Analytics
Figure: Rate-predictive control (RPC) uses a pre-set move rate, and tapers the move based on the PV’s predicted (apparent or already manifest) value. The U.S. Patent and Trademark Office (USPTO) has hundreds of patents for process control; as of this writing, RPC is the only one with the claim of being inherently adaptive. Courtesy: APC Performance LLC
Analytics March 26, 2019

What is rate-predictive control?

Advanced control: A new non-PID control algorithm, rate-predictive control (RPC), is adaptive to changes in process gain, which is helpful given the industry’s difficult history of loop tuning, auto-tuning, and model maintenance. RPC also can serve as a model-less feedback multivariable control algorithm.

By Allan Kern
Analytics February 8, 2019

AI application developers target well-site production optimization

Solutions range from predictive maintenance to artificial lift improvement.

By CFE Media
Predictive analytics as a service (PAaaS) will be the means to predict equipment breakdowns and downhole events such as liquid loading. Courtesy: eLynx
Analytics February 5, 2019

Predictive analytics in the upstream introduced as a service

Solution identifies production and equipment problems before they become apparent.

By Kevin Parker
Figure 1. Artificial intelligence is being applied to pipeline management based on its ability to identify patterns in data that are not always intuitively obvious to humans. Courtesy: OneBridge
Analytics February 4, 2019

With AI, zero failure is more than a pipe dream

Improve confidence with a complete view of data.

By Tim Edward and Rob Salkowitz
Figure 2. Providing subject-matter experts with visual representations of data allows them to interact directly to solve problems. Courtesy: Seeq
Analytics January 29, 2019

Basic steps to take when applying analytics processing

Upstream oil & gas operations improved using data analytics.

By Michael Risse
Figure 1. The network architecture supports groups of field instruments and actuators using mesh communication to support reliable data transfer. Each device acts as a data originator and potential relay point. Courtesy: Emerson Automation Solutions
Analytics October 29, 2018

Bring IIoT capabilities to refineries and process plants

The first step to bringing fieldbus networking and the Industrial Internet of Things (IIoT) into process manufacturing plants and refineries may be changing device-level networking practices.

By Dan Carlson
Courtesy: Niresh Behari
Analytics October 9, 2018

Growing role of human/machine interaction in risk management

A risk management evaluation for safety-critical equipment (SCE), including use of a risk matrix, is fundamental to controlling operating hazards, but even proven industry hazard determination templates won’t work with outdated data.

By Niresh Behari
Figure 1. By implementing a well data management system, producers increase efficiencies while reducing time-to-revenue. Courtesy: Micotan Software
Analytics October 1, 2018

Manage information based on each well’s lifecycle

A single source of truth can improve time-to-revenue.

By Frank Gannon
Figure 3. Optimization cycle. Courtesy: Stress Engineering Services
Analytics September 28, 2018

Digital twins support FPS asset integrity management

Strength comes from global performance model integrated with measured data.

By Scot McNeill, David Renzi, and Dilip Maniar
Analytics September 28, 2018

Asset platform for enhancing process manufacturing applications

TrendMiner's ContextHub is built around the structure of OSIsoft PI Event Frames and Asset Framework and is designed to broaden contextual information for root cause analysis and operational performance monitoring.

By TrendMiner