Reservoir
As Egypt’s largest oil and gas investor, Eni is ramping up its 2026–2027 drilling campaign with new investments cross the Mediterranean offshore, Nile Delta, Western Desert, and offshore Sinai to strengthen the country’s role as a regional gas and LNG export hub.
The industry is no longer short of measurements; the real challenge is converting them into timely reservoir decisions that protect value. That challenge is becoming more urgent as the industry depends increasingly on mature fields and existing infrastructure. The selected papers show how this need is being addressed across different producing regions.
This paper presents a case study from a mature field redevelopment project where pulsed neutron logging was integrated with advanced reservoir modeling to improve the understanding of fluid-contact dynamics and optimize new horizontal well placement.
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The deal comes only weeks after the private equity firm purchased a natural gas-fired plant operator. -
India’s state oil company is accepting proposals from potential technical service partners until 15 September for EOR projects in the Arabian Sea.
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The SPE IOR-EOR Terminology Review Committee has opened a period for public comments on a draft technical report.
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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.
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This study describes the performance of machine-learning models generated by the self-organizing-map technique to predict electrical rock properties in the Saman field in northern Colombia.
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Based on 6 years of firsthand experience, refrac experts share some of their biggest insights into where the US market is headed and how to identify the best candidates.
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The new frontier of production improvement combines surveillance techniques and analysis to determine which variables boost output.
