T-based 2 Clay type recognition method, device and storage medium based on spectral morphology

Abstract

The present invention provides a method, device and storage medium for identifying clay types based on T2 spectrum morphology, belonging to the fields of petroleum, natural gas geology and exploration and development engineering. The present invention takes core samples of the target interval, conducts X-ray diffraction experiments to clarify the types and contents of clay minerals; performs depth alignment on the cores, calibrates nuclear magnetic resonance logging data using the types of core clay minerals, and extracts characteristic parameters of the clay-bound water interval of nuclear magnetic resonance logging; divides each clay-bound water interval into the sum S of the left pore components and the sum S of the right pore components with the T2 time of the clay-bound water peak as the axis, and constructs sensitive parameters using T p , T A , S B , S 2L , S 2R , S A , S B ; constructs a clay type identification chart using the constructed sensitive parameters in combination with the experimental results of core clay mineral types and clay contents, and finally forms a continuous clay mineral identification result longitudinally in the wellbore. The present invention can accurately identify clay types. p as the axis, and divides it into the sum S of the left pore components A and the sum S of the right pore components B , and constructs sensitive parameters using T 2L , T 2R , S A , S B 2L , T 2R 2R , S A A and S B B ; constructs a clay type identification chart using the constructed sensitive parameters in combination with the experimental results of core clay mineral types and clay contents, and finally forms a continuous clay mineral identification result longitudinally in the wellbore. The present invention can accurately identify clay types.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploitation, and particularly to a method, device and storage medium for identifying clay types based on T 2 spectrum morphology. Background Art

[0002] Currently, the methods for identifying clay types are mainly divided into three categories, and each category has its own deficiencies:

[0003] The first category is experimental analysis method. Experimental analysis methods include X-ray diffraction method, infrared spectroscopy, scanning electron microscopy and thermogravimetric analysis to identify clay mineral types. X-ray diffraction is the most commonly used and authoritative method, and there is a clear industry standard in the industry - "Geological and Mineral Industry Standard of the People's Republic of China" (DZ / T 0206-2013). This method irradiates the sample with X-rays and analyzes the crystal plane spacing of the mineral according to the diffraction pattern to determine the type of clay mineral. The advantage of X-ray diffraction is that the identification accuracy is relatively high. It can not only identify the type of clay mineral, but also semi-quantitatively calculate the content of clay mineral. Scanning electron microscopy, infrared spectroscopy, thermogravimetric analysis, etc. identify clay minerals by means of optical observation or heavy ion adsorption. Although experimental methods, especially X-ray diffraction method, can accurately and directly judge the type of clay mineral, due to the high cost of continuous coring, it is difficult to obtain enough cores for experiments, and it is impossible to continuously characterize clay minerals longitudinally.

[0004] The second category is natural gamma ray spectrometry logging. Different types of clay minerals contain different proportions of radioactive elements. For example, illite is rich in potassium, and montmorillonite is related to specific uranium and thorium elements. Natural gamma ray spectrometry logging measures the gamma ray spectrum of the formation, separates the characteristic spectral peaks of radioactive isotopes through processing, calculates the content of each isotope, and establishes an identification chart for clay types to indirectly judge the type of clay mineral. The problem with this method is that there may be multiple minerals containing uranium, thorium, and potassium in the same formation, and the distribution and proportion of radioactive elements between different minerals are not fixed, resulting in the difficulty of uniquely corresponding a single gamma ray intensity data to a specific clay mineral. In addition, natural gamma ray spectrometry logging is extremely susceptible to interference from radioactive minerals in the formation, making the measurement results distorted.

[0005] The third category is the conventional curve inversion method. The conventional curve inversion method identifies and calculates the relative volume content of each clay mineral by finding sensitive curves with obvious responses of clay minerals and through methods such as combined modeling and multiple regression analysis. However, the common problem with conventional curves is strong multi-solution and low calculation accuracy. Summary of the Invention

[0006] Aiming at the problems of the prior art, the present invention provides a method for identifying clay types based on T 2 spectrum morphology, which uses nuclear magnetic logging T2 Identifying clay types based on the distribution and morphological characteristics of the clay-bound water peak in the spectrum, and solving the problem that the existing logging evaluation methods cannot accurately identify clay types.

