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Tachyus Partners With Texas A&M to Provide Petroleum Engineering Students New Technology Solutions

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Tachyus, a provider of data-driven production optimization software to the oil and gas industry, is partnering with the Texas A&M University Department of Petroleum Engineering to deliver new technology to students, faculty and researchers.

Through the partnership, graduate and PhD students within the petroleum engineering department at Texas A&M will have access to the Tachyus platform, which provides a digital transformation, proprietary modeling and optimization techniques that combines machine learning with reservoir physics. Several of the apps are designed to model and optimize enhanced oil recovery (EOR) processes, including waterflooding and carbon dioxide flooding. They allow the prediction of thousands of outcomes in a matter of minutes which allow reservoir engineers to increase production by an average of 10 percent and cut operating costs by more than 40 percent.

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Other apps are designed for oil and gas production optimization, such as surface and subsurface back allocation, decline curve analysis and the analysis of optimal infill drilling locations. Each of these apps allow users to increase production, increase recoverable reserves and to improve efficiency.

This technology will be available to assist and provide predictive analytics and insights in research assignments and allow for intelligent data management that delivers precise and comprehensive reporting. With this first-of-its-kind partnership, students will be empowered to experiment within the platform and familiarize themselves with its real-world applications.

“Texas A&M’s Petroleum Engineering Department is a very prestigious institution and was recently ranked by US News & World Report as the top program in the United States. We are thrilled for the opportunity to share our software with their students to assist in their research and modeling/optimization efforts in solving many of the oil and gas industry’s problems” said Tachyus CEO Fernando Gutierrez in a Dec. 8 announcement. “Our hope is to provide students the opportunity to further their industry knowledge and be part of the digital transformation movement we, at Tachyus, are trying to instill into the upstream space. Our platform aims to be a tool that allows students, early on, to become accustomed to modeling and optimization software so that upon entering the workforce they are acquainted and open to a technology forward solution.”

This unique partnership marks the beginning of a new wave of a digital forward workforce. Both Tachyus and Texas A&M recognize the role they play within the space to spearhead new initiatives which will reshape the oil and gas industry.

“Tachyus enables engineers, and now our students, to explore production optimization scenarios and recognize optimal operational and development plans resulting in significant cost reductions, production increases and ready-to-use injection strategies,” said Dr. Jeff Spath, Department Head Chair in Petroleum Engineering at Texas A&M University. “Ultimately this exposure to real data solutions and forecasting models will further our student’s value, experience and knowledge as they enter the working world. As the oil and gas industry faces unprecedented difficulties, we look forward to our relationship with Tachyus to drive the upstream space into new possibilities.”

The partnership will be ongoing. Tachyus will work closely with students to identify their specific needs and will then provide a specific TachApp solution to be utilized whether they are looking for waterflood management, probabilistic decline curve analysis, shale optimization, etc.

Tachyus is a developer of production optimization software that is tailored for oil and gas fields operating under secondary and tertiary recovery. This includes waterfloods and steamfloods. The startup, founded in 2013, will use the new injection to accelerate new technology development. The Tachyus platform is used by reservoir and production engineers to analyze historical data and build predictive models that help reveal the best ways to maximize output.

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