ABOUT SEEQ CORPORATION

Seeq® is an advanced analytics solution for process manufacturing data that enables organizations to rapidly investigate and share insights from data in historians, IIoT platforms, and database web services—as well as contextual data in manufacturing and business systems. Seeq’s extensive support for time series data and its inherent challenges enables organizations to derive more value from data already collected by accelerating analytics, publishing, and decision making. With diagnostic, monitoring, and predictive analytics powered by innovations in big data and machine learning technologies, Seeq’s advanced analytics solutions help organizations turn data into insights to drive process improvement and increase profitability. 

 
5 Questions To Ask Before Selecting A Process Data Analytics Solution   Leveraging Predictive Analytics: A Case Study    

5 Questions To Ask Before Selecting A Process Data Analytics Solution

 

Leveraging Predictive Analytics: A Case Study

 

 

FEATURED PRODUCTS

Organizer is Seeq’s application for engineers and managers to assemble and distribute Seeq analyses as reports, dashboards, and web pages.

Workbench is Seeq’s application for engineers engaged in diagnostic, descriptive, and predictive analytics with process manufacturing data.

CONTACT INFORMATION

Seeq Corporation

1301 2nd Avenue Suite 2850

Seattle, WA 98101

UNITED STATES

Phone: 206-801-9339

Contact: Jennifer Bentzel

SEEQ SOCIAL MEDIA

        

FEATURED ARTICLES

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, today announces the launch of a new program, the Seeq SaaS Workshop.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announces the release of R52 with new features to support the use of machine learning innovation in process manufacturing organizations.

  • Learn how to leverage data to implement proactive approaches to manufacturing issues through the use of predictive analytics.

  • At many process manufacturing operations, bearings fail exponentially and with little notice, leading to downtime that can become expensive and making scheduled maintenance difficult. System interdependence often means that a failure of one bearing results in the subsequent failure of other system bearings. Being able to prepare for and prevent the first bearing failure can reduce the costly and harmful effects of unplanned bearing failures.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announced today it has closed a $50 million Series C funding round, led by global venture capital and private equity firm Insight Partners. The round includes participation from existing investors Altira Group, Chevron Technology Ventures, Cisco Investments, Saudi Aramco Energy Ventures, and Second Avenue Partners. This round brings Seeq’s total funding since inception to approximately $115 million.

  • Manufacturing sites have many automatic controllers (typically in the hundreds or even thousands for large facilities). These controllers are designed to run in automatic mode without operator intervention. Most sites don’t have insight into how these controllers are actually performing. 

  • Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, announces a new packaging of Seeq features and applications as Seeq Team and Seeq Enterprise editions.

  • Seeq, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, and 2020 Microsoft Partner of the Year Finalist, announced today it is co-sponsoring the Microsoft Energy Core Methane Emissions Hackathon virtual event on March 1-8, 2021.

  • Performing a mass balance on manufacturing sites process units (or the overall plant) is critical for identifying a number of issues, including leaks, faulty sensors, meter calibration issues, process inefficiencies, and more. Unfortunately, the plants that do perform mass balances likely use a method that is difficult to maintain and does not update as new data is available for continuous monitoring.

  • It is critical for oil and gas companies to understand how productive their wells are, and when it is time for decommissioning. The Well Productivity Index is a valuable measure of individual well health, but it is difficult to scale to the number of wells owned, which typically number in the thousands for each operator.

  • In oil sands, on adjacent wells, there is potential for materials to move between wells (“well interaction”). Goal is to detect and take action on well communication

  • Salt deposition in crude and FCC fractionator overheads and hydroprocessing effluent trains can lead to various operational problems. It is critical to identify when the unit is operating in a condition with a high risk of salt deposition. If unmitigated salt deposition occurs, it can lead to an increase in corrosion and equipment fouling/plugging. This can cause loss of integrity, leading to potential process safety and economic risks. 

  • Blowout preventers (BOPs) are assemblies of valves, hydraulics, and electrical devices used to prevent the uncontrolled release of oil or gas. They are deployed on both land and ocean drilling rigs, secured to the wellhead at the top of the wellbore.

  • Pipeline operators face a constant balancing act of running their pipelines while protecting the environment from oil spills caused by a rupture. A sudden low-pressure event might indicate a pipeline rupture that threatens the environment. To minimize environmental impact, operators set parameters for low-pressure conditions that would cause a hard shutdown, or lockout. Lockouts can last for hours or days, greatly impacting the pipeline’s revenue.