[0007] The present invention provides a method for identifying clay types based on the 2 spectrum morphology, comprising the following steps:

[0008] Step 1): Take core samples from the target interval, conduct X-ray diffraction experiments to clarify the clay mineral types and contents;

[0009] Step 2): Perform depth alignment on the core;

[0010] Step 3): Based on the depth alignment of the core in Step 2), calibrate the nuclear magnetic resonance logging data using the clay mineral types of the core, and extract the characteristic parameters of the clay-bound water interval in the nuclear magnetic resonance logging: the transverse relaxation time T corresponding to the peak value of the clay peak p , the minimum T of the clay-bound water interval 2 time (T 2 time is the relaxation time) T 2L , the maximum T of the clay-bound water interval 2 time T 2R ;

[0011] Step 4): Divide each clay-bound water interval into the sum S of the left pore components and the sum S of the right pore components with the clay-bound water peak T 2 time as the axis p , and use T A , T B , S 2L , and S 2R to construct sensitive parameters for characterizing the morphology and distribution of the clay peak; A and S B ;

[0012] Step 5): Construct a clay type identification chart using the constructed sensitive parameters in combination with the experimental results of the clay mineral types and clay contents of the core. The established clay type identification chart is used to qualitatively identify the clay types in the formation, and finally form a continuous clay mineral identification result in the vertical direction of the wellbore.

[0013] Preferably, in Step 2), the effective porosity of the core samples in the X-ray diffraction experiment in Step 1) is jointly measured, and the core is depth-aligned using the results of the joint measurement of the effective porosity.

[0014] Preferably, the extraction of the maximum T 2 time T 2R of the clay-bound water interval in Step 3) is divided into three cases:

[0015] If the clay-bound water interval does not overlap with other spectra, the maximum T of the clay-bound water is considered 2 Time T 2R That is, the relaxation time when the pore component in the clay-bound water interval decreases to 0;

[0016] If the clay-bound water interval overlaps with other spectra, then n sampling points are continuously selected on the right side of the first peak of the superimposed spectrum. According to the above n sampling points, a trend line is fitted, the spectrum line of the clay-bound water interval in the overlapping area is predicted, and then the relaxation time when the porosity component corresponding to the trend line in the clay-bound water interval decays to 0 is used as T 2R ;

[0017] If the peak value of the clay-bound water is less than the preset peak value and the length of the clay-bound water interval is less than the preset maximum T of the clay 2 Time, then mirror fitting is directly performed on the right side of the peak value of the clay-bound water peak according to the spectrum line on the left side of the peak.

[0018] Preferably, the method for fitting the trend line according to the above n sampling points includes mathematical fitting methods such as the least squares method.

[0019] Preferably, the preset maximum T of the clay 2 Time is determined by the type of clay mineral with the maximum T 2 Time in the formation; the preset peak value is the maximum peak value of the superimposed spectrum.

[0020] Preferably, the preset maximum T of the clay 2 Time is 16 ms.

[0021] Preferably, the constructed sensitive parameter includes the distribution characteristic parameter relaxation time variable τ, where the relaxation time variable τ is determined by a function 2L Related to T 2R And T f Determined, characterizing the characteristics of different clay peaks in terms of relaxation time, τ = f (T 2L , T 2R ).

[0022] In the formula, T 2L 、T 2R Are respectively the minimum T 2 Time and the maximum T 2 Time of the clay-bound water, ms.

[0023] Preferably, the expression form of the constructed relaxation time variable τ is τ = a (log T 2R - log T 2L ), where a is a coefficient.

[0024] Preferably, the constructed sensitive parameters include the spectral form variable δ of the morphological feature parameters. The spectral form variable δ is determined by a function g related to S A , S B and characterizes the characteristics of different clay peaks in terms of spectral form. δ = g(S A , S B ); S A and S B are respectively the sum of the left pore components and the sum of the right pore components of the clay peak, in decimals.

