The Ocean Energy Safety Institute (OESI) is pleased to announce it will fund 10 proposals for innovation and technology development to improve the safety and environmental sustainability of oil and gas energy development. OESI received 41 project proposals for 12 distinct pathways. Total funding for the 10 projects selected will reach $3,885,057, pending successful contract negotiations.
Organized under an agreement between the Bureau of Safety and Environmental Enforcement, Department of Energy, and Texas A&M Engineering Experiment Station, OESI is a consortium of industry, national labs, NGOs, and academia created to support the development of critical safety and environmental improvements for all offshore energy activities, including renewable and traditional energy. These are the first grant awards from the OESI consortium, which includes wind energy, marine energy, and oil and gas. Grant awards for marine and wind energy proposals will be announced in the coming weeks/months.
Funding will be awarded to the following project titles and lead organizations:
| Project Title | Lead Organization | Requested Amount |
|---|---|---|
| 1.1 – Identify leading indicators for the risk of loss of well control | ||
| Developing and Field-Testing a New Framework for Identifying and Integrating Leading Indicators of Offshore Loss of Well Control Events | Louisiana State University | $499,956 |
| 1.3 – Standardize well control event consequence analysis to support consistent risk measurement | ||
| Standardize blowout event consequence analysis to support consistent risk measurement | Add Energy (ABL Group) | $354,160 |
| 2.2 – Early detection of well failure, including plugged and abandoned wells | ||
| Demonstration of a Real-Time Electromagnetic Method to Monitor Plugged and Abandoned Wells | University of Texas Austin | $399,997 |
| 3.1 – Develop methods to monitor asset health and assess life extension using in-situ inspection data | ||
| Sensor-assisted real-time dynamics-stress-fatigue estimations of riser-mooring umbilical using digital twin and machine learning | Texas A&M Engineering Experiment Station | $275,000 |
| 4.1 – Automated remote inspection techniques to produce desired risk-based safety and integrity management | ||
| Industry 4.0 – Hybrid Intelligent Autonomous Vehicle (HIAV), small form factor solution for the Offshore Oil and Gas and Renewables Market | Agellus Tankbot 360 Inc. | $317,760 |
| 5.3 – Enhance understanding of human factors based on past incident data to reduce incidents involving routine lifting operations | ||
| Reduce the frequency and impact of crane lifting-related incidents by developing an enhanced understanding of Human Factors issues/concerns | American Bureau of Shipping | $215,696 |
| 5.5 – Improved obstacle detection and automated collision warning systems | ||
| SMART-SEA: Safe Maneuvering using Augmented Radar Tracking for Sea-based Entity Avoidance | Texas A&M Engineering Experiment Station | $500,000 |
| 5.6 – Novel material and improved mechanical integrity of offshore grating | ||
| Design and Manufacturing of Sustainable and Durable Composites for Offshore Grating | Texas A&M Engineering Experiment Station | $428,142 |
| 5.7 – Improved inspection technology to detect mechanical integrity issues of offshore grating | ||
| Innovative Inspection Technology and Assessment Methodology for Integrity Management of Offshore Grating | Simpson Gumpertz & Heger | $399,732 |
| 7.1 – Measuring safety effectiveness of BSEE regulations | ||
| Risk-Based Evaluation of the Effectiveness of BSEE’s Regulations 30 CFR Part 250 | American Bureau of Shipping | $494,614 |
| TOTAL | $3,885,057 | |
Project Synopsis
Developing and Field-Testing a New Framework for Identifying and Integrating Leading Indicators of Offshore Loss of Well Control Events
PI: Yuanhang Chen, Louisiana State University
The project addresses challenges in offshore drilling and completion operations, focusing on kick detection and secondary well control. It seeks to develop an integrated real-time influx detection and profiling system, along with an updated set of leading indicators for offshore loss of well control. The goal is to improve the accuracy and reliability of detecting primary well control issues and mitigating secondary well control loss. The project’s scope is limited to offshore well control, and it acknowledges the limitations of individual methods currently in use. The assumptions include the conditionally independent nature of variables/events in the Bayesian Network for kick detection and the accuracy of the physics-based model in influx profiling, with uncertainties related to parameter estimation.
