Drilling Control System Research Articles

Design and dynamic analysis of the scissor deployable mechanism used in the drill for replicating ice cores from the borehole wall

The deep ice cores preserved within the polar ice sheets hold a wealth of valuable information, and the demand for ice cores in related scientific research is on the rise. Thus, the replication of ice cores from the borehole wall holds significant importance. However, current methods face limitations such as difficulties in whipstock retrieval, extended auxiliary working hours, structural complexity, and the necessity of ice core depth calibration. To address this, this study proposes a novel method for replicating ice cores from the borehole wall utilizing a thermal coring drill bit. The design and dynamic analysis of the scissor deployable mechanism employed to drive the drill bit movement were thoroughly examined through theoretical and simulation studies. The motion characteristics of the drill bit during the replication coring process and the stress–strain behavior of the scissor rods were determined and validated through drill bit movement experiments, demonstrating a maximum error of 10%. The findings reveal that the mechanism can meet the strength requirements across three operating stages: horizontal drilling, vertical coring, and ice core recovery, with maximum loads of approximately 284 N, 749 N, and 970 N, respectively. Increasing the thickness of the scissor rods and reducing their length can augment the load-bearing capacity of the structure. Additionally, the speed transmission characteristics derived from the scissor mechanism can offer theoretical support for the drill's control system.

Advancing real-time drilling trajectory prediction with an efficient nonlinear DDE model and online parameter estimation

This study introduces a streamlined approach to predict planar drilling trajectory by employing an efficient nonlinear Delay Differential Equation (DDE) model with high computational speed and predictive accuracy. The efficient model is validated and compared with other models by utilizing not just data from existing literature but also two sets of experimental data with two distinct rigs. Following the validation, the model is integrated with an online estimation technique—calibrating one parameter in real-time using historical data—empowering it to forecast drill bit paths with remarkable fidelity. The validation of the model and its estimation strategy underscores their potential for application in real-time drilling control systems, setting a new benchmark for future advancements in the field.

Statistics Pattern Cointegration Analysis-Based Bit Bounce Detection for Drilling Process

Fault detection is essential for the safety of drilling process. Without proper detection and appropriate treatment of bit bounce, it may result in serious drilling accidents. The data distribution shift will lead to the nonstationary property. Yet the statistics of drilling parameters may have similar equilibrium relationships across different depths due to the existence of automatic drilling control system. To solve the issue of distribution shift, a statistics pattern cointegration analysis based bit bounce detection method for drilling process is proposed. The statistics pattern of drilling parameters is constructed. The cointegration analysis is conducted to discover equilibrium relationships among nonstationary statistics for process monitoring. The corresponding alarm deadband is designed through the analysis of alarm duration and alarm deviation. An industrial case study from an actual drilling process is conducted to demonstrate the effectiveness of the proposed fault detection method. The proposed statistics pattern cointegration analysis approach is conducive to maintaining a satisfactory fault detection performance in the case of distribution shift in the industrial process.

시추장비 통합운용제어시스템 및 HILS 개발

시추장비 통합운용제어시스템 및 HILS 개발

Intelligent Risk-Based Cybersecurity Protection for Industrial Systems Control—A Feasibility Study

Summary Intelligent automated industrial process control, enabled by IR 4.0 technology, requires increased system integration and connectedness. With such development comes a heightened risk of cyberattack for operational technology (OT) systems, including industrial control systems (ICS) and industrial automation and control systems (IACS), historically shielded from cyberspace. Cyberattacks on OT systems can also impact the physical world. The recent attack on the US Colonial Pipeline interrupted delivery of oil along the US West coast for several days, resulting in a declaration of a state of emergency, while the Ukraine power grid attacks interrupted electrical power supply in Kyiv, impacting thousands of consumers. In 2021, an Equinor-operated platform on the Norwegian Continental shelf was hit by malware. The incident had the potential to affect the drilling control system (DCS). For ICS, the concern is ensuring a safe process, as opposed to the more traditional concern with data protection for information technology (IT) system management. To ensure safe implementation of advanced industrial systems control, while avoiding unnecessary operational downtime, there is a need for cybersecurity solutions that account for risk for the whole cyberphysical system (CPS), including the ICS, the work environment, the product, and the physical surroundings. Diagnostic models and methods must therefore be developed that cover the functionality of the whole CPS. Further, to account for process dynamics and evolving cyberattack threats, adaptability is required with respect to both process state and new types of attacks. For this purpose, knowledge-based awareness monitoring combined with existing cyberattack detection tools for ICS, known as ICS intrusion detection systems (IDS), is proposed, providing an element of artificial intelligence. Results from studies in a DCS environment indicate that existing monitoring applications can be used to detect and discern between different types of cyberattacks on CPSs. This indicates feasibility with respect to monitoring the control and IT components of the ICS system for building risk-based cybersecurity decision support solutions. The key challenge and novelty of the proposed approach is to extend the capability of cybermonitoring in systems control to automated evaluation of process risk, including risk to the physical environment. Such capability will enable appropriate decision support with respect to both process risk and operational downtime.

