214 results about "Density curve" patented technology

The invention is a seismic wave impedance inversion method, determining amplitude and phase spectrums of pos-stack seismic data, and extracting seismic subwaves on a near-well seismic channel and determining amplitude and phase spectrums, spectrum widths and master frequencies of the seismic subwaves; picking up seismic stratigraphic horizons corresponding to geological stratigraphic horizon and checking and correcting as well as smoothing and interpolating the picked horizons; demarcating logging acoustic time difference and density curves, and demarcating depth-domain logging acoustic time difference and density curves into time-domain ones, consistent with horizons of stacked seismic data, generating in-well wave impedances; making wavelet odd analysis and wavelet characteristic extraction on the stacked seismic data; providing high resolution wave impedance parameters for reservoir description in the exploration, development and recovery of oil fields.

The invention provides a method for predicting a brittleness index of shale, and belongs to the field of oil and natural gas prospecting. The method comprises the following steps of (1) preparing geology, logging and seismic data; (2) analyzing contents of quartz, clay and carbonate rocks in data by using rock mineral constituents of the shale and calculating the ratio of the content of brittle minerals to the content of total minerals, namely calculating a rock mineral brittleness index; (3) calculating rock mechanics characteristic parameters by using longitudinal wave velocity, shear wave velocity and a density curve in dipole acoustic logging data; (4) establishing a multiple regression model between a rock mineral brittleness index curve and a rock mechanics characteristic parameter curve at the position of a well point; (5) performing prestack inversion to obtain longitudinal wave velocity, shear wave velocity and density data bodies and calculating rock mechanics characteristic parameter data bodies; and (6) calculating by using the multiple regression model obtained in the step (4) and the rock mechanics characteristic parameter data bodies obtained in the step (5) to obtain brittleness index data bodies.

The invention relates to a method for carrying out online monitoring on an operating state of a transformer OLTC (on-load tap-changer) and belongs to the field of signal monitoring. The method comprises the following steps of: acquiring a mechanical vibrating signal of a box wall of a transformer in real time; carrying out phase space reconstruction on the vibrating signal x(t) by using a delay coordinate method; determining a designated area V of a reconstructed phase space; calculating density distribution of space phase points; calculating a correlation coefficient rho of a space density curve before and after the OLTC actuates; if the correlation coefficient rho is more than 0.8, judging that the operating state of the OLTC is normal; and if the correlation coefficient rho is less than 0.8, judging that the operating state of the OLTC is abnormal. By carrying out real-time monitoring on the vibrating signal in the actuating process of the OLTC, efficient and accurate judgment on the working state of the transformer OLTC can be implemented. The method can be widely used for the field of online monitoring and fault diagnosis of various transformer OLTCs.

The invention provides a user behavior analysis method and apparatus. The user behavior analysis method comprises the following steps: establishing an information connectivity graph according to the behavior data of a plurality of users; extracting a plurality of bipartite graphs based on a plurality of preset relationship models according to the information connectivity graph; obtaining a score density curve of the plurality of bipartite graphs based on a preset scoring model; and identifying suspicious user behaviors based on the score density curve. By adoption of the user behavior analysismethod provided by the invention, the abnormal user behaviors can be effectively identified, which is helpful for discovering a new network fraud mode and preventing the network fraud.

The invention discloses a dense clastic rock natural gas well productivity prediction method based on reservoir classification. The method includes the steps that the effective thickness of each reservoir and the effective thickness of each thin interbed are acquired according to logging information; the shale content of each reservoir is calculated according to a curve of natural gamma and three porosity; the porosity of each reservoir is calculated according to a curve of sound waves, neutrons and density, and the reservoirs are classified; the permeability and gas saturation of the reservoirs are calculated according to core analysis pore permeability and an Archie equation; reservoir classification calculation and summing are conducted through thickness weighting, and then a comprehensive gas index is acquired; the conception of the thin interbeds is introduced according to the differences of reservoir depositional microfacies, and then the improved comprehensive gas index is acquired; the relation between the improved comprehensive gas index and test productivity is built, and then the productivity of other reservoirs is predicted with the relation as a model. On the basis of ensuring simple operation, the method has high reservoir productivity prediction accuracy.

