BELSIM: Delivering Process Intelligence

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Boris Kalitventzeff, Founder and Chairman
As all energy intensive industrial processes, mature oil fields are often characterized by inefficient operation with very high energy consumption costs. A key tenet behind these conditions is the unavailability of reliable data—a prerequisite to good production optimization and to AI tools exploitation. While many companies use remote control sensors and downhole measurements to keep track of the production operations, most often, these data are not validated. At the wake of these concerns, a Swiss company, BELSIM brings to the fore the concept of data validation and reconciliation (DVR) that was authored by Boris Kalitventzeff, the founder and chairman of the company. BELSIM leverages DVR along with cutting-edge mathematical algorithms and modelling techniques to transform all the relevant production data into consistent, accurate, structured, and reliable information. This helps an oil and gas company—especially ageing companies— to operate effectively, detect deficiencies and risks in time, and alleviate process inefficiencies.

A worldwide leader in the field of DVR today, BELSIM started as a spinoff from the University of Liège, Belgium, back in 1986. Diverse sectors such as oil and gas refineries, power generation, industrial site energy utilities, and fertilizers, ride on BELSIM’s coattails to gain a better understanding of process operations—thereby translating their performance into significant ROI. Leveraging deep process intelligence to provide the best-in-class products, BELSIM believes that the future is AI, and its technological by-products will help manage big data and bolster existing analysis tools. “Meanwhile, industrial process managers today may still ignore that DVR applications provide indispensably validated, and structured data of their facilities,” expresses Kalitventzeff.



The company has spent years of research to build VALI, BELSIM’s online DVR solution—based on a process mapping model—that computes plant’s performance data, mass, and energy data points along with other key performance indicators with their level of accuracy and reliability. “The ideation for VALI stemmed from my analysis and synthesis experience as polytechnic officer for the Belgian army, which gradually led me to delve into chemical engineering,” recalls Kalitventzeff. During this time, he was very eager to solve the numerous data management and analytical problems that placed a thorn in the energy industry’s progress. Kalitventzeff started experimenting with probability theories and statistical formulation to find flaws in an industrial facility’s structural and digital framework. After a few years of tests and trials, Kalitventzeff and his team were able to develop VALI—a solution that complements the resourcefulness of AI tools and automates data processing operations, predicts future risks, limits environmental impact, and significantly improves overall workflow efficiencies in a variety of process plants.


The company will be continually collaborating with engineering enterprises namely in the U.S. to implement the technology, while supporting DVR R&D and training in various universities to encourage energy technology development and awareness at a foundational level



“AI tech providers recognize that about 60 percent of the cost of development of an AI model is the preparation of data (quality and structure, among others). VALI is the perfect tool to do that, although that’s not the sole advantage of using VALI,” explains Kalitventzeff.

To demonstrate the full capabilities of the solution, Kalitventzeff shares a case study of an international oil and gas company based out of Aberdeen, Scotland, that leverages VALI for extensive DVR. The client required a new means of monitoring their virtual flow metering that promised more efficacy and accuracy while developing reports for analysis. Prior to the implementation of VALI, the company suffered issues in the areas of multiphase flow meters, daily basic sediment and water measurement, and process flow meters, among other pertinent workflow operations. However, utilizing BELSIM’s solution, the client was able to make changes and accordingly optimize the plant’s performance. Additionally, owing to the company’s hydrocarbon engineering expertise, the petroleum company also witnessed a significant increase in the accuracy of temperature measurements, mass and energy balance, pressure drop calculations, and thermodynamic phase behaviour of hydrocarbons along new flow paths, in near real-time. The client’s plant operations were completely revamped, and VALI was at the heart of this comprehensive transformation, as it is often the case.

Moving forward, BELSIM intends to continue improving its existing software—which operates under a mathematical interior point optimization method—and drive DVR innovation throughout the energy sector. The company currently caters for industry giants like Aramco, EDF, Exelon, BP, Dana Petroleum, Larsen & Toubro, Air Liquide, Total, providing them with DVR solutions and other consulting services. Following BELSIM’s trajectory of growth, Kalitventzeff concludes by saying, “The company will be continually collaborating with engineering enterprises namely in the U.S. to implement the technology, while supporting DVR R&D and training in various universities to encourage energy technology development and awareness at a foundational level.”

Company
BELSIM

Headquarters
Zug, Switzerland

Management
Boris Kalitventzeff, Founder and Chairman and Boris Latour, CFO, Pascal Leurquin, CEO and Frederic Lecoq, COO

Description
BELSIM has spent years of research to build VALI, BELSIM’s online DVR solution—based on a process mapping model—that computes a plant’s performance,mass, and energy data points along with other key performance indicators with a their level of accuracy and reliability. When process parameters cannot be measured directly, VALI uses a Soft Sensing system to calculate their value. The same technique can be used to reduce investment in expensive measurement equipment. The company’s main objective is to improve data and facility management while ensuring production managers and C-suite executives consistently receive accurate information about their process plants

BELSIM