SLB Techlog (formerly Schlumberger Techlog) wellbore software is a leading petrophysical analysis and interpretation platform designed for geoscientists and engineers working with wellbore data. It provides a unified environment for integrating, visualizing, and interpreting logs, core data, borehole images, and production information across the entire well lifecycle—from exploration to production. As part of SLB’s DELFI cognitive E&P environment, Techlog 2024.5 emphasizes reliability, extensibility, and domain-specific advancements, supporting collaborative workflows in complex subsurface environments like deepwater, shale, and unconventional reservoirs. This release, available as of late 2024, continues the annual update cycle with a focus on enhanced user experience, Python integration, and petrophysical modeling, building on prior versions like 2024.3 and 2024.1.
Key New Features in Techlog 2024.5
Techlog 2024.5 advances the platform’s capabilities in image processing, layer modeling, and quantitative analysis, making it more efficient for multi-disciplinary teams. It introduces AI-assisted tools for faster interpretations while maintaining rigorous compliance with industry standards.
Automated Layer Geometry Initialization Users can now automatically initialize local layer geometry using zone images generated from borehole image interpretations via the ExpertDip plug-in. This streamlines structural modeling by importing interpreted boundaries directly into petrophysical workflows, reducing manual adjustments and improving accuracy in faulted or layered reservoirs.
Expanded Borehole Image Processing The new image processing wizard supports the COI 4-1 Weatherford™ tool, enabling seamless handling of diverse data sources alongside other providers. This broadens compatibility for processing a wider range of borehole images, facilitating comprehensive dip and fracture analysis regardless of acquisition tool.
Log Foundational Model Integration A new log foundational model serves as a tunable baseline for subsurface interpretations. Users can customize it locally with basin- or asset-specific data by selecting calibration wells, defining inputs/targets, and running tuning processes directly in Techlog. This AI-enhanced feature accelerates baseline creation while preserving data privacy.
Quanti.Elan Enhancements Building on 2024 series updates, Techlog Quanti.Elan now outputs detailed distributions of activated input parameters, endpoints, and variables during Monte Carlo simulations. This user-controlled feature allows precise management of data processing and storage, supporting advanced uncertainty quantification in lithology and fluid modeling.
Python and Workflow Improvements Workflow versions in the Python editor follow Semantic Versioning 2.0.0, with saved workflows checking compatibility against major versions. Custom initialization for temperature-, pressure-, and salinity-based computations in Quanti.Elan is now possible via Python libraries, enabling tailored petrophysical evaluations.
Studio and Visualization Updates Enhancements to Studio integration (in Petrel or standalone) include better variable indexing for top/bottom values, reference variables, and unit handling in logs. Histogram and logView tools receive stability fixes, while K.mod efficiently manages network structure changes post-learning for more robust rock physics modeling.
These features collectively reduce interpretation time by up to 30% in tested scenarios, enhancing focus on data-driven decisions for reservoir characterization and well planning.