Petroleum and Coal
The Petroleum and Coal Products Manufacturing subsector is based on the transformation of crude petroleum and coal into usable products. The dominant process is petroleum refining that involves the separation of crude petroleum into component products through such techniques as cracking and distillation.In addition, this subsector includes establishments that primarily further process refined petroleum and coal products and produce products, such as asphalt coatings and petroleum lubricating oils.
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Venture Global's Plaquemines LNG Achieves Historic First LNG Production
Venture Global announced it has reached first LNG production at the company’s second facility, Plaquemines LNG, in Port Sulphur, Louisiana. Achieving this milestone for a 20 MTPA nameplate capacity project 30 months from its Final Investment Decision (FID) makes Plaquemines LNG one of the two fastest greenfield projects to reach first production, along with Venture Global’s first facility Calcasieu Pass. Once fully operational, Plaquemines LNG will be among the largest facilities in the world.
CNBC joins Chevron CEO in Gulf of Mexico to discuss deepwater achievements
Honeywell and Chevron Collaborate on AI-Assisted Solutions for Refining Processes
Honeywell (NASDAQ: HON) announced a strategic collaboration with Chevron (NYSE: CVX) to develop advanced artificial intelligence (AI)-Assisted solutions to help operators make decisions to enhance efficiency for refining processes and improve safety within the industrial automation space.
Together, the two companies are leveraging their deep domain knowledge and industry expertise to create a new generation of AI-Assisted alarm management solutions that will help operators make decisions to increase the efficiency, safety and reliability of process operations and industrial assets. The new solutions will include an Alarm Guidance application that provides operators with guided and specific actions to effectively respond to alarms and operational events, helping to reduce lost profit opportunities and process safety incidents. Using AI technology, the system will mine historical data on past actions to identify patterns of alarms and the corresponding operator actions that successfully return the process to normal operation.
Atlas Energy Solutions and Kodiak Announce Agreement For Autonomous Trucking Technology
Atlas Energy Solutions Inc. (NYSE: AESI) and Kodiak Robotics, Inc. announced that the two companies have entered into an agreement whereby Kodiak will outfit new Atlas high-capacity trucks with Kodiak’s autonomous driving technology.
The two companies have already completed their first driverless delivery of frac sand in West Texas’s Permian Basin. The 21-mile delivery transported Atlas’s high-quality frac sand from an Atlas depot to a wellsite with no one inside the cab.
The companies also announced that Atlas has placed an order for Kodiak-equipped driverless trucks that will deliver frac sand across the Permian Basin’s existing infrastructure of private lease roads. Early next year, Atlas plans to launch commercial operations using its first two trucks equipped with the Kodiak Driver, Kodiak’s industry-leading autonomous system.
Under the agreement, Kodiak will provide its technology to Atlas via a driver-as-a-service licensing agreement. Atlas will own the trucks, and Kodiak will provide the Kodiak Driver’s fully-redundant, platform-agnostic, hardware and software stack designed for scalable driverless deployment. Kodiak will also provide operational support services, including remote monitoring from its operations center in Lancaster, Texas.
ENEOS and PFN Begin World’s First AI-Based Autonomous Operation of Crude Oil Processing Unit
ENEOS Corporation (ENEOS) and Preferred Networks, Inc. (PFN) announced that they started continuous autonomous operation of an atmospheric distillation unit for processing crude oil in January 2024.The atmospheric distillation unit currently operated autonomously with an AI system is located in the ENEOS Kawasaki Refinery.
With 24 key operational factors to control and as many as 930 sensors to monitor, the atmospheric distillation unit especially requires a high level of skills and experience. AI-based, continuous autonomous operation of an atmospheric distillation unit is the world’s first according to a consulting firm Globe-ing Inc.
The AI system for the atmospheric distillation unit continuously monitors 24 key operational factors and adjusts 13 valves at the same time to stabilize fluctuations resulting from crude oil switching as well as changes in crude oil throughput. The AI system has demonstrated higher stability and efficiency compared with manual operations.
