18results about How to "Increase vertical resolution" patented technology

The invention relates to the technical field of logging evaluation of a shale gas reservoir geologic model, and discloses a logging evaluation method suitable for the shale gas reservoir geologic model, which comprises the following steps: collecting and arranging logging data, including natural gamma, resistivity, interval transit time, density and neutron logging curves, based on geological data and logging data of adjacent wells, an initial geological model of the shale gas reservoir is established, a logging curve is preprocessed, including depth correction, environment correction, data smoothing, utilization of response characteristics of the logging curve, identification of cracks and stratification in the shale gas reservoir, and utilization of the logging data to calculate physical property parameters of the shale gas reservoir. According to the logging evaluation method, a plurality of reservoir parameters including the organic carbon content, the thermal maturity, the porosity, the permeability, the water saturation, the fracture development degree and the like can be obtained, and the comprehensive analysis of the parameters can more comprehensively reflect the reservoir characteristics, so that the accuracy of a geologic model is improved.

The invention relates to the field of optical detection, in particular to an interference confocal measurement system based on two-dimensional dispersion and a measurement method thereof. White light generated by a light source is collimated into parallel light through a first collimating lens, is shaped into rectangular light through a rectangular diaphragm, and is shaped into a linear light beam through a column focusing lens and a rectangular slit; the light is divided into reference light and object light through a beam splitter, the reference light is achromatic through a first achromatic objective lens, then enters a reference plane mirror and is reflected back to the beam splitter by the reference plane mirror, the object light is focused to positions of different depths of an object to be measured after being dispersed through a dispersion lens and is reflected back to the beam splitter by the object to be measured, and the two beams of light are reconverged in the beam splitter. And after being collimated by the second collimating lens, dispersed by the dispersion grating and achromatic by the second achromatic objective lens in sequence, the light is focused on the target surface of the spectrograph for spectrum and interference analysis. According to the invention, line scanning, dispersion and interference measurement are combined, so that the measurement precision can be greatly improved.

The present invention discloses an integrated optical waveguide device, an endoscope probe and an all-optical photoacoustic endoscope sensing system, wherein the core layer of the integrated optical waveguide device includes a wave splitter, a first wavelength transmission area and a sensing reflection area connected to the wave splitter in sequence along the light transmission direction; the wave splitter is used to separate light of different wavelengths; the first wavelength transmission area is used to realize the transmission of pulsed light; the sensing reflection area is used to simultaneously realize the transmission, reflection or resonance of a preset wavelength optical signal, and monitor the change of the resonant wavelength or the reflection wavelength, and then monitor the change of environmental parameters. In the endoscope probe, the sensing light signal and the pulse light signal share a double-clad optical fiber, making the endoscope probe more compact. The integrated optical waveguide device of the present invention can realize signal and function separation, and the endoscope probe including the integrated optical waveguide device has high sensitivity, high longitudinal resolution, small size, high integration, and can be used in narrow spaces such as inner cavities.

The present invention belongs to the field of rock and soil detection, and provides a downhole borehole nuclear magnetic resonance detection device and working method. The device includes a transmitting system, a transmitting coil, a receiving system, a receiving probe, a control system and a processor; the control system is connected to the transmitting system and the receiving system respectively; the transmitting system is connected to the transmitting coil, which is arranged on the face of the tunnel and is used to transmit a pulse signal of set frequency and amplitude; the receiving system is connected to the receiving probe, which is arranged in the borehole of the face of the tunnel and is used to collect the echo signal of the pulse signal and transmit it to the processor through the receiving system; the processor is used to obtain the detection result data according to the echo signal and analyze the imaging to identify the groundwater source.

The present invention discloses a label-free photoacoustic pathology microscopic imaging system and imaging method. The system includes: an optical surface wave sensor for carrying tissue samples and water layers; an excitation light generating device; a detection light generating device; an objective lens, which allows the excitation light beam and the detection light beam to be incident on the tissue sample through the optical surface wave sensor; a processing and control device, which is used to control the movement of the excitation light beam to scan the tissue sample; an optical surface wave sensor, which is used to fully reflect the detection light beam, so that the reflected detection light beam is emitted through the objective lens; a processing and control device, which is used to split the detection light beam, synthesize photoacoustic signals and reconstruct images to obtain a target image. The imaging system has a high degree of integration and integration, and uses the optical surface wave sensor as a slide to carry the tissue sample, which can retain high-frequency signals to a great extent and improve the longitudinal resolution. In addition, the excitation light beam and the detection light beam share an objective lens, which can better ensure the coaxiality of the two light beams.

