Halliburton Energy Services, Inc.

Aidan James Porter

Vitor Lopes Pereira

Robert Lynn Williams

Joshua Samuel Gollapalli

Dale E Jamison

Mateusz Michal Dyngosz

Lawrence Joseph Herskowitz

Charles Benjamin Broaddus

Determining the likelihood of an event occurring during a drilling operation can utilize various input parameters collected from one or more sensors located downhole or at a surface location of the borehole undergoing the drilling operation. The collected input parameters can be weighted according to user parameters and then calculated over time to determine a trend in the input parameters. The trend can be analyzed against one or more probability models, such as using a machine learning process, to determine a potential for the event to occur and an estimated time interval over which the event may occur. The results of this analysis can be used by users or drilling systems to implement corrective actions to reduce or avoid the potential for the event occurring.

Event detection using hydraulic simulations

A method for creating generated formatted data, that includes receiving, by a sequential data generator, raw data, where the raw data includes formation data at a drilling environment, processing the raw data to obtain generated recommendation data, where the generated recommendation data includes a proposed drilling location, and creating the generated formatted data, where the generated formatted data includes the generated recommendation data.

Service document generation using large language models

A method for detecting the occurrence of an event at a well comprising: recording a first set of measurements collected from the well; processing the recorded measurements to provide a first set of data; calculating a first score based on the first set of processed data; recording a second set of measurements collected from the well; processing the second set of recorded measurements to provide a second set of data; calculating a second score based on the second set of processed data; wherein the first set of processed data and the second set of processed data is the number median of absolute difference from normal; combining the first score and the second score using a weighted average; and comparing the combined scores to a predetermined rule based on a specified time frame; and allowing an operator to adjust parameters of the well operation based on the score comparison.

Method to detect real-time drilling events

A system usable in a wellbore can include a processing device and a memory device in which instructions executable by the processing device are stored for causing the processing device to: generate multiple predicted values of a first parameter associated with a well environment or a wellbore operation; determine a first trend indicated by the multiple predicted values; receive, from a sensor, multiple measured values of a second parameter associated with the well environment or the wellbore operation; determine a second trend indicated by the multiple measured values; determine a difference between the first trend and the second trend or a rate of change of the difference; and in response to the difference exceeding a threshold or the rate of change exceeding another threshold, determine a source of the difference including at least one of an erroneous user input, an equipment failure, a wellbore event, or a model error.

Determining sources of erroneous downhole predictions

A system for use in a wellbore can include a computing device that includes a processing device and a memory device that stores instructions executable by the processing device. The instructions can cause the processing device to generate a predicted value of a parameter associated with a well environment or with a wellbore operation. The instructions can also cause the processing device to receive sensor data that includes a measured value of the parameter; compare the predicted value to the measured value to determine a difference; and generate an interface for display that includes a data point associated with the difference plotted on a probability-mass distribution graph. The system can also include a sensor in electrical communication with the computing device and positionable proximate to the wellbore for generating the measured value of the parameter and transmitting the measured value of the parameter to the computing device.

Predicting wellbore operation parameters

A system for use in a wellbore can include a computing device including a processing device and a memory device that stores instructions executable by the processing device. The instructions can cause the processing device to generate a predicted value of a parameter associated with a well environment or a wellbore operation. The instructions can also cause the processing device to determine a tuning factor for adjusting the predicted value based on historical data. The instructions can also cause the processing device to apply the tuning factor to the predicted value to generate a tuned predicted value. The instructions can further cause the processing device to generate an interface for display that includes a data point associated with the tuned predicted value plotted on a graph.

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Lancashire, United Kingdom

Aidan James Porter