsorbed water. In Figure [c], the magnetic field frequency used is 23.7 MHz, and the non-oil signals in the T1-T2 spectrum include kerogen hydroxide and water (clay water, intergranular water). In Figure [d], the magnetic field frequency used is 21.36 MHz, and the non-oil signals in the T1-T2 spectrum include kerogen, crystal water, bound water, pore water, and free water. It can be seen that the number of effective signals and the interpretation results vary greatly, making it difficult to accurately evaluate brittleness.

[0060] Thus, the current understanding cannot accurately evaluate the content of clay minerals (excluding illite) and the content of organic matter, and thus cannot accurately evaluate the brittleness of shale.

[0061] To solve the above problems, the present invention provides a method and system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance. This method evaluates the content of brittle minerals or the brittleness index on the basis of finely identifying the types and occurrence states of pore fluids in shale reservoirs through T1-T2 two-dimensional nuclear magnetic resonance, without the need to add new technical means, and has the characteristics of economical measurement and accurate evaluation. It can effectively overcome the uncertainty in the measurement and interpretation of multi-component information of T1-T2 two-dimensional nuclear magnetic resonance in current shale reservoirs, realize the accurate evaluation of the brittleness of shale reservoirs, and provide reliable technical support for the engineering evaluation of shale oil and shale gas reservoirs.

[0062] Next, the detailed process of the method of the embodiment of the present invention will be described in detail based on the accompanying drawings. The steps shown in the flowchart of the accompanying drawings can be executed in a computer system including, for example, a set of computer-executable instructions. Although the logical order of the steps is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0063] Example 1

[0064] Figure 2 shows a schematic flowchart of a method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided in Embodiment 1 of the present invention. Referring to Figure 2 it can be seen that the method includes the following steps.

[0065] Sample preparation step: Collect a set number of fresh and well-preserved shale samples for the reservoir to be evaluated. In practical applications, take a rock sample slightly smaller than the volume of the magnetic field uniform area, and if possible, use wire cutting to obtain a standard-sized core column.

[0066] After the nuclear magnetic resonance analysis step and recording the weight, perform two-dimensional nuclear magnetic resonance analysis of T1-T2 on each shale sample based on the set configuration parameters to obtain the signal-to-noise ratio.

[0067] and a T1-T2 spectrogram whose signal peaks meet the set requirements;

[0068] Organic carbon content calculation step, determine the range of the organic carbon signal interval, and calculate the organic carbon content corresponding to the shale sample using the pre-constructed organic carbon calculation model based on the percentage content corresponding to the organic carbon signal area within the interval.

[0069] Clay mineral content calculation step, determine the range of the target clay mineral signal interval, and calculate the content of the target plastic clay minerals except illite based on the signal area within the target interval.

[0070] Shale brittleness evaluation step, based on the obtained organic carbon content and the content of the target plastic clay minerals, calculate the brittle mineral content and brittle index of the shale sample, and conduct a grading evaluation of the brittleness of the shale sample based on the calculation results.

[0071] Among them, the signal area (A TOC ) for calculating TOC (15 ≤ T1 ≤ 500, 30 ≤ T1 / T2 ≤ 600) is the organic carbon signal area, and calculate or read the signal area (A cly-b ) within the range of T2 ≤ 0.1 ms, 0.05 ms ≤ T1 ≤ 500 ms and the signal area (A cly-c ) within the range of T2 ≥ 0.1 ms, 0.1 ms ≤ T1 ≤ 10 ms as the clay signal area. The organic carbon calculation model is obtained by training based on the relative content percentages of the organic carbon analysis results of the set number of training shale samples and the signals in the corresponding intervals of the two-dimensional nuclear magnetic resonance analysis spectrogram in the model establishment step.

[0072] Furthermore, in one embodiment, in the nuclear magnetic resonance analysis step, the magnetic field strength of the T1-T2 two-dimensional nuclear magnetic resonance analysis instrument is 20 ± 5 MHz, the probe aperture is not less than 15 mm, the pulse sequence is the inversion recovery method (IR-CPMG), and the inversion method is the regularization method.

[0073] Based on this, in the nuclear magnetic resonance analysis step, the obtained effective T1-T2 spectrogram satisfies: the signal-to-noise ratio is not less than 1000, and the number of signal peaks is not less than 3.