The present invention discloses an optical path system and a laser radar. The optical path system emits N synchronous light beams into a rotating polyhedral prism, and forms N scanning lights through the rotating polyhedral prism. The scanning lights are reflected by a fixed polyhedral prism to form N vertical scanning lights that are synchronously emitted from the center of a circle toward the outside. Compared with a single light source, the refresh rate is increased by N times. When the refresh rate is maintained at 1 / N, the scanning time of each horizontal angle is correspondingly increased, the vertical scanning time within the horizontal scanning angle is increased, and the vertical resolution is increased. This laser radar includes N (at least two) laser transmitters, an optical path system, a horizontal rotation structure, and a motor control module. The laser emitted by the laser transmitter emits N vertical scanning lights through the optical path system. When the refresh rate remains unchanged, the rotation speed can be reduced, and the scanning time of each horizontal angle is increased, thereby increasing the vertical scanning time within the horizontal scanning angle, and increasing the vertical resolution by multiples.

The application discloses a sedimentary reservoir prediction method based on three-dimensional seismic data, which comprises the following steps: step one, feature extraction; step two, feature dynamic fusion; step three, model establishment and training; step four, optimization of storage prediction results; and step five, visualization interaction. The system comprises a data processing module, a feature fusion module, a model training module, a reservoir prediction module and a visualization interaction module. The dynamic weight distribution algorithm is used to fuse multi-dimensional features such as seismic waveforms, frequency spectra and geometric attributes, so that the vertical resolution of thin interbedded layers is significantly improved, the identification difficulty of hidden reservoirs is solved, and the loss risk is reduced. A double-channel neural network model is established to automatically extract seismic features and sedimentary facies knowledge, so that the deviation of artificial feature engineering is avoided, the rapid modeling demand of a complex sedimentary environment is met, and the prediction results are constrained and corrected, so that the continuity of a vertical sedimentary sequence is ensured.

This invention discloses an improved machine learning-based intelligent prediction method for stratigraphic models and related equipment. By fusing depth-aligned high-frequency active seismic source data and low-frequency passive seismic source data, a multi-dimensional complementary source feature vector is constructed, significantly improving the vertical resolution and deep penetration capability of stratigraphic prediction. A genetic algorithm is used to globally search and optimize the network parameters of the convolutional neural network. Combining binary encoding and genetic operations effectively avoids the pitfalls of traditional gradient descent methods, which are prone to getting trapped in local optima, thus improving the globality and stability of model parameter optimization. Through iterative fitness verification and threshold determination, the optimal network parameters are adaptively determined without manual intervention, significantly reducing the cost of hyperparameter tuning while effectively ensuring the generalization performance of the prediction model. The final prediction model can perform fast and accurate stratigraphic prediction based on real-time source data and can be widely applied in the field of data processing technology.

The invention discloses a near-surface velocity model establishment method and system based on VSP constraint, and belongs to the technical field of near-surface velocity modeling methods. Comprising the following steps: calibrating a first-motion wave travel time tomography inversion speed model by using a VSP speed to obtain a calibrated tomography inversion speed model, and calculating speeds of different layer sections to obtain speed calibration values; carrying out longitudinal subdivision on the calibration chromatography inversion velocity model to generate a subdivision grid model, and calculating the velocity of different layer sections to obtain a velocity correction coefficient; according to a multi-point geostatistics algorithm, spatial interpolation extrapolation is carried out on each speed correction coefficient, and a final speed model correction coefficient body is obtained; and calculating to obtain a near-surface velocity model based on the first arrival wave travel time tomography inversion velocity model and the final velocity model correction coefficient body. According to the method, the characteristics of high spatial lateral resolution of the first arrival tomography inversion velocity model and high longitudinal resolution of the VSP velocity model are effectively combined, and near-surface fine modeling is realized.