[0025] Preferably, the expression form of the constructed spectral form variable δ is δ = b (S B / S A ), where b is a coefficient.

[0026] Preferably, among them, the calculation processes of S A and S B are as follows:

[0027]

[0028]

[0029] Among them, φ i is the porosity component of the i-th relaxation time, in decimals.

[0030] Preferably, the method for constructing the chart is as follows: Using the relaxation time variable τ and the spectral form variable δ as the horizontal and vertical coordinate axes respectively, the change of the relaxation time variable τ represents the relative change of the clay composition; the change of the spectral form variable δ represents the change of the clay mixed layer state.

[0031] The present invention also provides a clay type identification device based on the T 2 spectral form, including a processor. The processor can execute a computer program, and the computer program can implement the above-mentioned clay type identification method based on the T 2 spectral form.

[0032] The present invention also provides a storage medium that stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned clay type identification method based on the T 2 spectral form.

[0033] Compared with the prior art, the present invention has at least the following beneficial effects:

[0034] (1) Comparison with existing experimental analysis methods: Although experimental methods, especially X-ray diffraction, can accurately and directly determine the types of clay minerals, continuous coring is costly, it is difficult to obtain sufficient cores for experiments, and it is impossible to continuously characterize clay minerals longitudinally. After calibration with regional experimental results, the present invention can perform continuous evaluation longitudinally.

[0035] (2) Comparison with natural gamma-ray spectrometry logging: When natural gamma-ray spectrometry logging detects the total amounts of three radioactive elements, uranium (U), thorium (Th), and potassium (K), in a formation, it cannot finely distinguish the specific types of different clay minerals with the same radioactive element content. At the same time, in the same formation, there may be multiple minerals containing uranium, thorium, and potassium simultaneously, and the distribution of radioactive elements among different minerals is not absolutely fixed, resulting in difficulty in uniquely corresponding a single gamma-ray intensity data to a specific clay mineral. In addition, natural gamma-ray spectrometry logging is extremely susceptible to interference from radioactive minerals in the formation, making the measurement results distorted. The present invention analyzes the morphology and distribution of the clay peaks of the nuclear magnetic resonance T 2 spectrum. Based on the calibration of the clay mineral types in the core, key parameters are found to characterize the clay peaks, sensitive parameters are constructed from the differences in relaxation time and peak area, characteristic charts of different clay mineral types are established, and then the types of clay minerals are identified, avoiding the problems encountered in natural gamma-ray spectrometry logging.

[0036] (3) Comparison with conventional curve inversion methods: Conventional curve inversion methods often search for sensitive curves with obvious responses of clay minerals, such as array induction logging curves and natural gamma curves, and identify and calculate the relative volume contents of various clay minerals through methods such as combined modeling and multiple regression analysis. However, the common problem of conventional curves is that they are greatly affected by pore structure, fluid properties, borehole environment, etc., have strong multi-solution characteristics, the curve modeling is often too ideal, and the calculation accuracy is low. The basis of this innovative method is nuclear magnetic resonance logging data. It utilizes the changes in the morphology and distribution of clay peaks caused by differences in the structures and adsorption capacities of different clay minerals. The relaxation time of the clay peak distribution is relatively early, and it is little affected by fluid properties, borehole environment, etc., solving the multi-solution problem encountered in conventional curve inversion methods.

[0037] In summary, the physical meaning and evaluation method of the present invention are completely different from those of the above methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 In (a), (b), and (c) of are the clay peak identification and fitting methods in three different situations of an embodiment of the present invention. (a) is the situation where the clay peak does not overlap with other spectral peaks. At this time, the leftmost first peak is the clay peak, and the two intersections of this peak with the x-axis are T 2L and T 2R; (b) shows the case when the clay peak overlaps with other spectral peaks. The superimposed spectrum in the figure is composed of three different single peaks (shaded in the figure). Take n sampling points (5 in the figure) on the right side of the peak value of the first peak in the superimposed spectrum for trend line fitting. The intersection of the fitted spectral line and the T 2 relaxation time coordinate axis is T 2R , and the intersection on the left side of the corresponding spectral peak is T 2L ; (c) shows the case when the clay peak is very small or not obvious. At this time, mirror the left spectral line of the clay peak directly on the right side of the peak value. The intersection of the fitted spectral line and the T 2 relaxation time coordinate axis is T 2R。

[0039] Figure 2 The following is an explanation of the spectral form index δ. In the figure, the clay peak is divided into the sum S 2 of the left pore components and the sum S p of the right pore components with the peak time T A as the axis to construct the spectral form index δ. B

[0040] Figure 3 This is a clay type identification chart established based on certain wells in an oilfield in an embodiment of the present invention.

