Abstract: This disclosure presents a fault prediction system using a deep learning neural network, such as a convolutional neural network. The fault prediction system utilizes as input seismic data, and then derives various seismic attributes from the seismic data. In various aspects, the seismic attributes can be normalized and have importance coefficients determined. A sub-set of seismic attributes can be selected to reduce computing resources and processing time. The deep learning neural network can utilize the seismic data and seismic attributes to determine parameterized results representing fault probabilities. The fault prediction system can utilize the fault probabilities to determine fault predictions which can be represented as a predicted new seismic data, such as using a three-dimensional image.

Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.

Abstract: A system for monitoring a pipe network for a fire protection system having an evaluation unit with a communication device, and at least one sensor which is arranged on or within at least one pipe of a plurality of pipes of the pipe network and is in communicative signal connection with the communication device. The at least one sensor is configured to collect measurement data indicative of changes in a hydraulic condition of the at least one pipe and to transmit this measurement data to the communication device of the evaluation unit. The evaluation unit is configured to evaluate the measurement data based on assigning the at least one pipe to the specific pipe category in order to generate an evaluation data record indicative of the hydraulic condition of the at least one pipe.

Abstract: A method for picking first breaks on a synthetic seismic dataset for a full wavefield travel-time inversion is provided. This method includes obtaining a synthetic seismic dataset and for each synthetic trace, determining a plurality of synthetic trace amplitude maxima and minima, determining a modified energy ratio trace, and forming a trace mask based at least in part, on an amplitude of the synthetic trace and on an amplitude of the modified energy ratio trace. The method further includes determining for each synthetic trace, a positive estimated first break based on the plurality of synthetic trace amplitude maxima and the trace mask and a negative estimated first bread based on the plurality of synthetic trace amplitude minima and the trace mask. The method concludes with determining a predicted first break for each synthetic trace from the positive estimate first break and the negative estimate first break.

Abstract: The systems, methods, and apparatuses described herein provide integrated weather forecast products designed to assist operations managers with operational decision-making related to a designated event or set of events. The present disclosure provides a way to process weather data from various sources and in diverse data formats containing varying spatial resolutions and temporal resolutions, in order to generate an integrated and cohesive weather projection product such that the weather projection product is continuous in both spatial and temporal domains, subject to data availability, relative to a designated event or set of events.

Abstract: A seismic observation device includes a data acquisition unit that acquires measurement data from each of a plurality of sensors that measure different types of state quantities related to movement of a ground, and an event determination unit that determines whether or not a predetermined event related to the movement of the ground has occurred on the basis of the measurement data from the plurality of sensors.

Abstract: A sonic tool is activated in a well having multiple casings and annuli surrounding the casing. Detected data is preprocessed using slowness time coherence (STC) processing to obtain STC data. The STC data is provided to a machine learning module which has been trained on labeled STC data. The machine learning module provides an answer product regarding the states of the borehole annuli which may be used to make decision regarding remedial action with respect to the borehole casings. The machine learning module may implement a convolutional neural network (CNN), a support vector machine (SVM), or an auto-encoder.

Abstract: Systems and methods of tracking attributes of objects, including a sensor configured to detect data related to one or more attributes of the object, a tracking device attachable to the object to transmit data detected by the sensor, a software application modifiable by a user, the software application being configured to receive transmitted data from the tracking device, firmware within a chip on the tracking device configured to determine a frequency of data transmissions from the tracking device to the software application based on transmission rules related to characteristics of transmitted data, and a display configured to show the frequency of data transmissions from the tracking device to the software application.

Abstract: An example method for monitoring operations of a business organization electronic computing device includes executing a checklist on a monitoring electronic computing device to obtain an operational status of an application being implemented on the business organization electronic computing device. Data is received from the business organization electronic computing device regarding the operational status of the application being implemented on the business organization electronic computing device. When a determination is made that the data identifies an operational threat for the business organization electronic computing device, an action is proposed or implemented to remediate the operational threat. An implementation of the checklist is adjusted based on an effectiveness of the action to remediate the operational threat.

Abstract: Data relating to an amount of contaminant in a fluid is obtained from a contaminant detection device. Aeration detection raw voltage data output and particle detection raw voltage data output from the contaminate detection device are received at an external data processing system separate and independent from the contaminate detection device. The aeration detection raw voltage data output and particle detection raw voltage data output are analyzed and cleaned to determine real time information on the amount of air bubbles and solid contaminate particles in the fluid, and then supplied to an onboard monitoring and controlling module of a machine for controlling one or more operations onboard the machine based on the determined amount of solid contaminate particles.

