000			03051nmc a2200313 4500
005			20260521161146.0
008			260224s xxu esp
041			_aEspañol
082			_a068.82 553.28 C62 2018 0015648
100	1		_aZambrano, Rafael _9700
100	1		_aParra, Daniel _9833
100	1		_aLamberghini, Lucía _9834
100	1		_aSaldungaray, Pablo J. _9720
100	1		_aMosse, Laurent _9721
111	2		_aCongreso de Exploración y Desarrollo de Hidrocarburos (10mo. : 2018 nov. 5 - 9 : Mendoza) _9573
111	2		_aSimposio de Evaluación de Formaciones (2018 nov. 5 - 9 : Mendoza) _9675
245	0	0	_aDesafíos y soluciones en la evaluación petrofísica de los reservorios tight gas. Caso Lindero Atravesado-Formaciones Lajas y Punta Rosada
270			_a29/06/2022 ; 26/02/2019
300			_a24 p. ; 371-395
520			_aThe evaluation of low porosity tight gas reservoirs presents several well-known challenges, our main goal is to accurately quantify the petrophysical properties to describe them. With a reliable petrophysical model, the next task is to reveal the key petrophysical responses that represent the link between petrophysics and production.The present work describes the main petrophysical challenges faced and a novel workflow used in the Lindero Atravesado field to overcome these defies. The proposed workflow helped to reduce the uncertainties on the computed petrophysical properties and to produce an accurate reservoir volumetric analysis. The workflow involves advanced measurements such as gamma ray spectroscopy, nuclear magnetic resonance (NMR) and dielectric dispersion logs. The good correlation between the petrophysical properties estimated from the novel workflow and the core analysis, demonstrates the benefits of using the advanced log measurements.The NMR log plays an important role in the workflow since it responds mainly to fluids and pore geometry, with an insignificant lithology influence. The final step of the workflow consists of a new methodology called "Factor Analysis" and it is based on the extraction of multi-modal information from the NMR T2 distribution to determine the optimal number of dominant modes (factors) that allow describing the reservoir. Each factor and its corresponding volume is associated to a pore and fluid type. Finally, a classification based on the Poro-Fluid volumes completes the analysis providing a prediction of reservoir production.A detailed description of the challenges faced and the novel workflow is presented with clear examples to illustrate the effectiveness of this approach for the optimization of well completion and field development.
650		0	_aTight gas _9701
650		0	_aEvaluación petrofísica _9835
650		0	_aEspectroscopía de GR _9836
650		0	_aDispersión dieléctrica _9837
650		0	_aResonancia magnética _9772
856			_uhttps://biblioteca.iapg.org.ar/ArchivosAdjuntos/Conexplor2018/SEF/1158.pdf
942			_cCONGTP _2ddc
999			_c128445 _d128445