Unconventional/complex reservoirs
With a strong presence across US shale in the Bakken, Anadarko Basin, Powder River Basin, and the Permian, Continental Resources is expanding into Argentina’s Vaca Muerta shale as the privately held E&P giant pursues international growth.
The DOE-backed EGS-Twin project aims to simulate geothermal production systems, helping operators better predict performance and maximize output.
Beetaloo Energy and Halliburton have signed an MOU to advance Beetaloo Digital, a proposed gas-powered AI data center hub in Australia’s Northern Territory that could create a new long-term market for Beetaloo Basin gas.
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This paper presents a novel modeling framework for predicting residual oil saturation in carbonate rocks. The proposed framework uses supervised machine learning models trained on data generated by pore-scale simulations and aims to supplement conventional coreflooding tests or serve as a tool for rapid residual oil saturation evaluation of a reservoir. -
One hydraulic fracturing job can stimulate two wells, but economic success hinges on doing it in the right place for the right price.
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This paper presents a multidisciplinary view of the evolution of a development project for the central area of Sururu and the method applied to address challenges and propose solutions.
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This paper assesses the potential of augmented depletion development in four US plays: Bakken, Eagle Ford, Midland, and the Anadarko Basin.
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Rig counts are down since 2023, but well productivity is marching forward.
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The deal comes only weeks after the private equity firm purchased a natural gas-fired plant operator.
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This paper describes a data-driven approach for liquid-loading detection and prediction that harnesses high-frequency gas-rate and tubinghead-pressure measurements to identify the onset of liquid loading and correct critical rates computed by empirical methods.
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This paper outlines the importance of numerical rate transient analysis for dry gas wells, describing a simple, fully penetrating planar fracture model.
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This study compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field in southern Iraq.
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This paper describes an approach that combines rock typing and machine-learning neural-network techniques to predict the permeability of heterogeneous carbonate formations accurately.
