Geospatial (Tuesday) and Literacy, Culture & Human Factors (Wednesday)

The legislation that regulates recording and use of bathymetric data or information about the seabed has been updated and is not well known among some stakeholders. This presentation is primarily aimed at those who map bathymetric data or collect any type of information about the sea bed. The presentation will provide an overall introduction to the new regulation and what it entails, what type of mapping activity that requires an application or report, how the actors should relate to the legal framework and how to apply, how to get access to Kartverkets batymetric data, as well as a demo of our new digital application service. We belive this presentation will be useful for ensuring compliance with the regulation, while also contributing to safe and efficient development within the industry.

Offshore exploration, site characterization, and inspection surveys are increasingly executed through remote operating models. The goal is to enable distributed teams to make timely, informed decisions from a shared operational picture.

In practice, this remains challenging. Operational data and acquired geodata are often fragmented across systems, updated asynchronously, and interpreted differently by offshore crews, onshore teams, and clients. The result is decision latency, lower confidence in remote risk assessment, and greater exposure to reruns, incomplete acquisition, and nonproductive vessel time.

Fugro Norway has addressed this in live offshore campaigns through an integrated operational and data management approach. Using ESRI-based dashboards, teams combine vessel position and track history, survey line status, weather forecasts, live video feeds, and near-real-time seabed visualizations in one operational view. This allows deviations, data gaps, and quality issues to be identified while acquisition is underway.

Building on this foundation, VirGeo® extends these capabilities through a connected data management environment acting as a single source of truth. In addition, VirGeo® provides connected data exchange, near real-time monitoring, operational data analytics, and geodata insights and analytics. By aligning operational context with incoming geodata in a decision-ready form, validation and reconciliation move closer to acquisition and reduce late manual verification and fragmented handovers.

This shortens decision cycles, reduces rerun exposure and non-productive vessel time, and speeds first usable data review. As offshore operations become more remote and make greater use of USVs, this shift from data availability to data alignment strengthens situational awareness and reduces operational uncertainty.

Data with geospatial context is the essential connective tissue linking subsurface and energy workflows, enabling efficient decision-making, operational efficiency, and supporting sustainability objectives. Despite its importance, handling geospatial data remains still one of the most complex elements within modern data ecosystems. When interoperability breaks down, the consequences may be rather silent but far-reaching, affecting data quality, workflows, and data platforms - including OSDU - and ultimately compromising the effectiveness of analytics and AI outcomes.

This presentation delves into the causes and failure points behind these geospatial interoperability challenges. Using seismic position data and metadata as an example, current data workflows - including data quality considerations - will be examined, along with their impact on diverse stakeholders, ranging from data and solution architects to end-users reliant on the data.

Attendees will gain insight into risks within geospatial workflows. Additionally, strategies to prevent the compromise of AI-driven insights, along with practical approaches to ensure data integrity, interoperability, and readiness for analytics, decision-making, and sustainable operations, will also be discussed.

Two years ago, at this conference, the argument was made that file format compliance remains indispensable even in the era of AI – that the foundation of reliable automation is a reliable benchmark. This argument holds, and we are beginning to see the tangible benefits of automation in data loading and QC.

Compliant and regularised subsurface data enables automated file identification and ingestion, systematic geodetic parameter validation, repeatable QC procedures, structured error reporting, and export to common exchange formats – all without manual intervention. The data lifecycle becomes more manageable, and each dataset is assigned an integrity indicator so that informed decisions are made. This process is established and in practical use today.

In this talk, we present practical experience of operating such workflows, examining both what is working and where the boundaries remain. Non-compliant data continues to present genuine challenges: CRSs that must be inferred when not explicitly declared, input files in formats that resist automation, poor quality scanned legacy data, and fundamental errors embedded invisibly within otherwise plausible datasets. In each of these cases, human expertise remains critical – and likely will for some time.

At these boundaries, there are feasible approaches to reduce the triage burden when data loading. Probabilistic, fuzzy CRS identification uses spatial and contextual clues to arrive at a reasoned prediction of positioning. Pattern recognition can identify fields within non-compliant files, and format fingerprinting can inform and refine future loading decisions.

Each improvement introduced into the automation workflow reduces the load on the analyst, allowing expertise to be directed toward genuine ambiguity rather than routine compliance checks. We explore the current industry state, emerging developments, and the challenges that still require solving before full automation can be achieved.

The Nyhamna gas plant, located in Aukra on Norway’s west coast, is a key component of the Ormen Lange development and plays a critical role in Europe’s energy supply by processing and exporting natural gas through the Langeled pipeline. Over time, the facility has evolved into a multi-field gas hub, handling large volumes of gas from multiple offshore assets.

Efficient operation and maintenance of such a complex facility rely heavily on the use of temporary equipment — non-permanent, movable assets such as electrical systems, lifting gear, scaffolding, and utility units. These assets are utilized across different departments, including electrical and mechanical disciplines, and are frequently installed, relocated, or removed depending on operational needs. In particular, electrical temporary equipment—including portable power distribution units, temporary cabling, and switchboards—directly interacts with live systems and supports critical activities such as permit-to-work and isolation processes. Mismanagement of these assets can introduce significant health, safety, and environmental risks, including potential ignition sources from batteries, diesel engines, and energized systems.