A complex model of a drilling rig rotor with adjustable electric drive

A modified mathematical model of an asynchronous electric drive of the rotor – a drill string – a bit – a rock is considered and implemented, which develops and generalizes the results of previously performed studies. The model includes the following subsystems: a model of an asynchronous drive with vector control; a model of formation of the resistance moment at the bottom of the bit, taking into account the peculiarities of the interaction between the bit and the rock; a model of a multi-mass mechanical part that takes into account the deformation of the drill string; subsystem for the drilling rig energy-technological parameters formation. The integrated model makes it possible to calculate and evaluate the selected drilling modes, taking into account their electro-mechanical, energy and technological efficiency and the dynamics of drilling processes. The performed computer simulation of drilling modes confirmed the possibility of a stick-slip effect accompanied by high-frequency vibrations during bit stops, which may change the direction of rotation of the bit, its accelerated wear and unscrewing of the drilling tool. Long bit stops lead to a significant decrease in the average bit rotation speed, which can explain the decrease in the ROP and increase in energy consumption when drilling in the zone of unstable bit rotation. The model can be used as a base for further improvement of rotary drilling control systems.

РАЗРАБОТКА СИСТЕМЫ УПРАВЛЕНИЯ ПОГРУЖНОГО ВЕНТИЛЬНОГО ЭЛЕКТРОПРИВОДА ЭЛЕКТРОБУРА

Due to the active development of the oil and gas service, the construction of oil and gas wells is becoming increasingly important for the economy of Russia. This work is aimed at developing a mathematical description and model of the control system of the valve electric drive of an electric drill, as well as analyzing the transient processes of the obtained system. The work presents a mathematical description of the dynamic modes of operation of the electric drive system with a synchronous machine with permanent magnets, and a structural diagram is built. Using the Matlab Simulink environment, a model of the system was built. Graphs of transient processes during start-up and load changes were obtained, based on which conclusions were drawn about the operation of the electric drill control system. It was found that the control system is capable of adapting and maintaining the speed at a given level when the load on the shaft and the control signal change.

Technology Focus: Offshore Drilling and Completion (October 2022)

Big data, in its many forms, has promised much to the oil and gas industry but mostly is perceived to have been slow to deliver. This is not at all surprising. We must walk before we can run, and, as experience has grown with the nuances and successful and unsuccessful avenues of investigation, the industry has continued to move forward. As the saying goes, “Data is like people: Interrogate it hard enough and it will tell you whatever you want to hear.” From early and almost naïve beginnings, where systems would confidently predict that Friday followed Thursday, we entered a phase where data mining began to provide insight. Often these insights confirmed long-established relationships; for example, in hydraulic fracturing, more than once I have seen heavily marketed research and development that professes to predict the onset of screenout conditions only to see that the system has effectively “seen” a Nolte-Smith relationship. These, however, are mere stumbles of any system picking itself up and beginning to move, and should be expected. What we have seen are continued areas of application opening up, where approaches deliver real efficiency gains and highlight further opportunities. The papers that I included this month fall into these categories, demonstrating real measurable efficiency gains and advantages, often processing volumes of data that previously could not be managed by conventional means. Performance measurement and drilling automation are two such examples, and the papers referenced this month, both as synopses and listed for further reading, fall into this category. Not surprisingly, as we apply data science to broader problem sets across the industry, we will see continued development and demonstrated success. Sharing these successes will ensure that this momentum is sustained and that advances continue. Recommended additional reading at OnePetro: www.onepetro.org. IPTC 21419 - Delivering More Fit-for-Purpose Wells With Low-Cost Approach at Untapped Area Matured Field—Application of Cone Concept Statistical Approach by M. Hatta M. Yusof, Petronas, et al. IPTC 21490 - Pore-Pressure Estimation by Using Machine-Learning Model by Pichita Booncharoen, Chevron, et al. SPE 209712 - Drilling Control System Automation To Control Axial Velocity Optimizes Tripping and Drilling Performance by Robert Bacon, Sekal, et al.

