Shale pore fluid type and porosity determination method, equipment and medium

Abstract

The invention provides a shale pore fluid type and porosity determination method, equipment and a medium. According to the method, nuclear magnetic resonance logging data of shale in a target layer section are obtained, T2 spectrum component stripping treatment is carried out on the nuclear magnetic resonance logging data to obtain a plurality of corresponding nuclear magnetic resonance logging T2 sub-spectrums, pore fluid type calibration characteristics are determined according to the difference condition of T1-T2 spectrograms of shale with different clay mineral contents and in different rock core saturation states, and the pore fluid type calibration characteristics are determined according to the difference condition of the T1-T2 spectrograms of shale with different clay mineral contents. Performing fluid type calibration on the plurality of nuclear magnetic resonance logging T2 sub-spectrums on the basis of the pore fluid type calibration characteristics to obtain a fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum, and further determining the effective porosity and the movable fluid porosity of the shale on the basis of the plurality of nuclear magnetic resonance logging T2 sub-spectrums and the corresponding fluid types. According to the method, the calculation precision of the porosity is improved, and meanwhile, a simple, convenient and reliable method is provided for fluid type judgment and porosity calculation of well logging which only measures one-dimensional nuclear magnetic resonance well logging and does not have a coring nuclear magnetic resonance experiment.

Description

Technical Field

[0001] The present application relates to the field of oil and gas exploration technology, and in particular to a method, device, and medium for determining the type and porosity of shale pore fluid. Background Art

[0002] Shale, as a typical unconventional reservoir, is characterized by a mixture of fine-grained minerals from multiple sources and types, and a complex micro- and nano-pore structure. The quality evaluation and efficient development of shale oil reservoirs rely heavily on the accurate characterization of the fluid mobility in shale pores. Its oil and gas accumulation process is characterized by a self-generation and self-storage model of organic matter generation and expulsion of hydrocarbons and in-situ enrichment and retention, which is significantly different from conventional buoyancy-driven reservoirs. This particularity makes the fluid types and spatial distribution in shale pores more complex and difficult to accurately characterize. The pore spaces in shale reservoirs that can store oil and gas are all effective pores, that is, the effective porosity only excludes the portion occupied by clay-bound water. Therefore, accurately calculating the effective porosity of shale is crucial for reservoir evaluation.

[0003] Currently, the common methods for determining the effective porosity of shale in existing technologies include: core experimental analysis method and well logging T2 cutoff value method;

[0004] Core analysis primarily utilizes a two-dimensional nuclear magnetic resonance (NMR) core analyzer to measure core samples. Fluid identification and porosity calculation are achieved by establishing a T1-T2 fluid type identification chart. However, due to the high cost of downhole shale coring and laboratory measurements, continuous vertical characterization is difficult to achieve. Furthermore, parameters such as magnetic field strength and frequency are not standardized across instruments, making it difficult to directly calibrate the test results and apply them to NMR logging data analysis.

[0005] The logging T2 cutoff value method is based on the difference in T2 relaxation time distribution of different pore fluids. 2cutoff ) divides the fluid intervals and calculates the corresponding porosity using an integral method. However, neither the fixed T2 cutoff nor the variable T2 cutoff method fully considers the complex pore structure and fluid distribution characteristics of shale. This, coupled with abnormal noise interference during logging, leads to large errors in porosity calculations, seriously affecting the accuracy of shale reservoir quality evaluation. Summary of the Invention

[0006] The embodiments of the present application provide a method, device, and medium for determining the type and porosity of shale pore fluid, which are used to solve the problems in the prior art of difficulty in classifying shale pore fluid types and low accuracy in calculating effective porosity.

[0007] In a first aspect, the present application provides a method for determining the type and porosity of shale pore fluid, the method comprising:

[0008] Acquiring nuclear magnetic resonance logging data of shale in a target layer, and performing T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain corresponding multiple nuclear magnetic resonance logging T2 sub-spectra;

[0009] The pore fluid type calibration feature is used to calibrate the fluid type of the multiple nuclear magnetic resonance logging T2 sub-spectra to obtain the fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum, wherein the pore fluid type calibration feature is used to indicate the T1-T2 signal interval distribution corresponding to the multiple pore fluid types, and the pore fluid type calibration feature is determined based on the differences in T1-T2 spectra under different clay mineral contents and different core saturation states.

[0010] Based on the multiple nuclear magnetic resonance logging T2 sub-spectra and the corresponding fluid types, the effective porosity and movable fluid porosity of the shale are determined.

[0011] In a possible implementation, performing T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra includes:

[0012] Independent component analysis technology is used to analyze the components of nuclear magnetic resonance logging data and obtain the corresponding T2 spectrum signal matrix;

[0013] Based on the sparse non-negative matrix decomposition technology, the T2 spectrum signal matrix is ​​subjected to multi-component signal and peak spectrum sorting processing to obtain multiple candidate nuclear magnetic resonance logging T2 sub-spectra;

[0014] Abnormal noise spectra are stripped from the plurality of candidate nuclear magnetic resonance logging T2 sub-spectra to obtain the plurality of nuclear magnetic resonance logging T2 sub-spectra.

[0015] In a possible implementation, before calibrating the fluid type of the plurality of NMR logging T2 sub-spectra using the pore fluid type calibration feature to obtain the fluid type corresponding to each NMR logging T2 sub-spectrum, the method further includes:

[0016] Obtaining compensated neutron logging data and clay mineral content of the shale in the target layer;

[0017] Determining the clay mineral structure water content of the target layer based on the nuclear magnetic resonance logging data and the compensated neutron logging data;

[0018] In the case of core depth regression, a mapping regression relationship is constructed based on the clay mineral structural water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale;

[0019] The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the clay mineral content of the continuous longitudinal shale to obtain the pore fluid type calibration characteristics.