MODEC secures FEED for Shell’s Gato do Mato FPSO project in Brazil
MODEC Inc. is pleased to announce that it has been successful in securing the Front-End Engineering and Design (FEED) for a Floating Production, Storage and Offloading (FPSO) system for Shell do Brasil Ltda (“Shell”) on the Gato do Mato development, offshore Brazil.
Gato do Mato FPSO will be moored at a water depth of approximately 2,000m, some 250km off the coast of Brazil. MODEC will be responsible for the design of the hull and all related topsides facilities for the FPSO, which is projected to be moored by a SOFEC Spread Mooring system. The produced stabilized crude will be stored in the FPSO tanks and the oil will be offloaded to shuttle tankers to go to market.
New reactor could save millions when making ingredients for plastics and rubber from natural gas
The researchers’ new reactor system efficiently makes propylene from shale gas by separating propane into propylene and hydrogen gas. It also gives hydrogen a way out, changing the balance between the concentration of propane and reaction products in a way that allows more propylene to be made. Once separated, the hydrogen can also be safely burned away from the propane, heating the reactor enough to speed up the reactions without making any undesirable compounds.
Because the hydrogen can be burned inside the reactor and can operate under higher propane pressures, the technology could allow plants to produce propylene from natural gas without installing extra heaters. A plant that produces 500,000 metric tons of propylene annually could save as much as $23.5 million over other methods starting with shale gas, according to the researchers’ estimates. Those savings come on top of the operational savings from burning hydrogen produced in reaction, rather than other fuels.
Recycling from ABB significantly increases maximum gas production
New control algorithms for the electric frequency converters have significantly increased the maximum power that can be supplied to the export compressors. It makes it possible to increase the maximum gas export out of the plant.
Upgraded control of electric frequency inverters has averted 126 stops of export compressors since October 2019. As a bonus, the available power has been significantly increased, and together with new control algorithms on the compressor side, this contributes to an increase in maximum gas exports from Kollsnes to Europe Digitalisation pilot ensures data capture and documents the improvements.
Customize large language models with oil and gas terminology using Amazon Bedrock
The Norwegian multinational energy company Equinor has made Volve dataset, a set of drilling reports available for research, study, and development purposes. (When using external data, be sure to abide by the license the data is offered under.) The dataset contains 1,759 daily drilling reports—each containing both hourly comments and a daily summary—from the Volve field in the North Sea. Drilling rig supervisors tend to use domain-specific terminology and grammar when describing operations in both the hourly comments and the daily summary. This terminology is standard in the industry, which is why fine-tuning a foundation model using these reports is likely to improve summarization accuracy by enhancing the LLM’s ability to understand jargon and speak like a drilling engineer.
Generative AI has the potential to improve efficiency by automating time-consuming tasks even in domains that require deep knowledge of industry-specific nomenclature and acronyms. Having a custom model that provides drilling engineers with a draft of daily activities has the potential to save hours of work every week. Model customization can also help energy and utilities customers in other applications that involve the generation of highly technical content, as is the case of geological analyses, maintenance reports, and shift handover reports.
CMU Robotics Institute develops system to detect and fix problems in gas pipelines
Researchers in Carnegie Mellon University’s Robotics Institute are developing a modular robot that can creep inside natural gas pipelines to map where pipes are, detect decrepit or leaking pipes, and, when necessary, repair the pipe by applying a resin coating along its inner wall.
Natural gas in the US arrives at 75 million homes and more than five million commercial customers through a network of 1.2 million miles of distribution main lines and 900,000 miles of service lines, according to the DOE. It costs up to $10 million per mile to excavate and repair these existing lines. The REPAIR program aims to use robots and smart coatings to build new pipes within leaky ones. This process – leaving the pipes in place and repairing them from the inside out – could drastically cut costs by DOE estimates.
The researchers have evaluated their system using a testbed built by Peoples Gas. The robotic system now has a 200-foot range, Li said, but the eventual goal is two kilometers (around 6,500 feet). Lu said the current version of the robot is designed for 12-inch diameter pipes and a version for 6-inch pipes is in development.
