A new, proprietary technique that improves production forecasts has been demonstrated on an Asian gas field. Multi-scale ensemble-based history matching (MS-EnOpt) improves production forecasting and reserve estimation, and provides engineers with an understanding of key reservoir uncertainties.
To help the industry identify new and previously overlooked prospects in Australia’s Gippsland Basin, CGG acquired a new basin-scale 3D seismic multi-client survey in 2020.
Four recent case studies document how an advanced seismic workflow, which integrates geoscience data, enables operators to enhance their reservoir characterization interpretation.
The North West Shelf of Australia is a prolific hydrocarbon province hosting significant volumes of hydrocarbons, primarily derived from Jurassic and Cretaceous targets. A new regional, integrated geoscience study has been undertaken by CGG to develop new insights into the paleogeography and petroleum systems ...
Exploration in the Northern North Sea has been extremely successful, with important discoveries such as Statfjord in 1974, and Oseberg, Snorre, Gullfaks and Troll, discovered in 1979. More recently, several smaller but still very valuable discoveries have been made, demonstrating the remaining potential of ...
A 24-well pad is auto-planned and shows the Separation Rule anti-collision display computed for all wells all at once. The color controls represent three collision risk categories: green = minimum risk, yellow = medium risk and red = stop drilling, maximum risk zones. (Source ...
HOUSTON–Cuttings are a valuable and cost-effective source of subsurface data from both vertical and lateral wells that is commonly overlooked in oil and gas exploration and development drilling. Advancements in analytical technologies have enhanced the data extraction from cuttings to provide key subsurface insights ...
Over the past 35 years, geothermal projects have been developed in the Upper Rhine Graben (URG) to exploit deep geothermal energy. Underneath approximately 2 km of sedimentary deposits, the deep target consists of a granitic basement, which is highly fractured and hydrothermally altered. Therefore ...
Data science-based methods, such as supervised neural networks, provide powerful techniques to predict reservoir properties from seismic and well data without the aid of a theoretical model. In these supervised learning approaches, the seismic to rock property relationship is learned from the data. One ...