10467results about "Borehole/well accessories" patented technology

A soil layer detection drilling device includes a drilling cylinder, and a soil-sampling assembly is provided inside the drilling cylinder. When the soil is drilled, equipment is in a vertical state, a controller is turned on to control a rotary motor to rotate, and the drilling cylinder is driven to drill the soil with the cooperation of drive wheels and a drive belt. Four slide blocks are evenly distributed around an outer circumference of a sliding disk and are matingly connected with slide grooves provided on an inner wall of the drilling cylinder, so when the drilling cylinder rotates, the soil-sampling assembly also rotates. A conical head first in contact with the ground starts to drill the ground, then the drilling cylinder gradually drills into a soil layer, and the drilling cylinder is idled as the drilling cylinder arrives at a certain depth, to clear soil on auger blades.

The invention provides an adaptive multi-modal feature fusion well logging interpretation method based on multi-task joint learning, and the model comprehensively employs a graph convolution network, a multi-head attention mechanism, a gating mechanism and an adaptive loss weight adjustment algorithm, and effectively integrates multi-well group well logging data and geological structure information. And the complex spatial relationship and geological similarity between the wells are fully captured. The model can process multi-source data in a unified manner, extracts high-level feature representation containing spatio-temporal correlation, avoids repeated feature learning, reduces calculation complexity, and ensures the consistency and complementarity of prediction task features at the same time. The self-adaptive loss weight adjustment mechanism dynamically optimizes weight distribution according to the loss change of each task, realizes balance optimization among different tasks, and comprehensively improves the prediction precision of each task. The physical constraint regularization module ensures that the prediction result not only has statistical accuracy, but also conforms to the actual geological physical law, so that the reasonability and reliability of the prediction result are improved.

The invention provides a geological exploration drilling device and method for geotechnical engineering design, and relates to the technical field of geological sampling, the geological exploration drilling device comprises a vehicle body, a propelling mechanism, a drill rod and a drill bit, the drill rod comprises a plurality of sampling barrels and locking assemblies arranged between every two adjacent sampling barrels, the drill bit comprises a drill barrel arranged at the bottom of the drill rod, a spacer bush arranged in the drill barrel and a plurality of cutting plates arranged on the side wall of the spacer bush at equal intervals in a sliding mode, the knocking assembly is arranged on the support, and the knocking assembly can strike the exterior of the drill rod in the process that the propelling mechanism drives the drill rod to vertically move. A soil core pressed into the drill rod can be cut off from an external soil layer, the bottom of the drill rod is sealed, it is prevented that in the upward moving process of the drill rod, the soil core slides off to affect soil sample collection, the drill rod can be assembled according to needs so that the soil core can be conveniently divided into multiple small sections, the soil core in the drill rod can be stably taken out, and the working efficiency is improved. The soil core is prevented from being taken out from a relatively long drill rod and fractured and crushed to influence subsequent detection.

Embodiments of systems and methods for converting thermal energy to electrical power are disclosed. In embodiments, a system for converting thermal energy to electrical power may include a thermal cycle device. The thermal cycle device may include an evaporator including a first fluid path for a flow of heated fluid and a second fluid path for a flow of a working fluid and configured to indirectly transfer heat from the flow of heated fluid to the flow of working fluid, a condenser to cool the working fluid, a pump to transport working fluid from the condenser, an expander to generate electrical power via the working fluid, and a loop for the flow of the working fluid. The system may include an amount of heat carrier injected into the loop and configured to adsorb and desorb the working fluid and generate additional heat to increase output of electrical power.

A method for constructing a high fidelity logging while drilling (LWD) log that includes obtaining a temporal well depth log and a plurality of temporal LWD logs from a drilling operation. The method further includes obtaining a temporal record of operational drilling parameters from the drilling operation. The method further includes determining, using a first machine-learning model, a temporal history of the drilling operation and constructing, using the temporal well depth log and the plurality of temporal LWD logs, a plurality of temporal property logs at each depth in the plurality of depths. The method further includes processing the plurality of temporal property logs with, at least, a second machine-learning model to form a plurality of corrected temporal property logs and aggregating the plurality of corrected temporal property logs to form a plurality of high fidelity LWD logs.

