Reservoir simulation
The authors present an efficient workflow using an embedded discrete fracture model to simulate carbon-dioxide flow by use of conductive faults.
The authors of this paper present an adaptive grid-coarsening approach based on constraints that honor reservoir structure and stratigraphy, preserve fluid volumes and contacts, and retain resolution near wells.
This paper provides guidelines for thermal modeling for carbon capture and storage projects in a depleted gas field.
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The paper describes an end-to-end deep surrogate model capable of modeling field and individual-well production rates given arbitrary sequences of actions. -
Physics-based simulations plus machine-learning exercises are yielding a more comprehensive look at production volumes from unconventional assets.
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As we see in these papers, new tools and techniques are being developed to match the ability of engineers to meet the challenges posed by assets such as shale reservoirs and maturing fields.
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This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells.
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In the complete paper, the authors present a novel approach that uses data-mining techniques on operations data of a complex mature oil field in the Gulf of Suez that is currently being waterflooded.
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The complete paper discuses a well with a history of sand production that exhibits long cyclic slugging behavior.
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Fit-for-purpose tactics likely will be of ever-increasing focus going forward. If it is not adding value, it should not be done. But “fit for purpose” encompasses a wide range of possibilities—leveraging new approaches as well as learning from old approaches and improving current approaches.
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In the complete paper, the authors revisit fundamental concepts of reservoir simulation in unconventional reservoirs and summarize several examples that form part of an archive of lessons learned.
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In the complete paper, a novel hybrid approach is presented in which a physics-based nonlocal modeling framework is coupled with data-driven clustering techniques to provide a fast and accurate multiscale modeling of compartmentalized reservoirs.
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In the complete paper, the authors reduce nonuniqueness and ensure physically feasible results in multiwell deconvolution by incorporating constraints and knowledge to methodology already established in the literature.
