Results
Abstract With the ever-increasing number of underwater assets and structures driven by the energy industry's shift to renewables, the need for reliable long-term remote monitoring solutions for both environments and assets is growing. Such solutions typically consist of a suite of sensors, the data transfer mechanism, and data analytics and visualization. Underwater wireless technology is the key enabler for such a holistic monitoring solution that can be used for a variety of applications. However, many commercial operations are designed around the assumption that underwater wireless technology is not yet suitable for today's operational needs. While there are several advancements in the domain of underwater wireless systems in recent times, they have not made it to operational commercial systems. In this paper, we look at the example of Acoustic Doppler Current Profilers (ADCPs), where a typical operation relies on either offline data download or using a cable to perform real-time data transfer. We then illustrate how such an operation can be transformed by integrating a smart modem that packs technologies such as software-defined design, edge computing, and machine learning along with robust and reliable high-speed underwater wireless communications to an ADCP to achieve flexible and reliable wireless data transfer. The software-defined design aspect allows easy integration to a variety of sensors, in this example an ADCP. The edge computing and machine learning aspects allow the modems to optimize the data for a high-speed acoustic link that supports adaptive modulation and automatic retransmission to avoid data loss. Smart scheduling techniques are incorporated into the solution to support extremely low-power modes to enable long-term deployments. An application-specific web-based user interface (UI) provides a seamless user experience during the whole operation. Integrating such innovations to form a holistic solution for long-term monitoring can drive down overall costs and improve operational safety.
- Information Technology > Communications > Networks (1.00)
- Information Technology > Architecture (1.00)
Design for preventing or minimizing the effects of accidents is termed accidental limit states (ALS) design and is characterized by preventing/minimizing loss of life, environmental damage, and loss of the structure. Collision, grounding, dropped objects, explosion, and fire are traditional accident categories.
- South America > Brazil (1.00)
- Oceania > Australia (1.00)
- North America > Canada (1.00)
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- Summary/Review (1.00)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
- (3 more...)
- Geology > Mineral (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Sedimentary Geology > Depositional Environment (0.67)
- Geology > Structural Geology > Tectonics > Plate Tectonics (0.67)
- Transportation > Marine (1.00)
- Transportation > Infrastructure & Services (1.00)
- Transportation > Ground (1.00)
- (36 more...)
- South America > Brazil > Campos Basin (0.99)
- North America > United States > Gulf of Mexico > Central GOM > East Gulf Coast Tertiary Basin > Viosca Knoll > Block 786 > Petronius Field (0.99)
- North America > United States > Gulf of Mexico > Central GOM > East Gulf Coast Tertiary Basin > Mississippi Canyon > Block 392 > Appomattox Field (0.99)
- (58 more...)
"In offshore and coastal engineering, metocean refers to the syllabic abbreviation of meteorology and (physical) oceanography" (Wikipedia). Metocean research covers dynamics of the oceaninterface environments: the air-sea surface, atmospheric boundary layer, upper ocean, the sea bed within the wavelength proximity (~100 m for wind-generated waves), and coastal areas. Metocean disciplines broadly comprise maritime engineering, marine meteorology, wave forecast, operational oceanography, oceanic climate, sediment transport, coastal morphology, and specialised technological disciplines for in-situ and remote sensing observations. Metocean applications incorporate offshore, coastal and Arctic engineering; navigation, shipping and naval architecture; marine search and rescue; environmental instrumentation, among others. Often, both for design and operational purposes the ISSC community is interested in Metocean Extremes which include extreme conditions (such as extreme tropical or extra-tropical cyclones), extreme events (such as rogue waves) and extreme environments (such as Marginal Ice Zone, MIZ). Certain Metocean conditions appear extreme, depending on applications (e.g.
- Europe > United Kingdom > England (1.00)
- Asia > Middle East > Saudi Arabia (1.00)
- Asia > Japan (1.00)
- (16 more...)
- Summary/Review (1.00)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
- (3 more...)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Sedimentary Geology > Depositional Environment (0.67)
- Geophysics > Electromagnetic Surveying (0.65)
- Geophysics > Seismic Surveying > Seismic Modeling (0.45)
- Transportation > Passenger (1.00)
- Transportation > Marine (1.00)
- Transportation > Infrastructure & Services (1.00)
- (36 more...)
- Europe > Denmark > North Sea > Danish Sector > Central Graben > Block 5504/12 > Tyra Field (0.99)
- Europe > Denmark > North Sea > Danish Sector > Central Graben > Block 5504/11 > Tyra Field (0.99)
- North America > United States > Colorado > Ice Field (0.98)
- (18 more...)
- Well Drilling > Well Planning > Trajectory design (1.00)
- Well Drilling > Drillstring Design > Drill pipe selection (1.00)
- Well Drilling > Drilling Operations (1.00)
- (53 more...)
