27 results about "T2 relaxation" patented technology

The invention belongs to the technical field of reservoir pore structure characterization, and relates to a nuclear magnetic resonance T2 spectrum pore diameter conversion method based on a least square method and mercury injection data. The method comprises the following steps: interpolating and fitting cumulative distribution frequency of nuclear magnetic resonance about relaxation time to obtain a relationship between the cumulative distribution frequency of the relaxation time and the radius of a mercury injection pore; interpolation and fitting are carried out on the cumulative distribution frequency of the high-pressure mercury injection relative to the pore radius, and the relation between the cumulative distribution frequency of the pore radius and the mercury injection pore radius is obtained; establishing an error function based on the relationship between the cumulative distribution frequency of the relaxation time and the mercury injection pore radius and the relationship between the cumulative distribution frequency of the pore radius and the mercury injection pore radius; establishing a conversion function for converting the cumulative distribution curve of the nuclear magnetic resonance T2 relaxation time into a cumulative distribution curve of a high-pressure mercury injection pore throat radius; and substituting the error function into a conversion function to solve a conversion coefficient in the conversion function, and completing nuclear magnetic resonance T2 spectrum aperture conversion.

The application discloses a low-permeability reservoir pore structure quantitative characterization method based on a nuclear magnetic resonance T2 spectrum multi-peak fitting, relates to the technical field of reservoir pore structure characterization, and comprises the following steps: preprocessing a nuclear magnetic resonance T2 spectrum, and decomposing the data after preprocessing by means of Gaussian multi-peak fitting; combining the peak area, the peak center and the peak width of each sub-peak to quantitatively characterize the porosity contribution and the pore size range of micro-pores, mesopores and macropores; introducing the sub-peak parameters obtained by multi-peak fitting into a permeability prediction model, correcting the model for predicting the permeability based on NMR T2 relaxation data based on the multi-peak fitting results, constructing a permeability model, and more accurately predicting the permeability, which has important significance for promoting reservoir prediction.

This technology provides a way to quickly and objectively evaluate the moisture content (water retention, etc.) of processed shrimp products in a manner that is robust enough for inter-lot comparisons, without relying on measurements involving destruction or heating, or on the subjective judgment of the measurer. [Solution] T2 relaxation data of a sample is acquired using a low-field nuclear magnetic resonance spectrometer, and a T2 distribution 41 is calculated by reconstitution processing. The T2 distribution is divided into a first region 42, a second region 43, and a third region 44 using boundary values ​​T2A (45) and T2B (46). Areas A1 (50), A2 (51), and A3 (52) of each region are calculated, and indices J1 and J2 are calculated. If indices J1 and J2 each meet the judgment criteria, the product is judged to conform to the quality standard; otherwise, it is judged not to conform to the quality standard, and the indices and judgment results are output.

This invention provides a deep learning-based method for calculating the relaxation time distribution of nuclear magnetic resonance (NMR) signals. Based on the characteristics of Laplace NMR signals, a mathematical model of an exponentially decaying signal with noise and an ideal relaxation time spectrum are constructed. The ideal relaxation time spectrum serves as a label, and the position of the spectral peak represents the exact value of either the T1 or T2 relaxation time. The full width at half maximum (FWHM) of the spectral peak corresponds to the uncertainty of the result. Simulated signals are generated from the mathematical model, and training and test sets are constructed. A network model is built, and the training data is input into the network model for training. The test data is then input into the network model for testing. The method provided by this invention relies on a mathematical model of the exponentially decaying signal during the relaxation process to construct a dataset for training. This eliminates the need to collect large amounts of real data and allows for NMR relaxation time spectrum calculations to be completed within seconds. Furthermore, it exhibits high robustness to test data with different signal-to-noise ratios.

The embodiment of the application relates to the technical field of nuclear logging, and discloses a training method of a logging model and a T2 relaxation spectrum determination method in nuclear logging, which comprises the following steps: obtaining a logging signal; intercepting a pure noise segment at the tail of the logging signal to generate real non-Gaussian noise data according to the pure noise segment; generating a pure echo train according to a preset T2 relaxation spectrum; determining a noise scaling coefficient according to the average power of the pure echo train and a preset target signal-to-noise ratio; determining noise adjustment data according to the noise scaling coefficient and the real non-Gaussian noise data, adjusting the pure echo train according to the noise adjustment data to obtain a noisy signal; constructing a training set according to the noisy signal and the preset T2 relaxation spectrum; and training the logging model based on the training set until a training termination condition is reached. The application can more accurately obtain the T2 relaxation spectrum in the logging process.

