Device and method for measuring organic carbon characteristics of oil and gas reservoir rock

Abstract

The invention belongs to the technical field of laser diagnosis, and discloses a device and method for measuring oil and gas reservoir rock organic carbon characteristics, the device comprises an LIBS spectrum system and an ultraviolet Raman laser system, the LIBS spectrum system comprises a nanosecond laser, the nanosecond laser is connected with a microscope through a light guide arm, a reflecting surface of a reflecting mirror is connected with the light guide arm, and the reflecting surface of the reflecting mirror is connected with the ultraviolet Raman laser system. A convex lens is arranged below the reflecting mirror, a detachable spectroscope is arranged above the reflecting mirror, and a CCD (Charge Coupled Device) camera is arranged in the horizontal reflecting direction of the spectroscope. The LIBS spectrum system provided by the invention is simple in light path adjustment; the microscope carrying the CCD camera can observe the surface appearance of the sample at any time. According to the method, the LIBS spectrum system and the Raman spectrum equipment are respectively used for measuring the spectrum data of each shale, the prediction model of the total organic carbon of the shale is constructed, and the rapid measurement of the total organic carbon of the rock can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of laser diagnosis, and in particular relates to a device and a method for measuring organic carbon characteristics of oil and gas reservoir rocks. Background Art

[0002] Oil and gas shales may contain oil and natural gas, which have rich resource reserves and are of great significance in the energy field. At the same time, TOC (total organic carbon) is one of the most important parameters for evaluating the oil and gas potential of shale. Rapid and accurate determination of the total organic carbon content of shale is of great significance for evaluating the oil and gas resource potential of shale and guiding the selection of geological sweet spots. Laser induced breakdown spectroscopy (LIBS) is abbreviated as LIBS. This technology focuses laser pulses on the sample to generate laser plasma and spectral emission, and uses a spectrometer to collect the characteristic spectrum of plasma emission, and then conducts qualitative or quantitative analysis of the element types and contents of the sample. LIBS has the advantages of simultaneous analysis of multiple elements, fast detection speed, and low sample damage. It has been widely used in metallurgical analysis, mineral identification and other fields. Raman spectroscopy is a fast and non-destructive analysis technology. When monochromatic light is incident on a medium, there will be two different scattering processes. Raman spectroscopy analyzes the structure of the material through the scattered light with a change in frequency. It has the advantages of non-destructive detection, simple pretreatment, and small sample volume.

[0003] Although laser spectroscopy technologies represented by LIBS and laser Raman spectroscopy have great application potential in the detection of organic components in oil and gas shales, single laser spectroscopy detection technology still faces the following technical problems. LIBS technology is a relatively mature element quantitative analysis method, but due to the complex carbon components in shale, some carbon elements exist in carbonates in the form of inorganic carbon, so the use of LIBS technology lacks a certain amount of theoretical explanation for the organic carbon content of shale. For Raman spectroscopy, CC and C=C bonds in shale organic carbon components can be characterized by D peaks and G peaks in Raman spectra. Such characteristic peaks do not exist in carbonates, so Raman technology can effectively identify TOC components in shale. However, since the intensity of laser Raman scattering spectrum signals is seriously affected by the optical structure, the fluorescence signals of complex mineral components in shale will seriously interfere with the detection of organic carbon signals, resulting in low quantitative analysis accuracy.

[0004] The Chinese patent publication number is CN116660242A, and the name is a patent application for a combined test system of a microscopic Raman spectrometer and a near-infrared spectrometer. The system includes a platform, a laser is provided above the platform, and a microscope is provided on the platform; it also includes a laser fiber, a collimating lens, a first reflector, a near-infrared light source, a beam splitter, an optical path converter, a second reflector, and a data processor. The optical path converter is connected to the microscope through an optical fiber probe, and the output end of the optical path converter is connected to the microscopic Raman spectrometer and the near-infrared spectrometer through optical fibers respectively; the first reflector and the second reflector respectively reflect the laser and the near-infrared light source to the sample on the platform, and the microscope guides the feedback signal to the optical path converter. This patent application can realize the combination of a microscopic Raman spectrometer and a near-infrared luminescence spectrometer, but cannot realize the rapid measurement of the total organic carbon content of rocks or rock soil. Summary of the invention