Automatic Measurement of the Dependence on Pressure and Temperature of the Mass Density of Drilling Fluids

Summary Drilling fluids are subject to substantial variations in pressure and temperature while they are circulated in a well. These changes are so great that the mass density of the drilling fluid varies significantly during circulation. Accurate estimation of the hydrostatic and hydrodynamic pressures therefore requires a reliable model of the pressure and temperature dependence of the mass density of the drilling fluid. Usually, the mass density of a drilling fluid is measured manually with a mud balance. The pressure and temperature dependence of the mass density of the fluid [i.e., its pressure, volume, and temperature (PVT) behavior] is then calculated from a PVT model of its components and their relative proportions. However, variations in the composition of the fluid mix and uncertainties in the PVT behavior of each component may lead to inaccuracies. To overcome these limitations, an apparatus has been designed to measure the PVT behavior of the drilling fluid directly and automatically. The setup measures both the mass density and the speed of sound of the fluid at specific conditions of pressure and temperature. It is possible to estimate the adiabatic compressibility from the speed of sound in the liquid mix. The device utilizes a heat exchanger from which the specific heat capacity of the drilling fluid can be derived. The isothermal compressibility can be calculated by combining the specific heat capacity and the adiabatic compressibility. While estimating the specific heat capacity using the heat exchanger, the thermal conductivity of the fluid is also estimated as a byproduct. A PVT model of the drilling fluid is obtained by combining measurements made at different conditions of pressure and temperature. The automatic and continuous provision of drilling fluid PVT behavior enhances the precision of model predictive drilling control systems and, at the same time, can simplify their configuration, therefore making them more accessible to any drilling operation.

A retrofitting control system design suitable for deep borehole drilling using legacy draw-works mechanical brake hardware

Deep drilling operations are typically needed when producing deep wells for hydrocarbon exploitation or geothermal energy applications. Since a notable portion of existing deep drilling rigs are still fielding manually operated draw-works (hoist) drum mechanical brake actuators, their usage puts notable constraints on the quality of borehole production and corresponding production rates. By retrofitting such mature drilling rigs with a suitable brake actuator servo mechanism, completely automatic drilling operation can be facilitated, thus also achieving borehole production efficiency improvements and meeting the increasingly stringent requirements on drilling control system performance. To this end, this paper presents the development of an automatic drilling control system based on an electrical servoactuator of the draw-works mechanical brake, with the control system arranged in the so-called cascade control system structure, and an automatic tuning procedure having been devised as well. Its robustness has been tested by means of root locus plots and simulation analysis of dominant closed-loop dynamics effects. The proposed control system has been verified by means of simulations first, which has been followed by a thorough experimental verification on an actual deep drilling rig retrofitted with electrical servodrive based-actuator of the winch drum mechanical brake. Field results have indicated that the proposed control system can maintain the drill-bit normal force within ± 10% of the target value during normal operation, with penetration rate variations typically being two to three times smaller compared to the case of human operator controlling the drilling process.

E&P Notes (May 2021)

E&P Notes (May 2021)

Development of a roof bolter drilling control process to reduce the generation of respirable dust

The drilling operation in the roof bolting process, especially in hard rock, generates excessive respirable coal and quartz dusts, which could expose the roof bolting operator to continued health risks. Previous research has shown that the amount of respirable dust produced is dependent on the main drilling parameters, specifically the drilling rotational and penetration rate. In this paper, a roof bolter drilling control process was proposed to reduce the generation of respirable dust. Based on the analysis of laboratory drilling test results, a rational drilling control process (adjusting rotational and penetration rates) to achieve the optimal drilling parameter for different rock types was proposed. In this process, the ratio between specific energy and rock uniaxial compressive strength was used as the index to determine the optimal operation point. The recommended drilling operation range for the rock type used in the experiment was provided, and the reduction in respirable dust generation was demonstrated. By following this control process, the drilling efficiency can be monitored in real time, so the system can stay in a relatively high-energy efficiency with less respirable dust production from the drilling source. This algorithm is targeted to be incorporated into the current roof bolter drilling control system for drilling automation so that a safe and productive drilling operation can be conducted in a healthy working environment.