Disclosed is a method for using a fracture density curve to forecast a fracture density body. The method for using the fracture density curve to forecast the fracture density body includes following steps: (1) preparing geology, well logging and earthquake data, performing normalization processing, inversion and attribute data body optimization on the related data, and obtaining the fracture density curve and an optimized data body of all wells after being normalized; (2) building various fracture density calculation models, bringing data on the fracture density curve of all the well after being normalized and curve data of the optimized data body into calculation, and selecting the fracture density calculation model most approximate to an actual fracture density situation according to calculation results; (3) bringing the optimized data body into the selected fracture density calculation model for calculating so as to obtain fracture density bodies after being normalized, and then obtaining the fracture density body of a time domain through reverse normalization processing. The method for using the fracture density curve to forecast the fracture density body can complete detailed description for the fracture density data body of the time domain, and then reduces well drilling risk, and improves shale gas exploration benefit.

The invention discloses a fracture development degree identifying method of a dense dolomite reservoir. The fracture development degree identifying method comprises the steps that the lithological refined division of the dense dolomite reservoir is carried out, and fracture characteristics of different lithological segments are described, and a chart of a corresponding relation between the different lithological segments and the fracture characteristics is established; the fracture line density characteristic values of the different lithological segments are intersected with various well logging parameters by using a scattering method; various sensitive well logging parameters are selected from the various well logging parameters, and a quantitative evaluation model between the various sensitive well logging parameters and the fracture line density characteristic values of the different lithological segments is established; according to the established quantitative evaluation model, the fracture line density value of every well logging point is calculated, and a fracture line density curve is drawn, and the fracture development degree of the dense dolomite reservoir is identified. By adopting the method provided by the invention, a fracture development degree of a dense dolomite type oil reservoir is effectively evaluated, and then a scientific basis is provided for the reasonable development of the dense dolomite oil reservoir.

The invention relates to a downhole wireless safety monitoring system based on mixed networking of 2.4 GHz and 433 MHz frequency ranges. The system consists of mobile nodes, fixed nodes, a gateway node, a transmission node and a ground main frame, wherein the mobile nodes are mainly carried by miners and are provided with sensors for monitoring the body temperature and pulse of each miner; the fixed nodes arranged in mine roadways are also provided with sensors for monitoring ambient gas density at real time; the ground main frame receives data collected in the downhole, displays personnel positioning information and physiological parameter information at real time, displays a gas density curve at real time, and is capable of setting up an overrun alarm and releasing act of rescue information to the downhole.

The invention discloses an on-line measuring method and apparatus for the degree of crystallization of a polymer used for injection molding. The method comprises the following steps: 1) acquiring the density of a complete crystal region of a polymer and the temperature-density curve of a complete noncrystal region of the polymer; 2) acquiring the density of a complete noncrystal region of a polymer melt in a die; 3) employing supersonic wave for real time detection of the current density of the polymer melt in the die and obtaining the real time degree of crystallization of the polymer melt according to the current density detected, the density of the complete crystal region and the density of the complete noncrystal region. The apparatus provided in the invention comprises a sensor unit, a data acquisition unit and a central processing unit, wherein, the sensor unit comprises a supersonic wave detection unit and a temperature sensor, the supersonic wave detection unit comprises a supersonic wave emitting unit and a supersonic wave receiving unit, and the temperature sensor and the supersonic wave receiving unit are respectively connected with the central processing unit through the data acquisition unit. The invention enables on-line measuring of the degree of crystallization of a polymer in the process of injection molding to be realized; the apparatus provided in the invention has the advantages of a low price and convenient usage.

The invention discloses a test method for current noise of a high-resistance device and a medium material, comprising the following test steps: firstly, arousing the low-frequency current noise of a high-resistance sample by utilizing a sample adapter; then amplifying the sample low-frequency noise by utilizing a low-noise current amplifier; collecting amplified noise signals by utilizing a data acquisition card; calculating the power spectrum density S0(f) of the collected current noise signals of which the high-frequency parts are attenuated by the amplifier; obtaining the amplitude-frequency characteristic curve of the current amplifier by utilizing a locking amplifier, and calculating a normalized curve Q(f) according to the amplitude-frequency characteristic curve; reducing the attenuated power spectrum density S0(f) by utilizing the Q(f), thus obtaining a power spectrum density curve S(f) of a reduced band spread; and finally, carrying out data analysis on the S(f) to screen devices or research sample reliability. By utilizing the test method, the problems of narrow times-number transmission band and insufficient test data in the existing test method for high-resistance sample noise are solved; and the test method provided by the invention has the advantages of high efficiency, automated operation and high precision of reduced data.