The application provides a method for predicting movable oil content in rock based on nuclear magnetic relaxation ratio, which comprises the following steps: 1) determining a nuclear magnetic base T2 relaxation spectrum of a core in a dry state and a T2 bulk relaxation parameter of white oil; 2) carrying out a complete saturation experiment on the core by using the white oil, carrying out T2 nuclear magnetic resonance test, and obtaining a T2 relaxation spectrum of the core in a saturated state; 3) subtracting the base signal of the core from the saturated T2 relaxation spectrum to obtain a T2 relaxation spectrum of the white oil in the core, and then obtaining the relationship between the relaxation time and the white oil bulk relaxation fluid ratio and calculating the total amount of the white oil bulk relaxation fluid; 4) centrifuging the obtained saturated core, determining the mass of the core and calculating the centrifugal movable fluid content, and establishing a movable oil content prediction formula based on the nuclear magnetic relaxation ratio. The application has reasonable design, the movable oil content is predicted by calculating the proportion of the nuclear magnetic resonance bulk relaxation signal of the oil in the rock, and the reliability of the nuclear magnetic technology in identifying the fluid distribution of the oil is improved.

This invention discloses a method for rapidly measuring the surface wettability of mineral particles based on low-field nuclear magnetic resonance (NMR), belonging to the field of wettability measurement technology. This invention uses the seated drop method to test the contact angles of some energy, metallic, and non-metallic mineral particles, then obtains the T2 relaxation spectrum through low-field NMR testing, and finally obtains the T2 weighted average value T for different wetting times. 2g The value was calculated, and T was calculated for different wetting times. 2g The slope value k of the linear function was obtained by performing a linear quantitative fitting between the value and the wetting time. T2g Then k T2g k is obtained by performing a first-order linear fit with the corresponding mineral particle contact angle θ. T2g The relationship between the contact angle θ and the wettability of the mineral particles being tested is expressed as k. T2g The wettability of mineral particles is obtained from the relationship between the contact angle θ and the T2 weighted average value. The linear model established in this invention, which relates the slope of the wetting time fitting function to the contact angle, is accurate and reliable. It can complete the evaluation of the wettability of mineral particle surfaces in just 3 minutes, and has the advantages of being fast and efficient.

The invention discloses an articular cartilage MRI (Magnetic Resonance Imaging) image intelligent enhancement and contrast optimization system, which belongs to the technical field of medical image processing and comprises a cartilage feature extraction module, a self-adaptive enhancement module, a contrast optimization module and a quality evaluation feedback module, the cartilage feature extraction module realizes cartilage region classification and structural analysis based on T2 relaxation time distribution features and multi-scale structure tensor features; the adaptive enhancement module performs differential enhancement according to the region type and the structural feature; the contrast optimization module realizes contrast dynamic optimization through nonlinear mapping and edge gradient adaptive adjustment; according to the articular cartilage MRI image display system and method, the display quality of the articular cartilage MRI image is remarkably improved, the cartilage display definition is improved by 73% or above compared with that of an original image, and a high-quality imaging basis is provided for accurate diagnosis of chondropathy.

The invention provides a method for testing a minimum utilization pore throat of oil and gas modified fluid, and relates to the technical field of oil and gas development, and the method comprises the following steps: carrying out a high-pressure mercury injection experiment on a first rock sample to obtain a quantitative relationship between the mercury injection pressure and the pore throat radius; performing a nuclear magnetic resonance T2 spectrum test on the second rock sample to obtain an original T2 relaxation spectrum; establishing a conversion relation between nuclear magnetic resonance T2 relaxation time and aperture by using high-pressure mercury injection data; applying formation pressure to the second rock sample, carrying out constant-temperature reaction, putting into a centrifugal machine, and applying centrifugal force to simulate a strong driving process; and performing nuclear magnetic resonance T2 spectrum test on the centrifuged second rock sample, and calculating the minimum operating aperture according to the conversion relation. According to the method, the temperature and pressure environment and the strong driving process of reservoir in-situ modification are effectively simulated, the minimum using pore throat of the fluid is obtained through quantitative calculation, the precision of the micro-nano pore diameter section is improved through the conversion relation established through the fractal theory, skeleton signal interference is removed, and the accurate fluid occurrence state change rule is obtained.