Mathematical Model of Wood Drilling Taking into Account the Mutual Infl uence of Electric Motors of Feed and Cutting

The Russian economy currently needs new approaches to solving old problems, that is, such methods that would increase the efficiency of production. In the case of woodworking, we can talk about the introduction of new management principles that ensure a higher quality of processing, even on old woodworking machines and centers. The implementation of such methods is impossible without the development of modern mathematical models of the cutting process, including wood drilling. (Research purpose) The research purpose is in constructing of a mathematical model that reflects the dynamics of wood processing by drilling, which is interconnected through the cutting process. (Materials and methods) Authors used mathematical and numerical modeling with extensive use of mathematical software packages, such as the MatLab mathematical modeling environment. (Results and discussion) The article presents the graphs of the drilling process state in the form of numerical simulation results carried out in the Matlab environment. (Conclusions) The article presents the developed model of the dynamics of the cutting system in two versions. The first version takes into account only the moments and forces associated with the formation of the cutting force in the processing zone. The second model includes an additional moment of resistance associated with the accumulation of chips in the chip-removing channels of the drill. This process has a significant impact on the stability of drilling, with the accumulation of chips in excess of a certain value, the system loses stability and there are raise the possibility of failure of both the drill and the entire spindle assembly. The developed mathematical model of the drilling control system, represented by the system of equations, adequately describes the process of wood processing by drilling on woodworking equipment.

Cranial Perforation Using an Optically-Enhanced Surgical Drill.

The design of mechanically clutched cranial perforators, used in craniotomy procedures, limits their performance under certain clinical conditions and can, in some cases, impose the risk of severe brain injury on patients undergoing the procedure. An additional safety mechanism could help in mitigating these risks. In this work, we examine the use of diffuse reflectance spectroscopy as a potential fallback mechanism for near real-time detection of the bone-brain boundary. Monte Carlo simulation of a two layer model with optical properties of bone and brain at 530 and 850nm resulted in a detectable change in diffuse reflectance signal when approaching the boundary. The simulated results were used to guide the development of an experimental drill control system, which was tested on 10 sheep craniums and yielded 88.1 % success rate in the detection of the approaching bone-brain boundary.

Cybersecurity: Preventing Infection in a Body of Data

Fool me once, shame on you; fool me twice, shame on me. That’s an adage that often alerts us to the dangers of knowing - and yet not mitigating - the repercussions of risk. And with the resurgence of cyberattacks globally, it’s also a wakeup call to cyber readiness. The oil and gas industry faces particular risk - though it’s not necessarily ready (Fig 1). Sixty-one percent of oil and gas professionals who are responsible for cyber risk said their organization fell short last year in protecting and securing its industrial control systems (ICS). Sixty-eight percent surveyed said their organization had experienced at least one cyber compromise in the past year, resulting in OT disruption or the loss of confidential information (Ponemon 2017). And perhaps most alarming: They did not have a clear strategy to address it. This is an industry where the opportunities for infiltration are nearly limitless. A typical large oil and gas company uses half a million processors just for reservoir simulation; it generates, transmits, and stores petabytes (each equal to 1,015 bytes) of sensitive field data; and it operates thousands of drilling and production control systems in diverse locations, with numerous fields, vendors, service providers, and partners (Mittal et al. 2015). ICS are used to control assets spanning thousands of square miles - such as the 2.6 million miles of oil and gas pipeline in the US alone (PHMSA). ICS may be as simple as a few panel-mounted controllers or as complex as interconnected and interactive distributed control systems with thousands of field connections. At the same time, cloud-based internet of things (IoT) technology, wireless communications networks, and analytical and automated tools are connecting operations in real time, with new data-based links between rigs, refineries, and headquarters. And as these connections multiply exponentially, the exposure - and thus the threats - increase. “The industry is increasingly becoming a target, with attacks growing in frequency, sophistication, and impact. Data is becoming more valuable, perhaps the most valuable commodity in the world right now, and oil and gas companies are oozing with data,” Ben Dickinson, global cybersecurity lead for ABB’s oil, gas, and chemicals unit, said at the 2019 SPE Offshore Europe conference.