[0005] In order to overcome the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a device and method for measuring the organic carbon characteristics of oil and gas reservoir rocks. The device includes a LIBS spectroscopy system and an ultraviolet Raman laser system, which utilizes spectral technology to evaluate and analyze shale, and integrates laser induced breakdown spectroscopy with Raman spectroscopy to achieve the measurement of total organic carbon in the sample.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] A device for measuring organic carbon characteristics of oil and gas reservoir rocks comprises a LIBS spectroscopy system and an ultraviolet Raman laser system, wherein the LIBS spectroscopy system comprises a nanosecond laser, wherein the nanosecond laser is connected to a microscope via a light guide arm, wherein the microscope comprises a reflector, wherein a reflective surface of the reflector is connected to the light guide arm, wherein a convex lens is arranged below the reflector, wherein a detachable spectroscope is installed above the reflector, wherein an eyepiece is arranged above the spectroscope, and a CCD camera is arranged in the horizontal reflection direction of the spectroscope; a LIBS probe is arranged beside the focus of the convex lens, wherein one end of the LIBS probe faces the focus of the convex lens, and the other end is connected to a multi-channel spectrometer; and a three-dimensional mobile platform is arranged below the convex lens.

[0008] Optionally, the multi-channel spectrometer is communicatively connected to a timing controller, the timing controller is communicatively connected to a computer, the timing controller is communicatively connected to the nanosecond laser, and the three-dimensional mobile platform is communicatively connected to the computer.

[0009] Optionally, the eyepiece, the reflection point of the beam splitter, the reflection point of the reflector and the focus of the convex lens are arranged in the same straight line direction.

[0010] Optionally, a collimating lens probe is provided on a side of the LIBS probe close to the focus of the convex lens, and a focusing lens probe is provided on a side away from the focus of the convex lens.

[0011] Optionally, the LIBS probe is connected to the multi-channel spectrometer via a multi-light beam.

[0012] The method for using the device for measuring the organic carbon characteristics of oil and gas reservoir rocks comprises the following steps:

[0013] S1: Collect the LIBS spectrum of the sample through the LIBS spectroscopy system; collect the Raman spectrum of the sample through the UV Raman laser system;

[0014] S2: Use the dimension reduction algorithm to fuse the LIBS spectrum with the Raman spectrum data to obtain spectral fusion data;

[0015] S3: Using the spectral fusion data as input variables, a quantitative analysis model of total organic carbon content is established to predict the TOC content of rocks.

[0016] Optionally, before step S1, the detection spectrum response efficiency of the multi-channel spectrometer is calibrated.

[0017] Optionally, before step S2, the LIBS spectrum and Raman spectrum data of the sample are normalized respectively.

[0018] Optionally, in step S2, PLS latent variables of LIBS spectrum and Raman spectrum data are extracted respectively, and the two latent variable data are spliced ​​to ensure that the contribution rate of the latent variables is higher than 95%.

[0019] Optionally, in step S2, a principal component analysis method is used to fuse the LIBS spectrum with the Raman spectrum data using a dimensionality reduction algorithm.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] In the LIBS spectroscopy system of the present invention, the laser outputs laser light through the light guide arm, and the optical path adjustment is simple; the microscope is equipped with a CCD camera to observe the sample surface morphology at any time, and the sample-mirror distance can be controlled in combination with a displacement platform; the LIBS probe is used to face the convex lens focusing point, which can achieve lateral light collection to avoid the loss of ultraviolet bands in the objective lens and the dichroic mirror during axial light collection; the optical path structure of the microscopic LIBS spectroscopy system is relatively stable, avoiding spectral fluctuations caused by factors such as vibration; and the influence of fluorescence can be avoided by using an ultraviolet Raman laser system. The use of a three-dimensional displacement platform can control the movement of the sample, and combined with a control system, automatic scanning can be achieved.