The invention discloses an earthquake prediction method and system for trona ore exploration, and the method comprises the steps: recognizing a trona development layer section and the thickness of a single layer through logging lithology interpretation in combination with logging and core data, and determining a trona sensitivity logging curve; establishing an isochronous stratigraphic framework by applying a well-seismic combined interpretation technology, tracking the ore-bearing position, and determining top and bottom boundary structural characteristics of the alkali-bearing ore position and ore body seismic facies characteristics; based on the top and bottom boundary structural features of the alkali-containing ore layer, a layer constrained structural model is created, a sensitive logging curve is selected to reconstruct a feature curve, the feature curve serves as a control waveform to conduct seismic waveform simulation inversion, and the distribution range of the trona ore body and the thickness of the ore layer are predicted; and depicting the spatial form of the trona ore body based on a seismic waveform simulation inversion result, and determining an exploration project distance and enclosing a first mining area in combination with comprehensive evaluation of ore deposit geological conditions. The earthquake prediction technology is used in trona ore exploration for the first time, and the exploration efficiency and the drilling success rate are improved.

The invention discloses a pipeline interior detection instrument, and relates to the technical field of pipeline detection, the pipeline interior detection instrument comprises a plurality of preset probe groups which are arranged in sequence, each preset probe group comprises a plurality of preset probes, and all the preset probes in each preset probe group are arranged in an annular array; the distance between every two adjacent preset probe groups is not an integral multiple of a measurement interval, and the measurement interval is the displacement of the preset probes in one measurement period. According to the invention, the plurality of preset probe groups are sequentially arranged, and the distance between every two adjacent preset probe groups is not the integral multiple of the measurement interval, so that the longitudinal measurement points of the pipeline can be encrypted, the longitudinal resolution of the detection in the pipeline can be improved, and the method can adapt to a high-speed detection scene; the preset probes in other preset probe groups can still perform normal detection, and the longitudinal resolution of the detection in the pipeline is still higher than the longitudinal resolution of a traditional detection instrument in the pipeline.

The invention provides a reservoir fluid identification method, device and equipment and a storage medium, and the method comprises the steps: obtaining geological information data of a research area, building an initial geoelectric model, and determining the top and bottom depths of each target stratum; acquiring wide-area apparent resistivity data of all stratums to obtain an overall wide-area apparent resistivity profile, and deleting data of each target stratum in the overall wide-area apparent resistivity profile to obtain an original wide-area apparent resistivity profile; based on a frequency spectrum encryption technology and a wide area electromagnetic method, obtaining wide area apparent resistivity data of each target layer; according to the initial geoelectric model, the undisturbed wide area apparent resistivity profile and the wide area apparent resistivity data of each target stratum, taking the initial geoelectric model as a current geoelectric model, executing a multi-target stratum progressive inversion strategy, and obtaining a target inversion apparent resistivity profile containing all target stratum information; and fluid identification and division are carried out according to the target inversion apparent resistivity profile. According to the method, the speed and the precision of fluid identification can be improved through multi-objective layer progressive inversion.

The invention relates to an unmanned aerial vehicle pseudo-random electromagnetic underwater pipeline leakage detection method and device, and the method employs the magnetic field response difference between a leakage region and a normal region, and recognizes the leakage position and range of a pipeline through the change of a magnetic field. Multi-sequence variable-frequency-density pseudo-random electromagnetic signals are transmitted through a host, an unmanned aerial vehicle carries a signal receiver to carry out signal measurement and feedback in a near-water-surface area, the detection requirements of underwater pipelines with different depths are met, the longitudinal resolution of pipeline leakage is improved, and meanwhile, underwater electromagnetic interference is effectively reduced by enhancing the strength of a main frequency signal, so that the detection accuracy is improved. Therefore, the water pipe leakage detection precision is obviously improved. According to the method, the unmanned aerial vehicle is adopted to carry the three-component magnetic field receiver, the three-component probe can capture magnetic field components in three orthogonal directions at the same time, and the characteristic helps to reduce the influence on data acquisition caused by the attitude change of the receiver when the unmanned aerial vehicle flies.

The present invention discloses a method, device, computing equipment, storage medium and product for extracting acoustic wave time difference, and relates to the field of oil and gas exploration. The method comprises: obtaining acoustic wave logging data corresponding to different depths in a target layer; calculating the Akaike information criterion value of a multi-channel waveform in the acoustic wave logging data corresponding to each depth, and determining the initial arrival of the acoustic wave corresponding to the depth; combining subarray data of different subarray spans by using a multi-source waveform similarity superposition method; performing dynamic windowing according to the initial arrival of the acoustic wave for any subarray span; calculating the two-dimensional correlation function of each subarray according to the slowness-time correlation method, and converting the two-dimensional correlation function into a one-dimensional coherence function; superimposing the one-dimensional coherence functions of all subarrays to estimate the slowness value of the wave on the subarray span, and determining the longitudinal wave time difference after performing depth migration. The present invention effectively improves the accuracy and longitudinal resolution of acoustic wave time difference extraction.

