Reservoir
Sponsored
MOSAIC's advanced Automated Reconciliation to Reserves Workflows enhances accuracy, speeds up processes, and meets the need for precise asset valuation. Equip your reserves teams with reliable information and insights to reduce uncertainty, boost efficiency, and make smarter business decisions.
A case study presented at ATCE took medical science to a new low—into the depths of the Permian Basin for application to downhole reservoir drainage diagnostics.
This paper discusses how a traditional stochastic approach in project economics used for screening and ranking can sometimes limit management visibility of all possible outcomes in a project.
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BKV Corp. has combined bullhead and liner refracturing methods to create an approach called the hybrid expandable liner system. -
AIQ, ADNOC, and SLB announced a new software suite that integrates artificial intelligence into reservoir analysis and field development projects.
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SponsoredThe Wyoming Gas Injection Initiative (WGII) makes available $22 million of matching funds from the State of Wyoming to implement, in close collaboration with oil and gas operators and Dow, multiple field pilot projects in the State of Wyoming. The Initiative will fund projects over a 3- to 5-year period to support developments with significant potential to enhance wel…
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The nearly $60-billion deal will see ExxonMobil more than double its Permian Basin output to over 1.3 million BOED.
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Permian producers are looking for new places and ways to sustain production in the giant basin.
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The project aims to reimage a 6,400-km2 seismic data set near the recently discovered Baleine field.
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The latest deal from Denver-based Civitas Resources brings its spending total this year to almost $7 billion.
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The authors of this paper present an artificial-lift timing and selection work flow using a hybrid data-driven and physics-based approach that incorporates routinely available pressure/volume/temperature, rate, and pressure information.
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The authors of this paper describe a procedure that enables fast reconstruction of the entire production data set with multiple missing sections in different variables.
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This paper presents a physics-assisted deep-learning model to facilitate transfer learning in unconventional reservoirs by integrating the complementary strengths of physics-based and data-driven predictive models.