The present application relates to the technical fields of magnetic resonance and medicine, and discloses a magnetic resonance-based vascular structure analysis method and apparatus, a computer device, and a storage medium. The method comprises: acquiring a first T2 relaxation time and a second T2 relaxation time, wherein the first T2 relaxation time is a T2 relaxation time obtained by performing nuclear magnetic resonance imaging using an SE sequence, and the second T2 relaxation time is a T2 relaxation time obtained by performing nuclear magnetic resonance imaging using a GE sequence; performing calculations on the basis of the first T2 relaxation time and the second T2 relaxation time, and determining an average radius of blood vessels and microvascular density within lesion tissue; and performing medical analysis on the basis of the average radius of blood vessels and the microvascular density. Hence, the average radius of blood vessels and the microvascular density within the lesion tissue can be provided and subsequently analyzed, thereby enabling evaluation of the vascular condition of the lesion tissue and quantitative analysis of vascular changes in regions surrounding the lesion tissue, facilitating comprehensive treatment effects, and improving the accuracy of early tumor diagnosis.

The invention discloses a device for measuring Young modulus of polybutylene-1, which belongs to the technical field of Young modulus measurement and has the measurement principle that the average T2 relaxation rate and Young modulus of the polybutylene-1 have good correlation. According to the measuring device, the Young modulus of a series of polybutylene-1 with different structures at different temperatures can be quickly obtained by utilizing the relationship. The method comprises the following steps: respectively measuring a stress-strain curve and a T2 relaxation curve of a polybutylene-1 sample in different states by using a stretching instrument and a low-field solid nuclear magnetic resonance spectrometer, obtaining Young modulus and a corresponding average T2 relaxation rate by using a corresponding program, and obtaining a linear function corresponding to the Young modulus and the average T2 relaxation rate; after the linear function is obtained, the Young modulus does not need to be obtained by repeatedly carrying out stretching detection on a sample through a stretching instrument like a traditional method, only the corresponding T2 relaxation time and phase composition need to be measured through a low-field solid nuclear magnetic resonance spectrometer, and then the Young modulus of polybutylene-1 in different states can be obtained by substituting the relaxation time and the phase composition into the function for calculation.

The invention relates to a magnetic resonance weighted imaging contrast quantification and relaxation time inversion method, and belongs to the technical field of magnetic resonance imaging. According to the method, human tissues are scanned through three groups of parameter differentiated fast spin echo sequences, interference factors such as equipment characteristics, proton density and deflection angles are eliminated by using parameter relevance among the sequences, a weighted weight is obtained through calculation of an amplitude image ratio, and finally accurate T1 and T2 relaxation values are obtained through inversion. The core innovation of the method lies in that quantification of weighted imaging is realized through scientific design of sequence parameters: ultra-long TR0 and ultra-short TE0 are adopted to construct a reference amplitude image, and an amplitude ratio and relaxation time are directly correlated through mathematical derivation in combination with a moderate comparison sequence of TR1 and TE1. According to the method, the subjective limitation of traditional weighted imaging is broken through, the image detail resolution is higher, the individual evaluation difference and the deviation between equipment can be effectively reduced, and a reliable quantitative basis is provided for early lesion detection, longitudinal curative effect tracking and group data comparison.

The application provides a novel ferrite bimodal magnetic resonance contrast agent and a preparation method thereof. The contrast agent comprises magnetic nanoparticles and ligands modified on the surface of the magnetic nanoparticles, wherein the magnetic nanoparticles are ferroferric oxide nanoparticles, and the ligands are triethylenetetramine hexaacetic acid. According to the application, the specific ligands are selected to modify the SPIO, so that the T1 and T2 relaxation rates can be significantly improved in the premise of not changing the core size and crystal structure of the nanoparticles, and the bottleneck of optimizing the bimodal performance is broken by precisely designing the interaction between the ligands and water molecules. The preparation method of the contrast agent is simple, the production cost is low, and the application is suitable for large-scale popularization and application.