[0074] In actual application, the measured T1-T2 spectrum should have a high signal-to-noise ratio, and the number of signal peaks should be no less than 3. Figure 3 shows an example of T1-T2 two-dimensional nuclear magnetic resonance analysis of the method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by the embodiment of the present invention. Specifically, the magnetic field strength of the T1-T2 two-dimensional nuclear magnetic resonance analysis instrument is 20 ± 5Mhz, the probe aperture is not less than 15mm, the pulse sequence is the inversion recovery method (IR-CPMG), the echo interval (TE) is 0.06ms, the waiting time (TW) is 10ms, the inversion method is the regularization method, and the measured T1-T2 spectrum is as shown in Figure 3[a] of the attached drawings.

[0075] Figure 3[a] is the T1-T2 spectrum of the shale oil core obtained through the coupling of instruments and parameters. It can be seen that the signal-to-noise ratio of the spectrum is high, with 5 signal peaks. The plastic clay mineral (P-clay) signals include clay-bound water (cly-b) and capillary-bound water (cly-c), and the organic matter signals reflected by total organic carbon (TOC). The signals other than P-clay and TOC reflect the brittle mineral signals. Figure 3[b] is the correlation analysis of Scly-b and Scly-c of the T1-T2 spectra of 10 samples with XRD mineral components (where clay minerals, quartz, potassium feldspar, plagioclase, pyrite, and carbonate rocks are analyzed once, and their sum is 100%; illite-smectite mixed layer, illite, and chlorite are analyzed separately for clay minerals, and their sum is 100%); it can be seen from Figure 3[b] that the correlations between Scly-b, Scly-c and clay minerals, illite-smectite mixed layer, and chlorite are relatively high, while the correlation with illite is relatively low, indicating that this peak reflects the content of plastic clay minerals other than illite; the reason is that illite contains paramagnetic substance Fe, and nuclear magnetic resonance is difficult to detect or the signal is weak.

[0076] In an optional embodiment, in the model establishment step, the organic carbon calculation model is established through the following operations:

[0077] Prepare a set number of fresh and well-preserved shale samples as training shale samples;

[0078] After recording the weight, perform total organic carbon analysis (TOC) on each training shale sample to obtain the corresponding organic carbon content data;

[0079] Perform T1-T2 two-dimensional nuclear magnetic resonance analysis on each training shale sample to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements;

[0080] Determine the organic carbon signal interval range, and calculate the relative content percentage corresponding to the organic carbon signal area of each training shale sample based on the signal area within the interval range;

[0081] An organic carbon calculation model is trained based on the relative content percentage of the organic carbon signal area and the obtained organic carbon content data.

[0082] Among them, the signal area (A TOC ) for calculating TOC (15 ≤ T1 ≤ 500, 30 ≤ T1 / T2 ≤ 600) is the organic carbon signal area.

[0083] Specifically, in one embodiment, an organic carbon calculation model is established as shown in the following formula:

[0084]

[0085] In the formula, C TOC is the organic carbon content of the target shale sample, a and b are regression coefficients, and ∑A i is the sum of the effective signal areas of the corresponding shale samples.

[0086] Furthermore, in one embodiment, in the clay mineral content calculation step, it includes:

[0087] Calculating the relative content percentage corresponding to the clay signal area of the shale sample based on the signal area within the target interval range;

[0088] Inputting the relative content percentage of the clay signal area into the pre-constructed plastic mineral calculation model to obtain the content of the target plastic clay minerals other than illite in the current shale sample.

[0089] Specifically, in one embodiment, in the model establishment step, it further includes:

[0090] Performing X-ray diffraction analysis (XRD) on each training shale sample to obtain the corresponding mineral and clay mineral analysis data;

[0091] Based on the T1-T2 spectrum of the training shale sample, determining the clay mineral signal interval range, and calculating the relative content percentage corresponding to the target clay mineral signal area other than illite for each training shale sample based on the signal area within the interval range;

[0092] Based on the plastic mineral content data calculated from the mineral and clay mineral analysis data, and training a corresponding plastic mineral calculation model based on it in combination with the relative content percentage of the target clay mineral signal area.

