Data Integrity

Rig data is often cleaned separately by every application. This article proposes one governed quality service that preserves raw evidence and serves trusted data.

Every data path in this series crosses the OT/IT boundary. How to protect the rig's network as models and data cross it, without opening a backdoor to control.

A practical architecture for shifting drilling RTOCs from continuous screen watching to contextual anomaly detection, human adjudication, and governed response.

How a rig-side data fabric can preserve useful high-frequency data, run engineering analytics locally, publish contextualized WITSML outputs, and support governed federated learning.

How Modbus, OPC UA, and edge computing turn high-frequency rig data into control-floor decisions, and why drilling still lacks a common control-layer standard.

WITS, WITSML, ETP and OSDU each do a different job for drilling data. Here is what each one standardizes, and why the data layer, not the algorithms, is the real foundation beneath drilling autonomy.

Every real-time drilling model, from torque and drag to hydraulics to the rig-state classifiers feeding the digital stack, needs to know exactly what is in the hole. That answer lives in the bottomhole-assembly record, and on most rigs it does not arrive until the company man closes the morning report, hours after the string is already downhole. The models run anyway, on assumptions, and every answer inherits the uncertainty.

In drilling operations, data is only as useful as the standards it is built upon. Two of the most consequential - yet frequently overlooked - factors in drilling data quality are the use of proper data formats and the selection of appropriate data recording frequencies. WITSML (Well Information Transfer Markup Language) provides the industry-standard framework for structuring and exchanging drilling data, while data frequency determines how granular and actionable that data t

In modern drilling operations, data flows from a wide range of sources simultaneously - surface sensors, MWD/LWD tools, mud logging units, lab analysis, and third-party systems. Each of these sources generates critical information, but their true value can only be unlocked when they are properly synchronized and integrated into a coherent picture of what is happening in the wel The Challenge: Data Lives in Silos One of the most common data integrity problems in drilling is no