[0020] In a possible implementation, the pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the continuous longitudinal shale clay mineral content to obtain the pore fluid type calibration feature, including:

[0021] Determine a low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum of a core sample of the shale in the target layer, wherein the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum is used to indicate the T1-T2 spectrum of the core sample at different core saturation states;

[0022] Determining the difference between the clay mineral content of the continuous longitudinal shale and the T1-T2 spectrum of the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment;

[0023] Based on the differences, the pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated to obtain the pore fluid type calibration characteristics.

[0024] In a possible implementation, the nuclear magnetic resonance logging data includes a nuclear magnetic resonance T2 spectrum. Before performing data analysis on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra, the method further includes:

[0025] determining a clay mineral content difference parameter based on the clay mineral content and the clay mineral content threshold;

[0026] Based on the clay mineral content difference parameter, the nuclear magnetic resonance T2 spectrum is standardized;

[0027] The normalized nuclear magnetic resonance T2 spectrum is smoothed and filtered.

[0028] In a possible implementation, the multiple nuclear magnetic resonance logging T2 sub-spectra include:

[0029] Clay-bound fluid spectrum, capillary-bound fluid spectrum, mesopore movable fluid spectrum and macropore movable fluid spectrum.

[0030] In a second aspect, the present application provides a device for determining the type and porosity of shale pore fluid, comprising:

[0031] An acquisition module is used to acquire nuclear magnetic resonance logging data of shale in a target layer, and perform T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra;

[0032] a processing module, configured to calibrate the fluid type of the plurality of nuclear magnetic resonance logging T2 sub-spectra using a pore fluid type calibration feature to obtain a fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum, wherein the pore fluid type calibration feature is used to indicate the distribution of T1-T2 signal intervals corresponding to the plurality of pore fluid types, and the pore fluid type calibration feature is determined based on differences in T1-T2 spectra for shales with different clay mineral contents and under different core saturation states;

[0033] The processing module is further configured to determine the effective porosity and movable fluid porosity of the shale based on the plurality of nuclear magnetic resonance logging T2 sub-spectra and corresponding fluid types.

[0034] In one possible implementation, the processing module is configured to perform component analysis on the nuclear magnetic resonance logging data using independent component analysis technology to obtain a corresponding T2 spectrum signal matrix; perform multi-component signal and peak spectrum sorting processing on the T2 spectrum signal matrix based on sparse non-negative matrix decomposition technology to obtain multiple candidate nuclear magnetic resonance logging T2 sub-spectra; and strip off abnormal noise spectra from the multiple candidate nuclear magnetic resonance logging T2 sub-spectra to obtain multiple nuclear magnetic resonance logging T2 sub-spectra.

[0035] In a possible implementation, the acquisition module is further configured to acquire compensated neutron logging data and clay mineral content of the shale in the target layer;

[0036] The processing module is further configured to determine the clay mineral structure water content of the target layer based on the target nuclear magnetic resonance sub-data and the compensated neutron logging data; and in the case of core depth retrieval, construct a mapping regression relationship based on the clay mineral structure water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale; and

[0037] The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the clay mineral content of the continuous longitudinal shale to obtain the pore fluid type calibration characteristics.

[0038] In one possible implementation, the processing module is used to determine the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum of the core sample of the shale in the target layer, and the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum is used to indicate the T1-T2 spectrum of the core sample under different core saturation states; determine the difference between the clay mineral content of the continuous longitudinal shale and the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum; and based on the difference, calibrate the pore fluid type and the corresponding T1-T2 signal interval distribution to obtain the pore fluid type calibration feature.

[0039] In one possible implementation, the processing module is further used to determine a clay mineral content difference parameter based on the clay mineral content and the clay mineral content threshold; standardize the nuclear magnetic resonance T2 spectrum based on the clay mineral content difference parameter; and perform smoothing filtering on the standardized nuclear magnetic resonance T2 spectrum.

[0040] In a possible implementation, the multiple nuclear magnetic resonance logging T2 sub-spectra include:

[0041] Clay-bound fluid spectrum, capillary-bound fluid spectrum, mesopore movable fluid spectrum and macropore movable fluid spectrum.

[0042] In a third aspect, the present application provides a device for determining the type and porosity of shale pore fluid, comprising:

[0043] The invention comprises: a processor, and a memory communicatively connected to the processor;

[0044] The memory stores computer-executable instructions;

[0045] The processor executes the computer-executable instructions stored in the memory to implement the method described in the first aspect and various possible implementations of the first aspect.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect and various possible implementation methods of the first aspect.

[0047] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in the first aspect and various possible implementation methods of the first aspect.