[0022] The present invention uses LIBS spectral system and Raman spectroscopy equipment to measure the spectral data of each shale, performs corresponding data preprocessing on the spectral data, extracts PLS latent variables, performs data fusion, and combines PLSR algorithm to build a prediction model for shale total organic carbon to achieve the measurement of shale total organic carbon.

[0023] The present invention integrates Raman spectroscopy technology and laser induced breakdown spectroscopy technology, performs data fusion on the basis of traditional spectral measurement technology, and combines it with machine learning algorithms to solve the difficulties in measuring the total organic carbon content of shale, providing a method for evaluating the properties and composition of oil and gas rocks.

[0024] The method of the present invention combines two laser spectra to establish a quantitative analysis model for the total organic carbon content of shale, integrates the advantages of the two technologies, and overcomes the shortcomings of the two laser spectroscopy technologies to a certain extent, and can realize the rapid measurement of the total organic carbon content of rocks or geotechnical materials; compared with conventional detection methods, this method does not require complicated acid washing pretreatment and continuous heating process during detection, has a low detection time cost, and can realize in-situ detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are for explanation purposes only and are not intended to limit the scope of the present invention in any way. In addition, the shapes and proportional dimensions of the components in the drawings are only for illustration purposes to help understand the present invention, and are not intended to specifically limit the shapes and proportional dimensions of the components of the present invention. In the drawings:

[0026] Figure 1 The present invention provides a method for measuring the total organic carbon content of oil and gas shale based on the fusion of laser induced breakdown spectroscopy and laser Raman spectroscopy.

[0027] Figure 2 The structure diagram of the LIBS spectroscopy system of the present invention is shown below;

[0028] Figure 3 A typical LIBS spectrum collected in the experiment of the present invention;

[0029] Figure 4 A typical Raman spectrum collected for the experiment of the present invention;

[0030] Figure 5 The quantitative analysis results of shale TOC obtained by applying the present invention;

[0031] Among them, 1. nanosecond laser; 2. light guide arm; 3. microscope; 301. CCD camera; 302. spectroscope; 303. eyepiece; 31. reflector; 32. convex lens; 33. three-dimensional moving platform; 34. stage; 4. LIBS probe; 41. collimating lens probe; 42. focusing lens probe; 5. multi-channel spectrometer; 6. timing controller; 7. computer. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that when an element is referred to as being "disposed on" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only embodiment.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0035] The present invention is described in detail below with reference to the accompanying drawings.

[0036] like Figure 1As shown, a device for measuring organic carbon characteristics of oil and gas reservoir rocks of the present invention comprises a LIBS spectroscopy system and an ultraviolet Raman laser system, wherein the LIBS spectroscopy system comprises a nanosecond laser 1, wherein the nanosecond laser 1 is connected to a microscope 3 via a light guide arm 2, wherein the microscope 3 comprises a reflector 31, wherein a reflective surface of the reflector 31 is connected to the light guide arm 2, wherein a convex lens 32 is arranged below the reflector 31, and a detachable spectroscope 302 is installed above the reflector 31; a LIBS probe 4 is arranged next to the focus of the convex lens 32, wherein one end of the LIBS probe 4 faces the focus of the convex lens 32, and the other end is connected to a multi-channel spectrometer 5; a three-dimensional mobile platform 33 is arranged below the convex lens 32, and the three-dimensional mobile platform 33 is communicatively connected to a computer 7.

[0037] The beam splitter 303 is at an angle of 45° to the horizontal direction. When the beam splitter 302 is installed in the microscope 3, half of the light propagates upward along the original direction, and the other half of the light is reflected horizontally. A CCD camera 301 is arranged in the horizontal reflected light direction of the beam splitter 302, and an eyepiece 303 is arranged in the vertical radiated light direction of the beam splitter 302.

[0038] When the beam splitter 302 is not installed, all the light propagates along the original vertical direction to the eyepiece 303, and the surface morphology of the sample can be clearly observed in the eyepiece 303. When the beam splitter 302 is installed, half of the light is horizontally reflected to the CCD camera 301, and the surface morphology of the sample can be observed through the CCD camera 301.