Big data analytics is a big deal right now in the oil and gas industry. This emerging trend is on track to become an industry best practice for good reason: It improves exploration and production efficiency. With the help of sensors, massive amounts of data already are being extracted from exploration, drilling, and production operations, as well as being leveraged to shed light on sophisticated engineering problems. So, why shouldn't a similar approach be applied when it comes to worker health and safety; especially when it's the norm across a wide variety of other industries? While the International Association of Oil and Gas Producers came out with a safety performance report that showed fatalities and injuries for the industry were down in 2019, the US Occupational Safety and Health Administration (OSHA) says that the oil and gas industry's fatality rate is 7 times higher than all other industries in the US.
- Government > Regional Government > North America Government > United States Government (0.72)
- Energy > Oil & Gas > Upstream (0.72)
- Health, Safety, Environment & Sustainability > Safety (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Data mining (1.00)
The oil and gas industry has picked up on the benefits of digitization and artificial intelligence (AI) in its day-to-day activities, and the health, safety, and environment (HSE) sector is no exception. While AI brings clear benefits, the risks that come with those benefits remain unclear. While touting the advances of technology in HSE at SPE's Virtual Annual Technical Conference and Exhibition (ATCE), Olav Skar, director of health, safety, security, and wells at the International Association of Oil and Gas Producers (IOGP), said, "I also see risks, and I remain concerned that we do not truly understand them." Skar spoke at ATCE on a panel that included Mohamed Kermoud, Schlumberger's global vice president for HSE, and Philippe Herve, the vice president of energy solutions at SparkCognition. The panel was moderated by Josh Etkind, Shell's Gulf of Mexico digital transformation manager.
- North America > United States (0.25)
- North America > Mexico (0.25)
After years of low oil prices, the focus is on adding a lot of value for a little cost. SPE's technical directors are talking about adding value to everything from a petroleum engineering degree to a wellbore. A failure to do so can mean a degree that does not prepare a student to contribute after graduation, or a well whose production fades early. Those working as petroleum engineers have a generation's worth of challenges to address due to the push into unconventional development. Those results will determine how much value can be coaxed from these ultra- tight rocks. For those designing projects that will get built, it pays to think small. A standardized, modular design can deliver value at a cost that is lower, and more likely to come in within the budget. Doing more with less in drilling means there are fewer drilling rigs in the world, and the job of many engineers still working will be to identify the best available technology to continue to reduce the number of rigs required.
The American Society of Safety Professionals (ASSP) Foundation released a fatigue-research report that shows the value of wearable technology in the workplace. The 3-year study was led by Lora Cavuoto at the University at Buffalo and Fadel Megahed at the Farmer School of Business at Miami University of Ohio. The project also involved researchers from Auburn University and the University of Dayton. The study, which ended in December, demonstrated how to capture a worker's safety performance and translate the data into personal fatigue levels. It is the first step in creating a comprehensive framework that can identify research-supported interventions that protect workers from injuries caused by being tired on the job.
- North America > United States > Ohio (0.27)
- North America > United States > Gulf of Mexico > Eastern GOM (0.27)
- Health, Safety, Environment & Sustainability > Safety (0.75)
- Data Science & Engineering Analytics > Information Management and Systems > Data mining (0.35)
Data Science and Business Intelligence Techniques for Learning from Environmental Accident Analysis for Offshore Oil Fields
Loretti, Rômulo Alves (Halliburton) | Da Costa, Vitor Felipe Pereira (Halliburton) | Memoria, Daniel Geraldo De Oliveira (Halliburton) | Barbosa, Andrezza Neves (Independent Author) | Oliveira, Helton Luiz Santana (Petrobras) | Wegner, Issac Rafael (Petrobras) | Zank, Cristiano Andre Christmann (Petrobras)
Abstract Incorporating data science and business intelligence (BI) techniques as a strategy and tool for improving and evolving process safety for the oil and gas industry is a no-return method that should provide extraordinary gains. The technology is a powerful and necessary partner for the oil industry to overcome the challenges of new frontiers for oil exploration and production. Additionally, this applies to the health, safety, and environmental segment of business because more challenging scenarios imply greater potential risks; therefore, access to information within the appropriate time, clearly, and consistently allows the longevity of business. Digital transformation, helped current activities supported by weak instruments (i.e., spreadsheets, e-mails, etc.) to migrate to a database structure that facilitated the understanding of their real situation within the appropriate time—at macro and micro levels—allowing adequate support for decision-making. BI tools aided by data science techniques facilitate decision-making, often extracting productive information from content-rich texts. The combination of data science techniques with BI tools enables a full-blown experience for business analysts through new insights, background connections not yet discussed, more professional visualizations, and telling the same or a new story using more complete, and often complex, innovative questions and answers. Answering essential questions for process safety in the oil and gas industry when analyzing environmental accidents, atmospheric dispersions, emissions, leaks, and spills in a structured method (presenting graphically within the context of rigs), multiple views of the problem allow improved management of efforts, which reduces the number of cases. The same concept can be expanded to questions related to injuries, machinery and/or equipment damage, performance, etc.
- North America > United States (0.68)
- South America > Brazil > Rio de Janeiro (0.47)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Campos Basin > Marlim Field > Macae Formation (0.99)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Campos Basin > Marlim Field > Lago Feia Formation (0.99)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Campos Basin > Area do 1-RJS-366 > Frade Block > Frade Field (0.99)
- (2 more...)