The invention relates to a frequency domain analysis method of bridge fatigue life on the basis of a dynamic weighing system. The frequency domain analysis method comprises the following steps: collecting data including the vehicle weight, the vehicle speed and the axle distance of each vehicle which passes through a bridge; calculating the collected data, and carrying out curve fitting; according to a fitting probability density curve, establishing a cellular automata simulation model of the vehicle, and generating a random traffic flow; simulating load time history under different vehicle flow density conditions, and loading the load time history to a bridge influence line to obtain stress time history data; carrying out FFT (Fast Fourier Transform) on the stress time history, obtaining PSD (Power Spectral Density), and calculating relevant parameters; using a Dirlik method to establish an experience form of a PDF (Probability Distribution Function); and calculating residual service life. Calculation time is greatly shortened.

The invention discloses a forecasting method for brittleness of a compact oil and gas reservoir and a device. The method comprises the following steps of: acquiring a model relation on the basis of an acquired well logging curve and utilizing the model relation to establish a shear wave velocity forecasting model; forecasting and acquiring a shear wave velocity curve on the basis of the shear wave velocity forecasting model; calculating an elastic parameter curve according to the shear wave velocity curve, a density curve and a longitudinal wave velocity curve; acquiring a quartz content data on the basis of a quartz content well logging curve and a post-stacked seismic data; acquiring a brittleness index on the basis of the quartz content data; acquiring a time depth curve and a seismic wavelet on the basis of pre-stacked seismic data, the longitudinal wave velocity curve and the density curve; and establishing an initial model on the basis of the time depth curve, the density curve and the elastic parameter curve, and then acquiring a compound angle set of different angles and establishing an inversion equation through the compound angle set and a pre-stacked angle set, thereby inversing and acquiring the data of Young modulus; acquiring the data of the brittleness index on the basis of the quartz content data and the data of Young modulus.

The invention relates to an intelligent optimized multi-attribute fusion method based on a crack model. The method comprises the following steps that S1) earthquake and logging data is loaded and calibrated; S2) a logging curve is corrected manually to ensure that the logging data matches the earthquake data; S3) a crack density curve is calculated, and different logging response and different earth physical response caused by different sizes of cracks are analyzed; S4) according to the earth physical response of the cracks of different sizes, logging is combined with earthquake to establish a crack network forward model, and optimized crack sensitive attributes are analyzed; S5) a crack sensitive parameter is introduced, and earthquake data is trained near a well point; and S6) the trained nonlinear relation is applied to the whole earthquake data body, and the aim of predicting the crack variable parameter is achieved. The fusion method has the advantages that the multiple crack attributes are combined and optimized via nonlinear expansion of the algorithm, and the multi-solution performance of prediction of cracks of different sizes is effectively reduced via multiple times of training learning and probability estimation.

A sensor apparatus and method that can measure either a linear position or an angular position of a device. A linear array of galvanomagnetic sensing elements is fixedly mountable adjacent the device. A target is connectable to the device such that the target moves adjacent a surface of the linear array in response to movement of the device and is shaped so that a magnetic flux density curve resulting from excitation of the sensing elements includes a peak and / or a valley. A first circuit excites each of the sensing elements, and a second circuit measures a magnetic flux density value at each of the sensing elements. A maximum and / or a minimum of the flux density curve indicates the position of the device.

A surface definition module of a hair / fur pipeline may be used to define a surface and an optimization module may be used to determine whether a hair is to be rendered upon the surface. In particular, the optimization module may be used to: determine a size metric for the hair; apply a first density curve to the size metric determined for the hair to generate a density multiplier value; and based upon the density multiplier value, determine whether the hair should be rendered.