[0041] Figure 4 This is the clay type identification result chart of Well A in an oilfield in an embodiment of the present invention. From left to right, the first track is the depth track, the second to fourth tracks are the conventional curve tracks, the fifth track is the nuclear magnetic resonance T 2 spectrum track, and the sixth track is the result of the identified clay type.

[0042] Figure 5 This is the flow chart of the clay type identification method based on the T 2 spectral form in an embodiment of the present invention. Detailed implementation manners

[0043] The following will describe in detail the specific implementation manners of the present invention with reference to the accompanying drawings.

[0044] As Figure 5 shown, the present invention provides a clay type identification method based on the T 2 spectral form, including the following steps:

[0045] Step 1): Take core samples of the target interval, conduct X-ray diffraction experiments to clarify the types and contents of clay minerals;

[0046] Step 2): Perform depth alignment on the core;

[0047] ​Step 3): Based on the core depth alignment in Step 2), calibrate the nuclear magnetic resonance logging data using the core clay mineral types, and extract the characteristic parameters of the clay-bound water interval in the nuclear magnetic resonance logging: the transverse relaxation time T corresponding to the peak value of the clay p , the minimum T of the clay-bound water interval 2 time T 2L , the maximum T of the clay-bound water interval 2 time T 2R ;

[0048] Step 4): Divide each clay-bound water interval with the peak value T of the clay-bound water 2 time as the axis T p into the sum S of the left pore components A and the sum S of the right pore components B . Use T 2L , T 2R , S A and S B to construct sensitive parameters for characterizing the morphology and distribution of the clay peak;

[0049] Step 5): Combine the constructed sensitive parameters with the core clay mineral types and the experimental results of the clay content to construct a clay type identification chart. The established clay type identification chart is used to qualitatively identify the formation clay types, and finally form a continuous clay mineral identification result in the longitudinal direction of the wellbore.

[0050] According to a specific implementation of the present invention, in Step 2), perform an effective porosity joint measurement on the core samples in the X-ray diffraction experiment in Step 1), and use the results of the effective porosity joint measurement to align the core depth.

[0051] According to a specific implementation of the present invention, the extraction of the maximum T of the clay-bound water interval in Step 3) 2 time T 2R is divided into three cases:

[0052] If the clay-bound water interval does not overlap with other spectra, it is considered that the maximum T of the clay-bound water 2 time T 2R is the relaxation time when the pore component in the clay-bound water interval decreases to 0;

[0053] If the clay-bound water interval overlaps with other spectra, continuously select n sampling points on the right side of the first peak of the superimposed spectrum. Fit a trend line based on the above n sampling points, predict the spectrum shape of the clay-bound water interval in the overlapping area, and then use the relaxation time when the porosity component corresponding to the trend line in the clay-bound water interval decays to 0 as T 2R ;

[0054] If the peak value of clay-bound water is less than the preset peak value and the length of the clay-bound water interval is less than the preset maximum T 2 time of clay, then directly perform mirror fitting on the right side of the peak value of the clay-bound water peak according to the spectral line on the left side of the peak value.

[0055] According to a specific embodiment of the present invention, the method for fitting the trend line based on the above n sampling points includes mathematical fitting methods such as the least squares method.