Standardize Blowout Event Consequence Analysis to Support Consistent Risk Measurement
PI: Ole Rygg, Add Energy (ABL Group)
The project focuses on enhancing blowout contingency planning (BCP) in the offshore oil and gas industry, particularly in response to the 2010 Gulf of Mexico Macondo incident. It aims to provide a comprehensive and detailed BCP that evaluates mitigating measures for blowout response and containment. The study acknowledges the shortcomings of existing industry guidelines and literature, seeking to fill the gaps by leveraging expertise in BCP and historic projects. The proposed deliverables include a summary of existing BCP guidelines, a recommended roadmap for best practices in BCP development and its subsets, a risk management tool for assessing blowout consequences, and documentation and guidelines on using this risk management tool. The project recognizes the complexity and unpredictability of blowouts and aims to provide valuable insights for better preparedness and risk management in the event of future incidents.
Demonstration of a Real-Time Electromagnetic Method to Monitor Plugged and Abandoned Wells
PI: Mohsen Ahmadian, University of Texas Austin
The project aims to address the challenge of modeling and detecting subsurface fluid flow through defective cement in wells using surface-based Controlled-Source Electromagnetic (CSEM) surveys. Current techniques for electromagnetic surveys primarily focus on diagnosing subsurface characteristics based on conductivity changes, but they struggle to detect fluid flow-induced self-potential (SP) changes in almost negligible conductivity variations. This limitation hinders the ability to monitor well integrity, particularly in Plugging and Abandonment (P&A) operations, where faulty sealing can lead to environmental risks. The project seeks to perform numerical experiments and demonstrate the concept at the Devine Field Test Site (DFTS) to assess the feasibility of using surface-based CSEM surveys for early detection of leaks in wells, potentially revolutionizing well monitoring technology. Assumptions include the detectability of SP current dissipation and potential limitations related to contrast agents, flow rate sensitivity, and the need for permanent monitoring stations.
Sensor-Assisted Real-time Dynamics-Stress-Fatigue Estimations of Riser-Mooring Umbilical using Digital Twin and Machine Learning
PI: MooHyun Kim, Texas A&M Engineering Experiment Station
The project encompasses several key elements: first, the development of a customized time-domain simulation tool for oil/gas platforms, validated through comparisons with physical data; second, the creation of algorithms for real-time monitoring of risers and lines, initially tested with numerical sensor data and adapted to account for real-world noise and behaviors like vortex-induced vibration; third, the establishment of algorithms for real-time inverse wave/current estimation using motion sensors and machine learning, verified against field data; fourth, the development of a real-time fatigue damage estimation algorithm based on time-domain simulations or machine learning, to be used for life-extension assessments; and fifth, the construction of a physical unit hosting sensors and algorithms for remote monitoring of various marine structures, potentially including unmanned platforms, ships, wind turbines, and marine energy devices, with the aim of commercialization. The project’s deliverables include comprehensive reports on each component’s development and validation.
Industry 4.0 – Hybrid Intelligent Autonomous Vehicle (HIAV), small form factor solution for the Offshore Oil and Gas and Renewables Market
PI: Kweku Sekyiamah, Agellus Tankbot 360 Inc.
Agellus Robotics Group plans to develop a staged gate technology development process for the commercialization of the HIAV (Highly Intelligent Autonomous Vehicle). The HIAV is a complex system comprising multiple integrated subsystems, both mechanical and software-based, which are controlled through a tiered interface. The goal is to create a remotely operated HIAV that can work in conjunction with the Ocean Aero Triton vehicle. Leveraging the open architecture of the Triton, the project aims to expedite the integration of the HIAV. The staged process involves progressing from early-stage concept development to the Basis of Design (BoD), Front-End Engineering and Design (FEED), and ultimately, building and testing the HIAV. Additionally, the project will focus on developing firmware and software technology for AI/ML and data analysis to support the HIAV’s operations.
