Reservoir characterization
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.
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.
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The authors introduce and compare two quality-control approaches based on two different signal-processing practices. -
Innovators at the Norwegian oil company have developed a machine-learning model that analyzes mud-gas data to predict the gas/oil ratio of wells as they are drilled—something that the industry has worked for decades to accomplish.
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Eni and IBM developed a cognitive engine exploiting a deep-learning approach to scan documents, searching for basin geology concepts and extracting information about petroleum system elements.
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SponsoredThermo Scientific e-Core Software is a unique, high-performance computing platform for the characterization of complex porous media. It focuses on the three essential components of Digital Rock Analysis: parallel computing, multiscale modeling, and process-based reconstruction of 3D volumes.
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The UK offshore Lancaster field was to prove that complex basement formations could be profitably developed. Instead, it is a reminder of how a long-term production test can drastically alter a reservoir model built upon years of exploration work.
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Advances during the past decade in using convolutional neural networks for visual recognition of discriminately different objects means that now object recognition can be achieved to a significant extent.
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Automated image-processing algorithms can improve the quality and speed in classifying the morphology of heterogeneous carbonate rock. Several commercial products have produced petrophysical properties from 2D images and, to a lesser extent, from 3D images.
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The complete paper presents a technical discussion of a new microsampling technique for LWD and a corresponding wellsite technique to provide compositional interpretation, contamination assessment, reservoir-fluid compositional grading, and reservoir compartmentalization assessment.
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In tectonically influenced regions, potential hydrocarbon traps are subject to complex states of stress. This scenario often translates into severe strike/slip (SS) and thrust-fault or reverse-fault (TF/RF) stress states.
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Duri Field in Indonesia is the largest active steamflood project in the world. The field produces 73,000 BOPD, and 10,000 optimization jobs are executed annually to support base production.
