ICURe Discover Award for Vitaly Starikov

Vitalii Starikov has been honoured with ICURe Discover Award from Innovate UK for his new R&D project idea in NetZero. The start-up idea, AI Methane Tracker, is to develop an intelligent system to detect and monitor methane emissions using satellite imagery. Vitalii’s ICURe Award  secures essential funding for early market discovery activities, further advancing the […]


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GeoDataScience talks at EAGE Petoleum Geostatistics, Porto

Three data science talks were contributed to EAGE Petroleum Geostatistics programme: Vitaliy Starikov presented a talk Unsupervised Classification of Flow Regime Features in Pressure Transient Responses sharing the progress of the AutoWell consortium. Dr Chao Sun and Gleb Shishaev were not able to present their work in person because of the visa logistics. However, their […]


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3D realistic fluvial facies modelling with GANs

This new Chao Sun’s publication competes his PhD thesis passed successfully earlier this year. A conditional GAN-based approach to build 3D facies models sequentially upwards  by Chao Sun, Vasily Demyanov, Daniel Arnold published in Computers & Geosciences Volume 181, December 2023, 105460 extends the earlier GAN papers and  presents an alternative way of simulating 3D […]


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Athos Nathanail successfully passed his PhD viva with the thesis – Capturing interpretational uncertainty of depositional environments with Artificial Intelligence

Congratulations to Athanasios A. Nathanail with passing his PhD viva with “flying colours” examined by Prof Dorrik Stow and Prof Mikhail Kanevski. The thesis offers a comprehensive insight into how AI can aid capture deposition interpretational uncertainty from outcrop patterns to make inferences about the conceptual model uncertainty based on the limited in core data […]


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A new GAN study for fluvial facies modelling got published in Computational Geosciences as an outcome of Chao Sun’s PhD

Geological realism in Fluvial facies modelling with GAN under variable depositional conditions by Chao Sun,  Vasily Demyanov,   Daniel Arnold Computational Geosciences, 10.1007/s10596-023-10190-w This study investigates generative adversarial networks (GANs)’ capacity to model multi-facies distributions of meandering systems. Earlier works showed that GANs outperform geostatistical methods in reproducing complex geometry, like the shapes of fluvial channels. […]


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A benchmark data set for meandering reservoir facie modelling published online and now available to download.

The GAN River-I data set is designed to provide a stern test for machine learning and geostatistical tools that wish to recreate the complex geometries of realistic facies distributions in subsurface reservoirs. It provides more complex, non-stationary facies distributions than earlier open data sets,  and is generated with FLUMY process-based algorithm. It has been puiblished […]


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GeoDataScience talks at GeoNetZero CDT annual conference in Edinburgh

Final year PhD students have presented summaries of their theses at the GeoNetZero CDT annual conference: Athos Nathanail – Assisted Geological Interpretation Based on Human-like Creative Computing – Depositional Environment Interpretation from outcrop data Chao Sun – Use of Artificial Intelligence to Generate Complex Fluvial Systems Quentin Corlay – Detection of Geobodies in 3D Seismic using […]


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CCS sandpit event at TU Delft

Heriot-Watt GeoDataScience group teams with TUDelft in a CCS sandpit – Innovative solutions on subsurface utilization for energy transition, September 11-15, 2022 organised by Denis Voskov (TU Delft) and Vasily Demyanov (HWU) The event provided a unique opportunity for PhD students from the two universities to exchange their research experience in reservoir characterization and modelling. […]


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