A color image forming apparatus includes a developing unit to which a developing bias with an AC component superposed is applied, wherein the DC voltage of the developing bias is adjusted to set the detected density of a solid image at a specified value, the light amount of radiation for exposing an image area having a width of a few dots adjacent to the white paper is adjusted to set the detected density of an image developed under a peripheral electric field at a specified value, and the gradation density curve is regulated by alternately adjusting the DC voltage, the light amount of radiation for exposing the image area having a width of a few dots adjacent to the white paper, and the amplitude of the AC component until the detected density of a mesh point image having an area ratio from 60 to 80% falls within a specified range.

A coupon fabrication with defined distortion in the form of marceled fibers and test protocol is employed to determine the shape of the failure probability density curve to improve the analyses of the risk of fiber distortion anomalies in composite structures. This protocol provides a method to determine the probability of and the severity of the various distorted fiber conditions that might exist on composite structure in fabrication and in service. A distortion characterization matrix is established for determining test shapes and providing defect characterization based on the results of tests on the selected shapes. Coupons for test are created using resin pool

The invention discloses a power curve fitting method of a wind turbine generator based on optimizing maximum value of probability density, comprising the following steps of: 1) collecting the needed data of wind turbine generator power curve in the appointed area; 2) pre-treating the data collected in step 1) to obtain the data needed by the experiment; 3)dividing the data set obtained in step 2) into N simulation areas; 4) fitting the probability density curve of the power value in each simulation area; 5)searching the maximum point of power value probability density curve in each simulation area, 6) counting the position of maximum position of probability density in many simulation areas, 7) amending the reference power in each simulation area, and 8) corresponding the representative air wind in each simulation to the amended reference power, and drawing the power curve figure.

The present invention discloses a field robot binocular vision navigation method and system. A baseline is defined at the middle of an image; a density curve is obtained on the baseline by using sector scanning; an angle constraint relation between a sector scanning density model and ridge lines is designed, and the angle constraint relation is used to search other ridge lines; logistic regression is adopted to identify nearest ridge lines, so that a ridge line spacing parameter can be obtained; the elevation map of crop ridges is obtained, and a height limit is added into the elevation map; the enhanced elevation map and a binary image are fused, so that a crop ridge confidence density map can be generated; and a ridge line extraction algorithm is applied to the crop ridge confidence density map so as to extract a navigation parameter. According to the field robot binocular vision navigation method and system of the invention, the enhanced elevation map is adopted to make up the defect of feature point sparseness; the weight of height information is increased; interference information which does not accord with specified height is filtered out; the concept of the confidence density map is adopted; the information of the enhanced elevation map and the binary image are fused; the sector scanning detection is adopted to detect the reference ridge line; a double-peak method is adopted to detect the adjacent ridge lines; logistic theories are used in combination; and therefore, the accuracy of ridge line detection can be improved.

The invention discloses a phase noise measuring method based on a wide frequency range, short response time and high resolution. The phase noise measuring method comprises the following steps of: firstly, conditioning and shaping a tested signal and a reference signal respectively, wherein the tested signal is stabilized by the conditioning, and the reference signal is shaped to be a high-frequency pulse suitable for sampling; secondly, carrying out standard phase shifting on the high-frequency reference pulse, and densely sampling the tested signal in a zero passage part by adopting the phase-shifted pulse and an original phase as a clock of an AD (analog-to-digital) converter, then recovering information indicating that the phases are overlapped and the overlapping is subjected to deviation, and controlling and processing the phase detecting information; thirdly, controlling a measuring gate with the processed phase detecting signal which serves as a switching signal, and carrying out high-resolution zero-clearance gating time measurement on phase overlapping points, thus showing the strength of phase noises by the variation of gating time; and fourthly, processing the gating time measuring information to achieve the conversion between the gating time variation and the phase noises, thus displaying a single-side phase noise power spectrum density curve of the tested signal.

The invention relates to a horizontal well crack recognition method. The horizontal well crack recognition method comprises the following steps: detecting a horizontal section of a horizontal well to obtain a well logging curve which is sensitive to a crack and a rock density curve, and further reconstructing to obtain a crack fractal index curve, a crack feature index curve and a stratum brittleness index curve; obtaining a crack index curve according to the various curves obtained by reconstruction; and recognizing development degree of the crack of the horizontal well in the horizontal direction according to the crack index curve, wherein the development degree of the crack is increased along with increasing of crack indexes. According to the method provided by the invention, response strength of the crack is amplified by well logging data, non-crack influences are eliminated, crack information is extracted comprehensively from the well logging data, and cracks of the stratum surrounding the horizontal well are recognized accurately.

