Data Is Data, But Can Data Talk to Other Data?
The world revolves around data. It drives almost everything that occurs in our daily lives and business operations. Data is knowledge and while decoding it is a challenge, the effort may lead to efficiencies and business returns. In the oil and gas industry, data helps petroleum engineers understand how and where wells were drilled, how wells interact, the composition of reservoirs, and, importantly, how reservoirs perform during their productive life. This knowledge empowers engineers to act in ways that may improve a well’s and field’s economics.
Collecting data and unlocking its secrets is the ultimate capital efficiency goal of E&P companies. Many people are familiar with how the digital data captured by the seismic industry has enabled explorationists to unlock the mysteries of the subsurface. Solving those mysteries improved finding and discovery rates, lowering costs. Downhole data telemetry technology enabled engineers to understand how best to produce a reservoir and maximize resource recovery, again improving economics. Later in a reservoir’s productive life, understanding how the output’s physical properties have changed enables decisions about how best to boost recovery by applying artificial lift technology, both lengthening a field’s life and improving its financial return. Tapping all this data provides a wealth of insights into how to improve petroleum operations.
The benefits from dissecting reservoir data are well understood but overcoming the difficulties of working with the data and optimizing capital deployment is a major challenge for E&P companies. Engineers frequently must work within silos of data. Because the nature of the data, both within and between silos, is often quite different, it becomes cumbersome, costly and time consuming to attempt to work with it. Developing a system that allows easier and faster integration of dissimilar data may help businesses make more informed decisions about how best to tap reservoirs and maximize recoveries – all critical for better capital allocation decisions and enhanced financial returns. The challenging environment facing oil and gas companies demands increased efficiency, which means thinking differently about how to work with available data to improve operational decision-making and profits.
For this Company Spotlight, we interviewed the several members of Datagration’s management team about how the company is helping the energy industry solve the issue of disparate data silos hindering organizations’ ability to fully implement advanced analytical tools, such as artificial intelligence (AI) and machine learning (ML). Datagration delivers an easy to implement, open, and collaborative ecosystem of domain-specific platforms that create solutions for E&P organizations by aggregating and integrating data from disparate legacy systems, databases, and unstructured documents into a unified cloud-based or on-premise environment. Combined with advanced AI / ML analytics, Datagration provides organizations with enhanced decision-making opportunities to maximize value creation. For more information on Datagration Solutions, please visit www.datagration.com.
Background: In 2010, after his previous AI application was acquired by Schlumberger in 2004, Michael Stundner (Datagration EVP of Technology) began establishing the PetroVisor platform, as he saw a gap in the integration of data into engineering workflows and processes in the energy industry. The first step in developing the platform was to create an open data aggregation system that could rapidly take data from any source and import it into PetroVisor, which led to building a data mapping wizard capable of combining large, disparate data sets efficiently. Once the data aggregation component was commercialized and adopted by several energy companies globally, the focus expanded to include automated workflows in order to increase productivity. Numerous “off-the-shelf” libraries/applications were developed alongside an easy-to-use scripting language that enables customers to quickly create their own automations. In May 2020, a highly experienced management team purchased the business, rebranded the company as Datagration, and a few months later raised capital to scale the business.
Value Proposition: E&P operators collect vast amounts of data, but they are typically captured and stored in legacy systems, software applications, and databases that are contained in isolated silos depending on the function (i.e. exploration, drilling, completion, production, etc.). When an analysis, whether routine or novel, requires …..READ MORE
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