Abstract: A method includes acquiring data associated with a field operation of equipment in a geologic environment; filtering the data using a filter where the filter includes, along a dimension, a single maximum positive value that decreases to a single minimum negative value that increases to approximately zero; and, based on the filtering, issuing a control signal to the equipment in the geologic environment.

Abstract: A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing, in potentially real time, anomaly pattern detection to optimize operational processes relating to well construction or subterranean drilling. For example, the disclosed systems use time-series data combined with rig states to automatically detect and split similar operations. Subsequently, the disclosed systems identify operation anomalies from a field-data collection utilizing an automated anomaly detection workflow. The automated anomaly detection workflow can identify operation anomalies at a more granular level by determining which process behavior contributes to the operation anomaly (e.g., according to corresponding process probabilities for a given operation). In addition, the disclosed systems can present graphical representations of operation anomalies, process behaviors (procedural curves), and/or corresponding process probabilities in an intuitive, user-friendly manner.

Abstract: A method for drilling a well includes generating a plurality of proposed drilling actions using a plurality of working agents based on a working environment, simulating drilling responses to the proposed drilling actions using a plurality of validation agents in a validation environment that initially represents the working environment, determining rewards for the proposed drilling actions based on the simulating, using the validation agents, selecting one of the proposed drilling actions, and causing a drilling rig to execute the selected one of the proposed actions.

Abstract: A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock

Abstract: Methods, computing systems, and computer-readable media for interpreting drilling dynamics data are described herein. The method can include receiving drilling dynamics data simulated by a processor or collected by a sensor positioned in a drilling tool. The method can further include extracting a feature map from the drilling dynamics data, and determining that a feature zone from the feature map corresponds to a predetermined dynamic state. The feature zone can be determined using a neural network trained to associate feature zones with dynamic states. Additionally, the method can include selecting a drilling parameter for a drill string based on the feature zone.

Abstract: A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.

Abstract: A method can include receiving sensor data during drilling of a portion of a borehole in a geologic environment; determining a drilling mode from a plurality of drilling modes using a trained neural network and at least a portion of the sensor data; and issuing a control instruction for drilling an additional portion of the borehole using the determined drilling mode.

Abstract: A method includes acquiring data associated with a field operation of equipment in a geologic environment; filtering the data using a filter where the filter includes, along a dimension, a single maximum positive value that decreases to a single minimum negative value that increases to approximately zero; and, based on the filtering, issuing a control signal to the equipment in the geologic environment.

Abstract: A method can include receiving channels of data from equipment responsive to operation of the equipment in an environment where the equipment and environment form a dynamic system; defining a particle filter that localizes a time window with respect to the channels of data; applying the particle filter at least in part by weighting particles of the particle filter using the channels of data, where each of the particles represents a corresponding time window; and selecting one of the particles according to its weight as being the time window of an operational state of the dynamic system.

Abstract: A method can include receiving multi-channel time series data of drilling operations; training a deep neural network (DNN) using the multi-channel time series data to generate a trained deep neural network as part of a computational simulator where the deep neural network includes at least one recurrent unit; simulating a drilling operation using the computational simulator to generate a simulation result; and rendering the simulation result to a display.

Abstract: A symmetry attribute is described that may be used for determining seismic stratigraphic features in a formation. In one example, seismic input data from a formation is processed to determine an attribute by selecting a center trace, assigning a first cluster of the traces to a left image and a second cluster of the traces to a right image, and determining symmetry about the center trace between the left and the right images.

Abstract: Picking a fault in seismic data samples is described. In one example, a minimum spanning tree is used. In another example, input seismic attribute data is determined based on the seismic data samples. Seeds are selected that represent locations in the seismic volume using the attribute data. A principle grid is generated using the seeds. A fault is picked in the seismic volume by applying a least costs process, for example a minimum spanning tree, to the principle grid. The fault is then interpolated to generate a fault surface of the seismic volume.

Abstract: Seismic stratigraphic features may be enhanced using orientation vectors. In one example, a process includes converting a seismic attribute section from a spatial domain to a spatial-frequency domain using a Fourier transform. For each filter in an orientation filter array, the seismic attribute section is convolved with a filter in the spatial-frequency domain. The convolution result is converted back to the spatial domain by inverse Fourier transform. For each point in the seismic section an orientation filter having a response with a maximum energy is found and the orientation is associated with the corresponding energy and the corresponding point.

Abstract: A method is disclosed for automatically extending interpreter horizon picks over a wider area of traces in such manner that the automatically generated picks are very similar to picks that an interpreter would pick manually. The method applies optical filters to seismic sections to determine the intrinsic orientation of seismic events. Seismic orientation is captured in the Orientation Vector Field, which is then used to guide the picking process.

Abstract: The invention relates generally to the field of oil and gas exploration and specifically to the use of well logs for exploration. This invention is directed to a method for estimating data that would have been collected in a region of a well log where there is a gap. This method uses identified elements in one data set to identify elements in another data set with data values indicative of the same geological characteristic as those in the first data set.

Abstract: The invention relates generally to the field of oil and gas exploration and specifically to the use of well logs for exploration. This invention is directed to a method for estimating data that would have been collected in a region of a well log where there is a gap. This method uses identified elements in one data set to identify elements in another data set with data values indicative of the same geological characteristic as those in the first data set.