Geosciences

Over the last decade, deep learning applied to image analysis has rapidly developed in scope to cover numerous fields. However, its potential remains underexploited in geology, despite the fact that it is a discipline that relies to a large extent on visual interpretation. To contribute to the digital transformation of industries related to the underground environment, researchers at IFPEN have implemented deep learning in three “profession-specific contexts”, each involving different types of geological images.

Today, characterization of geological reservoirs, a long-standing theme in petroleum exploration, becomes a base of interest for a variety of applications, such as CO2 and hydrogen storage as well as geothermal energy. In recent years, the combined use of 3D microtomography (or micro-CT ) imaging and advanced simulation techniques has allowed the emergence of a digital approach to computing the petrophysical properties of reservoir rocks (Digital Rock Physics). This represents a real complement - and in some cases an alternative - to traditional laboratory measurements.

Seismic imaging remains an important tool in the characterization of geological reservoirs. In the case of carbonate reservoirs, the biological origin of the sediments, as well as their transformation over time through diagenesis , results in numerous structural heterogeneities.

The present page presents the benefits of TRUE AMPLITUDE seismic reflection from VSPs for the geologist interpreter. Additionally, a method for the detection and quantification of INTERNAL OR INTERBED

Foam injection during oil production or ground remediation is aimed at overcoming problems of gravity segregation and viscous fingering a created by fluid injection. Improving this practice requires

The present booklet supports and amplifies the observations and methodological conclusions of the method of oriented 3 component VSP developed by IFP and CGG in the 1990's. Poster presented at the 3

Carbonate reservoirs present significant heterogeneities (in terms of types and scales) associated with the biological origin of sediments c, as well as the diagenetic transformations that took place