Presentations – Cegal Prizm Global User Group Meeting 2026
Cegal Prizm Global User Group Meeting 2026
Thank you to everyone who participated in the event on February 12, 2026 – in Stavanger, Houston, and online.
Here you can access the session recordings and presentation materials from this year’s gathering.
Each session reflects real user experiences, technical insights, and smart workflow extensions shared by users and experts across locations. You will find:
- Practical use cases from organizations using Prizm and Python Tool Pro
- Technical deep dives and automation examples
- Updates on new capabilities and product direction
- Best practices from both the Cegal team and the user community
Whether you joined live — or were unable to attend — you can now explore all sessions here.
Introduction and general comments
John Sayer – Director of Geoscience, Cegal, Vlad Rotar – Prizm Product manager, Cegal and Kjetil Fagervik – Sr. Geoscience Product Manager, SLB
AI Reservoir Characterization with Cegal Prizm and Python Tool Pro
Espen Haugsdal – RagnaRock Geo
Abstract:
This presentation demonstrates how AI-based reservoir characterization is streamlined using Cegal Prizm and Python Tool Pro, enabling direct integration with Petrel projects. The solution eliminates data movement friction by allowing AI workflows to run directly on Petrel data (seismic, wells, and horizons) without the need for manual exporting or reformatting. With a single click, users can activate advanced machine learning models that read inputs, train on the available wells, and output high-resolution 3D property cubes within seconds to minutes. The workflow supports rapid blind well validation, delivering geologically consistent predictions with minimal manual effort. This plug-in-based approach accelerates subsurface analysis and seamlessly embeds cutting-edge AI capabilities into everyday geoscience interpretation environments.
Enhancing Static Model Accuracy: An Iterative Approach to Variogram Inversion for Improved Simulation Validity
Pakorn Tangtuengtin – PTTEP
Abstract:
Accurate static reservoir models are foundational to reliable dynamic simulations and subsequent field development decisions in the conventional oil and gas workflow. However, building these models often involves challenges related to limited well data and the non-iterative nature of commercial software variogram analysis, which restricts the comprehensive exploration of subsurface heterogeneity.
This work addresses this limitation by focusing on the critical first step of static model construction: the iterative estimation and inversion of the spatial variogram. We developed a custom solution utilizing Cegal PTP to establish a seamless data link. This connector dynamically fetches property data from the active project, bypassing commericial platform's out-of-the-box constraints on manual variogram analysis.
The developed tool allows geoscientists to perform iterative variogram estimation and inversion efficiently. This iterative process maximizes the exploration of various spatial continuity scenarios, ensuring that the model captures as many aspects of the limited available data as possible. The final output is a set of optimized variogram parameters directly compared against the available variogram models in the commercial platform. This comparison provides a crucial validation step, enabling geoscientists to generate highly representative property models in Petrel, thereby significantly enhancing the quality and simulation validity of the resulting static reservoir model.
Application of Cegal Plug-in for Petrel in Seismic Interpretation and Well Planning: Improving Operational Efficiency in PTTEP Assets
Kanin Matangkapong - PTTEP
Abstract:
This paper presents the use of the CEGAL PTP plug-in for PETREK to improve efficiency in seismic interpretation and well planning for Gulf of Thailand assets, where compartmentalization and high well counts demand faster, standardized workflows.
The process is structured into three stages: (1) pre–well targeting, using automated geophysics-based interpretation of faults, horizons, and prospects; (2) well targeting, applying statistical and well-spacing methods through the OCEAN plug-in; and (3) post–well targeting, covering anti-collision checks, equipment estimation, and data transfer to drilling.
The implementation streamlines the workflow, reduces resource needs, and maintains a user-friendly interface. Overall, the plug-in provides fit-for-purpose solutions that enhance operational efficiency for PTTEP assets.
