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Mitsubishi Chemical Group Corporation, Japan’s largest chemical company, faced quality problems in the company's polymer manufacturing processes that could not be detected on time, resulting in impacts to production. Using Aspen Hybrid Models with Aspen Plus®, Mitsubishi Chemical Group Corporation had the opportunity to create a robust and performant model that accurately predicted quality issues and supported preventive actions.

Watch this video for an introduction of how Aspen Plant Scheduler and Aspen Mtell work together to predict and minimize the impact of downtime

ORYX GTL Limited is a gas-to-liquids (GTL) diesel and naphtha producer located in Doha, Qatar. The company is committed to reducing its carbon production through the minimization of flaring. By implementing AspenTech´s product and process quality analytics solution, Aspen ProMV®, ORYX was able to increase its diesel and naphtha yield.

Novozymes A/S, a global biotechnology company based in Denmark, was looking to support the development and optimization of biodiesel processes due to increasing biodiesel market demand, rising materials costs and more stringent industry regulations. Novozymes saw potential in combining AspenTech technology with its own unique design and processing expertise to more quickly identify new opportunities to increase profitability of biodiesel production processes.

A global leader in industrial data management from the shopfloor to the boardroom, we accelerate data-driven value creation in asset-intensive industries through robust data software offerings. 

Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, for improved geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

In depth imaging, depth calibration using well-tie updated velocity is generally applied to poststack data. This is the most correct type of depth calibration as it positions structures in their proper places.

One of the main challenges in seismic imaging, especially of land data, is building the near surface velocity model, as it is normally characterized by very low velocity values with different types of local anomalies. Resolving the near surface velocity model using only refraction data is insufficient, as it does not provide the required lateral resolution. Using only reflection data is equally insufficient, as it does not provide the required vertical resolution.

Geothermal energy is a key resource for providing clean, reliable and sustainable energy. Induced seismicity events, with magnitudes large enough to be felt by local communities and impact surface infrastructures, are an undesirable potential result of geothermal operations, and significantly impact social acceptance. Mitigating adverse effects is of upmost importance if one wishes to increase the number of safe, sustainable geothermal projects.