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New Pressure Sensor Technology for Offshore Oil and Gas Applications

Author: Chip Bremer

Emerson's David Andrew

David Andrew

At the May 6-9 Offshore Technology Conference, Emerson’s David Andrew will discuss a new pressure sensor technology that could have a significant impact in a variety of offshore and downhole oil and gas applications.

Paine 420-22-0010 Series Pressure Transmitter

The single crystal integrated capacitance sensor is the key technology in Emerson’s Paine 420-22-0010 Series Pressure Transmitter

The single crystal integrated capacitance sensor, a key technology in Emerson’s Paine 420-22-0010 Series Pressure Transmitter, is a highly reliable pressure sensor that has the potential to reduce costs and increase yield in offshore exploration and production. Its ability to stabilize rapidly to thermal effects while exhibiting excellent long-term drift behavior make it ideal for use in subsea and offshore environments.

To demonstrate its capabilities, this new sensor was subjected to a series of qualification tests in comparison to other industry-leading technologies.

David notes: Continue Reading

Podcast: Driving Operational Improvements in the Energy Industries

Emerson's Sudhir JainEmerson’s Sudhir Jain joins us in this FIRSTHAND Operational Certainty in a Pod podcast as a follow up to our earlier 5 Questions for an Emerson Expert podcast with Sudhir.

As an Operational Certainty consultant, he shares some of the oil & gas applications for operational improvements and describes how he works with clients to improve overall performance and sustain it over time.

We hope you’ll enjoy this episode and will consider subscribing to the whole FIRSTHAND: Operational Certainty in Pod series on your iOS or Android mobile device.


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Integrated Upper and Lower Completions Downhole Solution

The drilling and reservoir management side of upstream oil & gas exploration and production has relied on downhole sensors to help optimize these downhole operations. As technology has advanced, so has the level of information available to improve real-time decision making.

One example is the recent news release, Downhole Reservoir Network First to Connect Wireless Sandface Data to Upper Completion for Optimized Production. It describes a partnership between Emerson and Metrol on an Intelligent Multistage Completion Network (IMCN) solution. It is:

…an integrated upper and lower completions downhole solution that communicates wirelessly with instruments at the reservoir sandface, the physical interface between the formation and the wellbore.

Emerson’s Geir Aanensen explains:

For many operators, the sandface and lower completion have simply been considered ‘off limits’ for acquiring accurate multi-zone information’ – too much risk, too costly and too complex… With our new wireless interface that enables connection to sandface data and flow control instruments from Metrol, operators will have unrivalled insights into the reservoir’s flow characteristics, access to valuable data and the ability to optimize reservoir production management. Combining Roxar and Metrol technologies will ensure highly efficient well and reservoir management, while providing a life-of-well, permanent hybrid silicon on insulator (HS) gauge installation.

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Optimizing Hydrocyclone Separation Processes


Diagram of a hydrocyclone:
1. the liquid-solid mixture enters,
2. heavy solids leave,
3. cleaned liquid leaves.
Photo credit: “hydrocyclone” by VanBuren is licensed under CC BY 3.0

In the mining industry, hydrocyclones are mineral processing equipment used in slurry pulps to separate coarse and fine particles according to their size and density. From Wikipedia:

The mixture [slurry pulp] is injected into the hydrocyclone in such a way as to create the vortex and, depending upon the relative densities of the two phases, the centrifugal acceleration will cause the dispersed phase to move away from or towards the central core of the vortex.

Coarse particles exit the bottom of the device (underflow) while fine particles are carried by the central air column and exit at the top (overflow). In metal processing applications, the product stream is the overflow (fine particles) and is typically sent to flotation circuits. In coal and iron processing, the product stream is the underflow (coarse particles), as fines are separated from the final product as a means of quality control.

I connected with Emerson’s Cristián Doerr in the Mining Center of Excellence about Hydrocyclone Optimizer technology to improve separation efficiency and increase reliability.

Cristián noted that under certain conditions roping and plugging can occur where the hydrocyclones ceases to classify the particles. The shapes of the discharge are visibly different than normal operating conditions.

The roping condition occurs when the amount of solids in the underflow increases to such a point that its discharge velocity is limited, resulting in the accumulation of coarse solids in the separation chamber. This mass passes through the vortex, causing the inner air core to collapse and the discharge at the apex to take the form of a solid stream (rope) consisting of coarse material with high solids density. Roping conditions reduce recovery rates and efficiency in metals processing and lead to quality losses in coal & iron processing.

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Award-Winning Rock Type Classification with Machine Learning

Author: Samhita Shah

2019 Hart Energy Meritorious Awards for Engineering (MEA) InnovationThe results are in! Emerson’s Rock Type Classification (RTC) with Machine Learning has been announced as the winner of the 2019 Hart Energy Meritorious Awards for Engineering (MEA) Innovation in the category of Exploration/Geoscience. The MEA program recognizes new products and technologies that demonstrate innovation in concept, design and application.

“Our magazine and its predecessors have consistently honored technical innovation that allows our industry to overcome seemingly impossible challenges,” said Jennifer Presley, Executive Editor of E&P. “The Meritorious Awards for Engineering Innovation reflect the best of the best in technological advancement.”

Rock Type Classification with Machine LearningThe Rock Type Classification with Machine Learning application combines the latest innovations in geoscience, algorithms and statistical models to help oil and gas operators overcome the limitations of traditional methods for predicting facies and rock types from seismic data.

Earlier solutions deployed deterministic or stochastic seismic inversion methods to offer a first level approximation to a facies or rock type model. Unfortunately, such approaches suffer from non-uniqueness, lack the resolution required to accurately predict thin beds or intermediate-type facies, and frequently fail to model the high degree of heterogeneity that characterizes many oil and gas reservoirs. Continue Reading