Reservoir characterization
The objective of this study is to numerically investigate system behavior when storing H2/natural gas (CH4) mixtures in aquifer-related underground gas storage, and the effect of gas composition and salinity on energy-recovery efficiency.
The authors describe the effectiveness of an electromagnetic look-ahead service while drilling in terms of providing accurate formation profiles ahead of the bit to optimize geostopping efficiency.
In the past year, publications on CO2, natural gas, and hydrogen storage have increasingly focused on the design, evaluation, and optimization of storage plans. These efforts encompass a broad spectrum of challenges and innovations, including the expansion of storage reservoirs from depleted gas fields and saline aquifers to stratified carbonate formations and heavy-o…
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Part 3 of this series looks at the importance of performance analysis and how to generate the economic benefit for solving conformance or sweep efficiency problems. The economic elements of this review are very basic, but they will help you to determine a more-accurate understanding of the true economic benefit. -
The authors of this paper describe the characterization of fractures in the Mesozoic sandstones of the Phra Wihan Formation exposed at the southern part of Uttaradit Province in Thailand.
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This paper proposes a multidomain approach to tackle petrophysical and geomechanical aspects of a fracture system governing the carbonate layer of an exploration well in Kuwait to assess producibility and qualification for stimulation.
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This paper proposes a data-driven proxy model to effectively forecast the production of horizontal wells with complex fracture networks in shales.
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SponsoredIn a partnership with the American Institute of Formation Evaluation, TGS is now the only US data vendor offering report-sourced drillstem tests, available through TGS Well Data Analytics.
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This paper describes natural fractures and their effect on hydrocarbon productivity in the Vaca Muerta shale formation.
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The authors of this paper describe a solution using machine-learning techniques to predict sandstone distribution and, to some extent, automate the process of optimizing well placement.
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The seismic and well data investigation tool integrates work flows to provide a consistent analysis of reservoirs.
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In Part 2 of a series of articles, the author focuses on generating a connection between the problem types and various methods of trying to solve these problems.
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Artificial intelligence (AI) tools have been used in geological survey methods for many years. Gaining insight into the scale and trends of this implementation could assist surveyors in making informed decisions about buying or developing new technologies.
