18results about How to "Improve interpretation accuracy" patented technology

The invention discloses a crack effectiveness evaluation method and device based on conventional logging, equipment and a medium. The method comprises the following steps: calculating a resistivity reduction coefficient based on a resistivity curve; calculating an increase value of the interval transit time curve based on the interval transit time curve and shale content correction; calculating a resistivity invasion amplitude difference value based on the deep lateral resistivity and the shallow lateral resistivity; based on the resistivity reduction coefficient, the increase value of the interval transit time curve and the resistivity invasion amplitude difference value, calculating a crack effective evaluation index; establishing a relationship chart of the test results of the research area and crack effectiveness evaluation indexes, and determining a threshold value of the crack effectiveness evaluation indexes; and comprehensively evaluating the radial direction and the longitudinal direction of the crack based on the effective evaluation index and the threshold value of the crack. Based on the resistivity reduction coefficient, the increase value of the interval transit time curve and the resistivity invasion amplitude difference value, the crack effectiveness evaluation index is calculated, the crack envelope surface evaluation technology is established, and crack effectiveness evaluation is carried out on the complex reservoir.

The invention discloses an effective porosity and heavy oil saturation evaluation method and related equipment, and the method comprises the steps: calculating a plurality of groups of porosity components through collected echo measurement values, inverting a T2 spectrum by combining a dynamic logarithm spectrum splicing mode with the porosity components, and finally unfolding the T2 spectrum obtained through inversion by adopting MRIL-P or MRT to obtain the effective porosity. According to the method, a T2 spectrum is inversely generated in a logarithm spectrum splicing mode based on analysis of an MRIL-P or MRT spectrum unfolding principle; the problems of low precision of bound peaks and information loss before a certain moment can be solved by adopting a logarithmic spectrum splicing mode, so that the effective porosity is accurately obtained; by comparing the effective porosity obtained by the method with the helium porosity, the error is reduced to be within 1.5%, and the porosity explanation precision is obviously improved; by adopting the method, the technical problem that the effective porosity of the three-low characteristic region cannot be accurately calculated by the existing evaluation measure can be solved.

The invention discloses a well logging interpretation optimization method and device for a water-containing tight sandstone gas reservoir. The method comprises the following steps: determining a flow unit index by utilizing analysis test data of a rock sample; clustering the flow unit indexes, and dividing the rock sample into a plurality of rock physical facies types; for each type of rock physical facies, selecting a plurality of rock samples, and establishing a standard rock sample set; well logging interpretation models of different rock physical facies are established respectively; determining an Euclidean distance between a to-be-explained reservoir section of the to-be-explained well and a flow unit index related logging curve of a reservoir section corresponding to the rock samples in the rock sample set, and determining a rock physical facies type of the to-be-explained reservoir section according to the rock physical facies type of the optimal number of rock samples with the minimum Euclidean distance; and performing well logging interpretation on the reservoir section to be interpreted by using the corresponding well logging interpretation model. According to the method, the rock physical facies are divided based on the flow unit indexes, different well logging interpretation models are established respectively, the Euclidean distance is utilized to determine the rock physical facies, and the well logging interpretation precision is improved.

The invention discloses a method for determining well logging skeleton parameters of talc minerals and effective porosity of formations, which is characterized by comprising: obtaining the contents of various minerals in core samples at different depths of a coring well and the well logging curve of the coring well; establishing a calculation formula between the contents of various minerals at corresponding depths and the well logging values ​​on the well logging curve; solving the calculation formula according to the well logging skeleton parameters of known minerals to obtain the well logging skeleton parameters of the talc minerals; and solving the problem that the well logging skeleton parameters of the talc minerals are currently unknown and cannot be determined by a pure rock measurement method.

