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This paper focuses on the vital task of identifying bypassed oil and locating the remaining oil in mature fields, emphasizing the significance of these activities in sustaining efficient oilfield exploitation.

The objective of this study is to develop an explainable data-driven method using five different methods to create a model using a multidimensional data set with more than 700 rows of data for predicting minimum miscibility pressure.

Updates about global exploration and production activities and developments.

This section lists with regret SPE members who recently passed away.

The authors present an open-source framework for the development and evaluation of machine-learning-assisted data-driven models of CO₂ enhanced oil recovery processes to predict oil production and CO₂ retention.

The world’s reliable engine of crude demand growth is stalling out, and its impact on the upstream market is already being felt.

The authors of this paper propose hybrid models, combining machine learning and a physics-based approach, for rapid production forecasting and reservoir-connectivity characterization using routine injection or production and pressure data.

This paper presents an overview of the operator’s Marlim and Voador fields revitalization project, highlighting features and main achievements in the context of Campos Basin redevelopment.

his paper investigates the challenges faced in the development of mature and tight fields, primarily resulting from reservoir depletion, high operational costs, and uncertainty in reserves volumetric calculations.

From the papers reviewed, a spectrum of case studies addresses how practitioners are taking on the challenge of extending economic life and revitalization of mature fields through better understanding of the subsurface and adapting existing techniques and technologies in innovative ways.