[0039] The method for using the device for measuring the organic carbon characteristics of oil and gas reservoir rocks comprises the following steps:

[0040] S1: Collect the LIBS spectrum of the sample through the LIBS spectroscopy system; collect the Raman spectrum of the sample through the UV Raman laser system;

[0041] S2: Use the dimension reduction algorithm to fuse the LIBS spectrum with the Raman spectrum data to obtain spectral fusion data;

[0042] S3: Using the spectral fusion data as input variables, a quantitative analysis model of total organic carbon content is established to predict the TOC content of shale.

[0043] The method of the present invention combines two laser spectra to establish a quantitative analysis model for the total organic carbon content of shale, integrating the advantages of the two technologies and being able to achieve rapid measurement of the total organic carbon content of shale; compared with conventional detection methods, this method does not require complicated acid washing pretreatment and continuous heating process during detection, has a lower detection time cost, and can achieve in-situ detection.

[0044] Example 1

[0045] A method for using a device for measuring organic carbon characteristics of oil and gas reservoir rocks of the present invention specifically comprises the following steps:

[0046] Step 1: Completely build the LIBS experimental system.

[0047] The device for measuring organic carbon characteristics of oil and gas reservoir rocks of the present invention comprises a LIBS spectral system and an ultraviolet Raman laser system. The LIBS spectral system comprises a nanosecond laser 1. The nanosecond laser 1 is connected to a microscope 3 via a light guide arm 2.

[0048] Specifically, the ultraviolet Raman laser system adopts the RTS-mini confocal Raman microscope system of Zhuoli Hanguan. Its laser is a 325nm ultraviolet continuous laser with a nominal power of 200mW. It is magnified by a short working distance lens (40 times), and the laser spot diameter is about 5μm. The RTS-mini confocal Raman microscope system can control the spectrometer, obtain spectral data and analyze the spectrum.

[0049] The main factor that determines whether the Raman system can be applied to this patent is the wavelength of the laser. In Raman spectroscopy detection, when the sample is irradiated with excitation light, in addition to Raman scattered light, fluorescence may also be generated. Raman detection under the appropriate excitation wavelength can effectively avoid the influence of fluorescence. The Raman spectrum under ultraviolet laser is least affected by fluorescence, while the Raman spectrum under 532nm, 633nm, and 785nm wavelength excitation is very seriously affected by fluorescence, which will cause the Raman spectrum to be obscured. However, due to the limited equipment used, it is difficult to determine the exact applicable range of laser wavelengths.

[0050] The microscope 3 includes a reflector 31 , a reflective surface of the reflector 31 is connected to the light guide arm 2 , and a convex lens 32 is provided on the reflector 31 in the reflection direction of the light emitted by the light guide arm 2 .

[0051] Specifically, the light guide arm 2 is arranged horizontally, the reflector 31 forms an angle of 45° with the horizontal plane, and the convex lens 32 is arranged directly below the reflector 31 .

[0052] A detachable beam splitter 302 is installed directly above the reflector 31 . An eyepiece 303 is arranged directly above the beam splitter 302 . A CCD camera 301 is arranged in the horizontal reflection direction of the beam splitter 302 . The CCD camera 301 faces the beam splitter 302 .

[0053] A LIBS probe 4 is disposed beside the focus of the convex lens 32 , one end of the LIBS probe 4 faces the focus of the convex lens 32 , and the other end is connected to a multi-channel spectrometer 5 .

[0054] The multi-channel spectrometer 5 is communicatively connected to a timing controller 6, the timing controller 6 is communicatively connected to a computer 7, and the timing controller 6 is communicatively connected to the nanosecond laser 1. The LIBS probe 4 is connected to the multi-channel spectrometer 5 via a one-point multi-light beam.

[0055] The nanosecond laser 1 is connected to the light guide arm 2, and the other end of the light guide arm 2 is connected to the microscope 3. The laser is focused on the sample surface through the reflector 31 and then through the convex lens 32. At the same time, the characteristic spectrum lines emitted by the plasma are transmitted back to the spectrometer for analysis by the homemade LIBS probe, which integrates the collimating lens and focusing lens probe.

