Automating Geological Logging: Transforming PDFs and CSVs into Digital Ground Models with DAARWIN

In geotechnical engineering, data quality governs design reliability. The ground model is not a report — it is the analytical foundation upon which every parameter, simulation, and decision depends. Yet, while computational modeling has evolved rapidly, data management often remains anchored in fragmented, manual processes.

Despite the widespread use of numerical tools, engineers still spend extensive time processing borehole logs, laboratory results, and monitoring data delivered in multiple formats — PDF reports, CSV exports, Excel sheets, and AGS files. Each follows different conventions, requiring reformatting, alignment, and validation before interpretation. This not only delays analysis but also introduces the potential for human error at the very start of the project lifecycle.

DAARWIN bridges this gap. Designed as a geological logging and ground modelling platform, it automates the extraction, structuring, and validation of geotechnical data, generating structured datasets that form a consistent, traceable basis for reliable engineering interpretation and design.

The Hidden Inefficiency Beneath Every Ground Model

Every project produces extensive ground investigation data — borehole logs, CPT results, laboratory classifications, and instrumentation readings. Despite the rigor of these investigations, the resulting data typically lacks uniformity. Files remain dispersed across reports, spreadsheets, and local directories, each using unique conventions.

The issue is not the availability of information but its fragmentation. Engineers must continuously search, verify, and reformat datasets, reconciling depth intervals, units, and sample identifiers. Even minor inconsistencies — such as mismatched depths or ambiguous layer codes — can distort formation boundaries or influence parameter derivation.

These inefficiencies rarely appear in project schedules but have measurable impact. They delay design stages, reduce analytical throughput, and weaken traceability. In a discipline where a single incorrect layer boundary can alter settlement predictions or bearing capacity estimates, data inconsistency directly undermines engineering confidence.

Automation as a Foundation for Data Integrity

DAARWIN integrates automation into the earliest phase of the geotechnical workflow — the point where raw data first transitions into structured engineering information. Its intelligent recognition algorithms extract and standardize parameters across diverse input formats while maintaining full data traceability.

The platform automatically:

• Extracts borehole, laboratory, and monitoring data from PDFs with ≈97% accuracy, CSVs, Excel, and AGS files.

• Structures parameters including stratigraphy, material classification, and laboratory test results under unified conventions.

• Centralizes all processed data within a secure cloud environment, ensuring accessibility, version control, and audit trails.

By replacing manual compilation with automated standardization, DAARWIN establishes a repeatable, verifiable process that strengthens data quality before any interpretation or analysis begins.

From Data to Design Confidence

The impact of structured geological data extends beyond visualization. A consistent dataset directly enhances the reliability of analytical and numerical design by improving the definition of soil parameters and boundary conditions.

With DAARWIN, derived parameters such as stiffness, undrained shear strength, or unit weight can be systematically extracted from laboratory results and integrated into finite element or limit equilibrium models. This consistent data flow reduces the uncertainty associated with input selection and minimizes iteration cycles during design calibration.

By linking geological interpretation with computational modeling, DAARWIN enables engineers to progress from descriptive to performance-based understanding of the ground — closing the gap between field data and analytical validation.

Enhanced Visualization for Subsurface Interpretation

Accurate visualization is essential for verifying geological interpretation. DAARWIN’s ground modelling and visualization module provides a spatially coherent representation of the subsurface, integrating borehole, laboratory, and monitoring data within a single digital environment.

• Cross-sections and longitudinal profiles are automatically generated from structured data.

• Material zoning follows standardized classification systems for clarity and reproducibility.

• Engineers can compare campaigns, detect anomalies, and visualize data trends across project phases.

This interactive representation enhances coordination between geologists and designers, supporting more informed decisions during model calibration, design verification, and construction monitoring.

Quantifiable Improvements in Workflow and Reliability

The integration of automated geological logging produces measurable engineering benefits:

• ≈97% accuracy in digitalization and automated data extraction and classification.

• Up to 70% reduction in time dedicated to data preparation and verification.

• Improved reproducibility, ensuring consistent results across revisions and users.

• Comprehensive traceability, linking every dataset to its original source.

In practice, these improvements accelerate design delivery, improve documentation quality, and significantly reduce uncertainty during parameter calibration and performance validation.

Towards Adaptive Ground Models

As the geotechnical field advances toward real-time and performance-based design, the ability to continuously update ground models becomes critical. DAARWIN’s architecture supports the integration of monitoring data, allowing soil parameters to be recalibrated through back-analysis as construction progresses.

This approach promotes the development of adaptive ground models — digital representations of the subsurface that evolve with new information, enabling continuous comparison between predicted and observed behavior. By bridging data management, analysis, and performance monitoring, DAARWIN contributes to the broader vision of data-driven, adaptive geotechnical design.