Reservoir characterization
The technology has passed its first phase of qualification, with 84 nodes placed on the seafloor at a depth of 2,000 m to acquire 4D seismic data in the pre-salt Santos Basin.
Xu outlines the thinking and theories that led his team to six world-class oil discoveries that total more than 100 million tons of proven geological reserves since 2021.
This case study from SLB and offshore producer PRIO describes the longest openhole section in Latin America with the highest extended-reach drilling ratio in Brazil’s history.
-
This paper describes a novel 6.75-in. logging-while-drilling geochemical tool developed for accurate lithology, mineralogy, well-placement, and geosteering applications in complex reservoirs. -
This paper presents a self-supervised approach for training a seismic foundation model and demonstrates scenarios in which it is used for seismic data conditioning, interpretation, and inversion through six real-use cases.
-
This paper provides an overview of an operator’s application of 4D time-lapse seismic technology over approximately a decade and includes future perspectives.
-
This paper describes rock-compressibility correlations for carbonated naturally fractured reservoirs in Mexico that considers a range of important geological and dynamic aspects.
-
Data and impartial viewpoints can help de-risk exploration portfolios and keep resource estimates in check.
-
Geophysicist Markos Sourial discusses advances in seismic imaging, the challenges of modern data processing, and what they mean for the next wave of subsurface professionals.
-
This paper presents a novel methodology for assessing the rapid mineral carbonation of carbon dioxide through geochemical interactions with carbon-, magnesium-, and iron-rich minerals abundant in geological formations.
-
This study integrates physics-based constraints into machine-learning models, thereby improving their predictive accuracy and robustness.
-
This paper introduces a machine-learning approach that integrates well-logging data to enhance depth selection, thereby increasing the likelihood of obtaining accurate and valuable formation-pressure results.
-
This study aims to use machine-learning techniques to predict well logs by analyzing mud-log and logging-while-drilling data.