[0056] Optionally, a stage 34 is disposed at the focus of the convex lens 32, a three-dimensional moving platform 33 is disposed below the stage, and the three-dimensional moving platform 33 is communicatively connected to the computer 7. The three-dimensional displacement platform 33 can control the movement of the sample.

[0057] For LIBS quantitative analysis, when changing samples, the distance from the focusing lens to the sample surface (lens-to-sample distance) will be different due to the different sample thickness, which will lead to different spot sizes. Different spot sizes will seriously affect the quantitative results. When changing samples, the sample can be focused by controlling the movement of the Z axis and combining the CCD camera 301 (Charge-coupled Device) installed in the microscope, thereby ensuring the consistency of the lens-to-sample distance, reducing spectral fluctuations, and improving the quantitative effect.

[0058] During the experiment, it is necessary to target the sample surface multiple times. Moving the X-axis and the Y-axis can achieve point change, and the CCD camera (301) is used to prevent the laser from hitting the ablation pit.

[0059] The LIBS probe 4 is provided with a collimating lens probe 41 on a side close to the focus of the convex lens 32 , and a focusing lens probe 42 on a side away from the focus of the convex lens 32 .

[0060] The LIBS probe 4 needs to be collimated before focusing. The laser beam may be affected by various factors during propagation, including air disturbance and tiny defects of optical components, which may lead to a decrease in beam quality, an increase in divergence angle, and deformation of the light spot. Collimating the laser beam by the collimating lens probe 41 can ensure that the laser beam maintains a higher parallelism and a smaller divergence angle during transmission, thereby improving the quality of the laser beam.

[0061] The laser passes through the collimating lens probe 41 to ensure the collimation of the laser, and then passes through the focusing lens probe 42 to achieve the purpose of focusing, focusing the high-power pulse laser on the sample surface to induce plasma.

[0062] Specifically, M shale samples were targeted respectively, and a spectrometer was used to receive the characteristic spectral lines emitted by the transient plasma. The same sample was evenly targeted N times on the sample surface, and 5 shots were pre-ablated each time to pre-treat the surface of the sample to be tested. After pre-ablation, a cumulative 20 shots were then fired to reduce the impact of spectral uncertainty.

[0063] Step 2: Response efficiency correction of LIBS spectral system. Connect the optical fiber to the standard light source to calibrate the response efficiency of the entire spectral system. Repeat the measurement 5 times and take the average to establish the response function of the standard light source, that is, the ratio of the detected spectrum to the standard spectrum provided by the manufacturer in terms of wavelength. Divide the spectral data obtained in subsequent experiments by the wavelength to achieve the response efficiency correction of the spectral system.

[0064] Step 3: Preprocessing of LIBS spectral data. Process the recorded spectral data and intercept the spectral data of 30 pixels on the left and right of the characteristic spectral lines of carbon atoms at 193.09nm and 247.86nm. A total of 124 data points are obtained and the average spectral intensity is calculated. The data is then normalized to improve the calculation efficiency and model accuracy.

[0065] Step 4: Use the UV Raman laser system to collect the Raman spectrum of the shale sample. The incident laser uses a 325nm UV laser to weaken the influence of fluorescence. The integration time is set to 2s, and M shale samples are targeted respectively. The same sample should be evenly targeted N times on the sample surface to make the measured spectrum more representative.

[0066] Step 5: Preprocessing of Raman spectral data. For each spectrum, baseline correction is first performed to smooth the fluorescence background and eliminate cosmic rays. Finally, the D-peak and G-peak (1350cm-1, 1580cm-1) of the carbon atom crystal are extracted as characteristic spectral lines. Similarly, the spectral data of 30 pixels around the characteristic spectral lines (1350cm-1, 1580cm-1) are intercepted. A total of 124 data points are obtained, and the average spectral intensity is calculated. The data is then normalized to the mean.

