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Energy

Deploy and scale real-time AI copilots to optimize oil & gas operations

Basetwo provides a complete process engineering solution that integrates data pipelining, model simulation, economic optimization, and quality control into a single low-code platform.

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From crude oil to LNG, oil and gas refineries rely on the fundamentals of process engineering to achieve consistent product quality. However, refinery operations are often complex, making optimization challenging:

Heterogeneous material quality

Complex multi-step reaction dynamics

Noisy or sparse sensor information

Keep scrolling to see how Basetwo simplifies process optimization for oil and gas refineries.
RIG Load peak power reduction
upstream
drilling optimization
drilling optimization
midstream
LIQUEFACTION OPTIMIZATION
LIQUEFACTION OPTIMIZATION
HEAT EXCHANGER FOULING SOFT SENSING
downstream
FEED STREAM SOFT SENSING
FEED STREAM SOFT SENSING
CRACKING, FRACTIONATION, HYDROTREATING YIELD & ENERGY OPTIMIZATION

Oil Drilling Operations

With Basetwo, companies can connect to several data sources and leverage ML to predict power load and adaptively schedule diesel generator sets and/or energy storage systems to reduce power consumption, generator operating hours, and GHG emissions.

Drilling rigs can consume energy and emit GHG emissions equivalent to what’s required to power thousands of homes, even with dynamic power load profiles and alternative energy sources.

Oil Drilling Operations
conversion process

Conversion Processes

From FCC to steam reforming or gasification units, conversion processes are usually the most complex unit operations in a refinery. Due to nonlinearities and raw material disturbances, controlling and operating conversion unit operations is challenging, let alone optimizing them.

Basetwo empowers process engineers with a low code platform that provides an up-to-date digital representation of their conversion unit operations that enables real-time process understanding.

LNG Liquefaction

Optimizing the LNG liquefaction process is a significant challenge as it requires balancing a number of conflicting objectives, such as maximizing energy efficiency, reducing costs, and ensuring the quality of the final product.

Basetwo allows plants to leverage multi-objective optimization functions to simultaneously optimize several control variables in LNG liquefaction, such as adaptive tuning of refrigerant flow rates, inlet and outlet pressures of compressors and expanders, and the exit temperature after heat exchangers based on dynamic feed gas profile to minimize energy consumption and maximize LNG quality.

LNG liquefaction
process of making powder product using gas sweetening process

Gas Sweetening

Gas sweetening is a critical step in oil and gas operations that involves removing impurities such as hydrogen sulfide (H₂S) and carbon dioxide (CO₂) from natural gas. Optimization requires a deep understanding of the process dynamics and the ability to quickly respond to changing conditions.

Leveraging Basetwo allows plants to connect to several real-time sources to collect data such as feed gas composition, temperature, pressure, and product specifications and build machine learning models to make real-time predictions about final gas quality.

Distillation

Reducing the energy consumption of distillation is complex due to nonlinearities of upstream process disturbances that influence current operating conditions and process efficiency.

Basetwo’s modeling and optimization capabilities leverage industry-proven methods to generate and accurately predict operating information, enabling engineers to rapidly react to changes in process conditions driven by upstream output or other disturbances.

Distillation process using basetwo modeling capabilities

See how Basetwo can deliver:

15-20
Reduction in OPEX
5-15
Increase in yield and efficiency
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