German Acosta Valencia’s Post

AI Well Planner took 3 minutes to design a trajectory that saved over $700,000 while accounting for torque-and-drag for casing running, kick-off point, and DLS constraints. You probably wouldn't have had time to make a coffee...   We analyzed well construction costs affected by the trajectory, and selected the following factors: drilling cost per meter, drilling time, drilling fluid, casing, cement slurry, and cuttings disposal. We also considered that not every geometrically precise trajectory is suitable for running casing - AI Well Planner now takes into account torque-and-drag during the casing running process.   Redesigning the transport section from the previous post saved $745,000 compared to a design by human. The snapshot load graph also shows that the casing of the third section is at the limit of helical buckling. This is an extreme case, demonstrating AI Well Planner's ability to find the most optimal solution. In reality, a safety factor of 0.7-0.8 will be used for helical buckling. #ai #ml #machinelearning #drilling #drillingengineering #oilandgas

Axcel's Capability to Predict Drilling Risks Axcel is designed to predict a wide range of drilling risks, leveraging its advanced machine learning algorithms, real-time data integration, and historical data analysis. Here are some of the key drilling risks that Axcel can predict: 1. Kick and Blowout Risks: Pressure Monitoring: By continuously monitoring pressure levels, Axcel can predict potential kicks and blowouts, providing early warnings to prevent catastrophic failures. Mud Weight Optimization: Axcel can recommend adjustments to mud weight to maintain well control and mitigate kick risks. 2. Stuck Pipe Incidents: Torque and Drag Analysis: Axcel analyzes torque and drag data to identify conditions that might lead to stuck pipe incidents. Real-Time Monitoring: Continuous monitoring of drilling parameters helps in early detection of conditions that could cause the pipe to get stuck. 3. Wellbore Stability Issues: Formation Pressure Prediction: Axcel predicts formation pressures to prevent wellbore instability and collapse. Geomechanical Modeling: The system uses geomechanical models to assess the stability of the wellbore under various conditions. 4. Lost Circulation Events: Flow Rate Monitoring: Axcel monitors flow rates to detect signs of lost circulation, enabling quick response to minimize fluid losses. Fracture Pressure Prediction: By predicting fracture pressures, Axcel helps in avoiding lost circulation by maintaining mud weights within safe limits. 5. Drilling Fluid Contamination: Mud Property Analysis: Axcel analyzes drilling fluid properties to detect contamination and recommend corrective actions. Contaminant Source Identification: The system can identify the source of contamination, whether it’s from formation fluids or operational issues. 6. Hydrate Formation Risks: Temperature and Pressure Monitoring: Axcel monitors temperature and pressure conditions that could lead to hydrate formation. Predictive Modeling: The system predicts the likelihood of hydrate formation and provides recommendations to prevent it. 7. Equipment Failure: Vibration and Wear Analysis: Axcel analyzes vibration and wear data to predict equipment failures before they occur. Preventive Maintenance Scheduling: The system recommends maintenance schedules based on predicted equipment lifespan and performance. Conact Axcel : https://axcel.webnode.ro Find how AI can support! #AI #risk #drilling #prediction #virtualassistant #drillingengineering

UNDERSTANDING THE KEY DRILLING ERRORS In the drilling industry, several types of errors contribute to inefficiency and costly downtime. Based on recent research, we can identify four primary sources of errors: *Mechanical Errors (40%): Failures in equipment such as drill strings, pumps, and blowout preventers. *Human Errors (25%): Misjudgments in decision-making, failure to monitor warning signs, and lack of proper training. *Management Errors (20%): Poor planning, inadequate communication, and failure to update equipment or learn from past incidents. *Environmental and External Factors (15%): Unpredictable geological formations and adverse weather conditions. Moreover, underreporting of incidents, which is often tied to both human and management errors, is a critical issue that exacerbates these problems. How can Axcel, our advanced AI solution, address these challenges? For mechanical errors, Axcel can monitor equipment in real-time, predicting failures and suggesting preventive maintenance actions before issues arise. For human errors, Axcel acts as an assistant, helping teams make more informed decisions by analyzing vast datasets in real-time and flagging potential risks. For management errors, Axcel can provide insights based on historical data, allowing for better planning and communication across teams. For environmental factors, Axcel continuously adapts to changing conditions by processing data from the field and suggesting the safest and most efficient actions to take. By integrating Axcel into your operations, you can reduce errors, improve decision-making, and maximize productivity. The future of drilling is smart, predictive, and efficient—and Axcel is leading the way. Do you think AI solutions like Axcel can make a difference in reducing these errors? I’d love to hear your thoughts. If you found this insightful, please share it with your network and let’s start a conversation.Contact : rm@wellsolution.ro #DrillingInnovation #AIinIndustry #ErrorReduction #AxelAI #DrillingSolutions #EnergyEfficiency #NPTReduction