The application discloses a medical data index interpretation method and device, a storage medium and equipment. The method comprises the following steps: firstly, medical concepts and entity information of target problem text to be interpreted input by a target user are extracted; then, based on the medical concepts and entity information in the target problem text, a preset rule engine and a weak classifier are used to construct a candidate subgraph corresponding to the target problem text; then, a template text for prompting interpretation is constructed according to the candidate subgraph; and finally, an index interpretation result corresponding to the target problem text can be determined according to the template text for prompting interpretation. In this way, the dependency relationship between multiple groups of indexes is explicitly established by firstly extracting the medical concepts and entity information in the target problem text and then constructing the candidate subgraph, and the auxiliary reasoning result of the preset rule engine and the weak classifier is fused for medical data index interpretation, so that the index interpretation difficulty of the large model can be greatly reduced, and the interpretation accuracy of the medical data index is improved.

The application discloses a distributed adaptive framing output method based on large-range remote sensing images, and relates to the technical field of remote sensing image processing. The preprocessed large-range remote sensing images are stored in a COG format, the framing size and quantity are dynamically adjusted in combination with the target area range and resolution, the tasks are distributed by a data locality perception scheduler after Z-order curve sorting, the computing nodes load the framing data with a buffer area, the framing data is interpreted by a random forest, and the buffer area is cropped, finally, the virtual data set is aggregated, efficient distributed parallel processing of the large-range images is realized, the I / O bottleneck and the computing resource limitation are effectively relieved, the context missing problem on the framing boundary is solved, the intelligent interpretation efficiency and precision are improved, and the multi-resolution on-demand rendering and elastic expansion are supported to adapt to the data scale growth.

The invention relates to the technical field of image processing, in particular to a cat and dog allergen test paper result interpretation method based on artificial intelligence visual identification. Comprising the following steps: obtaining an allergy line sample set, collecting adsorption lines formed after a to-be-detected pet reacts with test paper, obtaining an aligned adsorption line set after multiple cycles, calculating a color mean value, selecting the allergy line with the maximum similarity, outputting an allergen corresponding to the allergy line, and the like. According to the invention, through multi-image alignment and equalization processing, single test errors such as environment illumination and shooting angles are significantly reduced; meanwhile, a similarity function is combined with a weight, an inhibition value and a convex optimization correction factor, so that a detection result is more accurate and reliable, when the similarity exceeds a threshold value, a suspected allergen can be quickly locked, and final verification is performed in combination with an increased dose exposure test. The method is compatible with various allergen test scenes, can be easily expanded to cloud big data management, and can greatly improve the efficiency and accuracy of cat and dog allergy detection.

This invention discloses a blood culture detection system based on spectral reflectance technology, comprising: a culture container for culturing samples; a sensor for sensing the sample state and changing color according to changes in the sample state; a light signal acquisition component for projecting single-wavelength light onto the sensor and receiving the reflected light signal after reflection by the sensor; and a reading module for obtaining a reading result indicating whether the sample is infected based on the received reflected light signal; the light source is used to project at least two different colors of single-wavelength light onto the sensor. This invention also discloses an alarm method for the blood culture detection system based on spectral reflectance technology. The blood culture detection system and alarm method of this invention, based on spectral reflectance technology, improve the accuracy of positive rate readings by using different wavelength light sources for detection.

The invention provides a spectrum inversion high-resolution processing method based on strong axis stripping, and relates to the field of seismic exploration, and the technical scheme is that the spectrum inversion high-resolution processing method based on strong axis stripping is characterized by comprising the following steps: inputting original seismic data, and extracting strong reflection wave event seismic data; subtracting the extracted strong reflection wave event seismic data from the original seismic data to obtain seismic data after strong reflection suppression; replacing the original seismic data with the seismic data subjected to strong reflection suppression, and establishing a spectrum inversion objective function; and solving the spectral inversion objective function to obtain a high-resolution seismic section which suppresses strong reflected waves and highlights weak signals. The method has the advantages that a spectral inversion high-resolution processing mechanism based on strong axis stripping is clear, and time domain iteration deconvolution stripping of the strong reflection wave event, spectral inversion high-resolution processing stripping of the strong reflection wave event, strong reflection suppression and spectral inversion high-resolution thin layer recognition are involved.

