5 entries found for "Data Management"

  How to practically implement RBI for oil and gas production, gathering, and midstream facilities in the United States.

by Michael Hurley, 3/11/2026

Tags: API 580 API 581 Asset Performance Management Consequence Corrosion CUI Damage Mechanisms Data Collection Data Management Data Validation HSE Inspection Integrity Operating Windows Mechanical Integrity Process Safety Management Regulation Reliability Risk Analysis Risk Based Inspection Risk Management System Implementation Technology Work Process

This document presents a practical framework for implementing Risk-Based Inspection (RBI) and Mechanical Integrity (MI) programs for U.S. oil and gas production, gathering, and midstream facilities. It outlines lifecycle asset management practices aligned with API 510/570/653, API 580/581, PHMSA pipeline safety rules, and OSHA PSM to prevent loss of containment, detect degradation early, and maintain safe, reliable operations.

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  What Do Good Refining Corporate Cultures Look Like?

by Michael Hurley, 2/8/2026

Tags: API 580 API 581 Asset Performance Management Data Management HSE Human Factors Mechanical Integrity Process Safety Management RBMI Reliability Risk Risk Management Technology Training Value Work Process

In the refining industry, "culture" is often only analyzed after a failure occurs. However, a robust culture is defined by observable, repeatable behaviors and daily decisions made under pressure. This article outlines the seven practical attributes of high-performing refining organizations and demonstrates how alignment between leadership values and technical integrity creates a safer, more profitable operation.

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  Leveraging AI to Accelerate Data Collection in Risk-Based Inspection Projects

by Stephen Elmer, 10/27/2025

Tags: API 580 API 581 Data Analysis Data Collection Data Management Data Migration Data Validation Risk Based Inspection Technology Value

Data collection is an RBI project bottleneck, often taking a very significant percentage of total effort due to manual interpretation of old, varied engineering documents. AOC developed AI-driven tooling to automatically extract, classify, and normalize this data, achieving a very high accuracy and significantly streamlining the process for faster, more reliable RBI implementation.

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