14 results about "Mud logging" patented technology

The application discloses a kind of paragenetic metamorphic rock weathering crust weathering alteration index calculation method, comprising: the mass percentage of element of mud logging cuttings is determined;The mass percentage of element is normalized;The mass percentage of element after normalization is converted into oxide molar ratio;According to the change trend of element oxide molar ratio, the relative loss and relative enrichment trend of various elements in paragenetic metamorphic rock weathering crust is judged;According to the trend of element relative loss or enrichment, the easily soluble element and the element easy to remain are determined, and the new paragenetic metamorphic rock weathering crust weathering alteration index calculation formula is fitted;The molar ratio of element oxide is brought into the new calculation formula established, according to the size of the weathering alteration index value calculated, paragenetic metamorphic rock weathering crust is identified, and paragenetic metamorphic rock weathering crust structure is divided.The application provides important technical support for oil and gas basin paragenetic metamorphic rock weathering crust reservoir research.

The application discloses a method for calculating a dynamic threshold value based on an MLP network to evaluate a risk of pipe sticking, and comprises the following steps: collecting real-time mud logging data on site; calculating a theoretical value of hook load and a theoretical value of torque by using a soft rod model; using an MLP neural network model to predict a dynamic threshold value of hook load and a dynamic threshold value of torque in combination with the mud logging data, the theoretical value of hook load and the theoretical value of torque; calculating a risk factor of pipe sticking; and monitoring a drilling state in real time, and issuing a warning in time according to the value of the risk factor to provide a scientific decision basis for an on-site operator. The application has the advantages of high calculation precision, strong adaptability and simple on-site operation, can self-adaptively identify the risk of pipe sticking, provides a scientific decision basis for the on-site operator, and effectively improves drilling efficiency and safety.

The application discloses a non-stirring type efficient degassing device, which comprises a spiral fluid collecting mechanism located at an upstream end of a process and used for continuously extracting drilling fluid; and an ultrasonic degasser located at a downstream of the process of the spiral fluid collecting mechanism and communicated with the spiral fluid collecting mechanism through a pipeline; a plurality of ultrasonic transducer oscillators are arranged in the ultrasonic degasser; the spiral fluid collecting mechanism extracts the drilling fluid and conveys the drilling fluid into the ultrasonic degasser through the pipeline; the ultrasonic degasser shakes the drilling fluid through vibration of the plurality of ultrasonic transducer oscillators to shake the drilling fluid to separate internal gas; the degassed drilling fluid is extracted into a chromatograph by a sample pump to be analyzed and detected. The device changes traditional stirring type degassing into non-stirring type degassing, realizes mud logging fluid degassing by using the ultrasonic degasser, achieves the design purpose of efficient degassing, and guarantees the real effectiveness of full hydrocarbon components of gas logging.

Embodiments of the invention relate to methods, systems, and software for identifying and quantifying subsurface hydrogen, helium, carbon dioxide, or other fluids using multiple indicia from geophysical well logs, other wireline logging tools, or mudlogging tools.

The application provides a kind of overflow risk key feature screening method based on data mining, relating to the technical field of oil drilling engineering, comprising: using weighted moving average filter to carry out noise reduction processing to mud logging sampling data, to obtain overflow data set;The correlation analysis is carried out to the overflow data set, to obtain multiple groups of high correlation variable set;For multiple groups of high correlation variable set, the overflow risk key feature screening is carried out through feature screening model, to obtain the overflow risk key feature set.The overflow risk key feature screening method provided by the application screens out important features, enhances data interpretability, thereby more deeply understands the correlation between each feature and overflow risk, improves the accuracy of overflow risk early warning model, and has important reference value for the diagnosis and early warning of overflow risk.

The utility model relates to a kind of mud logging sample detection and analysis integrated system, wherein integrated box interior is divided into sample preparation room and automatic analysis room by partition, partition one end is equipped with sample inlet bin, and sample inlet bin includes sample feeding part located in sample preparation room and sampling part located in automatic analysis room, sample tray loaded sample is first placed into sample feeding part, then is pushed into sampling part;Sample preparation room is equipped with sample preparation workbench, and sample preparation workbench is equipped with multiple sample preparation equipment;Automatic analysis room is equipped with equipment mounting seat and sampling mechanism, wherein equipment mounting seat is equipped with multiple analysis equipment, sampling mechanism is equipped with movable sampling base plate, and sampling base plate is equipped with sampling gripper, the sample tray in sample feeding part is sent into corresponding analysis equipment after being gripped by the sampling gripper.The utility model integrates sample preparation and each analysis procedure, and realizes automatic sample feeding analysis function, improves detection efficiency, and also reduces the exposure time of sample transfer.

The application discloses a kind of weathering alteration index calculation methods of orthometamorphic weathering crust, comprising: the mass percentage of element of mud logging cuttings is determined;The mass percentage of element is normalized;The mass percentage of element after normalization is converted into the mole ratio of oxide;According to the change trend of element oxide mole ratio, the relative loss and relative enrichment trend of various elements in orthometamorphic weathering crust are judged;According to the trend of element relative loss or enrichment, the easily soluble element and the element easy to remain are determined, and the calculation formula of new orthometamorphic weathering crust weathering alteration index is fitted;The mole ratio of element oxide is brought into the new calculation formula established, and according to the size of the weathering alteration index value calculated, orthometamorphic weathering crust is identified, and the structure of orthometamorphic weathering crust is divided.The present application provides important technical support for oil and gas basin orthometamorphic weathering crust reservoir research.