To address these challenges, a GIS-enabled inventory and tracking solution was developed using ArcGIS and Power Platform technologies. The system provides real-time spatial visibility of equipment location, status, ownership, and usage duration, enabling improved situational awareness and operational control. By integrating ArcGIS Experience Builder, Survey123, ArcGIS Online, Power Automate, and dashboards, the solution supports data capture, validation, workflow automation, and decision-making within a unified digital ecosystem. The approach enhances safety compliance, supports permit-to-work workflows, and reduces unnecessary equipment rental and manual tracking. The implementation demonstrates how geospatial technologies can enable smarter asset management & efficient operations.

A growing number of maritime industries, including offshore wind, seabed mineral exploration, fisheries, and petroleum, are increasing the demand for high-quality geospatial data.

At the sime time, data silos remain a persistent barrier in both public and private sector, limiting the efficient use of geospatial information by restricting access, creating duplication of effort and reducing the ability to integrate data across maritime domains.

This presentation explores the underlying reasons these challenges remain, with particular emphasis on the gap between technical solutions and their implementation - and demonstrates how improved data sharing can unlock significant collective value across sectors.

Drawing on experiences from public geospatial data management in Norway, and informed by the author’s role as Marine Geodata Coordinator at the Norwegian Mapping Authority, this presentation highlights how clear roles, governance structures, and a national spatial data infrastructure have played a key role in breaking down data silos and enabling cross-sector data integration.

We argue that collaborative and governance-related factors, including data ownership, incentives and trust often is more critical than the enabling technology itself.

Capital-intensive projects in the energy industry face constant vulnerabilities due to extreme commodity price volatility. While digital transformation promises advanced risk management through AI and Big Data, its effectiveness is frequently bottlenecked by a critical technological skill gap. To thrive, decision-makers in non-IT areas, such as industrial Project Management, must transcend traditional competencies and develop robust digital literacy.

This presentation explores how fostering a strong data culture empowers professionals to interact effectively with complex predictive systems. While state-of-the-art neural forecasting models excel at capturing market patterns, they often lack contextual adaptability during the result analysis phase, frequently delivering outputs in overly technical formats that hinder strategic interpretation.

To address this, we propose a "Cognitive Information Fusion" framework that formally integrates Human-Computer Interaction (HCI) with AI. Its primary goal is to foster accurate mental models of AI systems among non-technical users. By treating the HCI interface as an active fusion node rather than a passive dashboard, this system translates high-dimensional predictive uncertainty into interpretable visual analytics. This approach champions Professional Development by enabling non-technical teams to align algorithmic outputs with their own heuristic knowledge and critical thinking.

Evaluated in a real-world energy sector scenario, our proposed Human-in-the-Loop (HITL) methodology demonstrates that synergizing machine precision with human strategic oversight yields highly resilient decision-making. Ultimately, investing in digital literacy and human-centric design bridges the gap between algorithmic accuracy and practical economic utility, transforming passive users into active, critical thinkers in volatile environments.

Many organizations dedicate significant effort to defining data strategies and implementing management frameworks, yet a common challenge persists — a lack of confidence in the data itself. Issues such as poor data quality, unclear accountability, unreliable data source and fragmented processes often lead to inconsistent insights and limit the value organizations can derive from their data.

This presentation looks at why this gap in trust exists and explores where conventional data management approaches tend to fall short. It considers how the absence of clearly defined ownership and practical stewardship can weaken even well-intentioned data initiatives.

The session will also show how integrating data stewardship into everyday data management activities can make a measurable difference. It will outline practical ways to establish ownership, clarify responsibilities, and introduce governance practices that ensure data is not just handled, but properly cared for.

Insights and practical ideas will be shared on how to bring together data strategy, stewardship, and operational processes in a way that builds confidence in data. The session aims to provide a clear and realistic path toward creating reliable data environments that can support better decision-making.

In Collaborative Well Planning (CWP), data delivery speed is often assumed to be an integration challenge. In practice, the dominant constraint is human behaviour under time pressure: last minute data submissions, informal handovers and unclear ownership that undermine trust and traceability. These behaviours routinely stretch data preparation from hours into days—and carry forward into downstream workflows. This presentation describes how a shift towards small, user prepared data packages reduced CWP data delivery from 1.5 days to as little as 1.5 minutes, without adding heavyweight process or central bottlenecks. The change was enabled by empowering users to take control of their data and thus bypassing the formal data preparation and readiness checks that were needed to ensure successful well planning sessions. The human dimension is at the core of this, and why users disengage with the prescribed methods, even though they are straightforward and simple. By designing data workflows around real behaviour—rather than perceived ideal behaviour—governed data packages become an enabler of speed and not an obstacle.