Reservoir

This paper describes natural fractures and their effect on hydrocarbon productivity in the Vaca Muerta shale formation.

The authors of this paper describe a solution using machine-learning techniques to predict sandstone distribution and, to some extent, automate the process of optimizing well placement.

This study catalogs global gas/oil ratio data to identify currently produced light crude oils that could be rendered carbon neutral through the direct-air-capture mechanism.

A new program offers an affordable way to figure out if salt precipitation could be behind underperforming gas wells and suggests a path to higher production.

Artificial intelligence (AI) and machine learning (ML) technologies have rapidly progressed and have significantly affected traditional reservoir engineering, bringing innovative methodologies to reservoir simulations. However, it is essential to understand that these AI and ML technologies are only as effective and trustworthy as the data they are trained on.

A decade ago, SPE defined key R&D and technology challenges for the industry. To address the more uncertain environment of the 2020s and beyond, we have updated the grand challenges via a January 2023 SPE workshop.

The objective of this study was to establish an efficient optimization work flow to improve vertical and areal sweep in a sour-gas injection operation, thereby maximizing recovery under operation constraints.

The objective of this paper is to present a fundamentals-based model of three-phase flow consistent with observation that avoids the pitfalls of conventional models such as Stone II or Baker’s three-phase permeability models.

CNPC’s record-breaking 11,100-m exploration borehole in the Taklamakan Desert promises to unlock the science of producing oil and gas trapped in the world’s deepest reservoirs.

DJ Basin player enters the Permian Basin with a pair of asset purchases from private-equity vehicles.