[0093] In actual application, calculate or read the signal area (A cly-b ) within the range of T2 ≤ 0.1 ms, 0.05 ms ≤ T1 ≤ 500 ms and the signal area (A cly-c ) within the range of T2 ≥ 0.1 ms, 0.1 ms ≤ T1 ≤ 10 ms as the clay signal area, and divide them by ∑A i, calculate its relative content percentage (saturation) S cly-b 、S cly-c , thus, in an alternative embodiment, the relative content percentage corresponding to the clay signal area of the shale sample is calculated according to the following formula:

[0094]

[0095] In the formula, S cly-b represents the clay-bound water saturation, S cly-c represents the capillary-bound water saturation, A cly-b is the peak area of the clay-bound water signal; A cly-c is the peak area of the capillary-bound water signal, ∑A i is the sum of the effective signal areas corresponding to the shale sample.

[0096] Based on the above embodiments, the present invention realizes the evaluation of the brittle mineral content or brittle index on the basis of finely identifying the pore fluid types and occurrence states in the shale reservoir by T1-T2 two-dimensional nuclear magnetic resonance. As shown in Figure 3[a], 5 fluid signals are identified, and only 3 signals related to this patent are labeled; the occurrence state is to distinguish mobility, such as cly-b and cly-c respectively represent clay-bound water and capillary-bound water.

[0097] Among them, in one embodiment, the plastic mineral content data is calculated according to the following formula based on the mineral and clay mineral analysis data:

[0098]

[0099] In the formula, C P-clay is the total amount of plastic clay minerals; C I / S , C C , C K , …… are the contents of clay minerals other than illite, including the content of illite-smectite mixed layer (C I / S ), the content of chlorite (C C ), the content of kaolinite (C K ); C clay is the content of clay minerals. (C I / S , C C , C K , ……) and C clay are the analysis results of clay minerals and minerals by XRD twice, the sum of the contents of all clay minerals in the former is 100%, and the latter is the percentage of clay minerals in all minerals.

[0100] By S cly-b 、S cly-cFrom the correlation analysis of the contents of different types of clay minerals, the total amount of clay minerals, and different brittle minerals, it can be seen that these two parts of signals are the signals of clay minerals other than illite. The following plastic mineral calculation model is established, as shown in Figure 4[b] of the attached drawings:

[0101] C p-clay = a×(S cly-b + S cly-c ) + b (1)

[0102] In actual application, in one embodiment, in the brittle evaluation step, the brittle mineral content of the shale sample is calculated according to the following formula:

[0103] C b = 100% - (C TOC + C p-clay ) (6)

[0104] In the formula, C b is the brittle mineral content of the target shale sample, C TOC is the organic matter content of the target shale sample, and C p-clay is the content of plastic clay minerals other than illite in the target shale sample.

[0105] Furthermore, the brittle index of the shale sample is calculated according to the following formula:

[0106]

[0107] The present invention adopts the hot technology for researching shale oil and shale gas - T1-T2 two-dimensional nuclear magnetic resonance technology. By obtaining a high-quality T1-T2 spectrum to calculate the brittle mineral content or brittle index, it overcomes the uncertainty in the characterization of shale TOC and clay minerals caused by different instrument parameters and different measurement parameters, and overcomes the deficiencies of taking illite as a plastic mineral and organic matter as a brittle mineral. It realizes the evaluation of the compressibility while evaluating the reservoir property, oil-bearing property, and mobility of the shale reservoir through one technology, with simple operation, high accuracy, and very broad application scope and prospects.

[0108] Figure 4 shows a comparison schematic diagram of the analysis results of brittle minerals and clay minerals of the method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by the embodiment of the present invention. As shown in Figure 4, Figure 4[a] is the correlation analysis of 11 data points. The abscissa is the sum of the clay-bound water saturation and the capillary-bound water saturation (S cly-b + S cly-c ) that characterizes the plastic clay degree; the ordinate is the clay mineral content, where the square symbol represents the total clay mineral content, and the circular symbol represents the clay minerals without illite, that is, plastic clay minerals. It can be seen that (S cly-b + S cly-c)The correlation coefficients with clay minerals (all) and clay minerals (excluding illite) are relatively close, being 0.87 and 0.90 respectively. However, the sum of squared residuals of the two is quite different, being 885.75 and 181.89 respectively, indicating that (S cly-b +S cly-c )is more inclined to represent the content of clay minerals without illite. Figure 4[b] is the correlation analysis between brittleness and the content of XRD brittle minerals calculated according to Equation (6). Among them, the square symbols are those containing illite, and the circular symbols are those without illite (i.e., traditional brittle minerals). It can be seen that the correlation coefficients of the two are 0.91 and 0.88 respectively, which are also relatively close. However, the sum of squared residuals of the two are 178.56 and 869.03 respectively, indicating that T 1- The correlation between the brittle mineral content calculated by T2 nuclear magnetic resonance and the brittle mineral content of XRD containing illite is higher, and the dispersion degree of the data points is lower.

