Application of a Forced Vibration Modeling Approach to Better Quantify the Role of Downhole Vibrations and Excitation Tools

Nguyen, Khac-Long; Mahjoub, Mohamed; Dao, Ngoc-Ha; Menand, Stéphane

doi:10.2118/208698-ms

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…These simulations were over a time span of 200 s, encompassing a total of 20 drilling cycles or periods, allowing for total exploration of the system's response to different operational conditions in a detailed and extensive manner. Utilizing the dynamics module of the WellScan simulator, the study implemented a comprehensive model of the drilling configuration [42][43][44].…”

Section: Resultsmentioning

confidence: 99%

Investigation and Analysis of Influential Parameters in Bottomhole Stick–Slip Calculation during Vertical Drilling Operations

Ejike,

Obuobi,

Avinu

et al. 2024

Energies

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The critical factors that affect bottomhole stick–slip vibrations during vertical drilling operations are thoroughly investigated and analyzed in this research. Influential factors, such as rotation speed, weight on bit (WOB), bottom hole assembly (BHA) configuration, and formation properties, were studied in order to understand their part in the stick–slip phenomena. The analysis is based on a thorough review of previous research conducted on stick–slip drilling vibrations. A mathematical model was created that not only explains axial vibrations but also includes the torsional vibrations present in stick–slip occurrences, which helps with understanding the stick–slip phenomena better. This model can be used as an analytical tool to predict and evaluate the behavior of drilling systems under various operational circumstances. Furthermore, two drilling tests using a WellScan simulator were performed to validate the research findings and assess mitigation techniques’ viability. These test scenarios reflect the stick–slip vibration-producing situations, allowing us to test mitigation strategies. The finding of this study shows the effectiveness of two tactics for reducing stick–slip vibrations. First was the reduction of WOB, which successfully lowered the occurrence of stick–slip vibrations. The second was the increase in the rotation speed, which helped to control the stick–slip problem and increased the drilling speed. This study explains the complex dynamics of stick–slip vibrations during vertical drilling and offers practical, tried-and-true methods for reducing their adverse effects on drilling operations.

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Section: Resultsmentioning

confidence: 99%

Investigation and Analysis of Influential Parameters in Bottomhole Stick–Slip Calculation during Vertical Drilling Operations

Ejike,

Obuobi,

Avinu

et al. 2024

Energies

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Demonstration of Autonomous Drilling on a Full-Scale Test Rig

Mihai

Cayeux

Daireaux

et al. 2022

Day 2 Tue, October 04, 2022

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During recent years there has been an increased focus on automating drilling operations and several solutions are in daily use. We describe here results and lessons learned from testing on a full-scale test rig, the next step in drilling automation, namely autonomous drilling. By autonomous drilling we mean a system capable of taking its own decisions by evaluating the current conditions and adapting to them while considering multiple horizon strategies to fulfill the drilling operation goal. Autonomous drilling was demonstrated during a series of experiments at a full-scale test rig in Norway. The focus of the experiments was to reach the target depth as quickly and as safely as possible. Since the formation at the test rig is very hard, a previously drilled well was filled with weak cement of variable strengths to allow for fast drilling. As part of the experiments, it was planned to have drilling incidents to test the system capabilities in managing arising issues and recover from them. During the experiments no real-time downhole measurements were available, only surface data. In total 500 meters have been drilled in autonomous mode. The autonomous system is built as a hierarchical control system containing layers of protection for the machines, well and the commands, in addition to recovery procedures, optimization of the rate of penetration and autonomous decision-making. The system continuously evaluates the current situation and by balancing estimated risks and performance, e.g. risk of pack-off versus prognosed time to reach the target depth, decides the best action to perform next. The autonomous decision-making system is tightly connected with the control of the drilling machines and therefore it executes the necessary commands to follow up the computed decision. Drilling incidents may occur at any time and an autonomous system needs to be able to adapt to the current situation, such that it can manage drilling incidents by itself and recover from them, when possible. During the experiments, several drilling incidents occurred, and the system reacted as expected. Surface data, together with internally computed data from the autonomous decision-making algorithms, were logged during the experiments. Memory-based downhole data was available after the experiments were concluded. Based on all the data collected, an analysis of the behavior of the system was performed after the experiments. During the drilling experiments at the full-scale rig, the autonomous system adapted its decisions to the surrounding environment and tackled both smooth drilling situations and drilling incidents. To cope with possible lower situational awareness, the autonomous system manages by itself transitions from autonomous to manual mode if necessary. This feature, together with fault detection and isolation capabilities, are crucial for safe operation of an autonomous system.

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Interoperability of Real-Time Drilling Signals at the Rig Site: An Example Based on Mechanical Specific Energy

Cayeux

Daireaux

Macpherson

et al. 2023

Day 2 Wed, March 08, 2023

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Digitalization of the drilling process has the potential to improve drilling data quality and consistency, providing support for drilling optimization, safety and efficiency. A significant barrier to realizing this potential is the data streams from the multitude of service companies, which changes almost daily, with variable definition of each of the real-time signals. This paper provides a solution to this problem: a method describing the semantics of real-time drilling signals in a computer readable format. For illustration, consider the calculation of mechanical specific energy (MSE) in drilling. It is possible to calculate a simple MSE signal in many ways, by using surface or downhole measurements, by applying corrections to the raw data, or by interpreting the equation in alternate ways. There is typically only a delivered value – the underlying details are lost. Semantic graphs bring transparency to the calculation by describing facts about drilling signals that are interpretable by computer systems. This semantic information encompasses details about signal measurement, and about signal calculation, correction, or conversion, yet all without exposing proprietary mathematical methods of calculation. It is possible, using semantic graphs, to assess the meaning and potential application of a signal, and whether or not the quality of the signal is suitable for its intended purpose. A semantic network relies on a vocabulary that defines a specific language dedicated to a particular topic, here drilling signals. The semantic network language is versatile: an existing language can describe new information and newly created signals. This provides a method meeting future needs without having to modify a standard constantly. In practice, each data provider exposes the meaning of its signals in the form of individual semantic networks. Merging these distinct semantic graphs provides a larger set of facts. This opens the possibility for synergies between independent data providers. For instance, applying logical rules infers new information. Since it is possible to query the semantic graph for signals that have certain properties, discovery of the most relevant signals at any time is feasible. By keeping track of modifications made to the semantic network during the drilling operation, it is also possible to post-analyze facts known about the available drilling signals, in an historic perspective. This is essential information for interpreting real-time data during offline data mining. This work is part of the D-WIS initiative (Drilling and Wells Interoperability Standards), a cross-industry workgroup providing solutions to facilitate interoperability of computer systems at the rig site and beyond. The D-WIS workgroup continues to develop the semantic vocabulary. The benefit of a computer interpretable description of the meaning of real-time signal is not limited to signals in real-time. Indeed, the method allows automatic data mining of historical data sets, facilitating the application of machine learning methods.

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Application of a Forced Vibration Modeling Approach to Better Quantify the Role of Downhole Vibrations and Excitation Tools

Cited by 5 publications

References 18 publications

Investigation and Analysis of Influential Parameters in Bottomhole Stick–Slip Calculation during Vertical Drilling Operations

Investigation and Analysis of Influential Parameters in Bottomhole Stick–Slip Calculation during Vertical Drilling Operations

Demonstration of Autonomous Drilling on a Full-Scale Test Rig

Interoperability of Real-Time Drilling Signals at the Rig Site: An Example Based on Mechanical Specific Energy

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