Intelligent managed pressure drilling
Weatherford International has launched Victus intelligent managed pressure drilling (MPD), which features intelligent control and equipment automation.
Using an algorithmic model, it maintains bottomhole pressure to enhance the primary well control barrier. Victus also includes a new automated MPD riser system for floating drilling vessels, which minimizes rig up and rig down time. The integrated, compact and smart riser design reduces installation time from two days to less than 20 minutes.
“Victus is a breakthrough that combines human intelligence with machine communication to drive MPD to new heights,” said Anthony Spinler, vice president of MPD at Weatherford. “Customers can confidently drill ahead as if they have near-infinite mud weight options available at all times. They can reduce rig time, eliminate most drilling hazards, and use the blowout preventer only when necessary.”
Based on experience in more than 7,600 MPD operations, with more than 3.5mn hours of field data, Victus aims to improve safety and reduce costs for operations in deep water, shallow water or on land.
“Our personnel and the Weatherford intelligent control system give our customers real-time information to take the exact right action, at the right time, and to achieve the optimal outcome well after well,” said Etienne Roux, president of Drilling and Evaluation at Weatherford.
Look ahead while drilling
Schlumberger introduced the IriSphere look-ahead-while-drilling service at the Offshore Technology Conference. The new service provides the industry’s first application of electromagnetic (EM) technology for detecting formation features ahead of the drill bit in oil and gas wells.
The service uses EM-based resistivity measurements more than 30 metres ahead of the drill bit, which are then compared to a prepared model that incorporates offset and other data to reveal a true downrange representation of the formation while drilling. This enables operators to make proactive decisions rather than reacting to measurements at or behind the bit while drilling wells.
“IriSphere service was created in response to the needs of our customers for risk reduction, improved drilling efficiency and optimal casing point selection,” said Tarek Rizk, president, Drilling & Measurements, Schlumberger. “Knowing what conditions lie ahead of the bit while drilling enables operators to reduce uncertainties and minimize costs by identifying geological features and deciding which actions to take before encountering them.”
More than 25 field trials were conducted with the IriSphere service in Asia, Australia, Latin America and Europe. These trials included successfully detecting reservoirs and salt boundaries, identifying thin layers, and avoiding drilling hazards, such as high-pressure formations that can lead to wellbore stability issues.
Offshore Western Australia, one customer used the IriSphere service in an unexplored part of a field to detect the reservoir 19m ahead of the bit while drilling and determine reservoir thickness to be 25m. This avoided the need to drill a pilot hole, and subsequent coring operations were optimized based on data acquired while looking ahead of the drill bit.
Modular robotics technology
Repsol Sinopec Brasil, Ouro Negro and the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) have formed a partnership for the joint development of an autonomous modular robotic system to operate in and inspect oil wells. In the Wellrobot® project the goal is to create a new tool for well inspections aiming at plugging and abandonment (P&A) operations.
“At Repsol Sinopec Brasil we invest in innovative technologies, seeking a greater degree of automatization in our operations in order to help us increase their safety and generate energy in a more sustainable and efficient fashion”, highlights Tamara Garcia, research and innovation manager at Repsol Sinopec Brasil.
“Ouro Negro is a company that has innovation in its DNA. This project is totally aligned with the company’s strategy, not only in terms of its scope but also because of its adoption of the open innovation model, as this approach accelerates the development of disruptive technologies, which is what this partnership is all about. We are very pleased to be able to work alongside Repsol Sinopec Brasil and PUC-Rio”, says Eduardo Costa, Ouro Negro’s CEO.
“This robotic system will reduce costs, especially those related to well logging and rig time, and operational risks. It will optimise the critical plugging and abandonment process undertaken during decommissioning in mature basins”, adds Costa.
“The University-Company partnership will accelerate the development of this innovative robotic system by integrating teams with development knowledge of high-reliability hardware and intelligent control software required to perform the challenging tasks proposed”, concluded Marco Antonio Meggiolaro, PhD, coordinator of the Robotics Laboratory of PUC-Rio and professor of Mechanical Engineering Department of the Centre of Science and Technology of PUC-Rio (CTC/PUC-Rio).
Machine learning mooring line failure detection
DNV GL, the technical advisor to the oil and gas industry, has developed a solution that reduces the risk of offshore floating vessel mooring line failure going undetected by replacing physical sensors with a machine learning algorithm that accurately predicts line failure in real time.
The company’s Smart Mooring solution addresses growing industry concern about the high frequency of mooring line failure, and a vessel’s subsequent loss of station. Over the past two decades, more than 20 incidents have been reported globally involving failure of permanent mooring systems on floating structures. In the most severe cases, vessels have drifted and risers have ruptured, causing extended field shutdown, and risk to life, property and the environment.
Results from a numerical case study of a turret moored floating production, storage and offloading vessel (FPSO) with more than 4,000 test cases have demonstrated that DNV GL’s Smart Mooring solution can accurately identify when a mooring line has failed. Multiple pilot studies will be conducted on other offshore floating vessel types over the remainder of this year.
“Our Smart Mooring solution can be deployed to predict a mooring system’s response to various operating conditions. It determines when a mooring line has failed, more accurately and cost-effectively than physical tension sensors currently used to detect anomalies. Conservatively, we estimate it is half the cost to implement our solution versus installing a mooring line tension monitoring system for a brownfield operation,” said Frank Ketelaars, regional manager, the Americas, DNV GL – Oil & Gas.
Tension sensors can be difficult and costly to maintain, and field experience suggests that they can be prone to failure within the first few years of installation. DNV GL’s Smart Mooring solution can be used instead of replacing failed sensors in brownfield offshore operations, or as a complete alternative to implementing sensor technology in greenfield offshore oil and gas developments.
DNV GL’s experts developed the Smart Mooring solution by training a machine learning model to interpret the response of a vessel’s mooring system to a set of environmental conditions and are then able to determine which mooring line has failed.