The invention provides a navigation radar co-frequency interference inhibition method based on spatial correlation. The method comprises the steps of: loading spatial sea area clutter continuous images, and synchronously recording an image sampling point number, a bus number, a direction number and a display mode; utilizing correlation among radar image signals in a spatial domain, carrying out correlation coefficient calculation on adjacent storage lines; carrying out classified statistics on correlation coefficient histograms of signal lines and noise lines, drawing corresponding probability density curves, utilizing a fixed threshold method to determine detection thresholds; and judging the noise lines and the signal lines through the detection thresholds; and utilizing a close line substitution method to restore the noise lines detected out. Aimed at the distribution characteristic that co-frequency interference on the radar images is represented as rayed noise in the radial direction, the sea clutter spatial correlation is utilized for noise detection, noise pre-processing is carried out on original radar images, the co-frequency interference is filtered out, and the sea wave parameter inversion precision is improved.

The invention provides a method and device for determining TOC content. The method comprises the following steps: establishing a TOC optimally-estimated mineral rock physical model by utilizing data of laboratory-measured X-ray diffraction data, organic carbon density and logging density curve and the like; obtaining accurate TOC distribution on a well through an optimization iteration method; establishing a TOC quantity version by utilizing actually-measured TOC data and an equivalent medium model; determining TOC sensitivity elastic parameters; and finally, carrying out prestack elastic parameter inversion on earthquake reflection gather obtained through OVT region processing. The method and device for determining the TOC content realize the purpose of quantitatively forecasting space distribution of the TOC content by utilizing well-seism integration through statistical fitting, and solve the problem of not high TOC content forecasting result; and through using the laboratory-measured data and the rock physical model effectively, the estimated result is not only matched with the laboratory-measured value at the places of rock samples, but also can predicate the TOC content at the places without sampling points accurately.

The invention discloses a microwave determination method for breakable beads in a breakable bead filter rod. The microwave determination method comprises the following steps: collecting breakable bead samples, and measuring the diameters Db of the breakable beads; collecting a breakable bead filter rod sample, measuring the density rholij of the part which does not contain the breakable bead of the filter rod, and finding out the maximum value rholmax of rholij; measuring the density rholij of the part containing the breakable beads of the filter rod, finding out the maximum value rohbihmax of the unit density of the part in which each breakable bead is located, and finding out the minimum value rhomin of rohbihmax; measuring the density of the breakable bead filter rod by virtue of a microwave resonance method by taking the length of 1mm or less as a measurement unit, and drawing a density curve of the breakable bead filter rod by taking the length as a horizontal axis and the density as a vertical axis; and reflecting the existence the breakable bead by virtue of the appearance of a peak value in the curve, reflecting the position offset of the breakable bead by virtue of the corresponding length of the peak value, and reflecting the damage condition of the breakable bead by virtues of the variation of the peak value. The microwave determination method is simple, the operation is easy, and the existence, position offset and damage condition of the breakable bead in the breakable bead filter rod can be accurately determined.

A radar apparatus that focuses a subset of transmit beams within a field of view (FOV) is provided. The radar apparatus has a phased array transmitter that is operable to generate a transmit beam within the FOV, and a phased array receiver that is operable to receive a receive beam reflected from within the FOV. The apparatus also has a radar controller with an electronic circuit and electronic memory, the electronic memory having a plurality of pre-calculated beam density curves. The radar controller is operable to execute each of the plurality of pre-calculated beam density curves and steer at least one transmit beam generated from a particular executed beam density curve towards a sub-area of the FOV.