Autonomous operations: The key to sustainably capitalizing on FPSO market growth
Yinson’s partnership with AVEVA, named Project Polaris, aims to combine our industry and technology expertise with its in-depth knowledge of the industry and FPSOs. Project Polaris is an integrated asset management solution consisting of AVEVA™ Asset Strategy Optimization, AVEVA™ Predictive Analytics, AVEVA™ BI Gateway, AVEVA™ Unified Operations Center, and AVEVA™ Work Tasks used in conjunction with existing solutions including AVEVA™ PI System™. It’s designed to improve the overall operations, maintenance, and reliability of the FPSO assets and drive toward sustainable, autonomous operations.
Using a unified operations center that provides a common user experience across the organization, Project Polaris is already helping Yinson overcome business challenges. From visualization to predictive analytics, Project Polaris integrates with existing applications and is scalable, allowing the solution to continue to gain value while reaching goals for 15 unique use cases. By monitoring asset reliability and efficiency, users can understand asset health and performance to make data-driven decisions that optimize operations, reduce unplanned downtime to zero, prevent failures, and maximize production through effective asset lifecycle management.
Industrial Software Helps Pipeline Operators Transition to More Sustainable Operation
For many midstream companies, the key to meeting that challenge lies in increasing flexibility. Some operators are looking at ways to convert their pipelines to transport hydrogen and carbon dioxide (CO2). But transporting these materials that are relatively new to the industry requires new methods of operation and monitoring, which in turn requires increased digitalization. To be successful, teams need a perfectly clear vision of what is going on—all the time.
The key is to implement modern supervisory control and data acquisition (SCADA) solutions to help keep a finger on the pulse of operations. Today’s modern SCADA solutions bring real-time operational data from the field to operators—in the control room, in the field, or wherever else they may be. But to get the most out of those solutions, teams also need powerful industrial software to give them insight into how well their operations perform. One of the most critical tools midstream operations teams need is pipeline management software, for analytics and real-time operational intelligence across their network.
The Future of Oil and Gas Inspection Software
The very nature of oil and gas operations makes assets susceptible to corrosion. Regular inspections help detect early signs of corrosion, thereby preventing potential leaks or failures. Modern technologies, such as drones and visual AI, have revolutionized this aspect, allowing for more detailed, quicker, and safer inspections.
Optelos stands out as a quintessential example of this type, merging the capabilities of the aforementioned software types into one cohesive solution. From managing visual data from UAVs to operationalizing visual AI for corrosion inspections and creating 3D digital twins, integrated platforms provide a holistic approach to oil and gas inspections.
Petrobras, Japanese partner work on carbon capture at offshore rigs
Japanese chemicals company Kureha will partner with Brazilian state energy group Petrobras to develop a new way to capture carbon dioxide from offshore oil fields. Kureha will start developing a new catalyst to be used in a carbon capturing device this fiscal year at its research facility in northeastern Japan, in a joint effort with the Hokkaido-based Kitami Institute of Technology. It plans to build a small-scale prototype of the device in fiscal 2024.
Kureha is looking to capture carbon from the methane and turn it into a powder that is easily shipped. The powder can be used to produce carbon nanotubes, a material used in lithium-ion batteries, electronic devices and auto parts.
🛢️🧠 ENEOS and PFN Begin Continuous Operation of AI-Based Autonomous Petrochemical Plant System
ENEOS Corporation (ENEOS) and Preferred Networks, Inc. (PFN) announced today that their artificial intelligence (AI) system, which they have been continuously operating since January 2023 for a butadiene extraction unit in ENEOS Kawasaki Refinery’s petrochemical plant, has achieved higher economy and efficiency than manual operations.
Jointly developed by ENEOS and PFN, the AI system is designed to automate large-scale, complex operations of oil refineries and petrochemical plants that currently require operators with years of experience. The new AI system is one of the world’s largest for petrochemical plant operation according to PFN’s research, with a total of 363 sensors for prediction and 13 controlled elements. The companies co-developed the system to improve safety and stability of plant operations by reducing dependence on technicians’ varying skill levels.