[0048] The present application provides a method, device and medium for determining the pore fluid type and porosity of shale. The method obtains nuclear magnetic resonance logging data of shale in a target layer and performs T2 spectrum component stripping processing on the data to obtain multiple corresponding nuclear magnetic resonance logging T2 sub-spectra. The pore fluid type calibration characteristics are determined according to the differences in T1-T2 spectra of shales with different clay mineral contents and under different core saturation states. The fluid type is calibrated for the multiple nuclear magnetic resonance logging T2 sub-spectra based on the pore fluid type calibration characteristics to obtain the fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectra. The effective porosity and movable fluid porosity of the shale are then determined based on the multiple nuclear magnetic resonance logging T2 sub-spectra and the corresponding fluid types. The method improves the calculation accuracy of the porosity and provides a simple and reliable method for fluid type identification and porosity calculation in logging that only measures one-dimensional nuclear magnetic co-logging and does not involve core nuclear magnetic resonance experiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] Figure 1 Schematic diagram of a method for determining shale pore fluid type and porosity provided in an embodiment of the present application Figure 1 ;

[0051] Figure 2 A schematic diagram of multiple T2 sub-spectra of nuclear magnetic resonance logging shown in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of multiple nuclear magnetic resonance logging T2 sub-spectra and pore fluid type calibration features provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of calculation results of effective porosity and movable fluid porosity provided in an embodiment of the present application;

[0054] Figure 5 Schematic diagram of a method for determining shale pore fluid type and porosity provided in an embodiment of the present application Figure 2 ;

[0055] Figure 6 This is a schematic diagram of a continuous longitudinal shale clay mineral content provided in an embodiment of the present application;

[0056] Figure 7 A schematic diagram of the structure of a device for determining the type and porosity of shale pore fluid provided in an embodiment of the present application;

[0057] Figure 8A schematic diagram of the structure of a device for determining the type and porosity of shale pore fluid provided in an embodiment of the present application.

[0058] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0060] The terms "first," "second," "third," "fourth," and so forth (if any) in the description and claims of the present invention and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or sequential sequence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0061] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described in this application as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0062] Shale, as a typical unconventional reservoir, is characterized by a mixture of fine-grained minerals from multiple sources and types, and a complex micro- and nano-pore structure. The quality evaluation and efficient development of shale oil reservoirs rely heavily on the accurate characterization of the fluid mobility in shale pores. Its oil and gas accumulation process is characterized by a self-generation and self-storage model of organic matter generation and expulsion of hydrocarbons and in-situ enrichment and retention, which is significantly different from conventional buoyancy-driven reservoirs. This particularity makes the fluid types and spatial distribution in shale pores more complex and difficult to accurately characterize. The pore spaces in shale reservoirs that can store oil and gas are all effective pores, that is, the effective porosity only excludes the portion occupied by clay-bound water. Therefore, accurately calculating the effective porosity of shale is crucial for reservoir evaluation.

[0063] Currently, the common methods for determining the effective porosity of shale in existing technologies include: core experimental analysis method and well logging T2 cutoff value method;

[0064] Core analysis primarily requires laboratory core measurements using a two-dimensional nuclear magnetic resonance (NMR) core analyzer to establish a T1-T2 fluid type identification chart, enabling fluid type identification and corresponding porosity calculation. However, due to the high cost of downhole shale coring and laboratory measurements, continuous vertical characterization is difficult to achieve. Furthermore, parameters such as magnetic field strength and frequency are not standardized across different instruments, making it difficult to directly calibrate the test results and apply them to NMR logging data analysis.

[0065] The logging T2 cutoff value method is based on the difference in T2 transverse relaxation time distribution of different pore fluids, and sets the cutoff value T of each fluid interval. 2cutoff , thus using the integral method to calculate the corresponding porosity. This method relies primarily on core experimental calibration logging to determine the T2 cutoff value, which is computationally simple. However, both the fixed T2 cutoff and the variable T2 cutoff methods lack consideration of factors such as the complex pore structure and fluid type distribution of shale. Especially for shales with high clay content and low porosity, overlapping signals such as clay-bound fluid and capillary-bound fluid are difficult to separate, and there is interference from abnormal noise signals. These issues can lead to large errors in porosity calculations, thereby affecting the evaluation of shale reservoir quality.

[0066] In response to the problems existing in the prior art, the present application provides a method for determining the pore fluid type and porosity of shale. The method obtains nuclear magnetic resonance logging data of shale in the target layer and performs T2 spectrum component stripping processing on it to obtain corresponding multiple nuclear magnetic resonance logging T2 sub-spectra. The pore fluid type calibration characteristics are determined according to the differences in T1-T2 spectra of shales with different clay mineral contents and under different core saturation states. Based on the pore fluid type calibration characteristics, the multiple nuclear magnetic resonance logging T2 sub-spectra are calibrated for fluid type to obtain the fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectra. Then, based on the multiple nuclear magnetic resonance logging T2 sub-spectra and the corresponding fluid types, the effective porosity and movable fluid porosity of the shale are determined. This method improves the calculation accuracy of the porosity. At the same time, it provides a simple and reliable method for fluid type identification and porosity calculation in logging that only measures one-dimensional nuclear magnetic co-logging and does not have core nuclear magnetic resonance experiments.

[0067] The following specific embodiments are used to describe in detail the technical solution of the present application and how the technical solution of the present application solves the above technical problems. The following specific embodiments can be implemented independently or in combination with each other. For the same or similar concepts or processes, some embodiments may not be described in detail.

[0068] Figure 1 Schematic diagram of a method for determining shale pore fluid type and porosity provided in an embodiment of the present application Figure 1 .like Figure 1As shown, the method for determining the shale pore fluid type and porosity provided in this embodiment includes:

[0069] S101 , obtaining nuclear magnetic resonance logging data of shale in a target layer, and performing T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra.

[0070] The target layer section may be, for example, any layer section of shale.