Technology Focus: Drilling Systems Automation and Management (February 2020)

Technology Focus Drilling systems automation (DSA) is moving into commercial activities on a broad front. Equipment suppliers are delivering automated drilling-control systems, and everyone (equipment suppliers, service companies, drilling contractors, operators) is delivering systems-automation applications. These players are cooperating to deliver the degree of interoperability needed to make DSA function in this multicompany environment. Among this year’s chosen papers, the authors of paper SPE 194110 address interoperability of drilling sensor networks and describe a semantic system that allows a third-party application to discover types and classes of rig sensors and tailor them to the need of the application. The initial portion of the complete paper is an extremely read-able peeling of the layers of symptoms around a diagnosis. The layers peel with each discovered sensor, until the final step indicates why low-latency data delivers robust systems diagnosis (and hence automation). We are seeing commercial automation systems deployed in three modes: shadow mode, advisory mode, and closed-loop mode. In shadow mode, the systems run in parallel with drilling operations but do not interface with operational controls or people. This mode generally generates confidence in functionality and reliability. In advisory mode, the systems deliver advice in real time to users at the rig site or in remote centers and users may take that advice in con-trolling equipment or processes. Finally, in closed-loop mode, the systems control hardware directly and the user (typically the driller) has acceptance and override authority. Several of the papers presented this year deal with systems operating in the advisory mode. Automation also involves organizational change, and managing that change is a challenge. Paper SPE 194184 is a case history on successfully managing change when introducing an advisory sys-tem onshore. It explains, using some memorable written images, why the introduction of automation components needs careful training and human involvement. Another advisory system is the subject of paper IPTC 19269. This is a well-written account, led by an operator, on the development of a hybrid physics-based and data-driven model for drilling optimization. It is a case study into the development of advisory systems and their deployment in front of the drilling crew. The suggested additional-reading papers provide additional insight into developing topics: an operator’s DSA roadmap and experiences thus far, a call for open-source models and data, and the use of a digital twin of the drilling process. Recommended additional reading at OnePetro: www.onepetro.org. SPE 195818 What Drilling Automation Can Teach Us About Drilling Wells by Matthew Ray Isbell, Hess, et al. SPE/IADC 194082 Creating Open-Source Models, Test Cases, and Data for Oilfield Drilling Challenges by Paul Pastusek, ExxonMobil, et al. SPE 197465 Automatic Real-Time Monitoring of Drilling Using Digital-Twin Technologies Enhances Safety and Reduces Cost by Rolv Rommetveit, eDrilling, et al.

Integrated Deepwater MPD Control System Increases Accuracy, Ease of Use

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 194543, “Lessons Learned With Real Integration of a Deepwater Managed-Pressure-Drilling Control System,” by Svein Hovland, SPE, NOV; Robert van Kuilenburg, SPE, Noble Drilling; and Trym Eide, Christian Stridsklev, and Colin Munro, NOV, prepared for the 2019 IADC/SPE Managed Pressure Drilling and Underbalanced Operations Conference and Exhibition, Amsterdam, 9–10 April. The paper has not been peer reviewed. This paper presents lessons learned regarding design, testing, and installation of a completely integrated managed-pressure-drilling (MPD) control system on a deepwater drilling rig. For the installation described, all MPD control functions were installed permanently on the main drilling-control network of the drilling unit, providing direct access to high-speed data from other drilling machines that influence wellbore pressure. Moreover, the MPD control system has the ability to actively control these•drilling•machines. Introduction The authors have discussed in previous work that seamless integration with existing rig infrastructure will be instrumental in using MPD as standard operating procedure during drilling. Installing the MPD control system as an equal peer in the drilling-control network is key to this strategy. This allows for using existing high-speed, robust data networks, and optimization of the overall drilling process by including topdrive, mud pumps, drawworks, and MPD equipment in the management of pressure. Other authors have discussed strategies for integration and economic deployment of MPD on a contractor’s fleet of vessels. This strategy includes integration of MPD hardware and control systems with existing rig systems in close collaboration with original equipment manufacturers (OEMs) and suppliers. In this strategy, the drilling contractor will be responsible ultimately for delivering MPD functionality as an integral part of its drilling service. System Design A key part of the drilling contractor’s strategy is to use the same user interfaces, topologies, and infrastructure on all their drilling vessels. To accomplish this, the MPD control system must be integrated into the overall OEM drilling control system. These integrated drilling control systems are built for seamless integration of machine control, process management, and information sharing. The system networks, forming the backbone of the system architecture, are secured and prepared for any machine integration with redundant setups for a high level of system and operational availability. The segregated networks offer increased security and reliability. For the MPD-specific control tasks, the OEM maintains a code base of core MPD functionality that can be deployed quickly for standard deliveries. For integrated systems, the OEM and drilling contractor work together to review the existing drilling control system versions to ensure that the MPD installation is performed on the correct version of the drilling control system.