[0056] According to a specific embodiment of the present invention, the preset maximum T 2 time of clay is determined by the type of clay mineral with the maximum T 2 time in the formation. (For example, illite is generally less than 2 ms, montmorillonite is less than 1 ms, chlorite is about 5 ms, and kaolinite is 8 - 16 ms. If there is only illite-smectite mixed layer in the formation, then the preset maximum T 2 time of clay is 2 ms; if there is illite-smectite mixed layer and kaolinite in the formation, then the preset maximum T 2 time of clay is 16 ms); the preset peak value is the maximum peak value of the superimposed spectrum.

[0057] According to a specific embodiment of the present invention, the preset maximum T 2 time of clay is 16 ms.

[0058] According to a specific embodiment of the present invention, the constructed sensitive parameters include the distribution characteristic parameter relaxation time variable τ, where the relaxation time variable τ is determined by a function 2L related to T 2R and T f and characterizes the characteristics of different clay peaks in terms of relaxation time. τ = f (T 2L , T 2R ), where in the formula, T 2L , T 2R are respectively the minimum T 2 time and the maximum T 2 time of clay-bound water, in ms.

[0059] According to a specific embodiment of the present invention, the expression form of the constructed relaxation time variable τ is τ = a(log T 2R - log T 2L ), and a is a coefficient.

[0060] According to a specific embodiment of the present invention, the constructed sensitive parameters include the morphological characteristic parameter spectral morphology variable δ. The spectral morphology variable δ is determined by a function g related to S A , S B and characterizes the characteristics of different clay peaks in terms of spectral morphology. δ = g(S A , SB );S A and S B are the sum of the left pore components and the sum of the right pore components of the clay peak, respectively, in decimals.

[0061] According to a specific embodiment of the present invention, the expression form of the constructed spectral form variable δ is δ = b (S B / S A ), where b is a coefficient.

[0062] According to a specific embodiment of the present invention, among them, S A , S B The calculation process is as follows:

[0063]

[0064]

[0065] Among them, φ i is the porosity component of the i-th relaxation time, in decimals.

[0066] According to a specific embodiment of the present invention, the method for constructing the chart is as follows: taking the relaxation time variable τ and the spectral form variable δ as the horizontal and vertical coordinate axes respectively, the change of the relaxation time variable τ represents the relative change of the clay composition; the change of the spectral form variable δ represents the change of the clay mixed layer state.

[0067] The present invention also provides a clay type identification device based on the T 2 spectral form, including a processor, the processor can execute a computer program, and the computer program can implement the above-mentioned clay type identification method based on the T 2 spectral form.

[0068] The present invention also provides a storage medium, the storage medium stores a computer program, and when the computer program is executed by the processor, it implements the above-mentioned clay type identification method based on the T 2 spectral form.

[0069] Example

[0070] Step 1) Conduct X-ray diffraction experiments on the cores of the target interval to clarify the clay mineral types and contents. In this example, the target interval is located in the Wuerhe Formation of the Permian in the Junggar Basin, and the mainly developed clay minerals are illite, chlorite and montmorillonite, and the mainly developed clay mixed layer states are illite-smectite mixed layer and chlorite-smectite mixed layer.

[0071] Step 2) is to use the core effective porosity results as the basis, after accurately locating the core, use the core clay mineral type to calibrate the NMR logging data, and extract the clay bound water interval characteristic parameters of the NMR logging: the transverse relaxation time T corresponding to the clay peak value p , the minimum T of clay bound water interval 2 Time T 2L , the maximum T of the clay bound water interval 2 Time T 2R This example uses Schlumberger CMR nuclear magnetic logging data. The key parameter to be extracted here is the transverse relaxation time T corresponding to the clay peak value. p , the minimum T of clay bound water interval 2 Time T 2L , the maximum T of the clay bound water interval 2 Time T 2R . At the extraction of clay peak T 2L 、T 2R There are three different types of T 2 Spectral form: The first is Figure 1 (a) shows T 2 The clay bound water interval does not overlap with other spectra, so the morphology of the clay peak can be used to directly characterize the clay type and directly extract the peak and T 2 The intersection of the two ends of the relaxation time coordinate axis is T 2L 、T 2R The second is Figure 1 (b) shows T 2 The peaks of the spectrum, clay peaks and capillary bound water peaks are superimposed together. For this superimposed peak, first compare it with T 2 The intersection point on the left side of the relaxation time axis is defined as T 2L Then, several sampling points (5 in this embodiment) are selected continuously on the right side of the first peak, and trend line fitting is performed with these sampling points (the least squares fitting method is used in this embodiment), and the second half of the clay peak is predicted, and then the clay peak at this time is compared with T 2 The intersection point of the relaxation time coordinate axis is defined as T 2R , which can minimize the influence of other spectra. The third is Figure 1 (c) shows T 2 Spectral peak, at this time, the clay bound water peak is very small or not obvious, the clay bound water peak is less than the preset peak and the clay bound water interval length is less than the preset clay maximum T 2 time, then directly perform mirror fitting on the right side of the bound water peak according to the left spectrum line, and read the T at this time 2L 、T 2R .

