Systems and methods include a computer-implemented method for performing well placement and configuration. Two-dimensional (2D) target entry (TE) points are generated in an area of interest (AOI) for wells to be drilled in an oil reservoir, where the 2D TE points are positioned according to a defined well length resolution. A single lateral is designed for each well using the 2D TE points, where each single lateral is designed with a different length, completion zone, azimuth, and orientation. Using the single laterals, a dynamic reservoir simulation is executed for the wells to be drilled in the oil reservoir, including rotating between different three-dimensional (3D) configurations for each 2D TE. A 3D configuration for each 2D TE is selected for each lateral and based on executing the dynamic reservoir simulation.

Embodiments provide techniques for using data from a select set of wells to develop correlations between surface-measured properties, downhole coring parameters, and properties typically determined from subsurface measurements (e.g., from logging tool responses, core analysis, or other subsurface measurements). When new wells are drilled, the surface data acquired while drilling and coring parameters used downhole may be used as an input to these correlations in order to predict properties associated with subsurface measurements.

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.

Systems and methods for estimating reservoir productivity as a function of position in a subsurface volume of interest are disclosed. Exemplary implementations may: obtain an initial depth uncertainty model; obtain training depth uncertainty parameter values from the non-transient storage medium; obtain corresponding training depth uncertainty values; generate a trained depth uncertainty model by training the initial depth uncertainty model using the training depth uncertainty parameter values and the corresponding training depth uncertainty values; and store the trained depth uncertainty model.

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.

A system and method for controlling a drilling tool inside a wellbore makes use of Bayesian optimization with range constraints. A computing device samples observed values for controllable drilling parameters such as weight-on-bit (WOB) and drill bit rotational speed in RPM and evaluates a selected drilling parameter such a rate-of-penetration (ROP) for the observed values using an objective function. Range constraints can be continuously learned by the computing device as the range constraints change. A Bayesian optimization, subject to the range constraints and the observed values, can produce an optimized value for the controllable drilling parameter to achieve a predicted value for the selected drilling parameter. The system can then control the drilling tool using the optimized value to achieve the predicted value for the selected drilling parameter.

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.

A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.