[0071] It is understandable that due to the complex pore structure and complex distribution of fluid types in shale, the nuclear magnetic resonance logging T2 spectrum contains more signal components and may also contain abnormal noise signals; therefore, it is necessary to perform T2 spectrum component stripping processing on the nuclear magnetic resonance logging T2 spectrum to distinguish the signal components therein, thereby obtaining multiple nuclear magnetic resonance logging T2 sub-spectra.

[0072] In a possible implementation, a specific implementation of obtaining multiple nuclear magnetic resonance logging T2 sub-spectra may include, for example:

[0073] First, the independent component analysis (ICA) technique is used to analyze the components of the nuclear magnetic resonance logging data to obtain the corresponding T2 spectrum signal matrix;

[0074] ICA is a blind source separation technique that isolates statistically independent, non-Gaussian components from a multivariate signal. It assumes that the mixed signal is a linear combination of multiple independent source signals with non-Gaussian distributions. Its goal is to estimate the original source signals using the unmixing matrix, ultimately making the separated components statistically independent.

[0075] In this step, ICA assumes that the T2 spectrum observation signal of nuclear magnetic resonance logging is a linear mixture of several independent source signals, so the T2 spectrum signal matrix can be expressed as:

[0076]

[0077] Where X is the NMR logging T2 spectrum observation signal matrix; S k They correspond to T2 sub-spectrum signal matrices of multiple fluid types respectively; N represents the number of sub-spectra.

[0078] For example, N can be 4, S 1-4 They can be used to characterize the clay-bound fluid spectrum, capillary-bound fluid spectrum, mesopore movable fluid spectrum, and macropore movable fluid spectrum respectively; S5 is used to characterize the abnormal noise spectrum.

[0079] Since the essence of the signal in the T2 spectrum of nuclear magnetic resonance logging is the linear superposition of multi-exponential decay signals of different pore fluids, ICA can better capture statistically independent components than principal components analysis (PCA) and meet the spatial independence of fluid occurrence.

[0080] After obtaining the T2 spectrum signal matrix, perform blind source separation on it:

[0081] X=A*S

[0082] Among them, A is the mixing matrix, and S is the NMR logging T2 spectrum observation signal matrix.

[0083] Then, based on the sparse non-negative matrix decomposition technology, multi-component signal stripping and peak spectrum sorting processing are performed on the T2 spectrum signal matrix to obtain multiple candidate nuclear magnetic resonance logging T2 sub-spectra.

[0084] Use sparse non-negative matrix factorization (SNMF) technology to decompose non-negative sparse matrix;

[0085] SNMF is an improved method that introduces sparsity constraints on the basis of traditional non-negative matrix factorization (NMF). Its core goal is to achieve more efficient data dimensionality reduction and feature extraction by constraining the sparsity of the matrix after decomposition.

[0086] In this step, the following formula can be used for non-negative sparse matrix decomposition:

[0087] X≈W*H

[0088] Where W is the T2 subspectral signal matrix of multiple fluid types; H is the coefficient matrix, which represents the relative contribution weights of different fluid components at each depth point.

[0089] The sparsity optimization objective is:

[0090]

[0091] Among them, α and β are sparsity constraint parameters.

[0092] It can be understood that this step constrains sparsity and strengthens T2 subspectral peak positioning by introducing an adaptive regularization parameter.

[0093] Figure 2 Schematic diagram of multiple NMR logging T2 sub-spectra shown in the embodiment of this application. Figure 2As shown in FIG, since the signal components in the original T2 spectrum are complex, it does not have obvious features.

[0094] The candidate NMR logging T2 sub-spectra include the clay-bound fluid spectrum, the capillary-bound fluid spectrum, the mesopore movable fluid spectrum, the macropore movable fluid spectrum, and the anomalous noise spectrum. These sub-spectra were obtained by performing multi-component signal stripping and peak sorting on the original T2 spectrum using ICA+SNMF.

[0095] Since abnormal noise needs to be removed in the subsequent calculation process, the abnormal noise spectrum is stripped from multiple candidate NMR logging T2 sub-spectra to obtain multiple NMR logging T2 sub-spectra.

[0096] In a possible implementation, before determining the multiple NMR logging T2 sub-spectra, the NMR T2 spectrum may be normalized and filtered, as follows:

[0097] Since the clay mineral content will affect the nuclear magnetic resonance T2 spectrum, the clay mineral content difference parameter can be determined based on the clay mineral content and the clay mineral content threshold, and the nuclear magnetic resonance T2 spectrum can be standardized based on the clay mineral content difference parameter.

[0098] The clay mineral content is the mineral content corresponding to the core sample of the target layer. The standardization process can be performed using the following formula:

[0099] T2 norm (i)=[T2 raw (i)-μ T ] / σ T ×1 / [1+exp(-k(V Clay -V C )]

[0100] Among them, T2 norm (i) is the amplitude value of the data point of the i-th NMR T2 spectrum after normalization; T2 raw (i) is the original amplitude value of the data point of the i-th NMR T2 spectrum; μ T is the mean value of the nuclear magnetic resonance T2 spectrum; σ T is the standard deviation of the NMR T2 spectrum; V Clay is the clay mineral content; V C is the clay mineral content threshold; k is a dynamic adjustment factor, which is related to the shale formation.

[0101] The above standardization process comprehensively considers the influence of clay mineral content on the nuclear magnetic resonance T2 spectrum and introduces the clay mineral content difference term ΔV=V Clay -V C, the nonlinear sensitivity dynamic adjustment corresponding to the clay mineral content threshold is achieved through the S-shaped growth curve.

[0102] The normalized nuclear magnetic resonance T2 spectrum is smoothed and filtered.