The present invention provides a polyvinyl pyrrolidone-modified ferric oxide magnetic cluster and its preparation method and application, belonging to the field of material technology. The preparation method of the present invention directly removes the organic solvent from oil-soluble ferric oxide magnetic particles by rotary evaporation, and ultrasonically disperses them to prepare magnetic particle clusters in one step. The preparation method is simple, convenient and easy to operate, and can effectively reduce the operating steps of forming magnetic clusters in the prior art, and introduces fewer reagents, which is conducive to the clinical transformation of magnetic clusters. The polyvinyl pyrrolidone-modified ferric oxide magnetic clusters prepared by the present invention have uniform particle size and uniform dispersion, can convert small-sized particles with T1 imaging capability into clusters with strong T2 imaging capability, can effectively increase the T2 relaxation rate of particles, can be applied to magnetic separation or magnetic targeting technology, can be used as biomaterials, and have a wide range of applications.

The application discloses a kind of based on low-field nuclear magnetic resonance's poultry egg gender nondestructive identification method, belong to poultry egg detection technical field, comprising: S1, using low-field nuclear magnetic resonance equipment to carry out echo signal acquisition to poultry egg in turning chick period;S2, using non-negative least square optimization model to combine Tikhonov regular term to the echo signal of collection carries out spectrum inversion, reconstructs the T2 relaxation time spectrum related to poultry egg internal moisture and tissue structure distribution;S3, from T2 relaxation time spectrum, extract the multi-dimensional spectroscopy feature associated with poultry egg gender information, form the high-dimensional feature vector of representing embryo tissue microstructure difference;S4, high-dimensional feature vector is input into integrated classification model, and the output poultry egg gender identification result.The method of the application can be integrated on the automatic conveying line of hatching factory, realize multiple egg position parallel detection, fast non-contact identification and classification output, with high adaptability and engineering practicability.

The invention belongs to the technical field of nuclear magnetic resonance logging, and particularly discloses a pressure-maintaining coring nuclear magnetic porosity measurement method, system and program product, which are used for estimating pollution semaphore of pressure-maintaining liquid and correcting T2 relaxation distribution of a rock core through a corresponding convex optimization process. The relaxation component of the pressure maintaining liquid in an original signal is removed under the condition that the original relaxation signal of the rock core is not influenced, and the measured T2 relaxation distribution is ensured to be close to the real distribution of the rock core. By offsetting the pressure maintaining liquid signal component in the measurement signal, the interference of the pressure maintaining liquid signal on the measurement of the porosity of the rock core during the pressure maintaining coring can be effectively reduced, the measurement precision of the porosity of the rock core is improved, and the in-situ high-precision porosity measurement of the pressure maintaining coring sample beside the nuclear magnetic well is further realized.

The present invention falls within the area of well logging to evaluate formations in oil and gas producing fields. Particularly, the present invention describes a method for generating synthetic T1-T2 maps from marginal distributions of nuclear magnetic resonance logging tools, wherein the method comprises: decomposing marginal distributions of T1 and T2 relaxation times into an initial sum of log-normal functions with the same amplitudes and different means and standard deviations; setting the initial amplitudes, means and standard deviations so that the sum of log-normal functions corresponds to the marginal distributions of T1 and T2; and using the amplitudes, means and standard deviations set in a sum of two-dimensional log-normal functions to generate a synthetic T1-T2 map.

The invention provides a method for predicting rock movable oil content based on a nuclear magnet relaxation ratio. The method comprises the following steps: 1) measuring a rock core nuclear magnetic substrate T2 relaxation spectrum in a dry state and a T2 body relaxation parameter of white oil; 2) carrying out a complete saturation experiment on the rock core by using white oil, and carrying out a T2 nuclear magnetic resonance test to obtain a T2 relaxation spectrum of the rock core in a saturated state; 3) deducting a base signal from the saturated T2 relaxation spectrum of the rock core to obtain a T2 relaxation spectrum of white oil in the rock core, solving a relationship between relaxation time and a relaxation fluid proportion of the white oil body, and calculating the total amount of the relaxation fluid of the white oil body; and 4) centrifuging the obtained saturated rock core, measuring the mass of the rock core, calculating the centrifugal movable fluid content, and establishing a rock movable oil content prediction formula based on the nuclear magnet relaxation ratio. The method is reasonable in conception, the movable oil content is predicted by calculating the proportion of the relaxation signal of the nuclear magnetic resonance body in the rock, and the reliability of the nuclear magnetic technology in identifying the fluid distribution of the oil is improved.