  • Upstream oil collection networks have emergency shutdown systems to protect against damage; however, when the trip activates, rapid valve closure can cause water hammer to occur. This can cause mechanical damage to the system, vessels and/or cause relief valves or rupture disks to blow, with safety, reliability, and environmental impacts. The challenge faced by oil and gas operators is being able to proactively detect where water hammer happens to focus re-engineering of emergency shutdown (ESD) and equipment. This improves ESD valve and system design, to "build in" long-term improvements and eliminate the problem.

  • Drilling is critical for oil and gas exploration companies, which typically use third-party contract drillers to do the work. The service providers often preconfigure the depth and speed of the well-bore path via an auto-driller system that controls the process with occasional human intervention. However, many variables relating to the mechanical equipment and geology can cause unplanned vibrations. It can be difficult to communicate the best approach to the drillers, which tend to use default settings for holding a specific drill speed for long periods of time, which can be suboptimal. If left unchecked, sustained vibrations can damage the drilling rig, leading to costly repairs and delays.

  • Valves are one of the most common assets in the process industry, spanning all verticals. Chemicals, refineries, and petrochemicals, however, will find improved valve health diagnostics useful for critical valves and controllers in their plants, while upstream and midstream oil and gas companies may be focused on much larger, critical valves like pipeline or subsea valves. Using Seeq, process manufacturers are able to implement a condition-based monitoring analysis to monitor valve health across an entire fleet. Engineers can utilize the historical data to accurately create a predictive maintenance forecast and preemptively detect valve failures before they occur.

  • How Seeq allows navigation to past production runs to find past production settings and visibility into the relationship between the production settings and key process KPIs, like quality or production rate.

  • All manufacturing industries suffer a variety of different performance losses including production losses, product quality losses, energy losses, raw materials losses, environmental/regulatory losses and others. These losses can negatively impact profitability, environmental stewardship, and even license to operate. A manufacturer needed a way to gain insight into the leading causes of production losses, finding those times when equipment was not running at capacity and categorizing the loss by reason. 

  • Highly-efficient and improved facility operations require the management of chemical and energy usage to ensure that both air and water quality meet goals while minimizing cost. It can be difficult to attain this level of productivity within a comfortable working environment while avoiding the excessive use of chemicals and energy. Excess chemical use and energy consumption mean reduced profits. Solutions are necessary to allow for maximum operation efficiency.

  • In order to raise efficiency and production standards, it is important to be able to analyze the performance of batch processes and identify time spent in each of the different process phases. Increased visibility into unproductive process time (for example during cleaning and maintenance and shift v shift differences in manual re-cleaning events) is necessary in order to enable users to take actions to reduce them. With the ability to increase production opportunities when reducing waiting times, overall profitability can also increase. 

  • Engineers and subject matter experts within operations settings are tasked with driving operational excellence to improve quality, safety, and throughput in production operations. The new technologies proliferating as part of Industry 4.0 initiatives are raising and expanding performance expectations. Rapid, data-driven insights are becoming critical to balance resiliency and agility with efficiency. As an IT professional, supporting these efforts is imperative as operations leaders grapple to get the most out of investments in technologies that generate and use large volumes of data.

  • Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, and an AWS Industry Software Competency Partner, announces expanded support for Amazon Web Services cloud services.

  • Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, today announced it has been named a finalist for the Energy 2020 Microsoft Partner of the Year Award.

  • Monitoring control valve health and performance before situations reach crisis stage is an important aspect of managing oil and gas operations. Decision makers can gain better insights when using advanced analytics solutions that accommodate multiple forms of process industry time-series data to benchmark performance patterns. Consider these factors when searching for a better approach to control valve maintenance.

  • Despite the availability of advanced software, spreadsheets are still the default data analytics tool for operations managers at many municipal water systems and water distribution companies. However, an investment in analytics technology can pay for itself quickly by providing a relatively easy method to extract process data from various sources and then by performing an analysis to provide answers to previously difficult questions.

  • Advanced analytics is a key innovation for digital transformation. While many industrial companies are rolling out pilots and enterprise analytics projects, it is important for users to understand the features and capabilities of the analytics offerings.

  • Many oil producing wells require an artificial lift to increase the flow of fluids as the reservoir pressure is not high enough. Typically, electrical submersible pumps (ESPs) are used, but these pumps are not always operating efficiently and can cause costly downtime for operators. To avoid costly downtime operators must be able to detect events where flow drops, indicated by wellhead temperature drop, combined with motor amp and tubing choke data.

  • In some cases, natural gas flows are not corrected for variations in pressure and temperature. Where this occurs, the meter used to charge customers may read zero flow (“high-zero”) even when a small volume of gas is flowing through the meter.

  • Multi-phase flow meters are important for well surveillance and production allocation where there is multiple ownership. It is therefore important to track the accuracy of multi-phase flow meters, identify issues and ensure rapid corrective action. Read more to learn how the Seeq tools were used to analyze and monitor performance.