The invention relates to a method and device for determining the sweep range of a hydraulic fracturing propping agent, equipment and a storage medium. The method comprises the steps that the perforation position, microseism event parameters and hydraulic fracturing parameters of a fractured well are obtained; determining a micro-seismic event distance according to the perforation position and the micro-seismic event parameters; according to the micro-seismic event parameters and the hydraulic fracturing parameters, supporting dosage corresponding to the micro-seismic event is matched; according to the microseism event distance and the support dosage corresponding to the microseism event, establishing a mapping relation between the event distance and the support dosage and a mapping relation between the proppant distance and the support dosage; based on the mapping relation, the index coefficient and the classification coefficient of the propping agent are determined, and the microseism event with the classification coefficient being a specified value is used for indicating the sweep range of the propping agent, so that the sweep range of the fracturing propping agent can be effectively determined, the explanation precision of effective reconstruction cracks is improved, and the fracturing effect is accurately evaluated; and data support is provided for subsequent fracturing scheme design optimization.

The invention belongs to the technical field of seismic reflection interface tracking interpretation and quality control in the field of oil exploration and development, and discloses an interpretation horizon jump point recognition and correction method based on a variable balance difference algorithm. The method comprises the following steps of: calculating a jump point value generated due to non-closing at a horizon intersection point, determining a jump point coordinate or a lane number so as to quickly position a jump point, and calculating a correction value and automatically modifying a corresponding explanation scheme by taking the jump point as a circle center and utilizing a variable balance difference value algorithm according to the jump point value. The horizon explaining algorithm is applied to the horizon explaining process, the horizon explaining algorithm is applied to the horizon explaining process, the horizon explaining efficiency and precision are greatly improved, and the horizon explaining method has the advantages that the horizon explaining efficiency is improved.

This invention discloses a method for optimizing the phase of a mining area with a large gradient based on a probabilistic integral model, comprising: estimating the prior deformation variables of the mining area at different time periods by combining SAR image dates and prior probabilistic integral model parameters; converting the prior temporal deformation variables into radar line-of-sight deformation variables by combining satellite image parameters, and then converting the deformation variables into prior deformation phase values; constructing a full interferometric pair network based on SAR image data, removing the prior deformation phase from the differential interferometric phase to obtain the residual interferometric phase; selecting a homogeneous pixel set based on temporal amplitude values, calculating the coherence value of the residual phase, and constructing a complex coherence matrix; constructing a phase optimization model based on a coherence power weighting strategy to estimate the phase optimization estimate corresponding to the residual phase; and constructing a short-spatial-temporal baseline interferometric pair network to combine the interferometric phase calculated by the phase optimization estimate with the prior deformation phase of the same period to obtain the final optimized interferometric phase.

The present invention belongs to the technical field of image interpretation, and specifically discloses a polarization synthetic aperture radar complex image data transformation method, including: step 1, selecting a SAR complex image; step 2, converting the SAR complex image into an amplitude image A and a phase image φ; step 3, calculating the mean square error σ of the amplitude image A; step 4, calculating the U image according to the mean square error σ of the amplitude image A; step 5, calculating the phase image φ; step 6, calculating the phase V image according to the phase image φ; step 7, the calculation result (U, V) is the final SAR complex image data transformation result. The U and V obtained by the present invention through the transformation method have almost the same numerical range and statistical distribution form, which is conducive to improving the application degree and depth of phase data in SAR image target enhancement and detection, and improving the interpretation accuracy of SAR remote sensing images.