[0072] Step 3) Each clay peak obtained in step 2) is divided into peak value T 2 Time T p The axis is divided into the sum of the left pore components S A and the sum of the right pore components S B ,like Figure 2 As shown. Using T 2L 、T 2R , S A , S B Construct sensitive parameters relaxation time variable τ and spectral morphology variable δ.

[0073] In this embodiment, the expressions of the constructed relaxation time variable τ and spectral morphology variable δ are respectively

[0074] τ =0.983 * (lg T 2R -lg T 2L )

[0075] δ =1.026 * (S B / S A )

[0076] Among them, S A , S B The expression is:

[0077]

[0078]

[0079] Where, T 2L 、T 2R are the minimum T of clay bound water. 2 Time and maximum T 2 Time, ms; S A and S B The sum of the left pore component and the right pore component of the clay peak, respectively, decimal; φ i is the porosity component of the ith relaxation time, a decimal.

[0080] Step 4) Use the sensitive parameters constructed in step 3) and the clay mineral type and content experimental results of the target layer core to construct a clay type identification chart, such as Figure 3As shown below. In this embodiment, the method for constructing the chart is as follows: A clay type identification chart is constructed with the relaxation time variable τ as the abscissa and the spectral form variable δ as the ordinate. In this embodiment, the change in the relaxation time variable τ represents the relative change in clay composition. As the relaxation time exponent increases, the clay mineral type gradually transitions from mainly illite-smectite mixed layer to mainly chlorite. This is because the relaxation times of montmorillonite (<1 ms) and illite (<2 ms) are short, while the relaxation time of chlorite is relatively long (≈5 ms); the change in the spectral form variable δ represents the change in the clay mixed layer state. As the spectral form variable increases, the mixed layer type gradually transitions from the illite + illite-smectite mixed layer combination to the chlorite + chlorite-smectite mixed layer combination. This is due to the skewness in different directions of the two combinations on the nuclear magnetic spectrum (such as Figure 2 the skewness type shown is right skewness).

[0081] Step 5) Qualitatively identify the formation clay type using the established chart, and finally form a continuous clay mineral identification result longitudinally in the wellbore, as shown in Figure 4 below. Figure 4 The figure shows the clay type identification result chart of an example well in an oilfield. It can be seen that a set of glutenite reservoirs are developed in the depth section of 4952 - 4958 m. According to the clay type identification result, there are four clay types developed in this reservoir: illite + illite-smectite mixed layer, illite-smectite mixed layer, chlorite, and chlorite + chlorite-smectite mixed layer, and there is a relatively fast change in clay type longitudinally. Combining with the XRD results analysis of this depth section in Table 1, the clay type identification method proposed by the present invention is in good agreement with the experimental results. This example shows that the present invention can perform relatively accurate clay type identification.

[0082] Table 1

[0083]

[0084] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included within the protection scope of the present invention.