  • Gas is injected into wells to increase production. Due to the geographical distribution of wells there are a large number of compressors (over 140 units) which need routine monitoring by a small number of staff. Read more to learn how early detection of compressor operating problems allows operating condition adjustment and improved maintenance planning leading to lower maintenance costs and less production losses.

  • Liquid hydrocarbons are stored at a tank battery after removal from natural gas. The amount stored varies on the production rate from the well gathering stations. In cases where no pipelines exist, it is necessary to move the liquids to another site by truck. The challenge is to minimize the number of truck hauls, logistics contracts are a business cost, while preventing tank overfills. The analytics developed enabled optimization of truck hauls by scheduling truck hauls in the logistics system based upon the real-time process data at the tank batteries.

  • Data analysis is changing the landscape of the oil and gas industry. Operators are turning to the power of data to identify operational upsets throughout the field. Separation is one of the cornerstones of upstream operations. When separation problems occur, leading to gas blowby and liquid carryover, engineers need to be alerted of the situation so that they can correct it. Coriolis meters are frequently used because of their ability to tolerate sand, debris, and gas coming out of solution.

  • Are you challenged with managing the severity of reactor operation on a fixed-bed reactor and planning catalyst regeneration or replacement? It is important to analyze the catalyst activity and predict the end-of-useful life for the catalyst in order to optimize near and long-term economics. This process requires the calculation of normalized weighted average bed temperature, selecting historical data to “train” the correlations, and auto-updating with new data.

  • Predicting end-of-cycle (EOC) for a heat exchanger due to fouling is a constant challenge faced by refineries. Proactively predicting when a heat exchanger needs to be cleaned enables risk-based maintenance planning and optimization of processing rates, operating costs, and maintenance costs. Read more to learn how utilitzing the Seeq Formula Tool to monitor heat exchanger performance in the place of time-consuming spreadsheets will eliminate weeks of work for engineers, freeing them up to perform other valuable company tasks.

  • Production engineers are challenged on a daily basis with analyzing well performance. Due to disparate, non-integrated data sources this task can be very difficult and time consuming.

  • Wells require a significant amount of engineering to properly maintain, and it can be difficult to ensure that their complex completion design and spacing are optimized. This can be a drawn-out process with room for human error, as calculations are typically performed manually on paper in order to identify notable treating pressure changes over time. Read more to learn about eliminating manual data entry and dramatically shortening analysis time, leading to increasing process efficiencies.

  • Unmanned well sites in remote locations present operational challenges. Data must not only be collected, but it also must be monitored to uncover any discrepancies, and ideally predict any problems before they occur. Advanced analytics software, coupled with a sophisticated data collection system, can address these issues, and also provide additional benefits.

  • The oil and gas industry, like many others, is collecting and storing ever larger volumes of data. Although, there is value in this data, it is often difficult to unearth using conventional analysis tolls such as spreadsheets. To address this issue, new data analytics software platforms are being introduced specifically to deal with time-series data.

  • The data generation and collection strategies at the center of manufacturing processes have evolved dramatically, especially in recent years. Process manufacturers now collect and store huge volumes of data throughout their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos. In this paper, we propose five questions we believe every process manufacturing buyer should ask when evaluating a data analytics solution.

  • Often the first notification of a spill comes from a member of the public, hours and sometimes days after the first spill. This can intensify public health and environmental impacts and the cost of clean-up efforts. Following a sewer spill at an environmentally significant site at Midway Point in August 2017, TasWater sought a way to reduce the likelihood and impact of spill events occurring in the future.

  • Businesses rely on process units meeting or exceeding their operational plans. To ensure that operational plans are achieved, it is important that equipment operates as designed (i.e., delivers the required performance) and continues to operate in an optimum manner (i.e., remains reliable, in a good condition). The most common causes of missing operational plan targets are equipment failure, which results in unplanned downtime, and low quality or yields from production processes.

  • The prime reason most industrial plants still have internal, on-site maintenance staffs is to reduce repair times and unplanned downtime, which negatively impact revenue, customer satisfaction, cost, and other key business metrics. In most plants today, contracting with the equipment manufacturer for maintenance usually results in unacceptably long periods of downtime for critical equipment while waiting for a technician to arrive – particularly with the typical two passes required for inspection and repair.

  • At ARC Advisory Group’s 20th Annual Industry Forum in Orlando, Florida, Shawn Anderson, Senior Research Specialist for Fisher Valves, a division of Emerson Process Management, gave a presentation on how the company is leveraging the Industrial Internet of Things (IIoT) to help end users reduce valve-related unplanned downtime.