The application discloses a kind of high-temperature baked food vacuum cooling process in the prediction method of moisture migration, method is: to high-temperature baked food sample Establishing porous medium model, the temperature, moisture content and pressure data of sample are predicted;Sample is placed in the vacuum cavity of vacuum cooling device, set vacuum cooling working condition parameter, start and begin vacuum cooling, and obtain pressure, temperature and moisture content data by collection;In the process of sample vacuum cooling, the transverse relaxation time T2 spectrum of sample in the process of vacuum cooling is collected using nuclear magnetic resonance moisture meter;According to the relationship between moisture content and T2 relaxation spectrum in the process of vacuum cooling Peak area, the function model of moisture content change in the process of vacuum cooling is obtained by fitting function;Verify porous medium model.The application can predict the moisture migration of high-temperature baked food in the process of vacuum cooling by establishing porous medium model, and is verified by vacuum cooling device, to avoid the subjectivity and tediousness of experiment.

The invention discloses an egg sex nondestructive identification method based on low-field nuclear magnetic resonance, and belongs to the technical field of egg detection, and the method comprises the following steps: S1, adopting low-field nuclear magnetic resonance equipment to carry out echo signal acquisition on eggs in a hatching period; s2, performing spectrogram inversion on the acquired echo signals by utilizing a non-negative least square optimization model and combining with a Tikhonov regular term, and reconstructing a T2 relaxation time spectrum of moisture in the poultry eggs related to tissue structure distribution; s3, extracting multi-dimensional spectroscopic features associated with the gender information of the poultry eggs from the T2 relaxation time spectrum to form high-dimensional feature vectors representing embryonic tissue microstructure differences; and S4, inputting the high-dimensional feature vector into an integrated classification model, and outputting an egg sex identification result. The method can be integrated on an automatic conveying line of an incubation factory, multi-egg-position parallel detection, rapid non-contact recognition and classified output are achieved, and high adaptability and engineering practicability are achieved.

The application discloses a nuclear magnetic resonance method for in-situ characterization of dispersion of carbon nanotube slurry, and belongs to the technical field of dispersion test of carbon nanotube slurry, and comprises the following steps: testing T2 relaxation spectrum of a solvent in the carbon nanotube slurry to obtain a spectrum peak of the solvent; testing T2 relaxation spectrum of the carbon nanotube slurry to obtain a spectrum peak of the slurry; comparing the number and width of the spectrum peak of the solvent and the spectrum peak of solid particles; if the spectrum peak of the slurry T2 relaxation spectrum is a single peak, and the width variation of the spectrum peak is less than the width variation of the spectrum peak of the solvent, then the dispersion of the slurry is qualified. The method has the advantages of fast detection speed, high measurement accuracy, good repeatability and consistency, and no need for any treatment of the slurry, can realize real-time and in-situ detection of the dispersion of the slurry, and makes up for the shortcomings and deficiencies of traditional slurry dispersion test methods.

The present application provides a method and system for identifying fluid occurrence types in tight oil reservoirs based on nuclear magnetic resonance, belonging to the technical field of oil geological exploration and development. The method comprises: based on the comparison between the nuclear magnetic resonance T2 relaxation time cumulative distribution curve of the tight oil reservoir sample and the high-pressure mercury injection pore throat diameter cumulative distribution curve, the pore throat types are divided, and the T2 relaxation time is converted into the pore throat diameter; the fluids occurring in different types of pore throats are identified through nuclear magnetic resonance spectrum, the fluid occurrence types corresponding to different signal domain ranges are obtained, and the relative contents of each fluid occurrence type are calculated; based on the signal domain ranges of each fluid occurrence type of several samples, a nuclear magnetic resonance fluid occurrence type identification chart is established, and the identification standards of each fluid occurrence type are determined. The present application combines the pore size distribution of T2 relaxation time with the nuclear magnetic resonance spectrum, determines the pore size range corresponding to the fluid occurrence type, and calculates the relative content of the fluid through the signal intensity of each signal domain, which is more accurate.

