In just two weeks, Geoteric AI Seismic Interpretation corroborated that a fault-bound compartment containing a newly drilled well, was not in communication with other parts of the reservoir structure. As a result, PGNiG were able to update their geological model with the ability to identify new areas of compartmentalization, for new dynamic modelling and simulations to improve well planning and safety.
Building on Geoteric’s cutting-edge AI Fault Interpretation that accurately detects faults invisible to the human eye, Geoteric Seismic Interpretation software now includes structurally-aware AI Horizons. The technology identifies every event from surface to region of interest in hours and comes at a crucial time for operators facing demands to fast-track production.
Interpreting challenging seismic data is one of the largest problems faced by our customers. In order to visualise the 3D structural complexities of the subsurface, they require a 3D solution that only Geoteric AI Faults - 3D Networks provides. The 3D neural networks rapidly and accurately identify subtle structural features such as small-scale faults that are invisible to the human eye, even in challenging data.
Geoteric are the first AI Seismic Interpretation software provider to give users the choice between six trained and untrained neural networks - reducing fault interpretation time by up to 95%. The latest update to the technology 2022.2, introduces two brand new networks. Acorn, an untrained network that can be exclusively trained on your own seismic data, basin, reservoir or field - without bias and Meranti, a pre-trained network that more closely resembles traditional interpretation.
Ithaca Energy wanted a deeper understanding of the subsurface in an area currently under appraisal. In particular, structural and stratigraphic features that could be the cause of a disappointing Extended Well Test. Geoteric AI Seismic Interpretation helped Ithaca Energy make crucial decisions relating to field development planning. Our integrated workflows are helping to de-risk future well planning and better predict expected reservoir performance.
In this session, Mark Ackers, Subsurface Technical Services Lead at Sval Energi will demonstrate how Geoteric AI Fault Interpretation results were used to improve their reservoir model allowing for more accurate production history matching. Ultimately, Sval Energi were better able to predict future production, generating clear value for the company as a whole.
Sand injectites are complex geological features formed by remobilised liquified sediment being forcibly intruded into surrounding host rocks, typically at shallow subsurface depths. Despite their shallow subsurface depths, injectites can present significant challenges in terms of seismic imaging and interpretation due to their commonly thin nature and chaotic geomorphologies.
Subsurface sequestration of CO2 (CCS) is seen by many as an essential route towards carbon Net Zero. Recent software advances within the interpretation domain such as Artificial Intelligence (AI) are helping to solve CCS challenges and enable the interpreter to extract more detail than previously possible with shorter project cycle times.
Geoteric Webinar: Journey to NetZero - Shallow Geohazard Interpretation
Understanding the conditions of the seabed and the shallow subsurface are critical in the avoidance of many types of geohazards which could potentially impact on the safety and cost of engineering operations in offshore wind farms, as well as the longevity of the structures being installed.
Geoteric Webinar: AI Seismic Interpretation with structurally-aware AI Horizons
Completing your workflow with Geoteric AI Horizons. The most detailed and advanced AI seismic interpretation on the market with unparalleled subsurface accuracy. Dr. Ryan Williams, Senior Geoscientist will be showing how project cycle times are dramatically reduced without compromising on quality, resulting in greater efficiencies in sustainability projects, field development and increased well safety.
Geoteric Webinar: AI Fault Interpretation with Automatic Fault Surface Extraction
Understanding subsurface structure is critical in optimising asset plans, well safety and sustainability projects such as Carbon Capture and Storage (CCS). Here, Senior Geoscientist, Luis Gomez demonstrates how Geoteric AI Fault Interpretation with automatic fault surface extraction is shortening cycle times of subsurface projects all over the world.
Senior Geoscientist, Ryan Williams highlights the potential of utilising colour blending techniques in collaboration with AI fault and horizon extraction.
He also examines how coupling these techniques together enables the subsurface analyst to identify and delineate structural and stratigraphic features in a seismic volume in more detail and accuracy, in a fraction of time it would require to undertake a traditional interpretation.
Ryan Williams, Senior Geoscientist discusses the key role Geoteric can play a key role in realising CCUS projects and demonstrates fault analysis using Geoteric’s AI fault detection networks to identify unseen faults which could compromise integrity for CO₂ storage.
This presentation discusses how BHP applied Geoteric AI to support the rapid interpretation of a new seismic dataset in the Atlantis field. It also examines how BHP leveraged the prowess of this latest AI information to guide them into making better-informed decisions regarding well placement, reducing uncertainty and changing the risk profiles for future wells.
 Data courtesy of Atlantis field operator BP for allowing these results to be shown.
In this video, Lucy Plant, Regional Sales Manager - Americas, presents a case study led talk on how Geoteric's AI seismic interpretation technologies Collaborative AI and Geoteric Stratum™ can enhance subsurface understanding and how it can be used to advance the traditional seismic interpretation workflow we know today.
Dave Brett from Ithaca Energy, presents his independent and impartial perspective on how Geoteric's AI seismic interpretation tools and services added to the better understanding of the structural complexity of their prospect and the results and benefits they achieved when compared to traditional interpretation techniques.
Further information on this case study is highlighted in GEOExPro AI: Game-Changer in Development or Exploration - or Both?
Using the TERN Field (Northern North Sea) case study as his example, Senior Geoscientist Ryan Williams illustrates how Geoteric's AI seismic interpretation tools can assist in identifying and reducing risk to help drill wells safely, on time and within budget.
Owen Lee, SVP Global Sales presents an overview of Geoteric's core workflow with brief insights into its application across different global and geological settings.
Geoteric’s best in class geological evaluation software clearly visualises the subsurface, allowing interpreters to combine their knowledge with the best possible picture
throughout exploration, development and production.