There are many terms and definitions thrown around in the AI and ML space that it can be confusing even to trained data scientists. We have used many of these terms around our website. It may be helpful to define these terms to ensure we’re clear on all of the

Artificial Intelligence in Oil and Gas has become a very popular topic. MIT’s Sloan School of Management’s article, “Reshaping Business with Artificial Intelligence,” recently found that that 85% of corporate executives surveyed believe that AI will help their businesses gain or sustain competitive advantages. What might that look like for

The impact of Artificial Intelligence on an organization is an important topic when considering machine learning.  In a previous blog entitled, What Artificial Intelligence in Oil and Gas Brings to Production, we discussed a summary of key solutions that AI can target for problems facing most oil and gas organizations

A major challenge has been to foster cooperation between two groups with such different skills and backgrounds, O&G operation and data science. Failure of many projects is due to failure of collaboration of these groups to understand one another to achieve shared objectives. Data science often thinks models can be

In Artificial Intelligence(AI) and Machine Learning (ML), a model replicates a decision process to enable automation and understanding. AI/ML models are mathematical algorithms that are “trained” using data and human expert input to replicate a decision an expert would make when provided that same information. Ideally, the model should also

Artificial Intelligence in Oil and Gas is becoming a very popular topic. MIT’s Sloan School of Management’s article, “Reshaping Business with Artificial Intelligence,” found that 85% of corporate executives surveyed believed that AI would help their businesses gain or sustain competitive advantages. What does that look like for oil and

When it comes to event detection, a common question we receive is, what kind of events can AI detect?  We sub-categorize these events of interest into four different types: 1) High-Risk Events, 2) Sub-Optimal States, 3) Events Needing More Lead Time, and 4) Silent Killers. We will explain these event

We asked a Production Engineer what “a day in the life” is like, and what are common challenges that are faced as an operator or engineer. This P.E. was responsible for  300 to 400 wells, predominantly rod pumps at one producer and then ESP’s at another. What were some of

Moving to a digital oilfield is a critical enabler for producers in oil and gas. A critical focus is now on reducing operating costs, increasing employee productivity, and improving the ability to make informed and timely data-based decisions. For most oil and gas companies, the goal is clear, but the