Exciting News: AI-Enhanced Perforating Guns Transform Fracking Efficiency and Safety! We are thrilled to announce a significant advancement in the fracking industry with the introduction of AI-enhanced perforating gun systems. These innovative systems are designed to improve both efficiency and safety in well operations. The new perforating systems incorporate AI and machine learning to optimize the orientation and execution of perforations. This technology ensures that perforations are precisely aligned, significantly enhancing the effectiveness of fracturing operations and improving overall production. By using AI to control and monitor perforation angles, these systems reduce the risks of runaway perforations and ensure a more uniform treatment across the wellbore. Moreover, these advanced perforating guns feature improved safety mechanisms, such as digital communication platforms that reduce the risk of accidental detonations and allow for safer handling and arming processes. This not only increases operational safety but also allows for simultaneous wellsite operations, minimizing downtime and lowering completion costs. This breakthrough represents a significant step forward in sustainable and efficient energy production, showcasing how cutting-edge technology can revolutionize traditional industries. #Fracking #EnergyInnovation #PerforatingGuns #AI #MachineLearning #TechInEnergy --- For more details, check out the latest updates from JPT and Baker Hughes (https://lnkd.in/dg6gptEN) (https://lnkd.in/ex9VNQn) (https://lnkd.in/dTa9F6rv).

Ai and Drilling Engineering 🤖🛢 In the ever-evolving world of petroleum and natural gas engineering, AI-driven autonomous drilling rigs are making groundbreaking strides. These advanced systems create a continuous loop of decision-making based on data from various sensors on the rig, combined with the MudLog. This cutting-edge technology enables the drilling rig to autonomously decide the best course of action, ensuring precision, safety, and efficiency. One remarkable case study that highlights the potential of AI in drilling is Halliburton's first horizontal well drilled using fully automated AI-driven technology. This pioneering project demonstrates the transformative impact of AI on the drilling process, setting new standards for the industry. Learn more about this groundbreaking achievement: https://lnkd.in/e3mNzq8K #Drilling_Engineering #Ai #Petroleum_Engineering

This is one of my early works in the oil&gas industry more than a decade ago. https://lnkd.in/eaiSMtbp The LWD (Logging-While-Drilling) has the advantage of being capable of measuring the borehole physical properties (e.g. formation slowness) while drilling a wellbore. This LWD technology reduces the time&cost compared with the conventional Wireline measurement which deploys a measurement tool after the drilling which requires additional cost & time. The technology of LWD measurement was getting popular at that time and was getting more attention, but its technology was quite yet unmatured. This is partly because, as its name of the LWD suggests, the measurement of the formation slowness while drilling was extremely challenging (quite noisy because of a drilling noise, and banging noise etc). Accordingly, previously this work, the measurement of the shear slowness in the LWD condition was quite limited. In this work, for the first time in the oil&gas industry, a new technology was introduced to enable a robust slow shear measurement under the LWD condition. More importantly, not only this new technology gives a measurement robustness, it also allowed to extend the measurement range, meaning that it was a key enabler for a new formation measurement that could not be explored/assessed in this LWD technology (it was possible only in the Wireline measurement tools). I contributed, as a geophysicist/algorithm developer, to this work to establish an entire data processing workflow to solve an inverse problem* and its algorithm quality evaluation. At that time, the term of the Artificial Intelligence (AI) was not popular yet (no deep learning, but support vector machine in the machine learning was popular), but this kind of technical activity was more than AI, in the sense that everything should be white-box (i.e. explainable) with a rigorous validation process, including a failure and success of the measurement/processing. Now we have an AI in a various industry/daily use, and it is not difficult to develop/apply the AI if we don't need to take the quality/explainability into account or a research (it is inherently a black-box type of approach). But when it comes to the aplication to any mission-critical use cases, it is still quite a challenge. In this sense, I would say that AI is getting popular, but still its robustness/applicability is somewhat challenging as we previously faced with for the early LWD technology. In my next career endeavor, I will work for the AI. It will be my pleasure if I can dedicate myself to such AI challenges for various business scenes. *inverse problem: One field of mathematics/optimization problem. In this context, to extract a formation shear slowness from pressure sensor data based on a physics model in the wellbore.

