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5results about How to "Lower Exploration Costs" patented technology

A core capturing device based on ultra-short radius and multi-direction coring

PendingCN122280482ASolve the problem of excessive radial sizeAccurately reflects penetration rateRock coreClassical mechanics
This invention discloses a core capture device based on ultra-short radius and multi-directional coring, belonging to the field of core capture technology. It includes an ultra-short radius directional drill bit, a multi-directional capture chamber, a micro-steering joint, a chamber switching valve assembly, and an ultra-short radius measurement and control terminal. The ultra-short radius directional drill bit is composed of a hemispherical cutterhead and an elastic deflection base. This invention solves the problem of excessive radial dimensions in traditional devices through structural miniaturization and power transmission optimization. It is adaptable to ultra-short radius wellbore operation scenarios such as radial branch wells and sidetracking infill wells. By overcoming the limitations of traditional unidirectional sampling, it can obtain core samples from reservoirs in different directions, accurately reflecting the anisotropy of physical properties such as permeability and porosity, supporting fine reservoir evaluation. For complex conditions such as shale and fractured formations, the sealing and jamming control design of the capture mechanism is optimized to reduce core loss, fracture, and drilling fluid contamination, ensuring core integrity.
Owner:SICHUAN UNIV

Method and device for correcting AVO trend of pre-stack gathers of interbedded shale oil reservoirs

PendingCN122283899AImprove offsetImprove reliabilityWave fieldSeismic wave
This invention relates to the field of seismic exploration technology, and particularly to a method and apparatus for AVO trend correction of pre-stack gathers for interlayered shale oil reservoirs. The method includes: constructing seismic wavefield amplitude and travel time equations based on the steady-phase principle; establishing illumination weight coefficient equations based on deconvolution imaging conditions according to the seismic wavefield amplitude and travel time equations; determining illumination weight coefficients using the equations based on the forward-modeled wavefield propagation amplitude, receiver amplitude, shot amplitude, travel time from imaging point to shot point, travel time from imaging point to receiver point, travel time from shot point to receiver point, and angular frequency; and using the illumination weight coefficients to perform amplitude illumination compensation on the pre-stack gather seismic data to obtain the pre-stack gather imaging results after AVO trend correction. This invention can improve the accuracy of AVO in pre-stack seismic gathers, thereby identifying sweet spots in interlayered shale reservoirs with optimal reservoir and production potential, improving the reliability of geological models, reducing the risk of blind drilling, and saving exploration costs.
Owner:DAQING OILFIELD CO LTD +1

A coal seam lithium-rich seam detection method based on well logging curve and statistical analysis

The application discloses a coal seam lithium-rich layer detection method based on well logging curves and statistical analysis, and belongs to the technical field of mineral resource exploration. The method comprises the following steps: selecting a series of representative coal seam positions for systematic sampling, and preparing the samples into piston samples and powder samples; determining the kaolinite and lithium content of the powder samples, and distinguishing lithium-rich and ordinary coal samples; systematically determining various geophysical response parameters of the piston samples, such as density, resistivity and wave velocity, and screening out sensitive discrimination indexes for lithium enrichment; setting a window size, calculating the moving statistical value curves of the density, resistivity, wave velocity and other well logging curves sensitive to the lithium-rich layer, calculating principal components, and using the selected principal components and a support micro machine to train a prediction model, so as to predict the lithium-rich layer in the coal seam. The application combines geophysical logging, statistical analysis, principal component analysis and a support vector machine, and provides a fast, economical and non-destructive means for lithium resource exploration in coal.
Owner:CHINA UNIV OF MINING & TECH

A method and device for evaluating reservoir oiliness based on gas logging data

PendingCN122283950AImprove exploration efficiencyLower Exploration Costs
A method and apparatus for evaluating reservoir oil-bearing potential based on gas logging data, the method comprising: acquiring raw total hydrocarbon data and gas logging influencing factor data of a target formation in a study area; determining correction coefficients for each gas logging influencing factor, and obtaining corrected total hydrocarbon data based on the correction coefficients and raw total hydrocarbon data; calculating a similarity factor and a saturation factor using the corrected total hydrocarbon data; and determining the oil-bearing potential of the target formation based on the similarity factor and the saturation factor, and using a pre-established gas logging data interpretation chart in the study area.
Owner:CNPC GREATWALL DRILLING COMPANY +1

A method for predicting deep-sea rare earth elements in three dimensions by a hybrid attention network fusing spatial and depth data

ActiveCN121600396BRealize Quantitative Predictionincrease diversityAlgorithmPredictive methods
This invention discloses a hybrid attention network method for 3D prediction of deep-sea rare earth elements, integrating spatial and depth data, and relating to the interdisciplinary fields of artificial intelligence and marine mineral resources. The method first acquires multi-source environmental and depth data, which are then integrated, cleaned, spatially aligned, interpolated, and standardized to construct a model input containing environmental feature image patches and standardized depth values. Spatial feature vectors are extracted using a convolutional neural network, and depth feature vectors are encoded using a multilayer perceptron. The two types of features are concatenated, and dynamic weights are generated and weighted using an attention network to obtain a weighted feature vector. This weighted feature vector is input into the prediction head module, and the model is trained using a loss function, optimizer, and early stopping mechanism. The trained model is applied to a 3D mesh of the target region, and after inference prediction and de-standardization, the predicted 3D rare earth element content is output. Simultaneously, the feature contribution is analyzed through an interpretable model.
Owner:SOUTH CHINA SEA INST OF OCEANOLOGY CHINESE ACAD OF SCI