Our mineral imaging workflow is the result of a collaborative effort with the University of Twente (NL). In our mineral imaging process, we primarily focus on rock samples obtained from cores and plugs, although dry drill cuttings may also be considered. There is a vast number of existing cores and plugs worldwide, yet their potential value remains largely untapped. Deep Atlas presents an immense opportunity for industry stakeholders to maximize the information extracted from these rock samples, thereby maximizing their value.
Our team of seasoned geoscientists employs state-of-the-art processing algorithms to handle a vast volume of hyperspectral measurements, ranging from thousands to millions.
This allows us to deliver advanced mineralogical information tailored to your project’s requirements. The interpretation process combines geological knowledge, spectral analysis, and proprietary automation, resulting in accurate and precise data interpretation.
Deep Atlas utilizes proprietary in-house software for mineral identification. Our mineral imaging workflow, developed in collaboration with the University of Twente (NL), provides a rapid means of understanding the distribution of mineral species within the grains and the reservoir itself.
By leveraging machine learning techniques on a substantial dataset of mineralogy-analyzed plugs, we establish the relationship between mineral species distribution and reservoir flow
We provide semi-quantitative mineralogy logs, which map the mineralogy limited to active minerals in the short-wave infrared (SWIR) range. These logs can be easily incorporated into third-party subsurface or petrophysical software, aiding our clients in optimizing production and mitigating reservoir risk and uncertainty.