Reservoir
Operators aren’t rushing to drill, even as the closure of the Strait of Hormuz drives oil prices up.
The authors write that deployment of artificial-intelligence-based high-gas/oil ratio well-control technology enabled stabilization of well performance and maintenance of optimal production conditions.
The paper describes the revalidation of a deepwater prospect that resulted in a no-drill decision.
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The force required to drill through a rock is a direct test of its strength and stiffness. Developing a reliable measure of the properties of rock based on the force required to drill a long lateral is a large challenge. -
One of the biggest ways to lower the cost of production from shale would be to identify zones that are productive, or not, before fracturing them.
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With the recent drop in oil prices, operators are shifting to optimization of existing assets with minimal costs. For mature floods (water, chemical, and CO2), one low-cost optimization strategy is the intelligent adjustment of well-rate targets.
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Permanent downhole gauges (PDGs) can provide a continuous record of flow rate and pressure, which provides extensive information about the reservoir. In this work, a machine-learning framework based on PDG data was extended to two applications: multiwell testing and flow-rate reconstruction.
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The authors present a geology-driven deep-learning estimated-ultimate-recovery (EUR)-prediction model for multistage hydraulically fractured horizontal wells in tight gas and oil reservoirs.
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The importance of reducing emissions of methane, a short-lasting but powerful atmospheric greenhouse gas (GHG), received close attention from panelists at an IHS CERAWeek strategic dialogue, Tightening the Valves on Global Methane Emissions.
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When it comes to hydraulic fracturing, steadiness may not be a virtue. That was the conclusion of a test to see if rapid pump rate variations would lead to greater production than conventionally fractured stages when the pressure was held steady.
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In this paper, the authors introduce a novel semianalytic approach to compute the sensitivity of the bottomhole pressure (BHP) data with respect to gridblock properties.
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This paper critically investigates the impact of using realistic, inaccurate simulation models. In particular, it demonstrates the risk of underestimating uncertainty when conditioning real-life models to large numbers of field data.
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History matching is only one part of something more comprehensive—reservoir modeling.
