Wellbore Petrophysics

Effortlessly coordinate automated and enhanced algorithm pipelines, to enable streamlined well data processing and interpretation.

Overview

Effortlessly coordinate automated and enhanced algorithm pipelines, to enable streamlined well data processing and interpretation.

Wellbore Interpretation’s strength lies in its scalability; it can handle data volumes of any magnitude, while maintaining rapid delivery of results. This flexible solution equips you with the adaptability and effectiveness required for success. The workflows are enriched with Techlog domain workflows, which are rich in scientific depth and seamlessly integrated.

Make better decisions with cloud-based applications, designed to automate log quality assurance, conditioning, and interpretation to accelerate your subsurface knowledge acquisition.

Unlock the power of your domain workflows, tailored to meet the interpretation needs of diverse environments. Whether it's open or cased holes, our solution supports both standard and advanced logs, catering to multi-well and single-well evaluations. Rest assured, your interpretations will be rigorously validated by an array of QC tools. Plus, with our comprehensive suite of rock typing and log reconstruction modules, your options for analysis are further enriched

Capture knowledge

Parameter Augmented Learning

Our solution tracks interpretation parameter lineage, providing automated guidance for parameter optimization that helps geoscientists fast-track the interpretation of new data or review of previous results based on interpretation knowledge previously validated in the basin.

Wellbore - Parameter Augmented Learning

At a glance, see how a user can gain a comprehensive understanding of the accomplishments and outcomes achieved in prior interpretations, and rapidly access knowledge from past experiences.

Cognitive tools to explore the data

Track interpretation parameters used in the past to accelerate the initialization of formation evaluation workflows.

Share interpretation results and collaborate

OSDU™ Data Platform

A Techlog wellbore software user's interpretation is liberated to the Delfi platform ready to be shared and aid collaboration through the OSDU Data Platform.

Full field development solutions icon, blue

Increase efficiency of future interpretation

OSDU™ Data Platform

Target well analysis of interpretation parameters and push-back to Techlog software for faster model creation aligned with previous results with the OSDU Data Platform.

Accelerated decision-making

Wellbore Interpretation

Wellbore interpretation represents a groundbreaking, interactive method for leveraging wellbore data, harnessing the capabilities of intelligent data discovery through advanced AI/ML algorithms to achieve 2D/3D contextualization. It enables to Access Data from the entire basin and automate Log and marker conditioning using cloud-based machine learning algorithms and easy share with Techlog and Petrel for seamless collaboration and data flow.

Wellbore interpretation enables rapid decision-making on both wellbore and field scales within an adaptable collaborative environment. By utilizing machine learning to conduct cloud-based wellbore interpretation we enable interpreters to dedicate time to what really matters; simple integration with existing petrotechnical solutions.

Groningen Onshore: Log conditioning

This video illustrates log conditioning, starting with the creation of a workspace that triggers the log conditioning workflow. The computation is scaled using the power of the cloud to perform log conditioning steps including family assignment, unit correction, first and last reading, best log selection, outliers' detection, splicing up to composite log creation.

Moreover, the interpretation includes data QC and flagging of bad holes and out of bounds errors. A confidence factor is then computed to assess the composite log quality. User can create surface to review the distribution of the quality on the map.

Wellbore - Groningen-Onshore: Log Conditioning

This video illustrates log conditioning, starting with the creation of a workspace that triggers the log conditioning workflow.

Elements of log conditioning

Family assignment

Compute confidence in family assignment
Improve log recognition from 89.3% to 100%
Minimize wrong log assignment

Unit conversion

Select the most represented unit (clustering machine learning logs with wrong units can be identified)

Outlier detection

Remove values which are not physically possible

Bad hole flags

Calipers, rugosity and bulk Density Correction

Clean first/last reading

Detect and clean wrong first and last reading

Best log selection and splicing

Select log sets to be used for splicing algorithm, enables identification of the log sets with the maximum diversity of families

Log resampling and splicing

Resample to the most represented sampling rate
Minimize values editing while resampling
Provide uncertainties envelop (min/max)

Log uncertainly

The composite log's quality (%) is the average of best log r, outliers and coverage quality measures

From raw to composite

Go from raw logs to composite logs

Harness the power of cloud

BatchElan

With BatchElan , leverage the capabilities of elastic cloud computing to perform detailed and complex lithologic qualitative evaluations, handling a multitude of mineral inversion models across numerous wells and interpretation zones, while reducing the turnaround time from hours to minutes, mitigating uncertainty, and enhancing the decision-making process, empowering users to make more informed and assisted choices with a higher degree of confidence.

BatchElan is anchored on two pillars: