FEATURED ARTICLES

• Seeq Announces Partnership With Databricks To Accelerate IT-OT Data Convergence Across The Enterprise

  Seeq Corporation, a leader in advanced analytics for manufacturing, today announced a partnership with Databricks, the data and AI company, that brings a native integration between each company’s platform to​ simplify access to high quality asset and process data, unify IT and OT data processing and accelerate AI/ML adoption across the industrial manufacturing, pharmaceuticals, chemicals and energy sectors.​​ 

• Upcoming Webinar: People Transformation: A Practical Guide To Skilling Up People And Integrating Analytics To Deliver Business Value

  This webinar will explore some of the most common challenges companies have faced regarding skill up and how to navigate using datapoints derived from 100+ successful Seeq analytics training rollouts.

• Advanced Analytics Enable Process Manufacturers To Achieve Sustainability Goals

  Advanced analytics software offers a solution to chemical manufacturers who rely on statistical process control (SPC) charts for process monitoring.

• 5 Questions To Ask When Selecting An Advanced Analytics Solution

  New advanced data analytics have a huge positive impact on the growing volumes of data in many sectors. Learn how to leverage these new analytics in process manufacturing.

• Seeq Recognizes Its 2022 Reseller And Service Partners Of The Year

  Seeq Corporation, a leader in manufacturing and industrial internet of things advanced analytics software, announced its 2022 Reseller and Service Partners of the Year.

• A Guide To Advanced Analytics

  Process manufacturing teams now have visibility into both historical and near real-time data from their operation, and can even monitor this as it’s happening at remote locations. But the problem with this is that teams are drowning in data—”DRIP”—data rich, information poor.

• How To Use Advanced Analytics To Revitalize Six Sigma

  Lean and Six Sigma continuous improvement methodologies have been a foundation in process manufacturing industries for decades. In more recent times, industry 4.0 and data science innovations—such as machine learning, big data, and cloud computing—have improved analytic capabilities beyond historical limits, enabling the evolution of Lean and Six Sigma efforts. However, the foundational Six Sigma methodology of define, measure, analyze, improve, control (DMAIC) has remained the same. 

• Improve Water & Wastewater Operations With Advanced Analytics

  Across water and wastewater organizations, engineering decisions are too often made based on subjective judgements. Considering how inexpensive and easy modern automation makes it to generate and collect massive amounts of process data, the propensity to make decisions by gut feel may seem far-fetched to a bystander. For plant personnel, however, the struggle to improve upon instinct is often all too real.

• Predictive Analytics 101

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

• Bearing Failure Prediction

  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.

• Control Loop Performance Monitoring

  Manufacturing sites can have hundreds, or even thousands, of automatic controllers, but most sites don’t have insight into how these controllers are actually performing. 

• Mass Balance Calculations

  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.

• Well Productivity Index

  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.

• Well Interaction Detection

  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 Risk Monitoring

  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. 

• Remote Monitoring Of Blowout Preventers Improves Operations

  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.

• Lockout Pressure Optimization

  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.

• Emergency Shutdown (ESD) Water Hammer Characterization

  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.

• Detect Drilling Oscillations

  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.

• Valve Health Diagnostics

  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.

• Seeq For Operators - Find Production Settings

  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.

• Loss Monitoring And Categorization

  See how a manufacturer gained insight into the leading causes of production losses by finding times when equipment was not running at capacity and categorizing the loss by reason.

• Evaluation Of Operation Of Facility

  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. 

• Asset Utilization (OEE) Monitoring

  Increased visibility into unproductive process time is necessary to reduce inefficiencies. With the ability to increase production opportunities when reducing waiting times, overall profitability can also increase. 

• Enabling Engineers With Data Science

  It is important for IT professionals to support the efforts of driving operational excellence to improve quality and safety in production operations. 

   

   

• Charting A Path To More Cost-Effective Control Valve Maintenance

  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.

• Seeking Efficiency? Analytics Makes It Easy

  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 And Situational Awareness For Manufacturing Data

  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.

• Electrical Submersible Pump (ESP) Up-Time

  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.

• Meter Calibration Management

  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 Meter (MPFM) Analysis

  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.

• Remote Analysis Of Equipment 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.

• Truck Haul Analysis

  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.

• Field Wide Analysis

  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.

• Fixed Bed Catalyst End-Of-Run Prediction

  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.

• Heat Exchanger Monitoring And End-Of-Cycle Prediction

  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.

• Well Performance Trending

  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.

• Well Completion Analysis

  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.

• Gas Processing Data Analysis From Afar

  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.

• Adding Value With Analytics

  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.

• 5 Questions To Ask Before Selecting A Process Data Analytics Solution

  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.

• Leveraging Predictive Analytics: A Case Study

  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.

• Optimize Process Unit Results With Advanced Analytics For Condition-Based Monitoring

  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.

• Industrial IoT-Enabled Remote Monitoring Improves OEM Service Performance

  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.

• Leveraging IIoT Technologies To Reduce Unplanned Downtime

  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.