[0103] In this step, for example, an SG (Savitzky-Golay) filter may be used for filtering. For example, the following formula may be used:

[0104]

[0105] Among them, S filter (T 2i ) is the amplitude value of the data point of the i-th NMR T2 spectrum after filtering; S raw (T 2(i+j) ) is the amplitude value of the data point of the i+j-th NMR T2 spectrum in the sliding window; C j is the filter convolution coefficient; k is the window radius, and the total window length is 2k+1.

[0106] A low-order polynomial is used within the sliding window to perform a least squares fit on the local data, thereby calculating a smoothed estimate of the center point. SG filtering is used to achieve smoothing and noise reduction, minimize peak position shifts, and maintain peak morphology and other characteristics.

[0107] S102: calibrate the fluid type of the plurality of nuclear magnetic resonance logging T2 sub-spectra using a pore fluid type calibration feature to obtain a fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum.

[0108] The pore fluid type calibration feature, for example, can be used to indicate the distribution of T1-T2 signal intervals corresponding to multiple pore fluid types. This pore fluid type calibration feature is determined based on the differences in T1-T2 spectra for shales with varying clay mineral contents and at different core saturation states. Fluid types can include, for example, clay-bound fluid, capillary-bound fluid, mesopore mobile fluid, and macropore mobile fluid.

[0109] In this step, since multiple NMR logging T2 sub-spectra have been obtained, the fluid type corresponding to each NMR logging T2 sub-spectra can be determined based on the pore fluid type calibration characteristics.

[0110] Figure 3 This is a schematic diagram of a plurality of NMR logging T2 sub-spectra and pore fluid type calibration features provided in an embodiment of the present application. Figure 3 As shown in Figure 2, there is a corresponding relationship between the T2 sub-spectrum of NMR logging and the calibration characteristics of pore fluid types.

[0111] For example, at 4629.62 m, the results of multiple nuclear magnetic resonance logging T2 sub-spectra showed a high-amplitude clay-bound fluid spectrum, a low-amplitude capillary-bound fluid spectrum, an extremely low-amplitude mesopore movable fluid spectrum, no macropore movable fluid spectrum, and an abnormal noise spectrum. The results of pore fluid type calibration characteristics showed strong clay-bound water and capillary-bound water signals, and weak bound oil and movable oil signals. The two results were basically consistent.

[0112] At 4665.69 m, the results of multiple nuclear magnetic resonance logging T2 sub-spectra showed a high-amplitude clay-bound fluid spectrum, a medium-amplitude capillary-bound fluid spectrum, a high-amplitude mesopore movable fluid spectrum, a low-amplitude macropore movable fluid spectrum, and a spectrum without abnormal noise; the results of pore fluid type calibration characteristics showed a strong clay-bound water signal, a medium-amplitude bound oil signal, and a strong movable oil signal, and the two results were basically consistent.

[0113] The above results not only verify the accuracy of decomposition and noise stripping of multiple NMR logging T2 sub-spectra, but also demonstrate the simplicity of pore fluid type calibration features compared to two-dimensional NMR T1-T2 spectra for fluid type identification.

[0114] S103: Determine the effective porosity and movable fluid porosity of the shale based on the multiple nuclear magnetic resonance logging T2 sub-spectra and corresponding fluid types.

[0115] Among them, after obtaining the fluid type corresponding to each NMR logging T2 sub-spectrum, for example, the integration method can be used to calculate the porosity of four different pore fluid components: clay-bound fluid, capillary-bound fluid, mesopore movable fluid, and macropore movable fluid.

[0116] In a possible implementation, for example, the following formula may be used:

[0117]

[0118] Among them, Φ i Represent the porosity of different pore fluid components; T 2i Represents the NMR logging T2 sub-spectra of different pore fluid components; T 2min and T 2max are the minimum and maximum values ​​of the transverse relaxation time of the T2 sub-spectrum of nuclear magnetic resonance logging;

[0119] φ e =Φ 毛管束缚流体 +Φ 中孔可动流体 +φ 大孔可动流体

[0120] φ mf =φ 中孔可动流体 +Φ 大孔可动流体

[0121] Among them, Φ e represents effective porosity; Φ mf represents the movable fluid porosity.

[0122] Figure 4 This is a schematic diagram of the calculation results of the effective porosity and movable fluid porosity provided in the embodiment of the present application. Figure 4 As shown in FIG, there are multiple dots in the two columns corresponding to the effective porosity, which are the effective porosity obtained by actual measurement.

[0123] It is understandable that there is a difference between the effective porosity calculated by the traditional 3ms cutoff method and the effective porosity calculated in the embodiment of the present application, and the effective porosity calculated in the embodiment of the present application is more consistent with the effective porosity measured in the core, which also shows that the method provided in the embodiment of the present application improves the calculation accuracy of the effective porosity.

[0124] The method for determining the pore fluid type and porosity of shale provided in this embodiment obtains nuclear magnetic resonance logging data of shale in a target layer and performs T2 spectrum component stripping processing on the data to obtain multiple corresponding nuclear magnetic resonance logging T2 sub-spectra. The pore fluid type calibration characteristics are determined based on the differences in T1-T2 spectra of shales with different clay mineral contents and under different core saturation states. The fluid type is calibrated for the multiple nuclear magnetic resonance logging T2 sub-spectra based on the pore fluid type calibration characteristics to obtain the fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectra. The effective porosity and movable fluid porosity of the shale are then determined based on the multiple nuclear magnetic resonance logging T2 sub-spectra and the corresponding fluid types. This method improves the calculation accuracy of the porosity and provides a simple and reliable method for fluid type identification and porosity calculation in logging that only measures one-dimensional nuclear magnetic co-logging and does not involve core nuclear magnetic resonance experiments.