Seismic Machine Learning with Xarray
Alex Dunbar – Harbour Energy
Prizm-Powered Knowledge Management: Automating Interpretation Reporting & Data Liberation
Mordekhai – Cegal
Keeping well tops alive: automating well tops management with Cegal Prizm and Python Tool Pro
Bereke Kairanov – Inpex Idemitsu Norway
Abstract:
This presentation introduces an automated well-tops management workflow built with Cegal Prizm and Python Tool Pro, designed to ensure that well tops inside our company remain unified, consistent, and continuously up to date. The workflow links internal company well tops with data from the Norwegian Offshore Directorate (NOD), retrieves the latest tops, identifies missing or inconsistent markers, and synchronizes them. It automatically adds missing tops, corrects depth mismatches, and standardizes naming conventions to maintain a single, coherent stratigraphy across all wells. By replacing manual QC with a reproducible, automated process, the workflow helps keep our internal well-top catalogue “alive,” improving geological consistency, auditability, and decision quality across projects.
Utilization of API Solutions Across Platforms for Integrating NPD Shapefiles: From REST API to Petrel API with the Cegal PRIZM API
Mahmoud Kenawi - Cegal
From Development to Deployment: How Prizm via Remote Python Enables Geoscience Workflow Innovation
Trudy Watkins - Oxy
Abstract:
Initially, Prizm use was limited to a small group of citizen developers sharing geophysical workflows for local deployment. Remote deployment via docker containers, complemented by workshops and best practices, has expanded the user base while fostering cross-discipline collaboration. With a growing Prizm community, internal developments have streamlined routine and creative tasks across the geoscience function, from well planning and interpretation for geologists to velocity modeling and custom seismic attribute generation for geophysicists.
From Trees to Transformers – AI use cases with Prizm
Thomas Grant - Cegal
Abstract:
Missing log sections poses a significant challenge in geophysical studies, especially for velocity logs crucial for applications such as well ties, seismic interpretation, inversion, and velocity modelling. This article demonstrates how machine learning techniques developed in Python using Prizm can be leveraged to predict missing velocity and density log sections using more complete data from other wells.
We evaluate the impact of machine learning-predicted logs on the quality of well tie results using our new product, Blueback Well Ties. Our work indicates that the predicted logs lead to improved wavelets and more stable phase estimation during well ties compared to incomplete raw logs.
Probabilistic Fault Stability Screening with Cegal Prizm
Jung Chan Choi - NGI
Abstract:
As the scale of CO₂ storage projects increases, the potential for injected CO₂ to interact with faults also increases. Field screening needs, therefore, to incorporate probabilistic fault stability screening to ensure long-term containment integrity under uncertainty. This study introduces an integrated workflow that automates fault stability screening by seamlessly connecting a geologic model in Petrel with the Python-based fault stability analyzer, FracStress, via the Cegal Prizm platform. A proof-of-concept application to a hypothetical CO₂ storage site demonstrates how the workflow enables probabilistic fault stability assessment directly within Petrel, using uncertainty-aware inputs and automated execution. The results indicate that this approach improves efficiency and consistency by reducing manual data handling, streamlining stress analysis, and supporting transparent risk-informed screening decisions.
Streamlined Petrel-Techlog Data Management Integration
Carlos Macedo – Cegal
Abstract:
Working with petroleum data often means juggling multiple software platforms, and moving data between Petrel and Techlog has traditionally been a manual, time-consuming process. This talk walks through a practical solution developed using Cegal Prizm Python and Techlog's API to automate data transfer between these platforms.
I'll share how this integration streamlines everyday workflows, eliminating the repetitive export-import cycles that slow down subsurface teams. This is a technical case study covering the architecture, challenges encountered, and lessons learned along the way, and what we are planning to implement in the future.
The solution runs within familiar Python environments and leverages both platforms' APIs to create a seamless connection. Whether you're looking to build similar integrations or just curious about automating petroleum engineering workflows, I'll cover the practical details that actually matter when connecting these tools in real-world applications.