[0067] Step 6: Spectral data dimension reduction and data fusion. Extract the PLS (Partial Least Squares) latent variables of LIBS spectrum and Raman spectrum data respectively, and ensure that the contribution rate of latent variables is higher than 95% by controlling the number of selected latent variables, and obtain a latent variables and b latent variables respectively. The obtained latent variable data are spliced ​​to obtain spectral fusion data to achieve data dimension reduction and improve prediction accuracy. The number of latent variables here is selected comprehensively by the evaluation indicators of the quantitative analysis model established in step 7.

[0068] Optionally, the principal component analysis method is used to fuse the LIBS spectrum and Raman spectrum data. The PCA principal components of the LIBS spectrum and Raman spectrum data are extracted respectively, and the number of selected principal components is controlled to ensure that the cumulative contribution rate of the principal components is higher than 95%, and a latent principal components and b principal components are obtained respectively. The obtained principal component data are spliced ​​to obtain spectral fusion data to achieve data dimensionality reduction and improve prediction accuracy.

[0069] Step 7: Establish a quantitative analysis model for total organic carbon content in shale. The obtained spectral fusion data is used as input variables, and the PLSR regression algorithm is used to predict and analyze the TOC content of shale.

[0070] Different numbers of latent variables are selected to build quantitative analysis models, and the leave-one-out cross-validation method is used to evaluate the models. The cross-validation root mean square error of different models is calculated, and the model with the smallest cross-validation root mean square error is selected to avoid overfitting of the model and improve the generalization ability of the quantitative analysis model. When building a quantitative analysis model, support vector machine (SVM) and random forest (RF) algorithms can also be used according to different situations.

[0071] The integration time of the Raman experiment is determined according to the target material, and is based on the identification of obvious spectral features. At the same time, total organic carbon is an important parameter for evaluating the oil and gas potential of shale, and it is of great significance to quickly and accurately determine the total organic carbon content of shale.

[0072] Example 2

[0073] like Figure 2 As shown, the laser used in the LIBS experiment of this embodiment is a Nd:YAG laser with a pulse width of 8ns, a wavelength of 1064nm, a laser energy of 16mJ / pulse, and a repetition frequency of 5Hz; the nanosecond laser is connected to the light guide arm, and the other end of the light guide arm is connected to the microscope system. The laser is focused on the sample surface through a reflector and then through a lens. At the same time, the characteristic spectrum of the plasma emission is transmitted back to the spectrometer for analysis by a homemade LIBS probe, which integrates a collimating lens and a focusing lens probe. Each time the target is pre-ablated for 5 times, and after pre-ablation, a cumulative target is fired for 20 times. The exposure time of the spectrometer is 2ms, and the detection delay is 800ns.

[0074] The LIBS spectroscopy system changes the laser light path through a reflector, and then focuses the nanosecond pulse laser on the sample surface through a lens to generate plasma. The emission spectrum of the plasma is collected laterally by a self-made LIBS probe and transmitted back to the spectrometer for analysis via a multi-point optical fiber.

[0075] The Raman experiment in this example uses the RTS-mini confocal Raman microscope system produced by Zhuoli Hanguang Company. The excitation source is provided by a gas laser emitting 325nm radiation, which is magnified by a short working distance lens (40×). The laser spot diameter is about 5μm, and the objective lens light output power is about 2mW. The supporting software is used to control the spectrometer, obtain spectral data, and analyze the spectrum.

[0076] The target material used in this example is the oil and gas shale sample collected from the 7th section of the Yanchang Formation in a certain basin. 15 kinds of samples were collected, classified and crushed. The powdered samples were ground and passed through a 200-mesh sieve to reduce the unevenness. A part of the fine powder was pressed at a pressure of 30 MPa for 3 minutes to make a sheet sample. Three samples were selected as the verification sample set.

[0077] For each sample, the LIBS spectrum and Raman spectrum were obtained as Figure 3 and Figure 4 As shown. After spectral preprocessing, the corresponding characteristic spectral line data was intercepted and mean normalized, and the five PLS latent variables of LIBS spectral data and Raman spectral data were extracted and then data splicing was performed. The obtained spectral fusion data was used as the input variable, and the PLSR regression algorithm was used to predict and analyze the shale TOC content.