The invention discloses a GNSS-based large-scale marching type ionosphere disturbance three-dimensional monitoring method and system. The method comprises the following steps: calculating the total electron content of an oblique ionosphere between a satellite and a receiver by adopting non-difference non-combination precise point positioning; based on Savitzky-Golay smoothing and Butterworth band-pass filtering, the total electron content of the detrending oblique ionized layer is obtained; based on spatial and temporal distribution formed by multiple stations, multiple satellites and multiple elevation puncture points, a three-dimensional ionosphere electron density disturbance model is constructed, and ionosphere disturbance three-dimensional propagation characteristics are solved. According to the method, the total electron content of the detrended oblique ionized layer is obtained based on Savitzky-Golay smoothing and Butterworth band-pass filtering, trend removal and disturbance reservation can be better balanced, and the signal-to-noise ratio and reliability of the extracted large-scale marching type ionized layer disturbance signal are improved; meanwhile, the constructed three-dimensional ionosphere electron density disturbance model not only can reveal vertical coupling characteristics of ionosphere disturbance, but also can stably extract key propagation elements and improve monitoring accuracy.

This invention provides a method for determining deconvolution parameters and a method for processing seismic data, belonging to the field of seismic exploration of oil and gas. The method for determining deconvolution parameters includes the following steps: selecting N experimental parameter values ​​for the target exploration area and performing a first inverse selection process, a second inverse selection process, and a third inverse selection process respectively; based on the inverse selection results of the first, second, and third inverse selection processes, inversely selecting out N-1 experimental parameter values ​​to determine the deconvolution parameters, where N is an integer and N≥2. By integrating multiple qualitative and quantitative evaluation results and using an inverse selection method, the method achieves the determination of deconvolution parameters suitable for the target exploration area, and the results are unique, objective, and accurate, avoiding interference from subjective human factors, and obtaining deconvolution parameters that balance the vertical resolution and signal-to-noise ratio of seismic data.

The invention provides an earthquake attenuation gradient calculation method and system based on Hamiltonian characteristic analysis, and relates to the technical field of geophysical exploration and signal processing, and the method comprises the steps: obtaining at least two geophysical attributes sensitive to medium absorption attenuation through attribute extraction based on seismic data; based on geophysical attributes, constructing an effective quantum potential field which comprehensively reflects the absorptivity and heterogeneity of the underground medium; constructing a discrete Hamiltonian matrix for describing a seismic signal quantization system based on the effective quantum potential field; performing characteristic decomposition on the discrete Hamiltonian matrix to obtain an orthogonal quantum adaptive characteristic function; and analyzing local time-frequency spectrum attenuation characteristics of the quantum adaptive characteristic function, and obtaining a quantum attenuation gradient value through calculation and synthesis. The method solves the problems that an existing seismic attenuation gradient estimation method is low in resolution, poor in noise immunity, insufficient in capacity of distinguishing elastic impedance difference and inherent attenuation, and lack of a unified physics and mathematics framework for organically fusing multi-attribute information.

The embodiment of the invention discloses a troposphere temperature and water vapor inversion method combining GNSS-RO (Global Navigation Satellite System-Reverse Osmosis) and AMSR-E. A bending angle observation value of each ray path is obtained through calculation and inversion based on a GNSS-RO technology and serves as GNSS-RO observation data; an AMSR-E forward operator is obtained based on a radiation transfer model, and a brightness and temperature observation value is obtained through AMSR-E and serves as AMSR-E observation data; performing joint assimilation on the GNSS-RO observation data and the AMSR-E observation data by using a 1DVar algorithm which is improved by adding a physical constraint condition; iteratively solving the atmospheric state vector by adopting a Newton method; iterative solution of the atmospheric state vector is completed through a convergence criterion, and temperature and water vapor inversion of the stratified atmosphere is completed; the GNSS-RO provides temperature and humidity profile information with high vertical resolution, and the AMSR-E provides horizontal distribution information with high spatial resolution, so that the three-dimensional temperature and water vapor distribution of the atmosphere can be more comprehensively and accurately inverted by jointly using the data of the GNSS-RO and the AMSR-E.