[0109] For the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be carried out in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0110] It should be noted that in other embodiments of the present invention, the method can also be combined with one or several of the above embodiments to obtain a new shale brittleness evaluation method to achieve accurate interpretation of reservoir properties.

[0111] It should be noted that based on the method in any one or more of the above embodiments of the present invention, the present invention also provides a storage medium on which program codes capable of implementing the method described in any one or more of the above embodiments are stored. When the codes are executed by an operating system, the method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance as described above can be implemented.

[0112] Example 2

[0113] In the above embodiments disclosed by the present invention, the method is described in detail. The method of the present invention can be implemented by various forms of devices or systems. Therefore, based on other aspects of the method in any one or more of the above embodiments, the present invention also provides a system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance. The system is used to execute the method for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance described in any one or more of the above embodiments. Specific embodiments are given below for detailed description.

[0114] Specifically,Figure 5 The structural schematic diagram of the system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided in the embodiments of the present invention is shown, as Figure 5 shown. The system generally includes three parts: a hardware system capable of acquiring high-quality T1-T2 spectra, a spectrum processing subsystem, and a brittleness evaluation subsystem.

[0115] Among them, the hardware system for the high-quality T1-T2 spectra uses a T1-T2 two-dimensional nuclear magnetic resonance analyzer. Before analyzing with the instrument, a set number of fresh and well-preserved shale samples are collected for the reservoir to be evaluated through a sample preparation module;

[0116] Further, after recording the weights of the shale samples, the T1-T2 two-dimensional nuclear magnetic resonance analyzer performs T1-T2 two-dimensional nuclear magnetic resonance analysis on each shale sample based on set configuration parameters to obtain a T1-T2 spectrum whose signal-to-noise ratio and signal peaks meet the set requirements; during the process of analyzing the shale samples with the T1-T2 two-dimensional nuclear magnetic resonance analyzer, the magnetic field strength of the T1-T2 two-dimensional nuclear magnetic resonance analyzer is set to 20 ± 5Mhz, the probe aperture is not less than 15mm, the pulse sequence is the inversion recovery method (IR-CPMG), and the inversion method is the regularization method, so that the obtained effective T1-T2 spectrum meets the requirements: the signal-to-noise ratio is not less than 1000, and the number of signal peaks is not less than 3.

[0117] The spectrum processing subsystem includes:

[0118] An organic carbon content calculation module, which is configured to determine the range of the organic carbon signal interval and calculate the organic carbon content corresponding to the shale sample using a pre-constructed organic carbon calculation model based on the percentage content corresponding to the area of the organic carbon signal within the interval;

[0119] A clay mineral content calculation module, which is configured to determine the range of the target clay mineral signal interval and calculate the content of the target plastic clay minerals except illite based on the signal area within the target interval;

[0120] Further, the system further includes a model construction module, which is configured to train the corresponding organic carbon calculation model and plastic mineral calculation model based on the organic carbon analysis results, mineral and clay mineral analysis data of a set number of training shale samples and the relative content percentages of the signals in the corresponding intervals of the two-dimensional nuclear magnetic resonance analysis spectrum.

[0121] Further, in one embodiment, the model construction module establishes an organic carbon calculation model through the following operations:

[0122] Prepare a set number of fresh and well-preserved shale samples as training shale samples;

[0123] After recording the weight, perform total organic carbon analysis on each training shale sample to obtain the corresponding organic carbon content data;

[0124] Perform T1-T2 two-dimensional nuclear magnetic resonance analysis on each training shale sample to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements;

[0125] Determine the range of the organic carbon signal interval, and calculate the relative content percentage corresponding to the organic carbon signal area of each training shale sample based on the signal area within the interval;

[0126] Train a corresponding organic carbon calculation model based on the relative content percentage of the organic carbon signal area and the analyzed organic carbon content data.

[0127] Specifically, in one embodiment, an organic carbon calculation model is established as shown in the following formula:

[0128]

[0129] In the formula, C TOC is the organic carbon content of the target shale sample, a and b are regression coefficients, and ∑A i is the sum of the effective signal areas of the corresponding shale sample.