Abstract: A multi-scale unsupervised seismic velocity inversion method based on an autoencoder for observation data. Large-scale information is extracted by the autoencoder, which is used for guiding an inversion network to complete the recovery of different-scale features in a velocity model, thereby reducing the non-linearity degree of inversion. A trained encoder part is embedded into the network to complete the extraction of seismic observation data information at the front end, so it can better analyze the information contained in seismic data, the mapping relationship between the data and velocity model is established better, then the inversion method is unsupervised, and location codes are added to the observation data to assist the network in perceiving the layout form of an observation system, which facilitates practical engineering application. Thus a relatively accurate inversion result of the seismic velocity model when no real geological model serves as a network training label can be achieved.

Abstract: A method of predicting parameters of an earthquake uses an array of ionosondes to scan an observed volume of an ionosphere located above a seismically active zone. The method includes monitoring ionograms provided by the array of ionosondes; detecting the presence of at least one seismic-induced irregularity (SII); determining a first predicted parameter corresponding to an epicenter location; and determining one or more predicted parameters selected from a group consisting of a magnitude, a time of occurrence, and a hypocenter depth. Algorithms for calculating the predicted parameters are presented in detail.

Abstract: The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for analyzing filling for a karst reservoir based on spectrum decomposition and machine learning, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.

Abstract: A method of determining a shear-wave attenuated vertical component vertical seismic profile (VSP) dataset is disclosed. The method includes, obtaining a multi-component VSP dataset, including a vertical and a horizontal component, transforming the vertical component into a vertical spectrum and the horizontal component into a horizontal spectrum, and designing a band-pass filter based, at least in part, on an energetic signal of the horizontal spectrum. The method further includes determining a muted vertical amplitude spectrum by applying the pass-band filter to an amplitude spectrum of the vertical spectrum, determining an estimated noise model based on the muted vertical amplitude spectrum and the vertical spectrum; and determining the shear-wave attenuated vertical component VSP dataset by adaptively subtracting the estimated noise model from the vertical component of the multi-component VSP dataset.

Abstract: A vibratory meter (5, 1600) configured to predict and reduce noise in the vibratory meter (5, 1600). The vibratory meter (5, 1600) includes a sensor assembly (10, 1610) and a meter electronics (20, 1620) in communication with the sensor assembly (10, 1610). The meter electronics (20, 1620) is configured to provide a drive signal to a sensor assembly (10, 1610), receive a sensor signal from the sensor assembly (10, 1610) having one or more components, and generate a signal to be applied to one of the sensor signal and the drive signal to compensate for the one or more components.

Abstract: Methods for determination of mechanical properties of geological formations using deep learning include receiving, by a computer system, data acquired during drilling a geological formation. The computer system generates features of the data acquired during drilling. The features are indicative of mechanical properties of the geological formation. The computer system segments the features of the data acquired during drilling into sequences readable by a trained temporal convolutional network (TCN). The computer system determines the mechanical properties of the geological formation using the TCN based on the sequences obtained from the features of the data. A display device of the computer system generates a graphical representation of the mechanical properties of the geological formation.

Abstract: The present invention is a method or system for acceptance testing and commissioning of a LINAC and treatment planning system (TPS). For a LINAC commissioning, the present invention collects reference data from a fully calibrated LINAC and compares the reference data with machine performance data collected from LINAC. The compared results are analyzed to assess accuracy of the testing LINAC. For a TPS commissioning, the present invention collects standard reference data from standard treatment plans and standard input data and compares the standard reference data with results from standard tests that are performed by a testing treatment plan system. The compares results are analyzed to assess accuracy of the testing treatment plan system.

Abstract: A seismic observation device includes a data acquisition unit that acquires measurement data from each of a plurality of sensors that measure different types of state quantities related to movement of a ground, and an event determination unit that determines whether or not a predetermined event related to the movement of the ground has occurred on the basis of the measurement data from the plurality of sensors.

Abstract: Systems, computer readable, and methods concern receiving seismic data representing a subsurface volume. The method also includes determining, for the seismic data, analysis coordinates as a function of time. One or more of the analysis coordinates may vary in position over time. The method includes performing at least one of an interpolation or regularization process on the seismic data based at least partially on the analysis coordinates. The method also includes outputting a result of the at least one of the interpolation or regularization process.

Abstract: Various aspects described herein relate to a machine learning based detecting of fracture hits in offset monitoring wells when designing hydraulic fracturing processes for a particular well. In one example, a computer-implemented method includes receiving a set of features for a first well proximate to a second well, the second well undergoing a hydraulic fracturing process for extraction of natural resources from underground formations; inputting the set of features into a trained neural network; and providing, as output of the trained neural network, a probability of a fracture hit at a location associated with the set of features in the first well during a given completion stage of the hydraulic fracturing process in the second well.