[0125] Figure 5 Schematic diagram of a method for determining shale pore fluid type and porosity provided in an embodiment of the present application Figure 2 This embodiment is based on Figure 1 Based on the embodiment, a possible implementation method for determining the pore fluid type calibration characteristics is explained. Figure 5 As shown, the method includes:

[0126] S201. Obtain compensated neutron logging data and clay mineral content of shale in the target layer.

[0127] Among them, neutron logging is a neutron logging method that overcomes the influence of wellbore irregularities after performing layout correction on neutron logging. It simultaneously records two neutron curves with different source distances and is used to calculate porosity in openhole or cased wells.

[0128] The main principle is that an isotope neutron source (18Ci americium-beryllium neutron source) emits fast neutrons into the formation in the wellbore. Two thermal neutron detectors, one at a long and one at a short source distance, measure the thermal neutrons that are slowed down by the formation and scattered back into the wellbore, generating two count rates. The ratio of the count rates from the short- and long-source-distance detectors primarily reflects the formation's ability to slow down fast neutrons and thus characterizes changes in the formation's hydrogen content.

[0129] The clay mineral content can be measured, for example, by X-ray diffraction.

[0130] S202: Determine the clay mineral structure water content of the target layer based on the nuclear magnetic resonance logging data and the compensated neutron logging data.

[0131] in, Figure 6 This is a schematic diagram of a continuous longitudinal shale clay mineral content provided in an embodiment of the present application.

[0132] like Figure 6 As shown in Figure 2, the effective nuclear magnetic porosity mainly includes the porosity of capillary bound fluid type and the porosity of movable fluid type;

[0133] The total NMR porosity mainly includes: clay bound water porosity, capillary bound fluid type porosity and movable fluid type porosity;

[0134] Compensated neutron porosity mainly includes: clay structural water porosity, clay bound water porosity, capillary bound fluid type porosity and movable fluid type porosity.

[0135] Based on this, we can see that the difference between NMR logging data and compensated neutron logging data lies in the water porosity of clay structure.

[0136] Therefore, the difference between the NMR logging data and the compensated neutron logging data can be used to determine the porosity corresponding to the clay mineral structure water in the shale, that is, the clay mineral structure water content. Specifically, the following formula can be used:

[0137] Φ CSW =Φ CNL -Φ NMR

[0138] Among them, Φ CSW is the water porosity of clay mineral structure; Φ CNL To compensate for the supplementary neutron porosity corresponding to the neutron logging data; Φ NMR is the total NMR porosity corresponding to the NMR logging data.

[0139] S203: When the core depth is returned, a mapping regression relationship is constructed based on the clay mineral structural water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale.

[0140] The purpose of core depth retrieval is to restore the true depth of the core in order to obtain more accurate data.

[0141] In this step, for example, the following formula can be used to determine the clay mineral content of the continuous longitudinal shale:

[0142] V Clay =a*Φ CSW +b

[0143] Among them, V Clay is the volume of clay mineral content; Φ CSW is the porosity of structural water in clay minerals; a and b are the correlation coefficients of rock diagenesis.

[0144] Continue to see Figure 6 It can be seen that there is a corresponding relationship between the clay mineral content of the continuous longitudinal shale and the two porosities mentioned above. Therefore, a mapping regression relationship can be established based on the data corresponding to the core samples of the target layer to obtain the clay mineral content of the continuous longitudinal shale.

[0145] S204 , calibrating the pore fluid type and the corresponding T1-T2 signal interval distribution based on the continuous longitudinal shale clay mineral content to obtain the pore fluid type calibration feature.

[0146] Among them, after obtaining the continuous longitudinal shale clay mineral content, the pore fluid type and the corresponding T1-T2 signal interval distribution can be calibrated based on the T1-T2 spectra of the nuclear magnetic resonance experiment of the core under various saturation states to obtain the pore fluid type calibration characteristics.

[0147] In a possible implementation, the specific implementation of step S204 includes:

[0148] Determine the T1-T2 spectrum of the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment of the core sample of shale in the target layer.

[0149] The T1-T2 spectrum of the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment is used to indicate the T1-T2 spectrum of the core sample at different core saturation states. As can be understood, the T1-T2 spectrum data of the core sample at different core saturation states are different.

[0150] Determine the difference between the continuous longitudinal shale clay mineral content and the T1-T2 spectrum of the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment.

[0151] Based on this difference, the pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated to obtain the pore fluid type calibration characteristics.

[0152] The method for determining the type and porosity of shale pore fluid provided in the embodiment of the present application determines the shale clay mineral structural water porosity through compensated neutron logging and nuclear magnetic resonance logging; based on the core depth regression, the above-mentioned clay mineral structural water porosity and clay mineral content are used to establish a mapping regression relationship, and a vertically continuous shale clay mineral content curve is output. The pore fluid type and the corresponding T1-T2 signal interval distribution are then calibrated using the continuous vertical shale clay mineral content; this method can avoid the defects of relying solely on coring experiments to determine clay mineral content, such as high cost and data discreteness, while being able to efficiently identify fluid types and reducing the expensive cost of using systematic coring experiments to calibrate logging.