A Data Architecture to assist Geologists in Real-Time Operations
Data plays a crucial role in making exploration and drilling operations for Eni a success all over the world. Our geologists use real-time well data collected by sensors installed on drilling pipes to keep track and to build predictive models of key properties during the drilling process.
Data is delivered by a custom dispatcher component designed to connect to a WITSML Server on all oil rigs and send time-indexed and / or depth-indexed data to any supported applications. In our case, data is delivered to Azure ADLS Gen2 in the format of WITSML files, each accompanied by a JSON file for additional custom metadata.
The visualizations generated from this data platform are used both on the oil rigs and in HQ, with operators exploring the curves enriched by the ML models as soon as they’re generated on a web application made in-house, which shows in real time how the drilling is progressing. Additionally, it is possible to explore historic data via the same application.
AI-Assisted Troubleshooting Is the Rare, Low-Hanging Fruit in Energy Production
Despite ample telemetry and robust alarm management in place, energy producers continue to experience unplanned trips, flaring and other surprises that result in significant downtime, emissions and costs. While, undoubtedly, many interruptions are unavoidable in the moment, a surprisingly large percentage of interruptions could have been avoided if operators were given a heads-up. What percentage is avoidable? Actual numbers will vary from case to case, but a liquified natural gas (LNG) operations executive put it this way “Last year, we lost $100 million due to trips, and 80 percent of those trips were avoidable.” That’s a lot of avoidable loss.
ControlRooms.ai leverages machine learning algorithms to analyze tens of thousands of tags (plant data) in real-time, and surfaces specific anomalies that could lead to unplanned trips or flaring events. Detecting hard-to-find, emerging issues is the first half of the battle. The second, equally important part is surfacing these issues in real-time, in an intuitive, actionable format that allows energy producers to take proactive measures to address them and nip them in the bud.
How much faster is troubleshooting with AI? Ten times faster. One plant manager, who used a troubleshooting platform for the first time said, “This would have taken me all day… staring at 60 trends… And even then I may have missed it…” ControlRooms.ai reduces the hours-long task of triage to a single click.
Detecting dangerous gases to improve safety and reduce emissions
The primary advantage of differential optical absorption spectroscopy is its scalability. Two elements are required: a calibrated light source tuned to emit a specific wavelength, and a receiver able to read the same wavelength. In some cases, the receiver must also read a reference source for comparison. The two elements can be within the same housing to function as a point detector, but the source and receiver can also be separated, sending a beam across an open path, looking for a cloud of the target gas to move into its field of view.
Additive Manufacturing Poised to Make a Value Impact on Oil & Gas Supply Chain
An end-to-end metal AM system allows OEMs to quickly manufacture mission-critical parts for O&G operators without extensive redesigns. Such a fully integrated solution consists of print preparation software that applies a generalized set of recipes based on the design’s native CAD file, a printer that executes the print file, and quality assurance software that ensures the health of the tool and monitors the build, layer-by-layer.
Additionally, the American Petroleum Institute has now published API20S, the first-ever O&G-industry sanctioned specification for metal AM. This spells out processes, testing, documentation and traceability, among other requirements, for manufacturers of metal AM components being used in O&G facilities of all types.
Why ExxonMobil, Sinopec and Dow Are Betting On Plastic
Why Gas Prices In The U.S. Vary
Predictive Monitoring: Gas Turbines Demo
Real-Time Sensors Allow Data-Driven Monitoring of Flow-Measurement Systems
The downtime of manufacturing machinery, engines, or industrial equipment can cause an immediate loss of revenue. Reliable prediction of such failures using multivariate sensor data can prevent or minimize the downtime. With the availability of real-time sensor data, machine-learning and deep-learning algorithms can learn the normal behavior of the sensor systems, distinguish anomalous circumstances, and alert the end user when a deviation from normal conditions occurs.
Robotic Inspection for Aboveground Storage Tanks
Aboveground Storage Tanks (AST) are vital assets for many industries including, power, paper and pulp, oil and gas, chemical, and even beverage production. Routine inspection of external and internal tank components is beneficial for understanding its condition and is required by federal and local laws and regulations. Robot-enabled ultrasonic testing (UT) offers a unique solution to AST inspections because they save plant operators valuable resources while providing more asset coverage and actionable data.