Reduce the Frequency and Impact of Crane Lifting-related Incidents by Developing an Enhanced Understanding of Human Factors Issues/Concerns
PI: Kevin McSweeney, American Bureau of Shipping
The project aims to enhance crane safety in the offshore industry by identifying and addressing human factors contributing to lifting-related incidents. It involves a comprehensive review of existing literature and interactions with industry stakeholders to uncover these human factors. The scope extends beyond the Gulf of Mexico, encompassing international offshore oil and gas, as insights from one sector may apply to another. Known human factors such as non-compliance with company procedures, inadequate training, improper maintenance, and organizational culture will be examined within the context of regulatory Safety and Environmental Management Systems (SEMS) requirements, BSEE safety culture guidance, and Human Factors Engineering (HFE) standards. The assumption is that the industry will actively participate and share incident data and expertise to facilitate the project’s success.
SMART-SEA: Safe Maneuvering using Augmented Radar Tracking for Sea-based Entity Avoidance
PI: Mirjam Furth, Texas A&M Engineering Experiment Station
The project aims to address the increasing issue of collisions and near-misses between marine vessels and stationary offshore platforms. These incidents pose risks to property and lives and are exacerbated by factors such as poor visibility, inadequate hazard identification, and distracted vessel operators. The project’s main objective is to develop an all-weather “decision dashboard” for mariners, offering real-time alerts and course correction suggestions to prevent collisions with offshore platforms. The system utilizes onboard radar, AIS, and ENC data to function effectively in various weather conditions. Although it currently focuses on stationary hazards, it’s designed for future adaptability to moving objects. The project assumes meaningful radar signatures for hazards and onboard radar data availability, engaging experienced mariners and an Industrial Advisory Board to ensure industry relevance.
Design and Manufacturing of Sustainable and Durable Composites for Offshore Grating
PI: Shiren Wang, Texas A&M Engineering Experiment Station
The proposed scope involves addressing the need for sustainable materials in offshore grating structures to reduce environmental impact. The project aims to create a new class of composite materials by integrating geopolymer into fiber-reinforced bio-resins. These materials are expected to have outstanding properties, including fire resistance, mechanical strength, corrosion resistance, seawater resistance, lightweight, and cost-effectiveness. The project will investigate how different factors like volume fraction and processing affect the properties of the composites, considering both original and recycled glass fibers. The scope includes delivering a research report, a prototype of an offshore grating structure using the new materials, and a techno-economic analysis of the technology. The project is bounded by its relevance to offshore drilling and oilfield service companies and is based on the assumption that geopolymer can enhance the composite’s properties.
Innovative Inspection Technology and Assessment Methodology for Integrity Management of Offshore Grating
PI: Onder Akinci, Simpson Gumpertz & Heger
The project focuses on the development and testing of a novel grating inspection technology for offshore platforms, addressing the risks associated with grating corrosion and structural degradation. Corrosion in marine environments, particularly in crevices and stress-concentration areas, can compromise the integrity of gratings used for walkways and emergency evacuation. Visual inspection is often inadequate to detect these issues. The research involves a testing program that includes accelerated corrosion, introducing notches, and assessing load-bearing capabilities. Tri-axial accelerometers and displacement transducers will be used for data collection, and the results will be compared to finite element analysis. The study will focus on steel grating and fasteners, including their susceptibility to stress-corrosion cracking. The project aims to develop a reliable structural health monitoring system using wireless accelerometers and handheld devices for grating anomaly detection, ultimately delivering a technical report on the findings and methodology.
Risk-Based Evaluation of the Effectiveness of BSEE’s Regulations 30 CFR Part 250
PI: Harishbhai Patel, American Bureau of Shipping