Harnessing Machine Learning in Drilling Operations The Future of Drilling. This innovative approach is transforming the industry. → Optimizing Critical Parameters: Machine learning fine-tunes Rate of Penetration (ROP), bit wear, and weight on bit. This means drilling becomes faster and more controlled, leading to better resource management and less environmental impact. → Real-Time Data Analysis: Advanced algorithms analyze vast amounts of data in real-time. Patterns are identified, and predictions are made to enhance operational efficiency and safety. For example, predicting bit wear allows for timely replacements, reducing downtime and costs. → Boosting Productivity and Sustainability: The integration of machine learning in drilling operations not only boosts productivity but also paves the way for more sustainable and cost-effective practices. Before: Drilling operations relied heavily on manual monitoring and adjustments. This often led to inefficiencies and increased costs. Environmental impact was higher due to less optimized processes. Now: Machine learning provides precise control over drilling parameters. Operational efficiency has significantly improved. The industry is moving towards more sustainable practices. Machine learning is a game-changer in drilling operations. Its potential to transform the industry is immense. Genesis Energy Management Harnessing Digital Innovation for Superior Drilling Optimization #MachineLearning #DrillingOperations #Innovation #Sustainability #DataScience

Drilling engineer (Line): Hey DB, we need to identify the main risk for drilling the well we are planning on this specific field. Got any insights? Database (DB): Of course, Line! Based on the latest geological data and historical drilling reports, the main risk is the high pressure formation at 3000 m. This could cause hazardous blowouts. Line: That’s crucial info. Can you provide a statistical overview over which designs and corresponding NPT events? DB: Sure thing, Line. See following overview with casing design, NPT overview per section and I've taken the liberty to use my Generative AI-Berit to provide an similarity/differences plot for you. Now you can see which factors impacted the well. Line: Perfect. Thanks, DB. Now I'm able to make a documented decision, without spending 70% of my planning time looking for this information. DB: Anytime, Line. Let’s keep the project safe and get our ROI! Pro Well Plan AS #berit #genAI #data

While you're discussing over lunch why the markets and oil prices have dropped, AI Well Planner can design an entire well pad for you, accounting for anti-collision, torque-and-drag for casing running, kick-off point, and DLS constraints. So, you'll still have time to figure out where the markets will end up... And yes, the well pad can be redesigned every time a finely planned trajectory clashes with the harsh realities of directional drilling. Perhaps... Although all of this might become irrelevant if the oil price drops below $30 per barrel. What do you think? #ai #ml #machinelearning #drilling #drillingengineering #oilandgas

𝐀𝐃𝐒 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐚𝐧𝐝 𝐆𝐄𝐎𝐋𝐎𝐆 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐞 𝐃𝐫𝐢𝐥𝐥𝐢𝐧𝐠 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧, 𝐒𝐚𝐟𝐞𝐭𝐲, 𝐚𝐧𝐝 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞!   ADS Services LLC, a global leader in pressure management solutions for the drilling industry, announces a groundbreaking collaboration with GEOLOG that integrates AI into formation evaluation, automated well control, and drilling performance to elevate safety, reduce costs, and mitigate risk in drilling operations.  This partnership transforms drilling practices by harnessing the power of AI to deliver real-time monitoring, automated detection, and recommend corrective actions. By combining advanced Power Chokes™ technology with GEOLOG’s hardware and software for capturing critical drilling data and AI-driven data evaluation, GEOLOG and ADS’ joint offering is set to redefine safety standards and operational efficiency throughout the drilling industry. The two companies’ combined offering will be called “Drilling E.S.P.” – Evaluation, Safety, and Performance for drilling operations.  Charlie Orbell, CEO of ADS, stated, "ADS Services’ collaboration with GEOLOG signifies a paradigm shift in drilling operations, introducing AI as a key driver to enhance safety and improve drilling performance. By combining Power Chokes™ technology with GEOLOG’s AI-driven drilling automation software, we are charting a course toward a safer, more efficient future for the oil & gas industry."  As GEOLOG and ADS pioneer the integration of AI into drilling practices, stakeholders can anticipate a future characterized by heightened safety standards, optimized performance, and a commitment to utilizing cutting-edge technologies to ensure the success of drilling operations.  Richard A. Calleri, CEO of GEOLOG, commented, “Our mission, started five years ago, was to harness machine learning and AI to empower our clients to make smarter and faster decisions in drilling and resource management. This mission takes a major leap forward today thanks to this exciting collaboration with ADS. Our suite of AI solutions can quickly process a vast range of data, encompassing drilling parameters, formation evaluation, geological and geochemistry data, providing clear, actionable insights that drive operational excellence.” https://lnkd.in/gVMUYvpQ #partnership #drilling #evaluation #safety #safetyfirst #performance #ai #ml #machinelearning #mpd #powerchokes #wellcontrol #mudlogging #surfacesolutions #advancedsolutions #advancedtechnology #oilandgas #geothermal #unconventional #onshore #offshore