This invention relates to the field of oil and gas exploration and development technology, and is a method for oil-water identification based on radar model-based well logging nuclear magnetic resonance (NMR). It involves establishing radar charts corresponding to different fluid properties using five parameters: water affinity coefficient, oil affinity coefficient, and normalized original bound fluid signal, bound oil signal, and bound water signal. The radar chart of the original core sample whose fluid properties are to be identified is compared with the radar charts corresponding to the different fluid properties to determine the fluid properties of the original core sample. This invention combines the five parameters—water affinity coefficient, oil affinity coefficient, and normalized original bound fluid signal, bound oil signal, and bound water signal—to establish radar charts. By identifying the fluid properties of the formation through these radar charts, this method can effectively reflect the fluid property characteristics of the formation and provides important data support for subsequent well logging, oil testing, layer selection suggestions, and interpretation evaluation.

The present application relates to coal bed gas reserves prediction technical field, especially in kind based on while drilling data prediction coal bed gas reserves's method and device, the method, including real-time acquisition while drilling data with mud logging sensor, the effective gas volume that returns to wellhead in different time period is measured in real time through wellhead gas metering device, the effective gas is methane gas, the late time is calculated based on the physical property parameter of drilling fluid and effective gas, and the depth of well is returned to the position by using late time to while drilling data and effective gas volume;Based on the total hydrocarbon value measured in each period and effective gas volume, the coal bed gas volume corresponding to the period is calculated, the total volume of coal bed gas under the surface temperature and pressure condition is converted into the equivalent coal bed gas volume under the buried state of underground, the coal bed gas reserves contained in unit volume of coal rock is obtained, the present application can fully utilize the while drilling data obtained on site, realize the rapid and continuous prediction of coal bed gas content, and finally evaluate the coal bed gas reserves of the whole coal bed.

The application provides a water-bearing rock intelligent lithology identification method combining image recognition and spectrum analysis, comprising the following steps: 1, obtaining original drilling while cutting image and rock infrared spectrum data; 2, performing image pretreatment on the original cutting image; 3, performing cutting sample image feature extraction and normalization processing; 4, performing feature selection on the water-bearing rock spectrum data by using the Filter method and performing normalization processing; 5, based on a double migration feature fusion convolutional neural network, combining the cutting sample image feature and the rock spectrum data to construct a cutting feature analysis model; 6, combining the cutting feature and the rock spectrum data to establish a lithology template library; and 7, performing lithology identification. The application can more accurately identify the lithology in the process of mud logging, and improve the exploration and development efficiency of oil and gas resources.

The utility model relates to a kind of mud logging rock debris grinding cleaning mechanism, wherein outer mill disc assembly is located on the outside of grinding device, and outer mill disc assembly includes movable outer cover plate, outer cover plate is equipped with outer mill disc, driving mill disc is equipped on grinding device, when sample grinding, driving mill disc and outer mill disc close and form grinding space, outer cover plate is equipped with sample inlet component, and the sample inlet component is equipped with sample inlet and the grinding space intercommunication, lower hopper component is located below driving mill disc, and lower hopper outside in lower hopper component is equipped with movable dynamic outer peripheral plate driven by outer cover plate, lower hopper inside is equipped with lower discharging guide plate swinging driven by dynamic outer peripheral plate, cleaning component is located on the upside of grinding device and is equipped with liftable cleaning brush, when cleaning, outer mill disc and driving mill disc open, and cleaning brush is lowered into between outer mill disc and driving mill disc. The utility model can realize the automatic grinding operation of rock debris sample and the automatic cleaning operation of driving mill disc and outer mill disc.

The application relates to the field of correction technology, and discloses a Koala correction device and method for the output of a thermal resistance temperature sensor of a comprehensive mud logging instrument, which comprises a data acquisition module, a temperature gradient calculation module, a bias gradient calculation module, a bias value derivation module and a correction value calculation module; and further comprises a thermal resistance temperature sensor and an auxiliary temperature sensor.The temperature gradient calculation module calculates a temperature gradient according to the temperature data measured by the auxiliary temperature sensor, and calculates an average temperature according to the temperature gradient.The bias gradient calculation module calculates a bias value gradient according to the temperature gradient, the average temperature and a temporary bias value of the thermal resistance temperature sensor.The correction value calculation module calculates the bias value of the thermal resistance temperature sensor according to the bias value gradient and the temperature gradient, and further corrects the output temperature of the thermal resistance temperature sensor of the comprehensive mud logging instrument.

The application provides a tidal flat facies dolostone reservoir logging while drilling evaluation method, the method comprises the following steps: determining the marker layer on the upper part of the high-quality reservoir by using Ca, Mg and other elements according to element logging analysis, qualitatively identifying the reservoir by engineering logging parameters, obtaining the dissolution pore characteristics by scanning the rock debris backscattering imaging, calculating the elastic modulus of the rock by elements, finally forming the tidal flat facies dolostone logging while drilling evaluation method, which can provide the basis for trajectory optimization in the drilling construction process of the tidal flat facies dolostone formation, guide the drilling construction and improve the drilling rate of the high-quality reservoir.