The invention relates to a shale oil borehole wall collapse pressure prediction method. The method comprises the following steps: acquiring components, structures and physicochemical properties of a shale oil reservoir; carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined measurement experiments of different drilling fluid systems; constructing a shale oil reservoir rock heterogeneous water absorption and strength degradation equation; establishing ground stress and pore pressure profiles; converting the far-field crustal stress into a borehole and bedding coordinate system; calculating a well periphery stress field generated by water absorption of the surrounding rock; simulating and calculating the temperature field distribution of the rock and calculating a thermal stress value; the well periphery stress value under the force-chemical-thermal-bedding coupling effect is calculated in a superposition mode; constructing a well surrounding rock matrix and weak plane shear failure discrimination function and condition; constructing a shale oil reservoir collapse pressure numerical simulation iterative trial algorithm; determining a formation collapse pressure density control factor and a control mechanism; and the shale oil borehole wall collapse risk is reduced through optimization. According to the method, the shale oil borehole wall collapse pressure under the force-chemical-thermal-bedding coupling effect can be predicted more accurately.

Some implementations include a system comprising at least one coiled tubing extending from a surface of a wellbore to a bottomhole assembly (BHA); a power cable to be housed either inside or outside the at least one coiled tubing and to electrically couple a power supply at the surface of the wellbore with the BHA. The BHA comprises at least one capacitor to store electrical power received from the power supply via the power cable housed in the at least one coiled tubing; and at least one electrode electrically coupled to the at least one capacitor to receive the stored electrical power from the at least one capacitor and to periodically emit pulsed power discharges into a subsurface formation to drill the wellbore based on the stored electrical power received from the at least one capacitor.

The invention belongs to the technical field of oil and gas production and development, and discloses a sand production pressure difference and sand production quantity quantitative prediction method suitable for a high-temperature and high-pressure sandstone reservoir, which comprises the following steps: calculating static rock mechanical parameters of a target well; predicting initial crustal stress; establishing a porosity and permeability dynamic evolution model; establishing a three-dimensional finite element model; establishing a seepage stress coupling transient nonlinear finite element equation; applying well bottom pressure drop to simulate production, and determining sand production pressure difference; and establishing a sand production rate prediction model, and quantitatively predicting the sand production rate. According to the method, factors such as pore permeability stress, temperature change and water content influencing rock strength are comprehensively considered, a three-dimensional finite element model is established, a seepage stress coupling finite element equation and solving steps are established based on a reservoir elastic-plastic consolidation theory, critical plastic strain is introduced to quantitatively characterize the sand production risk, a sand production prediction model is established, and the rock strength is predicted. And finally, quantitative and accurate calculation and scientific pressure control of the critical sand production pressure difference and the sand production amount are realized.

The invention discloses a deep coal rock in-situ gas content and adsorption / free gas proportion calculation method and device, and relates to the field of reservoir resource potential evaluation.The deep coal rock in-situ gas content and adsorption / free gas proportion calculation method comprises the steps that an isotope fractionation model coupled with a double-dispersion pore structure (matrix pores and kerogen pores) and a multi-gas transmission mechanism (viscous flow, Knudsen diffusion and surface diffusion) is constructed; the accumulated analytic gas quantity and the apparent isotope value of the produced gas obtained through solving are fitted with the actually measured accumulated analytic gas quantity and the apparent isotope value of the produced gas, and key parameters corresponding to the optimal fitting result are obtained; and determining the in-situ gas content, the in-situ adsorption gas proportion and the in-situ free gas proportion according to the productivity evaluation parameters at the initial moment corresponding to the optimal key parameters. According to the method, the in-situ gas content, the in-situ adsorbed gas proportion and the in-situ free gas proportion of the deep coal rock are calculated on the basis of an isotope fractionation model coupled with a double-dispersion pore structure and a multi-gas transmission mechanism, so that the gas resource content of the deep coal rock is predicted.

