Quick Time to Value

ROI Case Study: Gas Lift Hole in Tubing

A hole in tubing for a gas lift operation is pretty difficult to detect before it happens; therefore, today’s case study is particularly interesting.  Note, in a previous blog on early event detection, we mentioned that our solution can examine calculated sensors. In the demonstration table above, we have readings
Quick Time to Value

ROI Cast Study: Gas Influx

In today’s example case, we are looking at the early detection of gas influx. This is an ESP sub-optimal state. In the demo slide above, we are looking at sudden fluctuations in amperage and tubing pressure. There is an increase in casing pressure as we can see.  At the end
Quick Time to Value

ROI Case Study: Early Event Detection of Tubing Failure

Tubing Failure Early Event Detection of a tubing failure can help you regain $3M or more in your oilfield.  In this example, we examine rod pump #10 and an example of its tubing failure. With OspreyData’s Production Intelligence solution, we are able to look at sensor data such as casing
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Jon Snyder Colorado school of mines digital oilfield unified monitoring
Company News, Events

Jon Snyder Recently Spoke at Colorado School of Mines

OspreyData’s Customer Engagement Manager, Jon Snyder, had the pleasure to present at his alma mater, Colorado School of Mines. The Mines’ Petroleum Engineering department recently started a Petroleum Analytics program to enhance students’ ability to analyze large sets of data specific to the oil and gas industry. Jon spoke of some of the
Quick Time to Value

Traditional vs. OspreyData Failure Detection Timelines

Failure detection timelines really help us drive home the point of how OspreyData’s Production Intelligence solutions can maximize your production even in the face of inevitable failures.  In the graphic above, we demonstrate the difference between the traditional failure model verses our early detection model.  Below, we explain the difference
Predictive Analysis

Event Detection: What Kind of Events Can AI Detect?

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
Production Optimization

Proactive Organization: Where AI Can Take You

For an operator, each day brings a different set of challenges as you look to improve your production and boost your profitability.  Here at OspreyData, we are firm believers that you can use data in order to more efficiently tackle your daily workloads.  That data helps you transform from being
Petroleum Expertise

Solving Problems Faster: Challenges for Operators & Engineers

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
Quick Time to Value, Unified Monitoring

Production Engineer Eric Clour’s Personal Testimony on Using UNIFIED MONITORING

With some key objectives in mind, we have developed a set of building blocks. We believe an effective monitoring solution must have robust abilities that can do the following: Visualize, annotate and track complex time series sensors across devices and lift types Construct and configure meaningful, actionable dashboards and reports