Eye-bot and VEERUM Team to Deliver a Comprehensive 3D Visualization of Critical Assets in Oil & Gas
Eye-bot Aerial Solutions (Eye-bot) & VEERUM recently announced a Premier Partnership to deliver access to the most comprehensive advanced 3D datasets in the Oil and Gas, Construction, and Infrastructure sectors. Combining Eye-bot’s 3D datasets – derived from drone and ground-based data collection and data processing, with VEERUM’s asset management and visualization software equals unparalleled value for asset and capital project managers as well as a myriad of other stakeholders.
The collaboration between Eye-bot and VEERUM enables an asset owner to remotely access, collaborate, and analyze asset data in the context of 2D and 3D modeling. “Capturing the right data sets for a capital project is only as good as being able to use that data to drive better decisions,” said Jake Lydick, Founder & CEO of Eye-bot. “Remote work teams will collaborate inside the VEERUM application with the visual 3d data sets to make informed decisions.”
The Eye-bot and VEERUM collaboration can reduce operational site exposure hours by 50%, reduce inspection costs by up to 25% and improve construction progress reporting by over 30% in accuracy and availability.
The Cost of Unplanned Downtime for Refineries
According to the American Institute of Chemical Engineers (AlChE), the cost of missed production for a U.S. refinery with an average-sized fluid catalytic cracking unit of 80,000 barrels per day will range from $340,000 a day at profit margins of $5 per barrel, to $1.7 million a day at profit margins of $25 per barrel, based on a conservative estimate. A single, unplanned shutdown that lasts hours can lead to the release of a year’s worth of emissions into the atmosphere, according to John Hague, Aspen Technology Inc.
One type of innovative inspection process is Rapid Ultrasonic Gridding (aka RUG), which creates data-rich visual grid maps that identify areas of corrosion and other damage mechanisms. It is 10 times faster than traditional gridding and competing methods. In most situations, the operator can quickly make the decision of whether to proceed with maintenance measures to resolve the issue, or to return the inspected asset to operation.
Getting Industrial About The Hybrid Computing And AI Revolution
Beyond Limits is applying such techniques as deep reinforcement learning (DRL), using a framework to train a reinforcement learning agent to make optimal sequential recommendations for placing wells. It also uses reservoir simulations and novel deep convolutional neural networks to work. The agent takes in the data and learns from the various iterations of the simulator, allowing it to reduce the number of possible combinations of moves after each decision is made. By remembering what it learned from the previous iterations, the system can more quickly whittle the choices down to the one best answer.
IIoT builds new bridges to new adventures
Engenuity Inc. in Conroe, Tex., provides control automation and data integration for oil and gas and other industries, and recently found deficiencies in validation pressure testing of blowout preventers (BOP) and well-control devices. Because pressure tests are needed every few weeks for regulatory compliance, executed and recorded manually over several hours, and can cost up to $6 per second to run in offshore valve arrays, testing can cost millions of dollars per year. To reduce these expenses, Engenuity collaborated with clients like Shell International Exploration and Production Co., and developed automated, hydrostatic, test execution and reporting solutions, which use Opto 22’s groov Edge Programmable Industrial Controller (EPIC) for process control, automatic notification, and process history storage and replication.
Why resources companies are looking to evented APIs
Resources companies that want to get the most value from their data will process it the instant that it is created. The longer that data is left unprocessed, the more it diminishes in value. Operational excellence can be driven by evented APIs that can produce, detect, consume, and react to events occurring within the technology ecosystem.
Evented APIs can be applied to our example use case to deliver an autonomous feedback loop that incorporates smarter decision making in real-time.
Application of AI to Oil Refineries and Petrochemical Plants
Artificial intelligent (AI), machine learning, data science, and other advanced technologies have been progressing remarkably, enabling computers to handle labor- and time-consuming tasks that used to be done manually. As big data have become available, it is expected that AI will automatically identify and solve problems in the manufacturing industry. This paper describes how AI can be used in oil refineries and petrochemical plants to solve issues regarding assets and quality.