[0130] In actual application, in one embodiment, the clay mineral content calculation module is configured to perform the following operations:

[0131] Calculate the relative content percentage corresponding to the clay signal area of the shale sample based on the signal area within the target interval;

[0132] Input the relative content percentage of the clay signal area into a pre-constructed plastic mineral calculation model to obtain the content of the target plastic clay minerals other than illite in the current shale sample.

[0133] Specifically, in one embodiment, calculate the relative content percentage corresponding to the clay signal area of the shale sample according to the following formula:

[0134]

[0135] In the formula, S cly-b represents the clay-bound water saturation, %, and S cly-c represents the capillary-bound water saturation, %; A cly-b is the area of the clay-bound water signal peak, A cly-c is the area of the capillary-bound water signal peak, and ∑A i is the sum of the effective signal areas of the corresponding shale sample.

[0136] Furthermore, the model construction module is configured to establish a plastic mineral calculation model through the following operations. In the model establishment step, it also includes:

[0137] Perform X-ray diffraction analysis on each piece of training shale sample to obtain corresponding mineral and clay mineral analysis data;

[0138] Based on the T1-T2 spectrogram of the training shale sample, determine the signal interval range of the clay mineral, and calculate the relative content percentage corresponding to the signal area of the target clay mineral other than illite in each training shale sample based on the signal area within the interval range;

[0139] Based on the plastic mineral content data calculated from the mineral and clay mineral analysis data, and based on the relative content percentage of the signal area of the target clay mineral, train the corresponding plastic mineral calculation model.

[0140] Specifically, in the process of constructing the plastic mineral calculation model, calculate the plastic mineral content data according to the following formula based on the mineral and clay mineral analysis data:

[0141]

[0142] In the formula, C P-clay is the total amount of plastic clay minerals; C I / S , C C , C K ,... are the contents of clay minerals other than illite, including the content of illite-smectite mixed layer (C I / S ), the content of chlorite (C C ), and the content of kaolinite (C K ); C clay is the content of clay minerals.

[0143] In actual application, in one embodiment, the brittle evaluation subsystem calculates the brittle mineral content of the shale sample according to the following formula:

[0144] C b = 100% - (C TOC + C p-clay )

[0145] In the formula, C b is the brittle mineral content of the target shale sample, C TOC is the organic matter content of the target shale sample, and C p-clay is the content of plastic clay minerals other than illite in the target shale sample.

[0146] In the system for evaluating shale brittleness using T1-T2 two-dimensional nuclear magnetic resonance provided by the embodiments of the present invention, each module or unit structure can operate independently or in combination according to the analysis and calculation requirements to achieve the corresponding technical effects.

[0147] It should be understood that the embodiments disclosed in the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should extend to equivalent alternatives of these features understood by those of ordinary skill in the relevant art. It should also be understood that the terms used herein are for the purpose of describing specific embodiments only and do not imply limitation.

[0148] As used herein, the phrase "one embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the phrase "one embodiment" appearing throughout the specification does not necessarily refer to the same embodiment.

[0149] Although the embodiments disclosed in the present invention are as described above, the above content is only an embodiment adopted for the convenience of understanding the present invention and is not intended to limit the present invention. Any person skilled in the art within the technical field to which the present invention pertains may make any modifications and variations in the form and details of the implementation without departing from the spirit and scope disclosed by the present invention. However, the scope of patent protection of the present invention shall still be subject to the scope defined by the appended claims.