[0078] Two latent variables were selected to construct a quantitative analysis model. Figure 5 The TOC calibration results and prediction results are shown. The coefficient of determination, calibration root mean square error, prediction root mean square error, and cross-validation root mean square error of the model are 0.9966, 0.1480, 0.1420, and 0.3776, respectively, indicating that the method can extract sufficient spectral information and provide acceptable prediction results with good robustness and stability.

[0079] Unless otherwise specified, the device elements involved in the above embodiments are all conventional device elements, and the structural settings, working modes or control modes involved are all conventional settings, working modes or control modes in the art unless otherwise specified.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in the field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A device for measuring the organic carbon characteristics of oil and gas reservoir rocks, characterized in that: The invention comprises a LIBS spectroscopy system and an ultraviolet Raman laser system. The LIBS spectroscopy system comprises a nanosecond laser (1). The nanosecond laser (1) is connected to a microscope (3) via a light guide arm (2). The microscope (3) comprises a reflector (31). The reflective surface of the reflector (31) is connected to the light guide arm (2). A convex lens (32) is arranged below the reflector (31). A detachable beam splitter (302) is installed above the reflector (31). An eyepiece (303) is arranged above the beam splitter (302). A CCD camera (301) is arranged in the horizontal reflection direction of the beam splitter (302). A LIBS probe (4) is arranged next to the focus of the convex lens (32). One end of the LIBS probe (4) faces the focus of the convex lens (32), and the other end is connected to a multi-channel spectrometer (5). A three-dimensional moving platform (33) is arranged below the convex lens (32).

2. The device for measuring the organic carbon characteristics of oil and gas reservoir rocks according to claim 1, characterized in that: The multi-channel spectrometer (5) is communicatively connected to a timing controller (6), the timing controller (6) is communicatively connected to a computer (7), the timing controller (6) is communicatively connected to the nanosecond laser (1), and the three-dimensional mobile platform (33) is communicatively connected to the computer (7).

3. The device for measuring the organic carbon characteristics of oil and gas reservoir rocks according to claim 1, characterized in that: The eyepiece (303), the reflection point of the beam splitter (302), the reflection point of the reflector (31) and the focus of the convex lens (32) are arranged in the same straight line direction.

4. The device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 1, characterized in that: The LIBS probe (4) is provided with a collimating lens probe (41) on the side close to the focal point of the convex lens (32), and is provided with a focusing lens probe (42) on the side away from the focal point of the convex lens (32).

5. The device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 1, characterized in that: The LIBS probe (4) is connected to the multi-channel spectrometer (5) via a multi-light beam.

6. A method for using the device for measuring organic carbon characteristics of oil and gas reservoir rocks according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1: Collect the LIBS spectrum of the sample through the LIBS spectroscopy system; collect the Raman spectrum of the sample through the UV Raman laser system; S2: Use the dimension reduction algorithm to fuse the LIBS spectrum with the Raman spectrum data to obtain spectral fusion data; S3: Using the spectral fusion data as input variables, a quantitative analysis model of total organic carbon content is established to predict the TOC content of rocks.

7. The method for using the device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 6, characterized in that: Before step S1, the detection spectrum response efficiency of the multi-channel spectrometer (5) is calibrated.

8. The method for using the device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 6, characterized in that: Before step S2, the LIBS spectrum and Raman spectrum data of the sample are normalized respectively.

9. The method for using the device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 6, characterized in that: In step S2, PLS latent variables of LIBS spectrum and Raman spectrum data are extracted respectively, and the two latent variable data are spliced ​​to ensure that the contribution rate of the latent variables is higher than 95%.

10. The method for using the device for measuring organic carbon characteristics of oil and gas reservoir rocks according to claim 6, characterized in that: In step S2, the dimensionality reduction algorithm is used to fuse the LIBS spectrum with the Raman spectrum data using principal component analysis.

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