Geologically Consistent Horizons with Machine Learning
Petrel by Schlumberger introduces a groundbreaking feature that leverages machine learning for multi-horizon prediction. This innovative technology enables the prediction of geologically consistent sequences, enhancing the accuracy of structural models. Users can predict horizons with non-consistent reflectors, truncations, salt bodies, channels, and unconformities. The predicted horizons can be seamlessly extracted and interactively filtered, providing a clean and precise interpretation that accelerates the creation of accurate structural models.
Predicting Fold-Related Natural Fracture Distributions
A new driver process called the Folding driver in Petrel enables the prediction of fold-related natural fracture distributions. This feature uses advanced calculations to generate fracture characteristics and store them as properties in existing grids. By integrating this driver with the Fault natural fracture prediction workflow, Petrel users can adopt a novel geomechanical and geological approach to understanding natural fracture distribution, enhancing reservoir characterization and modeling.
Efficiency and Accuracy in Structural Modeling Workflows
Petrel software has introduced improvements to structural modeling workflows, enhancing efficiency and accuracy. With segment filters based on fault block data, users can create depogrids tailored to specific regions. The addition of a copy global grid operation streamlines the extraction of a part of a depogrid based on various criteria. The updated grid contains fault, horizon, and zone properties, facilitating streamlined and precise structural modeling processes.
Enhanced User Interface for Uncertainty and Optimization Workflows
The latest version of Petrel features an improved user interface for Uncertainty and Optimization workflows. The Base case tab in the dialog box now offers a more intuitive and efficient experience, resembling the Workflow editor. With a new comments field and enhanced search functionality for utilities, operations, and processes, users can optimize their workflows with increased ease and effectiveness.
Guided Workflow for Estimating CO2 Capacity in Saline Aquifers
Petrel introduces a step-by-step guided workflow for estimating CO2 capacity in saline aquifers, empowering users to model the physical and chemical behavior of CO2 with ease. This guided workflow simplifies the setup of simulation models, facilitating accurate estimations of CO2 capacity in saline aquifers. By providing a user-friendly interface, Petrel enables efficient and insightful exploration of carbon storage potential in subsurface environments.
Streamlined Well Planning with Pad Well Design Process
In the Pad well design process, Petrel now allows users to insert multiple depth surfaces representing target reservoirs at once. This feature enhances well planning by enabling users to plan wells for multiple benches in a single session. By organizing output plans into separate reservoir target folders, Petrel facilitates streamlined and organized well design processes, optimizing operational efficiency.
Advanced Quantitative Interpretation with Machine Learning
Petrel introduces a powerful tool for quantitative interpretation (QI) utilizing machine learning to predict elastic and petrophysical properties from seismic angle stacks. By leveraging machine learning algorithms, users can enhance reservoir characterization and property prediction, improving decision-making processes. This advanced QI tool empowers geoscientists and engineers to extract valuable insights from seismic data, facilitating more accurate reservoir assessments.
Enhancing Structural Models with EDFM
Petrel now integrates Embedded Discrete Fracture Modeling (EDFM) for hydraulic induced fracture scenarios and large-scale systems in naturally fractured reservoirs. By representing fractures as discrete entities during reservoir modeling and simulation, EDFM enables more accurate and detailed modeling of fractured reservoirs. This integration enhances the simulation workflow within Petrel, providing users with comprehensive tools for advanced reservoir analysis and modeling.
Improved Visualization with Perceptual Color Tables
Petrel now offers perceptual color tables for improved visualization in subsurface modeling. Leveraging the Oklab color space, these color tables ensure visually consistent and balanced representations, enhancing the interpretation of geological data. By accounting for factors such as lightness, chroma, and hue, Petrel's perceptual color tables provide users with a more intuitive and accurate visualization experience, aiding in the effective analysis of subsurface structures.
Enhanced User Experience and Functionality in Petrel 2023.8
The latest release of Petrel, version 2023.8, focuses on enhancing quality, stability, and user experience. This update introduces new functionalities based on user feedback, ensuring a robust and easy-to-use platform. With improvements in well selection dialog boxes, database tasks, auto legends, and data management features, Petrel 2023.8 offers enhanced usability and efficiency, catering to the evolving needs of geoscientists and engineers in subsurface modeling.