Systems and methods for developing hydrocarbon reservoirs based on constrained natural fracture parameters. A natural fracture modeling is generated for a reservoir, an initial set of fracture model parameters is determined, and a fracture model optimization is conducted to determine an optimized set of fracture model parameters. The optimized set of fracture model parameters are used as a basis for modeling the reservoir, and the modeling is used to generate a simulation of the reservoir.

A monitoring system includes a flow line, an optical fiber coupled to the flow line, and a receiver coupled to an end of the optical fiber. The receiver is configured to detect at least one acoustic signal from the optical fiber. In addition, the monitoring system includes processor unit to detect a flow obstruction within the flow line based on the acoustic signal.

A sensor node system for mapping hydraulic fractures may include a localization system that identifies location information of the sensor node device with respect to an area of interest in a rock formation. The location information may include various magnetization parameters indicative of various signal strengths surrounding the sensor node device. The sensor node device may include a transceiver that exchanges signals with a base station and at least one other sensor node device. The transceiver establishes a communication link between the base station and the sensor node device. The transceiver may monitor at least one other communication link between the at least one other sensor node device and the base station. The sensor node device may include a processor that identifies distance information based on the location information and a predetermined number of signals associated to the various signal strengths surrounding the sensor node device.

A method of predicting hydrocarbon production from one or more artificial lift wells is disclosed. Test data is obtained from the artificial lift well. A decline curve model, representing well performance, is generated for one or more fluids in the artificial lift well. Measurement values are obtained from an artificial lift operation. For each of the obtained measurement values, a measurement model is generated that correlates the measurement values to the decline curve. A Kalman filter is used to predict production outputs of at least one of oil, gas, and water for the well, and to generate an uncertainty range for the predicted production outputs. The Kalman filter uses the decline curves to predict the production outputs, and uses the measurement models to correct and/or update the predicted production outputs. Hydrocarbon production activities are modified using the corrected and/or updated predicted production outputs.

A downhole tool movement control system and method of use, such as a movement control system to control the speed of a plunger tool when operating within a tubing string of a wellbore, such as when rising within a tubing string of a wellbore. In one embodiment, the downhole tool movement control system includes a system controller operating to control a system valve to regulate the plunger tool speed, the system controller settings based on a set of system parameters.

A method for training a predictive reservoir simulation in which high-confidence reservoir sample data is used to identify misallocated historical production data used in the simulation. A neural network algorithm is trained with high-confidence reservoir historical production data. High-confidence reservoir sample data is obtained by at least one sensor at a reservoir location over a time interval, after which the reservoir historical production data is parametrically varied over the time interval to determine a time-indexed discrepancy between the reservoir historical production data and the high-confidence reservoir sample data over the time interval. The time-indexed discrepancy and a defined threshold discrepancy are then used as inputs to a machine learning process to further train the neural network algorithm to identify reservoir historical production data whose discrepancy exceeds the threshold discrepancy and thereby constitutes misallocated historical production data. The misallocated data is later back allocated to respective wells by back propagation algorithm.

The disclosure provides a solution for monitoring stick-slip vibrations without using any surface torque measurements. Instead, the disclosure provides a method to monitor stick-slip vibrations based on rotational speed. A stick-slip monitor, a top drive controller and a method of operating a drill string are provided herein that use rotational speed for monitoring stick-slip vibrations. In one example, the method of operating a drill string includes: (1) performing a frequency domain analysis of an RPM signal associated with a top drive that is used to rotate a drill string, and (2) determining a presence of torsional oscillations of the drill string based on the frequency domain analysis of the RPM signal.

A method may include obtaining power production and fuel consumption data of a first piece of rig equipment through a flow meter, where the rig equipment includes a plurality of pieces of equipment. The method further includes feeding the power production and fuel consumption data of the first piece of rig equipment into a real-time monitoring system of the rig via the flow meter. The method further includes determining an energy efficiency, based on real-time performance, of the first piece of rig equipment using a consumption efficiency model. The method further includes comparing the energy efficiency of the first piece of rig equipment against continuously updated historical data of the first piece of rig equipment by a real-time database monitoring system. The method further includes identifying deficiencies of the first piece of rig equipment in real-time and determining maintenance or replacement of the first piece of rig equipment.

Disclosed are methods, systems, and computer-readable medium to perform operations including: generating, using a source wavelet and a current velocity model, modeled seismic data of the subterranean formation; applying a pre-condition to a seismic data residual calculated using the modeled seismic data and acquired seismic data from the subterranean formation; generating a velocity update using the source wavelet and the pre-conditioned seismic data residual; updating, using the velocity update, the current velocity model to generate an updated velocity model; determining that the current velocity model satisfies a predetermined condition; and responsively determining that the updated velocity model is the velocity model of the subterranean formation.

A method may include calculating a first set of hash values for a set of well log channels, extracting a well log channel snippet from an unknown well log channel, calculating a second set of hash values for the well log channel snippet, identifying, for the unknown well log channel, a matching well log channel by searching the first set of hash values with the second set of hash values, and storing, for the unknown well log channel, a channel context corresponding to the matching well log channel.