The invention relates to the technical field of engineering early warning, in particular to a drilling engineering early warning method and system, and the method comprises the following steps: collecting a plurality of operation parameters of drilling equipment in real time based on a drilling engineering environment, screening the data, carrying out the comparative analysis of the parameters, evaluating the deviation between the current operation parameter and the conventional operation data, and carrying out the early warning of the drilling engineering. And obtaining equipment operation deviation information. According to the method, the operation parameters of the drilling equipment are collected and processed, key parameters such as the drill bit speed and torque are monitored in real time, deviation with conventional data is found in time, the abnormal condition of the equipment can be quantitatively evaluated by analyzing the frequency and duration of the operation deviation of the equipment, and the stratum data aggregation and trend analysis are combined. The safety of drilling operation is enhanced, the stability of a drilling site can be evaluated by extracting key features such as stratum density and rock hardness, risk classification is performed accordingly, risk early warning is achieved, and potential accidents are effectively avoided.

The invention discloses an oil reservoir dynamic monitoring method and device. The method comprises the steps that sound wave data and temperature data collected by distributed optical fiber sensors in real time are obtained; the distributed optical fiber sensors are deployed in a plurality of injection and production wells according to a preset deployment rule; the sound wave data and the temperature data are input into an oil reservoir dynamic monitoring model, an oil reservoir fluid three-dimensional dynamic graph is output, and the oil reservoir fluid three-dimensional dynamic graph displays oil reservoir fluid state data; the reservoir dynamic monitoring model is obtained by training a Transform model by using historical sound wave data, temperature data and reservoir multi-source information in advance; in the training process, time and space grid alignment processing is carried out on historical sound wave data, temperature data and oil reservoir multi-source information, time-space sequence features are obtained, and the model identifies oil reservoir fluid state data in the time-space sequence features based on self-attention and multi-attention mechanisms. The accuracy and reliability of oil reservoir monitoring and analysis can be improved.

The invention discloses a tight reservoir three-dimensional crustal stress field modeling method based on an improved neural network. The tight reservoir three-dimensional crustal stress field modeling method comprises the steps that S1, a unified-format multi-source geological physical data tensor set is constructed; s2, constructing a frequency domain hierarchical enhancement-SIREN implicit neural network structure based on the unified format multi-source geological physical data tensor set; s3, inputting the candidate hyper-parameter configuration into the frequency domain hierarchical enhancement-SIREN implicit neural network to complete one-time model training; s4, aiming at each candidate hyper-parameter configuration, initializing an inner-layer population of the black widow optimization algorithm, completing second model training, and obtaining an optimal model parameter of the frequency domain hierarchical enhancement-SIREN implicit neural network; s5, tight reservoir fracturing parameter optimization and real-time safety window adjustment are achieved. According to the method, the continuous stress field can be quickly generated at the resolution of 1 m, real-time well section updating and fracturing scheme optimization are supported, and the fracturing transformation effect, the fracturing safety margin and the reliability of economic productivity prediction are remarkably improved in practical application.

A geothermal system is used for obtaining heated heat transfer fluid, such as steam, via heat transfer with an underground reservoir of magma. The geothermal system includes a wellbore extending between a surface and into an underground chamber formed in a reservoir of magma. The chamber may be formed by injecting a fluid at an increased pressure into underground magma to form a cavity that acts as the underground chamber.

A method can include receiving dielectric data from a downhole dielectric tool of a drillstring disposed in a borehole in a target material that includes a target material boundary between the target material and one or more other materials; generating a geosteering command, based at least in part on the dielectric data, that calls for orienting a drill bit of the drillstring with respect to the target material boundary; and issuing the geosteering command to a geosteering actuator of the drillstring.

The invention provides a drilling risk determination method and device. Before specific implementation, a graph auto-encoder is introduced and used, and a preset detection model which is based on physical constraints and has a good application effect is obtained through unsupervised learning and training. In specific implementation, current target logging data of a target well and a logging data set of a current time period can be firstly obtained; determining a current working condition according to the target logging data; according to the current working condition, the logging data set of the current time period and a preset geological-engineering pre-drilling evaluation profile, a target dynamic threshold value which aims at a current target well and is based on working condition constraints and considers the change condition of data processed in the current time period before graph self-coding is determined; processing the target logging data by using a preset detection model to obtain a corresponding target reconstruction error; and detecting whether a drilling risk exists according to the target reconstruction error and the target dynamic threshold. Therefore, the drilling risk can be accurately detected and identified, and the false alarm rate is reduced.

