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.
1301 2nd Avenue Suite 2850
Seattle, WA 98101
Contact: Jennifer Bentzel
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.
Like many other energy companies, Devon Energy, a leading independent oil and natural gas exploration and production company in North America, generates huge volumes of data. The company’s SCADA system monitors 6.5 million data points from multiple sites, with more than 10,000 updates per second.
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.
Seeq will join more than 500 control system integrators from around the globe on April 24-27 in San Francisco for the Control System Integrators Association (CSIA) Executive Conference.