Reservoir characterization
This study applies Monte Carlo simulation and an XGBoost regression model to assess the influence of various formations, geologic provinces, tectonic-plate types, and boundary conditions on hydrogen concentrations.
This paper presents a novel approach to predict reservoir porosity by conditioning seismic data, calibrating seismic impedance inversion, and tailoring rock-physics analysis.
This paper aims to assess the effectiveness of using advanced integrated production-data-analysis techniques for condensate-rich tight gas fields.
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ConocoPhillips has pulled out of the much-hyped Louisiana Austin Chalk play after the company’s test wells yielded a gusher of water. Meanwhile, an Australian operator flying under the radar continues to pursue the adjacent-but-even-more-challenging Tuscaloosa Marine Shale. -
In this paper, the authors discuss the characterization process for GR tools and how they behave in boreholes different from the one used in the University of Houston (UH) GR characterization pit.
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This paper discusses a study undertaken to gain better understanding of nuclear magnetic resonance (NMR) characteristics of volcanic reservoirs with different lithologies.
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For this year’s feature, the selected papers provide innovative work flows that assist in determining productivity, reduce the effect of uncertainty conditions, and spark rejuvenation.
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A new pulsed-eddy-current (PEC) electromagnetic (EM)-based tool called an enhanced pipe-thickness-detection tool (ePDT) has been introduced for the corrosion inspection of multiple pipes.
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Merging tried-and-true physics-based models with data science is bolstering the Houston independent’s reservoir-engineering work on its deepwater and shale assets.
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Wireline formation tests are a critical piece of the exploration and appraisal process, yet they come with a degree of uncertainty. The supermajor has tapped a new software developer to see if it can clear things up.
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While some try to put the two enormous oil producers toe-to-toe, the best thing to do might be to understand why they are different.
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To enhance the applicability of localization to various history-matching problems, the authors adopt an adaptive localization scheme that exploits the correlations between model variables and observations.
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A challenging problem of automated history-matching work flows is ensuring that, after applying updates to previous models, the resulting history-matched models remain consistent geologically.