The invention discloses a high-precision logging lithology intelligent identification method based on DenseNet-Transformer depth fusion. The method comprises the following steps: step 1, carrying out data preprocessing; and step 2, constructing a deep learning model in which a DenseNet mechanism and a Transform mechanism are fused. According to the method disclosed by the invention, efficient feature multiplexing is realized by using the dense connection characteristic of the DenseNet through a deep learning technology, and the global feature modeling capability is enhanced in combination with the Transform network, so that the lithology identification accuracy and generalization capability are remarkably improved. The method is suitable for intelligent analysis of complex logging data, especially shows excellent performance in the aspects of high-dimensional data processing and fine feature extraction, greatly improves the recognition difficulty of a traditional method in a complex stratum structure, and provides important technical support and efficient decision basis for the fields of oil-gas exploration, geological survey and the like.

The invention provides a drilling formation identification and adaptive parameter adjustment method and system, and the method comprises the steps: converting multi-source sensing data into structured formation feature representation through constructing a formation response mode library, and achieving the precise identification of formation interface distribution; a parameter response area distribution analysis and missing information reconstruction technology is adopted, recessive stratum characteristics are deeply excavated, and the internal law of stratum changes is revealed; an adjusting point optimization selection and enhanced drilling path planning mechanism is introduced, and an efficient drilling control network is constructed; potential field distribution is constructed through parameter change features, and coupling correlation between the parameter features and spatial positions is established; intelligent configuration and self-adaptive adjustment of drilling parameters are realized by combining harmonic force analysis and execution scheme generation; and finally, a complete drilling stratum identification and parameter control system is formed, an accurate and efficient technical solution can be provided for drilling operation in a complex stratum environment, and the drilling efficiency and the operation quality are improved.

This disclosure describes systems and methods for determining spatial distributions of petrophysical properties in a subsurface formation. A method includes obtaining input data including petrophysical data, geophysical data and geological data of the subsurface formation; selecting input features from the input data; forming a training dataset including the input features and corresponding labeled data representing a target petrophysical property of the subsurface formation; training, using the training dataset, an ensemble machine learning model; and determining a spatial distribution of the target petrophysical property based on the trained ensemble machine learning model.

A method for adaptively monitoring a subsurface fluid storage facility. The method may include parameterizing a gas storage model using a computation engine and executing the gas storage model in one or more simulators following which analysis operations may be executed on the modeling results to generate one or more reports and / or automatically or semi-automatically configure equipment associated with gas storage operations at a given resource site. The results from these tests may be fed into one or more analysis engines that condenses the vast simulation results into actionable insights and / or configuration settings, and / or safety data that may be used to optimize the configuration and / or operation of gas storage equipment at a given resource site. The method may pinpoint precise monitoring techniques to deploy at each stage comprised in the gas storage campaign thereby mitigating against gas storage project risks and operational costs.

The invention discloses a logging-while-drilling reservoir parameter dynamic prediction method based on double attention convolution LSTM, and the method comprises the steps: obtaining logging-while-drilling data and drilling data in real time, and carrying out the preprocessing of the data; establishing a DTW dynamic time window model based on a gradual transition strategy, and adaptively adjusting the length of an input sequence according to the stratum change speed; a double attention convolution LSTM model is combined with the DTW dynamic time window model to establish a feature-time double attention mechanism, and two dimensions of features and time are adaptively fused based on the convolution LSTM; setting a buffer area, storing data and controlling data quality; setting an online increment fine tuning strategy; and performing instance training, and performing multi-angle evaluation on the performance of the double attention convolution LSTM model by adopting multiple indexes. According to the scheme, the influence of features and time on the prediction accuracy is fully considered, and the prediction accuracy is improved.