Structure and Simulation of Roadway Disaster Simulation Control System for High Temperature Smoke Drill

In view of the outstanding problems of the training environment in the high-temperature smoke environment, such as failing to meet the actual combat requirements, poor effect and low efficiency, an integrated simulation exercise system of high-temperature smoke for coal mine emergency rescue is established, which mainly includes the high-temperature smoke control system and the smoke control system. The high temperature drill control system adopts PLC control temperature algorithm and introduces PID fuzzy control rule. The simulation results show that high accuracy of temperature and flue gas concentration can be achieved through PLC fuzzy PID control. The system can simulate the hot smoke environment and achieve the purpose of the actual exercise.

Automated Operations and Wired Drillpipe Benefit Arctic Drilling

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 191574, “Delivering Drilling Automation II: Novel Automation Platform and Wired Drillpipe Deployed on Arctic Drilling Operations,” by Riaz Israel, Doug McCrae, Nathan Sperry, Brad Gorham, Jacob Thompson, and Kyle Raese, BP, and Steven Pink and Andrew Coit, SPE, NOV, prepared for the 2018 SPE Annual Technical Conference and Exhibition, Dallas, 24–26 September. The paper has not been peer reviewed. This paper presents a case history of drilling automation system pilot deployment, including the use of wired drillpipe, on an Arctic drilling operation. Two major aspects of technology were introduced during this pilot, the first being a drilling automation software platform that allowed secure access to the rig’s drilling control system. The second component was a wired drillstring, which provides high-speed delivery of downhole data from a series of distributed downhole sensors. Introduction In an effort to enhance the safety of its operations, improve well construction efficiency, and leverage the potential opportunities presented by digitalization of drilling, the operator has initiated a Remote Operations and Intelligent Automation Project. The project involved the deployment of an automation operating system (AOS) on top of an existing drilling control system. The AOS provides the ability for secure, programmatic control of the rig’s major drilling hardware through the use of software. The software interface allows for custom configuration of several routine drilling activities for automated execution. The project also evaluated the latest version of the service company’s wired drillpipe (WDP). At the time of writing, the project has delivered eight wells, with various combinations of the technology implemented. The overall objectives of the project were to evaluate The readiness of the AOS for wider deployment The reliability of the latest version of WDP The maturity of the AOS drilling applications The effectiveness of this technology in reducing well costs For each well, key performance indicators (KPIs) were defined that aligned with the project-level KPIs and are dependent on the specific aspect of the technology being used on that well. Field Description The giant Prudhoe Bay field, on the North Slope of Alaska on the edge of the Arctic Circle, was discovered in 1968 with an initial estimate of 22 billion to 25 billion bbl of oil in place and has been in production since June 1977. Since the field began production, it has generated more than 12.5 billion bbl of oil, making it the most productive US oil field. The field has been a proving ground for advanced drilling techniques, including multilateral and coiled tubing, now used in oil fields around the globe. Production from Prudhoe Bay is supported by ongoing drilling activity. Technology Description An overview of the automation technology is presented in Fig. 1.

Real-time drilling optimisation – driving drilling excellence

Here we explore a real-time solution that anticipates drilling events and avoid delays caused by such issues as poor hole cleaning, higher torque and drag, swab and surge, stuck pipe, lost circulation, formation damage and wellbore instability. This is important if drilling optimisation is a major technical and corporate goal or if you wish to go beyond the traditional approach of collecting real-time data only to monitor operations. The presented state-of-the-art ‘real-time drilling optimisation’ solution creates a dynamic, real-time picture of the entire wellbore and key drilling variables and parameters using advanced, tightly coupled thermodynamic, hydraulic and mechanical drilling models and trend analysis applications to anticipate potential drilling issues in real-time while drilling. The solution can also be used to perform scenario based ‘what-if’ analysis and ‘look-ahead’ simulations of drilling operation with the purpose to analyse outcome of alternative operating scenarios. This is an effective solution that simplifies real-time data analysis by using trends and deviations between modelled and actual data to predict changing wellbore conditions and developing a digital twin of a wellbore. This paper includes robotic drilling automation, aimed at reducing invisible loss time, enhancing drilling efficiency and safety by applying operational safeguards to the drilling control system, providing automatic safety mechanisms and enabling automatic sequences. This paper highlights technical cases demonstrating how this analytic solution not only auto-detects symptoms (which can lead to drilling events or hazards, invisible loss time and non-productive time) but also optimises drilling performance through simulation well ahead of time, thus driving drilling efficiency.