The Use of Nuclear Magnetic Resonance (NMR) Measurements and Conventional Logs to Predict Permeability for a Complex Carbonate Formation

Permeability is one of the most important property for reservoir characterization, and its prediction has been one of the fundamental challenges specially for a complex formation such as carbonate, due to this complexity, log analysis cannot be accurate enough if it’s not supported by core data, which is critically important for formation evaluation. In this paper, permeability is estimated by making both core and log analysis for five exploration wells of Yammama formation, Nasiriyah oil field. The available well logging recorders were interpreted using Interactive Petrophysics software (IP) which used to determine lithology, and the petrophysical properties. Nuclear Magnetic Resonance (NMR) Measurements is used for laboratory tests, which provide an accurate, porosity and permeability measurements. The results show that the main lithology in the reservoir is limestone, in which average permeability of the potential reservoir units’ values tend to range from 0.064275 in zone YA to 20.74 in zone YB3, and averaged porosity values tend to range from 0.059 in zone YA to 0.155 in zoneYB3. Zone YB3 is found to be the best zone in the Yammama formation according to its good petrophysical properties. The correlation of core-log for permeability and porosity produce an acceptable R^2 equal to 0.618, 0.585 respectively

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Petrophysical properties difference of organic-rich and organic-poor shale reservoir using low-field nuclear magnetic resonance experiment in the Sangzhi block, South China

Interpretation ◽

10.1190/int-2019-0219.1 ◽

2020 ◽

Vol 8 (4) ◽

pp. T895-T905

Author(s):

Gang Zhao ◽

Wenlong Ding ◽

Yaxiong Sun ◽

Siyu Shi ◽

Baocheng Jiao ◽

...

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Shale Gas ◽

Hunan Province ◽

Organic Carbon Content ◽

Petrophysical Properties ◽

Low Field ◽

Porosity And Permeability ◽

Shale Reservoir ◽

Nuclear Magnetic

The petrophysical properties of rocks have an important influence on shale quality. To characterize the difference of petrophysical properties between organic-rich and organic-poor shale reservoirs, we used the low-field nuclear magnetic resonance (NMR) technique and field emission scanning electron microscopy analysis after argon-ion polishing or natural section to measure porosity and permeability from six core samples from well SY6 in the Sangzhi block, Northwest Hunan province. Some information about pore types, pore structure, residual porosity, movable porosity, and permeability based on the T2 spectrums’ difference of organic-rich and organic-poor shale samples were discussed. The shale sample test results show that the main pores size is mesopore, which provide most of shale gas reservoir space. The continuous peaks demonstrated the pores’ connectivity better than the isolated peaks, and shale gas can migrate freely between these connected pores and fractures. The permeability of all samples calculated by the classic Coates model is extremely low, which is not conducive to the migration of shale gas. We evaluated the dominating factors of NMR porosity and permeability and found that the relationships between NMR porosity and permeability and total organic carbon content, quartz minerals, and clay minerals are not clear, which may be a comprehensive influence. The research results have important guiding significance for shale reservoir quality evaluation in this area.

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Mississippian Porosity and Permeability: Core Comparison to Nuclear Magnetic Resonance

10.2118/173592-ms ◽

2015 ◽

Cited By ~ 1

Author(s):

Charles H. Smith ◽

Lynda Ziane

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Porosity And Permeability ◽

Nuclear Magnetic

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Predicting oil saturation of tight conglomerate reservoirs via well logs based on reconstructing nuclear magnetic resonance T2 spectrum under completely watered conditions

Journal of Geophysics and Engineering ◽

10.1093/jge/gxz109 ◽

2019 ◽

Vol 17 (2) ◽

pp. 328-338

Author(s):

Xiaojun Wang ◽

Zhenlin Wang ◽

Cheng Feng ◽

Tao Zhu ◽

Ni Zhang ◽

...

Keyword(s):

Experimental Data ◽

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Quantitative Prediction ◽

Quantitative Relation ◽

Oil Saturation ◽

Comparison Results ◽

Porosity And Permeability ◽

Nmr T2 Spectrum ◽

Nuclear Magnetic

Abstract Due to complex lithology, strong heterogeneity, low porosity and permeability; resistivity logging faces great challenges in oil saturation prediction of tight conglomerate reservoirs. First, 10 typical core samples were selected to measure and analyse the porosity, permeability, nuclear magnetic resonance (NMR) T2 spectrum and mercury injection capillary pressure (MICP) curve. Second, an empirical method was proposed for reconstructing the NMR T2 spectrum under completely watered conditions using MICP curve based on the ‘three-piece’ power function. The parameters of different models were calibrated via experimental data analysis, respectively. The 180 core experimental data from an MICP curve were used as the input database. Porosity and permeability were regarded as the MICP data selection criteria to apply this model in formation evaluation. The comparison results show good application effects. Finally, to reflect oil saturation, the ratio of T2 geometric means of NMR T2 spectra under oil-bearing and completely watered conditions was proposed. Then, the quantitative relation between oil saturation and the proposed ratio was established via experimental data from the sealed cores, which established a quantitative prediction on oil saturation of tight conglomerate reservoirs. This showed a good application effect. The average relative error and the root mean square error (RMSE) of the predicted oil saturation and sealed coring measurement were around 10 and 3%, respectively. As the proposed method is only influenced by the wettability of reservoir and viscosity of oil, it is not only appropriate for the studied area, but also for other water-wet reservoirs containing light oil. It is important for identifying oil layers, calculating oil saturation and improving log interpretation accuracy in tight conglomerate reservoirs.

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