The invention belongs to the technical field of construction control, and particularly discloses a dry-method precise positioning construction control system and method based on machine learning. Multi-dimensional data such as drilling resistance, vibration frequency, shovel head angle deviation, position and soil layer hardness are acquired in real time through a multi-source data acquisition module; the deviation calculation module carries out dynamic comparison analysis based on data corresponding to a preset sampling area, the dynamic adjustment module dynamically optimizes the drilling speed and angle through a multi-condition triggering mechanism and a transfer adjustment rule, and finally the control execution module generates a precise control instruction to drive the Luoyang shovel to execute deviation correction action. Through multi-dimensional data fusion analysis and a real-time dynamic adjustment strategy, the path precision and the stratum adaptability of the drilling operation are remarkably improved, meanwhile, the adaptability of equipment to stratum sudden change is improved, the construction risk under the complex geological condition is reduced, and collaborative optimization of the drilling efficiency and the operation safety is achieved.

Vibration in a drill string is damped with a damping system coupled to the drill string. The damping system includes a chamber, a gas and piston in the chamber, and a mass connected to the piston. The gas defines a spring having a spring coefficient that is dependent on a volume or temperature of the chamber. The damping system is tunable in real-time by varying the volume or temperature of the chamber. In alternatives with multiple chambers interconnected to one another via ports, chamber volume at the existing pressure can be varied by selective actuation of valves between the chambers or the pressure of the gas can be varied by compressing or expanding a connected bellows or by heating or cooling the temperature of the gas. The damping system can selectively damp both radial and torsional vibrations.

A borehole wall spin-shearing device includes a load applying assembly, a soil shearing assembly, and a data acquisition assembly, where the load applying assembly is configured to apply a vertical load and an axial rotational load to the soil shearing assembly; the soil shearing assembly includes a plurality of shear plates; the plurality of shear plates are configured to penetrate into undisturbed soil after being ejected due to the vertical load and then shear the undisturbed soil due to the axial rotational load; and the data acquisition assembly is configured to acquire torque values of the plurality of shear plates during a process of shearing the undisturbed soil. The borehole wall spin-shearing device can directly conduct an in-situ borehole shear test in an exploration borehole with a conventional diameter in China, reducing the cost of drilling. The borehole wall spin-shearing device achieves a high degree of automation throughout the test.

The invention discloses a three-foot portable multi-angle underwater adsorption anchoring drilling device. The drilling machine feeding component is installed on the drilling machine main body platform in a vertically movable mode, the three-foot supporting component is composed of a main foot and an auxiliary foot, the main foot and the auxiliary foot are installed on the drilling machine main body platform in an angle-adjustable mode, the main foot and the auxiliary foot are each provided with a micro-needle rotational flow suction cup, and after the micro-needle rotational flow suction cups suck the wall face of a to-be-drilled structure, the micro-needle rotational flow suction cups suck the wall face of the to-be-drilled structure. The drilling machine feeding component drills a to-be-drilled structure, the drilling machine feeding component achieves feeding and resetting of the drilling machine through positive and negative rotation of the motor so as to adjust the drilling operation depth, and the three-foot supporting component can change the feeding angle of a drill bit so as to meet the operation requirements of different drilling angles. The multi-angle drilling device can achieve multi-angle drilling operation in the repairing process of surface cracks of dams with different curvatures, meanwhile has the operation capacity in the complex water flow environment, can replace manual operation and improve the operation efficiency, and is easy to carry and store, wide in application range, safe and reliable.

The invention discloses intelligent low-clearance cast-in-place pile construction equipment, system and method. The construction site scanning and model building, paying-off and point position projection and correction, automatic construction path planning, drilling positioning, preparation work before drilling (burying of a soil layer structure integrity evaluation sensor), drilling construction and accurate control of perpendicularity and drilling depth, drilling lifting and in-hole environment detection are sequentially completed. And therefore, the intelligent construction operation of the cast-in-place pile is completed, the equipment has the construction characteristics of miniaturization and large drilling depth, and the intelligent construction operation under the low clearance working condition is perfectly achieved.

Apparatus and methods for monitoring emissions from a borehole to determine the composition of earthen material removed from the borehole are described. Monitoring can be done in real time as the borehole is being deepened with a millimeter-wave drilling beam. The present technology can monitor in real-time the elemental composition of the earthen materials (e.g., rock, minerals, crystals, metals, etc.) in a borehole created by a directed-energy beam that melts and vaporizes the earthen material materials in its path. Using a continuous emissions monitor (CEM) in combination with directed-energy excavation of a borehole enables rapid surveying of the subsurface for precious and commercial metals.