Claims

1. A method for identifying clay types based on T2 spectrum morphology, characterized in that: The steps include: Step 1): Take core samples from the target layer and conduct X-ray diffraction experiments to determine the type and content of clay minerals; Step 2): Depth homing of the core; Step 3): Based on the core depth return in step 2), the core clay mineral type is used to calibrate the NMR logging data, and the characteristic parameters of the clay bound water interval in the NMR logging are extracted: the transverse relaxation time T corresponding to the clay peak value p , the minimum T2 time T of the clay bound water interval 2L , the maximum T2 time T of the clay bound water interval 2R ; Step 4): divide each clay bound water interval into T2 times according to the clay bound water peak value. p is the axis, divided into the sum of the left pore components S A and the sum of the right pore components S B , using T 2L , T 2R , S A and S B Sensitive parameters were constructed to characterize the morphology and distribution of clay peaks; Step 5): A clay type identification chart is constructed based on the constructed sensitive parameters combined with the core clay mineral type and clay content experimental results. The established clay type identification chart is used to qualitatively identify the formation clay type, and ultimately forms a continuous clay mineral identification result in the vertical direction of the wellbore; Among them, the sensitive parameters constructed include the distribution characteristic parameter relaxation time variable τ, where the relaxation time variable τ is determined by T 2L and T 2R Related functions f Determined, it characterizes the characteristics of different clay peaks in relaxation time, τ = f (T 2L , T 2R ); Where, T 2L , T 2R The minimum T2 time and maximum T2 time of clay bound water, ms, respectively; The constructed relaxation time variable τ is expressed as τ = a (log T 2R -log T 2L ), where a is the coefficient; The sensitive parameters constructed include the morphological characteristic parameter spectrum morphological variable δ, which is composed of S A , S B The relevant function g is determined to characterize the characteristics of different clay peaks in the spectral morphology, δ = g(S A , S B );S A and S B are the sum of the left pore component and the sum of the right pore component of the clay peak, respectively, in decimals; The constructed spectral morphology variable δ is expressed as δ = b (S B / S A ), where b is the coefficient; Among them, S A , S B The calculation process is: Among them, φ i is the porosity component of the ith relaxation time, a decimal; The construction method of the figure is as follows: the relaxation time variable τ and the spectral morphology variable δ are the horizontal and vertical axes respectively. The change of the relaxation time variable τ represents the relative change of the clay component; the change of the spectral morphology variable δ represents the change of the clay mixed layer state.

2. The method for identifying clay types based on T2 spectrum morphology according to claim 1, characterized in that: In step 2), the effective porosity of the core samples from the X-ray diffraction experiment in step 1) is measured, and the depth of the core is traced using the effective porosity measurement results.

3. The method for identifying clay types based on T2 spectrum morphology according to claim 1, characterized in that: The maximum T2 time T of the clay bound water interval in step 3) 2R There are three cases of extraction: If the clay bound water interval does not overlap with other spectra, the maximum T2 time of clay bound water is considered to be 2R It is the relaxation time for the pore component in the bound water interval of clay to decrease to 0; If the clay bound water interval overlaps with other spectra, n sampling points are continuously selected on the right side of the first peak of the superimposed spectrum, and a trend line is fitted based on the n sampling points to predict the spectrum shape of the clay bound water interval in the overlapping area. Then, the relaxation time when the porosity component corresponding to the trend line in the clay bound water interval decays to 0 is taken as T. 2R ; If the clay bound water peak is less than the preset peak and the clay bound water interval length is less than the preset clay maximum T2 time, a mirror image fitting is performed directly on the right side of the clay bound water peak according to the spectrum line on the left side of the peak.

4. The method for identifying clay types based on T2 spectrum morphology according to claim 3, characterized in that: The method for fitting the trend line based on the above n sampling points includes mathematical fitting methods such as the least square method.

5. The method for identifying clay types based on T2 spectrum morphology according to claim 3, characterized in that: The preset maximum clay T2 time is determined by the type of clay mineral with the maximum T2 time in the formation; the preset peak value is the maximum peak value of the superposition spectrum.

6. The method for identifying clay types based on T2 spectrum morphology according to claim 5, characterized in that: The default clay maximum T2 time is 16ms.

7. A clay type identification device based on T2 spectrum morphology, characterized in that: The invention comprises a processor, wherein the processor is capable of executing a computer program, and the computer program can implement the clay type identification method based on T2 spectrum morphology as described in any one of claims 1 to 6.

8. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the clay type identification method based on T2 spectrum morphology as described in any one of claims 1 to 6.

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