AI for reading composite logs like a geologist?

Composite logs are useful but unstructured

For geologists, the composite logs are a key document to model the subsurface. They synthesize observations done while drilling and measurement performed in the open hole sections.

Unfortunately, the composite logs are frequently saved under unstructured formats such as PDF or graphic files, therefore, they cannot be used in any digitalized interpretation process unless they are reformated manually.

What AI has to do to read composites as a geologist?

Reading a composite log is complex. The information to be captured is graphical such as the lithological intervals or the hydrocarbon show symbols but also textual such as the geological descriptions. In addition, the information is displayed along a vertical depth axis to be recognized in order to link together the pieces of detected information

A unique interface and workflow to capture various information

The iQC platform authorizes to train and use computer vision and text analysis tools in the same workflow and in a unique Graphic User Interface. 

All the models are built, benchmarked and applied without coding, just by capturing the user experience in the GUI.

Extracted data are made available along a depth axis

iQC not only detects and classifies the graphical and textual information but also links the information together. In the case of composite logs, the unique index linking the lithology, shows and geological description is the well depth. Therefore, all detections are converted to depth prior to being exported using structured formats

Actionable data

Once structured the information becomes actionable data. The lithology and the shows of all the wells of a geological basin can be analyzed to detect patterns which could not be detectable without having access to thousand of lithological intervals, shows or descriptions.

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