Claims

1. A method for evaluating the brittleness of shale using T1-T2 two-dimensional nuclear magnetic resonance, characterized in that, The method includes: A sample preparation step of collecting a set number of fresh and well-preserved shale samples for the reservoir to be evaluated; A nuclear magnetic resonance analysis step of, after recording the weight, performing T1-T2 two-dimensional nuclear magnetic resonance analysis on each shale sample based on set configuration parameters to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements; An organic carbon content calculation step of determining the range of the organic carbon signal interval and calculating the organic carbon content corresponding to the shale sample using a pre-constructed organic carbon calculation model according to the percentage content corresponding to the area of the organic carbon signal within the interval; A clay mineral content calculation step of determining the range of the target clay mineral signal interval and calculating the content of the target plastic clay minerals except illite based on the signal area within the target interval; A shale brittleness evaluation step of calculating the brittle mineral content and brittleness index of the shale sample based on the obtained organic carbon content and the content of the target plastic clay minerals, and performing a grading evaluation on the brittleness of the shale sample based on the calculation results; Among them, the organic carbon calculation model is obtained by training based on the organic carbon analysis results of a set number of training shale samples and the relative content percentages of the signals in the corresponding intervals of the two-dimensional nuclear magnetic resonance analysis spectrum in the model establishment step; In the model establishment step, the organic carbon calculation model is established through the following operations: Preparing a set number of fresh and well-preserved shale samples as training shale samples; After recording the weight, performing a total organic carbon analysis on each training shale sample to obtain the corresponding organic carbon content data; Performing T1-T2 two-dimensional nuclear magnetic resonance analysis on each training shale sample to obtain a T1-T2 spectrum with a signal-to-noise ratio and signal peaks meeting the set requirements; Determining the range of the organic carbon signal interval and calculating the relative content percentage corresponding to the area of the organic carbon signal of each training shale sample based on the signal area within the interval range; Training the corresponding organic carbon calculation model based on the relative content percentage of the organic carbon signal area and the obtained organic carbon content data.

2. The method according to claim 1, wherein In the nuclear magnetic resonance analysis step, the magnetic field intensity of the T1-T2 two-dimensional nuclear magnetic resonance analysis instrument is 20 ± 5Mhz, the probe aperture is not less than 15mm, the pulse sequence is the inversion recovery method (IR-CPMG), and the inversion method is the regularization method.

3. The method according to claim 1, characterized in that, In the nuclear magnetic resonance analysis step, the obtained effective T1-T2 spectrum meets the requirements that the signal-to-noise ratio is not less than 1000 and the number of signal peaks is not less than 3.

4. The method according to claim 1, characterized in that, The organic carbon calculation model is established as shown in the following formula: where C TOC is the organic carbon content of the target shale sample, a and b are regression coefficients, and ∑A i is the sum of the effective signal areas of the corresponding shale samples.

5. The method according to claim 1, wherein In the clay mineral content calculation step, it includes: Calculating the relative content percentage corresponding to the area of the clay signal of the shale sample based on the signal area within the target interval range; Inputting the relative content percentage of the clay signal area into a pre-constructed plastic mineral calculation model to obtain the content of the target plastic clay minerals except illite in the current shale sample.

6. The method according to claim 5, characterized in that, Calculating the relative content percentage corresponding to the area of the clay signal of the shale sample according to the following formula: Wherein, S cly-b represents the clay-bound water saturation, and S cly-c represents the capillary-bound water saturation. A cly-b is the signal peak area of the clay-bound water; A cly-c is the signal peak area of the capillary-bound water, and ∑A i is the sum of the effective signal areas of the corresponding shale samples.

7. The method according to claim 1, characterized in that, In the model establishment step, it further includes: Performing X-ray diffraction analysis on each training shale sample to obtain the corresponding mineral and clay mineral analysis data; Determine the signal interval range of clay minerals based on the T1-T2 spectrogram of the training shale samples, and calculate the relative content percentage corresponding to the signal area of the target clay minerals except illite in each training shale sample based on the signal area within the interval range. Based on the plastic mineral content data calculated from the mineral and clay mineral analysis data, and train a corresponding plastic mineral calculation model based on the relative content percentage of the signal area of the target clay minerals in combination therewith.

8. The method according to claim 7, wherein Calculate the plastic mineral content data according to the following formula based on the mineral and clay mineral analysis data: Wherein, C P-clay is the total amount of plastic clay minerals; C I / S , C C , C K , …… are the contents of clay minerals other than illite, including the content of illite-smectite mixed layer (C I / S ), the content of chlorite (C C ), and the content of kaolinite (C K ); C clay is the content of clay minerals.

9. The method according to claim 1, wherein In the brittle evaluation step, calculate the brittle mineral content of the shale sample according to the following formula: C b = 100% - (C TOC + C p-clay ) Where C b is the brittle mineral content of the target shale sample, C TOC is the organic matter content of the target shale sample, and C p-clay is the content of plastic clay minerals other than illite in the target shale sample.

10. A storage medium, characterized in that, Program code for implementing the method according to any one of claims 1 to 9 is stored on the storage medium.

11. A system for evaluating the brittleness of shale using T1-T2 two-dimensional nuclear magnetic resonance, characterized in that, The system executes the method according to any one of claims 1 to 9.

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