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.
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