[0153] Figure 7 This is a schematic diagram of a device for determining the type and porosity of shale pore fluid provided in an embodiment of the present application. Figure 7 As shown, the device 700 for determining the type and porosity of shale pore fluid includes:

[0154] An acquisition module 701 is configured to acquire NMR logging data of shale in a target layer, and perform T2 spectrum component stripping processing on the NMR logging data to obtain a plurality of corresponding NMR logging T2 sub-spectra;

[0155] Processing module 702 is configured to calibrate the fluid type of the plurality of NMR logging T2 sub-spectra using a pore fluid type calibration feature to obtain a fluid type corresponding to each NMR logging T2 sub-spectrum, wherein the pore fluid type calibration feature is used to indicate the distribution of T1-T2 signal intervals corresponding to the plurality of pore fluid types, and the pore fluid type calibration feature is determined based on differences in T1-T2 spectra for shales with different clay mineral contents and under different core saturation states;

[0156] The processing module 702 is further configured to determine the effective porosity and movable fluid porosity of the shale based on the plurality of NMR logging T2 sub-spectra and corresponding fluid types.

[0157] In one possible implementation, the processing module 702 is configured to perform component analysis on the nuclear magnetic resonance logging data using independent component analysis technology to obtain a corresponding T2 spectrum signal matrix; perform multi-component signal and peak spectrum sorting processing on the T2 spectrum signal matrix based on sparse non-negative matrix decomposition technology to obtain multiple candidate nuclear magnetic resonance logging T2 sub-spectra; and strip off abnormal noise spectra from the multiple candidate nuclear magnetic resonance logging T2 sub-spectra to obtain multiple nuclear magnetic resonance logging T2 sub-spectra.

[0158] In a possible implementation, the acquisition module 701 is further configured to acquire compensated neutron logging data and clay mineral content of the shale in the target layer;

[0159] The processing module 702 is further configured to determine the clay mineral structure water content of the target interval based on the target nuclear magnetic resonance sub-data and the compensated neutron logging data; and in the case of core depth retrieval, construct a mapping regression relationship based on the clay mineral structure water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale; and

[0160] The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the clay mineral content of the continuous longitudinal shale to obtain the pore fluid type calibration characteristics.

[0161] In one possible implementation, the processing module 702 is used to determine the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum of the core sample of the shale in the target layer, and the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum is used to indicate the T1-T2 spectrum of the core sample under different core saturation states; determine the difference between the clay mineral content of the continuous longitudinal shale and the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum; and based on the difference, calibrate the pore fluid type and the corresponding T1-T2 signal interval distribution to obtain the pore fluid type calibration feature.

[0162] In one possible implementation, the processing module 702 is further used to determine a clay mineral content difference parameter based on the clay mineral content and the clay mineral content threshold; standardize the nuclear magnetic resonance T2 spectrum based on the clay mineral content difference parameter; and perform smoothing filtering on the standardized nuclear magnetic resonance T2 spectrum.

[0163] In a possible implementation, the multiple nuclear magnetic resonance logging T2 sub-spectra include:

[0164] Clay-bound fluid spectrum, capillary-bound fluid spectrum, mesopore movable fluid spectrum and macropore movable fluid spectrum.

[0165] This embodiment provides a device for determining the type and porosity of shale pore fluid, which can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail in this embodiment.

[0166] Figure 8 This is a schematic diagram of a device for determining the type and porosity of shale pore fluid provided in an embodiment of the present application. Figure 8As shown, the device 800 for determining the type and porosity of shale pore fluid may include at least one processor 801, at least one storage medium 802, and a communication interface 803. The at least one processor 801 is configured to implement the method provided in the above embodiment of the present application.

[0167] At least one memory 802 is configured to store program instructions and / or data. Memory 802 is coupled to processor 801. Coupling in the embodiments of the present application refers to an indirect coupling or communication connection between devices, units, or modules, and may be electrical, mechanical, or other forms, used for information exchange between the devices, units, or modules. Processor 801 may operate in conjunction with memory 802. Processor 801 may execute program instructions stored in memory 802. At least one of the at least one memory may be included in the processor.

[0168] Communication interface 803 is used to communicate with other devices via a transmission medium, enabling the device 800 for determining shale pore fluid type and porosity to communicate with other devices. Communication interface 803 may be, for example, a transceiver, an interface, a bus, a circuit, or a device capable of transmitting and receiving data. Processor 801 can use communication interface 803 to transmit and receive data and / or information, and to implement the methods provided in the aforementioned embodiments of this application. For details, please refer to the detailed description in the previous embodiments and will not be repeated here.

[0169] The specific connection medium between the processor 801, the memory 802 and the communication interface 803 is not limited in the embodiment of the present application. Figure 8 The processor 801, the memory 802 and the communication interface 803 are connected via a bus 804. The bus 804 is Figure 8 The connections between the other components are shown in bold lines, which are only for illustration and not intended to be limiting. The bus can be divided into address bus, data bus, control bus, etc. Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0170] In an embodiment of the present application, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the technical solution of the above-mentioned method embodiment is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0171] A computer program product is also provided in an embodiment of the present application, including a computer program. When the computer program is executed by a processor, the technical solution of the above-mentioned method embodiment is implemented. Its implementation principle and technical effect are similar and will not be repeated here.

[0172] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0173] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0174] It should be understood that the above-described device embodiments are merely illustrative, and the device of the present application may also be implemented in other ways. For example, the division of units / modules in the above-described embodiments is merely a logical functional division, and actual implementations may employ other division methods. For example, multiple units, modules, or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0175] In addition, unless otherwise specified, the functional units / modules in the various embodiments of the present application may be integrated into a single unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The aforementioned integrated units / modules may be implemented in the form of hardware or software program modules.