The present application discloses an apparatus and a device for sensing an analyte contained in liquid. The apparatus provided by the present application includes a liquid flow structure component and a sensing component. The liquid flow structure component includes: a measurement chamber configured to receive the analyte to be sensed, and wherein a sensible electrical signal is generated when the analyte to be sensed enters the measurement chamber along a first direction; an outlet chamber in fluid connection with the measurement chamber; and a nanochannel including a first opening connecting with the measurement chamber and a second opening connecting with the outlet chamber, so that the outlet chamber is in fluid connection with the measurement chamber, wherein a height difference between the first opening and the second opening of the nanochannel in the first direction is less than 20 µm. The sensing component is coupled to the measurement chamber to sense the electrical signal.

The invention discloses an overlying stratum time thickness-based energy homogenization processing method and device, electronic equipment and a medium. The method comprises the following steps: picking up a target geologic horizon and an overlying stratum of a whole work area; respectively smoothing the picked horizon and the overlying stratum to obtain a smooth horizon and a smooth stratum; time thickness is calculated according to the smooth horizon and the smooth stratum, and then the minimum value of the time thickness is determined; for each space point, calculating the ratio of the time thickness to the minimum time thickness as an energy compensation factor; and obtaining a post-stack seismic data volume with uniform energy of the target stratum according to the energy compensation factor. According to the method, the post-stack seismic data volume with relatively good amplitude consistency can be obtained, amplitude-preserved imaging is realized, the interpretation precision is improved, and changes of lithology and oil reservoirs in a geologic body space are truly reflected.

This invention relates to a method for identifying tight sandstone gas reservoirs, belonging to the field of oil and gas reservoir exploration and development technology. The method, based on original drilling data (field logging data and gas testing data), calculates the tight gas content index through parameter reconstruction. This index, geologically significant as a characterizing index of reservoir gas content, then establishes a correspondence between fluid properties in the study area and the tight gas content index and average sonic transit time. Finally, the fluid properties of the target layer are determined based on the tight gas content index and average sonic transit time. This method provides effective guidance for oil and gas exploration, evaluation, and development, improving the efficiency of drilling oil, gas, and water layer identification, reducing identification difficulty, and offering advantages such as simple operation, straightforward calculation, no need for highly skilled field personnel, high interpretation accuracy, and low processing time.

The invention provides an artificial intelligence interpretation method for multi-arm hole diameter logging data. The artificial intelligence interpretation method for the multi-arm hole diameter logging data comprises the steps that 1, imaging processing is conducted on logging interpretation data; 2, building a working condition interpretation model based on the convolutional neural network; step 3, training the built working condition interpretation model; 4, the well trained working condition interpretation model is utilized, and according to the collected actual multi-arm hole diameter logging data, the multi-arm hole diameter logging working condition is judged. According to the artificial intelligence interpretation method for the multi-arm hole diameter logging data, by combining the high-precision data acquisition capability of multi-arm hole diameter logging and the efficient intelligent analysis advantage of artificial intelligence, the interpretation efficiency and interpretation precision of multi-arm hole diameter logging interpretation work are effectively improved, and the labor intensity of workers is reduced.

This invention belongs to the field of electrical and magnetic variable measurement technology, specifically involving a method for measuring and identifying electromagnetic response electrical parameters based on linear background stripping and morphology-related parameters. The method involves a preset moving identification window width; within the selected window range, early and late multi-channel electrical responses of equal time periods are extracted from the first and last channels, respectively, and the summation and average are used to generate early and late characterizing multi-channel electrical responses; linear background removal is performed on the early and late characterizing multi-channel electrical responses to obtain early and late multi-channel abnormal morphology vectors; the correlation coefficient of the early multi-channel electrical responses with the late abnormal morphology is calculated to obtain the induced electromotive force (ICF) response identification factor at the center of the window; the window is moved point by point to obtain the distribution of ICF response identification factors corresponding to the overall data profile and normalized; the distribution and intensity characteristics of the ICF response in transient electromagnetic data are identified through its amplitude distribution, effectively improving the accuracy of ICF response identification in transient electromagnetic data.