- Management > Risk Management and Decision-Making (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Data mining (1.00)
- Health, Safety, Environment & Sustainability > Safety > Operational safety (0.94)
- (2 more...)
Abstract Well Integrity engineers are commonly challenged with using limited resources, and even more limited data, when trying to identify which wells amongst their diverse well inventory may be prone to damage and failure, the mechanisms and influential factors responsible for the potential damage and failures, and the reason why certain wells may pose the greatest risk. Furthermore, these integrity engineers are often uncertain as to the parameters that should be tracked; what inspection methods should be conducted, in which wells and at what frequency measures should be taken; and how the asset risks can be adequately determined and relayed to management to prioritize near-term and future financial investments into well integrity and decommissioning cost centres. In this paper, an approach and workflow are described on how the application of a combination of reliability and risk methods, parameter-based damage models and available field data can be used to develop a tool used by asset integrity and operations personnel to risk-rank wells by the probability of failure and associated consequences. Additionally, this paper illustrates how the approach and models developed are adaptable to both the damage mechanisms specific to the application and to the data and parameters that are currently being measured or readily obtained, or other related variables that can used as suitable proxy parameters. As experience and history build (adding to the understanding and prioritization of damage mechanisms and key parameters), and to improve estimated values of the associated probability of failure due to these mechanisms, the knowledge is fed back into the model to improve its predictive capabilities. This paper also describes how the methodology was applied by a commercial SAGD operator to develop a subsurface isolation risk assessment tool that was tailored to their wells, their application conditions and the parameters that they measure. The types of static and dynamic parameters that this tool considers, including geologic, well design, construction and operational data, are also illustrated, as well as how the tool is being used to prioritize injection and production wells by relative risk. Illustrative examples of how well, pad and asset risks are being identified, rolled-up across the asset and summarized are presented, and how well integrity and risk metrics are being communicated within the company. Ongoing activities to continue to update and advance the risk-ranking model are also noted; in particular, potential opportunities to develop improved mechanistic and data-driven models and predictions of damage and failure likelihoods, based on pooled reliability data and information across the broader thermal recovery sector.
- South America (1.00)
- North America > United States > Texas (1.00)
- North America > Canada > Alberta (1.00)
- (2 more...)
- Instructional Material (0.46)
- Overview (0.46)
- Well Drilling > Wellbore Design > Wellbore integrity (1.00)
- Well Drilling > Drilling Operations (1.00)
- Well Drilling > Casing and Cementing > Casing design (1.00)
- (10 more...)
- Information Technology > Data Science > Data Mining (1.00)
- Information Technology > Software (0.93)
- Information Technology > Information Management (0.92)
- (2 more...)
Abstract OSHA has reported in 2016 that the upstream industry has one of the highest rates of severe injuries, in some measures, it actually has the highest. Therefore, imagine a world where these accidents, injuries and diseases could be predicted before they actually happened. Such a system has been developed and tested that will redefine the HSE industry thinking. The Human Sensory Predictive Personal Protective Equipment (PPPE) system which is founded on a plurality of machine, predictive methods, and supervisory safety alert system was developed by the efactory (Saudi Aramco: Innovation lab). This game-changing system measures human sensory central and peripheral signals, via human – machine interface - namely brain signals measured by electroencephalography (EEG), and biometrics (heart rate, stress response, temperature, body position and location) measured by specialized sensors built into personal protective equipment (e.g. hard hats, safety glasses, gloves, and belts). The real time outputs from the PPPE could produce anticipated alerts and supervisory instructions to workers and worksite personnel. This innovative system predictively determines risk and alert levels associated to worksite tasks involving, personnel, equipment, and the environment. This system redefines the industry's current thinking through five core value propositions: situational awareness, knowledge and skill retention, biofeedback loops, predictive analytics, and safety alert system. Firstly, it is capable of identifying human awareness states (e.g. disengaged, boredom, fatigue, sleep deprivation) from a collection of brain signals, which is further validated by biometrics. These biological measurements are associated to an adaptive biofeedback system to the worker. The predictive analytics system contributes through a knowledge proposition of the potential of gathering sensory information based on ‘predictive opportunities'. In one work shift there are a total of 86,400 seconds of predictive power/employee that until now, have been left undiscovered. This further challenges and contributes to the well-known safety industry paradigms such as the Henrich - accident triangle. This biofeedback system leverages human machine interface collecting both the brain signals and biometrics. Currently, HSE alert systems do not provide methods and models to utilize awareness through the human computer interface (HCI). This intelligent human sensory system rises to the challenge in developing an innovative platform that could be capable of providing early detection and indication of any hazardous scenario in O&G operations.
- North America > United States (1.00)
- Asia > Middle East > Saudi Arabia (1.00)
- Health & Medicine > Therapeutic Area (1.00)
- Health & Medicine > Consumer Health (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- (2 more...)
- Health, Safety, Environment & Sustainability > Safety > Human factors (engineering and behavioral aspects) (0.87)
- Health, Safety, Environment & Sustainability > Health > Ergonomics (0.87)
- Data Science & Engineering Analytics > Information Management and Systems > Data mining (0.69)