Methods and systems for geophysical exploration include accessing, from a data store, measured gravity values for a geographical area; modeling gravity values for the geographical area; determining gravity anomaly values based on the measured gravity values and the modeled gravity values; A gravity anomaly map of the geographical area is generated based on the determined gravity anomaly values and physical locations in the geographical area associated with the determined gravity anomaly values. A dip surface is generated representing inclinations of the geographical area based on the gravity anomaly map. A gravity dip map of the geographical area is generated by combining the dip surface with the gravity anomaly map, and a visual representation of the gravity dip map of the geographical area is displayed, on a display device, wherein colors of the visual representation represent the values of the gravity map.

The invention belongs to the technical field of oil and gas development, and particularly relates to an oil and gas well blocking remover and a preparation method thereof. The blocking remover comprises the following components: 5-8% of low-carbon composite organic acid, 5-7% of fluoboric acid, 6-9% of ammonium bifluoride, 4-6% of an anti-acid sludge mutual solvent, 2-4% of a corrosion inhibitor, 2-4% of polyoxypropylene polyoxyethylene propylene glycol ether, 8-12% of a permeation dispersion surfactant, 2-5% of a sulfur dissolving agent, 2-5% of a stable chlorine dioxide solution and the balance of water. The preparation method comprises the following steps: adding the low-carbon composite organic acid, the fluoboric acid and the ammonium bifluoride into water and stirring; adding an acid sludge resisting mutual solvent and a sulfur dissolving agent, and stirring; adding the corrosion inhibitor, the polyoxypropylene polyoxyethylene propylene glycol ether and the permeation dispersion surfactant, and stirring; and finally, reducing the stirring speed, adding the stable chlorine dioxide solution, and stirring to uniformly mix. The blocking remover provided by the invention is comprehensive in blocking removal function, very good in dissolving and dispersing performance on complex blocking substances, very small in corrosion damage to a shaft pipe wall and wide in applicability.

The invention discloses a method and device for recognizing the water outlet position and the water outlet mode of a horizontal well based on DTS temperature profile features. Comprising the following steps: acquiring distributed optical fiber temperature sensing (DTS) temperature profile data along a horizontal shaft; establishing a multiphase flow horizontal well temperature prediction composite model as a forward model; an inversion model is established, and stratum permeability distribution and an oil-water output profile are obtained; according to the well section with the water phase liquid production capacity exceeding a preset threshold value in the production profile, the water outlet position of the horizontal well is recognized; and determining the water outlet mode of the horizontal well by combining the analysis result of the multiphase flow horizontal well temperature prediction composite model on the temperature response in different water outlet modes according to the temperature change characteristics presented at the identified water outlet position by the DTS temperature profile. Compared with the prior art, the water outlet position can be more accurately recognized, the water outlet mode can be effectively distinguished, the monitoring cost is reduced, and powerful technical support is provided for water control and oil stabilization of the horizontal well.

The embodiment of the invention relates to the technical field of petroleum and natural gas engineering, in particular to a drifting drilling tool determining method, device and equipment, and the method comprises the steps that first drilling parameter data corresponding to a drifting drilling tool and second drilling parameter data corresponding to a borehole casing are obtained; calculating a first blocking risk factor of the drifting drilling tool according to the first drilling parameter data, wherein the first blocking risk factor is used for representing the blocking possibility of the drifting drilling tool; calculating a second blocking risk factor of the borehole casing according to the second drilling parameter data, wherein the second blocking risk factor is used for representing the blocking possibility of the borehole casing; calculating a first tripping-in capability index of the drifting drilling tool according to the rigidity of the drifting drilling tool and the first blocking risk factor; calculating a second tripping-in capability index of the borehole casing according to the rigidity of the borehole casing and the second blocking risk factor; and according to the first tripping-in capability index and the second tripping-in capability index, whether the drifting drilling tool is matched with the borehole casing is determined.