[0176] If the integrated unit / module is implemented in hardware, the hardware may be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0177] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0178] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0179] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0180] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining the type and porosity of shale pore fluid, characterized in that: The method comprises: Acquiring nuclear magnetic resonance logging data of shale in a target layer, and performing T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain corresponding multiple nuclear magnetic resonance logging T2 sub-spectra; The pore fluid type calibration feature is used to calibrate the fluid type of the multiple nuclear magnetic resonance logging T2 sub-spectra to obtain the fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum, wherein the pore fluid type calibration feature is used to indicate the T1-T2 signal interval distribution corresponding to the multiple pore fluid types, and the pore fluid type calibration feature is determined based on the differences in T1-T2 spectra under different clay mineral contents and different core saturation states. Based on the multiple nuclear magnetic resonance logging T2 sub-spectra and the corresponding fluid types, the effective porosity and movable fluid porosity of the shale are determined.

2. The method according to claim 1, characterized in that The performing T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra includes: Independent component analysis technology is used to analyze the components of nuclear magnetic resonance logging data and obtain the corresponding T2 spectrum signal matrix; Based on the sparse non-negative matrix decomposition technology, the T2 spectrum signal matrix is ​​subjected to multi-component signal and peak spectrum sorting processing to obtain multiple candidate nuclear magnetic resonance logging T2 sub-spectra; Abnormal noise spectra are stripped from the plurality of candidate nuclear magnetic resonance logging T2 sub-spectra to obtain the plurality of nuclear magnetic resonance logging T2 sub-spectra.

3. The method according to claim 1, characterized in that Before calibrating the fluid type of the plurality of NMR logging T2 sub-spectra using the pore fluid type calibration feature to obtain the fluid type corresponding to each NMR logging T2 sub-spectrum, the method further includes: Obtaining compensated neutron logging data and clay mineral content of the shale in the target layer; Determining the clay mineral structure water content of the target layer based on the nuclear magnetic resonance logging data and the compensated neutron logging data; In the case of core depth regression, a mapping regression relationship is constructed based on the clay mineral structural water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale; The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the clay mineral content of the continuous longitudinal shale to obtain the pore fluid type calibration characteristics.

4. The method according to claim 3, characterized in that The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the continuous longitudinal shale clay mineral content to obtain the pore fluid type calibration feature, including: Determine a low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum of a core sample of the shale in the target layer, wherein the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment T1-T2 spectrum is used to indicate the T1-T2 spectrum of the core sample at different core saturation states; Determining the difference between the clay mineral content of the continuous longitudinal shale and the T1-T2 spectrum of the low-frequency multi-state two-dimensional nuclear magnetic resonance experiment; Based on the differences, the pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated to obtain the pore fluid type calibration characteristics.

5. The method according to claim 3, characterized in that The nuclear magnetic resonance logging data includes a nuclear magnetic resonance T2 spectrum. Before performing data analysis on the nuclear magnetic resonance logging data to obtain a plurality of corresponding nuclear magnetic resonance logging T2 sub-spectra, the method further includes: determining a clay mineral content difference parameter based on the clay mineral content and the clay mineral content threshold; Based on the clay mineral content difference parameter, the nuclear magnetic resonance T2 spectrum is standardized; The normalized nuclear magnetic resonance T2 spectrum is smoothed and filtered.

6. The method according to claim 1, wherein The multiple nuclear magnetic resonance logging T2 sub-spectra include: Clay-bound fluid spectrum, capillary-bound fluid spectrum, mesopore movable fluid spectrum and macropore movable fluid spectrum.

7. A device for determining the type and porosity of shale pore fluid, characterized in that: include: An acquisition module is used to acquire nuclear magnetic resonance logging data of shale in a target layer, and perform T2 spectrum component stripping processing on the nuclear magnetic resonance logging data to obtain a corresponding plurality of nuclear magnetic resonance logging T2 sub-spectra; a processing module, configured to calibrate the fluid type of the plurality of nuclear magnetic resonance logging T2 sub-spectra using a pore fluid type calibration feature to obtain a fluid type corresponding to each nuclear magnetic resonance logging T2 sub-spectrum, wherein the pore fluid type calibration feature is used to indicate the distribution of T1-T2 signal intervals corresponding to the plurality of pore fluid types, and the pore fluid type calibration feature is determined based on differences in T1-T2 spectra for shales with different clay mineral contents and under different core saturation states; The processing module is further configured to determine the effective porosity and movable fluid porosity of the shale based on the plurality of nuclear magnetic resonance logging T2 sub-spectra and corresponding fluid types.

8. The device according to claim 7, characterized in that The acquisition module is further used to acquire the compensated neutron logging data and clay mineral content of the shale in the target layer; The processing module is further configured to determine the clay mineral structure water content of the target layer based on the target nuclear magnetic resonance sub-data and the compensated neutron logging data; and in the case of core depth retrieval, construct a mapping regression relationship based on the clay mineral structure water content and the clay mineral content to obtain the continuous longitudinal shale clay mineral content of the shale; and The pore fluid type and the corresponding T1-T2 signal interval distribution are calibrated based on the clay mineral content of the continuous longitudinal shale to obtain the pore fluid type calibration characteristics.

9. A device for determining the type and porosity of shale pore fluid, characterized in that: The device comprises: Memory; processor; wherein the memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

10. A computer storage medium, characterized in that The computer storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

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