The invention belongs to the field of distributed generation power quality of a power distribution network of a power system and particularly relates to a system harmonic probability evaluating method based on the Markov chain Monte Carlo method (MCMC). The system harmonic probability evaluating method based on the MCMC comprises the steps that firstly, a harmonic injection current model of a point of common connection (PCC) is analyzed; secondly, the MCMC is deduced; thirdly, an MCMC sampling algorithm flow for harmonic probability evaluation of the power distribution network is put forward again; finally, typical quintuple harmonics and typical septuple harmonics injected into the PCC of the power distribution system are calculated according to the algorithm flow, based on the MCMC sampling method, for harmonic probability evaluation of the power distribution system, and thus a probability statistics characteristic value and a probability density curve of harmonic injection current of the PCC are obtained. According to the system harmonic probability evaluating method based on the MCMC, the influence of the ratio of linear loads to non-linear loads during different time periods is considered, solution is conducted according to the effective MCMC sampling method, the situation that historical measurement data and experience-based judgment results are excessively depended on is avoided, and thus results can be more comprehensive, more objective and more similar to the actual condition of the power distribution network.

The invention provides a method for automatic calculation of a lithological curve by employing a logging curve in geophysical exploration, and belongs to the field of petroleum geophysical exploration. The method includes: (1) loading the logging curve, comprising curves of gamma, spontaneous potential, resistivity, neutron, and neutron lifetime; (2) respectively correcting the five curves, and obtaining corrected curves; (3) respectively reading the maximum GMAXi and the minimum GMINi of the five curves from the corrected curves; (4) calculating the curve shale content relative value Shi; (5) calculating the shale content; (6) calculating the final shale content Vsh; (7) calculating the lithological curve with the combination of the final shale content Vsh obtained by the step (6) and a measured density curve Density; and (8) outputting the lithological curve.

The invention provides a method for predicting gas content of shale by using seismic data and belongs to the petroleum and natural gas exploration field. The method includes the following steps that: (1) geological, logging and seismic data are prepared; (2) a density logging curve-based gas content calculation model, that is VGAS=f(DEN) (1), is established through using high correlation between a density logging curve and shale gas content data, wherein VGAS is gas content, m<3> / t, DEN is a density logging curve, g / cm<3>, and f is a function relational expression between gas content and density; (3) post stack multi-attribute inversion is carried out, so that density curve data required by the gas content calculation model can be obtained; and (4) gas content prediction is carried out: the density curve data obtained in the step (3) are introduced into the formula (1), so that the gas content of the shale can be obtained.

The present invention provides a temperature increasing and pressurizing foam cement slurry density testing device, and belongs to the field of oil field foam cement slurry cementing. The device comprises a pressure system, a temperature system, a test system and a computer acquisition system. According to the present invention, the foam cement slurry is placed into a cavity of a pressure resistance kettle; a piston is arranged on the upper part of the cement slurry; a pressurizing chamber is arranged on the upper part of the piston; a specially made high precision displacement sensor is arranged on the piston; and the upper part of the piston is fitted with a precision pressure source. According to the present invention, under the pressure effect, the volume of the foam cement is compressed, the piston moves downward, the displacement amount is measured by the displacement sensor and is converted into the digital amount. With the device of the present invention, the density change law of the foam cement at a certain temperature under a certain pressure can be accurately measured; the computer acquisition system is adopted to display and record the pressure-temperature-density curve, such that the strong basis is provided for real evaluation of the density of the foam cement under the underground construction conditions.

The invention discloses a test apparatus and a test method for the heat insulation performance of a honeycomb panel. A test piece to be tested is a high temperature alloy honeycomb panel. The test apparatus comprises a laser, a controller, an optical path adjusting device, a test fixture, a temperature sensor and a data acquisition system. The test method provided by the invention comprises the following steps: disposing the high temperature alloy honeycomb panel in the test fixture; adjusting the laser, the controller and the optical path adjusting device to allow laser output to exactly satisfy requirements for a heating range of the test piece to be tested; compiling a laser power control program according to a heat flux density curve to be simulated in testing; adjusting the laser power control program, confirming that the test apparatus is completely right and then starting testing; and collecting testing data from the data acquisition system connected with the temperature sensor and disposing and analyzing the data. The test apparatus and the test method for the heat insulation performance of the honeycomb panel in the invention have the following advantages: small energy consumption, simple operation, capacity of convenient and rapid changing of a temperature and capability of accurate and effective testing of the heat insulation performance of the honeycomb panel.