Reservoir characterization
After 5 years of in-depth diagnostic research, the Oklahoma City-based operator shares more insights on fracture behavior.
This work investigates the root cause of strong oil/water emulsion and if sludge formation is occurring within the reservoir using a robust integrated approach.
In this work, a perturbed-chain statistical associating fluid theory equation of state has been developed to characterize heavy-oil-associated systems containing polar components and nonpolar components with respect to phase behavior and physical properties.
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This article presents a new data-driven analysis to locate low-frequency seismic sources, referred to as near-infrasound or infrasound sources. Combining these infrasound signals with microseismicity signals allows for better characterization and monitoring of the stimulated reservoir volume. -
SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems.
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The authors of this paper introduce a physics-based method for explicit pore-pressure prediction in naturally fractured shale petroleum reservoirs.
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The authors of this paper aim to identify the effect of various geologic controls on hydrocarbon maturation in the Delaware Basin by restoring regional cross sections and performing simulations of organic-matter maturity.
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This work applies an appropriate transient-test theory to demonstrate the applicability of each diagnostic plot along with clearly defining the characteristic features that allow each plot to be considered “diagnostic.”
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In the life cycle of a field, from exploration and production to development, as we hone our knowledge to understand the reservoir, we often explore various subdomains of formation evaluation at various scales. In this issue, we explore three such subdomains at three different scales.
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The authors of this paper describe an approach that combined active and passive near-field hydrophone measurements in a complex near-surface area offshore Abu Dhabi.
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The goal of this paper is to improve the understanding of uncertainties affecting well performance and reservoir connectivity in an offshore Malaysian field.
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The opening ceremony highlighted maximizing production sustainably to meet global demand, integration of simulation and optimization in a single platform with automation, and energy security.
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Large geological models are needed for modeling the subsurface processes in geothermal, carbon-storage, and hydrocarbon reservoirs. The size of these models contributes to the computational cost of history matching, engineering optimization, and forecasting. To reduce this cost, low-dimensional representations need to be extracted. Deep-learning tools, such as autoenc…