Some implementations provide a method for imaging one or more peripheral nerves in a region of a subject, which method includes: introducing a dose of an iron-based agent into the subject, wherein the dose causes a reduction of a T2 relaxation time of the subject's blood; and acquiring, from a magnetic resonance imaging (MRI) scanner, one or more fluid-sensitive MRI images of the region of the subject that has received the dose. The magnetic resonance (MR) signals from the subjects blood in the region is substantially reduced in response to the dose of the iron-based agent.

The invention discloses a dry fruit dryness multi-view intelligent detection method based on low-field nuclear magnetic resonance, and relates to the technical field of dry fruit dryness detection.The dry fruit dryness multi-view intelligent detection method comprises the following steps that S1, moisture activity evaluation indexes are provided; s2, performing T2 relaxation information analysis on the sample, wherein the T2 relaxation information analysis comprises T2 relaxation curve analysis and T2 relaxation information detection; s3, performing magnetic resonance image information analysis on the sample, wherein the magnetic resonance image information analysis comprises magnetic resonance image analysis, magnetic resonance image feature extraction, magnetic resonance image evaluation based on machine learning and magnetic resonance image evaluation based on a convolutional neural network; and S4, establishing a multi-view information fusion detection model, including model construction and model evaluation. According to the multi-view intelligent detection method for the dryness of the dried fruits based on the low-field nuclear magnetic resonance, a multi-view information fusion detection model is provided, moisture migration change and spatial distribution characteristics are effectively combined, the dryness of the dried fruits can be accurately evaluated, and the detection accuracy is superior to that of a traditional single information detection method.

This invention discloses a method for characterizing the pore size distribution of tight sandstone based on nuclear magnetic resonance (NMR) and peak coupling technology, belonging to the field of tight sandstone pore size characterization technology. The method includes obtaining the fourth derivative curve of the full pore size distribution curve of the tight sandstone sample using Peakfit software, identifying possible sub-peak positions; using the Peakfit software to deconvolve the full pore size distribution curve using a log-normal distribution, and iterating using an iterative peak sharpening algorithm until the chi-square goodness-of-fit standard value no longer changes; and finally, using the correlation coefficient r... 2 The goodness of fit between the fitted model and the original measurement data is evaluated using standard error (SE) and F statistical goodness of fit. This invention is applied to the identification and characterization of pore size distribution in tight sandstone, overcoming various limitations and problems of traditional nuclear magnetic resonance T2 relaxation time testing in characterizing the pore size distribution of tight sandstone. It features fewer limitations and faster, more accurate analytical results.

The invention relates to the field of data processing, in particular to an online detection method and system for dispersity of high-toughness silicon carbide ceramic slurry. Comprising the following steps: acquiring a surface image, nuclear magnetic resonance T2 relaxation imaging, magnetic field intensity and temperature data and slurry solid content information; evaluating the bubble presentation strength of the ceramic slurry, and evaluating a magnetic temperature stable factor; calculating an initial detection emphasis coefficient of the slurry sample; a T2 relaxation signal in the T2 relaxation imaging is extracted, curve fitting is carried out, the overall average deviation degree is calculated, the initial detection emphasis coefficient is corrected, and the detection emphasis coefficient is obtained; screening a high-confidence slurry sample from the slurry samples according to the detection emphasis coefficient; calculating the deterioration expression degree of the slurry; calculating a dispersity excellent score; and generating a final dispersity detection index. According to the method, the quality controllability and the product consistency in the ceramic slurry preparation process can be improved.

The invention discloses a quantitative characterization method for a low-permeability reservoir pore structure based on nuclear magnetic resonance T2 spectrum multi-peak fitting, and relates to the technical field of reservoir pore structure characterization, the nuclear magnetic resonance T2 spectrum is preprocessed, and Gaussian multi-peak fitting decomposition is performed on the preprocessed data; according to the peak area, the peak center and the peak width of each sub-peak, carrying out quantitative characterization on the porosity contribution and the aperture range of the corresponding micropores, mesopores and macropores; the sub-peak parameters obtained through multi-peak fitting are introduced into the permeability prediction model, the model for predicting the permeability based on the NMR T2 relaxation data is corrected based on the multi-peak fitting result, the permeability model is constructed, the permeability is predicted more accurately, and the method has great significance in promoting reservoir prediction.